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Article

Evaluation of Nitrogen Fertilizer Supply and Soil Nitrate Thresholds for High Yields of Foxtail Millet

by
Yiwei Lu
1,†,
Yu Zhao
1,†,
Xueyan Xia
1,†,
Meng Liu
1,
Zhimin Wei
1,
Jingxin Wang
1,
Jianjun Liu
2,
Jihan Cui
1,* and
Shunguo Li
3,*
1
National Foxtail Millet Improvement Center, Key Laboratory of Characteristic Grain Genetics and Utilization, Ministry of Agriculture and Rural Affairs, Hebei Coarse Cereal Research Laboratory, Institute of Millet Crops, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang 050035, China
2
Hebei Academy of Coarse Cereal Industry Technology, Handan 056000, China
3
Hebei Academy of Agriculture and Forestry, Shijiazhuang 050000, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agriculture 2024, 14(10), 1711; https://doi.org/10.3390/agriculture14101711 (registering DOI)
Submission received: 13 August 2024 / Revised: 25 September 2024 / Accepted: 26 September 2024 / Published: 29 September 2024
(This article belongs to the Section Crop Production)
Browse Figures
Versions Notes

Abstract

:
Foxtail millet is an important cereal crop in the North China Plain. However, excessive nitrogen fertilizer application over the years has led to declining yield and soil quality. This study investigated nutrient management strategies for foxtail millet based on crop yield levels and soil nutrient availability. In a field where targeted fertilization was conducted over six seasons, nitrogen fertilization effects and the dynamics of soil-available nitrogen were monitored continuously for two consecutive years (2022–2023) across five different foxtail millet varieties with varying yield levels. The study aimed to determine the optimal nitrogen application rate for achieving a high yield of foxtail millet, the minimum soil nitrate threshold required to maintain soil fertility, and the effective nitrogen application rate range for sustaining soil-available nitrate levels. Results showed that fertilization significantly affected dry matter weight during flowering, while variety affected dry matter weight at maturity. The average nitrogen application rate for achieving high yield across all five millet varieties was 141.3 kg·ha−1. Specifically, the average nitrogen application rate of nitrogen-efficient varieties achieving high yield (5607.32–5637.19 kg·ha−1) was 151.5 kg·ha−1, while the average nitrogen application rate of nitrogen-inefficient varieties achieving high yield (4749.77–4847.74 kg·ha−1) was 134.5 kg·ha−1. Soil NH4+-N and NO3−-N content increased when nitrogen application rate exceeded 360 kg·ha−1, posing environmental risks. To achieve high yield, soil nitrate levels would be maintained at an average of 17.23 mg·kg−1 (before sowing) and 9.75 mg·kg−1 (at maturity). A relationship between soil nitrate and nitrogen application rate was established: y = 867.5 − 50z (where y represents the optimal nitrogen application rate for high yield (kg·ha−1), and z represents soil NO3−-N content in the 0–20 cm layer before sowing, ranging from 10.0 to 17.35 mg·kg−1), which provided a practical method for nitrogen fertilization to achieve high yield of foxtail millet. In this study, the fertilization strategy was optimized according to soil nutrient level and yield targets, and the nitrogen application rate was controlled within 360 kg·ha−1 based on the soil nitrate nitrogen content, which will be instructive for reducing fertilizer use, maximizing fertilizer efficiency, and increasing yield.

