**About the Editors**

#### **Przemysław Barłóg**

Dr. Przemysław Barłóg has been working at the Poznan University of Life Sciences in Poland for 30 years as an academic teacher and scientist. Currently, he works as a professor in the Department of Agricultural Chemistry and Environmental Biogeochemistry. Under his supervision, more than 100 students have achieved a Master of Sciences (Msc) degree and three students have achieved a PhD in the field of soil fertilization, plant nutrition, and environmental protection. Dr. Przemysław Barłóg is the author of more than 100 original, peer-reviewed scientific papers, most of which are indexed in world databases such as Scopus. He is also the author of numerous monographs and popular articles concerning the basis of crop plant nutrition and fertilization, addressed to students and advisory staff in agriculture.

#### **Jim Moir**

My research focus is soil fertility based, investigating nutrient cycling in grazed grasslands, including plant nutrition. My research expertise is in nitrogen (N) and phosphorus (P) cycling and soil pH (acidity) issues in soil/plant/animal systems. My aim is to improve the efficiency and effectiveness of our grassland farming systems, towards the future sustainability of grazed grasslands. In collaboration with colleagues at Qinghai University I am working on a key project examining nutrient flows and sustainability issues in high altitude Chinese and New Zealand grasslands. In China, we work on the Qinghai-Tibetan Plateau, which is under high grazing pressure from farmers and threatened by severe degradation as a result. This is the largest grassland Plateau in the world and shares many common issues with New Zealand high country grasslands. This project aims to increase knowledge of these systems to improve the quality and long-term sustainability of grazed grasslands.

#### **Lukáš Hlisnikovský**

Lukáš Hlisnikovský works as a plant nutrition scientist. His focus is on long-term experiments. In these, he studies how different fertilization methods, sowing practices, and weather affect the yield and quality of the crops grown. His interests also include the study of the effect of fertilization on soil chemistry.

#### **Xinhua He**

Xinhua He is currently Professor at Sichuan Agricultural University, China, Research Professor at UC Davis and Adjunct Professor at University of Western Australia (UWA). After his PhD study at University of Queensland/Australia in 2002, Xinhua has then worked as Postdoctoral Fellow at UC Davis, University of Tokyo, and UWA; Research Scientist at USDA's Forest Service; and Associate Professor at UWA and University of Sydney. Xinhua has been focusing on carbon and nitrogen cycling in plant-soil-microbe systems, soil beneficial microbes in plant/soil health and interplant C/N movement under global environmental change scenarios, by employing routine ecophysiological and microbial approaches, <sup>13</sup>C and <sup>15</sup>N stable isotopes, and high-throughput sequencing, etc.. He has been serving as editorial board/organizing committee members for diverse international peer-reviewed journals/conferences. At present Xinhua has >250 journal papers with 9,400 citations.

## *Editorial* **Improving Fertilizer Use Efficiency—Methods and Strategies for the Future**

**Przemysław Barłóg**

Department of Agricultural Chemistry and Environmental Biogeochemistry, Poznan University of Life Sciences, Wojska Polskiego 71F, 60-625 Poznan, Poland; przemyslaw.barlog@up.poznan.pl; Tel.: +48-618-48-77-93

**Abstract:** This editorial introduces our Special Issue entitled "Improving Fertilizer Use Efficiency— Methods and Strategies for the Future". The fertilizer use efficiency (FUE) is a measure of the potential of an applied fertilizer to increase the productivity and utilization of the nutrients present in the soil/plant system. FUE indices are mainly used to assess the effectiveness of nitrogen (N), phosphorus (P), and potassium (K) fertilization. This is due to the low efficiency of use of NPK fertilizers, their environmental side effects and also, in relation to P, limited natural resources. The FUE is the result of a series of interactions between the plant genotype and the environment, including both abiotic and biotic factors. A full recognition of these factors is the basis for proper fertilization in farming practice, aimed at maximizing the FUE. This Special Issue focuses on some key topics in crop fertilization. Due to specific goals, they can be grouped as follows: removing factors that limit the nutrient uptake of plants; improving and/or maintaining an adequate soil fertility; the precise determination of fertilizer doses and application dates; foliar application; the use of innovative fertilizers; and the adoption of efficient genotypes. The most important nutrient in crop production is N. Hence, most scientific research focuses on improving the nitrogen use efficiency (NUE). Obtaining high NUE values is possible, but only if the plants are well supplied with nitrogen-supporting nutrients. In this Special Issue, particular attention is paid to improving the plant supply with P and K.

**Keywords:** ammonia volatilization; controlled-release fertilizers; crop genotypes; elemental sulfur; magnesium; nitrogen use efficiency indices; phosphorus; potassium; root architecture; sustainability; Soil Fertility Clock

#### **1. Introduction—Why Fertilizer Use Efficiency Should Be Improved**

According to forecasts, 9.7 billion people will be living on Earth by 2050, and about 10.4 billion by 2100 [1]. Right now, the world has the resources to feed a population of 8 billion. It is, therefore, necessary to seek optimal solutions in both the political and economic areas in order to solve the problem of the ever-growing demand for food. The expansion of agricultural areas at the expense of forests or shrubs, or even barren lands, either requires too much investment or is too risky in terms of the environment and the functioning of the global ecosystem [2–4]. Hence, the only rational direction for agricultural development is to maximize yields from the area already covered by agricultural activity [5,6]. There are some factors that are considered crucial in activities towards yield increase: breeding progress, the effective use of mineral fertilizers and crop protection measures, and farmers and their advisers having sufficient knowledge and skills [7]. The consumption of nitrogen fertilizers plays a special role in achieving this objective [8]. Mogollon et al. [9] presented several simulations showing that the global N input in agriculture in 2050 may fluctuate widely, ranging from 87 to 260 Tg N yr−1. One of the main factors differentiating the above range is the nitrogen use efficiency (NUE). Currently, it is assumed that recovery of N from applied fertilizers is at the low level of just 30–50% [10]. As a result, N that is not taken up by plants is dispersed into the environment, reducing the economic profitability of agricultural production and, at the

**Citation:** Barłóg, P. Improving Fertilizer Use Efficiency—Methods and Strategies for the Future. *Plants* **2023**, *12*, 3658. https://doi.org/ 10.3390/plants12203658

Received: 4 October 2023 Revised: 10 October 2023 Accepted: 16 October 2023 Published: 23 October 2023

**Copyright:** © 2023 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

same time, causing a number of adverse changes in the functioning of the biosphere. The most important of these concern such phenomena as greenhouse gas and ammonia emissions, the destruction of the ozone layer, the eutrophication of the environment, or the impoverishment of ecosystems in plant and animal species [11]. An increase in the NUE value can be achieved through the improvement of N fertilization technology, including the use of innovative solutions in the production technology and chemical composition of fertilizers [12]. An important factor shaping the NUE is the presence of appropriate amounts and forms of minerals in the soil, which support the uptake and processing of N into plant crops [7]. This objective can be achieved using P, K, Mg, S, and other fertilizers, separately, or together with N in compound fertilizers. Hence, the term "NUE" can be extended to include the concept of fertilizer use efficiency (FUE). Such a definition allows for a broader approach to the issues related to the effectiveness of the application of all fertilizers and is not limited to only one nutrient. The aim of this Special Issue is to present the latest knowledge and research results regarding the improvement of the FUE/NUE in the cultivation of various plant species.

#### **2. Special Issue Overview—General Topics**

#### *2.1. Factors Effecting Fertilizer Use Efficiency (FUE)*

The first chapter of the Special Issue comprises two papers that focus on factors limiting the uptake and use of nutrients from fertilizers by crops, as well as on the present strategies and prospects for improving fertilizer use efficiency [12]. The term fertilizer use efficiency (FUE) is not new. It has been widely used for decades, but has become widespread thanks to the use of the FUE indices to assess the global productivity of NPK fertilizers. The number of indices used to characterize the FUE is vast, and their choice depends on the purpose of the analysis and/or comparisons [10,13]. The first article in the presented series of publications shows the concepts and principles of calculating a relatively new index, which is the nitrogen gap (NG). The NG calculation is important for the identification of hotspots in N management for a given crop, including the inadequate supply of nutrients other than N and a set of activities needed to improve the level of soil fertility for a given crop [14,15]. The impact of soil factors on the FUE should be considered as several groups of phenomena and processes [12]. The first group refers to factors affecting the nutrient uptake. However, there is a major challenge for a farmer to synchronize the crop plant requirement for nutrients with their supply from both soil and applied fertilizers. Achieving this goal requires extensive knowledge of plant growth dynamics and the critical phases of crop formation. After recognizing the nutritional requirements of plants, another area of activities aimed at improving the FUE is to create optimal conditions for plant root growth and eliminate all factors limiting the inflow of nutrients to the root surfaces. The most important soil factors shaping the uptake of nutrients and the FUE are the soil texture, water content, soil compaction, temperature, soil reaction, salinity, soil organic matter, and nutrient shortage [12]. Among them, the soil compaction and pH are relatively easy to correct in agricultural practices. The presented literature shows that FUE values can be shaped by building appropriate root architecture (RSA) in crops. This is possible by applying proper fertilization with N and K [16]. Another way to improve the FUE is the use of new and innovative fertilizers [12].

The second overview article presents the concept of effective fertilization, defined as the Soil Fertility Clock (SFC) [7]. At the core of this concept, there are three basic facts: (i) a crop plant in a well-defined geographic area, provided with stable environmental and nutritional conditions, can reach maximum yield (Ymax); (ii) the key production factor is N, present in the soil or/and supplied to the plant as fertilizer (organic and mineral, Nf); (iii) all other nutrients, called nitrogen-supporting nutrients (N-SNs), affect the Ymax, in relation to their relative deficiency in available form in the plant rooting zone. The classic concepts of N-SNs do not take into account that crop plants differ in their sensitivity to the supply of N-SNs in two crucial aspects: during the growing season and in the course of crop rotation. The Soil Fertility Clock (SFC) is an approach based on three assumptions: (i) the

critical soil fertility is the value or range of soil nutrient content that is sufficient to provide an appropriate amount to the plant most sensitive to its supply in a given crop rotation; (ii) the non-sensitive plants in the given crop rotation create the necessary timeframe for the recovery of its original critical content; and (iii) the content of a specific nutrient cannot be a limiting factor in N uptake and utilization for any crop grown. The SFC concept is supported primarily by the yield-promoting role of P and K [7]. A deficiency of both nutrients in the soil during the critical stages of yield formation results in a decreased Nf efficiency, and consequently, a lower yield. Thus, the main goal of P and K application to the soil is to restore their content in the topsoil to the level required by the most sensitive crop in any given crop rotation.

#### *2.2. Improving FUE by Optimizing N Uptake and Rate*

One of the most important activities aimed at improving the FUE is the correct selection of the fertilizer dose for specific soil and climatic conditions, the applied agrotechnics, and the plants requirements in crop rotation. This can be achieved using analytical tools such as soil testing, plant tissue analysis, nutrient uptake dynamics, fertilizer rate response modeling, or digital and information technologies [7]. The standard methodology for determining the need for N fertilizers is based on data regarding the mineral nitrogen (Nmin) content in the soil [17]. Therefore, it is extremely important to identify and classify the factors affecting the mineralization processes of organic nitrogen and the Nmin content in the soil. The knowledge gained in this area can be translated into conscious control of Nmin, thus shaping the yield level. The first article included in the subsection discusses the influence of various tillage practices on the content of different forms of N in fluvo-aquic soil from Huang-Huai-Hai Plain in China [18]. The experiment evaluated the effect of five treatments where rotary tillage (RT), deep tillage (DT), and shallow rotary tillage (SRT) were used. The test plant was wheat. The results showed that the rotation tillage with deep tillage increased the total N and the content of the mineral nitrogen forms compared with RT-RT-RT. They especially improved the NO3–N and NH4–N content in 0–40 cm, with the highest value under DT-SRT-RT. However, the effect of deep tillage on dissolved organic N in deeper layers significantly declined with time. The highest wheat yield was under DT-SRT-RT in 2018 and 2019, with 6346 and 6557 kg ha<sup>−</sup>1, respectively. The N partial productivity demonstrated a similar trend with the wheat yield, with higher values of 28.98 and 29.94 kg−1, respectively. The authors also obtained the lowest apparent nitrogen loss values in the DT-SRT-RT treatment. It was suggested as the efficiency tillage practice to improve the NUE and the crop yield [18].

In field conditions, plants compete with each other for water and nutrients. Therefore, it is important to recognize the appropriate sowing density (SR) to minimize these effects and, at the same time, consciously combine yield components to obtain the maximum N productivity. The problem of the NUE's dependence on the sowing density in winter wheat cultivation in Jiangsu province (China) was analyzed by Mahmood et al. [19]. The authors put forward the hypothesis that there is an optimum seed rate to compensate the negative effects of decreasing N for balanced high yields and an improved NUE in wheat. The results revealed that the net photosynthetic rate, the stomatal conductance, the chlorophyll content, and the activities of metabolic enzymes significantly increased with increasing N levels and a decreasing seeding rate. The plant tillers, grain yield, dry matter before anthesis and N translocation, N agronomic efficiency (NAE), N recovery efficiency (NRE), and N uptake efficiency (NUPE) were highest in a combined treatment of N235 and SR180. However, N levels beyond 235 kg ha−<sup>1</sup> significantly decreased the NAE, NRE, and NUPE. The authors concluded that 1 kg N ha−<sup>1</sup> might be replaced by an increase of approximately 0.6 kg ha−<sup>1</sup> SR. In addition, by using a combination of N and SR (N235 + SR180), it is possible to obtain the maximum yield of winter wheat and improve the NUE parameters [19].

The objective of another paper was to determine the best pruning level and N dose based on the agro-physiological characteristics of kaffir lime under mild shading [20]. The research was based on the need to fill the information gap regarding growth and yield under mild-shading conditions and specific N recommendations for leaf-orientated production of kaffir lime. The experiment was carried out at the Pasir Kuda experimental field of IPB University, Bogor, Indonesia. The plant materials were nine-month-old seedlings obtained using a grafting technique that combined kaffir lime (*Citrus hystrix* DC) scions onto rangpur lime (*C. limonia* Osbeck) rootstock. Four levels of N dosage were tested. The optimum N rate was determined based on a regression curve. A N-sufficient condition was achieved as the effect of 20 and 40 g N plant−<sup>1</sup> application, producing a great growth and yield performance due to a high carbon assimilation rate. However, that does not automatically mean that a dose of 40 g N plant−<sup>1</sup> is the best fertilizer recommendation, as 20 g N plant−<sup>1</sup> is more efficient, with a relatively similar effect for increasing kaffir lime leaf production. With respect to pruning, a higher yield was obtained via leaving 30 cm of main stem above the ground, rather than shorter plants with a 10 cm main stem [20].

#### *2.3. Balanced Fertilization as Key to Efficient N Use*

Efficient N uptake, transport, and conversion into a crop depends on a good supply of plants with the remaining macro- and micronutrients [7]. The first publication dedicated to balanced fertilization described their results regarding fertilization in a rice–rice cropping system [21]. As rice is a nutrient-exhausting crop, its properly balanced fertilization is important to maintain a high productivity. The two-year experiment in a sub-tropical climate under the red and lateritic belt of the western part of West Bengal, India, was set up in a randomized complete block design with twelve treatments and three replications, with different rates of N:P:K:Zn:S application in both of the growing seasons, namely, Kharif and Boro. The results clearly indicated that imbalanced or insufficient nutrient application affects crop nutrient removal, thus affecting the growth and development of the plant. In addition, inappropriate nutrient supply over a long period reduces soil fertility, especially when a nutrient-exhausting cropping system, such as a rice–rice cropping system, is chosen. In this study, the recommended dose of nutrients was 80:40:40:25:20 and 120:60:60:25:20 kg ha−<sup>1</sup> of N:P2O5:K2O:Zn:S in the Kharif and Boro season, respectively. To summarize, balanced nutrient management in cropping systems is a cost-effective and environmentally friendly approach to targeting agricultural sustainability [21].

In another paper, the authors focused on interactions between differentiated fertilization management and environmental factors and their influence on potato yields and selected soil parameters [22]. The fertilization treatments represent different management practices and include: (1) an unfertilized control, (2) the application of cow manure (FYM), (3, 4) a combination of manure and two different mineral nitrogen rates (FYM + N1, FYM + N2), and (5, 6, and 7) a combination of FYM and mineral NPK fertilizers (FYM + N1PK, FYM + N2PK, FYM + N3PK), which represents the combination of manure and all three major mineral fertilizers (against FYM + N treatments). The experiment was carried out on three sites (different soils) and during four growing seasons. Both the growing season and fertilization significantly affected potato yields at all locations. The authors proved that FYM application was always associated with higher yields. However, FYM application did not provide enough nutrients (N) to fulfil the yield potential of potatoes. Therefore, the addition of mineral N significantly increased potato yields, especially at less-fertile sites. The FYM + NPK combinations significantly improved yields compared to the FYM + N treatments. Thus, the obtained results clearly confirm the important role of P and K fertilization in increasing N productivity via both natural and mineral fertilizers.

The role of balanced fertilization in yield formation was also analyzed via two longterm experiments. The first was set up in 1954 in Prague and analyzed the effect of weather and seven fertilization treatments (mineral and manure treatments) on winter wheat grain yield and stability [23]. Winter wheat is one of the most important crops in the world. Hence, analysis of the response of wheat varieties to perennial fertilization is particularly important for food security. The authors analyzed 23 growing seasons. They showed that the grain yield was positively associated with the April precipitation, the mean daily

temperature in October, and the daily maximum temperature in February. The yields were most stable between years when two fertilizer treatments were used that supplied a mean of 47 kg N ha−<sup>1</sup> yr−1, 54 kg P ha−<sup>1</sup> yr−1, and 108 kg K ha−<sup>1</sup> yr−1. The rate of N at which the grain yield was optimized was determined according to the linear-plateau (LP) and quadratic response models as 44 kg N ha−<sup>1</sup> yr−<sup>1</sup> for the long-strawed varieties and 87 kg N ha−<sup>1</sup> yr−<sup>1</sup> for the short-strawed varieties.

Another article included in this subsection presents the impact of well-balanced fertilization on the effective N fertilization of corn [14]. The objective of the study was the influence of the band application of a di-ammonium phosphate and ammonium sulfate mixture (NPS) on the possibility of lowering the total N dose. In order to assess the impact of fertilizing agents, seven nutrient efficiency indices and eight dry matter and N management indices were used. The total N uptake and NUE indices increased after band application. In addition, a trend of improved N remobilization efficiency and the N contribution of remobilized N to grain as a result of the band application of NP(S) was observed. The most effective use of N by corn was ensured via the use of an NPS mixture during the sowing of corn seeds (band application). From the point of view of the NUE indices, the optimal dose of N was 60 kg ha<sup>−</sup>1. With broadcast fertilization and/or a further increase in the N dose, without the simultaneous use of P and S, the values of the NUE indices deteriorated, especially in the year with the highest content of Nmin in the soil. Thus, a positive effect of the interaction of N and P(S) was confirmed in the conditions of soil rich in plant-available P.

Another publication concentrated on the improvement of N use by potato plants through the additional application of elemental sulfur, S0 [24]. Potatoes require a good supply of S0 for effective growth. Earlier studies showed that, in conditions of good S supply, a simultaneous increase in the NUE was noticed [25]. In this study, two main goals were set: (i) quantify the seasonal growth trends in the biomass of potato organs competing with tubers and (ii) evaluate the impact of S<sup>0</sup> on the in-season relationships within the biomass of potato organs. The research factors were two doses of N (60 and 120 kg ha−1), elemental sulfur fertilization (control and 50 kg ha−1), and different plant sampling dates (10-day intervals). It was found that the potato growth pattern coded at the onset of tuberization was a decisive factor for the dry matter partitioning between the potato organs during the subsequent tuber growth phase. The tuber yield-forming effect of added sulfur results from a balanced growth in stems during the ascending and the descending phase. At harvest, the average biomass of potato tubers on the main plot fertilized only with N was lower by 21% than that on the one receiving sulfur at the rate of 50 kg ha<sup>−</sup>1.

In a methodological publication by Hu et al. [26], a hypothesis was formulated that the optimal fertilizer doses can be determined via yield–fertilizer rate response modeling. For this purpose, the authors analyzed dozens of experiments with peanut plants located on the North China Plain. Two fertilization treatments, namely, that used by farmers (FP) and optimized fertilization (OPT), allowed for the regional mean optimal rate (ROMR) method to be applied. The authors determined the optimum fertilizer rate using the 2o regression curve. In order to assess the fertilization effectiveness, the authors used a number of indices: the RIEN (N reciprocal internal efficiency), PFPN (N fertilizer partial factor productivity), NUpE (N uptake efficiency), and NUtE (N utilization efficiency). The results of the experiments supported the hypothesis that the FP treatment with the OPT treatment, based on the RMOR method, promoted N use efficiency (PFPN and NUPE) and decreased the nutrient inputs from chemical fertilizer, especially N and P fertilizers, without the loss of peanut yield and NPK uptake. The research clearly shows that the RMOR method can be adopted in many countries and regions with widespread smallholder farms.

#### *2.4. FUE and Foliar Fertilization*

One way to provide plants with nutrients during the vegetative phase is foliar fertilization. This treatment allows for interventional (when deficiency symptoms appear) or

preventive fertilization, taking into account the growth phases in which plants show the greatest sensitivity to nutrient deficiency. The method bypasses the stage of the transformation of nutrients in the soil, and thus reduces the potential regression of components and/or dispersion into the environment. In addition, through the use of small doses, a high fertilizer productivity is achieved [27]. There are insufficient data in the literature on foliar fertilization with phosphorus and, in particular, on plants of the *Fabaceae* family. The results published in this Special Issue broaden our knowledge on foliar P application and its influence on selected growth parameters, the production, and the quality of peas [28]. The effect of foliar P application on the photosynthetic parameters, seed yields, and quality of four pea genotypes (two normal-phytate cultivars and two low-phytate) was investigated in a pot experiment in controlled conditions. The effect of the pea lines on the foliar P fertilization was different. In the case of the normal-phytate cultivars, the seed production was enhanced via gradual doses of the P-fertilizer, except for the highest dose of phosphorus (P3). Low-phytate cultivars showed a positive reaction to the P3 dose. The authors concluded that foliar P application could be an effective way to enhance the pea growth in the P-deficient condition, with a direct effect on the seed yield and quality.

The research objective of another publication was to verify the effect of the foliar application of waste elemental sulfur (S0) from biogas production in combination with conventional liquid UAN fertilizers applied in different ratios [29]. The reaction in maize was studied via a pot experiment. The following fertilization treatments were studied: control, UAN, UANS1 (N:S ratio, 2:1), UANS2 (1:1), and UANS3 (1:2). It showed that the application of UAN increased the N content in the plant and significantly affected the chlorophyll content (the N-tester value). The application of UANS had a lower impact on the N content and uptake than the application of UAN; however, it had a significant effect on the quantum yield of PSII. The authors conclude that the foliar application of UAN fertilizer in combination with S0 in a 1:1 ratio seems to be a sensible way to optimize the nutritional status of maize, both in terms of the economics of biogas purification, where the waste sulfur is reused as a fertilizer, and for environmental reasons.

Apart from P and S, the most important component for N uptake and metabolism in plants is Mg. In agricultural practice, farmers use two basic Mg fertilization systems: (i) the in-soil application of Mg fertilizer using lime for acidic soils and magnesium sulfate for soils with an optimum pH; and (ii) foliar fertilization. In studies carried out by Potarzycki et al. [30], a hypothesis was formulated that winter wheat fertilized with Mg increases nitrogen fertilizer (Nf) efficiency, regardless of the method of application. In order to achieve this, the authors set a two-factorial experiment with three doses of Kieserite (0, 25, and 50 kg ha−<sup>1</sup> of Mg) and two stages of foliar fertilization at the rate 2.4 kg Mg ha−<sup>1</sup> (control; I; II; I + II). A full dose of nitrogen was 190 kg ha<sup>−</sup>1. Twelve different parameters and indices (the total N accumulation, harvest index, partial factor productivity, nitrogen physiological efficiency, and others) were used to assess the impact of factors on the nitrogen efficiency (NUE) in wheat cultivation. The same set of indicators was used to assess the effectiveness of Mg fertilization. According to the study, the wheat yield increased as a result of the use of Mg. The method of application was of secondary importance. The yield gain, as a result of foliar fertilization with Mg fertilization, ranged from 0.6 to 0.9 t ha<sup>−</sup>1, while, in the soil, its application resulted in a yield gain in the range of 0.4–0.7 t ha−1. The main action of Mg, regardless of its application method, was the improvement of the index values characteristic for the NUE. The yield-forming effect of the applied Mg on the winter wheat was revealed via the increased N transfer to the grain.

In another publication included in this Special Issue, the authors investigated the effect of three foliar fertilizers (F, B, and C) and the mixture of the three (F + B + C) on the flower quality and the amount of new daughter corms produced by the five Gladiolus varieties in the climate conditions of the Carpathian Basin [31]. The *Gladiolus* genus is a perennial, monocotyledonous, geophyte, semi-rustic ornamental plant and includes about 260 species [32]. These plants are valued for the variety of shapes and colors of their flowers. However, they require appropriate growing conditions and the correct selection of varieties, in particular for degraded and saline soils. In the study, the authors used multicomponent foliar fertilizers that differed not only in the set of elements and their content but also in the presence of phytohormones. It should also be mentioned that N was included in each fertilizer. During the season, a total of four sprayings were carried out during plant development phases. The results of this experiment show that proper foliar fertilization can support and influence the growth, vase durability, and daughter corm production of some Gladiolus varieties. The highest yield of daughter corm production was observed with the mixture of the three foliar fertilizations (F + B + C). The result confirms that N productivity is stimulated not only via the dose of N but also via the appropriate balance of all nutrients [31].

#### *2.5. FUE and Innovations on the Fertilizer Market*

For many years, mineral fertilizers have been used to (i) ensure a good supply of nitrogen to plants, especially in critical phases; (ii) reduce the number of applications; (iii) reduce the nitrate content in plants; and (iv) limit nitrogen loss and reduce its negative impact on the environment [12]. In general, these fertilizers can be divided into two groups: slow-release fertilizers (SRFs) and controlled-release fertilizers (CRFs). With regards to N fertilizers from the CRF group, the effect of delaying N release is achieved through covering the granules with a different type of protective layer. Škarpa et al. [33] assessed the possibility of improving the efficiency of Nf and reducing its negative impact on the environment (N leaching) through the use of two CRF fertilizers: calcium ammonium nitrate (CAN) fertilizer coated with modified conventional polyurethane and CAN coated with vegetable oils. The influence of the CRF fertilizer was compared to that of the classic CAN. Three types of treatment were tested for both coated fertilizers: divided application (CAN, coated CAN), a single application of coated CAN, and a single application of CAN with coated CAN (1:2). The test plant was winter oilseed rape. The obtained results confirm that the application of coated CAN fertilizers increases the yield to a large extent, improves the efficiency of N fertilization, and reduces N losses, compared to the use of conventional CAN. In this study, a suitable method appears to be the application of a mixture of conventional CAN and coated CAN in a ratio of 1:2 during spring fertilization, ensuring a sufficient amount of rapidly releasing N during the regeneration of rapeseed and its slower release during further developmental stages. In terms of fertilizer production, oil-based polymer coatings on CAN fertilizer can be considered as an adequate replacement for partially modified conventional polyurethane [33].

The second publication on CRF fertilizers in this collection studied the possibility of enhancing the NUE in coffee cultivation (*Coffea arabica* L.). Freitas et al. [34] formulated a hypothesis that enhanced-efficiency N fertilizers and other fertilizers, such as ammonium nitrate and sulfate and prilled urea diluted in water, are options more suitable than conventional urea for reducing NH3-N losses in coffee production systems. In order to validate the hypothesis, field experiments were carried out, in which the authors tested the following fertilization treatments: prilled urea, prilled urea dissolved in water, ammonium sulfate (AS), ammonium nitrate (AN), urea + Cu + B, urea + adhesive + CaCO3, and urea + NBPT (all with three split applications), as well as blended N fertilizer, urea + elastic resin, urea-formaldehyde, and urea + polyurethane (all applied only once). The experiment with fertilizer treatments was conducted in coffee plantations in field conditions for two crop seasons in the Minas Gerais region, in Brazil. The treatments used in this study were applied at the 300 kg N ha−<sup>1</sup> dose per year. The authors proved a significant influence of various fertilization combinations on urea losses. Except for urea + adhesive + CaCO3 (27.9% of NH3-N losses), all N-fertilizer technologies reduced NH3-N losses compared to prilled urea. The lowest losses were observed for AS (0.6%) and AN (0.5%). The authors point out, however, that when choosing the right fertilization strategy (choice of treatment), the costs of the fertilizer application must be considered.

The problem of reducing losses of NH3-N from fertilizers was also studied by Cassim et al. [35]. The authors assessed different nitrogen (N) fertilizer technologies in corn production systems through the characterization of N sources, NH3-N volatilization losses, and their effects on the nutrient concentration and yield of corn grown in clayey and sandy soils in south Brazil. The following treatments were tested: control, three conventional N sources (urea, ammonium sulfate, and ammonium nitrate + calcium sulfate), and three efficiency-enhanced fertilizers (urea treated with NBPT + Duromide, urea formaldehyde, and polymer-coated urea + urea treated with NBPT and nitrification inhibitor, NI). The article features the physical properties of fertilizers obtained using scanning electron microscopy and X-ray diffraction. In general, the effect of N fertilizer technologies on N losses via the volatilization of NH3-N was ordered as follows: urea > URP + Ur-NBPT + IN > Ur-NBPT + Duromide > Ur-formaldehyde > ammonium nitrate + calcium sulfate > ammonium sulfate. The studies confirmed that ammonium sulfate and ammonium nitrate have the least impact on NH3-N losses (84 and 80% in relation to urea). Additionally, both fertilizers increased the corn grain yield. The yield increase in the clayey soil did not occur solely due to the reduction in losses via NH3-N volatilization. Other factors, such as S and B supplementation and N release at a controlled rate to synchronize with the crop demand, also influenced the increase in corn yield. The authors also presented interesting data regarding the effect of fertilizer treatments on the macro-i micronutrient content and the chlorophyll concentration (SPAD) at the R1 phenological stage (silking). The results suggest that the use of nitrification inhibitors in soil, which leads to an increased concentration of NH4 +, primarily reduces the uptake of Ca2+, and then Mg2+, to a lesser extent.

Biochars constitute a relatively new fertilizer on the market. In general, biochars are solid materials, rich in carbon, obtained from the thermochemical decomposition of organic biomasses. They may be treated as mineral fertilizers or as a component for the production of CRF fertilizers [12]. The in-soil application of biochars has a positive impact on carbon sequestration in soil and on reducing greenhouse gas emissions [36]. In addition, biochar application improves soil fertility and crop productivity. However, the literature does not provide sufficient data on the effect of biochars on the physiology of tomato yields. This gap is filled by the publication by Liu et al. [37]. The authors assumed that the improved agro-chemical properties of the soil using biochar and vermicompost had a positive effect on plant growth, selected physiological parameters, and the tomato yield. In order to verify this hypothesis, the authors set up an experiment, which scrutinized the effect of biochar (CK0%; BA3, 3%; BA5, 5%; by mass of soil) and vermicompost (VA3, 3%; VA5, 5%) on photosynthesis, chlorophyll fluorescence, and tomato yield under greenhouse condition. A number of parameters specific to photosynthesis and chlorophyll fluorescence in tomato plants were analysed. The optimal parameter values were obtained in the treatment with the highest rate of vermicompost (VA5). The treatments with BA registered lower values, but these were higher, however, than those with CK. In summary, the authors highlight that for one season of tomato production, the application of 3% vermicompost is considered economical with regard to improving photosynthesis, enhancing the WUE, and increasing the tomato yield.

