Assessing guava maturity by statistical analyses of dropped fruit impact responses.

摘要

A non-destructive method for assessing the maturity of guava fruit was developed based on the mechanical properties obtained from dropped fruit impact responses. The levels of maturity were classified with cluster and discriminant analyses on the raw impact measurements and their derived indices. The number of indices being processed was reduced with stepwise regression analysis. The accuracy of classification was improved using linear discriminant analysis to 76.3% with the penetrometer stiffness as a calibrator and to 84.2% with postharvest days as a calibrator. The performance shows that falling impact together with adequate statistical analyses provides a promising non-destructive approach in assessing the maturity of guava. The non-destructive nature was validated by repeating the test on the same specimen. The test mechanism is mechanical and can therefore be integrated as the maturity inference engine on an automated guava sorter