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鸡蛋是一种重要的食品,蛋白质是鸡蛋的主要营养成分。本研究利用可见近红外反射光谱技术无损检测新鲜鸡蛋的蛋白质含量。使用光谱仪获取新鲜鸡蛋在400~1100 nm波段范围内的漫反射光谱;分别使用多元散射校正(MSC)法和一阶导数法(1-D)对反射光谱进行预处理;对反射光谱、MSC处理光谱和1-D光谱,使用逐步回归法判别法选择最优波长组合,建立多元线性回归模型,使用全交叉验证法验证模型。结果表明,可见/近红外反射光谱经过多元散射校正后,确定的10个最优波长(400、403.16、407.9、714.6、715、715.58、970.4、970.75、973和974.45 nm)组合建立模型的校正和验证结果最好:选定模型的校正结果为R=0.92,SEC=0.42%;验证结果为Rcv=0.89,SECV=0.47%。研究表明可见/近红外反射光谱技术可以较好的预测新鲜鸡蛋的蛋白质含量,本研究可为可见近红外光谱技术在鸡蛋营养成分的快速检测提供一定的理论基础。
Egg is an important food, and protein is the major nutrient of eggs. In this study, non-destructive detection of fresh egg protein content using visible near-infrared reflectance spectroscopy. The diffuse reflectance spectrum of fresh eggs in the range of 400-1100 nm was obtained using a spectrometer. The reflectance spectra were preprocessed using the multivariate scatter correction (MSC) method and the first derivative method (1-D), respectively. The reflectance spectra, Spectra and 1-D spectra, the stepwise regression method was used to select the optimal wavelength combination, the multiple linear regression model was established, and the model was verified by the full cross validation method. The results show that the calibration of visible / near-infrared reflectance spectra after multiple scatter correction and the combination of the 10 optimal wavelengths (400,403.16,407.9,714.6,715,715.58,970.4,970.75,973 and 974.45 nm) The verification results are best: the calibration results of the selected model are R = 0.92, SEC = 0.42%; the verification results are Rcv = 0.89, SECV = 0.47%. The results show that visible / near-infrared reflectance spectroscopy can predict the protein content of fresh eggs well. This study can provide a theoretical basis for the rapid detection of nutritional components of eggs by visible near-infrared spectroscopy.