#### *2.6. Phosphor and Potassium Use Efficiency*

Besides N, phosphorus is the second most important nutrient in agriculture. The need to improve the use of P from fertilizers by crops stems from two basic factors: (i) the limited resources of raw materials economically viable for exploitation; (ii) the adverse effects of the component's dispersion into the environment [38]. Opportunities to improve the use of P from fertilizers can be explored in various ways. It is important to create not only the optimal conditions for the mobility of H2PO4 − ions (e.g., the soil pH) but also the right choice of doses and type of fertilizer. As the research of Santos et al. indicates [39], in order to improve the efficiency of P use, it is crucial to select the right variety to suit the environment/location. The authors investigated the additive and non-additive effects of commercially relevant traits for the popcorn crop (grain yield—GY, popping expansion—PE, and expanded popcorn volume per hectare—PV) in different conditions

of phosphorus (P) availability in two locations in Rio de Janeiro State, Brazil. Six S7 lines previously selected (three efficient and responsive; and three inefficient and non-responsive for P use) were used as testers in crosses with 15 progenies from the fifth cycle of intrapopulation recurrent selection of UENF-14. The 90-hybrid analysis allowed the authors to determine the combination with the highest impact of dominance genes on performance and responsiveness in the use of phosphorus for the GY, PE, and PV traits.

Chlorine is an essential micronutrient for plants. Its content in soils used for agriculture is usually at a much higher level than the nutritional needs of plants. One of the reasons for this condition is the widespread use of potassium in the form of chloride salt (KCl). Excessive Cl content in the soil can reduce the yield and quality of many crops and thus reduce the efficiency of K from fertilizers. The species sensitive to excess chlorine in the soil include coffee plants. High concentrations of Cl are related to an increase in plant water, which favors an undesirable fermentation of coffee fruits [40]. A way to bypass the problem would be to use K2SO4. However, this fertilizer increases the cost of fertilization. In the article, the authors proposed a partial replacement of KCl with K2SO4 [40]. To achieve this, the authors investigated the effect of blends of KCl and K2SO4 fertilizers at different proportions and their influence on the yield, nutritional state, and chemical composition and quality of the coffee beverage. The research clearly shows that the K content in the leaves was not influenced by the application of blends of K fertilizer while the Cl content increased linearly with the KCl applied. Fertilization with KCl reduces the cup quality and the activity of the polyphenol oxidase, probably due to the ion Cl. Taking into account the yield of coffee plants, the optimal ratio of KCl and K2SO4 was 1:3. However, the highest score in the cup quality test was observed with 100% K2SO4.

#### **3. Conclusions**

Improving the use of nutrients from fertilizers (the FUE) is one of the most important goals of modern agriculture in the context of the increasing demand for food and the growing pressure on the environment. This Special Issue presents a number of possibilities and strategies to improve the FUE. According to the presented publications, most of the research focuses on the possibility of improving the use of N by plants through balanced fertilization. Only in a state of equilibrium between the supplies of N and other nutrients to the plant during the growing season is it possible to effectively exploit the yield potential of a cultivated plant. The balanced fertilization of plants is, therefore, the key to sustainable agricultural production. Balanced fertilization should be supported by other activities aimed at improving the FUE, such as shaping the optimal conditions for nutrient uptake, including the effective use of P and K from fertilizers, foliar fertilization, or the application of innovative fertilizers with a controlled release rate of nutrients and/or nitrification inhibitors. At the same time, the development of new technologies and fertilization strategies should be accompanied by progress in plant breeding that better utilizes natural and anthropogenic sources of nutrients.

**Conflicts of Interest:** The author declares that there is no conflict of interest.

#### **References**


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**Witold Grzebisz \*, Jean Diatta, Przemysław Barłóg , Maria Biber, Jarosław Potarzycki, Remigiusz Łukowiak, Katarzyna Przygocka-Cyna and Witold Szczepaniak**

> Department of Agricultural Chemistry and Environmental Biogeochemistry, Poznan University of Life Sciences, Wojska Polskiego 28, 60-637 Poznan, Poland

**\*** Correspondence: witold.grzebisz@up.poznan.pl; Tel.: +48-618-77-88

**Abstract:** The Soil Fertility Clock (SFC) concept is based on the assumption that the critical content (range) of essential nutrients in the soil is adapted to the requirements of the most sensitive plant in the cropping sequence (CS). This provides a key way to effectively control the productivity of fertilizer nitrogen (Nf). The production goals of a farm are set for the maximum crop yield, which is defined by the environmental conditions of the production process. This target can be achieved, provided that the efficiency of Nf approaches 1.0. Nitrogen (in fact, nitrate) is the determining yield-forming factor, but only when it is balanced with the supply of other nutrients (nitrogen-supporting nutrients; N-SNs). The condition for achieving this level of Nf efficiency is the effectiveness of other production factors, including N-SNs, which should be set at ≤1.0. A key source of N-SNs for a plant is the soil zone occupied by the roots. N-SNs should be applied in order to restore their content in the topsoil to the level required by the most sensitive crop in a given CS. Other plants in the CS provide the timeframe for active controlling the distance of the N-SNs from their critical range.

**Keywords:** nitrogen; nitrate-nitrogen; nitrogen use efficiency; nitrogen-supporting nutrients; phosphorus; potassium; maximum attainable yield; soil fertility management

#### **1. Introduction—The Battle for Yield**

The required increase in total food production of around 70% in 2050, compared to 2010, will largely depend on increases in the yields of crop plants, which serve as staple food for humans [1,2]. At present, meeting the demand for food in the next 28 years, in connection with the required reduction in greenhouse gas emissions, poses a major challenge for global organizations (e.g., the United Nations), the Food and Agriculture Organization (FAO), and national governments [3,4]. Russia's war on Ukraine has clearly highlighted the importance of net food producers, such as Ukraine, in stabilizing the global food market. In the 2020/21 season, this country exported 69.8 million tons of all cereals, accounting for 11.8% of the global export. Ukraine's share in global exports of sunflower seeds and oil exceeded 50% (52%). The war collapsed exports from Ukraine, not only of cereals and sunflower products, but also soybeans and rapeseed [5,6]. Strubenhoff [6] has indicated four groups of activities that can be urgently taken by world leaders to save the world from hunger. Concerning the national level, he pointed to the need to change the food policies of the EU and the USA. In the case of the USA, the author suggested reducing the production of biofuels. In the case of the EU, the author indicated the need to move away from policies on reducing the use of mineral fertilizers. The general conclusion formulated by Strubenhoff [6] was as follows: "For the time being, we need more production, not less. Climate objectives are good to save the planet, but we also need to feed the people on the planet*"*. This should be seen as a motto for political and environmental players who truly understand the functioning of Planet Earth in a holistic, not reductionist sense.

The increase in food production by 2050 will in fact be the result of two main drivers, including the increases in arable land area and yields of main staple crops. The first, the

**Citation:** Grzebisz, W.; Diatta, J.; Barłóg, P.; Biber, M.; Potarzycki, J.; Łukowiak, R.; Przygocka-Cyna, K.; Szczepaniak, W. Soil Fertility Clock—Crop Rotation as a Paradigm in Nitrogen Fertilizer Productivity Control. *Plants* **2022**, *11*, 2841. https://doi.org/10.3390/ plants11212841

Academic Editor: Dimitris L. Bouranis

Received: 29 September 2022 Accepted: 21 October 2022 Published: 25 October 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

main factor in covering the food gap by 2050—is in fact a key constraint, as evidenced by the wide discourse pursued by decision makers in the area of food policy. This goal, in fact, is limited by a lack of fertile soils. The potential resources for expanding arable land area are predominantly in the tropics. However, these soils, despite high natural fertility, require large inputs of the means of production [7,8]. Moreover, the destruction of the rain forest is expected to completely disrupt the Earth's climate [9]. Thus, in order to cover the food gap by 2050, the main challenge facing the world is to increase the yields of crop plants in "old agricultural areas" [10]. The share of the second—but dominant—factor in covering the food gap by 2050 (crop yields), has been estimated at over 80% [11,12]. There are four main factors that are considered crucial in actions oriented toward yield increases. The first is breeding progress. Meeting the 2050 target requires an annual increase in the yield of major crops such as wheat, maize, rice, and soybean at the level of 2.4% annually. This target, as reported by Ray et al. [13], will not easily be met, as the current yield increases of these crops are much below this target, reaching in relative terms only 67% for wheat, 42% for maize, 38% for rice, and 55% for soybean. The second factor is inherent in the effective use of mineral fertilizers and other crop protection measures. The actions taken by farmers should, however, be in line with the main assumptions of the concept known as Intensification of Sustainable Agriculture, which indicates the effective use of production means, including fertilizers [14]. The term "battle for yield," as proposed in the title of this chapter, in the current geopolitical context refers precisely to the productivity of the basic unit of plant production (i.e., a single field) which, in fact, defines the homogenous fertility unit of the field [15].

The third factor—and, indeed, a dominant factor in the food production sector—is the effective use of fertilizer nitrogen (Nf). The Nf consumption, as forecast for 2050, is 76% higher than in 2000 (181 vs. 103 mln t y<sup>−</sup>1) [4]. In another study, the increase in the demand for Nf in 2050, compared to 2005, will be in the range of 43–73% [16]. The crucial problem with Nf use by farmers—both for production and, consequently, for the environment—is its low efficiency (recovery). Limiting the effectiveness of Nf to the right N dose, fertilizer approach, and even the timing of its application is a dramatic simplification of a complex problem [17,18]. A reduction in Nf consumption, in light of the drastic increase in N fertilizer prices in 2022, seems more realistic at present [19]. However, the sudden drop in Nf consumption, as observed in 2022 in Europe, could disrupt the global food production chain. The maintenance of the level of Nf consumption is crucial for food production in the old agricultural areas in the world [20]; for example, a simulation regarding reduced Nf consumption in the U.S. for maize and rice indicates a possible decrease in yields of 41% and 27%, respectively [21]. These theoretical considerations from 10 years ago should be considered, in the face of the current fertilizer crisis [6,19].

The fourth factor, which is decisive for the efficient use of production measures in agriculture, is the knowledge and skills of the farmers and their advisers, which are necessary to exploit the yield potential of the currently grown varieties. The real challenge for the farmer in the effective use of Nf is the correct diagnosis of the plant demand for N in the most critical phase(s) of the yield formation. At this particular stage of crop plant growth, a synchronization between the plant's requirements for N with its supply from soil (soil N resources plus controlled Nf application) is crucial for the formation of yield components. The farmer must know and recognize both the phases in which the plant builds up the yield components and the phases in which they are reduced. The importance of this issue can be presented through the examples of three crops. The first example concerns cereals, which deliver about 60% of carbohydrates and 50% of proteins to the world food market [22]. The key yield component determining the grain yield is the number of grains per unit area (grain density; GD). The most critical period of GD formation extends from the heading phase through flowering to the early milk (BBCH 71) [23,24]. Therefore, it can be called "the critical cereals' window". The second primary component of the yield is the grain weight (1000 grain weight; TGW), which is established during the grain filling period (GFP). This period extends from the early milk stage (BBCH 72) to plant maturity

(BBCH 90) [25]. Its impact on grain yield is much lower than that of GD [26]. For the second example, maize is a crop producing the greatest amount of food for humans or fodder for livestock [27]. The critical period of the primary yield's component formation is the stage of fifth leaf, in which the cob initials are formed. The key nutrient responsible for this process is the supply of N [28,29]. The third example is potatoes, the importance of which as food for humans has been growing rapidly [30]. The critical period for tuber yield establishment is tuberization [31]. The tuber yield depends on the number and weight of young tubers. These processes are driven by the supply of N, but also require a good supply of potassium (K) and phosphorus (P), at least [32,33]. These three examples allow us to conclude that the farmer's knowledge about the functions of N in plants is the absolute basis for determining an effective technological solution for the cultivated crops.

The basic questions to be asked here are as follows:


The third question is essentially sets the goal for this conceptual article.

#### **2. A New Paradigm of Nitrogen Use Efficiency Control—The Basis of the Concept**

There are five general assumptions to consider before any discussion or forecast of crop production outcomes (i.e., the yields) by scientists, farmers' advisors, and food policy makers. First, the amount of solar energy reaching any part of the Earth's land surface is determined by its geographical location [34]. In agriculture, the basic unit of analysis is a single field or its homogenous production part, which is directly managed by the farmer [15,35]. Second, the accumulation of dry matter by a plant during its life cycle, its growth rate, dry matter partitioning between plant organs, and subsequent remobilization depend on the water and N supply. Third, the amount of available N in the plant rooting zone during the growing season is critical for the formation of yield components and, consequently, for the yield. Fourth, the uptake and use of N by the plant depends on the availability of other essential nutrients present in the plant's rooting zone. Fifth, the capacity of the soil and its potential to provide these nutrients to plants is limited. Their content in the plant natural growth milieu (that is, soil) is not infinite and, therefore, needs to be both controlled and supplemented by the farmer.

The effects of climatic and soil factors (environmental conditions) on crop growth and yield are manifested in terms of the maximum attainable yield (Yattmax), which can be reached in well-defined geographic locations [36,37]. It is necessary to take into account that the use and impact of non-nutritional production factors on the grown crop is the result of a farmer's decision and/or legal limitations. Thus, on a specific field on a farm, the main issue for the farmer is to consider the effective management of N, which, in fact, depends in the current state of soil fertility. Sustainable management of N in the field should, therefore, be considered as a balance between necessary and sufficient conditions:


In fact, the necessary condition concerns the control of efficiency, which is the productivity of available N present in the soil zone occupied by plant roots during the growing season. The more detailed assumptions are as follows:

(1) A crop plant in a well-defined geographic area, provided stable environmental and nutritional conditions, can reach Yattmax.


These relationships can be expressed as a set of general formulae:

1. Actual yield:

$$\text{Y}\_{\text{a}} = \text{Y}\_{\text{attmax}} \times \text{EN} \tag{1}$$

2. Nitrogen Efficiency (EN):

$$\text{EN} = \text{EP} \times \text{EK} \times \text{EMg} \times \text{ES} \times \dots \dots \times \text{ETi} \tag{2}$$

where Ya denotes the actual yield; Yattmax denotes the maximum attainable yield; EN is the fractional value of NUE; and EP, EK, ... , ETi are the fractional efficiencies of various N-supporting nutrients (N-SNs).

When the fractional value of an N-SN's efficiency index approaches 1.0 (≤1.0), it indicates a sufficient range of content of the N-SN in available form in the soil. However, any deviation from 1.0 indicates a disturbance in the supply of a given nutrient to the currently grown crop, thereby reducing the NUE. Summarizing the above assumptions, it should be clearly stated that the key challenge for the farmer is to achieve high productivity of N fertilizer (Nf), but without a reduction in yield. This goal is achievable, provided that the critical level (sufficiency range) of soil fertility is achieved for N–SNs. Only at the equilibrium state between the supplies of N and N–SNs to the plant during the growing season—in particular, in the critical phases of yield component formation—is it possible to effectively exploit the yield potential of the currently cultivated plant.

#### **3. Nitrogen—A Unique and Critical Factor in Plant Production**

There exists a general consensus that the choice of a cultivar with well-defined yield potential is the basis of crop cultivation. Exploitation of the crop potential, however, essentially depends on the supply of water and N. For these reasons, these production factors are defined as yield-limiting [38,39]. These factors cannot be, however, treated as substitutes [40]. Water is a growth factor that regulates the plant temperature and, as a consequence, its whole metabolism and growth [41]. It has been well-documented that the amount of water available to the plant during the growing season is the result of both the water retention capacity of the soil and current precipitation. These two factors determine the Yattmax under well-defined climate and soil conditions [36]. Water acts as a natural carrier of nutrients, both in soils and in the plant [42].

The plant is an autotrophic organism which, in order to close its life cycle, must be supplied with adequate amounts of both water and nutrients at well-defined stages of growth [43]. Plant growth can be defined as a set of processes in which both the plant and the soil—as its natural growth medium—interact with each other throughout the growing season. The importance of N for plant growth and yield results from its presence in key biological molecules [42]. The key N-dependent enzyme, which is decisive in the survival of life on Earth, is the ribulose bisphosphate carboxylase-oxygenase enzyme, simply called Rubisco (RuBP). Its key function is the capture and subsequent fixation of the CO2 molecule, which is the basic substrate for the production of elementary sugar compounds [44,45]. The total mass of Rubisco in terrestrial plants has been estimated at ≈0.7 Gt. This enzyme constitutes 2.5–3% of the total leaf weight of leaves and about 50% of the total leaf proteins [46]. A hypothesis has recently emerged that Rubisco may also be treated a source of N during protein synthesis. This phenomenon is revealed only under conditions of excessive CO2 capture by the plant in the circadian cycle [46].

N, mainly as nitrate (N-NO3), also acts a local and systemic signaling molecule involved in the current regulation of the hormonal status and morphology of the plant [47,48]. For this reason, this inorganic N form has recently been termed a plant morphogen [49]. Clear evidence for the dominant role of N-NO3 in yield formation is its influence on plant

growth, which affects both the shoot and root system architecture [50]. The effect of N supply to the plant manifests itself in clear, visible changes in the architecture of the plant's canopy. As can be seen in Figure 1a, wheat plants grown on an N control plot (i.e., without Nf supply) presented stunted growth (i.e., dwarf stature), low weight and surface area of leaves, and pale green color. In contrast, plants well-fed with N were characterized by a well-developed shoot, high mass and surface area of leaves, and an intense green color. All of these plants, despite a significant difference in the architecture of shoots, were in the same phase of growth (i.e., booting; BBCH 40–49). This phase is the crucial for the development of yield structure and determines the number of fertile florets [51]. Excess N supply to the plant, as shown for maize, results in the establishment of more cobs per plant (Figure 1b). However, this does not mean a higher yield of grain. Excessive supply of N also results in excessive growth of non-productive plant parts, leading to a reduction in grain per unit area [52,53].

**Figure 1.** Impact of nitrogen fertilization on nutritional status of winter wheat and maize (photos by W. Grzebisz).

The introduction of new cereal phenotypes in the 1960s, such as varieties with reduced stem length, first for wheat and then for rice, significantly changed the shoot architecture (dwarfism of the shoot). These genetic modifications resulted in an increased harvest index (HI)—that is, the share of grain in the total shoot biomass—at the expense of the stem. Improvement of the harvest index (HI) is the greatest effect of the Green revolution, as it finally led to higher grain yields of cereals, including rice [54]. However, the exposition of dwarf genes has also caused a reduction in the root system size of wheat varieties, which is significantly smaller than that of the classic ones [55,56]. As a consequence, the semi-dwarf or dwarf growth mode of modern cereals varieties result in the higher yield, provided that the supply of nutrients (especially Nf) is high, and that the plants are strongly protected against pathogens [54,57]. It can, therefore, be concluded that the currently grown cereals, due to their high requirements for N on one hand, and their smaller root systems on the other hand, are extremely sensitive to the supply of nutrients responsible for the uptake of N from the soil. One of the proposed solutions aimed at the increase in nitrogen use efficiency (NUE) are new-generation varieties that are capable of developing deep root systems. The proposed ideotype of this root system—referred to as "steep, cheap, and deep"—assumes the effective uptake of water and dissolved nutrients (mainly nitrates) [58,59]. A reorientation of the current breeding approach is urgently required in intensive production systems, where high rates of Nf are typically applied. It can also

provide a good solution in areas with frequent periods of drought, regarding the main phases of plant growth.

#### **4. Nitrogen-Supporting Nutrients**

Plant growth and productivity are the result of the action of about 20 elements that must be present in the soil to complete the plant's life cycle. The biophysical functions of plant-related elements have been well-documented and presented extensively in textbooks and review articles [60–62]. Not all of these elements are considered as nutrients, but all of them have a positive impact on the yield of crop plants [63]. A typical example is titanium (Ti), the positive effect of which on many crops has been recently documented [64].

N, considered especially in the form of nitrate (as discussed in the previous section), is the key nutrient, affecting both the rate of plant growth and the formation of yield components. The key evidence, in addition to that discussed above, is the response of the yield to the application of N–P–K fertilizers in various mutual fertilization systems. The effect of the interactions between N and other basic nutrients has been well-presented in long-term static fertilization experiments [65–67]. As shown in Figure 2, winter rye cultivated on Luvisol in a 7-course crop rotation (including two years of alfalfa) for 40 years yielded on plots without K (NP) or P (NK) only 6% and 5% less than on the NPK plot. The lack of both nutrients (i.e., K and P), as evidenced on a plot fertilized only with N, resulted in a yield drop of only 2.5%. The yield on the absolute control (AC) plot (i.e., the plot without application of any fertilizer, mineral or organic) for 40 years, was 30% lower than that on the NPK plot. Moreover, the same level of yield was recorded on plots fertilized only with P or K. Slightly greater differences between fertilization treatments were recorded for spring barley. Relative yield reductions were: −10%, −7%, and −42%, for NP, NK, and AC, respectively, as compared to NPK. The same yield level as for AC was noted on plots fertilized only with P or K. It must be added that the yields on the N plot were lower by 10%, compared to NPK [65]. The above-documented trends of plants grown on the naturally low fertility soil (Luvisol), with respect to different combinations of basic nutrients, have been supported by data from fertile soils, such as Entisol in the Netherlands (calcareous Entisol, containing 30% clay, 10% CaCO3. The obtained data indicated that a lack of K fertilization over a period of 28 years did not adversely affect the yield of four crops grown in four-course crop rotation (sugar beets, spring barley, potatoes, and winter wheat) over 28 years. The lack of P was much more important, as its lack reduced the yield of sugar beets by 11%, but those of potatoes and spring barley by only 7% [68]. These two examples clearly show that the main source of P and K for crops is soil.

**Figure 2.** Effect of fertilization variants on yield of winter rye grown in 7-course crop rotation and monoculture (based on [65]). Legend: \* Yield on the NPK variant = 100%; \*\* yield reduction—yield gap due to crop monoculture.

All plant nutrients support plant growth and yield formation through their impact on the productivity of N which, to a great extent, depends on the application of Nf Figure 1a,b. It can be concluded that it is unrealistic to expect an increase in the yield of a modern variety, as discussed above, without delivering N from external sources, whether natural (e.g., manure) or mineral. For these reasons, all nutrients affecting plant growth and yield can be called "nitrogen-supporting nutrients" (N-SNs). Based on agronomic practice, the whole set of N-SNs can be divided into four groups: (i) basic macronutrients, such as potassium (K) and phosphorus (P); (ii) secondary macronutrients, including magnesium (Mg), sulfur (S), and calcium (Ca); (iii) micronutrients, such as iron (Fe), manganese (Mn), zinc (Zn), copper (Cu), boron (N), molybdenum (Mo), and chloride (Cl); and (iv) the beneficial group, composed of nickel (Ni), sodium (Na), silicon (Si), and titanium (Ti) [61,69].

The second important stage in the development of an economically and environmentally sound fertilization system using Nf requires knowledge regarding the patterns of accumulation of N-SNs during the growing season. The classic pattern for high-yielding winter oilseed rape (WOSR) is presented in Figure 3. There are some characteristics "hotpoints" in N-SN in-season patterns that require special attention by the farmer, based on the course of N accumulation. The most important points are:

	- a. Starting with the rosette stage in Spring;
	- b. Achieving the maximum K uptake over N at the full flowering stage (K2O:N as 1:1.6);
	- c. Declining from flowering to maturity (K2O:N as 1:1).

**Figure 3.** Patterns of nutrient accumulation during the growing season by high-yielding winter oilseed rape (simulation based on [70]).

The presented patterns of N, P, and K accumulation by WOSR during the growing season, obtained at the end of the 20th century, were very similar to their trends observed in the 1980s [71]. The same pattern has been observed for high-yielding rice [72]. The effective production of maize depends on the supply of K and N during the period preceding flowering, but requires stabilization of K accumulation up the milk stage [73]. It can be concluded that the high yield of the seed crops can be achieved, provided that the K:N ratio is higher than 1.0 during the vegetative phases for seed plant growth. In the light of the available data, the maximum K:N should be revealed for the high-yielding crop just before the end of the linear phase of its growth [74]. The seasonal pattern of basic nutrient accumulation by legumes is only slightly different. As observed for soybean, the maximum K was at the late vegetative stages, and the level then decreased smoothly, while the accumulation of N, P, Ca, Mg, and S progressed through to maturity. Moreover, the maximum K:N ratio was 0.6:1 [75].

#### **5. Potassium**

The biophysical functions of K are well recognized and described [76,77]. The most important functions of K in crop production are those that affect (i) nitrate-nitrogen uptake, (ii) protein synthesis, (iii) water management (i.e., control of the stomata circadian rhythm), (iv) growth of vegetative organs (i.e., transport of assimilates from leaves to the new buds and tissues), and (v) yield formation (i.e., transport of assimilates from leaves to growing fruits). All of these functions are inherent in the plant's growth cycle [72,78,79].

The deficiency of K during the growing period of the cultivated plant adversely affects N uptake and, thus, photosynthesis, leading to a reduction in assimilate production [80]. K deficiency in the first stages of plant growth reduces the growth of single cells. As a consequence, the growth rate of new tissues and organs is reduced (Figure 4a); this applies to both roots and shoots. The reduction in shoot biomass is slightly lower than that in root biomass [80,81]. As documented for sugar beet, the growth rate of fibrous roots is much faster in soil rich in available K, compared to the soil with medium content [82]. The rate of plant cell expansion depends on the action of auxins, the concentration of which in the plant and transfer to the roots is strongly related to the availability of N-NO3 in the soil [49,83]. The stunted stature of crop plants is the most striking visual symptom of K deficiency (Figure 4). In maize, the length of internodes is drastically reduced during the phase of shoot intensive growth (Figure 4b). In cereals, the classical symptom is the same (i.e., reduced length of the stem). The secondary outcome, which is important in grain production, is the reduced density of ears (Figure 4a). This yield component will not be compensated for by a larger number of grains per ear or weight, thus directly leading to a significant decrease in grain density [24,84].

Crop plants differ in their demand for K. A proposed grouping of crop plants, according to K accumulated at harvest, and proposed recently by White et al. [85], has significant weaknesses. In general, it is true that cereals or legumes accumulate less K than dicotyledonous crops (leafy, root, or tuberous plants). It cannot, however, be concluded from this that cereals are tolerant of low soil K fertility level. It has been well-documented that cereals and cruciferous crops develop a large and intensive root system which, in turn, increases the absorption area of the plant for K uptake [86,87]. This specific plant feature determines the rate of K uptake under critical conditions, such as low content of available K or mild water stress. Sandy soils, as compared to loamy soils, as a rule are poorer in available K. Moreover, a decrease in the content of available water results in a much faster decrease in the coefficient of K effective diffusion [82,88,89]. The greater sensitivity of dicotyledonous plants to the level of soil K fertility is the result of two reasons [74,86]:


**Figure 4.** The stunted stature of plants due to potassium deficiency is the primary signal of yield depression in crop plants. (photos by W. Grzebisz).

Numerous scientific articles and even academic textbooks have presented—seemingly true—opinions regarding the quantitative dominance of N uptake over K accumulated by crops during the growing season [61,90]. This opinion can be applied to low-yielding crops, due to the deficiency of K in the linear phase of the plant growth [91]. In the case of high-yielding crops (i.e., those which are able to exploit the potential of cultivated varieties), the dominance of K uptake over N has been well-documented (Figure 3; [72,82]). The classic example is maize [53]. This crop takes more K than N during the vegetative growth. This opinion is also in accordance with a study on nutrient accumulation by wheat in India [92]. The authors clearly showed that the unit accumulation of K was higher than N, and the optimal N:P:K ratio in the plant dry matter for high-yielding wheat was as 6.6:1:8.1.

Based on the amounts of key nutrients accumulated by winter oilseed rape (WOSR), three regression models of the seed yield have been developed [93]. It is necessary to emphasize that the yield of WOSR ranged from 2.223 to 5.807 t ha−1. The obtained regression models were as follows:

$$\text{IN} \to \text{Y} = 0.12\text{N} + 1.192 \qquad \text{for } \text{n} = 18, \text{R}^2 = 0.69 \text{ and } p \le 0.01,\tag{3}$$

$$\mathbf{K} \to \mathbf{Y} = 0.007\mathbf{K} + 1.6 \qquad \text{for } \mathbf{n} = 18, \mathbf{R}^2 = 0.89 \text{ and } p \le 0.01,\tag{4}$$

$$\text{Mg} \rightarrow \text{Y} = -0.005 \,\text{Mg}^2 + 0.39 \,\text{Mg} - 2.242 \quad \text{for } \text{n} = 18, \text{R}^2 = 0.61 \text{ and } p \le 0.01 \tag{5}$$

The final K uptake, regardless of the seed yield and weather conditions during the research, always exceeded that of N. The linear course for N and K clearly indicates that both nutrients were limiting factors for the yield. Moreover, the strength of the effect of N on WOSR yield, according to the R<sup>2</sup> coefficient, was much weaker compared to that of K. This model of N and K accumulation by seed crops is not new, having been defined about 40 years ago for winter wheat and WOSR [71,94].

The seemingly contradictory opinion regarding the impact of N and K on yield is explained in Figure 5. The amount of K in winter wheat (WW) during the Yield Formation Period (defined by the linear increase in dry matter)—a mega-phase covering the main phases such as stem elongation, booting, and heading—exceeded, regardless of the water conditions, the amount of N taken up. Moreover, the K:N ratio up to the beginning of wheat flowering for irrigated wheat was higher than 1.0. A sharp drop in K accumulation was revealed during the grain filling period. The course of N was significantly different from that of K, showing a net increase in its accumulation up to the early milk stage (BBCH 72), then decreasing slightly. These two (partly opposing) trends resulted in the K:N ratio narrowing at wheat maturity. The same trend of K accumulation has been recently observed in barley [95]. The presented data clearly explain the discrepancy in published data regarding the trend of K accumulation by high-yielding crops.

**Figure 5.** Nitrogen (N) and potassium (K) accumulation by winter wheat in critical stages of yield formation under various water conditions; means of three growing seasons (Grzebisz, not published). Legend: The different letters indicate significant differences between the treatments (*p* ≤ 0.05); \* irrigation and \*\* non-irrigation conditions of wheat cultivation, respectively; K, N, potassium and nitrogen, respectively.

The importance of K for yield formation is to be considered through the expression of yield components. It has been well-documented that K accumulation in seed crops reaches its maximum before flowering (Figures 3 and 5). In seed crops, this period is crucial for establishing the seed/grain density, which is treated as the key yield component [96]. It should be clearly stated that an adequate K supply to the seed crop during the Yield Formation Period (YFP) supporting N supply is the prerequisite of high yield. The presented opinion is neither a hypothesis nor an assumption, but a conclusion from our own studies and supported by available literature sources. The excessive uptake of K by wheat may result, however, in GD reduction, consequently leading to a decrease in grain yield [97]. This phenomenon has also been observed in maize and dicotyledonous plants, such as potato [52,98–100]. The unexpected effect of excessive K uptake can be explained by the accelerated supply of N to plants due to co-transport of NO3 <sup>−</sup> and K<sup>+</sup> ions through the plasma membrane [62,80].

The role of K in the transportation of assimilates in the phloem has been welldocumented [60]. The survival of seeds/grain in the period from setting up to the watery stage is inherently related to the supply of assimilates [101]; therefore, it can be concluded that K is responsible for the final seed/grain set. This concept is supported by the impact of the accumulated K on yield components, as shown in Equation (1). As recorded by Grzebisz at al. [93], K uptake at the beginning of WOSR flowering was the key factor, positively affecting the seed density (SD), while negatively affecting Thousand Seed Weight (TSW) at the same time:

$$\text{SD} = 203.3 \text{K} + 3462 \text{ for } \text{n} = 18, \text{R}^2 = 0.92, p \le 0.01 \tag{6}$$

$$\text{TSW} = -0.04\text{K} + 691 \text{ for } \text{n} = 18, \text{R}^2 = 0.48, p \le 0.05 \tag{7}$$

The first equation fully corroborates the opinion of Pan et al. [102], who clearly stated that a deficiency of K reduces the sink size capacity. The second equation clearly confirms the phenomenon known as the dilution effect [103], concerning the dilution of nutrients in seeds, including N. Most important is the fact that the productivity of 1 kg of Nf increased from 14 to 24 kg seeds kg−<sup>1</sup> Nf for K uptake of 178 and 504 kg ha−<sup>1</sup> and seed yield of 3.0 and 5.14 t ha<sup>−</sup>1, respectively [93]. Potatoes are considered to be a K-sensitive crop, in terms of both yield and tuber quality [104]. Studies on the effect of the N × K interaction on tuber yield have clearly shown that an increased dose of K fertilizer can significantly increase N productivity. This is an important premise for reducing the Nf dose [105,106].

