Want a Better Tasting Strawberry? Artificial Intelligence Is on the Case
April 7, 2021 In the future, strawberries may be larger and more flavorful than ever before thanks to computer technology. And that day could be a lot sooner than you think. New University of Florida research shows artificial intelligence can help scientists breed more flavor into the fruit.
Consumer panels are and have been the proven method for researchers to gauge whether new fruit varieties taste good enough to keep developing them for the market. But, in the evolving world of artificial intelligence, a computer can now give the same kind of vital feedback regarding aroma and taste – in a fraction of the time.
Vance Whitaker, a UF/IFAS Associate Professor of horticultural sciences, used an algorithm that gives him the ability to predict how a strawberry will taste, based on the chemical constitution of its fruit.
He published new research in the journal Nature Horticulture Research in which he and his team used taste-test panels and computer technology to identify the volatiles that give strawberries their unique tangy flavor.
Over seven years, 384 consumers came to the UF Sensory Lab in Gainesville to give their feedback on flavor and aroma of strawberry varieties. Whitaker and his team compared consumer preferences with results that came from an already established algorithm and found the volatiles he needs to boost in strawberries he breeds in the future to improve their flavor.
“Some volatiles are more important than others,” Whitaker says. “Knowing this allows us to focus in on a few high-impact breeding targets. In other words, now we know which volatile compounds we want to increase in breeding to achieve better flavor.”
To do the analysis, you need the sensory ratings and the chemical data on the same variety of strawberry, said Whitaker. Additionally, samples of strawberries from the same batch of fruit were sent to the lab for taste panels and chemical analysis simultaneously. Volunteers and the computer gave ratings for various UF/IFAS-bred strawberry varieties, including ‘Sensation’, ‘Florida Radiance’, and ‘Florida Beauty’.
The algorithm uses those data sets and compares them. Scientists found if they can measure the sugars, acids, and volatiles in each strawberry, they can predict with a high degree of certainty how good it will taste.
“In other words, you train the algorithm with both of those data sets, and it learns to predict the panel ratings from the chemical data,” Whitaker adds. “Basically, this helps us breed smarter for flavor.”
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