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Article

Response of Summer Foxtail Millet Yield and Water Productivity to Water Supply in the North China Plain

by
Wenying Zhang
1,2,
Bianyin Wang
1,2,
Binhui Liu
1,2,
Zhaoyang Chen
1,2,
Guanli Lu
1,2,
Caihong Bai
3 and
Yaoxiang Ge
3,*
1
Dryland Farming Institute, Hebei Academy of Agricultural and Forestry Science, Hengshui 053000, China
2
Key Laboratory of Crop Drought Tolerance Research of Heibei Province, Hengshui 053000, China
3
College of Smart Agriculture, Yulin Normal University, Yulin 537000, China
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(11), 2468; https://doi.org/10.3390/agronomy15112468
Submission received: 23 September 2025 / Revised: 17 October 2025 / Accepted: 20 October 2025 / Published: 23 October 2025
(This article belongs to the Section Water Use and Irrigation)
Browse Figures
Versions Notes

Abstract

Summer foxtail millet (Setaria italica L.) is a crucial crop in the arid and semi-arid regions of the North China Plain. Therefore, adopting effective irrigation management strategies is essential for conserving water resources while sustaining millet production in these water-limited areas. A two-year field experiment was conducted in Hengshui in 2020 and 2021 to determine the optimal irrigation amount for foxtail millet and evaluate the critical role of root distribution across various soil depths in determining yield and water productivity. Grain yield, yield-related traits, water use efficiency, and root traits were measured under six irrigation regimes (I0, I1, I2, I3, I4, and I5). Grain yield significantly increased with irrigation, but no further significant yield improvement was observed between the I3 and I5 treatments. The highest water productivity was observed under I3 in 2020 and I2 in 2021. Biomass, thousand grain weight, abortive grain rate, panicle dry weight, and water use efficiency under I3 were similar to those under I4 and I5 treatments. Root traits, including total root length, surface area, volume, and dry weight, did not significantly differ between I3, I4, and I5. Grey relational analysis indicated that total water content in the shallow soil layer (0–40 cm) had the greatest impact on yield. Overall, the I3 treatment (150 mm) is recommended as the optimal irrigation amount for increasing foxtail millet production and water use efficiency.

1. Introduction

Foxtail millet (Setaria italica L.) is a nutrient-rich cereal crop, containing high levels of protein, dietary fibre, minerals, and phytochemicals, and exhibits hypolipidemic and antioxidant properties and a low glycemic index, making it a promising candidate for enhancing nutritional and food security [1]. Initially domesticated in Northern China, foxtail millet has become one of the most important crops in the North China Plain (NCP) [2]. The NCP is a critical grain production base in China; however, agricultural water resources in this region are limited, posing significant challenges to sustainable crop production.
Previous studies have demonstrated that water deficit during the reproductive stage significantly reduces the number of tillers, grains per ear, and grain weight, ultimately leading to yield losses in foxtail millet. Additionally, the duration of water stress prior to flowering has been shown to influence yield [3,4,5]. While irrigation offers potential for improving millet productivity, improper water management under irrigated conditions often results in low yields [6]. Effective irrigation strategies can significantly reduce water consumption, enhance water productivity, and increase the productivity of field crops [7].
Optimal irrigation management is essential for the efficient use of water resources. The amount of irrigation applied plays a critical role in determining crop productivity. Onder et al. [8] reported that in the Amik Plain of Turkey, cotton yields were highest under full irrigation (100% water requirement), but the highest irrigation water use efficiency was achieved at 50% of full irrigation. Irmak et al. [9] found that maize yields were highest under fully irrigated conditions, while both excessive (125% of full irrigation) and insufficient (25%, 50%, and 75% of full irrigation) water application reduced grain yields. These findings are consistent with studies on other crops, such as wheat, where moderate irrigation levels were shown to maximize both yield and water use efficiency [10]. Furthermore, research on grain sorghum has demonstrated that managed deficit irrigation can maintain water use efficiency comparable to full irrigation while significantly saving water by strategically applying water during critical reproductive stages [11]. Therefore, optimal irrigation for crops is important for achieving sustainable agricultural production.
Water management has become a critical research focus in irrigated millet production systems. Determining the appropriate irrigation amount for foxtail millet is essential for optimizing water resource utilization in the NCP. The objectives of this study are to identify the optimal irrigation amount for foxtail millet cultivation based on grain yield, water use efficiency, the effect of root distribution at different depths, and economic profit in the NCP.