1. Introduction

Foxtail millet (Setaria italica (L.) P. Beauv.) is one of the oldest and most important domesticated crops globally. Before the prevalence of rice and wheat, it served as a staple food source in Asia, including China, Japan, India, and Korea, as well as across the Eurasian continent [1]. Its nutritional growth process demands appropriate levels of nitrogen [2]. Nitrogen deficiency often inhibits foxtail millet growth in field production. Optimal nitrogen levels significantly enhance its growth, increasing grain yield and quality [3,4]. Globally, the planting area of foxtail millet is about 1.8 million hectares. The cultivation of foxtail millet involves complex processes and relies heavily on manual labor. Small-scale farmers constitute a significant proportion of foxtail millet growers. These smallholder farmers face challenges such as high fertilizer consumption for grain production, high resource and environmental costs, and low nutrient utilization efficiency. Increasing nitrogen fertilizer application rate is the simplest and quickest method to enhance crop yield [5,6]. However, despite nitrogen fertilizer’s potential to significantly improve crop productivity and quality, excessive nitrogen application rates and low efficiency have led to serious environmental issues such as soil nutrient imbalances, pollution, nitrogen runoff, and substantial greenhouse gas emissions [7,8,9]. These issues result in high soil nitrogen accumulation, significant nitrogen leaching losses [10], and the increase in nitrate concentration in groundwater, posing threats to crop safety and sustainable production [11,12]. Therefore, optimizing nitrogen fertilizer management is crucial for achieving agricultural sustainability.
Ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3−-N) are two distinct forms of soil nitrogen and the primary forms utilized by plants. They are core focal points for studying soil nitrogen fertility and plant nitrogen uptake [13]. With increasing nitrogen application rates, levels of NH4+-N and NO3−-N tend to rise, leading to leaching in the 40–60 cm soil layer when nitrogen application is excessive. Previous studies have indicated that collecting soil samples at a certain depth (within the root absorption capacity of crops) and utilizing inorganic nitrogen (NO3−-N and NH4+-N) during the vigorous growth stage of crops to accommodate nitrogen fertilizer recommendations based on soil nitrogen levels is feasible [14]. This approach has been applied to wheat [15], maize [16], cotton [17], and other crops, where the optimal nitrogen application rate varies among crops due to differences in nutrient requirements and biomass accumulation levels.
Optimizing nitrogen fertilizer management not only addressed crop yield issues but also mitigated fertilizer misuse and soil nitrogen residue, thereby achieving sustainable agricultural development. However, previous studies recommending appropriated nitrogen application rates based on soil nitrogen levels have mostly focused on field crops and cash crops, with limited reports on millet. Therefore, this study used different nitrogen varieties (some high-efficiency varieties, including Jigu 20 (JG20) and Henggu 17 (HG17), and some low-efficiency varieties, including Zhonggu 9 (ZG9), Jigu 16 (JG16), and Jigu 39 (JG39)) as materials and conducted a two-year experiment to explore the effects of different nitrogen fertilizer levels on millet growth, yield, and soil nitrogen levels, as well as the impact of varying nitrogen fertilizer levels on soil nitrate nitrogen thresholds. The study also examined the relationship between soil nitrate nitrogen and nitrogen fertilizer levels while ensuring high millet yields. The objectives of this research were (i) to clarify the effects of nitrogen fertilizer application rate and the dynamics of soil-available nitrogen, (ii) to explore the optimal nitrogen application rate and minimum soil nitrate nitrogen threshold required to achieve high yield of foxtail millet, and (iii) to explore a fertilization method that balances high yield of foxtail millet with environmental friendliness in fertilizer application, aiming to provide a practical and efficient fertilization strategy for production.

2. Materials and Methods

2.1. Study Sites

The study was conducted at Gaocheng Experimental Station of Institute of Millet Crops, Hebei Academy of Agriculture and Forestry Sciences (114°46′56.129″ E, 37°55′28.199″ N, elevation 50 m) from 2022 to 2023 (Figure 1). The experimental field was established in 2019 and had undergone six growing seasons with fixed fertilizer gradients, cultivating winter wheat and summer foxtail millet. The region experiences a warm temperate semi-humid continental monsoon climate, predominantly featuring cinnamon soil. Annual average precipitation was 494.0 mm, primarily occurring in July and August, while the average annual temperature was 12.5 °C, with a frost-free period lasting 190 days. In 2022, the plow layer’s soil fertility was characterized by a total nitrogen content of 1.31 g·kg−1, a pH of 7.78, an available phosphorus content of 22.46 mg·kg−1, an available potassium content of 91.67 mg·kg−1, and an organic matter content of 15.92 g·kg−1.

2.2. Experimental Design and Project Measurements

The previous crop in the experimental field was wheat. The experiment employed a randomized complete block design with 5 main plots representing different nitrogen (N) fertilizer treatments: N0 (0 N kg·ha−1), N6 (90 N kg·ha−1), N12 (180 N kg·ha−1), N24 (360 N kg·ha−1), and N36 (540 N kg·ha−1) [18,19]. Each main plot consisted of subplots for 5 foxtail millet varieties: nitrogen-efficient varieties JG20 and HG17, and nitrogen-inefficient varieties JG39, ZG9, and JG16. The nitrogen recovery rates for different millet varieties are detailed in Table S1. The study comprised a factorial arrangement of 5 × 5 × 2 (5 N rates × 5 foxtail millet varieties × 2 years) in a total of 50 treatments, each replicated three times. All treatments received consistent levels of P2O5 (105 kg·ha−1) and K2O (75 kg·ha−1). The sources of N, P, and K were urea (46.4% N) (Shanxi Aoweiqianyuan Chemical Co., Ltd., Xinzhou, China), calcium superphosphate (12% P) (Guling Fertilizer Co., Ltd., Gejiu City, China), and potassium sulfate (50% K) (Luxi Chemical Group Co., Ltd., Liaocheng, China), respectively. Fertilization was carried out twice a year, applied as a base fertilizer before the sowing of millet and wheat. After soil incorporation, sowing was performed. Foxtail millet was sown in late June each year, with each plot covering an area of 60 m2, a row spacing of 0.4 m, and a plant density of 600,000 plants·ha−1. Protective rows were established between different fertilization levels to prevent interference between treatments. Field management practices followed conventional production methods, and samples were collected on 20 September during the maturity period of millet.
At the heading, flowering, and maturation stages, six millet plants were randomly selected from each subplot for three replications. These plants were divided into roots, stems, leaves, and panicles, then dried and weighed. At maturity, a sample plot from each treatment was harvested to assess the yield, with each plot manually harvested over an area of 1.6 m2 and the yield converted to per hectare.
Soil samples were collected from different millet variety plots at different fertilization levels at a depth of 0–60 cm (with 0–20 cm as one layer) before sowing and at maturity, with three repetitions. These samples were extracted with 2 mol·L−1 potassium chloride (KCl) for the determination of soil ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3−-N) levels using an AMS Alliance continuous flow analyzer [20]. The residual soil was air-dried, finely ground, and sieved through a 2.0 mm mesh. The soil’s pH was measured in a 1:2.5 water–soil mixture using a Seven Compact pH meter [21]. Available phosphorus was quantified in soil treated with 0.50 mol·L−1 sodium bicarbonate (NaHCO3) using the same continuous flow analyzer. Exchangeable potassium was extracted with 1.0 mol·L−1 NH4OAc and measured via flame photometry [22]. Organic matter was treated with a solution of potassium dichromate-sulfuric acid (K2Cr2O7−H2SO4) at 0.8 mol·L−1 and determined by a titration method [23].

