Quantitative study of impact damage on yellow peaches based on reflectance, absorbance and Kubelka–Munk spectral data

• DOI: 10.1039/d2ra04635k
• Publication Date: 2022-10-03T10:37:47Z
• Authors: Bin Li; Feng Zhang; Yande Liu; Hai Yin; Jiping Zou; Aiguo Ou-yang
• Keywords: Absorbance

Impact damage is one of the main forms during postharvest transportation and processing yellow peaches. Thus, a quantitative prediction impact degree peaches significant for their grading. In present study, mechanical parameters such as area, absorbed energy maximum force were obtained based on single pendulum collision device an intelligent data acquisition system. The reflection spectra (R) damaged areas collected by hyperspectral imaging system transformed into absorbance (A) Kubelka-Munk (K-M) spectra. R, A K-M preprocessed standard normal variables (SNV), moving average (MA) Gaussian filtering (GF). Partial least squares regression (PLSR) models support vector (SVR) original established, respectively. By comparative analysis, spectral with better performance (raw or spectra) selected from all spectra, characteristic wavelengths competitive adaptive reweighted sampling (CARS) uninformative variable elimination (UVE). PLSR SVR established. results revealed that K-M-GF-CARS-PLSR model best. For force, R P 2 RMSEP 0.870 77.865 mm2, 0.772 1.065 J, 0.895 47.996 N, Furthermore, values RPD 2.700, 1.768 3.050, 18.8%, 10.2% 21.6%, this study showed there was strong correlation between spectrum, which demonstrates feasibility quantitatively predicting spectrum. Therefore, work not only provide theoretical guidance grading fruits, but also enrich biomechanics.