The quantitative description of the impact damage of yellow peaches is an essential basis for evaluating their quality and guiding their postharvest handling. In this study, the combined hyperspectral technology and mechanical parameters method were used to quantitatively investigate the impact damage of yellow peaches. Firstly, the mechanical parameters, which are damaged area, absorbed energy, maximum contact force, and maximum stress of yellow peaches, were obtained by the impact device. The statistical regression models between mechanical parameters and damage area were established, and the results showed that the absorbed energy and maximum contact force are the optimal parameters to characterize the impact damage of yellow peaches. Then, the raw spectra were preprocessed by three spectral pretreatment methods, which are standard normal variate (SNV), multiplicative scatter correction (MSC), and SG smoothing, respectively, and the feature wavelengths were selected by the competitive adaptive reweighted sampling (CARS), and the quantitative relationships between spectra and mechanical parameters were successfully modeled based on partial least squares regression (PLSR). The results showed that there is a strong linear correlation between the spectral data and the mechanical parameters, and the prediction performance of the SNV-CARS-PLSR model is best, and the RP and RMSEP of the damaged area, absorbed energy, maximum contact force, and maximum stress of it were 0.920 and 86.452 mm², 0.845 and 1.303 J, 0.943 and 49.666 N, 0.660 and 0.146 MPa, respectively. In a word, this study shows that the combined hyperspectral technology and mechanical parameters method can be used to quantitatively assess the impact damage of yellow peaches, and guide the postharvest handling of fruits.

中文翻译：

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高光谱与力学参数相结合的黄桃冲击损伤定量评价研究

黄桃冲击损害的定量描述是评价其品质和指导其采后处理的重要依据。本研究采用高光谱技术与力学参数相结合的方法对黄桃的冲击损伤进行了定量研究。首先，通过冲击装置获得了黄桃的损伤面积、吸收能量、最大接触力和最大应力等力学参数。建立力学参数与损伤面积的统计回归模型，结果表明，吸收能量和最大接触力是表征黄桃冲击损伤的最佳参数。然后，通过三种光谱预处理方法对原始光谱进行预处理，分别为标准正态变量（SNV）、乘法散射校正（MSC）和SG平滑，并通过竞争自适应重加权采样（CARS）选择特征波长，成功地建模了光谱与力学参数之间的定量关系基于偏最小二乘回归 (PLSR)。结果表明，光谱数据与力学参数之间存在很强的线性相关性，SNV-CARS-PLSR模型的预测性能最好，损伤区域的RP和RMSEP、吸收能量、最大接触力, 最大应力分别为 0.920 和 86.452 mm 并通过竞争自适应重加权采样（CARS）选择特征波长，并基于偏最小二乘回归（PLSR）成功建模光谱与力学参数之间的定量关系。结果表明，光谱数据与力学参数之间存在很强的线性相关性，SNV-CARS-PLSR模型的预测性能最好，损伤区域的RP和RMSEP、吸收能量、最大接触力, 最大应力分别为 0.920 和 86.452 mm 并通过竞争自适应重加权采样（CARS）选择特征波长，并基于偏最小二乘回归（PLSR）成功建模光谱与力学参数之间的定量关系。结果表明，光谱数据与力学参数之间存在很强的线性相关性，SNV-CARS-PLSR模型的预测性能最好，损伤区域的RP和RMSEP、吸收能量、最大接触力, 最大应力分别为 0.920 和 86.452 mm²，分别为 0.845 和 1.303 J，0.943 和 49.666 N，0.660 和 0.146 MPa。总之，本研究表明，高光谱技术与力学参数相结合的方法可用于定量评估黄桃的冲击损伤，指导果实采后处理。