In previous studies, researchers have determined the classification of fruit ripeness using feature descriptor color features (RGB, GSL, HSV, and L * a b *). However, performance from experimental results obtained still yields that are less than maximum, viz maximal accuracy is only 76%. Today, transfer learning techniques been applied successfully in many real-world applications. For this reas...

We propose data-driven approaches to water content estimation and ripeness classification of the strawberry fruit. A narrowband hyperspectral spectroradiometer was used collect reflectance signatures from 43 fruits at different levels. Then, ground truth obtained using oven-dry method. To estimate content, 674 698 nm bands were selected create a normalized difference index. The index as an inpu...