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Optimization of kiwifruit irrigation strategies using multi-objective optimization algorithms coupled with water production functions

文献类型： 外文期刊

作者： Zheng, Shunsheng 1 ; Cui, Ningbo 1 ; Gong, Daozhi 3 ; Wang, Zhihui 1 ; Chen, Fei 1 ; Liu, Quanshan 1 ; Jiang, Shouzheng 1 ;

作者机构： 1.Sichuan Univ, State Key Lab Hydraul & Mt River Engn, Chengdu 610065, Peoples R China

2.Sichuan Univ, Coll Water Resource & Hydropower, Chengdu 610065, Peoples R China

3.Chinese Acad Agr Sci, Inst Environm & Sustainable Dev Agr, Beijing 100081, Peoples R China

关键词： Deficit irrigation; Precision irrigation; Multi-objective optimization; Water allocation strategy; Water deficit sensitivity index; Jensen model

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：8.9； 五年影响因子：9.3 ）

ISSN： 0168-1699

年卷期： 2025 年 237 卷

页码：

收录情况： SCI

摘要： Efficient irrigation strategies are crucial for improving crop yield, fruit quality, and water productivity (WP), particularly under water scarcity conditions. This study developed dated crop water production functions (DCWPF) to simulate kiwifruit yield and quality responses under deficit irrigation, and integrated them with multi-objective optimization (MOO) algorithms to identify optimal irrigation strategies under varying total available water (TAW) conditions. The Jensen model exhibited robust performance in simulating yield, while the Q-Rao model effectively captured the nonlinear response of fruit quality to water stress. Water deficit sensitivity indexes revealed that fruit expansion stage (III) was the most critical for yield, while moderate deficit during fruit maturation stage (IV) could improve quality traits. The multi-objective particle swarm optimization (MOPSO) exhibited superior performance in both computational efficiency and solution quality, highlighting its suitability for optimizing kiwifruit irrigation strategies. Under adequate TAW condition, the optimal relative evapotranspiration allocations across the four growth stages of kiwifruit were 0.53, 1.00, 1.00, and 0.90. At this strategy, a 7.2 % reduction in yield was traded off for a 9.1 % improvement in fruit quality and a 2.2 % enhancement in WP. Under limited TAW, the recommended strategies prioritized irrigation during stages III and II (flowering to fruit set stage). The findings not only provide theoretical support for irrigation water management in kiwifruit cultivation, but also demonstrate the effectiveness of coupling DCWPF with MOO algorithms for optimizing irrigation strategies, offering valuable insights into the application of multi-objective optimization in agriculture practices.

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