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Optimizing planting density and irrigation depth of hybrid maize seed production under limited water availability

Author

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  • Shi, Rongchao
  • Wang, Jintao
  • Tong, Ling
  • Du, Taisheng
  • Shukla, Manoj Kumar
  • Jiang, Xuelian
  • Li, Donghao
  • Qin, Yonghui
  • He, Liuyue
  • Bai, Xiaorui
  • Guo, Xiaoxu

Abstract

Improvement in seed vigor and yield of hybrid maize is required to ensure food security. Optimal planting density and irrigation depth are critical for hybrid maize seed production in arid areas. Using data from 2012 to 2017, a new integrated model optimized planting density and border irrigation depth for achieving high yield and seed vigor of hybrid maize under limited water availability. For field experiments, a planting density of 9.75 plants m−2 under full irrigation was in the control treatment. The results showed that water deficit decreased yield, evapotranspiration, and aboveground biomass per plant. The highest yield was obtained for the planting density of 12.75 plants m−2 under full irrigation. The single crop coefficient and crop water production function models were modified to simulate evapotranspiration and yield, respectively. Using kernel number per plant and plant growth rate during the flowering stage, a kernel weight model was established. The maximum yield and minimum irrigation depth were weighted and kernel weight was constrained. Three minimum relative kernel weight (RKWmin) options were considered, option 1 with RKWmin= 1.00 (control), option 2 with RKWmin= 0 (unconstrained), and option 3 with RKWmin ranged from 0.60 to 0.90. In option 1, the optimal irrigation depth during the growing season under control planting density decreased by 24.3–39.4% compared to the conventional practices. In option 2, yield increased but average kernel weight decreased by 25% than control. In the option 3, average yield and water use efficiency increased by 9.2% and 6.5% compared to option 1, respectively. The average planting density decreased by 10.2%, yield reduced by 2.0%, and water use efficiency reduced by 1.7%, but kernel weight increased by 9% compared to option 2. Thus option 3 can be recommended for hybrid maize seed production with limited water availability in arid regions of Northwest China. Our research provided a new theoretical method to improve yield, and ensure seed vigor of hybrid maize in arid regions.

