CAJ | 학술논문

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。
탐토응용부리협근홍외광보기술쾌속정량검측석육산개화과양화치적방법。석육양품경분쇄、혼균후재AntarisⅡ부리협근홍외광보분석의상소묘,획득기근홍외광보여국표법측정적산개화과양화치함량수거진행관련,용부리협변환근홍외광보기술결합편최소이승법건립근홍외광보여석육산개화과양화치함량적수학모형병진행예측。결과표명：산개모형중,교정결정계수화교차험증결정계수분별시0.99582화0.98687,교정균방차화교차험증균방차분별시0.1370화0.1900;과양화치모형중,교정결정계수화교차험증결정계수분별시0.99999화0.99926,교정균방차화교차험증균방차분별시0.756×10-4화0.684×10-3。용해모형대험증집양본진행예측병통계분석,표명예측치여측정치무현저차이,부리협근홍외광보기술쾌속정량검측석육산개화과양화치시가행적。
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.