大白桃糖度的近红外漫反射光谱无损检测试验研究

该研究应用近红外(near infrared, NIR)漫反射光谱定量分析技术开展了金华大白桃的糖度检测试验研究。用偏最小二乘回归(partial least square regression, PLSR)方法在800～2 500 nm光谱范围建模，通过比较果汁和不同部位果肉所对应的相关模型的预测结果发现：用水果3个部位(顶部、中部、底部)共9个检测点的果肉平均光谱和糖度平均值建立的模型的结果比果汁或单独某个部位果肉(3个检测点)所建立的模型的结果要好。在此基础上，分析了光谱微分和散射校正预处理对建模结果的影响，结果显示微分光谱建立的模型不如原始光谱建立的模型的结果好，光谱的散射校正处理(用多元散射校正MSC和标准正态变量变换SNV两种方法)有助于提高模型的预测性能。最终建立桃子果肉平均光谱经MSC和SNV散射校正后与糖度的相关模型，MSC和SNV对建模结果的影响基本一致，MSC-PLSR和SNV-PLSR模型的相关系数Rcal和交互验证相关系数Rcross-v分别为0.997和0.939。该研究表明近红外光谱检测技术可用于金华大白桃糖度的定量分析。

Nondestructive Sugar Content Determination of Peaches by Using Near Infrared Spectroscopy Technique

Near infrared (NIR) spectroscopy has been widely studied and used for rapid and nondestructive measurement of internal qualities of fruits such as sugar content, acidity, firmness, etc. The objective of the present research was to study the potential of NIR diffuse reflectance spectroscopy as a nondestructive method for the determination of sugar content of Jinhua peaches. NIR spectral data were acquired in the spectral region between 800 nm and 2 500 nm using a FT-NIR spectrometer with a bifurcated optic fiber and an InGaAs detector. Statistical models were developed using partial least square regression (PLSR) method by TQ Analyst software. The results of PLSR models for peach flesh of different parts and juice indicated that the model based on average spectra of nine measurements in three different parts of each fruit and the corresponding sugar content obtained better results than those models based on the flesh of one part of each fruit (three measurements) or juice. Spectral data preprocessing of derivative and scattering correction was also discussed. The results showed that the models based on original spectra were better than those based on derivative spectra; and spectra scattering correction could improve the performance of PLSR models. Finally, two models were established based on spectra after multiplicative scattering correction (MSC) and standard normal variate (SNV) preprocessing. The correlation coefficients of calibration and leave-one-out cross-validation of the two models were the same, Rcal=0.997 and Rcross-v=0.939. These results show that it is feasible to use NIR spectroscopy technique for quantitative analysis of peach sugar content.