#### **6. Phosphorus**

As in the case of K, the biophysical functions of P in plants are well-known and understood [60]. Three of its key functions can be treated as essential in agricultural practice. The first one concerns the biochemical energy (i.e., adenosine triphosphate; ATP), which is a high-P-energy compound. The synthesis of ATP is completely dependent on the supply of P to a plant. The generated energy is used in all plant energy transformation processes, starting with uptake of nutrients, and then their transport and transport of assimilates between the plant's organs. At the end of this (energy and matter) transformation chain, the accumulation of organic compounds takes place in the main crop products (e.g., seeds, grains, roots, tubers, fruits) [107,108]. The second key function of P is the synthesis of nucleic acids (DNA and RNA), constituting 40–60% of the organic P pool in the plant. These compounds are components of genes and chromosomes, constituents of the plant's genetic code. For this reason, they are responsible—among other aspects—for crop production; that is, the production of new generations of plants through seeds and grains [109]. The third crucial function of P, which is important in plant production, is phytin. This is a P storage compound in seeds/grains. The content of P in seeds is important, stimulating their germination and plant vitality in the early stages of growth [110,111].

Phosphorus is taken up by the plant from the soil solution as an orthophosphate ion (H2PO4 −, Pi) [112]. The amount of P needed to maintain the optimum rate of plant growth is much smaller, compared to N and K [85]. In general, the P requirements of non-seed plants is much lower that of the seed- or fruit-producing plants, ranging from 14 to 40 kg P ha−<sup>1</sup> [107]. As with nitrates, the uptake of orthophosphate ions is an energydependent process. The key reason is the high P concentration gradient of 10,000 between its concentration in the plant cell (cytosol) and the soil solution [113]. The uptake of P from the soil is, first of all, a function of the plant root density (RLD; cm roots cm−<sup>3</sup> soil). The content of available P in the soil solution is the second factor determining its acquisition from the soil [114,115]. The mechanisms of P extraction from the soil are diverse, depending on the current P nutritional status in the plant. Plants deficient in P trigger a number of processes, such as investment in the RLD and root surface area, symbiotic associations with arbuscular mycorrhizal fungi, rhizosphere acidification, and activation of phosphate transporters in the plasma membrane. All of these processes undergo acceleration when Pi concentration in the soil solution decreases [116–118].

Phosphorus deficiency results from low Pi supply to the plant root, due to its low content in the soil solution or unfavorable environmental conditions, including low temperature, water shortage/soil drought, and low soil pH, among others [119]. The visual symptoms of P deficiency—regardless of the plant species—can be seen on older leaves as bluish–violet discoloration, leading frequently to plant death due to disturbances to basic physiological processes (Figure 6a). These symptoms, appearing in the early stages of plant

growth, are an indirect signal of a deep disturbance in N metabolism [120]. Crop responses to P deficiency manifest as growth inhibition, even leading to a failure in development of reproductive organs, which is often observed in maize (Figure 6b). A mild deficiency causes a temporary, short-term slowdown in plant growth [121]. The first plant response to a slight P deficiency is very specific, being manifested by the ingrowth of roots at the expense of the shoot biomass [108,122]. In a Pi-rich growth milieu, plants take up excess P to their needs, accumulating it an inorganic form. This pool is used during the growth of reproductive organs, such as seeds, grains, and tubers/roots [109,123].

**Figure 6.** Symptoms of phosphorus deficiency in two different species grown in humid climate zone: (**a**) violet plants of winter oilseed rape are not able to conduct photosynthesis); and (**b**) violet maize plants at BBCH 33 often fail to develop a cob. (Photos by W. Grzebisz.)

Phosphorus yield-forming functions are best recognized for seed crops for which two critical stages have been identified. The first, minor function refers to all plants, and appears in the early stages of plant growth, being an important factor influencing the growth rate of roots and shoots [111,118]. For this reason, in plant production, a starting dose of P fertilizer is suggested to be applied, regardless of the content available P in the soil [124]. The second critical period for P uptake by dicotyledonous crops is poorly understood. In root and tuber crops, the increase in P accumulation is associated with the stage of intensive sugar or starch accumulation (Figure 7; [123,125,126]). As has been reported by Barłóg et al. [126], <sup>1</sup> <sup>4</sup> of the recommended P rate for sugar beets is sufficient to achieve a moderate yield (≈60 t ha−<sup>1</sup> FW); however, in order to exploit the sugar beet yield potential in Poland (≈80 t ha−<sup>1</sup> FW of storage roots)—which significantly depends on weather—the full P rate is needed. The key reason for this is that the storage yield depends on the supply of P to the plant during the late stages of growth. The advantage of a lower P dose (as shown in Figure 4) is the cessation of N accumulation in storage roots, resulting in both earlier sugar beet technological maturity and a lower content of so-called harmful N compounds [126].

In the case of seed plants, the main period of P requirement begins at the onset of flowering (Figure 3; [71,94]). Most of the P accumulated in the vegetative parts of these plants is then stored in seeds/grains. In a mature seed crop, between 85–95% of the total accumulated P is in seeds/grains [127,128]. The P remobilization efficiency ranges from 60–85% [129]. The degree of depletion of P in vegetative plant parts by the growing seeds/grain is not limited by its content in those organs, as has been suggested by Veneklass et al. [109]. In fact, it depends on the number of seeds/grains per plant that act as a physiological sink [127]. The key reason for the excess of P in vegetative plant parts is not the low rate of P remobilization from vegetative plant parts, as suggested by Wang et al., [130], but the low requirements of the growing seeds/grains [127].

**Figure 7.** Effect of NPK fertilization systems on nitrogen accumulation in storage roots of sugar beets (based on Szczepaniak et al. [125]). Legend: PK—NPK100—the applied amount of P and K; N control; NP25K25—P and K applied at a dose of 25% compared to NPK100.

For low-yielding seed plants, and such a model dominates in the world, the P plant resources accumulated before flowering are sufficient to ensure even a moderate yield. The essence of the matter is the dilution effect that P is subject to in the reproductive organs of the plant [127,131,132]. However, a completely different model of the P management functions in high-yielding seed plants. In the first stage of reproductive organs growth, P is effectively re-mobilized and then re-translocated from the vegetative plant parts to the growing seeds/grains. The P resources accumulated in the plant before flowering, as a rule, are sufficient to cover the needs of the reproductive plant's organs. One of the reasons for this is the high P plasticity in seeds/grains, expressed by a very high rate of its dilution. This phenomenon has been observed for maize, wheat, rice, and winter oil seed rape [108,127]. In the second stage of seed/grain growth, the increased demand for P can be covered by P taken up by the plant from the soil [108,133]. This strategy is especially important for rice, which takes up 40–70% of the total P from the soil during the grain-filling period [129].

The reliability of long-term experiments for the assessment of P management by plants is limited by too high doses of P fertilizers used annually [65–67]. As a result, the recovery of P, even assessed over a long period, is typically low. As has been reported by Buczko et al. [66], the annual rate of P ranged from 10 to 210 (with an average of 60.7) kg ha−<sup>1</sup> y<sup>−</sup>1. The relative increase in yield, even on soil naturally poor in the available P, did not exceed 10%. Consequently, these data cannot be used to determine the sufficiency level of available P (P-SL) in the soil for the tested plants. A high P recovery (P-R) is usually expected in soils poor in available P. As shown in Figure 8, wheat responded to P fertilization up to 45 kg P2O5 ha−1. This P dose increased the content of available P in the soil to a level sufficient for the maximum yield of wheat in this particular study. There was no increase in the yield above the range of 16–18 mg P kg−<sup>1</sup> soil. Above this range, there was no response of wheat to an increase in the content of available P just before flowering [134]. In the presented example, the P recovery was 65% in the variant with 15 kg P2O5 ha<sup>−</sup>1, 50% in the variant with 45 kg P2O5 ha<sup>−</sup>1, and only 16% in the variant fertilized with 150 kg P2O5 ha−1. Moreover, in P-R, starting from a plot of 45 kg P2O5 ha−1, this perfectly fits into the power function:

$$\text{P}-\text{R}=1751 \text{P}\_{\text{f}}{}^{-0.94} \text{ for } \text{R}^2 = 0.999 \text{ and } \text{n}=8 \tag{8}$$

This example clearly demonstrates that Pf rates above that required for P–SL do not affect crop yield. Excessive P content in vegetative wheat parts, above P–SL, indicates insufficient size of wheat sink (the number of grain per unit area) to utilize these resources. This means that, for current wheat varieties, it is necessary to prepare new plant nutrition standards. Those that were developed 40–50 years ago are not reliable in current agricultural practice [135]. In the presented case, however, the most important fact is that the partial factor productivity of Nf (PFP-Pf) increased from 28 to 45 kg grain kg Nf <sup>−</sup><sup>1</sup> in the control P plot and 45 kg P2O5 ha<sup>−</sup>1, thus determining the appropriate P-SL range.

Two conclusions summarize this section: first, the shortage of P significantly reduces, while its excess supply does not affect, N productivity; second, the Pf rate should adjusted to the soil level of availability that maximizes the productivity of Nf of the currently grown plant.

**Figure 8.** Yield of wheat response to the content of available phosphorus (based on [134]). Legend: \* SR, \*\* SL, phosphorus sufficiency range, sufficiency level of the content of available P (determined by Olsen method).

#### **7. Efficient Nitrogen Management—The Soil Fertility Clock Concept**

#### *7.1. Definition of the Concept*

The role of Nf in crop production, which is the absolute basis of food production, results from its effects on the rate of plant growth, partitioning of assimilates between plant parts, formation of yield components, and quality of plant products [136]. The dominant impact of N on the life cycle of crop plants, as presented above, is justified at three levels of organization of the plant production process: (i) biochemical, (ii) physiological, and (iii) agronomic.

The key productive function of all other nutrients is to support the actions of N and, in fact, to control its productivity. The nitrogen use efficiency (NUE) is defined as the amount of main product per unit of N taken up by the plant during its growing season [137]. For this reason, any sophisticated attempt to calculate efficiency indices for K, P, or even for other nutrients is useless for a farmer. The calculation is useful, but only for understanding basic biophysical processes in crop plants [85,138,139]. The supply of N-SNs to the currently grown plant should be maintained at the level that maximizes—and not reduces—the yield-forming effects of N. It is necessary to take into account that the farmer cultivates plants in a specific sequence, called crop rotation. Therefore, the key goal of the farmer is to determine the critical level of soil fertility, not for all crops in rotation, but for the most sensitive plant to the nutrient, decisive for N productivity. This is the key challenge for the farmer, which should be treated as a necessary condition aimed at the development of an effective Nf management system for both farm economics and without imposing negative pressure on the health of the environment.

#### *7.2. Maximum Attainable Yield—A Farm Production Goal*

The potential yield of the grown plant—that is, the yield achieved under optimal environmental conditions (climate + soil) and rational management of the applied resources—is a theoretical term. This term, however, defines the production target, which may not be achievable in real production conditions [140,141]. Despite this, farmers need data on the maximum yields of crops that are grown in the geographical area of their production activity. This forms the basis for assessing the distance from the actual yield (Ya) to the realistic production target, namely, the maximum attainable yield (Yattmax). There are several ways to calculate or forecast Yattmax and Ya. There is no doubt that the most important factor determining N uptake from the soil solution is water, the carrier of ions arriving at the root surface [60]. Therefore, one of the most frequently used methods for Ya determination relies on water productivity, in terms of water use efficiency (WUE). This method assumes a fixed amount of yield per unit of water [142]:

$$\text{WUE} = \frac{\text{Y}\_{\text{a}}}{\text{ET}\_{\text{a}}} \tag{9}$$

where Ya is the actual yield (kg, t ha<sup>−</sup>1) and ETa is the water use (i.e., water transpired by a plant or evaporated from the bare soil; mm, m3);

This method assumes that a plant's yield increases with an increasing amount of available water. Hence, the yield defined in this way is called "the water-limited yield" (WLY) [142]. This method has been modified by Grzebisz et al. [82], as follows:

$$\text{WLY} = \text{TE} \left( \text{R} - \Sigma \text{E}\_{\text{s}} \right) + \text{WR} \tag{10}$$

where TE is the transpiration efficiency (TE = *k*/VPD; *k* is the biomass transformation ratio), VDP is the vapor pressure deficit (hPa), R is the total sum of rainfall during the growing period of the cultivated crop (mm, m3), Es is the seasonal soil evaporation (equal to 110 mm), and WR denotes the water reserves in the rooted soil zone (mm, m3).

The main component of this equation is TE. Its value for wheat in Australia has been estimated at 20 kg grain mm−<sup>1</sup> of water, with a maximum of 30 kg grain mm−<sup>1</sup> [143]. However, this index depends on the amount of water available during the growing season; for example, as reported for spring triticale grown in a humid climate (Poland), the TE value ranged from 15 to 39 kg grain mm−<sup>1</sup> [93]. This wide range clearly indicates the high sensitivity of this index to soil fertility and, consequently, to the effect of nutritional factors on plant growth and yield. Moreover, WLY cannot be regarded as a constant climatic value, as it largely depends on the amount of available water during the growing season for the currently cultivated crop. As shown in Figure 9, for maize, the WLY ranged from 8.52 t ha−<sup>1</sup> in a year with a normal pattern of weather conditions to 5.68 t ha−<sup>1</sup> in a year with drought. The obtained yields, despite the completely different course of weather, were relatively high. The main reason for this was soil fertility (sandy loam, naturally rich in available K and other nutrients). The main conclusions that can be drawn from this Figure are as follows:


The yield drop was accelerated by the increased dose of Nf. This unexpected effect (i.e., yield suppression) was due to the excessive accumulation of N in maize biomass before flowering, which resulted in a reduction in the number of kernels per cob [144,145].

The analysis of the partial factor productivity of the Nf index (PFP-Nf), for the presented case, is even more interesting. In 2001, the highest value of the index (109 kg grain kg Nf <sup>−</sup>1) was recorded on a plot with high K level and fertilized with 100 kg N ha−1. The highest yield, however, was achieved on a plot with a medium K availability range and with 140 kg N ha−1, resulting in PFP-Nf of 100 kg grain kg Nf <sup>−</sup>1. Both values are high, compared to the literature data [146]. In the presented case, it is worth discussing the rational choice of both N and K fertilizing systems. Raising the K soil fertility level to the high class resulted in a reduction in the dose of Nf by 40 kg ha<sup>−</sup>1. It is necessary to take into account the fact that, on the field with the medium K level, the application of 140 kg N ha−<sup>1</sup> increased the yield by 29%, when compared to the treatment with 100 kg N ha<sup>−</sup>1.

**Figure 9.** Effect of K soil fertility on maize yield in two years differing in water regime (modification based on [144]). Legend: \* soil K fertility level: M, medium, D, high; \*\* Partial factor productivity of Nf (kg grain kg−<sup>1</sup> Nf).

The WLY concept is a good tool for scientific studies. In agricultural practice, its use requires a set of data that is not typically readily available to the farmer. Moreover, this method does not explain the action of factors responsible for WUE. A proposed alternative method for determining Ya is the concept of nitrogen gap (NG) [91]. The main components of this methodological approach for yield gap calculation are the Nf applied to the crop (which is known to the farmer) and the main yield. This data set may be enriched with other environmental and agronomic data that impact the NUE. The calculation procedure consists of the following steps:

$$\text{Partial Factor productivity of N}\_{\text{f}}; \quad \text{PFP}\_{\text{Nf}} = \frac{\text{Y}}{\text{N}\_{\text{f}}} \left( \text{kg} \,\text{kg}^{-1} \,\text{N}\_{\text{f}} \right) \tag{11}$$

Attainable maximum yield : Yattmax = *c*PFPNf · Nf t, kg ha−<sup>1</sup> (12)

$$\text{Yield Gap}: \qquad \text{YG} = \text{ Y}\_{\text{attmax}} - \text{ Y}\_{\text{a}} \left( \text{t} \,\text{ha}^{-1} \right) \tag{13}$$

$$\text{Nitrogen Gap (N}\_{\text{uw}}):\qquad \text{NG} = \frac{\text{YG}}{c \text{PFP}\_{\text{Nf}}} \Big(\text{kg N} \,\text{ha}^{-1}\Big)\tag{14}$$

where

Nf is the amount of applied fertilizer N (kg ha<sup>−</sup>1);

PFP-Nf is the partial factor productivity of Nf (kg grain/seeds, tubers, etc., per kg Nf);

Yattmax is the maximum attainable yield (t ha<sup>−</sup>1); *c*PFP-Nf is the average of the third quartile (Q3) set of PFPNf indices, arranged in ascending order (kg grain/seeds, tubers, etc., per kg Nf); YG is the yield gap (t ha<sup>−</sup>1);

NG is the nitrogen gap (kg N ha−).

The advantage of this method over the WLY is its simplicity in determining both Ya and Yattmax in a well-defined soil–climatic geographical area. The farmer, having access to data on environmental and agronomic production conditions (e.g., soil texture, soil pH, contents of basic nutrients, plant variety, level of plant protection, date of sowing) in their production region, can determine factors limiting the Yattmax. The Ya is a function of the formula:

$$\text{Y}\_{\text{a}} = \text{Y}\_{\text{attmax}} - \text{YG} \tag{15}$$

The NG values are required to produce a Yattmax diagram, showing the distance between Ya and Yattmax. The detailed procedure for preparing the NG diagram has been described in recently published papers [147,148]. The distance Ya for a specific field from Yattmax can also be expressed by the fractional Ya index (Yaf):

$$Y\_{\text{af}} = \frac{Y\_{\text{a}}}{Y\_{\text{attmax}}} \tag{16}$$

A value of Yaf approaching 1.0 indicates sustainable management of applied Nf.

#### *7.3. Factors Affecting N Fertilizer Use Efficiency*

As shown in Equations 1 and 2, the Ya of the cultivated plant is the result of the interaction between Yattmax and efficiency of applied Nf (ENf). In turn, the ENf depends on the effectiveness of other factors that limit or increase the productivity of Nf.

The total number of factors which impact ENf can be divided into five main groups:


The first group of production factors (i.e., organization and management of plant production processes on the farm) should not have a negative impact on the yield. In an economically well-run farm, the effectiveness of this group of factors should be at the level of 1.0—this is, after all, a basic prerequisite of the food production approach, known as the Sustainable Intensification of Agriculture (SIA) [14]. However, its implementation is only apparently easy. In fact, plant production on farms is under deep economic pressure [149]. A classic example is the method of plant cultivation. The economical decision to grow crops in monoculture, instead of crop rotation (a classical example is maize), may significantly reduce production costs, but a farmer must be aware of yield decreases [150]. There remains, however, uncertainty regarding the effectiveness of other production factors, which usually deteriorate. The decrease in yields of classic cereals grown under long-term monoculture is substantial. As shown in Figure 1, for winter rye, it can reach −20% under NPK treatment. The shortage of K resulted in a yield drop by 24% and that of P by 33%. There are also negative environmental effects to such an approach [151].

The farmer must effectively manage all agronomic factors and the health of the plant [61]. The efficiency of these factors, in accordance to the SIA concept, should be also set at 1.0. In this group, tillage and crop rotation are of particular importance for the available N pool and the uptake of its inorganic forms (Nmin) by plants [152,153]. The main task of soil tillage is to mix plant residues, manure, and mineral fertilizers—especially those containing low-mobility nutrients (P, K)—into the topsoil. No less important is the loosening of deeper soil layers and elimination of the plow sole [154]. The main production goal of this set of agronomic treatments is to increase the potential of the currently grown plant to penetrate the subsoil with its roots. It cannot be considered as only a source of water, as it is an important source of both Nmin and N-SNs. Under conditions unfavorable to plant growth, such as drought, the yield is largely determined by water and nutrient resources in the subsoil [155–157]. Unfortunately, the greatest weakness of the current methods for diagnosis of soil fertility and the resulting fertilization recommendations (apart from N) is a lack of methods for assessing the capacity of these resources and the availability of N-SNs. A simple technical and diagnostic solution is the use of extractants for Nmin [158,159].

The succession of plants grown on a given field is highly important for the effective management of N. A classic, biologically documented pattern of plant succession is the Norfolk rotation, which has been known for about two centuries [54]. As shown in Figure, 1, the cultivation of winter rye, a crop considered by farmers to be tolerant to monoculture, resulted in the significant yield reduction, which was exacerbated by the lack of balance of N with other nutrients. The cultivation of winter wheat (WW) after cereals also leads to yield reduction [67,160]. As has been reported by Babulicova [160], the yield of WW following legume plant was 29% higher than that following cereals. The well-established crop sequence is based on the assumption that dicotyledonous and monocotyledonous crops should be cultivated alternately in successive years. The advantages of crop rotation, regarding the efficient use of Nf are [65,87,161,162]:

	- a. Mobilization of the soil nutrient resources (root exudates, mycorrhiza);
	- b. Increased soil water capacity, resulting in better infiltration of rainwater;
	- c. Increased exploration of the subsoil (i.e., growth of cereal roots in the root pores of dicots).

Crop rotation should not be considered by the farmer as a factor that decreases yield. Unfortunately, this is not the case, as has been evidenced in the scientific literature and agricultural practice. The key reasons for yield reduction due to wrongly planned crop succession (or even monoculture), to a great extent, are:


#### **8. An Efficient System for Management of N-SNs—Principles of the Soil Fertility Clock**

#### *8.1. State of K and P Fertility Level and Food Production*

The crop production potential of a single field in inherently related to its soil fertility level, presented as the depth of the humus profile and the content of available nutrients [165]. Fertile soil creates conditions for the build-up of a large (extensive) root system, which is crucial for the uptake of non-mobile nutrients, such as phosphorus and potassium [166].

The share of N, P, and K fertilizers in total nutrient uptake by cereals has been assessed as 33% for N, 16% for P, and 19% for K [167]. In China, as reported by Ren et al. [168], K fertilizer covers less than 20% (18.5%) of the total K in winter oilseed rape at harvest. Khan et al. [169], who studied 1400 field trials fertilized with K, did not observe any significant impact of the applied K (as KCl) on the yield of basic crops. According to MacDonald et al. [170], 29% of the world area of arable soils shows a deficit, while the remaining part shows a surplus of available P. The significant impact of P fertilizer can be revealed, as a rule, on soils with a low content of available P. The yield loss due to deficiency of P supply (P yield gap) to wheat is 22% (18–28%), 55% for maize (47–66%), and 26% for rice (18–46%). Moreover, the application of P fertilizers reduced this production gap to only 17% for wheat, 46% for maize, and 15% for rice [116]. At this point, it is necessary to ask whether the yield gap is actually due to a deficiency of available P, or the ineffectiveness of Nf due to the imbalance of P and other nutrients.

The key question to be formulated is: what is the appropriate level—or rather, the critical range—of N-SNs content in the soil? In the light of the facts presented above, classic P and K management strategies require significant modifications. The basis for these required corrections is the fact that the plants are grown in a cropping sequence determined by the economic goals of the farm. Not all modern crop sequences follow rational principles (i.e., biologically based crop plant succession) [54,171–173]. It has been well-documented, in millions of scientific articles, that the deviation of a particular cropping sequence from biological rules leads to a decrease in yield. The classic example is the Rothamsted longterm experiment with winter wheat [67]. Wheat followed directly by wheat or grown in monoculture yielded a significantly lower level, compared to that following dicotyledonous plants. Second, the maximum grain yield achieved under non-optimal rotation was, in this example, both lower and, at the same time, required a higher Nf rate. These results clearly indicate lower unit Nf productivity due to N immobilization, disturbance in uptake of N-SNs, and stronger pressure by pathogens [150,174–176].

The soil resources of P and K are the main source of nutrients for the cultivated crop. Over-exploitation of available pools of these nutrients leads to the degradation of soil fertility, subsequently resulting in the lower Nf productivity. Moreover, these processes create a multi-level risk, for the yield, farm economics, and the environment (Photos 2 and 3; [177]). The productivity of a particular field is determined by the level of soil fertility, conditioned by water capacity and the content of available N-SNs in the rooting zone of the currently cultivated crop [153,154,157]. At present, the subsoil resources of N-SNs are not included in typical soil fertility status diagnostic procedures. Moreover, there is a frequently presented opinion regarding their low significance for the plant growth and yield [178]. In the light of the published data, the share of P and K from fertilizers for crop plant nutrition is of secondary importance for the maintenance and synchronization of plant needs and nutrient supply from the soil. The logical conclusion to be drawn from these facts is unambiguous: the farmer's goal for effective management of Nf is not to use P and K fertilizers or other carriers of these nutrients for direct feeding of the plant, but to coordinate the soil fertility level to maximize Nf use efficiency.

#### *8.2. Management of Soil Fertility—Oriented to Cropping Sequence*

Soil productivity is the ability of arable soil to provide the currently grown plant with air, water, and nutrients in the required amounts, mutual proportions, and ratios, ensuring full expression and development of the yield components [179]. This general property of arable soils has been indicated as one of the most important objectives listed in the Sustainable Development Goals (SDGs) by the United Nations in the 2030 Agenda for Sustainable Development [180]. This global goal can be achieved, but only through two targeted actions. The first is oriented towards stopping the degradation of soil fertility. This action refers to the world regions where soil fertility has been drastically reduced [10,177]. The second requires a significant correction in N-SN management strategies in areas of the world with advanced crop plant productivity. The so-called Old Agricultural Areas of the world will be decisive for food supply to the growing human population in the coming decades.

At present, two main concepts dominate in soil fertility management. The first—called the maintenance approach—is based on the assumption that the main goal of N-SNs is necessary to maintain the content of available nutrients at a certain level, allowing crop growth and yield. Three phases of soil fertility build-up can be distinguished using this approach: (i) build-up, (ii) maintenance, and (iii) draw-down [181]. In practice, the recommended rates of nutrients increase with the size of the gap between the maintenance level and the actual soil fertility status for a given nutrient. In most countries, using this fertilization approach, the nutrient doses recommended by agrochemical testing laboratories are consistent with the state of its deficiency. A classic example is the K recommendation in China for WOSR yielding at 3.75 t ha−<sup>1</sup> [168]. The decreasing content of available K (NH4OAc-K extraction method) resulted in increasing the dose of applied K from 232 kg ha−<sup>1</sup> at low K range to 50 kg ha−<sup>1</sup> at high K range. The second approach, called sufficiency ranges, is based on the required (i.e., sufficient) level of the given nutrient for the respective crop [181].

These two fertilization strategies are based on the assumption that low-mobility nutrients are as effective as nitrate nitrogen [147]. The coefficient of effective diffusion for the N form is 2.7 × <sup>10</sup>−<sup>1</sup> cm<sup>2</sup> <sup>s</sup>−1. In comparison, this index for K+ and NH4 <sup>+</sup> ions are about 100-fold lower (1–28 × <sup>10</sup>−<sup>8</sup> and 6.1 × <sup>10</sup>−<sup>8</sup> cm2 <sup>s</sup>−1, respectively). For H2PO4 − ions, this index is 10,000-fold lower, compared to nitrates [182,183]. The differences in the uptake rates of N and K are shown for sugar beets in Figure 7. Within 7 days of sugar beet growth in July, the N-NO3 resources, but not K, were completely depleted (100%) to a depth of 1.8 m. For K, this level of depletion was reached at a depth of 0.5 m. The most intensive uptake of both nutrients took place in the soil layer (0.0–0.6 m). There are two main conclusions to be drawn from Figure 10:


**Figure 10.** Degree of nitrate and potassium utilization in the soil during the maximum stage of K accumulation by sugar beets (based on [74]).

The classic concepts of N-SNs do not take into account two crucial facts; that crop plants differ in their sensitivity to the supply of N-SNs:

a. During the growing season;

b. In the course of crop rotation.

The efficient management of N-SNs in a soil/plant system should be based on the following principles of crop production:

	- a. Seed crops show critical periods, in terms of P requirements, during the vegetative (minor one) and reproductive (main one) periods of growth;
	- b. All crops are sensitive to K during the linear phase of growth.
	- a. Seed crops is to strengthen N action;
	- b. Dicotyledonous crops is acceleration of the early rate of the plant growth (mostly up to the rosette stage).

All of these points should be taken into account by the farmer during the process of development of the fertilization system.

Soil Fertility Clock (SFC) is an approach based on three assumptions which are key to the effective management of Nf:


The SFC concept is visualized in graphical abstract and explained in Figure 11 and Table 1. The critical K level for oilseed rape or any other dicotyledonous crop creates favorable conditions for the succeeding crop; that is, cereals, and most often wheat. The K level will still be high enough to cover the K requirement of wheat. A third crop in a certain cropping sequence—for example, maize—requires the farmer's attention to adjust the K content. This is necessary only if the K content drops below the medium level. This is very probable when harvest residues are removed from the field (Table 1). The critical period of K correction, which must be oriented toward the so-called crop rotation critical K level is, in the discussed case, the spring barley growing season. This is a key term in the agronomic clock for determining both the level of K in the soil and determining the fertilization needs for the plant sequence spring barley → winter oil-seed rape. Managing P in crop rotation is a bit more complicated. It requires, regardless of the grown crop, the use of a starting dose of P fertilizer. Basic P fertilization complies with the principles presented for K. An additional component of an effective system regarding the full set of nutrients is

foliar fertilization. This method allows for the correction of plant nutritional status—in fact, N action—but only at stages preceding the critical stages of yield formation.

**Figure 11.** The crop rotation conceptual approach for the sufficient K level and range on sandy loam for sensitive and non-sensitive K plants. Legend: <sup>1</sup> CL–N-Sc, CL–Sc, CR–N-Sc, <sup>2</sup> CR–Sc: critical level and critical range for non-sensitive and sensitive plants to the content of available K (determined by the Egner–Riehm method).

**Table 1.** Phosphorus and potassium balance in four-course rotation with winter oilseed rape. under full use of straw 1,\*, t ha−1.


<sup>1</sup> Simulation based on authors own data; \* average range of soil fertility with P and K; \*\* recovery of P and K from straw during four-course rotation, phosphorus −50%, potassium −90%.

#### **9. Conclusions**

Many factors directly and indirectly affect the yield of plants grown on the farm. The dominant one is N, which determines the dynamics of plant growth, partitioning of assimilates between the plant's organs, the expression of yield components, and consequently the yield. Currently, effective plant production is based on the use of Nf. The first step in an efficient management of Nf is to determine the maximum attainable yield of crops grown on the farm. This yield category is defined by the basic environmental factors, i.e., climate and soil fertility, but at the same time it is strongly modified by agronomic factors (crop rotation, soil tillage, plant protection). However, the most important of these factors is the Nf dose. The target yield can be achieved as long as the efficiency of Nf approaches 1.0, but at the same time the Nf, regardless of the dose, does not reduce the yield. The synchronization of N demand, which varies in the plant's life cycle with the rate of its uptake (in fact, nitrate) from the soil, is not dependent on its soil resources. This condition is met, but only when it is balanced with the supply of other nutrients (nitrogen-supporting nutrients; N-SNs). This, it can assumed that effective control of Nf efficiency does not only depend on its applied dose. The yield of high-yielding crops determines the interaction efficiency of N × P and N × K. The requirements of crop plants for P and K during the growing season are time-separated. The period of intensive biomass growth is a critical stage in the sensitivity of the plant to the supply of K. In seed plants, the N × K interaction predefines the development of yield components. The sensitivity of plants to the supply of P is revealed both in the early stages of growth and in the phase of yield realization. The second phase is crucial for seed plants. Phosphorus deficiency results in poor development of fruits, grains and seeds. A deficiency of both nutrients in the soil during the critical stages of yield formation results in both a decreased Nf efficiency, and consequently, a lower yield. The basic production unit on a farm is the field, on which plants are grown in a specific time-sequence, known as crop rotation. The condition for achieving the required level of Nf (≤1.0) efficiency is the high effectiveness of other production factors, which is to be set at ≤1.0. The operational basis of an effective control of Nf efficiency is the content of P and K in the soil, which should be oriented to cover the requirements of the most sensitive plant in a well-defined crop rotation. Thus, the main goal of P and K application to the soil is to restore their content in the topsoil to the level required by the most sensitive crop in a given crop rotation. The other crops grown in this cropping sequence provide the time-frame to actively control the distance between the current P and K content from the required critical ranges.

