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Quantitative analysis and detection of adulteration in pork using near-infrared spectroscopy

机译:用近红外光谱法定量分析猪肉中的掺假

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Authenticity is an important food quality criterion. Rapid methods for confirming authenticity or detecting adulteration are increasingly demanded by food processors and consumers. Near infrared (NIR) spectroscopy has been used to detect economic adulteration in pork . Pork samples were adulterated with liver and chicken in 10% increments. Prediction and quantitative analysis were done using raw data and pretreatment spectra. The optimal prediction result was achieved by partial least aquares(PLS) regression with standard normal variate(SNV) pretreatment for pork adulterated with liver samples, and the correlation coefficient(R value), the root mean square error of calibration(RMSEC) and the root mean square error of prediction (RMSEP) were 0.97706, 0.0673 and 0.0732, respectively. The best model for pork meat adulterated with chicken samples was obtained by PLS with the raw spectra, and the correlation coefficient(R value), RMSEP and RMSEC were 0.98614, 0.0525, and 0.122, respectively. The result shows that NIR technology can be successfully used to detect adulteration in pork meat adulterated with liver and chicken.
机译:真实性是重要的食品质量标准。食品加工者和消费者越来越需要快速的方法来确认真实性或检测掺假。近红外(NIR)光谱已用于检测猪肉中的经济掺假。猪肉样品以10%的增量掺入肝和鸡肉。使用原始数据和预处理光谱进行了预测和定量分析。通过对掺有肝脏样品的猪肉进行标准正态变量(SNV)预处理,通过偏最小二乘法(PLS)回归,相关系数(R值),校准的均方根误差(RMSEC)和预测均方根误差(RMSEP)分别为0.97706、0.0673和0.0732。用原始光谱通过PLS获得了最佳的掺假鸡肉样品模型,相关系数(R值),RMSEP和RMSEC分别为0.98614、0.0525和0.122。结果表明,近红外技术可以成功地用于掺假肝,鸡肉的猪肉中的掺假。

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