2. Materials and Methods

2.1. Site Description

The experiment was conducted at the Hengshui Dryland Agricultural Experimental Station (115°42′53″ E, 37°54′37″ N), located in Hebei Province, Northern China, during the 2020 and 2021 growing seasons. The soil at the experimental site is classified as silt loam, with a pH of 8.1 (1:2.5 (w/v) ratio of soil to distilled water), a soil organic carbon content of 1.13%, a bulk density of 1.58 g cm−3, total nitrogen equal to 0.030 g·kg−1, available phosphorus equal to 7.3 mg kg−1, and exchangeable potassium equal to 155.1 mg kg−1 for the tillage soil layer.

2.2. Plant Material

Five summer foxtail millet varieties—Zhonggu2, Jigu39, Yugu18, Jigu168, and Jigu22—were used in this study. These varieties were provided by the Institute of Crop Science, Chinese Academy of Agricultural Sciences; the Institute of Summer Millet, Hebei Academy of Agricultural Sciences; the Institute of Crop Science, Shandong Academy of Agricultural Sciences; and the Anyang Academy of Agricultural Sciences.

2.3. Field Experiment

The experiment was arranged in a randomized block design with three replicates for each variety. Each plot measured 3.0 m × 2.2 m and was surrounded by a 20 cm thick concrete wall to prevent water exchange between plots. The soil depth of each plot was 3.0 m. A movable shed was installed to exclude rainfall during the growing season.
Before sowing, nitrogen (urea, 46.4% N), phosphate (superphosphate, 12% P2O5), and potassium (potassium sulphate, 60% K2O) fertilizers were applied as a basal fertilizer at 225, 225, and 225 kg ha–1, respectively. No additional fertilizers were applied during the growing season.
Foxtail millet plants were subjected to six irrigation treatments (I0, I1, I2, I3, I4, and I5). Irrigation was applied twice during the growing season: once at the jointing stage and once at the grain-filling stage. The irrigation amounts for each treatment were as follows: I0: 0 mm, I1: 60.0 mm, I2: 120.0 mm, I3: 150.0 mm, I4: 180.0 mm, and I5: 210 mm. The irrigation volume was precisely controlled using a water metre.
The experimental plots were covered with transparent arched plastic shelters, with the lowest point of the arch positioned 3.0 m above the soil surface to exclude rainfall. The shelters remained open during dry conditions and were only closed during rainfall events throughout the growing season. All field managements were consistent across plots, except for irrigation. Seeds were sown manually, and at the seedling stage, plants were thinned to a density of 60 plants m−2 with a row spacing of 20 cm. Before planting, the soil was irrigated to ensure that the soil moisture in the top 1 m of the soil profile exceeded 80% of the field capacity, promoting uniform germination across all treatments.
At harvest, 100 plants were randomly selected from each plot to measure panicle dry weight (PDW). Subsequently, all plants within each plot were manually harvested. Grain and straw were dried to a constant weight at 80 °C to determine grain yield (GY) and straw yield (SY). Thousand grain weight (TGW) was measured manually.

2.4. Measurements

Soil water content was measured at sowing and harvest using the gravimetric method [12] at soil depths of 0–20, 20–40, 40–60, 60–80, 80–100, 100–120, 120–140, and 140–160 cm.
Root samples were collected during the 2020 and 2021 growing seasons at maturity. Soil cores were extracted using a 9 cm inner-diameter corer to a depth of 160 cm, with increments of 20 cm. Three cores were taken for each treatment. The soil samples were placed in mesh bags and washed to isolate the roots. Root length (RL), root volume (RV), and root surface area (RSA) were measured using a scanner (Expression 12000XL, Epson, Beijing, China) and analyzed with WinRHIZO software (WinRHIZO Pro 32-bit 2013e). The roots were then dried to a constant weight at 80 °C to determine root dry weight (RDW).

2.5. Calculations

The following parameters were calculated:
Biomass = GY + SY;
Abortive grain rate (AGR) = 1 − (grain weight per panicle/panicle weight per plant);
Water reduction in soil storage (WRSS) = soil water content at harvest − soil water content at sowing;
Total water consumption (TWC) = (soil water content at harvest − soil water content at sowing) + irrigation volume;
Water productivity (WP) = grain yield/TWC;
Root length density (RLD), root surface area density (RSAD), root volume density (RVD) and root dry weight density (RDWD) were calculated from the volume of the soil cores and the RL, RSA, RV and RDW, respectively.
Economic profit (EP) = GY × average price − irrigation water volume × water price;
1−actural yield (Ya)/maximum yield (Ym) = yield response factor (Ky) × (1 − TWCa/TWCm).

