Machine learning is making fruits and vegetables more delicious

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And revealing surprises about why we like some varieties more than others. 🍎 engineering

Actually, there are several reasons. Most of them stem from the fact thatof what the food industry encourages plant breeders to prioritize when developing new varieties — called “cultivars” — of produce.

The researchers behind this study focused on dozens of varieties of tomatoes and blueberries, including commercial cultivars sold in supermarkets, heirloom varieties more likely to be found at farmers markets and farm-to-table restaurants, and newly developed strains that recently graduated from breeding programs.

Their model revealed how much the various chemical components correlated with the human tasters' ratings for each of the varieties. Surprisingly, the sugars and acids in the fruits only accounted for roughly half the variation in the tasters' preferences from one variety to the next. They use tools like drones and autonomous robots to “quantify whatever traits are important” in a process called high-throughput phenotyping, he says. Existing technologies have been up to the task of measuring traits like how much fruit a cultivar produces and what color those fruit are.Measuring taste has proven far more difficult because there were really just two options: the breeder could sample fruit themself or they could assemble a panel of testers.

 

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