Reduced Nitrogen Input Combined with Nitrogen-Saving japonica Rice Varieties Balances Yield and Nitrogen Use Efficiency in The Lower Reaches of the Yangtze River in China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Field Conditions and Rice Varieties
2.2. Experimental Design and Growth Conditions
2.3. Sampling and Measurements
2.4. Determination of Yield and Its Components
2.5. Determination of Total N Content, Various N Use Efficiencies, and Estimation of Apparent Remobilized Non-Structural Carbohydrates (NSCs)
- Remobilized NSC in stem and leaves (Kg) = amount of biomass in stem and leaves at heading—amount of biomass transfer in stem and leaves at maturity;
- Ratio of remobilization of NSC in stem and leaves (%) = remobilized NSC in stem and leaves/amount of biomass in stem and leaves at heading;
- N accumulation (NA, kg ha−1) = dry matter weight in the above—ground × N content;
- N use efficiency for grain (NUEg, kg grain kg−1 N) = grain yield/N accumulation at maturity;
- Agronomic N use efficiency (NAE, kg grain kg−1 N) = (grain yield in N application plot—grain yield in N blank plot)/N rate;
- N partial factor productivity (NPFP, kg grain kg−1 N) = grain yield/N rate;
- N physiological efficiency (NPE, kg grain kg−1 N) = (grain yield in N application plot—grain yield in N blank plot)/(N accumulation in N application plot—N accumulation in N blank plot);
- NSC contribution to grain (%) = (NSC content in stems and sheaths at heading stage—NSC in stems and sheaths at maturity stage)/total grain yield.
2.6. Statistical Analysis
3. Results
3.1. Grain Yield and Yield Components
3.2. Tillering and Productive Tiller Percentage (PTP)
3.3. N Absorption and Use Efficiency
3.4. Non-Structural Carbohydrate (NSC) Remobilization
3.5. Correlation of NSVs and GVs with Yield and N Use Efficiency
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Month | Mean Temperature (C°) | Solar Radiation (MJ m−2 per Month) | Precipitation (mm per Month) | |||
---|---|---|---|---|---|---|
2021 | 2022 | 2021 | 2022 | 2021 | 2022 | |
May | 22.3 | 21.5 | 391 | 320 | 53.9 | 12.3 |
June | 26.5 | 28.2 | 513 | 521 | 17.4 | 35.4 |
July | 28.5 | 30.1 | 501 | 523 | 143.8 | 27.5 |
August | 28.1 | 30.5 | 532 | 485 | 46.1 | 32.5 |
September | 26.7 | 23.5 | 387 | 367 | 7.5 | 3.3 |
October | 19.3 | 17.5 | 369 | 348 | 88.2 | 67.6 |
Nitrogen Rate | Total Nitrogen (kg ha−1) | Base Fertilizer (kg ha−1) | Tiller Fertilizer (kg ha−1) | Spikelet- Promoting Fertilizer (kg ha−1) | Ratio |
---|---|---|---|---|---|
N20 | 300 | 90 | 120 | 90 | 3:4:3 |
N16 | 240 | 72 | 96 | 72 | 3:4:3 |
N12 | 180 | 54 | 72 | 54 | 3:4:3 |
N8 | 120 | 36 | 48 | 36 | 3:4:3 |
N0 | 0 | 0 | 0 | 0 | / |
Type 1 | Variety 2 | Nitrogen Treatment | Panicles (×104 ha−1) | Spikelets Per Panicle | Seed Setting Rate (%) | 1000-Grain Weight (g) | Yield (t·ha−1) |
---|---|---|---|---|---|---|---|
NSV | WMJ | N0 | 248.83 ± 1.91 c | 125.23 ± 0.76 d | 89.37 ± 0.23 a | 28.09 ± 0.03 a | 7.82 ± 0.07 d |
N8 | 308.20 ± 2.98 a | 148.17 ± 0.40 b | 85.19 ± 0.37 bc | 27.66 ± 0.07 b | 10.76 ± 0.07 b | ||
N12 | 308.91 ± 3.69 a | 152.36 ± 0.94 a | 85.64 ± 0.17 b | 27.40 ± 0.09 b | 11.04 ± 0.10 a | ||
N16 | 281.26 ± 0.66 b | 152.26 ± 0.54 a | 84.51 ± 0.18 c | 27.46 ± 0.13 b | 9.94 ± 0.07 c | ||
N20 | 287.69 ± 3.24 b | 142.37 ± 0.81 c | 81.72 ± 0.45 d | 27.49 ± 0.19 b | 9.84 ± 0.13 c | ||
YNJ | N0 | 250.51 ± 2.11 d | 127.56 ± 0.40 d | 89.80 ± 0.45 a | 28.08 ± 0.07 a | 8.06 ± 0.02 e | |
N8 | 308.88 ± 2.03 a | 151.05 ± 0.77 b | 85.48 ± 0.08 b | 27.73 ± 0.06 ab | 11.06 ± 0.12 b | ||
N12 | 311.98 ± 1.00 a | 155.06 ± 0.95 a | 85.59 ± 0.09 b | 27.48 ± 0.09 b | 11.38 ± 0.08 a | ||
N16 | 287.61 ± 1.63 c | 154.86 ± 0.55 a | 84.43 ± 0.18 c | 27.53 ± 0.12 b | 10.35 ± 0.08 c | ||