2.6. Statistical Analysis

Data from three replicates for each variety were averaged and analyzed using IBM SPSS Statistics 21 (IBM Corp.Chicago, IL, USA). Grey relational analysis was processed in SPSSAU (Version 20.0) [Online Application Software], retrieved from https://spssau.com/index.html (accessed on 4 January 2025).

3. Results

3.1. Yield, Biomass, Thousand Grain Weight, Abortive Grain Rate, and Panicle Weight

In 2020 (Figure 1), GY generally increased with increasing irrigation amounts, except for the I4 treatment, where the yield (7.01 t hm−2) was lower than that of the I3 and I5 treatments. No significant differences were observed between the I3 and I5 treatments. The highest GY (7.44 t hm−2) was achieved under the I5 treatment, which was significantly higher than that of the I2, I1, and I0 treatments. The I0 treatment resulted in the lowest grain yield.
In 2021, GY exhibited a similar trend across treatments as in 2020. However, the yields under the I2, I3, I4, and I5 treatments were significantly lower in 2021 compared to 2020, while the yields under the I0 and I1 treatments were significantly higher. The highest GY (6.42 t hm−2) was observed under the I5 treatment, followed by the I3 treatment (6.22 t hm−2). No significant differences were detected among the I1, I2, I3, I4, and I5 treatments in 2021.
Irrigation significantly influenced the biomass, TGW, AGR, and panicle dry weight (PDW) of summer millet (Table 1). In 2020, compared to the control (I0), the I1, I3, I4, and I5 treatments significantly increased biomass and PDW, while the I1 and I5 treatments significantly increased TGW. Additionally, the I3, I4, and I5 treatments significantly reduced AGR. In 2021, the I3 treatment significantly decreased biomass, AGR, and PDW, while the I1 treatment significantly increased TGW. Conversely, the I5 treatment significantly reduced TGW.

3.2. Water Productivity and Water Economic Benefit

The WP of summer millet varied significantly among irrigation treatments (Figure 2). In both 2020 and 2021, two peaks in WP were observed. The first peak occurred under the I0 treatment, with values of 30.10 kg mm−1 hm−2 in 2020 and 27.44 kg mm−1 hm−2 in 2021. The second peak was observed under the I3 treatment in 2020 (27.84 kg mm−1 hm−2) and the I2 treatment in 2021 (28.80 kg mm−1 hm−2). The lowest WP values were recorded under the I5 treatment (23.70 kg mm−1 hm−2) in 2020 and the I4 treatment (21.48 kg mm−1 hm−2) in 2021.
As shown in Table 2, the benefit of millet varied with the irrigation treatments. In 2020, the greatest benefit was achieved under the I3 treatment (150 mm), reaching 26,972.15 RMB ha−1. In 2021, the maximum benefit occurred under I5 (210 mm) at 25,560.99 RMB ha−1, followed by the I3 treatment (24,787.94 RMB ha−1).

3.3. Water Reduction in Soil Storage, Total Water Consumption, and Yield Response Factor (Ky)

The WRSS decreased significantly from the I2 treatment in both 2020 and 2021 (Figure 3). The highest values were observed under the I0 treatment in 2020 (167.41 mm) and 2021 (190.65 mm), while the lowest values were recorded under the I5 treatment in 2020 (97.36 mm) and 2021 (53.04 mm). No significant differences were observed among the I2, I3, I4, and I5 treatments in 2020 or among the I2, I4, and I5 treatments in 2021.
TWC increased with increasing irrigation amounts, reaching peak values of 307.36 mm in 2020 and 263.04 mm in 2021 under the I5 treatment (Figure 3). No significant differences were detected between the I4 and I5 treatments in 2020 or among the I3, I4, and I5 treatments in 2021.
Figure 4 reveals a negative correlation between TWC and soil WRSS in summer foxtail millet, with increased utilization of soil water associated with decreased total consumption.
Figure 5 shows a positive correlation between total water consumption and grain yield, suggesting that the higher grain yield was driven by increased water use.
The yield response factor was 0.7102 for 2020 and 0.6251 for 2021 (Figure 6), which demonstrated a yield reduction in response to decreased irrigation.

