Development of a deep-learning phenotyping tool for analyzing image-based strawberry phenotypes.

Additionally, when samples were categorized based on other important phenotypic parameters such as flower area, unripe fruits, and leaf area into different size-based clusters at specified times before fruit harvesting, a notable trend emerged: an increase in the size of these phenotypes was associated with a substantial increase in yield ( p <0.05) ( Figures 8B–D ). 3.5.

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