Fresh water isn’t unlimited. Rainfall isn’t predictable. And plants aren’t always thirsty.
Fresh water isn’t unlimited. Rainfall isn’t predictable. And plants aren’t always thirsty.
Just 3% of the world’s water is drinkable, and more than 70% 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% of the water consumed by more traditional methods, according to new Cornell 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, the Roxanne E. and Michael J. Zak Professor in Energy Systems Engineering in the Smith School of Chemical and Biomolecular Engineering.
Read more at Cornell University
Photo Credit: aderna via Pixabay
