*2.2. Climatic Potential Yield—CPY*

The maximum attainable yield of a particular crop, typical for the climatic region, is determined by the prevailing meteorological conditions. Based on this assumption Licker et al. [35], proposed to use the term, the climatic potential yield (CPY), instead of the less precisely defined, Yield Potential. The CPY can be defined as the maximum yield of a crop plant cultivar grown under a natural water supply, provided the optimization of other growth conditions. The yield gap (YG) is calculated based on the algorithm:

$$\text{YG} = \text{CPY} - \text{Y}\_{\text{a}} \tag{5}$$

**Figure 1.** Graphical presentation of Water Limited Yield and loss/gain yield of winter wheat. Legend: WLY—water-limited yield; YL—yield loss; YG—yield gain; 0.32—the yield gap fraction; C—water control; I, D—plots irrigated or with imposed drought by water shortage during stem elongation and heading. (Author's own result; unpublished) \* yield gain (−)/yield loss.

The fraction of the yield gap (YGf) is a relative measure (a value, extending from 0 to 1) of the Ya distance to the yield defined by the dominant weather conditions within a given climatic region (see Equation (4)). YGf values approaching zero, indicate that meteorological conditions during the growing season were favorable, allowing the attainment of the climatic yielding potential by the grown crop. The best source of CPY data are experiments conducted by accredited Experimental Stations. An example of CPYs and their respective indices are shown in Table 1. The differences between CPY and Ya for winter wheat were extremely pronounced. The calculated YGf accounted on average for 58% for winter wheat as compared to 26% for sugar beets. The low year-to-year variability of this index for both crops indicates (i) stability of the CPY for these two crops, irrespective of weather variability during the growing season, (ii) the presence of other growth factors affecting the actual yield. The main reasons for the recorded difference between winter wheat and sugar beets are soil conditions. In Poland, winter wheat, despite high requirements for soil fertility, is cultivated on a broad range of soil agronomic classes [36]. In contrast, sugar beets are cultivated on very fertile soils [37]. The second growth factor, significantly impacting the CPY of wheat, is the level of crop protection and the level of applied N. The higher input of agronomic measures resulted in a CPY increase of 13%.


**Table 1.** The Climatic Yield Gap for basic seed crops in Poland, t ha−1.

CPY—the climatic yield potential; Ya—actual yield; YG—yield gap; YGf—the yield gap fraction; a1, a2—medium and high input of production measures (crop protection + higher N rate); SD—standard deviation; CV—coefficient of variation.

#### *2.3. Partial Factor of Productivity of Nitrogen—PFPN*

Nitrogen is, assuming the same meteorological conditions (precipitation) for a given locality (region), the key growth factor limiting yield [28,38]. Hence, the amount of Nf or the whole N input at the beginning of the growing season becomes the principal independent variable, affecting both the plant growth rate during the growing season and its yield [39,40]. The efficiency of Nf can be determined, using the concept of the partial factor productivity of fertilizer nitrogen, (PFPN) [41]. This approach is frequently applied for making a country-to-country comparison [42]. The procedure to calculate the maximum attainable yield (Yattmax), and in consequence, the nitrogen gap (NG) based on PFPN, requires data on the unit productivity of the applied Nf under optimum growth conditions, i.e., the ample availability of nitrogen. The following set of equations can be used to calculate both indices:

	- Maximum attainable yield Yattmax = *c*PFPNf · Nf (t, kg ha−1) (7)
		- Yield Gap YG = Yattmax − Ya (8)

$$\text{Nitrogen Gap} \qquad \qquad \text{NG} = \text{YG/cPFP}\_{\text{Nf}} \tag{9}$$

