基于可解释性机器学习的影响长江流域棉花农艺性状的关键气象因子解析

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中图分类号：S562 文献标识码：A 文章编号： 1000-4440（2026）03-0554-09

，，，等.基于可解释性机器学习的影响长江流域棉花农艺性状的关键气象因子解析[J].农业学报，2026，42（3） ：554-562.

doi：10.3969/j.issn.1000-4440.2026.03.013

Analysis of key meteorological factors affecting cotton agronomic traits in the Yangtze River Basin based on interpretable machine learning

XU Jianwen， LIU Jianguang， LI Jian， ZHAO Jun， XU Xu， SHAO Mingcan（situtefs，Nanjing ，China）

Abstract：Basedon the data fromthe national coton varietyregional trials inthe Yangtze River Basin from 2020 to 2024，this studysystematicallyanalyzedtheeffectsof meteorologicalconditions at diferent growth stagesoncottonproduction，andusedthe ShapleyAdditiveExplanations （SHAP）method toquantifytheeffectsand interactionsof meteorological factors.The results showed that，compared withthe linear regresion model and the support vector machine（SVM）model， therandom forest model and the XGBoost model exhibited beter predictive performanceforcoton agronomictraitssuch as bolls per plant，fiberlength，andfiberspecific strength.Accumulated temperature，numberof high-temperaturedays，and number of sunnydays were the key meteorological factors afecting coton traits，and their effects displayed obvious stagespecificcharacteristics during the growth period： increasedaccumulated temperature during the bol-opening stage promoted earlinessandshortenedthegrowthperiod；high temperature during thewhole growth period and the flowering and boll-forming stage adversely affected fiber quality traits includingfiberlength，elongation，and uniformity；sunny days from seedling emergence to flowering were conducive to the improvement of fiber length and fiber specific strength.Synergistic or antagonistic effects existed amongmeteorological factorsduring the formationof cotton

yieldandfiberquality.Thisstudyprovidesatheoreticalbasisfortheoptimizationofcottoncultivationmanagementandthe adjustment of breeding objectives under climate change.

Key Words： coton；agronomic traits；machine learning；meteorological factors

棉花是关系国计民生的重要战略物资，具有重要的经济地位。（剩余10679字）