**Author Contributions:** Conceptualization, W.G.; methodology, W.G.; software, P.B.; validation, W.G., J.D. and P.B.; formal analysis, W.G.; investigation, P.B., M.B., J.P., R.Ł., K.P.-C. and W.S.; resources, J.P. and W.S.; data curation, R.Ł. and K.P.-C.; writing—original draft preparation, J.P. and P.B.; writing review and editing, W.G.; visualization, J.P.; supervision, J.D.; project administration, M.B. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


**Przemysław Barłóg \*, Witold Grzebisz and Remigiusz Łukowiak**

Department of Agricultural Chemistry and Environmental Biogeochemistry, Poznan University of Life Sciences, Wojska Polskiego 71F, 60-625 Poznan, Poland; witold.grzebisz@up.poznan.pl (W.G.); remigiusz.lukowiak@up.poznan.pl (R.Ł.)

**\*** Correspondence: przemyslaw.barlog@up.poznan.pl; Tel.: +48-618-48-77-88

**Abstract:** Fertilizer Use Efficiency (FUE) is a measure of the potential of an applied fertilizer to increase its impact on the uptake and utilization of nitrogen (N) present in the soil/plant system. The productivity of N depends on the supply of those nutrients in a well-defined stage of yield formation that are decisive for its uptake and utilization. Traditionally, plant nutritional status is evaluated by using chemical methods. However, nowadays, to correct fertilizer doses, the absorption and reflection of solar radiation is used. Fertilization efficiency can be increased not only by adjusting the fertilizer dose to the plant's requirements, but also by removing all of the soil factors that constrain nutrient uptake and their transport from soil to root surface. Among them, soil compaction and pH are relatively easy to correct. The goal of new the formulas of N fertilizers is to increase the availability of N by synchronization of its release with the plant demand. The aim of non-nitrogenous fertilizers is to increase the availability of nutrients that control the effectiveness of N present in the soil/plant system. A wide range of actions is required to reduce the amount of N which can pollute ecosystems adjacent to fields.

**Keywords:** crop growth rate; fertilizer market; nitrogen use efficiency; nitrogen gap; nutrient uptake; partial factor productivity; root architecture

#### **1. Fertilizer Use Efficiency—A Real Farming Practice**

*1.1. Nitrogen Gap and the Maximum Attainable Yield*

A farmer needs to recognize production boundaries in order to develop an effective production program for each of the crops grown on the farm. The key to the sound management of production processes is a knowledge of the maximum yield that can be achieved in a production area with a well-defined climate and soils. The actual yield (Ya) of a currently cultivated crop may be simply presented as the difference between the maximum attainable yield (Yattmax) and the yield gap (YG). The relationship between these terms may be expressed as the formula:

$$\text{Y}\_{\text{a}} = \text{Y}\_{\text{attmax}} - \text{YG} \tag{1}$$

Ya is a real, harvested yield in the current growing season under actual environmental, agronomic and management practice on the farm. To define the Yattmax of this crop, two conditions must be fulfilled. The first concerns a strictly defined climatic area and the dominating, i.e., standard, weather conditions [1,2]. The second necessary condition is the level of soil fertility, agronomic conditions and management of the production processes on the farm. These factors modify the Yattmax of the grown crop [3,4]. All of these factors must be oriented towards optimizing the supply of nutrients to that particular crop only [5]. The YG is a measure of the ineffectiveness of production factors, in fact expressed in the ineffectiveness of fertilizer nitrogen (Nf), or available N present in the soil/plant system during the growing season of the currently grown crop [6]. The basic and at the same

**Citation:** Barłóg, P.; Grzebisz, W.; Łukowiak, R. Fertilizers and Fertilization Strategies Mitigating Soil Factors Constraining Efficiency of Nitrogen in Plant Production. *Plants* **2022**, *11*, 1855. https:// doi.org/10.3390/plants11141855

Academic Editor: Dimitris L. Bouranis

Received: 29 June 2022 Accepted: 12 July 2022 Published: 15 July 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

time simplest method for calculating both components of the Ya formula is to use the efficiency index of Nf known as the Partial Factor Productivity of Fertilizer N, PFPNf [7]. Considering both the yield and the environmental aspects of the on-farm production process, the farmer's goal should not be to determine the YG, but rather the ineffectiveness of the applied Nf. The quantitative expression of N inefficiency is the nitrogen gap (NG) [8]. In fact, two sets of data are needed to determine both the YG and the NG, i.e., (i) the actual yield harvested by the farmer, and (ii) the amount of applied Nf. The calculation procedure consists of a set of formulas:

Partial Factor Productivity of Nf:

$$\text{PFP}\_{\text{Nf}} = \frac{\text{Ya}}{\text{N}\_{\text{f}}} \left( \text{kg} \,\text{kg}^{-1} \,\text{N}\_{\text{f}} \right) \tag{2}$$

Attainable, maximum yield:

$$\mathbf{Y}\_{\text{attmax}} = \mathbf{c} \mathbf{P} \mathbf{F} \mathbf{P}\_{\text{Nf}} \times \mathbf{N}\_{\text{f}} \left( \mathbf{t} \text{ or } \mathbf{k} \mathbf{g} \text{ ha}^{-1} \right) \tag{3}$$

Yield Gap:

$$\text{YG} = \text{ Y}\_{\text{attmax}} - \text{ Y}\_{\text{a}} \left( \text{t } \text{ha}^{-1} \right) \tag{4}$$

Nitrogen Gap:

$$\text{NG} = \frac{\text{YG}}{\text{cPFP}\_{\text{Nf}}} \left( \text{kg} \,\text{N} \,\text{ha}^{-1} \right) \tag{5}$$

where: PFPNf—partial factor productivity of Nf, kg grain/seeds, tubers etc. per kg Nf; Ya—actual yield of a currently grown crop, t ha−1; Nf—the amount of applied fertilizer N, kg ha−1; Yattmax—the maximum attainable yield, t ha−1; cPFPNf—the average of the third quartile (Q3) of the set of PFPNf indices arranged in ascending order, kg grain/seeds, tubers etc. per kg Nf; YG—yield gap, t ha<sup>−</sup><sup>1</sup> ; NG—nitrogen gap, kg ha−<sup>1</sup> of N.

The NG calculation is important for the farmer for at least three areas of his production activity: (i) the determination of Yattmax, which determines not only the maximum yield for the production area, but also determines the potential requirements of the cultivated crop for N; (ii) the identification of hotspots in N management for a given crop, including an inadequate supply of nutrients other than N; (iii) the set of actions needed to improve the level of soil fertility for a given crop.

The data on NG is used to construct a diagram of the impact of the NG change on trends in actual and maximum yields (Figure 1). The target of the NG construction is to find the maximum attainable yield (Yattmax) for the geographical area of the farm operation. The Yattmax value is determined by the intersection of Ymax and Ya linear regression models. In this specific case, representing 16 fields located in a small region of central-western Poland, the weather and soil conditions are stable. Yattmax for winter wheat reached 7.99 t ha−1. Moreover, both Ya and Yattmax showed significant variability in the amount of *notworkable* Nf during the growing season. The course of both models indicates a surplus of Nf on fields No. 13 and 10 as the main reason for its lower use efficiency. The maximum YG on field No. 13 reached 3.729 t ha<sup>−</sup>1, i.e., it constituted 47% of the actual yield. The diagnostic goal of the NG diagram construction is to identify the key factors responsible for YG appearance as a result of Nf inefficiency. The ranges for the evaluation of the effect of any production factor were constructed using a clear scale: low, medium, high, which were in special cases underlined by "very". The use of this scale to assess the production effect of Nf is shown in Table S1 (Supplementary Material).

**Figure 1.** Diagram of yield trends in response to the nitrogen gap (NG) change. Example for winter wheat (based on Grzebisz and Łukowiak [8]). Key: Yattmax—maximum attainable yield; Ya—actual

### yield; 1–16 are the field numbers. *1.2. Fertilizer Use Efficiency—FUE*

The term Fertilizer Use Efficiency—FUE is not new. It has been widely used for decades but has become widespread recently thanks to the use of the FUE indexes to assess the global productivity of NPK fertilizers [7,9]. The productivity of nutrients applied in fertilizers can be estimated by the same formula as shown in Equation (2) for fertilizer N. Another methodological way for FUE determination is to use a set of indices used in field experiments such as Apparent Nutrient Efficiency (ANeE) and/or Apparent Nutrient Recovery (ANuR):

$$\text{ANuE} = \frac{\text{Y}\_{\text{f}} - \text{Y}\_{\text{c}}}{\text{N}\_{\text{r}}} \tag{6}$$

$$\text{ANuR} = \frac{\text{Nu}\_{\text{f}} - \text{Nu}\_{\text{c}}}{\text{N}\_{\text{r}}} \tag{7}$$

where: ANuE—Apparent Nutrient Efficiency, kg yield kg−<sup>1</sup> nutrient applied; ANuR— Apparent Nutrient Recovery, %; Yf, Yc—yield on a plot with and without fertilizer, t or kg ha−1; Nr—the rate of a nutrient applied as fertilizer, kg or g ha−1; Nuf, Nuc —the uptake of a tested nutrient on a plot with and without fertilizer, kg, g ha<sup>−</sup>1.

The recorded values of ANuE and ANuR usually show a decreasing trend, with an increase in the rate of the nutrient applied as fertilizer, which is satisfactory for the researcher. Moreover, the values obtained have a tendency opposite to the soil fertility indexes for a given nutrient [7]. It simply means that FUE is highly dependent on the current soil fertility level, which the farmer needs to know. However, the main disadvantage of these two indices is that the farmer does not have a control plot to assess the actual nutrient productivity in the applied fertilizers. The values of the ANuR indices, evaluated on the global scale, are low and amount to 40–65% for N, 15–25% for P, and 30–50% for K used in fertilizers [9]. At this point it is necessary to pose the question, what is the main source of nutrients for the currently grown crop?

The productivity of nutrients taken up by the crop during one growing season can also be estimated by the partial nutrient balance (PNB) method:

$$\text{NuE} = \frac{\text{Nu}\_{\text{f}}}{\text{Nu}\_{\text{f}}} \times 100\% \tag{8}$$

where: NuE—Nutrient uptake Efficiency, kg kg−1; Nut—the uptake of a tested nutrient, kg or g ha<sup>−</sup>1; Nuf—the rate of a nutrient applied as fertilizer, kg, g ha−1.

The efficiency of N, P, and K using this method show much higher values or even a surplus of nutrients [10]. The low efficiency of nutrients using the differential methods, but high yield indirectly indicates that the main source of nutrients for crops grown in one growing season is soil [11].

The main problem is the assessment of the production role of nitrogen, which plants take in in two distinct inorganic forms, i.e., as nitrate (NO3 <sup>−</sup>1) and ammonium (NH4 +) [12]. Nitrates affect plant growth in many ways, inducing plant morphology, physiology through hormones and finally metabolism through their influence on the production of organic acids [13–15]. Plants fed with nitrates, compared to ammonium, show a high growth rate, which results in higher yields [16]. The above-identified aspects of the impact of N on plants are fully supported by field experiments and agricultural practice [17,18]. As shown in Figure 2, the yields of winter wheat grown on the control plot (non-fertilized) and on the plots fertilized with K, P in the same way since 1957, did not show large differences. The average yield for these three objects of 4.38 ± 0.14 t ha−1, can be considered as high. The primary reason for such a high yield, despite the lack of N fertilization, was alfalfa as a forecrop. The use of 90 kg N ha−<sup>1</sup> increased the yield by 1.94 t ha−1. The same level of yields was also recorded for the NP and NK plots. The lack of response to the P or K application clearly emphasizes the importance of these two nutrients for plant growth and yield. This conclusion was fully confirmed by the yield achieved on the NPK plot. Even more important is the fact that N use efficiency (NUE) increased by 10–13%, compared to incomplete fertilization treatments. The observed interaction was even more important for P use efficiency (PUE), which in the NPK plot increased by 9% and by 73% compared to NP and P treatments, respectively. The same trend was observed for potassium. The importance of the N × PK interaction on the productivity of Nf is observed for all crops, regardless of the world region [17,19,20]. The complex effect of N on plant growth and yielding clearly indicates the superior function of N in crop production. It can, therefore, be concluded that the production efficiency of nutrients, applied as mineral fertilizers, can be mainly evaluated through their impact on NUE. Thus, the search for indicators of productivity or efficiency for other nutrients is pointless. This is well presented in the analysis of the causes of the NG (Table S1).

**Figure 2.** Effect of long-term differentiated fertilization on yield of winter wheat, mean of 2005–2008 years (own projection based on Blecharczyk et al. [17]). Key: AC—absolute control; K, P, N—experimental trials since 1957; LSD0.05—Least Significant Difference; 0/0/0\*—respective values of nitrogen, phosphorus, and potassium use efficiency.

#### *1.3. Factors Affecting Fertilizer Use Efficiency*

Fertilizer use efficiency is the result of a series of interactions between plant genotype and environment, including both abiotic and biotic factors. Full recognition of these factors is the basis for proper fertilization of plants in farming practice, aimed at maximizing the FUE values. The soil is both the growth environment for plants and their main reservoir of water and nutrients. Hence, the impact of soil factors on nutrient uptake and FUE should be considered at the level of several groups of phenomena and processes (Figure 3).

**Figure 3.** Fertilizer Use Effectiveness (FUE) indices in response to soil physical and chemical properties and processes responsible for nutrient uptake: (**A**) release of nutrients from solid phase; (**B**) processes of nutrient transport from the soil to the root surface; (**C**) the plant's physiological response to conditions of nutrient supply; (**D**) processes of nutrient transportation to the plant shoot; (**E**) nutrient remobilization and transfer into grain/seeds. Blue arrows—transport processes; red arrows—influencing and feedback responses. FUE indices explanations: PFPNf —partial factor productivity of nitrogen; ANuE—apparent nutrient efficiency; NG—nitrogen gap; NRE—nitrogen remobilization efficiency; CNR—contribution of remobilized N to grain; ANuR—apparent nutrient recovery; NuE—nutrient uptake efficiency; PE—physiological N efficiency; Umin—minimum uptake of a nutrient for the maximum rate of plant growth.

In the first group (A) all of the factors, both abiotic and biotic, that lead to the release of nutrients from their solid phase in the soil to their solution phase should be analyzed. The next group of factors (B) is concerned with the processes of transporting nutrients from the soil to the root surface. The third group (C) of factors influencing FUE concerns plant responses manifested by changes in architecture and root growth rate. This group of factors, also related to plant activity, should consider the composition of the root exudates in the plant root—mycorrhizal system. For the assessment of the effectiveness of fertilizer application, the processes taking place in the plant itself, related to transport, assimilation in the aboveground mass (D), as well as remobilization of components and their transfer from the vegetative parts to the generative crop (E), are also important.

#### **2. Factors Affecting Nutrient Uptake**

#### *2.1. Plant Growth and Nutrient Requirement*

A major challenge for the farmer is to synchronize the crop plant requirement for nutrients with their supply from both soil and applied fertilizers. The term synchronization refers to the amount of a nutrient that must be taken up by the crop at a certain stage of its growth as a prerequisite for a development of yield components. The expected degree of a given yield component formation depends on the growth rate of the crop, which in turn depends on the supply of N. For example, the critical stage of yield formation by winter oilseed rape (WOSR) reveals itself at the phase of inflorescence development (BBCH 50–59; coding system of growth stages, abbreviation in German: Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie [21]). As shown in Figure 4, WOSR fertilized with N as ammonium nitrate (AN) in two equal rates of 80 kg N ha−<sup>1</sup> applied at BBCH 22 (spring restart of WOSR) and BBCH 30/31 reached the maximum growth rate (CGRmax, 20.4 g m−<sup>2</sup> day−1) at full flowering. This value was the prerequisite of both the highest yield and the lowest, in its year-to-year variation (coefficient of variation, CV of 5.6%).

**Figure 4.** Crop growth rate (CGR) of winter oilseed rape (WOSR) during the growing season as affected by nitrogen fertilizer (based on Barłóg and Grzebisz [22]). Key: CGR—crop growth rate, N–0—absolute control, N–80 + 80\*–N rate of 160 kg N ha−<sup>1</sup> applied at the onset of the growing season restart in Spring; \* ammonium nitrate; 30, 51, 62, 69, 79, 89—WOSR growth stages in BBCH scale.

For comparison, plants fertilized with the same N dose, but applied as calcium ammonium-nitrate (CAN), yielded on average at the same level, but showed much higher year-to-year variability. The main reason was a slightly lower CGRmax (19.1 g m−<sup>2</sup> day<sup>−</sup>1), resulting in a higher CV (16%). Moreover, plants fertilized with AN reached the maximum N accumulation at the full flowering stage (BBCH 65), while those fertilized with CAN much later, i.e., at the beginning of pod growth (BBCH 71). The observed delay was due to the excessive growth of secondary branches, which is not always coordinated with higher yield [23]. The lower yield on the N control plot was mainly due to a significantly lower rate of dry matter accumulation, which resulted in a much worse status of the yield components at maturity. The existing relationship between nutrient uptake by a plant and its growth rate can be summarized by the equation [24]:

$$\mathbf{U\_{min}} = \mathbf{C\_c} \times \frac{\mathbf{dW}}{\mathbf{dt}} \times \frac{1}{\mathbf{w}} \times \frac{\mathbf{W}}{2\pi \mathbf{rL}} \text{ or } \mathbf{U\_{min}} = \mathbf{C\_c} \times \text{RGR} \times \frac{\mathbf{W}}{2\pi \mathbf{rL}} \tag{9}$$

where: Umin—minimum uptake of a nutrient for the maximum rate of plant growth, g or kg plant−<sup>1</sup> or unit area; Cc—critical concentration of a nutrient in a plant, g, mg kg−<sup>1</sup> DW; W—aboveground biomass of a plant, g or kg DW; r—root diameter, mm or cm; L—root length, cm or m; 2πrL—root surface area, mm<sup>2</sup> or cm2 or m−2; dW dt <sup>×</sup> <sup>1</sup> <sup>W</sup>—the relative growth rate of a plant, RGR, g g−<sup>1</sup> t <sup>−</sup>1; t—time: day or year.

This equation clearly shows that the minimum amount of a given nutrient taken up by a plant over a specific period of time is necessary to maintain its critical concentration in plant tissues, determining the plant's optimum growth rate. In the numerator of the equation, apart from the nutrient concentration, is the plant biomass, determined by two factors, i.e., the period duration (t—time) and the root surface area, as the denominator.

The first challenge for the farmer in exploiting the yielding potential of the grown crop is to recognize the critical stage(s) of yield formation, or more precisely, the formation of yield components. Plant crop development is usually described on a 100-point scale (stages), divided into 10 phases [25]. Farmers need to know this scale to control the development of yield components. However, its use by the farmer for precise fertilization requires identifying those stages, which are crucial for the development of the main yield component. The degree of its development is closely related to the crop biomass, which is described by the sigmoid crop growth model [26]. The accumulation of crop biomass during the growing season, based on this model, shows variable growth rates in different phases, which fits with exponential, linear, quadratic or linear-plateau regression models (Figure 5). This trait can then be used to determine the three growth mega-phases of crops [8,27]:


**Figure 5.** A conceptual pattern of dry matter accumulation by a typical seed/grain crop. Key: CK1, CK2—cardinal stage 1 and 2, respectively [8].

The first mega-phase refers to all crops, but the last one only to seed plants. The intersection points of CFP and YFP as the first pair, and YFP and YRP as the second, termed as cardinal knots (CKs), are two crucial points of the crop yield development [8]. CK1 is the change point at which the crop changes its rate of dry matter accumulation from the exponential to the linear model [26]. CKs are used by farmers as diagnostic steps to assess the crop nutritional status. CK1 is a crucial point at which to correct the nutritional status of all crop plants, regardless of the species [28]. In the case of cereals, CK1 refers to the borderline of tillering and the beginning of the stem elongation phase (BBCH 29–31). For dicots, this cardinal knot is related to the rosette stage. A classic example is winter oilseed rape ([25]; Figure 6). The critical nutrient concentration specified at CK1 is important, mainly for correcting the N status of the currently grown plant. For most crops, CK1 is the date of the maximum relative growth rate (RGR) of the crop. A classic example is maize. As shown in Figure 7, maize reached the maximum RGR on the 48th day after sowing (BBCH 15 to 17) and then its value decreased with increasing maize biomass. This particular period of maize growth is associated with the appearance of inflorescences [29,30]. Thus, the date

when the plant reaches its maximum RGR defines the first cardinal phase of yield formation by the crop, i.e., CK1.

**Figure 6.** The Cardinal Stage 1 (CK1): winter wheat (monocot) (**a**) and winter oilseed rape (dicot) (**b**). Photos by W. Grzebisz.

**Figure 7.** Relative growth rate (RGR) of maize during the growing season in response to foliar zinc (Zn) application (based on Grzebisz et al. [31]—modified).

Moreover, as shown in Figure 7, the zinc (Zn) foliar treated maize maintained, more strictly extended the duration of the RGR peak. As a consequence of the prolonged biomass growth at BBCH 15–17, a second RGR peak, but much smaller, appeared during flowering. The yield increases due to zinc application before the CK1 resulted in a yield higher by 1.49 t ha<sup>−</sup>1. The partial factor of N productivity (PFPNf) increased from 66.7 to 79.3 kg grain per kg of Nf. The direct reason for the yield increase was the uptake of an N increase of 46.4 kg ha−<sup>1</sup> [31]. The given example clearly indicates that the use of macronutrient fertilizers requires the precise diagnosis of the critical phase (s) of yield formation by the crop.

The second cardinal phase (CK2) is very well-defined for seed crops. This stage proceeds the date of flowering (Figure 8). For some crops, their nutritional status at CK2 can be used to forecast the yield. A classic example is maize. The nutrient content at this stage in the cob leaf is used to indicate the nutritional status of maize and delivers a highly reliable yield prognosis [32,33]. The same rule is observed for winter oilseed rape. The content of nutrients in leaves at flowering can be used to forecast the seed yield [34]. This relationship explains the opinion of Schulte auf'm Erley et al. [21] on the importance of the inflorescence phase in winter oilseed rape for the yield. However, the latest that the N dressing can be conducted is at the rosette stage [35].

**Figure 8.** The Cardinal Stage 2 (CK2): winter rye (monocot) (**a**) and winter oilseed rape (dicot) (**b**). Photos by W. Grzebisz.

Nitrogen fertilization in cereals, to meet the requirements at CK2, should be conducted in the period between the date of the growth rate change (transition point) and flowering (Figure 5). In fact, in cereals, the last dose of N is applied at the end of the stem elongation phase. This phase precedes the period of the highest rate of ear growth, i.e., booting, which is responsible for the number of grains per unit area [36,37]. A separate case is bread wheat, where the last dose of N is used during the heading stage. The main goal is to increase the protein content in the grain [38].

A relevant and crucial component of nutritional crop status evaluation is a welldefined range of nutrient concentration in indicative plant parts and the relationships between them. Theoretically, there are some sophisticated methods for crop nutritional status assessment. The most commonly used are DRIS (Diagnosis and Recommendation Integrated System) and CND (Compositional Nutrient Diagnosis) [39,40]. In practice, farmers use, the sufficient ranges (SR) method to gain a quick evaluation of the crop nutritional status [41]. The biggest disadvantage of the SR method is the need for a large data set that is required for the calibration of the established ranges [42]. Moreover, most of the current ranges used by farmers were generated in the past for crops yielding at much lower levels than today. Table 1 compares the SRs for maize and sugar beet at CK1. The presented ranges, in spite of elaboration in different regions of the world (Europe, USA), differ only slightly. This suggests their suitability for world-wide application. It is much more difficult to make a reliable assessment of the nutritional status of sugar beets or potato (Table 1). For example, the Bergmann' sufficiency ranges developed at BBCH 41 for

sugar beet are not currently suitable for correcting the nutritional status of currently grown varieties. The last date of this crop fertilization with N must precede BBCH 33 [43,44].


**Table 1.** Sufficient ranges of key nutrient contents in crop plants at the first cardinal stage (CK1).

Maize has been subjected to in-depth studies on its nutritional status at the onset of flowering (Table 2). The presented ranges, despite different origin in terms of geographical region and publication year, differ only slightly. The biggest differences concern the content of Ca and K. The main reason for these variations is the calibration of plant tests under conditions of significant differences in the content of soil Ca and K in the area of the conducted research.

**Table 2.** Evaluation of maize nutritional status based on nutrient sufficiency ranges for the early leaf—the beginning of flowering—CK2.


<sup>1</sup> corrected by author.

#### *2.2. The Root System Architecture—RSA*

This section may be divided by subheadings. It should provide a concise and precise description of the experimental results, their interpretation, as well as the experimental conclusions that can be drawn. The uptake of nutrients related to the incorporation of ions or molecules into the plant's organism consists of a series of sequential processes that can be divided into three main ones:

	- a. transport of ions/molecules from the soil solution towards the root surface,
	- b. ingrowth of the root into soil patches rich in available nutrients;

The processes mentioned in points 2 and 3 are extensively described in scientific books and extended reviews [16,47]. Here, we discuss the key processes related to root system growth during the growing season. The functions of the root system of crop plants can be considered from several points of view [48–50]:

	- a. release of organic compounds → a source of energy for microorganisms present in the rhizosphere
	- b. release of protons or chelating agents → increase in nutrient availability
	- c. deposition of carbon by dead roots → humus build-up;

The root system, despite seasonal dynamics and spatial variability, is a conservative trait of the plant. It can be characterized as a three-dimensional structure, creating the root system architecture (RSA) [51,52]. The components that describe RSA include three main characteristics of the root system:


Generally, on the basis of the plant branching patterns, the root systems of crops, that are botanically justified, are classified as taproots (dicotyledonous species, dicots) and fibrous roots (monocotyledonous species, monocots). The main components of the taproot system are PR, LS, and AR roots. The fibrous root system consists of PR, seminal roots, crown roots and AR roots [53].

The spatial distribution of roots in the soil profile is important for both the current rate of crop growth, as a decisive factor for the uptake of water and nutrients, and for maintaining soil fertility due to allocation of carbon. The spatial arrangement of the root system in the soil profile, in spite of its heterogeneity, can be described by specific parameters or indices. This concerns, first of all, the general shape of the root system profile down to the soil. The key parameters are: (i) distribution of the total root biomass, (ii) plant rooting depth, (iii) root length density [48,54]. Root distribution with depth can be best described using, for example, an exponential model by Gerwitz and Page [55]:

$$\mathbf{Y} = \mathbf{A} \begin{pmatrix} 1 \ - \ \mathbf{e}^{-\mathbf{c}\mathbf{x}} \end{pmatrix} \tag{10}$$

where: Y—the cumulative fraction of roots between a soil layer of 0–10 cm and the depth x + 10 cm (cm); x—a defined soil layer below 0–10 cm; c—an empirical fitting parameter that determines the root distribution with depth.

This equation or others, more mathematically advanced, are used to define the effective rooting depth (ERD) as the key RSA parameter [56,57]. Most of the root biomass is present in the topsoil, decreasing exponentially with the soil depth. As estimated by Fan et al. [56] for main crops grown in a humid climate 50% of the root biomass is in the top 20 cm. The remainder part of roots, present in the subsoil, is important for water and nutrient uptake. Under conditions of drought, the uptake of water and nutrients from deeper soil layers is critical for both growth and yield maintenance [58]. The ERD is defined as the potential depth of the soil profile from which plant roots can extract the maximum amount of water available to plants from the soil during dry years. The soil layer, extending between the soil surface and the ERD, is known as the effective root zone (ERZ) [59]. This zone, depending on the assumption, covers 80% or even to 95% of the total root mass or root extent. As reported by Fan et al. [56], 50% of wheat root biomass is present within 16.8 cm of the soil surface layer, while 95% reaches down to 103.8 cm of the soil profile. In agricultural practice, the ERD is used to assess both the water resources for the currently

grown crop and/or the dose of irrigation water. For example, the ERZ in the Czech Republic is estimated at 80–100 cm for winter cereals, and at 40–50 cm for potatoes [60].

The role of the subsoil in plant growth and yielding is usually ignored in the diagnosis of crop plant fertilization. This ERD is, in fact, used as a routine diagnostic tool to determine the content of mineral nitrogen (Nmin). For most crops, this analysis is performed down to a depth of 90 cm [61]. Subsoil is an important storage of other nutrients, including P [62]. Current studies document that these P resources are used by plants, provided that the P balance in the topsoil is negative. This conclusion is probably the result of using powerful extractants to determine the available P [63]. A study by Barłóg et al. [64] clearly showed that extraction solution for Nmin determination can also be used to determine the resources of other nutrients. As shown in Figure 9, the seasonal pattern of available P (0.01 M CaCl2 extract; soil: solution ratio as 1:5), regardless of the season (crop), was stable. The P content was in a declining pattern in the soil profile. With the exception of 2005, its content was lower at crop maturity compared to spring. These P resources can be exploited by plants to up to 60% of its total content in the 0.9 m soil layer [65].

**Figure 9.** The seasonal patterns of available phosphorus distribution within soil layers (based on Łukowiak et al. [65]). Key: WW—winter wheat, OSR—oilseed rape. Letters indicate significant differences between treatments.

#### *2.3. Root System Growth during the Growing Season*

The genetically determined root system of plants is heterogeneous both in time and in soil space [48,66]. The first variable is inextricably linked with the plant's life cycle. Generally speaking, the growth of the root system as an integral part of the shoot system, is a result of both organs functional interdependences [67,68]. Maintaining a stable but temporary balance between the supply of water and nutrients to the shoot by the roots and the return supply of assimilates to the roots form the shoots is the basis that determines the plant growth rate, development of yield components, and yield [69].

The relationship between these two organs of the plant during its life cycle is not constant, as expressed by the ratio of the biomass of the shoot to the biomass of the root (S/R). Its value, as a rule, increases with plant growth (Figure 10). A frequently asked question concerns the relationship between shoot growth and the ability of the root system to supply the required amount of nitrogen [67]. In cereals, the highest rate of N uptake by roots occurs in the period from the end of tillering to the stage of full stem elongation (BBCH 29 to BBCH 37; Figure 6). For example, during this period, the rate of N uptake by winter rye plants on a plot fertilized with NPK and manure (long-term static experiment, existing 30 years before the study) was 3- and 10-fold faster compared to plants grown on a plot fertilized only with manure or on the absolute control [70]. Moreover, the rye root system on the NPK + manure plot was both shallower and more branched than on the absolute control [71]. This is in line with current studies on wheat, highlighting the importance of the early stages of stem elongation for the development of yield components [37]. Moreover, the period of the highest N uptake by winter rye confirms the well-defined CK1 (Figure 5).

**Figure 10.** The general pattern of the growth of the root and shoot biomass of cereals during the growing season (based on Grzebisz [70]). Legend: R/S—root to shoot biomass ratio.

The second variable affecting the RSA concerns the impact of soil and environmental conditions on the development of the root system during the growing season. The primary factor of root growth is temperature, which determines the rate of all metabolic and physiological processes during a plant's life cycle [12]. The optimum temperature for root growth is much lower for plants from temperate than tropical climates [69]. The second factor is water, the function of which, similarly to temperature, cannot be separated into individual processes [72]. The third factor is soil fertility, which determines the efficiency of water and nitrogen [5]. The effect of soil fertility on RSA depends on the course of temperature and water conditions during the growing season. Any change in the environmental conditions for the worse (temporary water shortage, lower level of soil fertility, low availability of nitrate nitrogen) increases the plant's input into the root system size, mainly increasing its rooting depth—the primary root and root hair length, while reducing the development of lateral roots. The observed morphological changes are due to the actions of hormones, which are dependent on the availability of nitrate nitrogen [73,74].

