A Dynamic Process-Based Method for Screening Salt-Tolerant and High-Yielding Crop Varieties

Abstract

Maize, the most important cereal crop worldwide, is moderately sensitive to salt stress. Given the challenges of soil salinization, developing methods to screen and cultivate salt-tolerant maize varieties is vital for enhancing food security. Among the options, process model-based assisted screening is an effective method for faster and more thorough screening of salt-tolerant varieties. In this study, a method for quickly screening salt-tolerant and high-yielding crop varieties is proposed by combining a coupled model of crop growth and water–salt response with fitness function. Then, this method was applied to the saline areas of the Hetao Plain in China to demonstrate its applicability. This study includes three parts. Firstly, field trial data from 10 commonly grown maize varieties in Hetao Plain (i.e., Xianyu 335, Yinyu 238, Jindan 73, Deke 622, DK-815, Heyu 157, Xianyu 1321, Jinrun 919, Tianci 19, and Xianyu 1225) were used to calibrate the model for different maize varieties. Moreover, model accuracy was evaluated using four indexes including the regression coefficient (b), coefficient of determination (R²), root mean square error (RMSE), and Nash–Sutcliffe efficiency coefficient (NSE). Secondly, scenario simulations were conducted using the calibrated model by setting nine initial salinity scenarios to simulate daily dynamic crop growth and soil water–salt changes for the 10 maize varieties. Finally, salt-tolerant and high-yielding maize varieties were screened based on the fitness function method during crop growth periods. The results showed that the simulation model was applicable and functioned effectively for all 10 maize varieties in the region, with the determination coefficient (R2) and Nash–Sutcliffe efficiency coefficient (NSE) of simulated plant height and leaf area index being above 0.90. Furthermore, the R2 of soil water content, soil electrical conductivity, and groundwater depth are 0.51, 0.52, and 0.60, respectively. Afterward, the fitness function values were calculated to bridge the linkage between simulated indicators and scenarios to screen varieties step by step according to the predetermined percentage of screening. Jindan 73, Xianyu 1225, and DK-815 were eventually determined as the most suitable salt-tolerant and high-yielding maize varieties. Therefore, the above results show that the proposed method is suitable for saline crop variety screening with flexibility and applicability.

Keywords

• maize
• scenario simulation
• fitness function
• variety screening
• salt tolerant and high yielding
• process-based model