N20 | 297.85 ± 3.06 b | 144.80 ± 0.82 c | 81.84 ± 0.41 d | 27.57 ± 0.18 b | 9.73 ± 0.11 d | ||
GV | HD5 | N0 | 221.87 ± 6.72 c | 112.21 ± 2.18 d | 92.53 ± 0.37 a | 28.55 ± 0.04 a | 6.57 ± 0.07 d |
N8 | 271.10 ± 3.96 b | 130.94 ± 0.59 c | 90.53 ± 0.16 b | 26.75 ± 0.11 c | 8.60 ± 0.15 c | ||
N12 | 285.15 ± 3.60 a | 134.64 ± 0.77 b | 86.83 ± 0.40 c | 27.17 ± 0.21 b | 9.06 ± 0.02 b | ||
N16 | 291.24 ± 3.02 a | 137.13 ± 0.74 a | 85.58 ± 0.12 d | 27.39 ± 0.25 b | 9.36 ± 0.07 a | ||
N20 | 288.49 ± 5.39 a | 137.50 ± 0.44 a | 87.58 ± 0.73 c | 27.39 ± 0.25 b | 9.51 ± 0.02 a | ||
MGJ200 | N0 | 217.53 ± 1.14 e | 117.75 ± 2.25 d | 92.62 ± 0.37 a | 28.63 ± 0.04 a | 6.79 ± 0.17 e | |
N8 | 264.77 ± 3.40 d | 137.49 ± 0.62 c | 90.62 ± 0.16 b | 26.83 ± 0.11 c | 8.85 ± 0.10 d | ||
N12 | 278.13 ± 6.95 c | 141.62 ± 0.46 b | 86.88 ± 0.45 c | 27.44 ± 0.42 b | 9.39 ± 0.17 c | ||
N16 | 288.93 ± 2.01 b | 143.98 ± 0.78 a | 85.30 ± 0.57 d | 27.47 ± 0.25 b | 9.75 ± 0.06 b | ||
N20 | 298.44 ± 2.33 a | 144.37 ± 0.46 a | 87.60 ± 0.73 c | 27.34 ± 0.08 b | 10.32 ± 0.15 a | ||
Source of variation | |||||||
T | ** | ** | ** | ns | ** | ||
V | ns | ** | ns | ns | ** | ||
T × V | ** | ** | ns | ns | * | ||
N | ** | ** | ** | ** | ** | ||
T × N | ** | ** | ** | ** | ** | ||
V × N | ** | ns | ns | ns | ns | ||
T× V × N | ns | ns | ns | ns | ** |
Varieties 1 | Yield Components | Direct Path Coefficient | Indirect Path Coefficient | Correlation | |||
---|---|---|---|---|---|---|---|
Panicles | Spikelets per Panicle | Seed Setting Rate | Grain Weight | ||||
WMJ | Panicles | 0.7254 | 0.6040 | −0.3850 | −0.5065 | 0.9830 ** | |
Spikelets per panicle | 0.3117 | 0.2595 | −0.1775 | −0.2609 | 0.9150 ** | ||
Seed setting rate | 0.0234 | −0.0124 | −0.0133 | 0.0158 | −0.5494 * | ||
Grain weight | −0.0152 | 0.0106 | 0.0127 | −0.0102 | −0.7668 ** | ||
YNJ | Panicles | 0.6763 | 0.5838 | −0.4546 | −0.5069 | 0.9424 ** | |
Spikelets per panicle | 0.5862 | 0.5060 | −0.3676 | −0.4711 | 0.9387 ** | ||
Seed setting rate | 0.2765 | −0.1859 | −0.1734 | 0.1979 | −0.4941 | ||
Grain weight | 0.0720 | −0.0540 | −0.0579 | 0.0516 | −0.7081 ** | ||
HD5 | Panicles | 0.7648 | 0.7380 | −0.6790 | −0.5872 | 0.9853 ** | |
Spikelets per panicle | 0.5748 | 0.5546 | −0.4882 | −0.4366 | 0.9886 ** | ||
Seed setting rate | 0.2210 | −0.1962 | −0.1877 | 0.1060 | −0.8600 ** | ||
Grain weight | 0.1796 | −0.1379 | −0.1364 | 0.0861 | −0.7382 ** | ||
MGJ200 | Panicles | 0.8297 | 0.8048 | −0.7046 | −0.5920 | 0.9921 ** | |
Spikelets per panicle | 0.5126 | 0.4972 | −0.4340 | −0.3910 | 0.9742 ** | ||
Seed setting rate | 0.2415 | −0.2051 | −0.2044 | 0.1091 | −0.8150 ** | ||
Grain weight | 0.1818 | −0.1297 | −0.1387 | 0.0821 | −0.6921 ** |
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Zhang, X.; Zhang, H.; Wang, Z.; Gao, Y.; Liu, X.; Shu, X.; Chen, Y.; Xiao, N.; Pan, C.; Zhou, J.; et al. Reduced Nitrogen Input Combined with Nitrogen-Saving japonica Rice Varieties Balances Yield and Nitrogen Use Efficiency in The Lower Reaches of the Yangtze River in China. Agronomy 2023, 13, 1832. https://doi.org/10.3390/agronomy13071832
Zhang X, Zhang H, Wang Z, Gao Y, Liu X, Shu X, Chen Y, Xiao N, Pan C, Zhou J, et al. Reduced Nitrogen Input Combined with Nitrogen-Saving japonica Rice Varieties Balances Yield and Nitrogen Use Efficiency in The Lower Reaches of the Yangtze River in China. Agronomy. 2023; 13(7):1832. https://doi.org/10.3390/agronomy13071832
Chicago/Turabian StyleZhang, Xiaoxiang, Honggen Zhang, Zi Wang, Yingbo Gao, Xin Liu, Xiaowei Shu, Yueqi Chen, Ning Xiao, Cunhong Pan, Juan Zhou, and et al. 2023. "Reduced Nitrogen Input Combined with Nitrogen-Saving japonica Rice Varieties Balances Yield and Nitrogen Use Efficiency in The Lower Reaches of the Yangtze River in China" Agronomy 13, no. 7: 1832. https://doi.org/10.3390/agronomy13071832