Machine Learning Models Predict Crop Water Use With High Accuracy

For as long as farming has existed, the question of how much water a plant truly needs on any given day has been answered with intuition and approximation. Researchers at the Hebrew University of Jerusalem have now trained machine-learning models on seven years of precise plant measurements to predict daily crop water use with meaningful accuracy — a step toward irrigation systems that listen to what plants themselves are communicating. The work, spanning tomatoes, wheat, and barley, suggests that deviations from predicted water use could serve as early warnings of stress long before a farmer'

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Machine Learning Models Predict Crop Water Use With High Accuracy

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