数字农科院2.0

Mapping the Evolution of DSSAT Model Research: Trends, Transitions, and Future Frontiers

文献类型： 外文期刊

作者： Gao, Shikai;He, Pengcheng;Fu, Yuliang;Li, Yanbin;Wang, Hongfei;Wang, Qian;He, Aofeng;Liu, Yihao;Zeng, Wei;Li, Hao;Chen, Xiaochuan;Liu, Xinru;Ren, Tianli;Wang, Yaobin;Gong, Xuewen

作者机构：

关键词： DSSAT model;bibliometric analysis;evolutionary trajectory;climate change;crop modeling

期刊名称： AGRONOMY-BASEL

ISSN：

年卷期： 2026 年 16 卷 2 期

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收录情况： SCIE（2025版）

摘要： This study presents a comprehensive bibliometric analysis of the DSSAT crop modeling field from 1990 to 2024, identifying its evolutionary trajectory and emerging frontiers. A comprehensive bibliometric analysis and network visualization were conducted using VOSviewer, CiteSpace, and Bibliometrix. Analyzing 6165 Scopus-indexed publications, we found the research focus has shifted from foundational yield simulation and calibration toward addressing complex climate-water-food challenges. Three distinct developmental phases were identified: an initial establishment phase, a methodological refinement phase, and a current technology integration phase dominated by machine learning and remote sensing applications. The results reveal that machine learning, model-data fusion, and sustainability assessment represent the most active research frontiers. This analysis provides a systematic map of the field's intellectual structure and offers evidence-based predictions for its future development, highlighting the transition of DSSAT from a specialized crop model to an interdisciplinary decision-support platform for sustainable agriculture.

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