To delineate the role of PFPNf on yield, the critical value of PFPNf has to be defined in the set of data obtained. The critical PFPNf (*c*PFPNf) is calculated as the average of the third quartile (Q3) of PFPNf values measured for each crop in a particular growing season. To determine the *c*PFPNf, the calculated PFPNf values are ranked in ascending order. The third quartile comprises values above the 75th percentile. The *c*PFPNf is the average of the PFPNf values of the Q3. In the last step of the procedure, the nitrogen gap (NG) is calculated by transforming YG into the amount of the available N, but not used by the crop during the growing season [39]. The NG data can be used to prepare a graphical model of the efficiency of available N, i.e., mineral nitrogen present in the soil/crop plant system during the growing season of an actually grown crop. As shown in Figure 2, Yattmax for 32 tested fields in 2020, amounted to 8.663 t ha−1. Theoretically, at this yield level, the soil Nmin content at wheat harvest is "zero". The excess of Nmin, as indicated by negative values of NG, leads to a yield decline and vice versa. The key question is to indicate a reason for the appearance of the NG and its size. In most studied cases, it was the excess of applied Nf, concomitant with the low fertility of a soil agronomic class.

**Figure 2.** Trends in actual and maximum attainable yields in response to Nitrogen Gap in winter wheat. Legend: NG—nitrogen gap; Yattmax—maximum attainable yield; Ya—actual yield.

#### **3. Soil Factors—Limiting Crop Plant Growth**

*3.1. Growth Factors Efficiency and Yield*

A crop yield depends on its potential to take in water and nutrients in well-defined stages of its growth [43]. Three groups of factors are responsible for the exploitation of the yielding potential of a particular crop cultivar: (i) weather conditions during the growing season, (ii) soil fertility level, (iii) soil and crop managemen<sup>t</sup> systems [35,43]. Weather conditions during the growing season in non-irrigated agriculture are the strongest environmental factor, significantly affecting year-to-year variability in yields [44]. Soil productivity 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 [45]. Mueller et al. [46] classified natural factors constraining plant productivity into three main groups, comprising: (i) soil moisture and its thermal regime—directly related to weather variability during the growing season and to in-season changes in water availability in the soil profile, (ii) root growth pattern and nutrient uptake patterns, (iii) field topography. Soil fertility can be defined as the inherent soil potential for supply of air, water, and nutrients to the currently grown crop plant in the required amounts and chemical forms, necessary for exploiting its yielding potential [47]. The key question with respect to the optimum ranges of growth conditions for a currently cultivated plant on a given field cannot be simply answered. The main reason is the huge number of factors that affect plant growth during the growing season, and its subsequent yield. Wallace and Wallace [43] sugges<sup>t</sup> the existence of more than 60 factors, grouped into seven categories, including both biophysical soil properties (five groups), weather and soil, and finally crop managemen<sup>t</sup> methods. Based on these evaluations, the production outcome, i.e., actual yield (Ya) can be considered as a function of the climatic potential yield (CPY) and the efficiency of factors (E), affecting yield:

$$\text{Y} = \text{CPY} \cdot (\text{E}\_1 \cdot \text{E}\_2 \cdot \text{E}\_3 \cdot \dots \text{ E}\_{\text{n}\cdot 1} \cdot \text{E}\_{\text{n}}) \tag{10}$$

The strength of each factor's impact on yield declines in accordance with its partial fraction, approaching 1.0. The value of 1.0 for a given factor indicates its optimum status with respect to the rate of plant growth, the formation of yield components, and the eventual yield.

#### *3.2. Soil Fertility Constraints—Humus Content and Water Resources*

During the first step in nitrogen gap (NG) amelioration, it is necessary to develop a set of effective diagnostic tools for recognizing the main soil characteristics—constraints that negatively affect plant growth. The second step should be oriented to working out a set of agronomic methods, allowing for the NG cover. Four groups of growth factors require a farmer's serious attention when evaluating the strength of soil factors that limit plant growth during the growing season. They are (i) total soil moisture amount and its availability to plants, (ii) the size of the in-season mineral nitrogen pool, (iii) pool of available nutrients responsible for N efficiency to plants during the growing season, (iv) plant accessibility to all sets of nutrients within the growing season.

The most important of these factors is water managemen<sup>t</sup> before and during the growing season. World crop production systems to 60–80% depending on the amounts of water accumulated in the soil profile, strictly in the layer occupied by roots of the currently grown plant [48]. The quantity and availability of water stored in the soil profile to plants depend both on soil texture and its structure [49]). The capacity of the root zone (RZC) for water (the volumetric water capacity, VWC, at field capacity within a range of 10 and 1500 kPa suction) is measured for crop plants down to 100 cm [50]. In Europe, the RZC100 for sandy soils is in the range of 50 to 100 mm, and for loamy soils from 100 to 200 mm.

