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Ripe juicy tomatoes are perfect for just about any meal. The quality and flavor of vine ripened tomatoes is best when picked at exactly the right time. Now pioneering Artificial Intelligence (machine learning) is being developed in Israel that can help farmers optimize their harvest times to pick the finest quality produce, reported Israel 21c.
The Hebrew University Study
Researchers at Hebrew University of Jerusalem (HUJI) developed a machine learning model that can assess the quality of tomatoes before they are harvested. Traditional methods can only determine the quality only after the crops are picked.
The study, published in the Computers and Electronics in Agriculture scientific journal, found a new method that could make harvesting tomatoes easier, more cost-effective, and sustainable.
The HUJI researchers worked with researchers from Bar -Ilan University in Ramot Gan and the government’s Volcani Center Agricultural Research Organization to use hyperspectral imaging – or images of spectral bands – to develop the learning model that demonstrated a high level of prediction accuracy.
What Does This Mean for Farmers
This new method allow farmers to monitor quality parameters that include firmness, weight, citric acid, and lycopene content – an antioxidant –, according to a press release from Hebrew University.
“Our research aims to bridge the gap between advanced imaging technology, AI, and practical agricultural applications,” Dr. David Helman from the Hebrew University’s Robert H. Smith Faculty of Agriculture, Food, and Environment, said in the press release.
“This work has the potential to revolutionize quality monitoring not only in tomatoes but also in other crops. Our next step is to build a low-cost device (ToMAI-SENS) based on our model that will be used across the fruit value chain, from farms to consumers.”
AI Uses in Agriculture
With a growing world population and the need to grow 70 percent more food, using AI could go a long way in meeting the challenge, according to a blog on Basic AI.
There are many uses for AI in agriculture from increasing crop yield, precise irrigation, automated weed control, as well as using satellites to predict droughts and pest infestations. There are even robot pickers that know which fruit is ready to pick.
An Israeli startup Tevel Aerobotics Technologies developed flying autonomous robots that can pick fruit. Founder and CEO Yaniv Maor, used AI to teach the robots about each fruit, the trees, how to access the fruit, and how to pick it. The startup’s robots are picking pears in Israel and other fruits in Europe and the US.
The potential uses for AI in farming are growing by leaps and bounds. All of these advancements will go a long way to feeding a hungry world. And Israel is leading the way.
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