3.4. Root Traits

Irrigation enhanced RLD, RSAD, RVD, and RDWD (Figure 7). In 2020, the I3 treatment resulted in the largest RLD (3.28 m dm−3) and RSAD (2.17 cm2 dm−3). RDW remained stable as irrigation increased from I2 to I5, with the largest RVD (1.34 cm3 dm−3) observed under the I5 treatment, followed by the I3 treatment (1.24 cm3 dm−3). No significant differences were observed in all root traits among the I2, I3, and I4 treatments. In 2021, the I2 treatment exhibited the highest RLD (3.61 m dm−3) and RSAD (2.52 cm2 dm−3), followed by the I3 treatment. The largest RV and RDWD were observed under the I3 and I5 treatments, respectively. All root traits showed no significant differences between the I2 and I3 treatments.

3.5. Grey Relational Analysis of Total Water Consumption

Grey relational analysis (GRA) was employed to assess the importance of TWC to GY at different soil depths. The grey relational grade (GRG) values for TWC ranged from 0.725 to 0.912 in 2020 and from 0.557 to 0.678 in 2021 (Table 3). In both years, the mean TWC at the 20 cm soil depth exhibited the highest GRG, followed by TWC at 40 cm, 100 cm, and 60 cm depths. The GRG values for TWC at 80 cm, 120 cm, 140 cm, and 160 cm depths varied between years and were less significant compared to the shallower depths.
For TWC under different irrigation treatments, the importance of TWC at the 20 cm depth under the I0 and I3 treatments in 2020 aligned with the mean TWC across all six treatments. Similarly, in 2021, the importance of TWC at the 20 cm and 40 cm depths under the I2, I3, and I4 treatments was consistent with the mean TWC across all six treatments observed for these depths.

4. Discussion

In the semi-arid regions of northern China, irrigation is crucial for achieving high GY in crops. However, optimizing irrigation water application can significantly reduce water usage while maintaining stable grain production [13]. In this study, the GY of foxtail millet increased with higher irrigation amounts, but no significant yield improvement was observed when irrigation exceeded 150 mm (I3 treatment) in both 2020 and 2021. This suggests that excessive water application does not always translate into higher grain yields, as additional water may be lost through soil evaporation, particularly in arid conditions [14,15]. Moreover, over-irrigation can lead to waterlogging, nutrient leaching, and the displacement of salts from the rhizosphere, which can negatively impact yield.
WP is a key metric for assessing whether agricultural practices can enhance GY with reduced water input. One effective strategy to improve WP is by reducing total irrigation water [16]. For instance, Li and Zhou [17] found that winter wheat irrigated with 75 mm at the elongation stage achieved higher grain yields (6750–7500 kg ha−1) and WP (>16.5 kg mm−1 ha−1) compared to traditional irrigation practices in the North China Plain. In our study, the highest WP values in 2020 and 2021 were observed under the I3 (28.80 kg mm−1 hm−2) and I2 (27.84 kg mm−1 hm−2) treatments, respectively. The GY, biomass, TGW, and PDW of foxtail millet did not significantly decrease under the I3 treatment compared to the other treatments. Economic benefits are important to millet growers. AGR is an important trait to be considered. In this study, AGR did not significantly increase under I3 treatment compared with other treatments in both 2020 and 2021. Additionally, WRSS was lower and TWC was higher under the I3 treatment, with no significant differences in RSS and TWC compared to the I2 and I4 treatments in both years. These findings suggest that an irrigation level of 150 mm may be sufficient to maintain high grain yields.
Improving GY and WP can be directly linked to enhancing the crop’s ability to absorb water from the soil. The root system of foxtail millet plays a critical role in water and nutrient uptake, which directly impacts grain yield. Water availability is essential for root growth, and an increase in root biomass under water-deficit conditions can enhance aboveground biomass production, ultimately boosting yield [18]. Melons increased their root growth in response to deficit irrigation conditions [19], whereas potatoes exhibited similar root growth under both deficit irrigation and full irrigation treatments [20]. The proper irrigation amount is essential for optimizing root growth and increasing economic benefit. In our study, the highest irrigation amount did not result in the largest root system. Instead, root traits under the I2 and I3 treatments were superior compared to other treatments, with no significant differences observed between I2 and I3. The improved WP and relatively higher yields under these treatments can be attributed to the enhanced root system, as roots are integral to water uptake and grain yield production [13,21,22]. Furthermore, the I3 treatment provided the highest economic return in 2020 (26,972.15 RMB ha−1). Although I2 achieved a slightly higher benefit in 2021 (exceeding I3 by 773.95 RMB ha−1), the I3 treatment demonstrated consistently high performance across both years. Therefore, the I3 treatment appears to be the optimal irrigation strategy.
The influence of TWC at various soil depths on GY is critical for yield improvement in arid and semi-arid regions, yet it remains poorly understood. To address this, we employed grey relational analysis to evaluate how TWC at different soil depths affects GY. This method has been successfully used to analyze relationships between meteorological factors and yield-related traits in crops such as soybean [23], maize [24], wheat [25], and rice [26]. Our results indicate that TWC in the shallow soil layer (0–40 cm) had the greatest impact on GY, underscoring its importance for achieving high yields in summer foxtail millet. Furthermore, the TWC in the shallow soil layer under the I3 treatment was both more significant and consistent across 2020 and 2021, reinforcing the conclusion that the I3 treatment represents the best irrigation management strategy in this study.