The amount of storage and available water depends to a grea<sup>t</sup> extent on the content of soil organic matter (SOM, humus). In regions, or even in fields with a high contribution of sandy soil, the best option to increase VWC is to raise the humus stock (HS) in the soil profile. This operation can be only successful if the depth of the organic layer is increased [51]. It has been well-documented that the amount and resistance of soil humus to degradation processes is a function of soil texture [52]. Loveland and Webb [53] in an extensive review showed that the minimum content of humus required to maintain soil productivity is 1.7% for sandy soil (4% of clay particles) and almost 6% for clay loam (38% clay particles). The humus content in a particular soil is, in fact, a constant value, defined by the content of total silt and total clay. Based on this assumption Piéri [54] developed a soil degradation index, termed as the humus stability index (S), whose formula is as follows:

$$\mathbf{S} = (\mathbf{H}/\mathbf{Si} + \mathbf{C}) \cdot 100 \tag{11}$$

where: S—index of soil humus stability, H—humus content (%), Si and C denote silt and clay content (%), respectively.

The S index is a simple index to determine the current status of soil degradation. Four classes of soil sensitivity to degradation, based on the S index can be applied:


The S value above nine indicates that the humus content is at an optimum to protect the stability of the soil structure. In the next step in the procedure, evaluating the status of soil humus, the humus stock gap (HSG) can be calculated [55]:

$$\text{SHS}\_{\text{SD}} = \text{OC} \cdot 1.7 \cdot 10 \tag{12}$$

$$\text{HSG} = \text{HS}\_{\Lambda} - \text{SHS}\_{\text{SD}} \tag{13}$$

where:

> SHSSD—Standardized Humus Stock, t ha−1; HSA—Actual Humus Stock, t ha−1;

HSG—Humus Stock Gap, t ha−1; OC—mean value of organic carbon content, kg m<sup>−</sup>2; 1.7—constant used to recalculate the OC content into humus;

10—constant, recalculating kg m<sup>−</sup><sup>2</sup> into t ha−1.

The yield gap/gain (YG/G), i.e., yield loss or gain, based on the humus content, can be calculated based on the formula:

$$\text{YG}/\text{YG} = \text{HSG} \cdot 15.6 \tag{14}$$

where: 15.6—constant, recalculating HSG into grain yield [56].

The OC data for the SHSSD calculation with respect to European soils were based on data reported by Batjes [57]. The average content of humus in Luvisols in the soil layer of 0.0–0.3 m is 85 t ha−1, increasing up to 154.7 t ha−<sup>1</sup> in a soil profile of 1.0 m. In Cambisols, the respective values are 117.3 and 200.6 t ha−1. Both figures are low as compared with Chernozems, for which the respective values are 153 and 374 t ha−1. The simple calculation of HSG shows that a net increase in the humus stock of 1 g m<sup>−</sup>2, which is equal to 17 t ha−<sup>1</sup> of humus, results in a yield increase of 265.2 kg ha−1. The potential yield increase can to a grea<sup>t</sup> extent be explained by the higher water-holding capacity of humus. As reported by Libohova [58] 1.0 g of humus holds up to 1.5 of water.

The main reason for the degradation of humus stock (HS) in arable soils is the rapid mineralization rate of the labile organic carbon pool, irrespective of soil managemen<sup>t</sup> [59]. This process is accelerated by intensive NPK fertilization and soil plowing [60]. The regeneration of the HS in arable soil is a long-term process. The most effective amelioration strategies oriented towards an HS increase in arable soils, tested in long-term trials, rely mostly on intensive manure application. In European soils, as reported by Powlson et al. [61], expectations regarding the effect of manure are rather low. A yearly application of 10 t manure over 90 years can raise the humus content in a soil layer of 0.3 m

only by 4.8%. As reported, however, by Szajdak et al. [62], a yearly application of 30 t ha−<sup>1</sup> of manure to light soil over 38 years doubled the humus content. Despite the HS increase, no differences in rye yields were recorded compared to the effect of NPK application alone. The main practical disadvantage of this approach to HS increase, even in mixed farming, is its theoretical quality. This solution is not realized in farming practice due to a lack of manure. The option, applied in intensive agriculture, oriented only towards crop plant production, is the managemen<sup>t</sup> of straw directly in the field. As frequently reported, this method of straw managemen<sup>t</sup> can both increase the HS and yields of succeeding crops [63].

