Fresh water isn't unlimited. Rainfall isn't predictable. And plants aren't always thirsty. Just 3 percent of the world's water is drinkable, and more than 70 percent of that fresh water is used for agriculture. Unnecessary irrigation wastes huge amounts of water -- some crops are watered twice as much as they need -- and contributes to the pollution of aquifers, lakes and oceans. A predictive model combining information about plant physiology, real-time soil conditions and weather forecasts can help make more informed decisions about when and how much to irrigate. This could save 40 percent of the water consumed by more traditional methods, according to new Cornell University research. "If you have a framework to connect all these excellent sources of big data and machine learning, we can make agriculture smart," said Fengqi You, energy systems engineering professor. You is the senior author of "Robust Model Predictive Control of Irrigation Sys...
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