Suggested Citation

  • Shi, Rongchao & Wang, Jintao & Tong, Ling & Du, Taisheng & Shukla, Manoj Kumar & Jiang, Xuelian & Li, Donghao & Qin, Yonghui & He, Liuyue & Bai, Xiaorui & Guo, Xiaoxu, 2022. "Optimizing planting density and irrigation depth of hybrid maize seed production under limited water availability," Agricultural Water Management, Elsevier, vol. 271(C).
    • Handle: RePEc:eee:agiwat:v:271:y:2022:i:c:s0378377422003067
    DOI: 10.1016/j.agwat.2022.107759
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    1. Igbadun, Henry E. & Tarimo, Andrew K.P.R. & Salim, Baanda A. & Mahoo, Henry F., 2007. "Evaluation of selected crop water production functions for an irrigated maize crop," Agricultural Water Management, Elsevier, vol. 94(1-3), pages 1-10, December.
    2. Shi, Rongchao & Tong, Ling & Ding, Risheng & Du, Taisheng & Shukla, Manoj Kumar, 2021. "Modeling kernel weight of hybrid maize seed production with different water regimes," Agricultural Water Management, Elsevier, vol. 250(C).
    3. Pandey, R. K. & Maranville, J. W. & Chetima, M. M., 2000. "Deficit irrigation and nitrogen effects on maize in a Sahelian environment: II. Shoot growth, nitrogen uptake and water extraction," Agricultural Water Management, Elsevier, vol. 46(1), pages 15-27, November.
    4. Jia, Qianmin & Sun, Lefeng & Ali, Shahzad & Zhang, Yan & Liu, Donghua & Kamran, Muhammad & Zhang, Peng & Jia, Zhikuan & Ren, Xiaolong, 2018. "Effect of planting density and pattern on maize yield and rainwater use efficiency in the Loess Plateau in China," Agricultural Water Management, Elsevier, vol. 202(C), pages 19-32.
    5. Ren, Xinmao & Sun, Dongbao & Wang, Qingsuo, 2016. "Modeling the effects of plant density on maize productivity and water balance in the Loess Plateau of China," Agricultural Water Management, Elsevier, vol. 171(C), pages 40-48.
    6. Rao, N. H. & Sarma, P. B. S. & Chander, Subhash, 1988. "A simple dated water-production function for use in irrigated agriculture," Agricultural Water Management, Elsevier, vol. 13(1), pages 25-32, April.
    7. Pandey, R. K. & Maranville, J. W. & Admou, A., 2000. "Deficit irrigation and nitrogen effects on maize in a Sahelian environment: I. Grain yield and yield components," Agricultural Water Management, Elsevier, vol. 46(1), pages 1-13, November.
    8. Wang, Jintao & Kang, Shaozhong & Zhang, Xiaotao & Du, Taisheng & Tong, Ling & Ding, Risheng & Li, Sien, 2018. "Simulating kernel number under different water regimes using the Water-Flowering Model in hybrid maize seed production," Agricultural Water Management, Elsevier, vol. 209(C), pages 188-196.
    9. McCown, R. L. & Hammer, G. L. & Hargreaves, J. N. G. & Holzworth, D. P. & Freebairn, D. M., 1996. "APSIM: a novel software system for model development, model testing and simulation in agricultural systems research," Agricultural Systems, Elsevier, vol. 50(3), pages 255-271.
    10. Yuan, Chengfu & Feng, Shaoyuan & Huo, Zailin & Ji, Quanyi, 2019. "Effects of deficit irrigation with saline water on soil water-salt distribution and water use efficiency of maize for seed production in arid Northwest China," Agricultural Water Management, Elsevier, vol. 212(C), pages 424-432.
    11. Li, Sien & Kang, Shaozhong & Li, Fusheng & Zhang, Lu, 2008. "Evapotranspiration and crop coefficient of spring maize with plastic mulch using eddy covariance in northwest China," Agricultural Water Management, Elsevier, vol. 95(11), pages 1214-1222, November.
    12. Wang, Jintao & Kang, Shaozhong & Du, Taisheng & Tong, Ling & Ding, Risheng & Li, Sien, 2019. "Estimating the upper and lower limits of kernel weight under different water regimes in hybrid maize seed production," Agricultural Water Management, Elsevier, vol. 213(C), pages 128-134.
    13. Rotili, Diego Hernán & Abeledo, L. Gabriela & deVoil, Peter & Rodríguez, Daniel & Maddonni, Gustavo Ángel, 2021. "Exploring the effect of tillers on the water economy, plant growth and kernel set of low-density maize crops," Agricultural Water Management, Elsevier, vol. 243(C).
    14. Jiang, Zehui & Liu, Chao & Ganapathysubramanian, Baskar & Hayes, Dermot J. & Sarkar, Soumik, 2020. "Predicting county-scale maize yields with publicly available data," ISU General Staff Papers 202009110700001775, Iowa State University, Department of Economics.
    15. Wang, Yufeng & Kang, Shaozhong & Li, Fusheng & Zhang, Xiaotao, 2021. "Modified water-nitrogen productivity function based on response of water sensitive index to nitrogen for hybrid maize under drip fertigation," Agricultural Water Management, Elsevier, vol. 245(C).
    16. Zhang, Dongmei & Guo, Ping, 2016. "Integrated agriculture water management optimization model for water saving potential analysis," Agricultural Water Management, Elsevier, vol. 170(C), pages 5-19.
    17. Farre, Imma & Faci, Jose Maria, 2006. "Comparative response of maize (Zea mays L.) and sorghum (Sorghum bicolor L. Moench) to deficit irrigation in a Mediterranean environment," Agricultural Water Management, Elsevier, vol. 83(1-2), pages 135-143, May.
    18. Kang, Shaozhong & Hao, Xinmei & Du, Taisheng & Tong, Ling & Su, Xiaoling & Lu, Hongna & Li, Xiaolin & Huo, Zailin & Li, Sien & Ding, Risheng, 2017. "Improving agricultural water productivity to ensure food security in China under changing environment: From research to practice," Agricultural Water Management, Elsevier, vol. 179(C), pages 5-17.
    19. Domínguez, A. & de Juan, J.A. & Tarjuelo, J.M. & Martínez, R.S. & Martínez-Romero, A., 2012. "Determination of optimal regulated deficit irrigation strategies for maize in a semi-arid environment," Agricultural Water Management, Elsevier, vol. 110(C), pages 67-77.
    20. Jiang, Xuelian & Kang, Shaozhong & Tong, Ling & Li, Fusheng & Li, Donghao & Ding, Risheng & Qiu, Rangjian, 2014. "Crop coefficient and evapotranspiration of grain maize modified by planting density in an arid region of northwest China," Agricultural Water Management, Elsevier, vol. 142(C), pages 135-143.
    21. Li, Yong & White, Robert & Chen, Deli & Zhang, Jiabao & Li, Baoguo & Zhang, Yuming & Huang, Yuanfang & Edis, Robert, 2007. "A spatially referenced water and nitrogen management model (WNMM) for (irrigated) intensive cropping systems in the North China Plain," Ecological Modelling, Elsevier, vol. 203(3), pages 395-423.
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    Cited by:

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    2. Chen, Shichao & Liu, Wenfeng & Morel, Julien & Parsons, David & Du, Taisheng, 2023. "Improving yield, quality, and environmental co-benefits through optimized irrigation and nitrogen management of hybrid maize in Northwest China," Agricultural Water Management, Elsevier, vol. 290(C).
    3. Hao, Baozhen & Ma, Jingli & Si, Shihua & Wang, Xiaojie & Wang, Shuli & Li, Fengmei & Jiang, Lina, 2024. "Response of grain yield and water productivity to plant density in drought-tolerant maize cultivar under irrigated and rainfed conditions," Agricultural Water Management, Elsevier, vol. 298(C).
    4. Pan, Xiaofan & Zhang, Hengjia & Yu, Shouchao & Deng, Haoliang & Chen, Xietian & Zhou, Chenli & Li, Fuqiang, 2024. "Strategies for the management of water and nitrogen interaction in seed maize production; A case study from China Hexi Corridor Oasis Agricultural Area," Agricultural Water Management, Elsevier, vol. 292(C).

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