5. Conclusions

The 150 mm irrigation (I3 treatment) improved water use efficiency without compromising yield or other traits and enhanced root development. The 150 mm irrigation (I3 treatment) is the most efficient and economic irrigation strategy for sustainable millet production. Total water content in the shallow soil layer (0–40 cm) had the greatest impact on yield.

Author Contributions

Conceptualization, W.Z. and B.W.; methodology, W.Z., B.W., B.L., Z.C. and G.L.; formal analysis, Y.G. and C.B.; resources, B.W.; writing—original draft preparation, B.W., Y.G., B.L. and G.L.; writing—review and editing, W.Z., C.B. and Z.C.; supervision, W.Z., Y.G. and B.W.; project administration, W.Z. and B.W.; funding acquisition, W.Z., Y.G. and C.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the China Agricultural Research System, grant number CARS-06-14.5-A34; Hebei Agriculture Research System, grant number HARS-HBCT2024080202; the National Science Foundation of China, grant number 32260534, 32460465; and the Research Foundation for Talented Scholar, grant numbers G2019ZK40 and G2019ZK45.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Agronomy 15 02468 g001
Figure 1. Grain yield of summer foxtail millet under six irrigation treatments. Different lowercase letters denote significant differences among treatments (p < 0.05).
Figure 1. Grain yield of summer foxtail millet under six irrigation treatments. Different lowercase letters denote significant differences among treatments (p < 0.05).
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Figure 2. Water productivity of summer foxtail millet under six irrigation treatments. Different lowercase letters denote significant differences among treatments (p < 0.05).
Figure 2. Water productivity of summer foxtail millet under six irrigation treatments. Different lowercase letters denote significant differences among treatments (p < 0.05).
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Figure 3. Reduction in soil storage and total water consumption of summer foxtail millet under six irrigation treatments. Different lowercase letters denote significant differences among treatments.
Figure 3. Reduction in soil storage and total water consumption of summer foxtail millet under six irrigation treatments. Different lowercase letters denote significant differences among treatments.
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Figure 4. The relationship between total water consumption and reduction in soil storage in summer foxtail millet.
Figure 4. The relationship between total water consumption and reduction in soil storage in summer foxtail millet.
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Figure 5. The relationship between total water consumption and grain yield in summer foxtail millet.
Figure 5. The relationship between total water consumption and grain yield in summer foxtail millet.
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Figure 6. Yield response factor (Ky) in summer millet.
Figure 6. Yield response factor (Ky) in summer millet.
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Figure 7. Root length, root surface area, root volume, and root dry weight of summer foxtail millet under six irrigation treatments in 2020 and 2021.
Figure 7. Root length, root surface area, root volume, and root dry weight of summer foxtail millet under six irrigation treatments in 2020 and 2021.
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Table 1. Biomass, thousand grain weight, abortive grain rate (AGR), and panicle weight (PW) of foxtail millet under six irrigation treatments in 2020 and 2021.
Table 1. Biomass, thousand grain weight, abortive grain rate (AGR), and panicle weight (PW) of foxtail millet under six irrigation treatments in 2020 and 2021.
Treatments20202021
Biomass
