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A new approach for spatial optimization of crop planting structure to balance economic and environmental benefits

文献类型： 外文期刊

作者： Hu, Mengmeng 1 ; Tang, Huajun 1 ; Yu, Qiangyi 1 ; Wu, Wenbin 1 ;

作者机构： 1.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, State Key Lab Efficient Utilizat Arid & Semiarid A, Beijing 100081, Peoples R China

2.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Minist Agr & Rural Affairs, Key Lab Agr Remote Sensing AGRIRS, Beijing 100081, Peoples R China

关键词： Optimal crop planting structure; Multi-objective interval parameter; programming; Life cycle assessment; Dyna-CLUE model; MaxEnt model; Uncertainty analysis

期刊名称：SUSTAINABLE PRODUCTION AND CONSUMPTION （ 影响因子：9.6； 五年影响因子：10.5 ）

ISSN： 2352-5509

年卷期： 2025 年 53 卷

页码：

收录情况： SCI

摘要： With limited land resources and water scarcity, scientifically optimizing crop layouts is essential for ensuring the sustainable development of agricultural systems. This study introduces a hybrid approach to crop layout optimization in Heilongjiang Province, focusing on planting the most suitable crops in appropriate regions. The approach integrates multi-objective interval parameter programming, life cycle assessment, maximum entropy (MaxEnt), and the dynamic conversion of land use and its effects (Dyna-CLUE) model. The results indicate that slope, population density, and mean temperature of the coldest quarter are the main factors influencing the distribution of rice, maize, and soybeans, respectively. Highly suitable areas for rice cultivation account for 10.3 % of the province's land area, primarily in the Three Rivers Plain. Comparisons of the optimal planting structure from the optimized simulation to the 2021 baseline show that although economic benefits may decrease by 1.7% to 4.2 %, the crop carbon footprint could be reduced by 9.3 % to 10.7%. These findings highlight the importance of balancing economic and environmental benefits in optimizing crop structures. Furthermore, the proposed model shifts the focus from quantitative optimization of crop planting to spatial optimization, emphasizing the importance of determining where crops should be planted rather than solely focusing on how much to plant.

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