2.3. Statistical Analysis

A combined variance analysis was conducted using the data processing system DPS 9.05. The minimum significant difference (Duncan) at the 0.05 and 0.01 probability levels was employed to assess the significance between the independent and dependent variables. Histograms, scatter plots, and Pearson correlation analyses were generated in Origin Pro 2022 (Origin Lab Co., Ltd., Northampton, MA, USA). Linear plus platform model analysis was conducted using SPSS 25.

3. Results

3.1. Agronomic Traits under Different Nitrogen Application Levels

Except for dry matter accumulation after flowering (DMAA), all traits showed highly significant differences based on variety and fertilization levels (Table 1). The dry weights of flowering stems and leaves (FST), flower spikes (FSP), and flowering dry matter (FDM) were significantly affected by fertilization (FFST = 15.1, FFSP = 12.7, FFDM = 14.9). The dry weights of mature stems and leaves (MST), mature spikes (MSP), and mature dry matter (MDM) were significantly affected by variety (FFST = 12.6, FFSP = 10.0, FMDM = 12.6). DMAA was mainly influenced by variety. With increasing nitrogen application, the averages of FST, FSP, FDM, MST, MSP, MDM, and DMAA performed better in the N12 treatment (180 N kg·ha−1), significantly increasing by 24.32%, 18.37%, 22.50%, 20.93%, 16.33%, 18.84%, and 13.79%, respectively, compared to the N0 treatment. The DMAA of ZG9 and JG16 was higher than that of JU20 and HG17, with ZG9 and JG16 exceeding JU20 by 6.5% and 13.5%, respectively, and ZG9 and JG16 exceeding HG17 by 1.55% and 10.85%, respectively, although these differences were not statistically significant (p < 0.05). The effect of different planting years on millet plant growth was inconsistent, with DMAA in the 2022 growing season being 1.37 times higher than in the 2023 growing season.

3.2. Grain Yield of Foxtail Millet under Different Nitrogen Application Levels

As the nitrogen application rate increased, the yield of the five varieties initially rose and then declined in two years (Figure 2a,d). In 2022, yield (4721–6222 kg·ha−1) under the N6 and N12 treatments surpassed the N0 treatment by 5.59% and 23.71% (Figure 2a). In 2023, yield remained between 5065 and 6034 kg·ha−1 under the N12, N24, and N36 treatments (Figure 2d). The yield of foxtail millet varied among different varieties. Varieties JG20 and HG17 consistently produced higher yields than others (Figure 2b,e). Yield disparities were noted among various fertilizer treatments. In 2022, N12 treatment was recorded with the highest average yield (5396.44 kg·ha−1), marking an increase of 1.27% to 11.10% compared to other treatments (Figure 2c), and in 2023, N12 treatment was recorded with the highest average yield (5428.76 kg·ha−1), marking an increase of 0.37% to 28.62% compared to other treatments (Figure 2f).

3.3. Yield Related Traits under Different Nitrogen Application Levels

The combined analysis of variance showed that, except for the number of spikes per acre (SN), all traits exhibited significant differences related to variety and fertilization (Table 2). SN was primarily influenced by variety. Spike weight (SWE) and grain weight (GWE) were mainly affected by year and variety. Yield was primarily influenced by fertilizer and variety. As nitrogen application increased, SN showed a trend of first increasing and then decreasing, with a 6.99% increase in SN under the N12 treatment (180 N kg·ha−1) compared to the N0 treatment. Both SWE and GWE were highest under the N36 treatment (540 N kg·ha−1), while yield reached its peak under the N12 treatment, exceeding the N0 treatment by 4.45%. Thus, millet yield was influenced by fertilizer and variety, as well as by the number of spikes per acre in the field.

