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ESTIMATION OF FRESHNESS OF BEEF USING NEAR-INFRARED SPECTROSCOPY

机译:近红外光谱法估计牛肉的新鲜度

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摘要

As adenosine 5'-triphosphate (ATP) is automatically degraded during storage of beef, Ki-value increases. From an experimental result showing that Ki-value was highly proportional to the volatile basic nitrogen (VBN) of beef, it was confirmed in this study that Ki-value could be a useful index for the freshness of beef. Therefore, a calibration model for estimating Ki-value was developed using near-infrared spectroscopy (NIRS) and principal component regression (PCR), and validated. The coefficient of determination (R{sup}2), standard error of calibration (SEC), and standard error of prediction (SEP) of the calibration model developed using the absorption spectra were 0.53, 8.7%, and 9.3%, respectively. To improve the prediction of the calibration model, the second-order derivative spectra were calculated and used to develop a calibration model. The NIR wavelength range of 1200 to 1300 nm produced the best calibration model, of which the R{sup}2, SEC, and SEP were 0.93, 8.3%, and 7.7%, respectively. It was concluded that it was feasible to estimate the freshness of beef through measurement of Ki-value with NIRS.
机译:由于牛肉储存过程中5'-三磷酸腺苷(ATP)会自动降解,因此Ki值会增加。从显示Ki值与牛肉的挥发性碱性氮(VBN)高度成比例的实验结果中,可以确定Ki值可以作为牛肉新鲜度的有用指标。因此,使用近红外光谱(NIRS)和主成分回归(PCR)开发了用于估计Ki值的校准模型,并进行了验证。使用吸收光谱建立的校准模型的测定系数(R {sup} 2),校准标准误差(SEC)和预测标准误差(SEP)分别为0.53、8.7%和9.3%。为了改善校准模型的预测,计算了二阶导数光谱并将其用于开发校准模型。 1200至1300 nm的NIR波长范围产生了最佳的校准模型,其中R {sup} 2,SEC和SEP分别为0.93、8.3%和7.7%。结论是,通过用NIRS测量Ki值来估计牛肉的新鲜度是可行的。

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