#### *3.3. Nutrient Availability and Crop Plant Accessibility to the Nutrient Pools*

The agronomic term nutrient availability refers to the amount of a particular nutrient taken up by the currently grown crop within a single growing season. Chemical tests of extractable nutrients are only an approximation of the amount of a given nutrient which potentially can be taken up by the crop plant [64]. In addition, the content of available nutrients is, as a rule, determined in the upper soil, limited usually to a layer of 0.2 m [65]. The term accessibility refers to the crop plant's access to soil pools of attainable nutrients within the growing season [64]. Plant access to a respective nutrient pool depends on the rate of root system growth, which is driven by the hormonal status of a plant, which to a grea<sup>t</sup> extent depends on plant access to nitrate nitrogen. A decreased supply of N-NO3 to the aboveground plant parts affects the pattern of dry matter partitioning, leading subsequently to an increase of its investment into roots [66,67]. This crop plant strategy is oriented towards the capture of water, nitrogen, and nutrients supporting their use efficiency. It prevails in regions and soils sensitive to temporary water shortages [68,69].

The observed trends of crop plant response to irrigation are fully corroborated by the fact that ample water supply is a decisive yield factor, providing an optimum supply of nutrients, mainly N [46]. As shown in Figure 3, the yield of spring triticale decreased in accordance with the decreased amount of available water. However, the absolute and relative yield decrease, i.e., YG and YGf were much lower under K fertilized treatment. The main reason for the observed trend variability was the impact of K application on WUE. As a rule, the WUE-Eta trend reflected the trend of Ya, very well, but its steepness was lower on the K fertilized plots. The WUE-WLY indices showed different trends of dependence on K treatment. The index value, under conditions of K fertilizer application, increased in the opposite direction to the quantity of supplied water, i.e., from 23 kg grain mm<sup>−</sup><sup>1</sup> on the irrigated plot to almost 39 kg grain mm<sup>−</sup><sup>1</sup> on the plot with the artificial drought imposed during the stem elongation stage of triticale. It can be concluded that under natural precipitation, the yield gap can be ameliorated, at least partly, through the supply of nutrients like K, which exert a significant impact on water and nitrogen managemen<sup>t</sup> by crop plants [26,70].

Fertilizer recommendations, except for mineral N (Nmin), do not consider the content of available nutrients in the sub-soil. The total content of the majority of nutrients, taking K as a classic example, depends on the content of clay minerals [71,72]. The content of available nutrients is also sensitive to other soil characteristics, for example, soil pH (phosphorus, micronutrients); manure application, and the content of organic matter (nitrogen, phosphorus, micronutrients); fertilization, and cropping sequence (nitrogen, phosphorus) [65,71–75]. The sub-soil has numerous functions; as a source of water, nitrogen, available pools of other nutrients, and as a natural milieu for the plant root system [76,77]. As shown in Figure 4, crop plants can penetrate the soil for K down to a depth of 0.90 m of the soil profile. In the presented case, the strongest soil depletion with the CaCl2-extractable K was recorded for winter oilseed rape. This phenomenon is corroborated by the fact that this crop has an extremely high requirement for K during the spring vegetation [78]. The same phenomenon was observed for phosphorus. As reported by Łukowiak et al. [79], crop plants can exploit the CaCl2-extractable P down to 0.9 m of the soil profile. The authors of this study documented that the recovery of 60% of the available P pool was concomitant with the highest yield of winter oilseed rape (WOSR). This figure may seem

shocking, but it refers to the P content in the soil solution. An open question remains as to the contribution of the sub-soil P pool in the total P taken up by the currently grown plant. In the case of seed crops, for example, WOSR, an important part of P is taken up by plants following the onset of flowering [80]. A permanent application of P fertilizers, as documented for long-term experiments, leads to the enrichment of the sub-soil with P. As a consequence of this operation, this pool becomes a considerable source of P for high-yielding crops [81]. It can be, therefore, concluded that chemical tests for the soil pools of nutrients in the subsoil cannot be limited only to the Nmin content [82,83]. It has been recently documented that the simultaneous determination of Nmin and some other key nutrients in the CaCl2-solution is a source of knowledge of both their pools and the occurring relationships between them [82,83].

