In this study, apples were damaged by dropping from different heights(40、60、80、100 and 120 cm) to the marble ground and stored at 1 °C and then the quality and dielectric parameters of the apples were measured after different storage durations (1、5、9、13、17、21 and 25 d). The results showed that the firmness, density, titratable acidity (TA), vitamin C and moisture content decreased, the browning degree and total soluble solid/titratable acidity(TSS/TA) increased, the total soluble solid (TSS) exhibited a increasing–decreasing trend with the storage time increased. The higher the drop height of the apples, the lower the firmness, density, TSS, TA, vitamin C and moisture content and the greater the browning degree and TSS/TA. A principal component analysis showed that two principle components could represent the dielectric parameters of the damaged fruit, and the accumulated variance contribution rate was more than 80%. At the characteristic frequency, which was selected using a gray correlation analysis, the principle components predicted the quality parameters and established the prediction models for quality parameters. The determination coefficients of prediction equation about density, TSS, TA, vitamin C and moisture content were all greater than 0.6, it was indicated that the prediction results of these quality parameters were better. The results are expected to provide a reference for the rapid evaluation of quality changes for damaged fruit by using electrical properties.

中文翻译：

---

利用介电特性测定青苹果的理化品质

本研究通过将苹果从不同高度（40、60、80、100和120 cm）掉落到大理石地面上并在1°C下存放来对其进行损坏，然后在不同存放时间下测量苹果的质量和介电参数（1、5、9、13、17、21和25 d）。结果表明，硬度，密度，可滴定酸度（TA），维生素C和水分含量降低，褐变度和总可溶性固形物/可滴定酸度（TSS / TA）增加，总可溶性固形物（TSS）呈增加趋势–随存放时间的增加呈下降趋势。苹果的跌落高度越高，硬度，密度，TSS，TA，维生素C和水分含量越低，褐变程度和TSS / TA越大。主成分分析表明，两个主成分可以代表损伤果实的介电参数，累积方差贡献率大于80％。在使用灰色关联分析选择的特征频率处，主成分预测质量参数并建立质量参数预测模型。有关密度，TSS，TA，维生素C和水分含量的预测方程的确定系数均大于0.6，表明这些质量参数的预测结果较好。预期结果将为通过使用电性能快速评估受损水果的质量变化提供参考。在使用灰色关联分析选择的特征频率处，主成分预测质量参数并建立质量参数预测模型。有关密度，TSS，TA，维生素C和水分含量的预测方程的确定系数均大于0.6，表明这些质量参数的预测结果较好。预期结果将为通过使用电性能快速评估受损水果的质量变化提供参考。在使用灰色关联分析选择的特征频率处，主成分预测质量参数并建立质量参数预测模型。有关密度，TSS，TA，维生素C和水分含量的预测方程的确定系数均大于0.6，表明这些质量参数的预测结果较好。预期结果将为通过使用电性能快速评估受损水果的质量变化提供参考。维生素C和水分含量均大于0.6，表明这些质量参数的预测结果较好。预期结果将为通过使用电性能快速评估受损水果的质量变化提供参考。维生素C和水分含量均大于0.6，表明这些质量参数的预测结果较好。预期结果将为通过使用电性能快速评估受损水果的质量变化提供参考。