3.4. Relationship between Yield and Nitrogen Fertilizer Application Levels

By fitting the nitrogen application rates and yields of different varieties, the optimal nitrogen requirement for five millet varieties in 2022 was determined to be between 59.5 kg·ha−1 and 129.4 kg·ha−1, with yields ranging from 4530.5 kg·ha−1 to 5927.4 kg·ha−1. However, the R2 values for nitrogen application and yield for HG17 and ZG9 were 0.015 and 0.011, respectively, so these two varieties are not considered at this time (Figure 3b,c). In 2023, the optimal nitrogen requirements for JG20, HG17, ZG9, JG16, and JG39 were determined to be between 128.8 kg·ha−1 and 155.3 kg·ha−1, with yields varying from 4728.9 kg·ha−1 to 5885.8 kg·ha−1. The average nitrogen application for high-yielding millet varieties was 141.3 kg·ha−1. Among them, the high nitrogen efficiency varieties had yields between 5607.32 kg·ha−1 and 5637.19 kg·ha−1, with an average nitrogen application of 151.5 kg·ha−1, while the low nitrogen efficiency varieties yielded between 4749.77 kg·ha−1 and 4847.74 kg·ha−1, with an average application of 134.5 kg·ha−1.

3.5. Soil NH4+-N and NO3−-N Content before Sowing and at Maturity

A two-year integrated analysis of soil NH4+-N content revealed that with nitrogen application rate below 360 kg·ha−1, NH4+-N levels in the 0–60 cm soil depth before sowing and at maturity remained low in 2022–2023. However, levels increased when the nitrogen application rate exceeded 360 kg·ha−1. Notably, the NH4+-N content before sowing at a depth of 40 to 60 cm was 23.0% to 65.2% higher than in other treatments (Figure 4a,e). At maturity, the NH4+-N content in the 0–60 cm soil depth was 20.71% to 54.67% higher than in other treatments (Figure 4b,f).
The two-year integrated analysis of soil NO3−-N content demonstrated that when nitrogen application rate was between 360 kg·ha−1 and 540 kg·ha−1, the soil NO3−-N content before sowing was 0.84 to 10.03 times higher than in other treatments in 2022. When nitrogen application rate exceeded 360 kg·ha−1, the soil nitrate nitrogen was surplus (Figure 4c). In 2023, soil NO3−-N content in the 0–20 cm depth before sowing increased progressively when nitrogen application rate exceeded 180 kg·ha−1, being 16.87% higher than the N0 treatment (Figure 4g). With nitrogen application rate under 180 kg·ha−1, soil NO3−-N levels at maturity decreased with greater soil depth, showing a 1.11 to 1.28 times reduction at 60 cm compared to 20 cm. Conversely, when nitrogen application rate exceeded 360 kg·ha−1, soil NO3−-N content was 1.69 to 10.02 times higher than the N0 treatment (Figure 4h), indicating enhanced migration to deeper layers and posing environmental risks.

3.6. Relationship between Soil NO3−-N Content and Yield under Different Nitrogen Application Levels

We fitted the soil NO3−-N content in the 0–20 cm layer before sowing and at maturity with the corresponding yield of foxtail millet in 2023 (Figure 5). Achieving a high yield of foxtail millet and stable soil nutrient output was generally realized when the soil NO3−-N content ranged from 15.68 mg·kg−1 to 19.43 mg·kg−1 before sowing and from 8.60 mg·kg−1 to 11.90 mg·kg−1 at maturity, with an average content of 17.23 mg·kg−1 (before sowing) and 9.75 mg·kg−1 (at maturity).
High yields of foxtail millet were achieved when soil NO3−-N levels of nitrogen-efficient varieties JG20 and HG17 ranged from 16.10 to 17.70 mg·kg−1 (average value 16.9 mg·kg−1) before sowing and from 8.90 to 9.60 mg·kg−1 (average value 9.25 mg·kg−1) at maturity. For nitrogen-inefficient varieties JG39 and ZG9, high yields were achieved when soil NO3−-N levels ranged from 15.68 to 19.43 mg·kg−1 (average value 17.56 mg·kg−1) before sowing and from 8.6 to 11.90 mg·kg−1 (average value 10.25 mg·kg−1) at maturity.

3.7. The Relationship between Optimal Nitrogen Application Levels and Soil Nitrate Availability

Performed fitting was applied to analyze the relationship between nitrogen application rate, the yield from 2022, and the soil NO3−-N content in the 0–20 cm depth before sowing in 2023 (Figure 6). The fitted equation for nitrogen application rate and pre-sowing NO3−-N content was z = 0.02x + 12.35 (where x and z represented nitrogen application rate and NO3−-N content, respectively). The equations modeling the relationship between nitrogen application rate and yield for JG20, HG17, ZG9, JG16, and JG39 were y = −0.01x2 + 6.83x + 5186.87 (JG20); y = (4.55 × 104)x2 − 0.57x + 5577.41 (HG17); y = −0.008x2 + 3.04x + 4470.36 (ZG9); y = −0.007x2 + 2.69x + 4696.02 (JG16); y = −0.002x2 + 1.65x + 5123.07 (JG39), where x and y denoted nitrogen application rate and yield, respectively (Figure 6a–e). The fitted nitrogen application rates were 959 − 50z, 1250.83 − 50z, 807.5 − 50z, 809.5 − 50z, and 1030 − 50z kg·ha−1 for each variety (z being the soil NO3−-N content before sowing), offering optimized fertilization strategies for high-yield foxtail millet. Without distinguishing between varieties, the general equation for nitrogen application rate and yield was y = −0.006x2 + 3.00x + 4982.66, where x and y denoted nitrogen application rate and yield, respectively (Figure 6f). The fitted nitrogen application rate for high yield potential was 867.5 − 50z kg·ha−1 (10 < z < 17.35), providing a straightforward reference for high-yield fertilization management of foxtail millet (Figure 6g).