The maximum demand for nutrients by a plant, as shown in Figures 4 and 5, occurs during the linear phase of the biomass accumulation by the crop. Soil inherent (quasi natural) resources of nutrients can be potentially high, but the plant's nutrient requirements at the maximum growth are higher than their supply to the plant from soil solution [8]. The rate of any given nutrient movement in the soil solution towards the root surface depends, among others, on the value of its diffusion coefficient. In pure water, the differences between diffusion coefficients for nutrients are small compared to their values in the soil solution (Table 3). The coefficients for NH4 <sup>+</sup> and K+ are about 100-fold lower compared to the nitrate ion (NO3 −). An even lower value is the attribute of the orthophosphate ion. Moreover, the differences between the values of the diffusion coefficients for all these ions increase with the decrease in the water content in the soil [75].


**Table 3.** Coefficients of effective diffusion for main nutrients in water and soil solution 1.

<sup>1</sup> source: Raynaud and Leadley [76]; Clarkson [77].

The absorption of a given nutrient by the plant root results in a decrease in its concentration around the root. This phenomenon is called the depletion zone, which is specific for each individual nutrient [67]. The size of the nutrient depletion zone (NDZ) is determined by two key variables: (i) value of its diffusion coefficient (Deff); (ii) soil exploitation time by the root (t). The influence of both variables on NDZ can presented in the formula:

$$\text{NDZ} = \left(2 \times \text{D}\_{\text{eff}} \times \text{t}\right)^{1/2} \tag{11}$$

where: NDZ—the size of the depletion zone, cm; Deff—diffusion coefficient of a particular nutrient, cm2 s<sup>−</sup>1; t—time, s.

The NDZ arises when:


The uptake of nutrients during the Yield Formation Period (YFP) of plant growth depends on the rooting depth and the root length density (RLD, cm cm<sup>−</sup>3) of the growing crop. The effect of RLD on the size of NDZ is nutrient specific. The rate of nitrate nitrogen ion (NO3-N) movement to the root is the most rapid of any nutrient, resulting in the fastest increase in NDZ around the root. Competition between neighboring roots occurs when their density exceeds 1–3 cm cm−3. Maize with an RLD of 3 cm cm−<sup>3</sup> absorbs about 70% of NO3-N present in the soil solution. At the same time, the degree of P and K depletion does not exceed 5% and 10%, respectively [78]. Competition between the roots for P may occur, provided the RLD exceeds 30 cm cm−<sup>3</sup> [79]. The RLD for crop plants rarely exceeds 2–5 cm cm−3. The exception are grasses, for which this parameter is in the range of 3–20 cm cm−<sup>3</sup> [79]. An apparent paradox for both traits of RSA is that the greatest RLD values in the topsoil, regardless of the crop, decline exponentially with depth [67]. Current studies on winter wheat and winter oilseed rape have shown that the critical RLD of 1 cm cm−<sup>3</sup> was 32 and 45 cm, respectively [80]. These data indicate that there is no competition between roots for NO3-N below this depth. However, it can be assumed that the presence of roots in the deeper soil layers has a significant impact on the yield. As recently presented by Grzebisz et al. [35], the content of NO3-N in the soil layer (0.6–0.9 m) was the key nutritional factor that determined the yield of winter oilseed rape (WOSR). As shown in Figure 11, the greater the decrease in the NO3-N content during YFP, the greater the WOSR yield obtained. During YFP, the sequential application of Nf creates rich N-NO3 zones in the topsoil, while the deeper soil layers are, as a rule, much poorer in nitrate content. Nevertheless, no reduction in root growth is observed within this mega-phase, either in the topsoil or the subsoil [71,81]. The ingrowth of the primary root in the subsoil and the simultaneous growth of lateral roots in the rich NO3-N niches in the topsoil can be explained by the *foraging strategy* of a crop [54,82]. This phenomenon entails the synchronization of both the local and systemic signals within a plant in response to the NO3-N status in the soil profile. The decrease in concentration of NO3-N in the subsoil, which is a typical phenomenon during YFP, leads to the increased flow of auxin to the apex of the primary root. As a consequence, it stops the growth of lateral roots within a soil zone poor in nitrates. At the same time, the induced systematic signal released by the apex of the primary root results in a compensatory growth of lateral roots in soil zones rich

in nitrates [83]. The application of Nf by the farmer during the growing season leads to the formation of soil zones—*foraging patches* for a plant, which temporarily differ in the concentration of NO3-N. Therefore, it can be concluded that a split N fertilization system is a useful way to increase the efficiency of the applied Nf.

**Figure 11.** The amount of the soil and fertilizer N depleted during the Yield Formation Period (YFP) depending on nitrogen (Nf) rate. Key: High, Low yield of winter oilseed rape. (Based on Grzebisz et al. [35]).

#### **3. Soil Factors Affecting FUE**

*3.1. Soil Texture*

The most important soil physical properties include: soil texture, density, structure, porosity, consistence, temperature, air and color. Among them, soil texture is the basic physical feature that determines not only the other physical properties of the soil, but also the chemical ones [84]. The percentage and mineralogical composition of the smallest mineral fractions in the parent rock determines the primary soil potential to supply plants with nutrients, which is the function of weathering and transforming primary minerals [85]. In addition, the content of mineral colloids is positively correlated with soil organic matter (SOM), which in turn is a source of organic colloids, which have a great impact on the water retention of the soil, cation exchange capacity, erosion processes, as well as soil microbial activity [86]. SOM sequestration is achieved through various mechanisms which include the formation of clay-humic complexes, sorption of organic matter on clay particles, fixation of organic carbon in the crystal lattices of clays and the formation of organometallic compounds such as Ca, Fe and Al humates through humification processes [87,88]. In general, the greater the SOM concentration, the greater the sorption capacity of the soil, and potential for water retention in soil [89] and nutrients [90]. Numerous studies show that soils with a high proportion of clay particles have a higher content of nutrients than soils with a low content of nutrients, not only in terms of general forms, but also plantavailable forms [91,92]. At the same time, the clay content affects the fixation and de-fixation processes of some nutrients, especially K+ [91]. On the one hand, excessive fixation reduces the pool of mobile K<sup>+</sup> ions in the soil and reduces the use of potassium from fertilizers, especially in dry soil conditions. On the other hand, it prevents the leaching of potassium from the soil [93]. Moreover, adsorption and non-exchangeable ammonium nitrogen (NH4 +) fixation in soil is highly dependent on clay mineral composition [94]. Another problem with soil texture is water infiltration and the leaching of nitrates (NO3 −) resulting from ammonium nitrification. Coarser-textured soils are more susceptible to soil N loss following the leaching of NO3 −, and thus have potentially lower FUE values [64]. Furthermore, soil texture largely affects fertilizer and soil P transformations in soils. In coarser-textured soils the content of labile P fractions after adding phosphorus fertilizers is higher than in

clay and loam soils. Therefore, in these soils there is a high risk of P transfer from soil to water systems [95].

#### *3.2. Water Content*

One of the most important factors controlling nutrient uptake and utilization by plants is the water content of the soil. First of all, water determines the processes of nutrient release from the soil solid phase to the solution phase [96,97]. Water deficiency in soil negatively affects microbiological activity and the processes of mineralization/biological fixation [98]. Water is also essential for dissolving and releasing nutrients from mineral fertilizers, including controlled release fertilizer [99]. However, from the point of view of the process of uptake of nutrients by plants, two phenomena deserve special mention: mass flow and diffusion [100]. Water deficiency in the soil reduces the intensity of both processes, and thus leads to a reduction in the amount of nutrients flowing to the root surfaces [101]. In this aspect, the degree of plant reaction to water stress depends on the element and its function. According to Oliveira et al. [102], in maize the proportion of mass flow contribution to Ca, Mg, N, S and K transport was as follows: 100, 63, 56, 45 and 10%, respectively. This series clearly shows that the supply of plants with Ca and Mg may be severely limited in drought conditions, despite their relatively high concentration in the soil compared to other macronutrients [103]. Taking into account the diffusion processes, a water shortage in the soil will primarily limit the mobility of phosphate ions and micronutrients. Moreover, it will lead to the intensification of precipitation processes and the crystallization of amorphous compounds of phosphorus with other cations, depending on the pH [104]. As the water deficit in the soil increases, the proportion of pores filled with air increases, mechanical resistance increases, and the rate of root growth decreases. Under conditions of high soil oxygenation, the potential of the soil to supply plants with some micronutrients is reduced (Fe, Mn), whose higher oxidation state forms are less plant-available than the reduced forms [105]. The second group factors effecting NUE directly relates to the plant response (growth) and its ability to convert in biomass the assimilated/remobilized nutrients, especially nitrogen [106]. Water has a direct effect on root growth. In order to meet the demand for water, the roots constantly explore the soil, building a very complex, branched architecture [107]. An increase in the number of hairs and diameter root tips has been observed in plants under drought conditions. Root hairs greatly increase root-soil contact and the surface area available for adsorbing water and nutrients [108]. However, dense and deep root systems are not always good under all hydrological conditions, for example they poorly capture water from the topsoil under low rainfall conditions [109]. In drought conditions, the above-ground mass is reduced more than the underground mass, which in the case of a long-lasting drought may limit the inflow of assimilations and stop root growth, with all the negative effects of this phenomenon [110]. Lupini et al. [111] reported that water stress in durum wheat reduces the values of NUE, NUpE, and NUtE indices, regardless of the genotype. However, it should be remembered that excess water is just as harmful to plants as is its deficiency. One of the reasons for this is the reduction in the oxygen content in the soil needed for the respiration of plants and microorganisms [98]. In addition, large amounts of iron or manganese are released, which in excess may be toxic or interfere with the absorption of other nutrients. This phenomenon is particularly harmful in the cultivation of rice paddy on acidic soils [112].

#### *3.3. Soil Compaction*

Another important physical factor influencing nutrient uptake from soil, as well as their utilization from fertilizers, is soil compaction. Compaction affects plant growth by reducing the content of soil air and plant-available water, and the consequent restricted root growth results in the plant being unable to obtain an adequate amount of nutrients. Soil compaction can be assessed by measuring the following soil properties: bulk density, porosity and mechanical impedance [113]. Mechanical impedance is defined as a physical

barrier to developing roots as a result of excessive bulk density. In general, root growth rates decrease sharply for soil mechanical impedance values between 0.8 and 3 MPa. On the other hand, when assessing soil compaction by soil bulk density, most authors give the value of 1.47–1.85 g cm−<sup>3</sup> as critical for crops, depending on the percentage of clay [114,115]. The turgor in the cells in the elongation part of the roots determines their ability to overcome the mechanical resistance of the soil [116]. The greater it is, the greater the probability of root growth into the zone of compacted soil [117]. At the same time, root elongation is facilitated by root secretions and abraded side cells of the roots, which reduce the effect of the friction force [118]. When the mechanical resistance is too high, changes are observed at the physiological level (accumulation of solutes, reduction in the growth rate, new cell production) as well as anatomical (increase in the root diameter and the share of mechanical tissue in the direction of growth) [119,120]. The entire root system develops into less resistant parts of the soil, often forming a shallow system with the roots parallel to the soil surface [121]. According to Ramalingam et al. [122] the root length density at 30–60 cm soil depth decreased with hard compaction (to 70% of control) and increased with moderate compaction (to 135%). At the same time, the number of roots with a deep angle (i.e., 45◦ to 90◦ from the horizontal) correlated with the root length density and its proportion was lower in compacted soil. Considering the root architecture, the studies carried out so far have shown that deeper root growth is more important for N uptake than increased root density [123]. In this respect, it is necessary to remove the soil compaction in the subsoil. On arable land, the use of heavy machinery increases the risk of soil compaction especially in the subsoil [124]. Changes in the root architecture mean that the plant is unable to fully use nutrients, especially those whose main reservoirs are in deeper layers of soil [125]. Regardless of the soil depth, when the soil is characterized by excessive bulk density and/or mechanical impedance, the roots develop mainly in macro-pores [126]. This results in a poor supply of nutrients in plants under soil drought conditions, as the macro-pores in soil water retention only contribute to a small extent [98]. Another important issue with soil compaction is the loss of nitrogen from the soil through the emission of its gaseous forms into the atmosphere. As a result of soil compaction and the oxygen deficiency caused by this process, the activity of denitrifying bacteria increases and the production of N2O and N2 increases [127]. The emission of these gases to the atmosphere is favored by the low values of the parameters that define gas diffusivity in compacted soils [128]. According to Ruser et al. [129], high N2O emissions in compacted soils occurred at a water-filled pore space > 70%. N2 production took place only at the highest soil moisture level (>90% water-filled pore space) but it was considerably less than the N2O-N emission in the most compacted areas in a potato field. Soil compaction also increases the volatilization of ammonia, as compared to uncompacted soils [130]. However, for this gas, the emissions are mainly determined by other soil physical and chemical characteristics [131].

#### *3.4. Soil Temperature*

Temperature has a substantial effect on some soil properties as well as root growth. Important processes depend on the temperature of the soil, such as: soil structure, aggregate stability, soil moisture content and aeration, soil pH, cation exchange capacity (CEC), soil microbial activities and organic matter decomposition [132]. A soil temperature between 2–38 ◦C increases the decomposition of organic matter by stimulating microbial activities and increasing the solubility of chemical compounds [133]. As a result of decomposition, the resources of N, P, S and other nutrients available to plants increase [134]. From the point of view of the nutritional status of plants, an extremely important temperature-dependent process is the availability of P to plants. Soils with low temperature have low availability of P because the release of P from organic material is limited [135]. Soil temperature also influences the P diffusion coefficient in the soil. Yilvainio and Pettovuori [136] observed that water-soluble P increased with soil temperature from 50 to 250 ◦C due to the increase in the movement of P in soil controlled by diffusion. Soil temperature also affects nutrient uptake

by changing soil water viscosity and root nutrient transport. At low soil temperature, nutrient uptake by plants is reduced as a result of high soil water viscosity and low activity of root nutrient transport [137]. In general, low temperature decreases both root elongation and branching. However, low temperatures inhibit shoot growth more than root, leading to a high root/shoot dry matter ratio [138]. Vessel lignification can be delayed and axial hydraulic conductivity is higher in roots grown at low temperatures compared to high temperatures [139]. Thus, tomato, for example, showed that low soil temperature results in reduced root growth, tissue nutrient concentrations and, as a consequence, the amount of the component taken from the soil [140]. The unfavorable effect of higher temperature is marked in various ways. Too high a temperature may lower the CEC, and at the same time cause an increase in the concentration of hydrogen protons (increase in soil acidification) due to the high rate of soil organic matter decomposition. The plant's response to temperature changes depends not only on the plant species, but also on the content of nutrients in the soil. According to Xia et al. [141], negative effects of excessive temperature on P content and uptake occur especially in P-poor soils. The authors also found that an overly high root zone temperature reduced root vitality and plant phosphorus content, which in turn affected plant growth and light energy utilization efficiency.

#### *3.5. Soil Reaction*

Among a number of chemical parameters describing the chemical properties of soils, the use of nutrients from fertilizers is very much influenced by its pH [142]. This feature directly relates to the concentration of active H+ protons in aqueous solutions, and indirectly it is a measure of the acidity or alkalinity of a soil. The influence of soil pH on the nutrient uptake of plants results from many different phenomena and processes. The most important ones include: effecting the content of plant-available forms of nutrients in soil; capacity and proportions between cations in CEC; activity of trace elements and heavy metals; soil microbial activity, biological N2 fixation; emissions of ammonia and other gases from the soil [143,144]. Both too acidic and alkaline soils have a negative effect on nutrient uptake. However, the phenomena occurring in acidic and alkaline soils differ significantly in terms of processes contributing to their degradation. A significant problem of acidified soils is an increase in exchangeable aluminum (Al3+) [145]. The content of this form of aluminum monomers rapidly increases in soils below pH 5.0–5.5 ([146]; Figure 12). An excessive amount of Al3+ ions in the soil negatively affects the nutrient uptake processes and plant growth [147]. Numerous studies show that even at the stage of nutrient uptake, unfavorable phenomena take place, such as the competition of Al3+ ions with other ions for attachment sites in the apoplast, in carriers, attachment to the ATPase of cytoplasmic membranes and disruptions in the operation of the proton pump [148,149]. An excessive content of Al3+ ions in the soil significantly reduces the uptake of Mg2+ ions. This is due to the similar size of the hydrated ions [150]. One of the most important consequences of the presence of exchangeable aluminum in the soil is the disturbance of the growth and development of the root cap, and consequently the shortening of the root length and unfavorable changes in its structure [151]. For most crops, even a small concentration of exchangeable aluminum (in nanomoles) in the root cells is a toxic factor for the metabolic, physiological, genetic and biochemical processes taking place in the plant [152]. The reduction in the root system negatively affects the use of nitrogen in fertilizers and increases the risk of nitrate being washed out from the soil [153]. Moreover, nitrate nitrogen, which is not taken up by plants, is reduced to gaseous compounds, including N2O [154]. In highly acidic soils, apart from exchangeable aluminum, excessive amounts of manganese (Mn2+) and iron (Fe2+) can also appear, which can further disrupt the proper growth and development of plants [155].

**Figure 12.** Exchangeable aluminum (Al3+) content as a function of soil pH measured in suspension of 1 molar KCl (1:2.5, *w*/*v*). Sandy soils, western Poland (*n* = 986). The red lines indicate the critical points for soil pH and Al3+ content. Source: Błaszyk [146].

#### *3.6. Soil Salinity*

In arid or semi-arid climates, the problem is not soil acidification, but alkalization and salinity [156]. Under low rainfall conditions and a high evaporation rate, Na+ ions, as well as various soluble salts, accumulate in the soil. Their excessive accumulation contributes to the significant advantage of OH<sup>−</sup> ions over H+ and, consequently, to an increase in soil pH to the level of 9–10 [157]. Soil alkalinity can also be increased by the addition of water containing dissolved bicarbonates, especially when irrigating with high-bicarbonate water [158]. The low osmotic potential of water in saline soils adversely affects water absorption by plants and nutrient uptake [159]. Salinity of soil significantly decreases P uptake by plants because phosphate ions precipitate with Ca ions contained in saline soils [160]. However, the alkalinity of soils is most often associated with the Na concentration [161]. Alkaline soils are characterized by unfavorable physical conditions, low content of plant-available forms of microelements and phosphorus, components determining nitrogen metabolism in the plant. During nutrient uptake processes, Na+ ions compete for carriers with other nutrients in cationic form, in particular with K+ ions [162]. This is a negative phenomenon because Na, dissimilar to K, negatively affects the activity of plant enzymes [163]. The reduced uptake of K+ ions also means the insufficient or slower transport of NO3 − from the roots to the above-ground parts, and thus poor efficiency of N from fertilizers [164]. Furthermore, an excess of Cl− ions in the soil has a negative effect on NO3 − uptake. However, as recent studies show, optimal NO3 − vs. Cl− ratios become a useful tool to increase crop yield and quality, agricultural sustainability and reduce the negative ecological impact of NO3 − on the environment and on human health [165]. Under saline soil conditions, plants change their root architecture, which also has negative consequences for nutrient uptake [166].

#### *3.7. Soil Organic Matter*

The content of soil organic matter (SOC) in soil is one of the most important features influencing soil fertility [167]. Changes in SOC are associated mainly with changes in macronutrient contents, such as N, P and sulfur (S) which are chemically bound to carbon (C) in organic compounds [168]. Therefore, in systems where SOC content is declining, soil fertility declines over time and soils become increasingly dependent on the use of mineral fertilizers, especially nitrogen [169]. A total loss of organic N directly translates into a weaker potential of soils to release mineral forms that are taken up by plants. At the same time, under such conditions, the demand for N from fertilizers increases. Numerous experiences show that the most effective use of N from fertilizers is observed

in the small dose range [9,170]. Conventional tillage with plowing can reduce SOC stocks by 30–60% [168]. Changes in NUE resulting indirectly from the increase in the degree of SOC degradation are confirmed by research of Luis et al. [171]. The authors calculated that over many years the efficiency of nitrogen fertilization application decreased from 68% in 1961 to 47% in 2010. This means that the use of N from fertilizers deteriorated and N losses to the environment increased by 21%.

In general, the transformation of native soil to agricultural uses leads to a decline in SOC levels [172]. However, agricultural land uses do not always result in losses of SOC. The rate and direction of changes in the C content in soils depend on the soil use system, irrigation, crops, and the level of organic matter return to the soil [173,174]. Failure to plow or use various simplified systems leads to the accumulation of SOC, especially in topsoil [175]. Reduced tillage in comparison with ploughing increased SOC stocks in the surface layer (0–10/15 cm) by 20.8% or 3.8 t ha−1, depleted SOC stocks in the intermediate soil layers to 50 cm soil depth with a maximum depletion of 6.6% or 1.6 t ha−<sup>1</sup> in 15/20–30 cm and increased SOC stocks in the deepest (70–100 cm) soil layer by 14.4% or 2.5 t ha−<sup>1</sup> [176]. However, the use of natural and organic fertilizers is of greater practical importance in maintaining an appropriate SOC [177]. Szajdak et al. [178] reported that a yearly application of 30 t ha−<sup>1</sup> of manure to light soil over 38 years doubled the SOC content. The increase in plant biomass as a result of the use of NPK fertilizers leads to an increase in the influx of C to the soil. Nevertheless, accumulation of C in soil is not favored by an excess of N in the soil from high fertilizer application rates and/or low plant uptake can cause an increase in the mineralization of organic carbon which, in turn, leads to an increased loss of C from soils [179].

#### *3.8. Nutrient Shortage*

Factors responsible for nutrient deficiency in crops can be divided into two main groups: (i) causing an absolute deficiency of nutrients in soil, resulting from low nutrient contents in the parent soil material, low level of SOC, nutrient losses from the soil, e.g., Mg leaching, long-term unbalanced crop fertilization practice neglecting nutrient depletion in soils through crop nutrient removal; (ii) causing an induced deficiency, resulting from factors that disturb the flow of nutrients to the root such as: improper moisture and temperature of soil, ion competition, factors responsible for root system size, etc. [12]. The natural source of most nutrients in the soil are primary and secondary minerals. As a result of weathering, often stimulated by the activity of living organisms, potentially available nutrients are released into the environment. Their reactions in soil and fate in the environment depend on the type of element. Some nutrients are strongly absorbed in the soil, others are easily lost (by leaching or emission). The first group includes K. The ions of this element can be absorbed in the soil in an exchangeable and non-exchangeable form [180]. The second type of adsorption prevents the elution of K<sup>+</sup> ions from soil, but on the other hand this leads to a reduction in the potential to supply plants with K. This phenomenon is responsible for the poor efficiency of K from fertilizers on soils rich in mineral colloids. The strength of the non-exchangeable K ion fixation increases in dry years, which further aggravates the symptoms of water stress [181]. Non-exchangeable adsorption may also apply to other cations, e.g., Mg. However, in relation to Mg, the degree of soil moisture has a greater practical importance, as this element is assimilated by plants as a result of a mechanism known as mass flow. Contrary to K, Mg is less readily absorbed [103]. This is one of the reasons for the relatively easy leaching of Mg from the soil. An absolute deficiency of K and Mg leads to a poor efficiency of N, as both elements greatly affect the metabolism and transport of N in plants [16]. Studies conducted on sugar beet show that Mg applied to the soil significantly increases the agronomic efficiency of N, but in the range of low doses of N (Figure 13). This indicates that an excess of nutrients in the soil may not lead to better FUE/NUE values. Phosphorus and micronutrient deficiencies in the soil are often the result of an inappropriate pH range in the soil. In an acidic reaction, the adsorption of P on iron and aluminum compounds increases, while in an alkaline pH, insoluble calcium phosphates precipitate in the soil [104]. An inappropriate soil pH also influences, directly or indirectly, the content of plant-available forms of K, Mg and Ca [144]. Thus, in order to restore the optimal conditions for the uptake of nutrients, it is necessary to regulate and/or constantly control the soil pH. If this does not help, then one option is to enrich the soil with nutrients to eliminate their absolute deficiency, or to support the plants by foliar fertilization.

**Figure 13.** Effect of nitrogen application (40, 80, 120, 160 and 200 kg N ha−1) on the agronomic efficiency of nitrogen (AEN), calculated for white sugar yield of sugar beet, depending on the availability of magnesium in the soil—kieserite application at a rate of 24 kg Mg ha<sup>−</sup>1. Mean for two years for sandy soil (**a**) and loamy soil (**b**). Source: Pogłodzi ´nski et al. [182].

#### **4. Innovations on the Fertilizer Market**

Innovations in the fertilizer market involve two main areas of research activity. The first one concerns the process of obtaining raw materials and the production of fertilizers. The production of fertilizers, especially nitrogen ones, is energy-intensive and is a significant source of greenhouse gases. In this context, two strategies for the production of ammonia are considered: blue hydrogen—steam methane reforming with carbon capture and storage (CCS) and green hydrogen—electrolysis of water, to generate hydrogen and oxygen in a process driven by sustainable energy [183]. The second area of fertilizer production, mainly aimed at improving NUE indicators, concerns a number of application aspects and the chemical composition of fertilizers. Research shows that about 40–70% of N, 80–90% P and 50–70% of K from fertilizers is lost to the environment and cannot be used by plants, thus posing a threat to the environment [184]. For many years, the fertilizer industry has been improving and introducing Slow-Release Fertilizers (SRF) and Controlled-Release Fertilizers (CRF) [185].

The advantages of nitrogen fertilizers from the SRF and CRF groups derive from the following features: (i) they ensure a good supply of nitrogen to plants, especially in critical phases; (ii) they reduce the number of application rates; (iii) they reduce the nitrate content in plants; (iv) they limit nitrogen losses and reduce its negative impact on the environment [186,187]. With regards to nitrogen fertilizers from the SRF group, the delay of action is achieved by the formation of slightly soluble compounds, most often polymers based on urea and aldehydes, e.g., formaldehyde [188]. The condensation products of urea and other compounds can be used as solid (e.g., ureaform) or liquid fertilizers (e.g., urea-triazone). Research shows that liquid slow-release nitrogen fertilizer increases yields and nitrogen use efficiencies (NUE) in rape plants compared with a standard urea fertilizer [189]. For the production of CRF fertilizers, highly water-soluble compounds are used. Dissimilar to SRFs, controlled-release fertilizers (CRFs) are less influenced by soil temperature or texture, and they are not so dependent on soil microbiology [190]. The effect of delaying N release is achieved by covering the granules with a different type of protective layer (e.g., sulfur coatings, polystyrene, polyethylene, polyurethane, polysulfone resin and waxes coatings, siloxanes, etc.) [191–195]. The protective layers prevent the inflow of water from the soil to the inside of the granules and the dissolution of the contained compounds. The positive effects of different coated urea fertilizers on crop yield and NUE have been observed by many authors [196–198]. Recently, a great deal of attention has been paid to fertilizers using biochar and lignite for coatings, as they allow for the cheap production of CRF fertilizers [186]. Additionally, carbon-based materials, which contain humic acids act on plants such as biostimulants. The results of Wen et al. [199] also suggest that biochar-based slow-release nitrogen fertilizers could significantly improve the water-holding and waterretention capacity of soil. As a result, on the field scale, in rice cultivation, the optimal dose of N in the form of CRF (coated with lignosulfonates) fertilizer was 20% compared to using traditional nitrogen fertilizer [200]. In turn, according to Ghafoor et al. [198], biochar-based CRF fertilizers effectively reduce the nitrogen-release rate (69.8% of nitrogen was released after 30 days) and possess low nitrogen-leaching-loss amounts (10.3%), low nitrogen migrate-to-surface-loss amounts (7.4%), and high nitrogen-use efficiency (64.27%), as compared to other N fertilizers, consequently effectively promoting cotton plant growth. According to Guo et al. [201] fertilization of maize with CRF fertilizer with the addition of humic acids allows not only an increase in NUE, but also significantly reduces the emission of N2O from the soil to the atmosphere by 29.1–32.6% compared to CRF fertilizer without humic acids. For the production of CRF fertilizers, nitrogen stabilizers are also used: urease and nitrification [185]. Among the various urease inhibitors, the most commonly used are N-(n-Butyl) thiophosphoric triamide (NBPT) and N-(n-propyl) thiophosphoric triamide (NPPT). The most commonly applied nitrification inhibitors are: 2-chloro-6-(trichloromethyl) pyridine (nitrapyrin), dicyandiamide (DCD) and 3,4-dimethylpyrazole phosphate (DMPP). The literature shows that the application of these inhibitors has considerably reduced inorganic N leaching, N2, NO and N2O emission while at the same time improving crop yield and N use efficiency [202,203] However, their effect on yield is very variable and depends on many factors. The application of fertilizer with urease inhibitors can increase the content of ammonium nitrogen in the soil by 10–59% compared to treatments without these inhibitors [204]. According to some researchers, it may increase the N resources in the soil and, consequently, gas losses of N (NH3, N2O) from the soil [205]. Therefore, the combined application of urease inhibitors with nitrification inhibitors reduces multiple losses associated with volatilization and denitrification [206]. Urea with urease and nitrification inhibitors can be used simultaneously to improve the N uptake, seed yield and grain protein contents, for example in quinoa [207]. Meta-analysis by Yang et al. [208]. showed that among the popular nitrification inhibitors, DCD was more effective than DMPP on increasing plant productivity. An increase in crop yield by DMPP was generally only observed in alkaline soil. This is confirmed by the results of Alonso-Ayuso et al. [209], who on soil with a pH of around 8.0 obtained after DMPP application allowed a 23% reduction in the fertilizer rate without decreasing maize yield and grain quality.

With respect to physical characteristics, in recent years urea has been produced with larger granules, facilitating mixing with fertilizers of similar grain size and bulk density, and allowing a wider spreading width compared to traditionally granulated urea. This is especially suitable for the fertilization of rice [210].

Innovations in the phosphorus fertilizer market also include the production of fertilizers with a controlled phosphorus release rate (CRFs). Their use increases the efficiency of using P from fertilizers (PUE) compared to traditional phosphorus fertilizers, and at the same time they reduce the negative impact of fertilization on the environment [191,211]. The rate of phosphorus release from fertilizers depends on a number of factors, including type and thickness of coating material, soil temperature and pH, humidity and microbial activity [193,212]. According to Fertahi et al. [213], 3 days after the application of phosphorus

fertilizers, 100% P was released from water-soluble triple superphosphate (TSP) granular fertilizers, and only 60% from biopolymer coated TSPi. Next, Barbosa et al. [214] reported that biochar-based phosphate fertilizers have potential as a support material to increase the availability and efficiency of N use by plants. It should be mentioned that phosphorus fertilizers with a controlled phosphorus release rate also include: partially acidulated phosphoric (PAPR) and thermophosphates [215,216]. Stabilization of phosphorus transformations in the soil, and thus an increase in the potential P uptake from fertilizers, can be achieved by adding chemicals, the so-called phosphate boosters [217]. Their task is to decrease P-adsorption in soil and increase soluble-P from applied fertilizer-P [218]. Another solution for the future increase in PUE may be the addition of solubilizing bacteria [219]. In the foliar fertilizer market, fertilizers containing P in the form of phosphonates are now available. They have a beneficial effect not only on the nutritional status of plants, but also on their tolerance and resistance to fungal parasites [220].

The introduction of amino acids or other organic compounds of a biostimulating nature to the composition of fertilizers has also been a breakthrough in the foliar nutrition of plants. Amino acid molecules, distinct from technical salts or synthetic chelates, are electrically neutral, therefore the assimilation time of nutrients from fertilizers is short and their use will improve the nutrient use efficiency compared to traditional foliar fertilizers [221–223]. Glutamic acid has a particularly strong complexing effect [224]. On the other hand, some ammonium acids show a typical biostimulating character; for example, tryptophan, which is an auxin precursor. As demonstrated by Gondek et al. [225], NPKS soil fertilizer with the addition of thryptophan increased the maize biomass and the use of N and S from the fertilizer by 27% and 17%, respectively, compared to fertilizer without an amino acid. The incorporation of various organic and mineral substances into the soil together with fertilizers is an important way to improve the efficiency of using nutrients from fertilizers. As reported by Palanivell et al. [218], clinoptilolite zeolite application could contribute to an improved use of nitrogen, phosphorus, and potassium fertilizers to prevent soil, air, and water pollution. This treatment also improved nitrogen, phosphorus, and potassium use efficiency. The use of slow-release fertilizer hydrogels (SRFH) is also of interest. SRFHs are a combination of a super absorbent hydrogel (SAH) and a fertilizer with both water retention and slow-release properties [226]. Polymer super-absorbents are macromolecular compounds capable of absorbing water or physiological fluids in amounts much greater than their mass. They can be added to the soil or to fertilizers [227,228]. Among other things, chitosan-based hydrogels can be used as an additive to fertilizers [229].

