Unlocking China's grain yield potential: Harnessing technological and spatial synergies in diverse cropping systems

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Agricultural Systems Pub Date : 2025-03-08 DOI:10.1016/j.agsy.2025.104308

Zhen-Zhong Dai , Sen Chang , Guo-Rong Zhao , Jia-Jia Duan , Hao-Yuan Liang , Zhi-Yuan Zhu , Sheng-Li Liu , Yong-Zhong Feng , Xing Wang

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引用次数: 0

Abstract

Context

Diversified cropping patterns (CPs) offer significant technical advantages in improving crop yields and enhancing resource efficiency. Achieving high-precision, multi-objective spatial optimization of CPs layouts is essential for implementing precise food security policies and building sustainable agricultural systems.

Objective

This study aims to analyze and predict the spatiotemporal evolution trends of seven CPs for maize, rice, and wheat in China from 2015 to 2030. It seeks to identify high-precision potential yield enhancement zones and multi-season cropping restoration zones and propose spatial optimization plans and technical optimization strategies for CPs.

Methods

Using the PLUS-Bayesian network-Geodetector framework, this study predicts the spatial layout of CPs in 2030, conducts multi-objective spatial layout optimization, and determines technical directions for CPs in key application regions.

Results and conclusions

From 2015 to 2030, the application area of staple CPs declined significantly, with non-grain cropping and single-season grain cropping trends persisting. Multi-objective optimization results show that optimizing CP technologies in yield zones and promoting multi-season cropping in restoration zones could increase grain yields by over 100 million tons, reduce nitrogen fertilizer use, and improve water management efficiency. Regional differences in CPs evolution and yield-influencing factors were identified, and zoning optimization plans and technical directions for 2030 were proposed.

Significance

This study presents a high-precision, multi-objective spatial optimization method for cropping patterns, offering practical solutions for increasing crop yields, improving resource efficiency, and supporting sustainable agriculture in China. It also provides new ideas and methods for building a sustainable global agricultural development framework.

Abstract Image

查看原文本刊更多论文

释放中国粮食产量潜力：利用不同种植制度的技术和空间协同效应

多样化种植模式在提高作物产量和提高资源效率方面具有显著的技术优势。实现CPs布局的高精度、多目标空间优化对于实施精准粮食安全政策和构建可持续农业系统至关重要。目的分析和预测2015 - 2030年中国玉米、水稻和小麦7种CPs的时空演变趋势。确定高精度的增产潜力区和多季种植恢复区，提出CPs的空间优化方案和技术优化策略。方法采用plus -贝叶斯网络-地理探测器框架，预测2030年城市CPs的空间布局，进行多目标空间布局优化，确定重点应用区域CPs的技术方向。结果与结论2015 - 2030年，主粮cp的应用面积明显减少，非粮食种植和单季粮食种植趋势持续。多目标优化结果表明，优化产区CP技术，在恢复区推广多季种植，可使粮食增产1亿吨以上，减少氮肥用量，提高水分管理效率。分析了区域内cp演化和产量影响因素的差异，提出了2030年分区优化规划和技术方向。本研究提出了一种高精度、多目标的种植格局空间优化方法，为提高作物产量、提高资源效率、支持中国农业可持续发展提供了切实可行的解决方案。为构建可持续的全球农业发展框架提供了新的思路和方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Agricultural Systems 农林科学-农业综合

CiteScore

13.30

自引率

7.60%

发文量

174

审稿时长

30 days

期刊介绍： Agricultural Systems is an international journal that deals with interactions - among the components of agricultural systems, among hierarchical levels of agricultural systems, between agricultural and other land use systems, and between agricultural systems and their natural, social and economic environments. The scope includes the development and application of systems analysis methodologies in the following areas: Systems approaches in the sustainable intensification of agriculture; pathways for sustainable intensification; crop-livestock integration; farm-level resource allocation; quantification of benefits and trade-offs at farm to landscape levels; integrative, participatory and dynamic modelling approaches for qualitative and quantitative assessments of agricultural systems and decision making; The interactions between agricultural and non-agricultural landscapes; the multiple services of agricultural systems; food security and the environment; Global change and adaptation science; transformational adaptations as driven by changes in climate, policy, values and attitudes influencing the design of farming systems; Development and application of farming systems design tools and methods for impact, scenario and case study analysis; managing the complexities of dynamic agricultural systems; innovation systems and multi stakeholder arrangements that support or promote change and (or) inform policy decisions.