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Simulating kernel number under different water regimes using the Water-Flowering Model in hybrid maize seed production

Author

Listed:
  • Wang, Jintao
  • Kang, Shaozhong
  • Zhang, Xiaotao
  • Du, Taisheng
  • Tong, Ling
  • Ding, Risheng
  • Li, Sien

Abstract

Flowering Model, can accurately simulate the kernel number of maize based on the flowering characteristics and is very suitable for hybrid maize seed production where the number of pollen grain is always the main strain for kernel formation. However, it isn’t suitable for the water deficit condition. Therefore, the Water-Flowering Model was built by incorporating the seed-set capacity of female plant into Flowering Model and simulating the effect of water deficit on flowering characteristics in the form of water production function. The experiment conducted at Shiyanghe Experimental Station of China Agricultural University in 2014 and 2015 was used to calibrate and validate the Water-Flowering Model, respectively. The regression coefficient (b), determination coefficient (R2), relative root mean square error (RRMSE), Nash and Sutcliff modelling efficiency (EF), average relative error (ARE) and concordance index d of Willmott between the measured data and simulated results of 2015 was 0.78, 0.78, 0.2787, 0.29, 0.2501 and 0.84, respectively. To some extent, the model can be used to simulate kernel number in hybrid maize seed production under different water regimes in this area. But the key parameter, pollen density threshold (PDmin), is heavily influenced by meteorological factors. Therefore, PDmin should be related to meteorological factors instead of using an average value during the flowering stage to accurately simulate kernel number using Water-Flowering Model.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:agiwat:v:209:y:2018:i:c:p:188-196
    DOI: 10.1016/j.agwat.2018.07.014
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    References listed on IDEAS

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    1. Chen, Jinliang & Kang, Shaozhong & Du, Taisheng & Guo, Ping & Qiu, Rangjian & Chen, Renqiang & Gu, Feng, 2014. "Modeling relations of tomato yield and fruit quality with water deficit at different growth stages under greenhouse condition," Agricultural Water Management, Elsevier, vol. 146(C), pages 131-148.
    2. Yang, J.M. & Yang, J.Y. & Liu, S. & Hoogenboom, G., 2014. "An evaluation of the statistical methods for testing the performance of crop models with observed data," Agricultural Systems, Elsevier, vol. 127(C), pages 81-89.
    3. 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.
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    Cited by:

    1. Kang, Jian & Hao, Xinmei & Zhou, Huiping & Ding, Risheng, 2021. "An integrated strategy for improving water use efficiency by understanding physiological mechanisms of crops responding to water deficit: Present and prospect," Agricultural Water Management, Elsevier, vol. 255(C).
    2. 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.
    3. 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).
    4. 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).

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