The use of digital imaging, chlorophyll fluorescence and Vis/NIR spectroscopy in assessing the ripening stage and freshness status of bell pepper fruit

The optimal quality, the marketability and the shelf-life of pepper fruit often depend on the ripening stage at harvest. Moreover, it is necessary to estimate the process of ripening in various steps of the supply chain. The potential of four non-destructive techniques as rapid tools for discriminating the process of ripening was investigated. Chlorophyll fluorescence, Vis/NIR spectroscopy, two commercial digital imaging cameras- one R-G-B dslr and a modified R-G-NIR compact camera were assessed as alternatives to color measurements in classifying pepper fruit according to their ripening stage. Freshly harvested mature bell pepper fruit 'cv. Denver' were sorted in six distinct ripening stages (S1-S6), from green to full red (mature green 100% green-S1, green to brown-S2, brown-S3, orange-S4, red-S5 and full red-S6 stage), by visually assessing their color. From the results, it is concluded that the a* /b* color parameter that was determined using a colorimeter was proven to be the most accurate descriptor in ripening stage classification, either at harvest or during storage, as confirmed by che-mometrics, such as principal component (PCA), partial least square (PLS) and support vector machine (SVM) analyses and mean comparisons, as well. Therefore, the increase of a* /b* ratio can be used as an indicator to estimate the degree of fruit ripeness. The a* /b* ratio was strongly correlated with fruit spectral reflectance and chlorophyll fluorescence data, as well as with two imaging indices generated by digital R-G-B and R-G-NIR imaging techniques that are reported for the first time on fruit in this study. The above results indicate that it is possible to estimate the a* /b* ratio and simultaneously the ripening stage of pepper fruit with high accuracy and consistency, by using individually several non-destructive techniques. However, freshness status of bell pepper fruit can be reliably assessed, irrespectively of the ripening stage at harvest, only by spectral reflectance data and indeed even by processing only specific wavelengths that were identified after implementing the genetic algorithm.