Prediction of the ripening stages of papayas using discriminant analysis and support vector machine algorithms.

Background: Evaluation of the quality properties of papaya becomes essential due to the acceleration of the fruit shelf-life senescence and the deterioration factor of the expected postharvest operations. In this study, the colour features in RGB, normalised RGB, HSV and L*a*b* channels were extracted and correlated with mechanical properties, moisture content (MC), total soluble solids (TSS) and pH for the prediction of quality properties at five ripening stages of papaya (R1-R5).

Results: The mean values of colour features in RGB , normalised RGB HSV , and L*a*b* were the best estimator for predicting TSS with R  ≥ 0.

Finite Element Modelling for Predicting the Puncture Responses in Papayas.

This study aims to develop a finite element (FE) model to determine the mechanical responses of Exotica papayas during puncture loads. The FE model of the puncture-test was developed using the ANSYS 19.1 software.