**Figure 3.** Effect of water treatments and potassium managemen<sup>t</sup> on indices of water use efficiency (based on [26]. Legend: IR, RF—irrigated and rainfed water treatments; FK+M, ST+H—water shortage imposed at \* stem elongation + heading; \*\* flowering + early milk. WUE—water Use Efficiency; Eta—calculated based on evapotranspiration; WLY—calculated based on FAS approach [33].

**Figure 4.** Status of CaCl2 extractable K during the growing season in three consecutive years (author's own result; unpublished). Legend: a, b, c—soil layers of 0–0.30, 0.30–0.60, 0.60–0.90 m; WW—winter wheat; WR—winter rye; WOSR—winter oilseed rape; \*the same set of letters indicates a lack of significant difference between the treatments.

The vertical trends in nutrient content variability need to be considered when working out fertilization recommendations. It has been well-documented in literature that the subsoil significantly impacts both the profile of crop rooting and in consequence the uptake of water and nutrients [76]. Rooting depth is not a constant pattern, even for the same crop. It changes due to the impact of numerous biophysical, environmental, and also soil and crop managemen<sup>t</sup> factors [84]. The rate and habit of the root system, similarly to the shoot, undergo temporal changes during plant development and in response to its nutritional status [85]. The depletion of N-NO3 at the onset of WOSR flowering in the soil layer of 0.9 m depth is a prerequisite of high yield [80]. The efficient uptake of NO3 − ions depends on the respective concentration of K+ in the soil solution [86]. For the lowyielding WOSR plantation P resources in the vegetative organs at the onset of flowering are sufficiently high to cover the requirements of the growing seeds. A high-yield of seeds can be achieved, but only provided there is efficient remobilization of P from vegetative tissues, and its simultaneous uptake from the subsoil [77,79,87]. It is necessary to take into account two other important facts. The first refers to the growth status of the root system. The onset of flowering results in the progressive root system dying, i.e., the rate of root mortality is higher than the appearance of new roots [64,88]. It is necessary to stress that the uptake of both, K and P depends to a much greater degree on the root elongation rate than on the concentration of both ions in the soil solution [89]. So far, the routine fertilizer recommendations have neglected the vertical variability of factors responsive to nutrient uptake by crop plants. This knowledge gap is one of the key reasons for the differences in the prognosis of crop production intensification in a sustainable way.

#### **4. The In-Season Management of Nitrogen—Cardinal Growth Stages**

The first task in the reorientation of the crop production system is to calculate the total requirement of a currently grown plant for nitrogen. This can be calculated for an average yield harvested on a particular field or based on the potential yield of a given cultivar in the same climatic region. Two additional components have to be taken into account to make a reliable estimation of the total N requirement by the currently grown cultivar. The first is nitrogen concentration in the main product, for example, seeds or grain. There is still ongoing scientific discussion with respect to the extent to which N concentration in seeds or grain is a conservative, i.e., genetically, or environmentally governed trait [90–92]. The second component refers to the partitioning of N taken up by the crop between the main yield, and its by-product, for example, between grain and straw. At harvest, this process refers to the value of the nitrogen harvest index (NHI), which is a conservative trait of seed crops [11,93].

Total N input (Ni) in the soil/crop system for an assumed yield of grain/seeds is calculated based on the algorithm:

$$\text{N}\_{\text{i}} = (\text{Y}\_{\text{CPY}} \cdot \text{G}\_{\text{Nc}}) / \text{NHI} \tag{15}$$

where:

> Ni—nitrogen input, kg ha−1;

YCPY—climatic potential yield of the grown cultivar, kg ha−1;

GNc—grain/seed nitrogen concentration, kg <sup>t</sup>−1;

NHI—nitrogen harvest index, a value in the range of 0.6–0.8.

