Soybean Yield Simulation and Sustainability Assessment Based on the DSSAT-CROPGRO-Soybean Model

Author:

Zhang Lei1,Cao Zhenxi123ORCID,Gao Yang134ORCID,Huang Weixiong5ORCID,Si Zhuanyun4ORCID,Guo Yuanhang1,Wang Hongbo123,Wang Xingpeng1236

Affiliation:

1. Modern Agricultural Engineering Key Laboratory at Universities of Education Department of Xinjiang Uygur Autonomous Region, College of Water Hydraulic and Architectural Engineering, Tarim University, Alar 843300, China

2. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Tarim University, Alar 843300, China

3. Western Agricultural Research Center, Chinese Academy of Agricultural Sciences, Changji 831100, China

4. Institute of Farmland Irrigation, Chinese Academy of Agricultural Sciences, Xinxiang 453002, China

5. Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, School of Environmental Studies, China University of Geosciences, Wuhan 430078, China

6. Key Laboratory of Northwest Oasis Water-Saving Agriculture, Ministry of Agriculture and Rural Affairs, Shihezi 832000, China

Abstract

In order to ensure national grain and oil security, it is imperative to expand the soybean planting area in the Xinjiang region. However, the scarcity of water resources in southern Xinjiang, the relatively backward soybean planting technology, and the lack of a supporting irrigation system have negatively impacted soybean planting and yield. In 2022 and 2023, we conducted an experiment which included three irrigation amounts of 27 mm, 36 mm, and 45 mm and analyzed the changes in dry mass and yield. Additionally, we simulated the potential yield using the corrected DSSAT-CROPGRO-Soybean model and biomass based on the meteorological data from 1994 to 2023. The results demonstrated that the model was capable of accurately predicting soybean emergence (the relative root mean square error (nRMSE) = 0, the absolute relative error (ARE) = 0), flowering (nRMSE = 0, ARE = 2.78%), maturity (nRMSE = 0, ARE = 3.21%). The model demonstrated high levels of accuracy in predicting soybean biomass (R2 = 0.98, nRMSE = 20.50%, ARE = 20.63%), 0–80 cm soil water storage (R2 = 0.64, nRMSE = 7.78%, ARE = 3.24%), and yield (R2 = 0.81, nRMSE = 10.83%, ARE = 8.79%). The biomass of soybean plants increases with the increase in irrigation amount. The highest biomass of 63 mm is 9379.19 kg·hm−2. When the irrigation yield is 36–45 mm (p < 0.05), the maximum yield can reach 4984.73 kg·hm−2; the maximum efficiency of soybean irrigation water was 33–36 mm. In light of the impact of soybean yield and irrigation water use efficiency, the optimal irrigation amount for soybean cultivation in southern Xinjiang is estimated to be between 36 and 42 mm. The simulation results provide a theoretical foundation for soybean cultivation in southern Xinjiang.

Funder

Tarim University President’s Fund Project

Major Science and Technology Project of Xinjiang Production and Construction Corps

Tarim University Graduate Student Research and Innovation Program

Publisher

MDPI AG

Reference53 articles.

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