Rapid Detection of Surface Color of Shatian Pomelo Using Vis-NIR Spectrometry for the Identification of Maturity

Abstract

Shatian pomelo is one kind of high-quality fruits grown in south China. Modern agricultural planting technology for Shatian pomelo closely relates to the rapid identification of its maturity. As surface color reflects the maturity of fruits, quantitative determination on the color indices of L*, a*, and b* is significant for maturity judgment. Chemoinformatic models were applied for quantitative detection of L*, a*, and b* for Shatian pomelo, by using visible and near-infrared (Vis-NIR) spectrometry. To enhance the analytical accuracy and model stability, we proposed the combined use of moving window partial least squares (MWPLS) and modified optical path length estimation and correction (MOPLEC) to search for high-signal wavelength combinations, in fully optimizing the modeling parameters. Results indicated that the chemoinformatics that we proposed performed well for nondestructive evaluations of the maturity of Shatian pomelo. This technology is expected to be utilized for quality evaluations of some other agricultural and planting fruits.