Feasibility Study on Quantitative Pixel-Level Visualization of Internal Quality at Different Cross Sections Inside Postharvest Loquat Fruit

Visualizing the quality variation inside loquat fruit at pixel level is important to deeply understand its ripening process and further optimize its preharvest planting pattern and postharvest storage strategy. Total soluble solids (TSS) is a major quality attribute of loquat fruit and detecting changes in its content can be used to monitor the ripening and postharvest senescence of loquat fruit. The refractometer method cannot provide detailed TSS distribution within loquat flesh, because the analysis focuses on measuring the mean TSS of only a flesh cube, which is used to make juice for the refractometer measurement. In this study, hyperspectral imaging was used to measure and visualize internal TSS distribution within loquat fruit. Loquat fruits with different TSS contents were selected and cut at different cross sections for imaging. Different calibration and wavelength selection algorithms were applied and compared. The uninformative variable elimination by partial least square regression model with preprocessing from spectral set I (468–1026 nm) was identified as the best model for the TSS determination of loquat flesh, which had a high prediction ability with a correlation coefficient of 0.960 and residual predictive deviation of 3.513. On the basis of the best model, the quantitative TSS distribution at different cross sections inside loquat fruit was visualized at pixel level. The results showed that hyperspectral imaging is a feasible way of visualizing the spatial changes of TSS distribution inside loquat fruit at pixel level, which would be helpful to understand the detailed TSS change inside postharvest loquat fruit.