Yield, Economic Performance, and Machine Learning-Based Prediction of Wheat across Diverse Cropping Systems and Varieties under Arid Conditions of Rajasthan, India

Smart Agricultural Technology一手来源 · 原始研究11月1日 · 周日阅读 0

核心看点

基于多耕作制度与品种数据的小麦产量机器学习预测研究，方法有参考价值但属区域性论文，未达每日精选门槛。

关注点

该研究在印度拉贾斯坦邦干旱条件下比较多种种植制度与小麦品种的产量和经济表现，并构建机器学习预测模型，可为旱区作物产量预测建模提供方法参照，结论外推需谨慎。

发布主体的原始资料；自述数据与结论仍以原文限定为准。

论文信息

Madan Lal Reager / Sandip Garai / Maksud Hasan Shah 等 8 人

Smart Agricultural Technology

DOI: 10.1016/j.atech.2026.102735

论文摘要

Yield, Economic Performance, and Machine Learning-Based Prediction of Wheat across Diverse Cropping Systems and Varieties under Arid Conditions of Rajasthan, India。Smart Agricultural Technology

论文原文与出版信息

Smart Agricultural Technology

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农业人工智能

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智慧农业产量预测小麦旱区农业

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