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

Jintao Wang, Shaozhong Kang, Xiaotao Zhang, Taisheng Du, Ling Tong, Risheng Ding and Sien Li

Agricultural Water Management, 2018, vol. 209, issue C, 188-196

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.

Keywords: Flowering characteristics; Water deficit; Relative evapotranspiration; Maize pollen density; Seed-set capacity (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:agiwat:v:209:y:2018:i:c:p:188-196

DOI: 10.1016/j.agwat.2018.07.014

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