The application of nanotechnology to the development of new types of fertilizers is considered to be one of the most promising options to significantly increase global plant production without negatively affecting the environment [230]. According to the European Commission [231], "Nanomaterial" means a natural, randomly generated or manufactured material containing particles in a free state or in the form of an aggregate or agglomerate in which at least 50% or more of the particles in the numerical particle size distribution have one or more dimensions in the range of 1 nm–100 nm. Nanoparticles are 100 to 1000 times larger than the size of the individual ions of nutrients that are involved in biochemical reactions [232]. However, they are in dimensions similar to or smaller than a number of anaotomous structures of plant tissues, e.g., plasmodesmata, cell wall pore sizes, or stomates [233]. Therefore, the presence of nanoparticles in foliar fertilizers improves the bioavailability of nutrients due to the nano-size, large specific surface area and greater reactivity of the compounds [234]. Fertilizers applied to the soil create the possibility that particles in the "nano" size may not be easily fixed between sheets of secondary minerals, and so not easily leached away from the soil [235]. The advantages of nanofertilizers also include the application of nutrients in a relatively smaller amount, ultimately reducing the cost of transport and at the same time improving the ease of application [236]. Nanofertilizers are usually divided into three groups: (i) classic fertilizer, but containing nano-scale particles; (ii) classic, traditional fertilizers with the addition of fertilizers in the form of nanoparticles; (iii) nanoscale coating fertilizer, referring to nutrients encapsulated

by nanofilms or intercalated into nanoscale pores of a host material [237]. The nanocarriers used in the last group, such as zeolites, chitosan, clay and other nanomaterials, can provide plants with an even release of macronutrients during vegetation, which in the case of nitrogen and phosphorus improves their use in fertilizers [238,239]. Currently, the market of foliar fertilizers is developing intensively, which, apart from traditional compounds containing microelements, also contain noble metals, in particular silver ions, showing specific properties as pesticides on the "nano" scale [233,240]. Despite the large amount of literature on the potential use of nanofertilizers, there is little credible scientific evidence to demonstrate their advantage over traditional fertilizers. According to Kottegoda et al. [241] application of urea-coated hydroxyapatite nanohybrids (HA–urea) results in the enhancement of nitrogen use efficiency and reduces the environmental impacts of rice cultivation. Raguraj et al. [242] reported an increase in tea yield by 10–17%, while reducing the urea dose by 50% compared to traditional urea. Li et al. [243] reported that application of P in the formulation of nanoscale hydroxyapatite (nHA) had beneficial effects on soybean P and Ca content upon high precipitation intensities. However, the authors did not record any significant difference in the effect of fertilizers on the soybean biomass. A meta-analysis by Kah et al. [244] found that the median efficacy gain of nanofertilizers over conventional fertilizers was 19, 18 and 29% for categories of macronutrients, micronutrients and nanomaterials acting as carriers for macronutrients, respectively. However, Kopittke et al. [245] are critical of these results. The authors note that numerous researchers describe the positive aspects of nanofertilizers, but the experiments often lack an appropriate control object that would allow an objective assessment of their effects on plants. In terms of the potential use of nanofertilizers in the future, carbon nanotubes (e.g., consisting of 60 atoms of C-fullarens), which may contain nutrients, mainly microelements, or other bioactive compounds, are of interest [230,235,246]. As a result of such a formulation, future nanofertilizers will fully meet the criteria of CRF fertilizers.

#### **5. FUE—A Message for Agricultural Practice**

The stagnation in the increase in the crop yields is well-documented [247,248]. Despite considerable progress in breeding and the continual release of new varieties, the real improvement in NUE is small [249]. The challenge for the farmer to exploit the yield potential of the grown variety is:

	- a. growth and architecture of the root system
	- b. water and nutrient availability;

The effective control of the set of factors indicated above is crucial to optimizing NUE. The general formula can be written as:

$$\text{NUE} = \frac{\text{Nitrogen Ferritzer Rate}}{\text{growth factors}} \tag{12}$$

The denominator includes all growth factors that determine the plant's uptake and utilization available N present in the soil-plant system during the growing season. The fractional value of all these factors, excluding N, should be ≤1.0 [5,8]. If the fractional value of a given growth factor approaches 1.0, its negative impact on NUE decreases and vice versa. The main challenge for the farmer in using Nf efficiently is to mitigate, or rather eliminate, the cause that leads to its fractional value drop below 1.0. Insufficient recognition of this

value, and worse, the lack of action to control its value, is the main reason for low NUE both on the farm and worldwide [250,251].

The numerator of this equation is not the first but the second step in an effective control of the Nf use efficiency. The amount of Nf applied must meet at plant's requirement for N to exploit its yield potential, taking into account both the stage of growth and the spatial variability in plant N status [252]. The effective determination of the amount of Nf requires the use of appropriate diagnostic tools. The first dose of Nf, regardless of the crop, must be based on the content of Nmin in the effective rooting depth of the currently cultivated plant [61]. A comprehensive view of the nutritional status of a plant in its full vegetation should be based on data on the content of both Nmin and other nutrients in the soil [64]. The control of the plant nutritional status during the growing season, in fact, is limited to N. The chemometric diagnostic tools are good, but their use is limited. These methods are time-consuming and because of the delay between the sampling time and the delivery of the data to the farmer, they do not show the real condition of the plant N status. Real-time data can be obtained by using remote sensing techniques [253,254]. These methods rely on the absorption and reflection of solar radiation by a plant canopy. From this property of the plant, a number of crop characteristics can be determined in real time, such as (i) plant biomass, (ii) leaf area index, (iii) nitrogen content, (iv) chlorophyll content [255]. Biometric and nutritional data obtained at the cardinal stages of plant growth, combined with the required sum of the physiological effective temperatures at a given stage, form the basis for determining the crop growth rate. These data are used to forecast a plant's demand for N in strictly defined stages of its development. This is the basis for determining the appropriate dose of Nf. The spatial differences in the values of the field spectral indices can be used to develop a zonal map, showing the temporary crop N status. These maps are the basis for the application of Nf according to a plant's requirements in a well-defined field area [36,256].

#### **6. Conclusions**

The production efficiency of all nutrients, applied as mineral fertilizers, can be evaluated mainly through their impact on nitrogen use efficiency (NUE). The effectiveness of nitrogen present in the soil/plant system depends on the degree of correction of soil factors limiting plant growth and nitrogen uptake at critical stages of yield formation by the currently cultivated plant by other fertilizers, including lime. There are a number of soil factors that limit nitrogen uptake and reduce NUE indices. Some of them can be easily controlled by the farmer, for example soil compaction, pH, organic matter as well as content of plant-available nutrients that improve metabolism and the use of N by plants. Moreover, regardless of the crop, an N dose must be based on the soil content of Nmin in the effective rooting depth and/or plant nutrition status at critical growth stages. Improvement of the parameters characterizing FUE/NUE parameters can also be achieved through the proper selection and use of innovative fertilizers. In recent years, slow- and controlled-release fertilizers produced with the use of biochar, lignite or other carbon-containing organic compounds have been of particular interest. In addition to the standard advantages of this type of fertilizer, a positive effect on the physical and chemical properties of the soil, as well as the growth of the root system can be achieved. Nanofertilizers are a new, promising direction of fertilizer development. Of particular interest is the possibility of using fullarens as nutrients carriers. Unfortunately, a reliable assessment of nanofertilizers is limited by a relatively small amount of data from field trials. Summing up, it is worth noting that regardless of the solution used to improve the NUE indicators, each action has a positive effect on the biogeochemical cycle of biogenic elements, and at the same time can help to protect the environment and reduce fertilization costs.

**Supplementary Materials:** The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/plants11141855/s1, Table S1: A detailed analysis and evaluation of agronomic factors responsible for nitrogen gap (NG).

**Author Contributions:** Conceptualization, P.B. and W.G.; methodology, P.B. and R.Ł.; software, R.Ł.; validation, P.B, W.G. and R.Ł.; formal analysis, P.B. and W.G.; investigation, P.B., W.G. and R.Ł.; resources, P.B. and W.G.; data curation, P.B.; writing—original draft preparation, P.B. and W.G.; writing—review and editing, P.B. and W.G.; visualization, P.B. and R.Ł.; supervision, P.B. and W.G.; project administration, P.B. and W.G. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** The authors would like to thank the editor and reviewers for their valuable comments and suggestions, which substantially improved the manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


**Przemysław Barłóg 1,\*, Remigiusz Łukowiak <sup>1</sup> and Lukáš Hlisnikovský <sup>2</sup>**


**Abstract:** Increasing the efficiency of nitrogen use (NUE) from mineral fertilizers is one of the most important priorities of modern agriculture. The objectives of the present study were to assess the role of different nitrogen (N), phosphorus (P) and sulfur (S) rates on maize grain yield (GY), crop residue biomass, NUE indices, N concentration in plants during the growing season, N management indices and to select the most suitable set of NUE indicators. The following factors were tested: band application of di-ammonium phosphate and ammonium sulphate mixture (NPS fertilizer at rates 0, 8.7, 17.4, 26.2 kg ha−<sup>1</sup> of P) and different total N rates (0, 60, 120, 180 kg ha−<sup>1</sup> of N). In each year of the study, a clear trend of increased GY after NP(S) band application was observed. A particularly positive influence of that factor was confirmed at the lowest level of N fertilization. On average, the highest GY values were obtained for N2P3 and N3P1 treatments. The total N uptake and NUE indices also increased after the band application. In addition, a trend of improved N remobilization efficiency and the N contribution of remobilized N to grain as a result of band application of NP(S) was observed. Among various NUE indices, internal N utilization efficiency (IE) exhibited the strongest, yet negative, correlation with GY, whereas IE was a function of the N harvest index.

**Keywords:** agronomic efficiency; nitrogen gap; nitrogen remobilization efficiency; partial factor productivity; plant nutrient diagnosis; starter fertilization

#### **1. Introduction**

Maize is one of the most important crops in the world. Among all cereals, it ranks second in terms of cultivated area (197 million hectares), just behind wheat (216 million hectares). Nevertheless, its global production between 2018 and 2020 was 1137 million tonnes, which was approximately 50% higher than the production of wheat [1]. According to the forecast, the global maize area in 2030 will expand even more (+5%), and the average yield, due to improving technology and cultivation practices, will increase by 10% [2]. In Poland, maize is also one of the dominant species. The area of maize grown for grain is about 1.0 million hectares, and maize for silage covers approximately 0.68 million hectares [3]. The yielding potentials of modern grain crop varieties are 11.6–12.8 t ha−<sup>1</sup> [4]. In agricultural reality, however, they are lower (7.0–7.5 t ha−1) and constitute about 60% of the breeding potential. There are many reasons for this state of affairs, one of which is inadequate agro-technology, a low level of fertilization and an imbalance of minerals.

The main factor determining photosynthesis, dry matter distribution and water efficiency is the concentration of soil available nitrogen (Nmin) as well as the running N fertilization [5,6]. Unfortunately, the recovery of N from applied fertilizers (Nf) ranged from 30 to 50% only [7]. The part of Nf that is not consumed by the currently grown crop undergoes numerous processes that result in its loss to neighboring ecosystems, including both water and air [8,9]. Crop genetic improvements along with agronomic attempts to

**Citation:** Barłóg, P.; Łukowiak, R.; Hlisnikovský, L. Band Phosphorus and Sulfur Fertilization as Drivers of Efficient Management of Nitrogen of Maize (*Zea mays* L.). *Plants* **2022**, *11*, 1660. https://doi.org/10.3390/ plants11131660

Academic Editor: Dimitris L. Bouranis

Received: 20 May 2022 Accepted: 20 June 2022 Published: 23 June 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

take control of N management in agriculture comprise a set of different strategies, which, in fact, focus on the increase in nitrogen use efficiency (NUE) [10–12].

At the beginning of plant growth, standard broadcast fertilization does not always ensure proper plant nutrition because, depending on soil properties, part of the component introduced into the soil in the form of fertilizer will land in places that are beyond the range of crop roots [13]. An alternative fertilization method is to place the fertilizer in close proximity to the seeds. This type of fertilizer application, also referred to as fertilizer placement, band application or initial, significantly accelerates the growth of maize and improves the plants' nutritional status at the beginning of the growing season [14]. This is due to both the increased concentration of minerals in close proximity of developing seedlings and the shaping of root architecture by N and P in particular [15–17]. In addition, this method of nitrogen application places the nutrient in a deeper, wetter soil layer, resulting in improved N uptake and limited N losses out to the environment [18]. Consequently, band placement not only prompts yield growth but also increases the values of NUE indices [17,19]. In general, fertilizer placement leads to an increase in maize yield in comparison to broadcast irrespective of the N fertilizer type [20]. Nevertheless, the use of ammonium phosphate proves to be the most productive of methods [21–23]. Despite numerous scientific findings on the beneficial impact of band application on maize yield and NUE, the N ratio still poses a problem and is little recognized, especially in conditions of high N demand. Apart from the many advantages of band fertilization, sprouting plants may become damaged, particularly when high rates of N fertilizers are used, where N comes in the form of NH4-N [24].

Another problem associated with improving the use of N from fertilizers is the correct balance of nutrients. In temperate climate conditions, phosphorus (P) is of particular importance in maize cultivation. The initial growth of maize is slow; the root system is poorly developed, which causes low uptake of nutrients, including nitrogen, and at the same time, periodic temperature drops in the spring cause disruptions in phosphorus uptake and metabolism [13]. In addition, phosphate ion absorption and/or even the formation of insoluble compounds occur in soils, leading to poor use of phosphorus from broadcast fertilizers [25,26]. The risk of insufficient absorption of phosphorus in the spring by young maize plants can be mitigated by early application of the so-called starter fertilization [22,23]. Some authors recommend using this method on soils low in P and/or those with factors that hinder its uptake [27]. However, as research indicates, even in conditions where soil is rich in phosphorus, band application positively affects the grain yield of cereal crops [28]. Some authors also point out that on alkaline soils, the effect of ammonium phosphates on the maize dry matter and the use of P from fertilizers depend on their chemical composition, i.e., the N:P ratio [29]. Thus, a fertilizer containing diammonium phosphate (DAP) with additional sulfur (S) seems interesting and worth investigating. The results of this study suggest that early season growth of maize in some areas of the USA may benefit from S fertilizer application [30]. Most often, the assessment of the effect of ammonium phosphates on nitrogen management is carried out in the phase of physiological maturity of the plant. However, this assessment is an ex-post analysis and allows only for a determination of the sources of the component necessary during the period of growth and pouring of seeds/kernels.

A standard NUE assessment uses partial factor productivity (PNF), agronomic efficiency (AE) and apparent N recovery efficiency (RE) indices [31]. In the author's own study, a relatively new index was also tested, called the nitrogen gap (Ngap), in an attempt to determine its viability in the NUE assessment in specific field experiments [32]. The value of the Ngap indicates the pool of nitrogen not used in crop formation, resulting either from external (e.g., dry soil) or internal (e.g., imbalance of components) factors. After flowering, the role of soil nitrogen in grain yield formation diminishes, and the importance of N remobilized from green parts increases [5,33]. Therefore, in order to fully understand the impact of phosphorus fertilization on the uptake and use of N from fertilizers, it is also necessary to take into account the growth stages preceding the maturation of plants. The character of

nitrogen management can be assessed by using indicators such as nitrogen remobilization efficiency (NRE) and contribution of remobilized N to grain N content (CNR) [34]. In this research, a hypothesis was formulated that the above-mentioned indicators remain in close relation with the grain yield and nitrogen accumulation in key points of maize growth, i.e., in the sixth–seventh leaf stage and at the beginning of flowering. Furthermore, the research hypothesis states that band application of DAP with added S improves NUE and prompts the reduction in the total N rate. This assumption was based on the following facts: low mobility of P in acidic soil, the specific demand of maize for P in the initial phase of growth and the stimulating effect of S on the metabolism of N compounds [22].

The objectives of the present study were: (i) to determine the maize yield-forming reaction to increasing rates of nitrogen fertilization in comparison to various rates of band application of NP(S); (ii) to evaluate the effect of NP(S) fertilization on the nutritional condition of maize at the seventh leaf stage, beginning of flowering and technological maturity; (iii) to establish the correlation between the level of maize yield, NUE indices and nutrient content with respect to the interaction of N and P(S) fertilizations.

#### **2. Results**

#### *2.1. Grain Yield and Crop Residue Biomass*

The average grain yield (GY) in both years (2019–2020) was at a similar level of 8.45 and 8.00 t ha−1, respectively. The difference was 5.6%. The higher grain yield in the first year resulted from better weather and soil conditions at the start of the growing season—a damp spring and a high concentration of mineral nitrogen in soil. Unfortunately, in 2019, during intensive maize growth, kernel silking and at the beginning of kernel pouring, in June and July, weather conditions were unfavorable for the formation of the basic elements of the crop structure (Supplementary Materials, Table S1). Later precipitation only increased the dry matter of the vegetative parts, whereas in 2020, summer precipitation did not limit the silking and pouring of kernels. Consequently, the yield of post-harvest residue in 2019 (10.2 t ha<sup>−</sup>1) was considerably higher (by 34.2%) than in 2020 (*F*1,78 = 44.9; *p* < 0.001).

In the given years, no significant statistical differences between the fertilization treatments were confirmed. However, in each year of the study, a clear and unequivocal trend of increased GY after NP(S) band application was observed (Supplementary Materials, Figure S1). A particularly positive impact of this type of N application was confirmed at the lowest level of nitrogen fertilization (N1). At that level, the greatest GY was obtained after an application of the highest rate of NPS (N1P3 treatment). In 2019, the difference in relation to the absolute control (N0P0) was 22.5%, and in 2020, 24.3%. At N2, high increases in GY were also observed after the application of the highest NP(S) rate (N2P3). For N3, the differences in the years were transparent. In 2019, higher rates of ammonium phosphate lowered GY. In 2020, the highest increase in GY was obtained for the N3P3 treatment. In relation to the control, the difference was 31.8%. For comparison reasons, the maximum growth of GY in the treatment without NPS, but with the highest rate of total N, was only 16.4%.

The analysis of variance showed a significant impact of the fertilizing factor on the mean values of GY for the two years (Figure 1a). Significant differences were recorded between the control (N0P0) and N2P3 and N3P1. Regardless of the N rates (without taking N0P0 into consideration), an average influence of the ammonium phosphate and ammonium sulphate mixture on GY was as follows: P0 (7.82) < P1 (8.10) < P2 (8.54) < P3 (8.81 t ha<sup>−</sup>1). Meanwhile, the impact of total N rates on GY was as follows: N1 (8.00) < N2 (8.33) < N3 (8.62 t ha<sup>−</sup>1). In the above series, GY growth as a result of the maximum NP(S) application rate was 12.7%, and the total nitrogen rate was 7.8%.

**Figure 1.** Maize grain yield, GY (**a**) and crop residues biomass, SDM (**b**) depending on fertilization treatments. Two-year average values. Means within a column followed by the same letter indicate a lack of significant difference between the fertilized treatments (HSD test). Hatched bars represent 2 × SEM ranges.

The studied factor did not differentiate the dry matter of post-harvest residue—straw yield (SDM)—in any significant way. However, fertilization clearly increased the dry matter of the vegetative parts. In both years, AP application had a positive effect on SDM, especially in N1 and N2 treatments. A difference between the years was registered for the N3 treatment. In the first year (2019), the higher rate of AP did not stimulate SDM at the same level as in 2020 (Figure S1).

On average, over the two years of study, the highest increase in SDM was obtained for N1P3, N2P2 and N2P3 treatments (Figure 1b). The difference in SDM between the nitrogen control (N0 = 7.23 t ha−1) and the highest rate of total nitrogen (N3 = 9.00 t ha−1) was approximately 24.5%, while the difference between the phosphorus control (P0 = 7.93 t ha<sup>−</sup>1) and P3 treatment (9.22 t ha−1) was approximately 16.3%. Despite this, these differences were not significant.

The biological maize yield (the sum of GY and SDM) also increased as the rates of N and P became higher, regardless of the year (Figure S1). In 2019, the highest biological yield was obtained under the N1P3 treatment, and in 2020, under N3P3.

The studied factor did not exert any major impact on the harvest index (HI). As opposed to GY and SDM, no clear trend was observed in terms of the general effect of fertilization. The parameter for N0P0 was 46.9% and 54.6%, depending on the year, whereas the maize fertilized with N and P showed HI values ranging from 41.0% (N2P2) to 49.5% (N3P2) in the first year, and from 49.7% (N2P2) to 54.7% (N3P0) in the following year.

#### *2.2. Nitrogen Concentration and Accumulation at Maturity*

The nitrogen content in maize significantly depended on the growing season, fertilization treatment and the studied part of the plant (Table 1). In the first year (2019), the N content in grain and in straw was higher than in 2020. At the same time, the accumulation of total N was also considerably higher in 2019 (269.9 kg ha<sup>−</sup>1) than in 2020 (216.9 kg N ha−1). The nitrogen harvest index (NHI) was, in turn, lower in 2019 (55.2%) than in 2020 (60.9%).

The studied factor notably influenced the content of N in grain (Ng) and in crop residues (Ns) in each year (Table S2). On average, for the two years of study, the greatest content of N in grain was registered for the treatment with the maximum fertilization rate of N and P (N3P3). The use of band application of DAP caused a particular increase in Ng at the level of N1. A similar interrelation was also obtained for Ns (Table 2). As a result of the fertilization impact on N concentration in grain and in crop residues, as well as on dry matter of the earlier mentioned maize parts, real differences in the accumulation of total N (TN) were recorded. A significant increase in TN in comparison to the control (N0P0) was registered in the following treatments: N1P3, N2P2, N2P3, N3P2 and N3P3. Depending on the treatment, the difference was 51.0–56.8%.

**Table 1.** Nitrogen (N) concentration and accumulation in maize at maturity (harvest) depending on fertilization treatments.


\*\*\*, \*\*, \* significant at *p* < 0.001, *p* < 0.01, *p* < 0.05, respectively; n.s.—non-significant; means within a column followed by the same letter indicate a lack of significant difference between the fertilized treatments (HSD test).

The average impact of P(S) rates on TN over the two years was as follows: P0 (228.2) < P1 (237.2) < P2 (257.2) < P3 (274.3 kg ha−1). For comparison reasons, the effect of the N rates was as follows: N1 (8.00) < N2 (8.33) < N3 (8.62 t ha−1). The maximum difference for NPS rates was 20.2%, and for the full rate of N, it was 7.8%. The NHI values were not significantly differentiated by the application of NPS fertilization. The study did not prove any notable influence of "year × NP(S) treatments" interaction on the content or accumulation of nitrogen.

#### *2.3. Nitrogen Use Efficiency Indices*

The values for nitrogen fertilization efficiency indices are shown in Table 2. It is clear that the NP(S) treatments had a significant effect on indices such as PFP, PNB, RE, IE and Ngap. For comparison purposes, the growing season considerably influenced such indices as PNB, IE and Ngap. The studies did not confirm any great impact of "year × NP(S) treatments" on the values of the above-mentioned indices, however. In relation to PFP and Ngap, it was the total N fertilization that played the vital role. Higher N rates lowered PFP, yet increased Ngap. NP(S) fertilization brought the values of PFP up, regardless of the N fertilization levels (except for the N3P3 treatment). In relation to Ngap, a reverse interdependence was obtained. Along with the P increase, the Ngap value became lower.


**Table 2.** Nitrogen use efficiency (NUE) indices depending on fertilization treatment.

\*\*\*, \* significant at *p* < 0.001, *p* < 0.05, respectively; n.s.—non-significant; means within a column followed by the same letter indicate a lack of significant difference between the fertilized treatments (HSD test). PFP—partial factor productivity of N; AE—agronomic efficiency of N; PNB—partial N balance; RE—apparent N recovery efficiency; IE—internal N utilization efficiency; Ngap—N gap.

Negative Ngap values for N1 prove that N deficiency ensures a maximum yield and, at the same time, potential N soil mining, whereas for N3 and N2, the positive index values confirm the surplus of N that was not transformed into GY. The agronomic efficiency of N (AE) rose as the P rate increased. The highest AE value was obtained for the N1P3 treatment. Moreover, PNB and RE values were the highest for N1P3. The lowest values of both indices were obtained for N3, without a concomitant use of NPS. At the same time, the highest IE value was recorded in the control, while the lowest values were obtained for N2P2 and N3P3 treatments. Out of all the N and P fertilization treatments, the best use of TN was obtained for N1P0 and N1P3. Physiological N efficiency (PE) varied significantly among treatments. It is, however, worth mentioning that the lowest values were registered for the treatments without phosphorus (N1P0 and N2P0). Principal component analysis (PCA) was used to determine the relationships between the GY and NUE indices. The correlation matrix can be found in the Supplementary Materials (Table S3). The results of the PCA procedure were visualized in biplots (Figure 2). In addition, the interdependencies of the properties were analyzed with Pearson correlation coefficients (Table S4).

Based on the PCA analysis, three main components, representing the GY, SDM, N content and NUE indices, accounted for 89.9% of the total variance. The first principal component (PC1) explained 39.4% of the total variability, and the next two components (PC2 and PC3), respectively, 34.6% and 18.8% of the total variance (Table S3). As the two first principal components dominated, the results of the PCA analysis are presented on the PC1–PC2 biplot. PC1 consisted of variables related to the SDM, TN, RE and IE, as well as the GY and NHI. The loading exerted by PFP, Ngap and PNB influenced PC2. As shown in Figure 2, the GY was significantly related to the TN, IE, NHI and SDM. However, the GY showed negative relationships with the IE and NHI. This resulted from the fact that, in 2019, maize developed a greater biomass of crop residues than in 2020, thus lowering the share of N accumulated in grain (NHI) and N utilization efficiency (IE). The second group of parameters consists of such indices as RE, AE, PE, PNB, PFP and Ngap. A particularly strong correlation was noted between PFP and Ngap parameters. The year and fertilization treatments modified the values of the investigated parameters, as demonstrated by both PCA biplots. On the PC1–PC2 biplot axes, most of the treatments were grouped closest to the Tukey median (in the bagplot) or in the bagplot cover region. Only two treatments (N3P0 in 2020 and N1P3 in 2019) were separated by a significant distance from the Tukey median. At the same time, both variants were on the opposite side of the axis representing such indices as SDM, RE and NHI. On the axis representing NUE indices on the opposite sides of the median were variants from the N3 group and variants from the N1 group but with phosphorus at the rates of P2 and P3, while on the axis representing GY, on its opposite side, treatments such as N1P0, N1P1 (2020) and N2P2, N3P3 (2019) were placed. Close to the axis but near the Tukey median, treatments such as N2P2 and N3P3 from 2020 were found.

**Figure 2.** Principal component analysis (PCA) biplot of the maize yield and N use efficiency indices. The dark blue square denotes the Tukey median, the blue square is the bagplot, the light blue square is the bagplot cover. Key: GY—grain yield; SDM—crop residues (straw) biomass; TN—total N accumulation; NHI—N harvest index; PFP—partial factor productivity of N; AE—agronomic efficiency of N; PNB—partial N balance; RE—apparent N recovery efficiency; IE—internal N utilization efficiency; Ngap—N gap. The treatments in 2019 are marked in red and the treatments in 2020 in black.

#### *2.4. Nitrogen Status of Maize*

The nutritional assessment was carried out in the seventh leaf stage and at the beginning of flowering. The growing season had a significant impact on the maize dry matter in the first term, as well as on its N content (Table 3). No significant interaction was found for "year × fertilization treatments". Greater dry matter (DM) was obtained in the first year, however, with a slightly lower N content. As a result, N accumulation in plants in 2019 was higher than in 2020.


**Table 3.** Effect of the growing season and fertilization treatments on maize dry matter (DM) and nitrogen (N) status at the seventh leaf stage and at the beginning of flowering.

\*\*\*, \*\*, \* significant at *p* < 0.001, *p* < 0.01, *p* < 0.05, respectively; n.s.—non-significant; means within a column followed by the same letter indicate a lack of significant difference between the fertilized treatments (HSD test).

In general, NP(S) application improved maize nutritional status in terms of N content. However, these changes were not statistically significant. The differences in comparison to the control were particularly visible at N1, while for N3, the differences in N content were inconclusive (Table S2).

As opposed to the first term, at the beginning of flowering, fertilization significantly differentiated N accumulation in plants (Figure 3). Both N and P fertilization increased the content of N in plants. For N1, along with the NP(S) rate increase, N accumulation rose by 13.3%. For N2, the maximum accumulation of N was recorded for treatments with P1 and P2 rates, while for N3, the highest N accumulation was registered after an application of the highest NPS rate, i.e., P3. The differences between N accumulation for P0 and other treatments were approx. 12–13%.

**Figure 3.** Content of nitrogen (N) in maize at the beginning of flowering depending on fertilization treatments. Two-year average values. Means within a column followed by the same letter indicate a lack of significant difference between the fertilized treatments (HSD test). Hatched bars represent 2 × SEM ranges.

#### *2.5. Dry Matter and N Remobilization Indices*

The effect of fertilization on the average values of indices describing the management of dry matter and N after flowering is shown in Table 4. The analysis of the growing season shows that the DMI and NI indices were higher in 2019 than in 2020. At the same time, a reverse interdependence was confirmed in relation to other indices. The values of DMR, DMRE and CDMR indices were negative in the first year of the study. In 2020, the values of the indices were positive. Such correlation resulted from a high growth of vegetative maize parts after flowering. In contrast to DM, the NI and NR indices were positive regardless of the year. NRE and CNR index values also confirm that nitrogen accumulated more in the green plant parts than in grain. The fertilization factor, however, had no significant impact on their values, nor did it exert any real influence in either year of the study. Nevertheless, some real trends emerged worth describing in terms of plants' reaction to the growing season and the NP(S) fertilization (Table S5). In this reference, as a result of the NP(S) application, the value index of NRE increased for N1 but only continued to grow up to the rate of P2. At the higher levels of nitrogen fertilization, the highest values were obtained in the treatments with a lower rate of P (N2P1) or without band application (N3P0), whereas the values of the CNR index were the highest for N1P0, N2P1, N3P0. The lowest CNR values were obtained in the N1P3, N2P3 and N3P1 treatments but without significant differences among treatments.

**Table 4.** Effect of the growing season and fertilization treatments on maize dry matter (DM) and nitrogen (N) management indices.


\*\*\*, \* significant at *p* < 0.001, *p* < 0.05, respectively; n.s.—non-significant; means within a column followed by the same letter indicate a lack of significant difference between the fertilized treatments (HSD test). DMI—dry matter increase; DMR—dry matter remobilization; NI—nitrogen increase; NR—nitrogen remobilization; DMRE—dry matter remobilization efficiency; CDMR—contribution of DMR assimilates to grain; NRE—N remobilization efficiency; CNR—contribution of remobilized N to grain N content.

In order to determine the interdependencies of the studied factors with the grain yield or the dry matter of the vegetative parts, a PCA analysis was carried out. Consequently, three factors were obtained, which, in combination, explained 94.6% of the total variance (Table S6). However, the first two, PC1 and PC2, explained 62.3% and 20.6% of the variance, which is equal to 82.9% of the total. Therefore, PC1 and PC2 were used to explain the interrelation between the analyzed parameters and the impact of the individual fertilization treatments on the axes representing particular variances (Figure 4). The indices of N nutrient management (CNR, NRE) were significantly, in a positive way, correlated with the DMRE and CDMR indices. The indices correlated more with GY than with DMRE and CDMR. The last two indices, however, negatively correlated with the content of N in plants at the flowering growth stage. That particular parameter, in turn, positively correlated with the dry matter of post-harvest residue and, interestingly, with the plants' dry matter at the seventh leaf stage. The values of correlation coefficients between the various features are included in the materials (Table S7).

