Predicting Maturity Quality Parameters of Strawberries Using Hyperspectral Imaging

Abstract

Non-destructive measurement of some internal properties of fruits for quality and safety isbecoming important to the consumers and the industry in whole. The main goal of this research is to developprediction models that can estimate firmness and soluble solids content (SSC) in Akihime strawberries usinghyperspectral imaging in the visible range. A spectral imaging system was developed based on a liquid crystaltunable filter to take images from 450 nm to 650 nm at 2 nm interval. Using the technically ripe sample sets, thefive-predictor firmness model (510, 650, 644, 628, and 598 nm) had an SEP of 0.364 and a correlationcoefficient r of 0.784. The SSC calibration models, however, require individual maturity level analysis for morereliable predictions.