Soluble solids content monitoring and shelf life analysis of winter jujube at different maturity stages by Vis-NIR hyperspectral imaging

Visible and near infrared (Vis-NIR) hyperspectral imaging was used for soluble solids content (SSC) monitoring and shelf life analysis of winter jujube at different maturity stages. Relationships between SSC of mid-ripe and ripe fruit and their spectral data were investigated using support vector regression (SVR) and partial least squares regression (PLSR) models. The best determination coefficient and residual predictive deviation of the external validation set were 0.837 and 2.47 for mid-ripe winter jujube, and 0.806 and 2.28 for ripe winter jujube, respectively. This implied that the more effective prediction performances for SSC emerged from SVR model using the effective wavelengths screened by successive projections algorithm (SPA). A significant correlation between the spatial distribution of SSC and maturity and shelf life was found in the prediction maps. Furthermore, shelf life was analyzed using a library for support vector machines (LIBSVM) with an accuracy of 89% and 91% for mid-ripe and ripe fruit in the external validation set, respectively. These results indicate the great potential of hyperspectral imaging for quality monitoring and shelf life analysis of postharvest winter jujube. •SSC in winter jujube significantly correlated with maturity stage and shelf life.•The SPA-SVR model performed well in SSC prediction.•Spatial distribution was mapped for monitoring SSC evolution.•The SPA-LIBSVM model was satisfactory for shelf life analysis.