The key objective of nitrogen fertilizer (Nf) application is to synchronize its application time with the crop plant requirement. The dominant factor is the stage of plant growth and the required content of N, which progressively increases with the crop growth. The right determination of the Nf dose in the critical stage of yield formation is, therefore, the decisive factor in the exploitation of the yielding potential of the currently cultivated crop. The crop demand for N in a particular growth stage depends on the rate of plant biomass growth, primarily driven by temperature and water supply [94]. The sum of physiologically active temperatures (GDD), and water and nitrogen supply are major factors for the quantity of biomass produced by the crop during the respective phase [95]. The rate of seed crop

growth throughout the vegetative season is not constant. Based on this criterion, three mega-phases can be distinguished, named as canopy foundation (CF), yield component construction (YCC), and yield realization (YR) [96]. The first two periods describe the vegetative part of the plant life cycle and the third one its reproductive phases (Figure 5). The shape of the dry matter accumulation curve can be described mathematically using very sophisticated models [97]. In cereals, the CF period, extending from sowing up to the end of tillering, is responsible for the number of tillers per plant. The course of dry matter accumulation is best described by the exponential regression model. The YCC period, extending from the beginning of stem elongation up to flowering, is responsible for the set of flowers. The rate of dry matter accumulation during this period is best described by the linear regression model. The dry matter yield of wheat at the end of the CK2 can be used to make a prognosis of grain yield [98].

**Figure 5.** A conceptual pattern of dry matter accumulation by a typical seed/grain crop. Legend: CK1, CK2—cardinal stage 1 and 2, respectively (author's own concept).

The borderline stages of plant growth, which occur between the mega-phases of CF and CYC, and between the CYC and YR periods, can be named Cardinal Knots (CKs), i.e., CK1 and CK2, for the first and second borderline of consecutive mega-periods, respectively. These two CKs are decisive stages for yield component formation. For example, as shown in Figure 6, the content of soil nitrate-nitrogen (NN) during the YCC period of oilseed rape undergoes a strong depletion (=N uptake by WOSR during the YCC period). The recorded NN depletion significantly affected the seed density, which was the key yield component, determining seed yield (R<sup>2</sup> = 0.89, *p* ≤ 0.001). What is most important, however, is the fact, that the dependence obtained clearly defines the rosette stage (BBCH 30) as the decisive stage for the yield prognosis (NNop = 163.3 kg ha−<sup>1</sup> for Yamax = 77.6 · 1000 seeds m<sup>−</sup>2). The result obtained indicates that in farming practice, the time of Nf application has to precede the BBCH 30. In maize, the second rate of Nf is applied, based on Nmin determination, at the 5th leaf stage [99,100].

The yield realization (YR) period commences from the onset of flowering and persists up to the physiological maturity of the plant. It can, however, be divided into two parts. The first part extends from flowering up to the watery stage of the seed/grain plant growth, i.e., to BBCH 71 (15% of seed/grain DW). It has well been documented that nitrogen supply to a seed crop, like cereals and oilseed rape, significantly affects the degree of yield component expression. The N pool accumulated by the seed plant during its vegetative growth, i.e., before flowering, considerably impacts the number of seed/grain per field unit area (physiological sink capacity) [101–103]. The second part of the YR period, which begins from the early milk-stage (BBCH 72) and finishes at physiological plant maturity (BBCH 89/90), is termed as the grain/seed filling period (GFP, SFP). The course of dry matter accumulation can be described by different mathematical models, but the linear or quadratic dominate. During this particular period, grain/seed reaches its final individual weight [104].

**Figure 6.** The response of seed density of winter oilseed rape to the content of nitrate nitrogen at the rosette stage and its uptake by the crop up to flowering. (based on [80]. Legend: NN- the content of nitrate nitrogen at BBCH 30; ΔNN—the change of the NN content during the period extending from the rosette up the flowering stage of WOSR growth.

Efficient in-season N management, including knowledge of Nmin resources, should be oriented towards covering the plant N requirements during the period extending from the onset of flowering to the physiological plant maturity. For the seed crops, 75–85% of the N finally accumulated in seeds/grains originates from the pre-flowering resources, i.e., present in vegetative plant parts [90,105]. Post-flowering N managemen<sup>t</sup> by the crop canopy can be described by three algorithms:


where:

> Nhv—N amount in vegetative organs of crop canopy at harvest, kg ha−1;

Nfl—N amount in vegetative organs of crop canopy at the onset of flowering, kg ha−1; Nt—total N amount in crop canopy at harvest, kg ha−1.