4. Discussion

4.1. High Yield of Foxtail Millet Depended on Rational Nutrient Management

Differences in grain yield among various varieties result in varying fertilizer requirements. Therefore, understanding the characteristics of varieties in terms of yield and nutrient utilization is crucial for optimizing agricultural production [24]. In this study, the average nitrogen fertilizer application rate for achieving high yields across five foxtail millet varieties was 141.3 kg·ha−1. Specifically, nitrogen-efficient millet varieties achieved high yields with an average nitrogen fertilizer application rate of 151.5 kg·ha−1, Nitrogen-inefficient millet varieties achieved high yields with an average nitrogen fertilizer application rate of 134.5 kg·ha−1, which was correlated with their inherent nitrogen use efficiency. Similar findings have been observed in rice [25], where nitrogen fertilizer utilization efficiency varied with different nitrogen application rates. Another study showed that the effect of increasing yield was more significant when hybrid foxtail millet varieties received a nitrogen fertilizer application rate of 155 kg·ha−1 compared to 108 kg·ha−1 for non-hybrid varieties [18]. Our results further confirmed the previous literature’s conclusions that varietal differences contributed to varying nitrogen fertilizer requirements.
High crop yield requires not only nitrogen-efficient varieties but also an appropriate nitrogen fertilizer application rate. In the semi-arid loess plateau region, the optimal nitrogen fertilizer application rate for spring wheat was around 105 kg N ha−1 [26]. Research on optimal nitrogen fertilizer application rates for maize suggested that a TN supply (a mixture of environmental, soil, crop residues, and fertilizer N) ranging from 361 to 497 kg·ha−1 resulted in higher grain yield, greater nitrogen use efficiency (NUE), and reduced environmental nitrogen losses, whereas a nitrogen application rate of 229 to 315 kg·ha−1 was sufficient for achieving a high yield of maize [27]. A nitrogen application rate of 193 to 291 kg·ha−1 could ensure both maize’s yield and less soil nitrogen surplus, with higher nitrogen recovery in the soil–maize system [28]. For oats, an optimal nitrogen fertilizer application rate of 80 kg·ha−1 appeared to maximize fodder yield and nitrogen use efficiency [29]. Over a two-year period, the yields of five millet varieties (JG20, HG17, ZG9, JG16, JG39) showed an initial increase followed by a decrease with increasing fertilizer application rates, revealing optimal nitrogen fertilizer application rates for achieving high yields of foxtail millet crops and underscoring the need to avoid excessive nitrogen fertilization in crop production to prevent the deterioration of crop population structure [30,31].

4.2. The Availability of Soil Nitrate Nitrogen Was a Direct Factor Influencing Yield of Foxtail Millet

Millet yield was not only correlated with nitrogen fertilizer application rate but also directly influenced by soil-available nitrogen content [32]. When nitrogen fertilizer application rate exceeded a threshold, yield ceased to increase significantly, and this may lead to various adverse environmental events such as nitrogen surplus in the soil [33]. Previous studies have found that soil accumulations of NO3−-N and NH4+-N were high with nitrogen application rates of 400–500 kg·ha−1 [19]. Soil nitrogen residue increased with a nitrogen fertilizer application rate of 0.42 g N kg−1 (equivalent to 504 kg·ha−1 N) [34]. Significant accumulation of soil nitrate occurred when nitrogen application rate exceeded 180 kg ha−1, with peak values gradually shifting deeper into the soil layers annually [35]. We found that nitrogen application rates exceeding 360–540 kg·ha−1 resulted in an increase in NO3−-N and NH4+-N content in different soil layers during pre-sowing and maturation periods, with higher nitrogen content observed in deeper soil layers. Our study further validated these findings.
Different varieties of millet required different soil nitrate nitrogen thresholds to achieve a high yield. Millet achieved a high yield when the soil nitrate nitrogen was between 15.68 and 19.43 mg·kg−1 in the 0–20 cm depth before sowing and 8.60–11.90 mg·kg−1 at maturity. Previous research has confirmed that wheat and maize crops at harvest maintain soil fertility and prevent leaching into deeper soil layers (>100 cm depth) with a residual NO3−-N threshold in the root zone (0–100 cm soil layer) of approximately 100 kg·ha−1 (equivalent to a soil NO3−-N threshold of about 10 mg·kg−1) [36]. Critical nitrate thresholds in the root zone for biochar (NI), straw incorporation (SI), and straw biochar incorporation measures were 49, 104, and 67 kg·ha−1, respectively, preventing nitrogen from leaching into the 100–200 cm soil layers [37]. Discrepancies in the soil nitrate nitrogen thresholds of this study and previous findings may be due to differences in crop nutrient demand characteristics and dry matter accumulation levels. This study enriched existing research by exploring nitrate nitrogen thresholds for high yields of millet, contributing to the diversity of crop types studied.

