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Updated: Sep 19, 2025

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions
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基于机器学习的干旱预测,使用埃塞俄比亚的Palmer干旱严重程度指数和TerraClimate数据

Tadele Melese1,2, Gizachew Assefa3, Baye Terefe4

  • 1Department of Natural Resource Management, College of Agriculture and Environmental Science, Bahir Dar University, Bahir Dar, Ethiopia.

PloS one
|June 18, 2025
PubMed
概括

在埃塞俄比亚,准确的干旱预测至关重要. 机器学习模型,特别是随机森林模型,在使用气候数据对干旱严重程度的分类方面表现强,有助于水资源管理和农业规划.

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Water plays a significant role in the life cycle of plants. However, insufficient or excess of water can be detrimental and pose a serious threat to plants.
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Though evaporation from plant leaves drives transpiration, it also results in loss of water. Because water is critical for photosynthetic reactions and other cellular processes, evolutionary pressures on plants in different environments have driven the acquisition of adaptations that reduce water loss.
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