The patterns of N accumulation by the plant between particular CKs during the growth of a crop are the basis for a build-up of an efficient strategy of the in-season N status correction. Any free choice of Nf timing and its dose, as frequently observed in classic or even modern fertilization programs, does not fit the crop requirements for N, being the main reason for its inefficiency. A sound strategy of N managemen<sup>t</sup> in seed crops, despite an almost similar accumulation pattern throughout the life cycle, is crop-specific. For example, in bread wheat, the key period of yield component formation extends from CK1 to CK2. During this period, the requirement for N results from both (i) the number of grain per unit area, and (ii) the required protein content in grain [106]. Consequently, a nitrogen fertilization strategy based on the correction of the plant N status in both CK1 to CK2 should also take into account protein concentration in grain. As a rule, any increase in the number of grains per unit field area results in a protein concentration decrease [107]. Therefore, any fertilization strategy, oriented to the increase in the crude protein concentration, requires an extra Nf dose, which should be applied at the end of the CK2. In maize, its nutritional status at the 5th leaf stage, which slightly precedes CK1, is decisive for the degree of yield component expression [108,109]. Nitrogen fertilizer should be applied just at such a time preceding this cardinal stage of maize growth because it affects the potential number of leaves and cobs. Nitrogen status in maize at the CK2, before the beginning of flowering, is important for the yield development, but it has only a predictive value [110]. In farming practice, it makes no sense to apply Nf at this particular stage because the yield was already fixed in much earlier stages of maize growth.

Nitrogen efficiency depends on the supply of other nutrients needed for its uptake and utilization [70,111–113]. It is necessary to pay attention to the fact that the accumulation of K by major crop plants, like wheat, oilseed rape, sugar beets, or potato, is as a rule higher as compared to N [114,115]. The maximum K uptake by high-yielding WOSR reaches its maximum during the phase of the main stem elongation [77,78]. It can, therefore, be concluded that an efficient uptake of K from the subsoil by some crops, in comparison to N, is a necessary condition for the effective uptake of nitrogen. As recently reported by Grzebisz et al. [80], the efficient uptake of NO3 - ions by WOSR depends on the adequate concentration of K and other nutrients, such as Ca and Mg in the sub-soil. All these nutrients are responsible for the development of yield components by crop plants.

One of the most important priorities in the breeding of crop plants is to increase the uptake efficiency of nutrients, especially of N and P from soil. Efficient acquisition of water and nutrients is required for the realization of both production and environmental goals. The efforts of key breeders have recently focused on the improvement of root system traits through [116–119]:


#### **5. Yield Gap Recognition and Diagnosis of Limiting Factors**

An efficient N managemen<sup>t</sup> strategy should be based on three major variables that affect the plant growth of a particular crop. Yield variability within a field is a result of (i) the stage of a crop plant growth, (ii) spatial variability in N uptake by plants, (iii) vertical variability in soil N pools, and a plant's access both to these pools and other nutrients responsible for N use efficiency. It is necessary to assume that the expression of yield components is a result of the growth pattern of a crop plant encoded in its early stages [80,120]. The principal difficulty in determining the right Nf dose is the number and strength of plant growth limiting factors with respect to their spatial variability on the field. Yield, in fact, its spatial variability within a field, is the ex-post result of (i) the degree of yield constraints recognized during the growing season, (ii) the efficiency of production measures applied to ameliorate constraints limiting plant growth and yielding. The spatial variability of yield is the main reason for the necessity for dividing the entire field area into zones that differ considerably in productivity [121]. The key challenge is to find a criterion for the particular field division into zones of the same level of productivity.

The target of modern agriculture is to work out and implement a set of highly reliable diagnostic tools which will be capable of defining the methods and approaches to the efficient use of Nf, that are in accordance with the concept of sustainable agriculture [21,122]. This concept, taking the field as the key production unit, is based on three main objectives:

(1) fulfilling the food production gap, in fact, ameliorating the nitrogen gap;