4.3. Proper Nitrogen Management Was Important to Maintain Soil Fertility and Reduce Environmental Risks

To mitigate environmental risks associated with improper fertilization, proper nitrogen management is crucial for maintaining soil fertility and reducing environmental impact. This study identified pre-sowing NO3−-N content in soil as a key indicator for determining optimal fertilization level, which established the formula for the optimal nitrogen application rate for a high yield of millet: y = 867.5 − 50z (10 < z < 17.35), where y represents the optimal nitrogen application rate and z denotes the pre-sowing soil NO3−-N content in the 0–20 cm layer. Nitrogen fertilizer application was controlled within 360 kg·ha−1 units to minimize its impact on soil-available nitrogen. Agricultural professionals can use this equation to apply nitrogen fertilizer corresponding to local pre-sowing soil NO3−-N level. We provided a rapid, efficient fertilization, balancing yield with an environmental approach. This study helped achieve precise fertilization in practical production by adjusting fertilization schemes based on soil nitrogen levels, reducing the risk of nitrogen overapplication, improving fertilizer use efficiency, and increasing crop yields. It also provided a flexible fertilization management strategy that can be adapted to different soil conditions and crop needs, enhancing agricultural management adaptability. However, due to the complexity of agricultural environments (such as variations in temperature, precipitation, and sunlight), soil NO3−-N levels were influenced by multiple factors. Predictive parameters may vary significantly across different climatic conditions, soil types, cropping systems, and management practices [38]. By conducting a three-year positioning fertilization experiment, we simulated five relatively stable plots with different soil fertility backgrounds, addressing the limitations of single-point experiments. The results of this experiment provided important insights for nutrient management in the summer millet region, but there were certain limitations for nutrient management in the spring millet region. Therefore, the recommended nitrogen application based on soil NO3−-N should be regarded as a consultative guideline. In the future, we will continue to conduct experiments to further validate and optimize our research findings.

5. Conclusions

There were few reports recommending appropriate nitrogen application rates based on soil nitrogen levels in foxtail millet. Therefore, this study investigated the effects of different nitrogen fertilizer levels on the growth, yield, and soil nitrogen levels of foxtail millet, as well as the impact of different nitrogen fertilizer levels on the soil nitrate nitrogen threshold, in order to determine the range of effective nitrogen fertilizer application to maintain soil nitrate levels. Different varieties of foxtail millet resulted in varying nitrogen fertilizer requirements, with an average nitrogen application rate of 141.3 kg·ha−1 achieving high yield across five varieties. Specifically, the average nitrogen application rate of nitrogen-efficient millet varieties achieving high yield (5607.32–5637.19 kg·ha−1) was 151.5 kg·ha−1, while the average nitrogen application rate of nitrogen-inefficient varieties achieving high yield (4749.77–4847.74 kg·ha−1) was 134.5 kg·ha−1. To achieve a high yield of millet, soil nitrate nitrogen levels should ideally be maintained at an average of 17.23 mg kg−1 (pre-sowing) and 9.75 mg·kg−1 (at maturity). When soil managers have knowledge of soil nutrient status, we recommended applying nitrogen at a rate of 867.5 − 50z kg·ha−1 (where z represents soil nitrate nitrogen content, and 10 < z < 17.35 mg·kg−1), which not only ensured high yield of foxtail millet but also maintained soil fertility.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture14101711/s1, Table S1: The nitrogen recovery rates of different millet varieties.

Author Contributions

Y.L., Y.Z. and X.X. conducted data analysis and wrote research papers; M.L. and Z.W. carried out experiment and sample analysis; J.W. and J.L. assisted with statistical analysis; J.C. and S.L. revised the manuscript and were in charge of overall direction and planning. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Millet Sorghum Industrial Technology System Construction Project (CARS-06-14.5-A23), Hebei Modern Agricultural Industrial Technology System Construction Project (HBCT2024070101, HBCT2024070202), Hebei Academy of Agriculture and Forestry Sciences Basic Scientific Research Business Funds Lump Sum Project (HBNKY-BGZ-02).

Data Availability Statement

Relevant data applicable to this research are within the paper.