The PCA biplot indicates the dominant impact of the seasonal factor on the axes arrangement of the interrelations mentioned above (Figure 4). As the analysis shows, most treatments were grouped near the Tukey median. Along the GY axis, quite a distance from the median, the following treatments were placed: control (N0P0) in 2019 and 2020, and the N1P0 treatment in 2020. On the opposite side of the median, the points representing different treatments were more scattered on both sides of the GY axis and, at the same time, the treatments creating clusters were more determined by the growing season than the fertilizer rate. On the left-hand side of the GY axis, therefore, for the high GY values, the treatments representing high fertilizer rates in 2020 were present (N2P2, N3P2, N3P3). For the lower GY values, on the right-hand side of the axis, various treatments from 2019 appeared, such as N2P1, N2P2 and N3P3. This result emphasizes the role of the growing season in the modification of the interdependencies among the treatments.

**Figure 4.** Principal component analysis (PCA) biplot of the maize yield, N content and accumulation, and N management indices. The dark blue square denotes the Tukey median, the blue square is the bagplot, the light blue square is the bagplot cover. Key: GY—grain yield; SDM—crop residues (straw) biomass; TN—total N accumulation; DM1—dry matter of plant at seventh leaf growth stage; N*c*1—N concentration at seventh leaf growth stage; N*a*1—N accumulation at seventh leaf growth stage; DM2—dry matter of plant at flowering; N*c*2—N concentration at flowering; N*a*1—N accumulation at flowering; DMRE—dry matter remobilization efficiency; CDMR—contribution of DMR assimilates to grain; NRE—N remobilization efficiency; CNR—contribution of remobilized N to grain N content. The treatments in 2019 are marked in red and the treatments in 2020 in black.

#### **3. Discussion**

The study reveals a lack of a significant impact of the growing season on grain yield. Maize requires between 500 to 800 mm of water depending on the environment [35]. In both growing seasons, the precipitation was approximately 250–300 mm. Taking into consideration the low water retention of the sandy soil and its water demand of 500 mm, it can be assumed that in the years of the study, water deficiency reached about 200–250 mm, and a potential grain yield loss could have reached 4–5 t ha−<sup>1</sup> [36]. The stages of maize susceptible to water stress are the vegetative and reproductive stages, where yield loss may be as high as 18.6–26.2% and 41.6–46.6%, respectively [37]. The least favorable weather conditions during flowering were recorded in 2020. They were, however, compensated by heavy precipitation during the grain filling stage, whereas in 2019, the drought in June and early July occurred during the most intensive period for the plant. The negative effect of the drought on GY at that stage is manifested mainly in the reduction in plant height, leaf size and delay in leaf tip emergence [38]. Nevertheless, the drought may have also had a negative impact on the tasseling growth stage and successful pollination. As a result, GY was slightly higher in 2019 than in 2020.

A considerable difference was, however, recorded in the dry matter of post-harvest residues, as the vegetative growth was stimulated by heavy precipitation in 2019. Additionally, a high content of Nmin in the soil in 2019 largely stimulated the development of vegetative biomass. Bearing in mind the variable weather and soil conditions, the influence of N and P(S) fertilization on the maize yield was quite similar over the years of the study; no statistically significant interaction was recorded. Nonetheless, at a higher level of nitrogen fertilization (N3 = 180 kg ha−<sup>1</sup> of N), the degree of plant reaction to the band application of NPS depended on the year. In 2019, the yield-forming impact of the factor on GY and SDM was lower than in 2020, which resulted from a variable Nmin content in the soil. The optimal N rate in maize cultivation depends on many factors. The most important ones include: soil type, the course of weather, water availability, Nmin content in soil, as well as the time and method of nitrogen application [12,39,40]. According to the literature, N fertilization greatly increases GY, most often within the rate range of up to 120–220 kg ha−<sup>1</sup> N [41–44]. Research carried out in northern China showed that the economically optimal N rate may be considerably higher and depend on the soil type [45]. According to the authors, it was 265 kg ha−<sup>1</sup> of N in black soil, while in aeolian sandy soil, it was 186 kg N ha−1. Ahmad et al. [46] point out that N applied to the soil in excessive amounts disturbs plant maturation and diminishes GY. In our own studies, the influence of the N rate on GY significantly depended on the ammonium phosphate fertilization level. On average, for the 2 years, the highest GY increase in comparison to the control was obtained for N2P3 (120 kg ha−<sup>1</sup> of N) and N3P2 (180 kg ha−<sup>1</sup> of N). It should, however, be emphasized that only slightly lower yield in comparison to the above-mentioned treatments was obtained for N1P3 (60 kg ha−<sup>1</sup> of N). The difference was only 1.5–1.6%. Concurrently, the result indicates the dominant yield-forming impact of localized placement of NPS in comparison to the broadcast fertilization of N. In the present study, the optimal P rate depended on the level of N fertilization. For N1, the ideal rate was 26.2 kg ha−<sup>1</sup> of P. For comparison purposes, during the broadcast application of P, the optimal rate in maize cultivation may reach even up to 100 kg ha−<sup>1</sup> of P [47]. However, it should be stressed that the impact assessment of a single element P on maize in a ternary fertilizer mixture (N+P+S) is very difficult. Moreover, the fertilizer also included zinc (Zn). Both S and Zn have a positive effect on the uptake and metabolism of N in early growth, and consequently, on maize yielding [30,48]. The study hypothesis states, however, that the main components modifying the level of maize yielding and NUE indices are N and P. The hypothesis was based on the proven role of NH4 <sup>+</sup> and PO4 <sup>−</sup><sup>3</sup> ions in root formation, N uptake and, as a result, maize yield. The plants react much better to N in the form of di-ammonium phosphate (DAP) than to N with ammonium nitrate and urea applied, either before sowing, as fertilizer placement at sowing or at the fifth/sixth leaf growth stage [17,20,22]. Additionally, according to Weiß et al. [23], the starter fertilization DAP increases GY to a greater extent than a simultaneous application of triple superphosphate and ammonium nitrate. The result clearly indicates a synergistic effect of NH4 <sup>+</sup> and PO4 <sup>−</sup><sup>3</sup> ions. It is physically impossible to isolate the N or P effects in a binary fertilizer. The synergistic impact of N and P applied as DAP results from both specific transformations of NH4 <sup>+</sup> and PO4 <sup>−</sup><sup>3</sup> ions in soil, as well as their influence on root morphology [20]. Both ions feature low effective diffusion coefficients in soils [49]. The NH4 <sup>+</sup> ions readily bind to negative charges on the surface of clay minerals and become fixed [50], while PO4 <sup>−</sup><sup>3</sup> ions are readily fixed by adsorption to aluminum and other metal hydroxides or are precipitated depending on the pH as Fe-, Aland Ca-phosphates [51]. According to Bordoli and Mallarino [27], P increased GY only in very low or low soil testing, and there was no response to P on any site. In our own study, despite high P concentration in the soil, P application may have had a positive impact on the maize yield, as the soil pH was acidic (5.2–5.3), and chemical sorption of P could have taken place [52]. Unlike broadcast fertilization, with or without soil incorporation, banding application reduces the surface area of contact with soil, thereby reducing PO4 −3 immobilization by fixation to various cations. Moreover, both ions stimulate the initiation and elongation of lateral roots on the part of the root system that is within or close to their

respective nutrient depots, which is caused by the accumulation of the plant hormone auxin [53,54]. N and P also have a positive effect on root growth in soil zones distant from the nutrient patch [16]. In order to obtain a maximum maize yield, an early supply of adequate amounts of phosphorus to the plants is crucial [13]. Placing a NP mineral fertilizer near the maize seeds leads to a higher plant-available P concentration in the soil, greater uptake by plants and a higher unit production [15,22].

The content of nitrogen in the grain and in the post-harvest residue was higher in 2019 than in 2020. The result can be directly associated with the difference of Nmin concentration in the soil. Fertilization treatments also exerted a great impact on the N content in grain. However, the experiment did not confirm any significant interrelation between the two factors. The average N content in grain was 17.9 and 16.3 g kg−<sup>1</sup> of DM, depending on the year. According to Tenorio et al. [55], the grain of maize cultivated in the northcentral region of the USA ranged from 7.6 to 16.6 g kg<sup>−</sup>1. Therefore, the N concentration obtained can be considered as being in the optimal range for maize grain. In addition, this level of Ng indicates a high efficiency of the soil (even on the control) as well as fertilization treatments. The high efficiency of N accumulation in grain was assured by high concentration of K and Mg in the soil [56]. Along with the N and P(S) rates, the N concentration increased, reaching the maximum value for the N3P3 treatment. The highest accumulation of TN (276.0 kg ha−<sup>1</sup> of N) was also obtained for this treatment. It resulted from the stimulation of the highest NPS rates, N uptake and dry matter accumulation as a consequence of N absorption of solar radiation during plant maturation [57]. As Figure 3 shows, GY was positively correlated with TN. The regression equation for this correlation is as follows:

$$\text{GY} = 4.7591 + 0.0142 \times \text{TN}; \text{R}^2 = 0.72; p < 0.001; n = 26\tag{1}$$

In order to assess the efficiency of nitrogen fertilization (NUE), several standard indices were used: partial factor productivity (PFP), agronomic efficiency (AE), partial N balance (PNB), apparent N recovery efficiency (RE), internal N utilization efficiency (IE) and physiological N efficiency (PE). Additionally, a relatively new index was chosen—nitrogen gap (Ngap)—indicating potential yield losses as a result of imbalanced fertilization [32]. Among them, PFP, RE, IE and Ngap were considerably differentiated by fertilization factors. The values of the first three indices decreased as the N rate became lower. It is a general rule that the indices are higher with a low N rate [58]. PFP is a simple production efficiency expression, calculated in units of crop yield per unit of N applied. The advantage of PFP over others results from its sensitivity both to the course of weather and experimental factors. As the literature shows, the PFP values in maize cultivation for grain stay within the range of 6.1 and 114.9 kg kg−<sup>1</sup> [14,44,59–61]. Thus, the PFP are within the above-mentioned range, yet they remain quite high. The result confirms the high productivity of the applied nitrogen. The experiment proved that PFP increased as the amount of NPS incorporated into the soil became higher and/or as the N share in the starter rate was greater. The differences were not significant but nevertheless clear for N1 and N2, while for N3, the differences were the smallest, clearly indicating the productivity decrease in high NPS rates when the maximum N rates were used. The other indices closely associated with the N rate—PNB and RE—point to the same trend. The expression of plant N content per unit of fertilizer N applied (PNB) indicates that, for N1, the maize effectively took advantage of the soil resources (the values were higher than 1). For N3, in turn, excessive N fertilization was recorded, expressed through values lower than 1 [62]. Regardless of the fertilization level, N exhibited a positive impact of NPS on the PNB values. With regard to RE, the index values for maize are, on average, 24.3–58.2% N [6,45,61]. Dhakal et al. [44] reported that the mean RE was 70% at the lowest N rate (60 kg ha−<sup>1</sup> of N) compared to 50% at the highest N rate (240 kg ha−<sup>1</sup> of N). The index is often used, as it measures the accumulation of the component in soil and/or the potential N losses to the environment [7]. In the present study, RE values were approximately 76.4% in 2019 and 60.8% in 2020. On average, for N1, N2 and N3, the index was 94.3, 63.7 and 47.7%. The use of NPS increased RE at every treatment level (and, at the same time, lowered potential losses of N to the environment), especially for the N1 treatment. For N1P3, the average value was >100%. The result can also be explained through the soil mining of N. A full confirmation of the hypothesis comes from the Ngap index. At the level of N1, negative values of Ngap were obtained and decreased along with the NPS rate. For N2 and N3, the positive values indicate the excess of N, which is the nitrogen not fully used by the plant. In the experiments, the AE index was also used to evaluate NUE. It reflects more closely the direct production impact of an applied fertilizer. Despite the fact that no statistically significant differences were obtained, a strong and clear trend of improving the index through the band application of NPS was noted. The trend was particularly transparent for N1 and then for N2. Typical AE levels of N for maize range from 1.9 to 29.0 kg grain kg−<sup>1</sup> N [6,44,59,61,63]. Unlike this index, IE differentiated substantially between N and P(S) treatments. On average, over the two years of the study, lower values were recorded for N2P2 and N3P3 than for the control or for N1P0. The result indicates that 1 kg of uptaken nitrogen was more effective in terms of yield forming when NPS was being simultaneously applied. In summary, we can conclude that a shortage of P during the early growth stages results in a GY decrease, in turn negatively affecting NUE indices. The advanced procedure of NUE indices evaluation relies on the degree of their sensitivity to indicators of maize GY and N status at harvest. The PCA analysis revealed a number of interesting interrelations among the studied features. GY was positively correlated with TN, NHI and the NUE—IE index. The reliance of GY on IE and IE on NHI is described through the following equations:

$$\text{GY} = 12.004 - 0.1094 \times \text{IE}; \text{R}^2 = 0.42; p < 0.001; n = 26\tag{2}$$

$$\text{IE} = -10.845 + 0.7819 \times \text{NHI}; \text{R}^2 = 0.55; p < 0.001; n = 26\tag{3}$$

The increase in IE is associated with an increase in NHI, which in turn was associated with a higher N translocation efficiency in later stages of the grain filling period [31,60]. In our experiment, the NPS rate increase did not lead to the improvement of NHI. The plant response to this type of fertilization depended on the level of N fertilization.

The effect of applied fertilization treatments on NUE can be considered on many different levels. There are two stages that deserve special attention: (i) N uptake and accumulation in plants; (ii) remobilization of N from vegetative to generative parts. During the first stage, a phase of intense N accumulation in plants can be distinguished. It starts right after the sixth/seventh leaf growth stage and lasts until the beginning of maize flowering [64]. The optimal N content in maize at the sixth/seventh leaf growth stage ranges from 3.5 to 5.0 g kg−<sup>1</sup> [65]. In our own study, the N content was therefore within the optimal range. Maize fertilized with NPS showed a higher concentration of that component than without NPS but only for the N1 and N2 treatments. The beneficial influence of NPS was particularly transparent for N1. As for N3, a positive impact of that factor was overshadowed by high rates of N. There are several possible explanations for the positive effect of banding NPS on N uptake and concentration. At the initial growth stage, this phenomenon can be explained by an increased Nmin and P concentration in the soil solution near the roots [54]. At the same time, ammonium-induced acidification in the rhizosphere resulted in the increased solubility of sparingly soluble P compounds, such as apatite and struvite, resulting in higher P availability compared with the supply of NO3-N [25,26]. Rhizosphere acidification induced by banding DAP application also increases the uptake of a greatly important element, namely Zn [17]. The authors also observed that there was a higher N uptake rate per unit of maize root biomass in response to band application of DAP compared with other treatments. The rise in the concentration of N in maize may also be explained through the modification of root architecture as a consequence of a high concentration of NH4-N and P in the soil layer around the developing plants. Weligama et al. [21] report that band application increases total root length and root dry matter, while according to Ma et al. [17], it also positively conditions lateral root development. Ammonium only has a minor effect on root hair length or density, and an excess of phosphorus even reduces those features [66,67]. Earlier research additionally showed

a beneficial effect of DAP application on maize N nutritional status at the sixth/seventh leaf stage, expressed by the plants' dry matter and SPAD index [14]. However, the influence depended on the depth at which the fertilizer granules were placed. In terms of N content, the optimum depth was 5–10 cm. At another critical growth stage, the beginning of flowering, localized NPS fertilization increased the total accumulation of N in plants. This was, among other factors, the consequence of better plant nutrition at an earlier stage. The amount of N at the flowering stage is particularly important, as after that stage, root activity and the ability to uptake N from the soil diminish [64]. According to Pampana et al. [34], before silking, maize uptakes approximately 64–70% of nitrogen from the soil. Most of the N in cereal kernels comes from the remobilization processes. The share of that form of N in kernels may constitute 50–90% of total nitrogen in cereal kernels [68,69]. As the main goal of maize cultivation was grain, therefore, the regression curves were determined to show the dependence of GY on N accumulation at the sixth/seventh leaf stage and flowering:

$$\text{16 } \text{7 Teaf: GY} = \text{5.436} + \text{8.092} \times \text{Na1; R}^2 = \text{56; p} < 0.001; n = 26\tag{4}$$

$$\text{Flowering: GY} = 5.14 + 1.401 \times \text{Na2; R}^2 = 46; p < 0.001; n = 26\tag{5}$$

In terms of plant nutrition diagnostics, the first interdependence is vital, because it is the last growth stage to change that in agricultural practice.

In order to determine the impact of N management on maize yielding, several indices were used. As far as the physiology of yielding is concerned, the following factors are considered largely relevant: dry matter remobilization efficiency (DMRE); contribution of DMR assimilates to grain (CDMR); nitrogen remobilization efficiency (NRE); contribution of remobilized N to grain (CNR). Earlier research confirmed that depending on the hybrid maturity class of maize, indices' values DMRE, CDMR, NRE and CNR can be 16.9–24.5%, 24.9–35.8%, 38.0–44.4% and 40.2–50.3%, respectively [34]. In comparison to these values, our own study obtained similar values for NRE and CNR. Nevertheless, DMRE and CDMR were negative. In 2019, the increase in the total maize biomass after anthesis (positive values of DMA) resulted mainly from the rise of the green parts of biomass. Thus, the DMR index was negative and, consequently, so were the DMRE and CDMR indices. This means that in 2019, the current photosynthesis was significantly responsible for the accumulation of DM in kernels. Such a reaction of plants is characteristic for the "stay green" types [5]. Ray et al. [33] also obtained negative results of DM remobilization indices as a consequence of large increases in maize biomass in the post-silking period. Unlike DM management indices, the nitrogen management indices (NRE and CNR) obtained in our studies were positive. These values confirm that N accumulation in kernels mainly relies on N remobilization. At the same time, in 2019, the remobilization index was considerably lower than in 2020, which should be associated with various concentration levels of Nmin in the soil [5]. When maize N uptake is sustained throughout the grain filling period, less N is mobilized from vegetative organs, thereby increasing leaf area duration, delaying senescence and enhancing dry matter accumulation in grains [70]. In the conducted research, the fertilization factor changed the values of NRE and CNR indices in a particular way, usually making changes only up to a certain level. At the level of N1, the highest NRE value was obtained for the P2 rate, and at the level of N2, for the P1 rate, whereas for CNR, the optimum treatment was N2P1, followed by N1P0. The directions of the index value changes clearly indicate a competition between the main plant parts to obtain nitrogen and carbon, most probably determined by the plants' N nutritional status. This is confirmed by the lack of a positive correlation between the mentioned indices and the grain yield. As the earlier studies confirm, remobilization of N from vegetative plant parts was covered mainly by depletion of stem N at high N supply and by depletion of leaf N at low N supply [34,71]. If the main source of remobilized N was leaves, this brought about early leaf senescence and led to the decreasing accumulation of dry matter in grains from the current photosynthesis [72]. In the present studies, rising NPS rates boosted N accumulation in plants; therefore, the potential of utilizing N from leaves was high, but the real translocation of N to kernels

was lower due to a higher metabolic activity of leaves well nourished in N and P(S). Our studies confirm earlier observations, where fertilization treatments without phosphorus (NK), indices of remobilization and contribution activities were higher than in treatments without nitrogen but with phosphorus (PK) [33]. At the same time, our studies indicate that N management indices do not have to have a linear correlation with NPS rates.

#### **4. Materials and Methods**

#### *4.1. Experiment Location and Design*

The experiment was carried out in 2019–2020 at Brody, Poznan University of Life Sciences Experimental Station, in Poland (52◦26 18 N 16◦17 40 E). The following factors were tested: band application of ternary fertilizer mixture (NPS) and different total N rates. Treatments of NP(S) fertilization were as follows: P0—control; P1—8.7; P2—17.4; and P3—26.2 kg ha−<sup>1</sup> of P (17%, 33% and 67% of total P uptake for grain yield = 9.0 t ha<sup>−</sup>1). The N rates were as follows: N0—control; N1—60; N2—120; and N3—180 kg ha−<sup>1</sup> of N. A nitrogen rate of 180 kg ha−<sup>1</sup> corresponded to 100% of maize requirement for this nutrient in mineral fertilizers. The effect of mineral fertilization with NP(S) was compared to the absolute control (AC), without fertilization with these components. NP(S) were applied to the soil using fertilizer NPS(+Zn) in the proportion 20-20-35+0.3 (calculated for N, P2O5, SO3, Zn). The fertilizer is based on two main chemical compounds: di-ammonium phosphate, DAP [(NH4)2HPO4] and ammonium sulfate [(NH4)2SO4]. Therefore, on plots with localized fertilization P1, P2 and P3, the doses of ammonium nitrogen (NH4-N) were 20, 40 and 60 kg ha−<sup>1</sup> of N. A detailed summary of the doses of N, P, S and Zn used in the experiment is given in Table 5. In order to simplify the notation of fertilization treatments, the NPSZn rates were recorded as P rates.


**Table 5.** Rates of nutrients (N, P, S and Zn) depending on the fertilization treatment.

\* Nitrogen band application of di-ammonium phosphate (DAP) and ammonium sulfate.

The NP(S) fertilizer was applied while sowing the seeds. The fertilizer was banded to 5 cm below and away from the seeds. In treatments without NP(S) fertilization or with low total N rates, the maize requirement for N was supplemented with ammonium nitrate (34% N)—broadcast application immediately before sowing. Potassium fertilization was carried out in early spring in the form of potassium salt K(S, Mg) in proportion 41(15, 6.5) at the rate of 66.4 kg ha−<sup>1</sup> of K, regardless of the NPS treatment.

A randomized complete block design (RCBD) with four replicates was applied in the experiment. The area of an individual plot was 24.0 m<sup>2</sup> (3 × 8 m). The variety *Zea mays* L. "ES Zizou" was used in the experiment (Euralis Semences, Lescar, France), which is a variety of FAO 220 earliness; type of seeds: flint-dent/flint; average early vigor and "stay green" type. Maize was also a forecrop. Sowing was performed on 20 April 2019 and 21 April 2020 with 95,000 seeds per hectare. The row spacing was 0.75 m, while the stem spacing was 0.14 m. Plant protection included the application of herbicide (mixture of terbuthylazine, S-metolachlor and mesotrione) before the emergence of the plants.

#### *4.2. Soil and Meteorological Conditions*

According to the World Reference Base for Soil Resources [73] classification system, the soil in the experiment was classified as Haplic Luvisols. The topsoil was characterized by sandy loam, and the subsoil was characterized by loam texture. The soil organic matter content in the topsoil was around 1.37%. To assess the pH and plant-available nutrient contents, soil samples were collected each year in early spring (March/April), before the application of mineral fertilizers. The soil pH at a depth of 0–0.3 m was acidic in each season. According to the Polish classification [74], the contents of plant-available P in the topsoil were high, irrespective of the year. The content of K in the first year was medium but in the second, very high. The content of Mg was very high; Ca—low; micronutrients—medium; and S—medium. The total content of Nmin (sum of NH4-N and NO3-N in soil depth 0.0–0.9 m) ranged from 33.0 to 93.6 kg ha−<sup>1</sup> of N (Table 6).


**Table 6.** Agrochemical properties of soil prior to experiment.

\* soil pH was determined in suspension of 1 M KCl; plant-available nutrients using the Melich 3 method [75] and mineral nitrogen using 0.01 M CaCl2 [76].

The characteristics of climatic conditions were based on data from the meteorological station belonging to the Poznan University of Life Sciences Experimental Station in Brody (west Poland). The long-term (1960–2018) average yearly precipitation and temperature in the study area are about 590 mm and 8.5 ◦C, respectively. In 2019 and 2020, the sum of precipitation was 403 and 496, and the average temperature 12.0 and 11.9 ◦C. In these years, the sum of precipitation during the growing season (April–September) was 253 and 313 mm, respectively. For comparison, the sum of precipitation for the long-term period was 356 mm. Both growing seasons also differed in their rainfall distribution. In the first year, May had better conditions for maize growth than in 2020. In turn, in the second year, the weather conditions were better in June and August. However, rainfall during flowering was greater in 2019 than in 2020 (Figure 5). Mean temperature during the maize growing season was 16.5 ◦C in 2019 and 15.7 ◦C in 2020.

**Figure 5.** Air temperature and precipitation during 2019–2020 growing seasons of maize (in decades of the month). Key growth stages: BBCH 17—seventh leaf growth stage; BBCH 61—onset of flowering. Source: Poznan University of Life Sciences Experimental Station in Brody.

#### *4.3. Plant Sampling and Analysis*

Plant samples were collected at the following growth stages: seventh leaf (BBCH 17—coding system of growth stages, abbreviation (in German): Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie; [77]); beginning of flowering (BBCH 61/62) and technological maturity (BBCH 91/92). Depending on the year (2019 and 2020), the sampling dates were as follows: 8 and 16 June, 19 and 27 July, 27 September and 6 October. In order to obtain the grain yield, maize cobs were hand harvested from an area of 5.25 m<sup>2</sup> (2 rows × 3.5 m). Next, the cobs were counted and threshed using the laboratory threshing machine; the moisture of seeds was also determined. The biomass of plant vegetative parts was determined by randomly sampling 5 plants from each plot, regardless of the date of sample collection. The plant samples were dried at 60 ◦C and ground afterward. Nitrogen contents were determined with the Kjeldahl method using a Kjeltec Auto 1031 Analyzer (Foss Tecator AB, Hoganas, Sweden). Total nitrogen uptake (TN) was calculated by summing up the amount of nitrogen accumulated in grains (GN) and in the post-harvest residues (SN).

#### *4.4. Nitrogen Use Efficiency Indices*

In order to assess the effectiveness of nitrogen (N) fertilization, the following standard indices were used [62]:

$$\text{partial factor productivity of N (PFP)} = \text{GY/N}\_{\text{f}} \text{ [kg seeds kg}^{-1} \text{ N}\_{\text{f}}] \tag{6}$$

$$\text{algorithm efficiency of N (AE)} = (\text{GY} - \text{GY}\_0) / \text{N}\_{\text{f}} \text{ [kg seeds kg}^{-1} \text{ N}\_{\text{f}}] \tag{7}$$

$$\text{partial N balance (PNB)} = \text{TN/N}\_{\text{f}} \text{ [kg N kg}^{-1} \text{ N}\_{\text{f}}] \tag{8}$$

apparent N recovery efficiency (RE) = (TN <sup>−</sup> TN0)/Nf [kg TN kg−<sup>1</sup> Nf] (9)

internal N utilization efficiency (IE) = GY/TN [kg seeds kg−<sup>1</sup> TN] (10)

physiological N efficiency (PE) = (GY <sup>−</sup> GY0)/(TN <sup>−</sup> TN0) [kg seeds kg−<sup>1</sup> TN] (11)

where GY—grain yield (kg ha−1); GY0—grain yield in treatment without N application (kg ha−1); Nf—input of N in mineral fertilizers (kg ha−1); TN—total N accumulation in above-ground biomass of maize (kg ha<sup>−</sup>1); TN0—total N accumulation on control (kg ha−1).

Additionally, the efficiency of N can be determined using the nitrogen gap (Ngap) index based on the concept proposed by Grzebisz and Łukowiak [32]. The following set of equations can be used to calculate Ngap:

maximum attainable yield (GYmax) = cPFP · Nf [kg ha<sup>−</sup>1] (12)

$$\text{grain yield gap (GY}\_{\text{gap}}) = \text{GY}\_{\text{max}} - \text{GY}\_{\text{a}} \text{[kg} \,\text{ha}^{-1}\text{]} \tag{13}$$

$$\text{nitrogen gap (N}\_{\text{gap}}) = \text{GY}\_{\text{gap}} / \text{cPFP [kg ha}^{-1}] \tag{14}$$

where cPFP is the third quartile (Q3) of the partial factor productivity (PFP) values measured for each plot with N fertilization (kg seeds kg−<sup>1</sup> Nf); Nf—input of N in mineral fertilizers (kg ha<sup>−</sup>1); GYa—grain yield on each plot in a particular growing season (kg ha−1).

#### *4.5. Dry Matter and Nitrogen Management Indices*

The assessment of the impact of fertilization on the method of dry matter (DM) and N management by maize was based on the following indices [68]:

$$\text{dry matter increase (DMI)} = \text{DM}\_{\text{FI}} - \text{DM}\_{\text{A}} \text{ [g plant}^{-1}] \tag{15}$$

dry matter remobilization (DMR) = DMA <sup>−</sup> DMS [g plant<sup>−</sup>1] (16)

$$\text{dry matter recombination efficiency (DMRE)} = \text{(DMR/DM}\_{\text{A}}) \times 100 \, [\, \% ] \tag{17}$$

contribution of DMR assimilates to grain (CDMR) = (DMR/DMG) × 100 [%] (18)

$$\text{In nitrogen increase (NI)} = \text{TN}\_{\text{H}} - \text{TN}\_{\text{A}} \text{ [g plant}^{-1}] \tag{19}$$

$$\text{Initrogen remombilization (NR)} = \text{TN}\_{\text{A}} - \text{N}\_{\text{S}} \text{ [g plant}^{-1}] \tag{20}$$

$$\text{nitrogen removal}\\ \text{lithization efficiency (NRE)} = \text{(NR/TN}\_{\text{A}}) \times 100 \text{ [}\%\text{]} \tag{21}$$

contribution of remobilized N to grain (CNR) = (NR/NG) × 100 [%] (22)

where DMH—total above-ground biomass (dry matter) at maturity (g plant<sup>−</sup>1); DMA—total above-ground biomass at anthesis (g plant−1); DMS—dry matter of crop residues (stems, leaves, husk, corncob) at maturity (g plant−1); DMG—dry matter of grains at maturity (g plant−1); TNH—total N content of above-ground biomass at maturity (g plant−1); TNA—total N content of above-ground biomass at anthesis (g plant−1); NS—N content of crop residues (stems, leaves, husk, corncob) at maturity (g plant−1); NG—N content of grains at maturity (g plant<sup>−</sup>1).

#### *4.6. Statistical Analysis*

The effects of individual research factors (year, NP treatments) and their interactions were assessed by means of the two-way ANOVA. If the F-ratio was larger than the critical value (*p* < 0.05), the differences between the treatments were evaluated by using the HSD (Tukey's) test (for α = 0.05). The distribution of the data was checked using the Shapiro– Wilk test and the homogeneity of variance with the Bartlett test. Standard error of the mean (SEM) was used to indicate statistical error. Principal component analysis (PCA) was applied for evaluation of the relationships between variables. The Tukey median is surrounded by a bag containing 50% of the data points. The bagplot visualizes the location, spread, correlation, skewness and tails of data. The bagplot cover contains the inliers and outside of the "fence" are outliers [78]. In addition, the relationships between traits were analyzed using Pearson's correlation and linear regression. Statistica 13 software (TIBCO Software Inc., USA) was used for all statistical analyses [79].

#### **5. Conclusions**

The effect of nitrogen application on the maize yield and nitrogen management indices depended on the amount of mineral nitrogen in the soil, nitrogen doses and the method of its application. The most effective use of nitrogen by corn was ensured by the use of ammonium phosphate and ammonium sulphate during the sowing of corn seeds (band application). From the point of view of NUE indices, the optimal dose of N was 60 kg ha<sup>−</sup>1. With broadcast fertilization and/or a further increase in the N dose, without the simultaneous use of P and S, the values of NUE indices deteriorated, especially in the year with the highest content of Nmin in the soil. Thus, a positive effect of the interaction of N and P(S) was confirmed in the conditions of soil rich in plant-available phosphorus.

Band application had a particularly positive effect on total N accumulation, nitrogen harvest index and internal N utilization efficiency. These parameters were closely related to the grain yield. For diagnostic purposes, the accumulation of N in the above-ground part of maize at the sixth–seventh leaf stage was important.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/ 10.3390/plants11131660/s1, Figure S1. Maize grain yield (GY), crop residues biomass (SDM) and total dry matter (TDM) depending on the year and fertilization treatments; Table S1. Maize yield components depending on the year and fertilization treatments; Table S2. Nitrogen concentration in dry matter (DM); accumulation of N in particular plant organs and total N accumulation by maize depending on the year and fertilization treatment; Table S3. Correlation matrix loadings and variance of the significant principal components (PCs) for grain yield of maize and nitrogen use efficiency (NUE) indices (n = 26); Table S4. Pearson correlation matrix between maize grain yield (GY), crop residues dry matter (SDM), total nitrogen accumulation (TN) and nitrogen use indices (n = 26); Table S5. Dry matter and nitrogen management indices depending on fertilization treatment; Table S6. Correlation matrix loadings and variance of the significant principal components (PCs) for grain yield of maize and dry matter and nitrogen management indices (n = 26); Table S7. Pearson correlation matrix between maize grain yield (GY), crop residues dry matter (SDM), total nitrogen accumulation (TN) and nitrogen content at early growth stages and N remobilization and contribution to grain (n = 26).

