摘要
探讨应用傅里叶近红外光谱技术快速定量检测腊肉酸价和过氧化值的方法。腊肉样品经粉碎、混匀后在AntarisⅡ傅里叶近红外光谱分析仪上扫描,获得其近红外光谱与国标法测定的酸价和过氧化值含量数据进行关联,用傅里叶变换近红外光谱技术结合偏最小二乘法建立近红外光谱与腊肉酸价和过氧化值含量的数学模型并进行预测。结果表明:酸价模型中,校正决定系数和交叉验证决定系数分别是0.99582和0.98687,校正均方差和交叉验证均方差分别是0.1370和0.1900;过氧化值模型中,校正决定系数和交叉验证决定系数分别是0.99999和0.99926,校正均方差和交叉验证均方差分别是0.756×10-4和0.684×10-3。用该模型对验证集样本进行预测并统计分析,表明预测值与测定值无显著差异,傅里叶近红外光谱技术快速定量检测腊肉酸价和过氧化值是可行的。
The aim of the present study was to investigate application of Fourier transform near-infrared（FT-NIR） spectroscopy to rapidly determine the acid value（AV） and peroxide value（PV） of Chinese bacon.Samples were crushed,mixed evenly and then scanned on an Antaris Ⅱ FT-NIR analyzer.The IR spectra were correlated with the AV and PV values obtained by the national standard methods.Based on FT-NIR spectra,a mathematical predictive model was established and validated for AV and PV values,respectively,by means of partial least squares（PLS） regression.The coefficients of determination of calibration（R2cal） and cross validation（R2cv） for AV were 0.99582 and 0.98687,respectively,and the root mean square errors of estimation（RSMEE） and cross validation（RSMSECV） were 0.1370 and 0.1900,respectively.For PV,the R2cal and R2cv were 0.99999 and 0.99926,respectively,and the RSMEE and RSMSECV were 0.756 × 10-4 and 0.684 × 10-3,respectively.The models were used to verify samples and the statistical results showed that there was no significant difference between the predictive and chemical values.Thus,FT-NIR spectroscopy is applicable for rapid detection of AV and PV in Chinese bacon.
出处
《肉类研究》
2012年第3期30-33,共4页
Meat Research
基金
重庆市科技攻关计划项目(CSTC
2009AB1173)
关键词
近红外光谱
酸价
过氧化值
腊肉
偏最小二乘
FT-NIR
acid value
peroxide value
Chinese bacon
partial least squares（PLS）