Acknowledgments

We are grateful to the farmers in our study for their patience and support.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Locations of the study sites.
Figure 1. Locations of the study sites.
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Figure 2. Yield of foxtail millet among years, fertilizers, and varieties. In the planting seasons of 2022~2023 in China, the variation in foxtail millet yield among years (a,d), fertilizers (c,f) and varieties (b,e) is depicted. The histogram represents the average yield, while scatter plots represent the yield data of all samples. Different colors of scatter plots indicate different treatment methods, such as variety and fertilization. Different lowercase letters on different columns indicate statistical significance at the p < 0.05 level according to the Duncan’s test.
Figure 2. Yield of foxtail millet among years, fertilizers, and varieties. In the planting seasons of 2022~2023 in China, the variation in foxtail millet yield among years (a,d), fertilizers (c,f) and varieties (b,e) is depicted. The histogram represents the average yield, while scatter plots represent the yield data of all samples. Different colors of scatter plots indicate different treatment methods, such as variety and fertilization. Different lowercase letters on different columns indicate statistical significance at the p < 0.05 level according to the Duncan’s test.
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Figure 3. The response relationship between yield and nitrogen application rate. (a–e) show the fitting relationship between N input in 2022 and the yield of JG20 HG17 ZG9 JG16 JG39 varieties, while (f–j) show the fitting relationship between N input in 2023 and the yield of JG20 HG17 ZG9 JG16 JG39 varieties.
Figure 3. The response relationship between yield and nitrogen application rate. (a–e) show the fitting relationship between N input in 2022 and the yield of JG20 HG17 ZG9 JG16 JG39 varieties, while (f–j) show the fitting relationship between N input in 2023 and the yield of JG20 HG17 ZG9 JG16 JG39 varieties.
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Figure 4. The soil NH4+-N content before sowing and at maturity stage and the soil NO3−-N content before sowing and at maturity stage under different nitrogen application levels. (a,b) showed the soil NH4+-N content before sowing and at maturity under different nitrogen fertilizer levels in 2022. (c,d) showed the soil NO3−-N content before sowing and at maturity under different nitrogen fertilizer levels in 2022. (e,f) showed the soil NH4+-N content before sowing and at maturity under different nitrogen fertilizer levels in 2023. (g,h) showed the soil NO3−-N content before sowing and at maturity under different nitrogen fertilizer levels in 2023.
Figure 4. The soil NH4+-N content before sowing and at maturity stage and the soil NO3−-N content before sowing and at maturity stage under different nitrogen application levels. (a,b) showed the soil NH4+-N content before sowing and at maturity under different nitrogen fertilizer levels in 2022. (c,d) showed the soil NO3−-N content before sowing and at maturity under different nitrogen fertilizer levels in 2022. (e,f) showed the soil NH4+-N content before sowing and at maturity under different nitrogen fertilizer levels in 2023. (g,h) showed the soil NO3−-N content before sowing and at maturity under different nitrogen fertilizer levels in 2023.
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Figure 5. Response relationship between millet yield and nitrate nitrogen content at different nitrogen levels. (a,b) represented the fitting relationship between mature and pre sowing NO3−-N content and JG20 yield, (c,d) represented the fitting relationship between mature and pre sowing NO3−-N content and HG17 yield, (e,f) represented the fitting relationship between mature and pre sowing NO3−-N content and ZG9 yield, and (g,h) represented the fitting relationship between mature and pre sowing NO3−-N content and JG39 yield.
Figure 5. Response relationship between millet yield and nitrate nitrogen content at different nitrogen levels. (a,b) represented the fitting relationship between mature and pre sowing NO3−-N content and JG20 yield, (c,d) represented the fitting relationship between mature and pre sowing NO3−-N content and HG17 yield, (e,f) represented the fitting relationship between mature and pre sowing NO3−-N content and ZG9 yield, and (g,h) represented the fitting relationship between mature and pre sowing NO3−-N content and JG39 yield.