**Author Contributions:** Conceptualization, P.B.; methodology, P.B., R.Ł. and L.H.; validation, P.B.; formal analysis, P.B. and R.Ł.; investigation, P.B. and R.Ł.; resources, P.B. and R.Ł; data curation, R.Ł.; writing—original draft preparation, P.B., R.Ł. and L.H; writing—review and editing, P.B. and R.Ł.; visualization, R.Ł.; project administration, P.B. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data sharing not applicable.

**Acknowledgments:** The publication was co-financed within the framework of Ministry of Science and Higher Education programme as "Regional Initiative Excellence" in years 2019-2022, Project No. 005/RID/2018/19. The authors would like to thank Roman Błaszyk from Phosagro Poland for ammonium phosphate supplies and financial support for field research. The authors would like to thank the editor and reviewers for their valuable comments and suggestions, which substantially improved the manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


**Fengmin Shen †, Changwei Zhu †, Guiying Jiang \*, Jin Yang, Xuanlin Zhu, Shiji Wang, Renzhuo Wang, Fang Liu, Xiaolei Jie and Shiliang Liu \***

> College of Resources and Environmental Sciences, Henan Agricultural University, Zhengzhou 450002, China **\*** Correspondence: jgy9090@126.com (G.J.); slliu70@163.com (S.L.); Tel.: +86-0371-68555200 (G.J.);

† These authors contributed equally to this work.

**Abstract:** Nitrogen is a vital element for soil fertility and crop productivity. The transformation of nitrogen is directly affected by tillage practices for the disturbing soil. The characteristics of different nitrogen forms under different tillage modes are still unclear. A 3-year cycle tillage experiment was carried out to assess the combination of rotary tillage (RT), deep tillage (DT), and shallow rotary tillage (SRT) on nitrogen transformation and distribution, wheat yield and nitrogen balance in fluvo-aquic soil from Huang-Huai-Hai Plain in China. The results showed the rotation tillage cycle with deep tillage in the first year increased the total nitrogen (TN), and the main nitrogen form content in 0–30 cm compared with continued rotary tillage (RT-RT-RT). Moreover, the nitrate (NO3 −-N) and ammonium nitrogen (NH4 +-N) content were improved in 20–40 cm by deep tillage practice with the highest value as 39.88 mg kg−<sup>1</sup> under DT-SRT-RT. The time, tillage, and depth significantly affected the different nitrogen forms, but there was no effect on dissolved organic carbon (DON) and soil microbial biomass nitrogen (SMBN) by the interaction of time and tillage. Moreover, compared with RT-RT-RT, the rotation tillage promoted the spike number and kernels per spike of wheat, further increasing the wheat yield and nitrogen partial productivity, and with a better effect under DT-SRT-RT. The NO3 −-N and NH4 +-N trended closer and positively correlated with wheat yield in 0–40 cm in 2019. The rotation tillage with deep tillage improved the different forms of nitrogen in 0–30 cm, wheat yield, and nitrogen partial productivity, and decreased the apparent nitrogen loss. It was suggested as the efficiency tillage practice to improve nitrogen use efficiency and crop yield in this area.

**Keywords:** rotation tillage; fluvo-aquic soil; wheat-maize system; nitrogen forms; nitrogen distribution

#### **1. Introduction**

Nitrogen is the necessary element for the plant, which directly decides the crop yield [1]. The nitrogen transformation is affected by various factors, such as tillage, irrigation, fertilization, and so on. Tillage practice is a common agricultural practice to directly disturb and change the soil's physical properties, further affecting soil nutrient conversion and crop productivity [2]. The disturbance degree on soil varies from different tillage methods. Therefore, the effect of different tillage practices on soil physicochemical properties from different depths is different. Moreover, the tillage not only affects the change in soil nitrogen content, but also affects the profile distribution of soil nitrogen due to the downward shift of nitrogen and the effect of crop roots and may therefore influence crop yield and quality [3,4].

Soil nitrogen exists as organic components, its transformation in the soil is essentially associated with the interconversion of inorganic forms such as ammonium (NH4 +-N), nitrate (NO3 −-N), and organic components [5], and is regulated by interactive processes of production and consumption [6]. The transformation process is driven by soil microorganisms. Soil microbial biomass nitrogen (SMBN) and dissolved organic nitrogen (DON)

**Citation:** Shen, F.; Zhu, C.; Jiang, G.; Yang, J.; Zhu, X.; Wang, S.; Wang, R.; Liu, F.; Jie, X.; Liu, S. Differentiation in Nitrogen Transformations and Crop Yield as Affected by Tillage Modes in a Fluvo-Aquic Soil. *Plants* **2023**, *12*, 783. https://doi.org/ 10.3390/plants12040783

Academic Editors: Przemysław Barłóg, Jim Moir, Lukáš Hlisnikovský and Xinhua He

Received: 30 December 2022 Revised: 28 January 2023 Accepted: 7 February 2023 Published: 9 February 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

<sup>+86-0371-68555200 (</sup>S.L.)

are important labile soil organic nitrogen (SON) fractions, which are considered actively involved in N mineralization and are potentially more sensitive indicators for agricultural management [7,8]. Although DON only accounts for 0.15–0.19% of soil TN, it is one of the relatively active components of the soil organic nitrogen pool and has important effects on nitrogen transformation and the environment. DON also represents a source of energy and nutrients for microbial growth and activity [9]. Tillage practice directly affects this process by changing the soil microenvironment, such as soil structure, and regulating the soil temperature and moisture, further mediating soil microorganism community and structure, and finally determining the nitrogen transformation. Studies have shown that conservation tillage usually increased soil N content compared to conventional tillage [2,3,10–12], but long-term no-till and reduced tillage produce nutrient accumulation and N mineralization in the soil surface [13], and may also cause topsoil compaction [14], leading to a reduction in the air-filled pore space [15,16], which may decrease the root absorption of soil nutrients and water [17]. Minimum tillage, often in combination with other practices, has been promoted to improve soil health through enhanced microbial activity and increased soil organic matter (SOM) in the surface layer [18–20]. long-term no-till management is a benefit for soil N stocks, N mineralization, and efficient fertilizer N use in corn-based cropping systems on well-drained soils. A meta-analysis by Mahal et al. [21] found that no-till increased potentially mineralizable N relative to moldboard plowing. Tillage can increase rates of soil C and N mineralization by disrupting aggregates and incorporating residue. Yuan et al. [6] found that no-tillage combined with maize straw mulching could simultaneously maintain the retention and availability of soil N to achieve effective N cycling in agroecosystems. Meanwhile, nutrients concentrated near the surface of no-till soils may increase the possibility of loss via erosion, runoff, and volatilization. Nutrient stratification may also reduce the availability and uptake of nutrients by crops.

In contrast, deep tillage can loosen the soil and promote crop roots grow and absorb more soil nutrients, but it may increase the loss of soil nitrogen and other nutrients, and accelerate soil erosion, cause serious environmental pollution and soil degradation thereby affecting ecosystem functions in the field [22,23]. Therefore, rotational tillage with the combination of different tillage practices was suggested to dismiss the disadvantage of long-term mono-conventional tillage [24]. Rotation tillage techniques that reasonably combined different tillage measures can effectively counteract some defects caused by mono-tillage practices [25–27]. In recent years, periodic disturbance of continuous NT systems in the form of occasional tillage, one-time tillage, strategic tillage, targeted tillage, single inversion tillage, one cycle of tillage, etc., has been promoted as a potential strategy to address the challenges of long-term NT management [28–31].

Huang-Huai-Hai Plain is the main agricultural region in China, with mainly wheat and maize double cropping systems. The long-term mono-rotary tillage with soil disturbance depth of around 15 cm in this area leads to a shallow plow layer and thick plow bottom, leading to the uncoordinated supply of soil water, fertilizer, gas, and heat, restricts the extension of crop roots, and impedes the increase in crop yields. Thus, optimum tillage practices are essential for crop production in this area. Therefore, the objectives of this study are (i) to clarify the differentiation in nitrogen transformation and distribution by the different tillage modes (ii) to assess the effect of different tillage modes on crop yield, nitrogen use efficiency, and nitrogen balance (iii) to select the optimum tillage mode according to the above results.

#### **2. Results**

#### *2.1. Distribution of Soil Total Nitrogen under Different Tillage Modes*

The total nitrogen content (TN) decreased with soil depth under all tillage treatments during 2017–2019 (Figure 1). The tillage affects the TN in the 0–40 cm soil layer in 2017 and the effect decreased within 0–30 cm in 2018 and 2019. TN content was no different in 0–10 cm and 40–50 cm in 2017 among the treatments, while it was significantly higher under the treatments with deep tillage combination in 20–40 cm than that under RT-RT-RT. During 2018 and 2019, the deep tillage increased TN content in 0–30 cm soil layer compared with RT-RT-RT, with the higher one under DT-SRT-SRT and DT-SRT-RT as 1.14 g kg−<sup>1</sup> and 1.13 g kg<sup>−</sup>1, respectively, in 2018.

**Figure 1.** Soil total nitrogen content in different soil layers under different treatments. Note: Different lowercase letters indicate significant differences between different treatments at the same soil layer (*p* ≤ 0.05).

#### *2.2. Distribution of Soil Alkaline Nitrogen under Different Tillage Modes*

Similar to TN, the alkaline nitrogen content (AN) under all treatments was decreased with the increase in soil depth during 2017–2019 (Figure 2). Compared with RT-RT-RT, the AN was affected by treatments with deep tillage in 0–40 cm in the first year (2017), and the effect decreased within 0–30 cm during the following two years. During the three-year experiment, the AN content was increased under the treatments with deep tillage compared with that under RT-RT-RT. While among the treatments with deep tillage, AN content did not demonstrate a significantly different or clear trend. It indicated that the effect of deep tillage was bigger than the combined other two tillage modes.

**Figure 2.** Soil alkaline nitrogen content in different soil layers under different treatments. Note: Different lowercase letters indicate significant differences between different treatments at the same soil layer (*p* ≤ 0.05).

#### *2.3. Distribution of Soil Nitrate Nitrogen under Different Tillage Modes*

The nitrate nitrogen (NO3 −-N) content under all treatments was decreased with the increase in the soil depths, and the effect of tillage on NO3 −-N in 0–40 cm during 2017–2019 (Figure 3). In the first year, the NO3 −-N content in 0–20 cm soil layer under RT-RT-RT did not differ from that under the treatments with deep tillage, while, which was lower under RT-RT-RT in 0–40 cm during the following two years. Meanwhile, the NO3 −-N content in 30–40 cm soil layer under treatment with deep tillage increased with time, the NO3 −-N content under DT-SRT-SRT treatments was significantly higher than that under RT-RT-RT treatments, the highest increase was 35.12% in 2018. In 2019, the NO3 −-N content in the 0–40 cm soil layer was significantly increased under DT-SRT-RT with the highest value of 39.88 mg kg−1. This indicated that the deep tillage accelerated the NO3 −-N leaching into the deeper soil layer.

**Figure 3.** Soil nitrate nitrogen content in different soil layers under different treatments. Note: Different lowercase letters indicate significant differences between different treatments at the same soil layer (*p* ≤ 0.05).

#### *2.4. Distribution of Soil Ammonium Nitrogen under Different Tillage Modes*

The ammonium nitrogen (NH4 +-N) content under all treatments decreased with the increasing soil depths, and it slightly increased with time. The effect of tillage on NH4 +-N in 0–40 cm during 2017–2019 (Figure 4). Similar to NO3 −-N, the NH4 +-N content in 0–20 cm soil layer under RT-RT-RT did not differ from that under the treatments with deep tillage, while it was lower under RT-RT-RT in 0–40 cm during the following two years. Meanwhile, the NH4 +-N content in 0–30 cm soil layer under treatment with deep tillage significantly increased with time, the NH4 +-N content under DT-SRT-SRT treatments was significantly higher than that under RT-RT-RT treatments, the highest increase was 35.12% in 2018. In 2019, the NH4 +-N content in the 0–40 cm soil layer was significantly higher under DT-SRT-SRT than that under RT-RT-RT with the highest value of 23.82 mg kg−<sup>1</sup> in the 0–10 cm soil layer.

#### *2.5. Distribution of Soil Dissolved Organic Nitrogen under Different Tillage Modes*

The soil dissolved organic nitrogen content (DON) under all treatments decreased first and then slightly increased with time. The major change happened in the 10–30 cm soil layer (Figure 5). The DOC content did not differ from all treatments in 0–10 cm in 2017, but it decreased under RT-RT-RT in the following two years. The DOC was no different in the 40–50 cm soil layer in 2017 and 2018, while it was in the 30–50 cm soil layer in 2019. It indicated that the effect of deep tillage decreased in the third year. Although the DON, generally, was no different among the treatments with deep tillage, the DON under DT-SRT-SRT and DT-SRT-RT was significantly higher than that under RT-RT-RT in 0–30 cm in 2018 and 2019, with the highest value of 23.37 and 25.49 mg kg−<sup>1</sup> under DT-SRT-SRT in the 0–10 cm soil layer.

**Figure 4.** Soil ammonium nitrogen content in different soil layers under different treatments. Note: Different lowercase letters indicate significant differences between different treatments at the same soil layer (*p* ≤ 0.05).

**Figure 5.** Soil dissolved organic nitrogen content in different soil layers under different treatments. Note: Different lowercase letters indicate significant differences between different treatments at the same soil layer (*p* ≤ 0.05).

#### *2.6. Distribution of Soil Microbial Biomass Nitrogen under Different Tillage Modes*

The microbial biomass nitrogen content (SMBN) under all treatments decreased with soil depth increasing during 2017–2019 (Figure 6). Although the SMBN slightly fluctuated during the three years, it increased under the treatments with deep tillage compared with DT-SRT-RT in the 0–40 cm soil layer in 2017 and 2019, and in 0–30 cm in 2018. Generally, SMBN did not differ from the treatments with deep tillage in all the depths and years. The SMBN was significantly higher under DT-RT-SRT than under RT-RT-RT in the three-year experiment, with the highest values of 61.06, 63.03, and 63.26 mg kg−<sup>1</sup> in 0–10 cm in the three years.

**Figure 6.** Soil microbial biomass nitrogen content in different soil layers under different treatments. Note: Different lowercase letters indicate significant differences between different treatments at the same soil layer (*p* ≤ 0.05).

#### *2.7. The Three-Factor Analysis with Time, Tillage, and Soil Depth on Nitrogen Forms*

The multivariate analysis demonstrated that all nitrogen forms were affected by tillage time (year), tillage modes, and soil sample depth, respectively (Table 1). Therein, the effect of soil depth was the most important factor in the different nitrogen forms. All the nitrogen forms were affected by the interaction of tillage time and sample depth, tillage mode, and sample depth. However, there was no interaction effect on DOC and SMBN by tillage time and tillage mode.



The source of variation: "Time" means the tillage duration (year); "Tillage" means the five tillage modes; "Depth" means the five sample depths. \* represented *p* ≤ 0.05; \*\* represented *p* ≤ 0.01; NS represented *p* > 0.05.

#### *2.8. Wheat Yield, Yield Component, and Fertilizer Partial Productivity*

The wheat yield, yield components, and nitrogen partial productivity changed over different years (Table 2). In the first year (2017), the spike number and thousand kernel weight did not differ from treatments, the difference in yield was driven by kernels per spike. The higher wheat yield was found under RT-RT-RT and DT-RT-RT with 6717 and 6383 kg ha<sup>−</sup>1, respectively. In 2018 and 2019, generally, the wheat yield and yield component all showed higher under the treatments with deep tillage compared with RT-RT-RT. The highest wheat yield was under DT-SRT-RT in 2018 and 2019 with 6346 and 6557 kg ha−1, respectively. The N partial productivity demonstrated a similar trend with wheat yield, with a higher value of 28.98 and 29.94 kg kg−<sup>1</sup> in 2018 and 2019, respectively.

#### *2.9. The Nitrogen Balance under Different Treatments*

The nitrogen balance was calculated in 2019 (Table 3). Although the initial inorganic nitrogen under RT-RT-RT was the lowest one in all the treatments, the nitrogen absorbed by the crop was also the lowest one. The apparent nitrogen loss was the highest one with 46.11 kg ha<sup>−</sup>1. This indicated that the rotation tillage modes helped to decrease the apparent nitrogen loss, and increase the nitrogen use efficiency.

**Table 2.** Wheat yield, yield components, and fertilizer partial productivity.


Note: Different lowercase letters after the numbers indicate significant differences between different treatments (*p* ≤ 0.05).

**Table 3.** The nitrogen balance under different treatments in 2019.


Note: Different lowercase letters after the numbers indicate significant differences between different treatments (*p* ≤ 0.05).

#### *2.10. The Correlation Analysis between Nitrogen Forms and Wheat Yield during 2017–2019*

The correlation analysis found that the different nitrogen form in different soil layers was negative in the first year of the three-year rotation, while the correlation increased with time (Figure 7). In 2019, except TN and AN, the other nitrogen forms content was all significantly positively correlated with wheat yield in the 0–10 cm soil layer. Additionally, the NO3 −-N and NH4 +-N were positively correlated with wheat yield in the 0–40 cm soil layer.

**Figure 7.** The correlation between nitrogen forms and wheat yield under different soil layers.

#### **3. Discussion**

#### *3.1. The Effect of Tillage Practice on Total Nitrogen*

Soil total nitrogen (TN) is the pool of nitrogen. It is one of the important indicators to assess soil fertility, but the major component of TN is organic nitrogen [32,33], which needs to transform into inorganic nitrogen such as nitrate nitrogen and ammonium nitrogen, to be absorbed by the crop. Soil tillage practices directly change the soil structure to improve the soil microenvironment [34], further mediating the nitrogen transformation process. Although the TN content is not sensitive to agricultural management, the different tillage practices change the TN vertical distribution by the different disturbance degrees of soil [35,36]. The TN content was changed in the 0–40 cm in the first year by different tillage practices, while the effect was decreased in the 0–30 cm during the following two years in this study. In addition, the effect of deep tillage mainly happened in 10–30 cm, and the combination tillage cycle with deep tillage increased TN content compared with RT-RT-RT. This might be because deep tillage helped to mix the surface soil and the deeper soil, the fertilizer, and the nutrient also mixed and provided the source of organic matter, which led to the TN content accumulation in the deeper soil layer [23,37]. The effect of deep tillage on soil nutrients and structure will decline with time [38]. Our results were in accordance with Han et al. [39] and Zhang et al. [23]. While Wang et al. [40] found that subsoiling—no tillage—subsoiling alternately could increase the TN content in the 0–20 cm soil layer, it did not affect the 20–40 cm soil layer. This might be because the soil disturbance by subsoiling was less than that by deep tillage, and the deep tillage takes more source of fertilizer or crop residue from the surface layer into the deeper soil layer [12,41].

#### *3.2. The Effect of Tillage on Nitrogen Components*

The nitrogen components were more sensitive than soil total nitrogen to tillage practices. Nitrate and ammonium nitrogen are the major inorganic nitrogen form in the soil, and they are also the main nitrogen form absorbed by the crop [42]. Their content is determined by the transformation between organic and inorganic nitrogen forms [5] and is regulated by interactive processes of production and consumption [43]. Soil microbial biomass nitrogen (SMBN) reflects the microorganism community, it is used to assess the nitrogen transformation process. Dissolved organic nitrogen (DON) is part of nitrogen that is relatively easy to transform. Tillage regimes impact the depth distribution of soil organic matter and affect the soil pore architecture which in turn influences soil aeration, and further regulates the nitrification, denitrification, and the relevant microorganic community and structure, finally affecting the NO3 −-N and NH4 +-N, DON, and SMBN content [44,45]. Mondal et al. [46] reported that soil nitrogen status can be improved through no-tillage adoption particularly in the surface soil layer in a global meta-analysis. Minimum tillage, often in combination with other practices, has been promoted to improve soil health through enhanced microbial activity and increased soil organic matter (SOM) in the surface layer [18–20]. In contrast, deep tillage or deep subsoiling was conceived to break up the hard pan in farmland, eliminating soil compaction to boost plant root proliferation, penetration, nutrient uptake, and air permeability [38], improving biological health and physical properties of soil [47], facilitating rain infiltration and water retention [48], and hydraulic conductivity [49]. As a result, deep tillage accelerates the nitrogen transformation and distribution in different soil depths, meanwhile allowing the yield of crops to be continuously enhanced. Our study found that deep tillage promoted NO3 −-N and NH4 +-N transportation into the deeper soil layer, especially for NO3 −-N. However, the effect of deep tillage on DON in deeper layers significantly declined with time. Although the deep tillage significantly increased the SMBN compared with RT-RT-RT, there was no significant change in the same soil layers with time. NO3 −-N cannot be fixed by soil colloid particles, and easily leach with soil water. Deep tillage promotes the soil pore and water storage capacity and helps the soil nitrification and NO3 −-N leaching [48,50]. For DON, although it is relatively easy to transform by the microorganism, there is still part of it belongs to organic form, this might the reason for the shorter affected by the deep tillage.

#### *3.3. The Effect of Tillage on Wheat Yield and Nitrogen Balance*

The tillage practices affect the soil structure and nutrient cycle, further regulating crop growth and yield [23]. Previous studies showed that although the no-till or minimal tillage profited to increase the soil nutrient in the surface soil layer [19,20,46], the effect on crop yield was different. Generally, no-till is considered shallow compaction or soil hardening by farm machinery traffic can lead to soil constraints to crop growth [51]. In contrast, most studies reported that deep tillage can increase crop yield by breaking up the hard pan in arable land and eliminating soil compaction to boost plant root proliferation, nutrient uptake, and air permeability [43]. As a result, deep tillage increases the plant availability of subsoil nutrients, which increases crop yield if nutrients are growth-limiting and allows the yield of crops to be continuously enhanced [43]. A similar result was found in this study, the wheat yield was increased under treatment with deep tillage compared with RT-RT-RT. Meanwhile, the nitrogen partial productivity demonstrated a similar trend with wheat yield. This indicated that deep tillage improved the nutrient absorbed by wheat and promoted the yield component and wheat yield. The correlation analysis also supported that it was a closer relationship between the wheat yield and nitrogen forms with time.

#### **4. Materials and Methods**

#### *4.1. Site Description*

The field experiment was carried out in 2016 at Yuanyang, Henan, China (35◦19 N, 113◦50 E). This area is a warm temperate continental monsoon climate. The mean annual air temperature is 14.5 ◦C, the mean annual precipitation is 615 mm, and the annual sunshine hours are 2324 h. The soil type is sandy fluvo-aquic soil developed from Yellow River alluviation, which is Calcaric Cambisol according to WBR [52]. The initial soil properties before the experiment in the 0–20 cm soil layer were: organic matter content 17.3 g kg<sup>−</sup>1, total nitrogen 1.00 g kg<sup>−</sup>1, alkaline nitrogen 71.33 mg kg−1, available phosphorus 21.6 mg kg−1, available potassium 108.0 mg kg−1, pH 7.2. The field experiment was a winter wheat (*Triticum aestivum* L. Zhengmai 369)—summer maize (*Zea mays* L. Xundan 29) crop rotation.

#### *4.2. Experimental Design*

The randomized block design with three replicates was carried out. Five treatments with different combinations of tillage modes with three-year cycles were set as (1) continuous rotary tillage (RT-RT-RT); (2) deep tillage–rotary tillage–rotary tillage (DT-RT-RT); (3) deep tillage–rotary tillage–shallow rotary tillage (DT-RT-SRT); (4) deep tillage–shallow rotary tillage–shallow rotary tillage (DT-SRT-SRT); (5) deep tillage–shallow rotary tillage– rotary tillage (DT-SRT-RT). Each plot was 99.2 m2. The information tillage practice before winter wheat seeding during 2016–2018 was demonstrated in Table 4.


**Table 4.** The soil tillage practice before winter wheat seeding during 2016–2018.

The tillage practice is detailed as follows. Summer maize straw was incorporated with all tillage practices. For rotary tillage, a rotary tiller was prepared twice with a depth of 13–15 cm. For deep tillage, first moldboard plows with 28–30 cm, then a rotary tiller was prepared twice with 15–18 cm. For shallow rotary tillage, a rotary tiller was prepared twice with 5–8 cm. The winter wheat was seeded by a seeder machine with a rate of 232.5 kg ha<sup>−</sup>1. The basal fertilizer (N-P2O5-K2O = 20-16-16) was applied 750 kg ha−1, and then applied 69 kg N ha−<sup>1</sup> at the regreening stage in the wheat season. The summer maize and fertilizer were seeded simultaneously with maize density as 67,500 plant ha−<sup>1</sup> and 750 ha−<sup>1</sup> component fertilizer (N-P2O5-K2O = 28-10-12).

#### *4.3. Soil Sample Collection and Measurement*

The soil was sampled after the wheat harvest during 2017–2019. The 0–50 cm depth soil with 10 cm intervals was sampled by the mixture of 5–10 cores. The sample was divided into two parts, one part was stored at 4 ◦C in the refrigerator to determine soil nitrate nitrogen (NO3 −-N), ammonium nitrogen (NH4 +-N), dissolved organic nitrogen (DON), and microbial biomass nitrogen (SMBN). The other part was air-dried and sieved through 0.85 mm and 0.25 mm to determine the soil alkaline nitrogen (AN) and total nitrogen (TN). The AN was measured by Conway method, and TN was determined by the micro-Kjeldahl method [53]. NO3 −-N and NH4 +-N were extracted from 10 g of fresh soil in 50 mL of 2 mol KCl L−<sup>1</sup> (1:10 soil: solution ratio) before filtering [54]. The NO3 −-N and NH4 +-N concentrations in the extract were determined using an automated colorimeter (automatic chemical analyzer, Easychem Plus, Via Fratta Rotonda Vado Largo, Italy, Europe).

The dissolved organic nitrogen (DON) content was extracted using the method presented by Gigliotti et al. [55]. Briefly, 10 g of fresh soil with water at a soil-to-water ratio of 1:2 was shaken for 30 min h at 250 rev/min and 25 ◦C. Next, the supernatant was centrifuged for 10 min at 4000 rev/min before passing through a 0.45 μm membrane filter. The filtrate was measured using a TOC analyzer (Leeman, US17192017, Mason, OH, USA).

The soil microbial biomass nitrogen (SMBN) content was estimated using chloroform fumigation extraction according to the method presented by Vance et al. [56]. Briefly, 20 g of fresh soil was fumigated for 24 h at 25 ◦C with ethanol-free chloroform, the non-fumigated portion was completed simultaneously. Next, the soils were extracted using 60 mL of 0.5 mol K2SO4 L−1, shaken at 200 rev/min for 30 min, and filtered using filter paper (12.5 cm diameter). The organic nitrogen contents in the extracts were determined using a TOC analyzer (Lehman US17192017). In addition, the SMBN content was calculated according to Jenkinson et al. [57]. as follows: microbial biomass nitrogen = *E*N/*k*EN, where EN is the D-value between organic nitrogen extracted from fumigated soils and non-fumigated soils; *k*EN = 0.45.

#### *4.4. Grain Yield, Yield Components, Aboveground Biomass, and Nitrogen Accumulation*

Three replicates of wheat samples (each 1 m2) were randomly selected from each plot to measure yield components (spike number per hectare, grain number per spike, and 1000-grain weight) and nitrogen accumulation at the maturity stage. After threshing, drying, and weighing, wheat grain yield, and straw were calculated according to the national wheat grain and straw warehousing standard (at a moisture content of about 14%). The plant samples were oven dried (80 ◦C) over 48 h and weighed. The grain and straw were divided into two parts, and their nitrogen (N) content was analyzed using the micro-Kjeldahl method (Bao, 2000). Total aboveground nitrogen accumulation was calculated as the grain and straw N content, and the relevant biomass.

We used the certified standard reference materials (bush leaves, GBW07602 (GSV-1); soil, GBW07420), purchased from the National Center of Standard Material in China, to check the measurements.

#### *4.5. Calculation*

The nitrogen absorbed by aboveground biomass was calculated according to Lu et al. [58].

$$\text{GNA} = \text{GB} \times \text{GNC} \tag{1}$$

SNA = SB × SNC (2)

$$\text{ANA} = \text{GNA} + \text{SNA} \tag{3}$$

where GNA was grain nitrogen accumulation (kg·ha−1); GB was grain biomass (kg ha−1); GNC was grain nitrogen content (kg kg<sup>−</sup>1); SNA was straw nitrogen accumulation (kg ha−1); SB was straw biomass (kg ha−1); SNC was straw nitrogen content (kg kg−1); ANA was aboveground nitrogen accumulation (kg ha<sup>−</sup>1).

The apparent nitrogen loss (ANL) was calculated based on the ANA according to Xue et al. [59].

ANL = NI − NO (4)

$$\text{NI} = \text{IINS} + \text{NAR} \tag{5}$$

$$\text{NNO} = \text{ANA} + \text{RINS} \tag{6}$$

where ANL was apparent nitrogen loss (kg ha−1); NI was nitrogen input (kg ha−1), it was the sum of IINS and NAR; IINS was initial soil inorganic nitrogen storage (kg ha−1) in the 0–20 cm soil layer; NAR was nitrogen application rate in wheat season (kg ha−1); NO was nitrogen output (kg ha−1), it was the sum of ANA and RINS (kg ha−1); ANA was aboveground nitrogen accumulation (kg ha−1); RINS was residue inorganic nitrogen storage (kg ha<sup>−</sup>1) in the 0–20 cm soil layer after wheat harvest in 2019.

#### *4.6. Statistical Analysis*

Microsoft Excel 2020 (Microsoft Corp., Redmond, WA, USA) was used to input and organize the data, using SPSS Software (ver. 20.0; SPSS Inc., Chicago, IL, USA) for statistical analysis. The ANOVA analysis was used to compare the difference in different nitrogen forms, grain yield, yield components, nitrogen partial productivity, and nitrogen balance indexes between different tillage modes. The multiple comparisons by the least significant range method (LSD) were to analyze the effect of tillage mode, soil depth, and tillage time on the different nitrogen forms. Origin Pro (ver. 8.5; OriginLab Corporation, Northampton, MA, USA) was used to create the graph. All statistical analyses were performed at a significance level of *p* ≤ 0.05.

#### **5. Conclusions**

The findings carried out from the 3-year cycle tillage experiment showed that the rotation tillage with deep tillage in the first year increased the total nitrogen and the major nitrogen forms content compared with RT-RT-RT. Especially they improved the NO3 −-N and NH4 +-N content in 0–40 cm, with the highest value under DT-SRT-RT. The time, tillage, and depth significantly affected the different nitrogen forms, but there was no effect on DON and SMBN by the interaction of time and tillage. Meanwhile, the rotation tillage promoted the spike number and kernels per spike of wheat, further increasing the wheat yield and nitrogen partial productivity, and with a better effect under DT-SRT-RT. The available nitrogen forms such as NO3 −-N, and NH4 +-N were closely positively correlated with wheat yield in 0–40 cm at with time.

**Author Contributions:** Conceptualization, G.J., F.S. and C.Z.; methodology, F.S. and C.Z.; software, J.Y., X.Z., S.W. and R.W.; validation, X.J. and S.L.; formal analysis, J.Y.; data curation, J.Y., X.Z., S.W., R.W. and F.L.; writing—original draft preparation, F.S. and C.Z.; writing—review and editing, G.J. and S.L.; visualization, J.Y., X.Z., S.W. and R.W.; supervision, G.J. and S.L.; project administration, G.J. and S.L.; funding acquisition, G.J., S.L. and X.J. All authors have read and agreed to the published version of the manuscript.

**Funding:** The work was financially supported by the National Key Research and Development Program of China (Grant No. 2021YFD1700904), the Key Research Project of Henan Colleges and Universities (Grant No. 23A210014), Innovation Training Project of Henan Agricultural University (Grant No. 2022-171), and Undergraduate Laboratory Opening Project of Henan Agricultural University (Grant No. 2022-A161).

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


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