UF Algorithm for Tastier Strawberries
Vance Whitaker, a UF/IFAS associate professor of horticultural sciences, has developed an algorithm that allows scientists to predict how a strawberry will taste. The data is based on the chemical constitution of its fruit. And takes much less time than a typical consumer taste-test panel.
Whitaker and his team used consumer volunteers as well as the new algorithm and found the volatiles they need to boost the strawberry's flavor.
As quoted from a recent UF/IFAS blog post, Whitaker says, "Machine learning algorithms are especially useful for analyzing “big data. Some volatiles are more important than others. 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.”
The discovery has helped scientists learn that 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. A better tasting strawberry can lead to increased consumer choices as well as demand for the new tastier strawberries.