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Figure 6. Response relationship between nitrogen application rate and yield, as well as soil NO3−-N levels before sowing (a–f) and the relationship between optimal nitrogen application levels and pre-sowing soil nitrate response (g).
Figure 6. Response relationship between nitrogen application rate and yield, as well as soil NO3−-N levels before sowing (a–f) and the relationship between optimal nitrogen application levels and pre-sowing soil nitrate response (g).
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Table 1. The interaction of year, variety, and fertilization on the agronomic traits of foxtail millet.
Table 1. The interaction of year, variety, and fertilization on the agronomic traits of foxtail millet.
TreatmentFST (g·plant−1)MST (g·plant−1)FSP
(g·plant−1)		MSP (g·plant−1)FDM
(g·plant−1)		MDM (g·plant−1)DMAA (g·plant−1)
Year
202210.5 b13.7 b3.3 b17.9 a13.8 b31.6 a17.8 a
202314.5 a14.5 a7.1 a14.5 b21.5 a29.0 b7.5 b
Fertilizer
N011.1 c12.9 c4.9 c14.7 b16.0 c27.6 c11.6 b
N612.6 b13.8 bc5.6 bc16.0 a18.2 b29.8 b11.6 b
N1213.8 a15.6 a5.8 a17.1 a19.6 a32.8 a13.2 a
N2413.3 ab14.4 b5.2 b17.1 a18.5 ab31.5 ab13.0 a
N3611.5 c13.8 bc4.5 bc16.1 a16 b29.9 b13.9 a
Variety
JG2011.6 c12.2 c5.0 a17.0 a16.6 c29.2 bc12.6 ab
HG1713.2 a14.1 b5.3 a17.2 a18.5 a31.3 ab12.9 ab
ZH912.2 bc14.5 ab5.1a15.8 b17.2 b30.3 b13.1 ab
JG1612.8 ab15.6 a5.4 a17.0 a18.2 a32.6 a14.3 a
JG3912.6 b13.4 bc5.2 a14.9 c17.8 a28.3 bc10.2 b
F-value and significance
Year (Y)230.3 **4.0 *799.3 **89.0 **439.8 **15.4 **186.7 **
Fertilizer (F)15.1 **5.3 **12.7 **5.9 **14.9 **6.6 **1.4 NS
Variety (V)6.7 **12.6 **1.9 NS10.0 **5.4 **12.6 **4.9 **
Y × F5.8 **1.7 NS5.6 **3.5 **5.0 **1.0 NS2.5 *
Y × V0.7 NS0.7 NS1.1 NS5.1 **0.8 NS1.6 NS1.3 NS
F × V1.5 NS0.6 NS2.8 **0.9 NS2.0 *0.7 NS0.6 NS
Y × F × V1.1 NS0.5 NS1.3 NS0.6 NS1.1 NS0.4 NS0.7 NS
FST: straw weight at flowering stage; MST: straw weight at maturity stage; FSP: spike weight at flowering stage; MSP: spike weight at maturity stage; FDM: total weight at flowering stage; MDM: total weight at maturity stage; DMAA: dry matter accumulation after anthesis. Means in columns followed by different lowercase letters are significantly different at p < 0.05 according to Duncan’s test. * means p < 0.05, ** means p < 0.01, and NS means non-significant.
Table 2. The interaction of year, variety, and fertilization on foxtail millet yield and related traits.
Table 2. The interaction of year, variety, and fertilization on foxtail millet yield and related traits.
TreatmentSN (Ten Thousand Plants·ha−1)SWE (g)GWE (g)Yield (kg·ha−1)
Year
202242.15 a20.07 a16.34 a5119.23 a
202340.80 a18.46 b14.86 b5129.79 a
Fertilizer
N040.80 ab18.40 b14.90 c5182.10 a
N642.00 ab18.71 b15.29 bc5289.80 a
N1243.65 a18.88 b15.29 bc5412.60 a
N2440.80 ab20.06 a16.07 ab5198.95 a
N3640.05 b20.26 a16.47 a4539.07 b
Variety
JG2046.80 a18.02 b14.38 b5637.19 a
HG1743.80 b19.77 a15.92 a5607.32 a
ZH939.60 c19.40 a15.95 a4749.77 b
JG1640.50 c19.13 a15.58 a4780.51 b
JG3936.60 d19.99 a16.17 a4847.74 b
F-value and significance
Year (Y)2.4 NS24.9 **28.0 **0.02 NS
Fertilizer (F)2.2 NS5.4 **4.3 **14.85 **
Variety (V)16.7 **4.5 **5.2 **26.72 **
Y × F6.9 **5.0 **4.6 **6.48 **
Y × V5.4 **2.1 NS4.0 **6.02 **
F × V3.0 **1.7 *2.2 **0.71 NS
Y × F × V1.2 NS1.3 NS2.0 *1.20 NS
SN: Spike number per hectare; SWE: spike weight; GWE: grain weight; Yield: yield per hectare. Means in columns followed by different lowercase letters are significantly different at p < 0.05 according to Duncan’s test. * means p < 0.05, ** means p < 0.01, and NS means non-significant.
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Lu, Y.; Zhao, Y.; Xia, X.; Liu, M.; Wei, Z.; Wang, J.; Liu, J.; Cui, J.; Li, S. Evaluation of Nitrogen Fertilizer Supply and Soil Nitrate Thresholds for High Yields of Foxtail Millet. Agriculture 2024, 14, 1711. https://doi.org/10.3390/agriculture14101711

AMA Style

Lu Y, Zhao Y, Xia X, Liu M, Wei Z, Wang J, Liu J, Cui J, Li S. Evaluation of Nitrogen Fertilizer Supply and Soil Nitrate Thresholds for High Yields of Foxtail Millet. Agriculture. 2024; 14(10):1711. https://doi.org/10.3390/agriculture14101711

Chicago/Turabian Style

Lu, Yiwei, Yu Zhao, Xueyan Xia, Meng Liu, Zhimin Wei, Jingxin Wang, Jianjun Liu, Jihan Cui, and Shunguo Li. 2024. "Evaluation of Nitrogen Fertilizer Supply and Soil Nitrate Thresholds for High Yields of Foxtail Millet" Agriculture 14, no. 10: 1711. https://doi.org/10.3390/agriculture14101711

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