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Non-destructive Determination of the quality components in fresh pork meat using near diffuse reflectance spectroscopy

机译:在漫反射光谱附近使用近漫反射光谱法不破坏性测定新鲜猪肉中的质量成分

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Two kinds of sampling methods of optics integrating sphere diffuse reflectance chamber and optical fiber diffuse reflectance probe were employed to collect the near-infrared spectra of 72 fresh lean pork meat samples, respectively. The amount of fat, protein and water in pork meat were determined by the national standard analysis methods as reference. The quantitative analysis models of the above constituents in pork meat were developed by using partial least squares (PLS) regression with internal cross-validation and optimized through spectra pretreatment and spectra region selection. The correlation coefficients (R~2) of the calibration models of fat, protein and water based on integrating sphere diffuse reflectance were 90.24%, 91.95% and 90.15%, respectively. And the values of RMSECV of these models were 0.377%, 0.011% and 0.323%, respectively. For the models on optical fiber bundle diffuse reflectance spectra, the values of R~2 were 83.68%, 87.97% and 83.27% respectively, the values of RMSECV were 0.321%, 0.0099% and 0.277%, respectively. The calibration models were further validated by the prediction sample sets. The prediction mean square error (RMSEP) of the three constituents were 0.254%, 0.011% and 0.168% for the models established on integrating sphere diffuse reflectance spectra, the value of R~2 were 96.64%, 91.51% and 97.45%, respectively. For the models on diffuse reflectance optic fiber probe spectra, the values of RMSEP were 0.361%, 0.012% and 0.193%, respectively, the values of R~2 were 81.03%, 84.48% and 91.39%, respectively. T test results showed that there was no significant difference between actual values and the values predicted by the NIR models. Although the optical integrating sphere got a little higher prediction accuracy and stability than the optical fiber diffuse reflectance probe, both sampling methods could meet the rapid non-destructive determination of the amounts fat, protein and water in pork meat, and the latter is more suitable for hand-held and convenient.
机译:使用两种光学光学聚散射反射室和光纤漫射反射探针的采样方法分别收集72个新鲜贫猪肉样品的近红外光谱。猪肉中脂肪,蛋白质和水的量由国家标准分析方法确定为参考。通过使用内部交叉验证的局部最小二乘(PLS)回归和通过光谱预处理和光谱区域选择来开发猪肉中上述成分的定量分析模型。基于整合球漫射反射率的脂肪,蛋白质和水校准模型的相关系数(R〜2)分别为90.24%,91.95%和90.15%。这些模型的RMSECV的值分别为0.377%,0.011%和0.323%。对于光纤束弥散反射光谱的模型,R〜2的值分别为83.68%,87.97%和83.27%,RMSECV的值分别为0.321%,0.0099%和0.277%。预测样本集进一步验证了校准模型。在集成球体漫反射光谱上建立的模型的三种成分的预测均方误差(RMSEP)为0.254%,0.011%和0.168%,R〜2的值分别为96.64%,91.51%和97.45%。对于弥漫反射光纤探针探针光谱的模型,RmSEP的值分别为0.361%,0.012%和0.193%,R〜2的值分别为81.03%,84.48%和91.39%。 T测试结果表明,实际值与NIR模型预测的值之间没有显着差异。尽管光学积分球比光纤漫射反射探针具有更高的预测精度和稳定性,但是两种采样方法都可以满足猪肉中脂肪,蛋白质和水的快速无损测定,后者更适合用于手持和方便的。

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