Adaptabilities of Water Production Function Models for Rice in Cold and Black Soil Region of China

Abstract

Crop water production function models (WPFMs) are a required method to study the relationships between yield and water consumption under regulated deficit irrigation (RDI). In this study, a pot experiment was established to study the effect of water deficit during both individual growth stages and across two consecutive growth stages of rice on yield, water consumption, and water use efficiency (WUE) in 2017 and 2018. Light, medium, and severe water deficits were set as 80~90%, 70~80%, and 60~70% of fully saturated soil moisture content, respectively. The accuracies of five WPFMs were tested based on the experimental results. The results showed that yields and WUE of a light water deficit were higher than those of medium and severe water deficits at each growth stage. The yields and WUE of light drought stress treatments in the flowering and milky stages were higher than the fully saturated soil moisture control by 4~7.4% and 5.3~20.6%, respectively. Water consumption decreased with increasing water deficit across two consecutive growth stages. The Minhas model had the highest simulation accuracy of the five WPFMs, with relatively lower AE, RMSE, Cv, CRM, and higher R2, which were 0.0002, 0.0634, 6.9965, 0.0002, and 0.9951 in 2017 and 0.0110, 0.0760, 8.9882, 0.0131, and 0.9923 in 2018, respectively. The sensitivity indices for the Minhas model more accurately reflected the sensitivity of rice yield to water deficit at different growth stages in 2017 and 2018, compared with the Jensen model, Stewart model, Blank model, and Singh model. Rice yield was most sensitive to water deficit at the jointing and booting stage. The results indicate that the Minhas model is the most suitable WPFM for guiding rice irrigation practices in cold black soil regions of China.

Estimating Water Use Efficiency for Major Crops in Chihuahua, Mexico: Crop Yield Function Models vs. Evapotranspiration

“…The crop yield function holds paramount importance in agricultural contexts as it serves as a fundamental metric for assessing the productivity and efficiency of farming practices [29]. This function provides a quantitative relationship between various input factors such as water, nutrients, sunlight, and crop management practices, and the resulting output in terms of harvested crops [30].…”