RESULTS: The mean values of colour features in RGB R m , G m , B m , normalised RGB R nm , G nm , B nm HSV H m , S m , V m , and L*a*b* L m , a m , b m were the best estimator for predicting TSS with R2 ≥ 0.90. All colour channels also showed satisfactory accuracies of R2 ≥ 0.80 in predicting the bioyield force, apparent modulus and mean force. The highest average classification accuracy was obtained using LDA with an average accuracy of more than 82%. The study showed that LDA, LSVM, QDA and QSVM obtained the correct classification of up to 100% for R5, whereas R1, R2, R3 and R4 gave classification accuracies in the range between 83.75-91.85%, 85.6-90.25%, 85.75-90.85% and 77.35-87.15% respectively. This indicates R5 colour information was obviously different from R1-R4. The mean values of the HSV channel indicated the best performance to predict the ripening stages of papaya, compared to RGB, normalised RGB and L*a*b*channels, with an average classification accuracy of more than 80%.