(t ha−1)		Thousand Grain Weight (g)Abortive Grain Rate (%)Panicle Dry Weight
(t ha−1)		Biomass
(t ha−1)		Thousand Grain Weight (g)Abortive Grain Rate (%)Panicle Dry Weight
(t ha−1)
I0 (CK)10.15 d2.88 b16.61 a6.18 c11.97 a2.84 b23.27 ab6.70 a
I112.47 b2.98 a14.68 ab6.84 b12.19 a2.96 a24.79 a6.62 a
I211.17 cd2.91 ab15.35 ab7.74 c11.44 a2.81 bc22.6 ab6.37 a
I311.87 bc2.95 ab13.86 bc8.10 ab12.21 a2.89 b22.12 b6.40 a
I412.85 ab2.95 ab13.47 bc7.76 b12.34 a2.82 b22.61 ab6.84 a
I513.92 a3.00 a12.50 c8.77 a11.54 a2.77 c24.44 ab6.32 a
Different lowercase letters denote significant differences among treatments (p < 0.05). Values are given as mean ± standard deviation, and different lowercase letters indicate significant differences at p ≤ 0.05 levels in the same line (Duncan’s multiple-range test).
Table 2. The benefit of millet with different irrigation volumes.
Table 2. The benefit of millet with different irrigation volumes.
YearIrrigation Volume
(mm)		Price of Water (RMB m−3)Grain Yield
(t ha−1)		Price of Millet
(RMB m−3)		Economic Benefit
(RMB ha−1)
2020014.5418,163.78
6015.8422,315.64
12016.6424,627.46
15017.3426,972.15
18017.0425,347.75
21017.4426,593.45
2021014.86419,387.87
6015.98423,843.86
12016.02423,993.36
15016.22424,787.94
18016.18424,599.17
21016.42425,560.99
Table 3. The grey relational grid and comprehensive ranking of total water consumption and mean total water consumption at different soil depths under six different irrigation treatments with grain yield.
Table 3. The grey relational grid and comprehensive ranking of total water consumption and mean total water consumption at different soil depths under six different irrigation treatments with grain yield.
Soil Depth2020
I0I1I2I3I4I5Mean
GRGCRGRGCRGRGCRGRGCRGRGCRGRGCRGRGCR
20 cm0.91210.87640.96720.98710.97930.97230.9121
40 cm0.87920.91610.9440.96230.98120.97140.8792
60 cm0.87440.86750.96430.96620.97240.97320.8744
80 cm0.86550.89430.9910.95740.98610.97410.8655
100 cm0.87830.83160.79350.95450.91660.94350.8783
120 cm0.72580.91420.73460.95160.92350.86270.7258
140 cm0.81760.55180.60580.87870.73670.87760.8176
160 cm0.76770.55670.69670.69480.70480.66880.7677
2021
20 cm0.83330.92110.94110.92010.96010.79350.6781
40 cm0.81870.89030.88720.87920.93540.85730.6532
60 cm0.82940.89520.84240.86230.94130.89610.6264
80 cm0.82260.73580.82850.84140.95520.87520.6026
100 cm0.85420.82660.75070.78350.92450.57280.6293
120 cm0.89110.80370.47580.65880.88460.85640.6065
140 cm0.82650.82750.8730.72860.58580.69270.5767
160 cm0.72880.8440.79560.66470.64570.72260.5578
GRG: grey relational grad; CR: comprehensive ranking; I0, I1, I2, I3, I4 and I5:I0: irrigation treatment with 0 mm, 60.0 mm, 120.0 mm, 150.0 mm, 180.0 m and I5: 210 mm water, respectively.
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Zhang, W.; Wang, B.; Liu, B.; Chen, Z.; Lu, G.; Bai, C.; Ge, Y. Response of Summer Foxtail Millet Yield and Water Productivity to Water Supply in the North China Plain. Agronomy 2025, 15, 2468. https://doi.org/10.3390/agronomy15112468

AMA Style

Zhang W, Wang B, Liu B, Chen Z, Lu G, Bai C, Ge Y. Response of Summer Foxtail Millet Yield and Water Productivity to Water Supply in the North China Plain. Agronomy. 2025; 15(11):2468. https://doi.org/10.3390/agronomy15112468

Chicago/Turabian Style

Zhang, Wenying, Bianyin Wang, Binhui Liu, Zhaoyang Chen, Guanli Lu, Caihong Bai, and Yaoxiang Ge. 2025. "Response of Summer Foxtail Millet Yield and Water Productivity to Water Supply in the North China Plain" Agronomy 15, no. 11: 2468. https://doi.org/10.3390/agronomy15112468

APA Style

Zhang, W., Wang, B., Liu, B., Chen, Z., Lu, G., Bai, C., & Ge, Y. (2025). Response of Summer Foxtail Millet Yield and Water Productivity to Water Supply in the North China Plain. Agronomy, 15(11), 2468. https://doi.org/10.3390/agronomy15112468

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