提取近红外光谱有效变量快速检测猪肉挥发性盐基氮
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摘要
以市售新鲜冷藏(4℃)猪肉为研究对象,采用蒙特卡洛-无信息变量消除算法和连续投影算法对原始近红外光谱的800个波长变量进行提取,共筛选出与挥发性盐基氮含量直接和间接相关的有效波长变量36个,并采用偏最小二乘法构建预测模型,验证集的相关系数和标准偏差分别为0.876 4和1.205 7 mg/100 g。
Total volatile basic nitrogen(TVB-N) content is an important reference index for evaluating pork freshness. This study attempted to measure the TVB-N content in pork meat using near infrared spectroscopy with Monte Calo uniformative variable elimination(MCUVE) and successive projections algorithm(SPA). The results showed that 36 effective wavelength variables directly and indirectly related to the TVB-N content were selected with MCUVE and SPA from the 800 wavelength variables in the original NIR spectra of fresh chilled pork(at 4 ℃), and the proposed partial least squares(PLS) model had good performance with correlation coefficient of prediction(Rp) of 0.876 4, and standard error of prediction(sEP) of 1.205 7 mg/100 g, respectively.
Total volatile basic nitrogen(TVB-N) content is an important reference index for evaluating pork freshness. This study attempted to measure the TVB-N content in pork meat using near infrared spectroscopy with Monte Calo uniformative variable elimination(MCUVE) and successive projections algorithm(SPA). The results showed that 36 effective wavelength variables directly and indirectly related to the TVB-N content were selected with MCUVE and SPA from the 800 wavelength variables in the original NIR spectra of fresh chilled pork(at 4 ℃), and the proposed partial least squares(PLS) model had good performance with correlation coefficient of prediction(Rp) of 0.876 4, and standard error of prediction(sEP) of 1.205 7 mg/100 g, respectively.
引文
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[20]HAO Y,SUN X,ZHANG H,et al.Application of effective wavelength selection methods to determine total acidity of navel orange[J].Sensor Letters,2011,9(3):1229-1234.
[21]ROSESEL R V,BEHRENS T.Using data mining to model and interpret soil diffuse reflectance spectra[J].Geoderma,2010,158(1):46-54.
[2]刘燕德,陈兴苗,欧阳爱国.可见/近红外光谱法无损检测赣南脐橙可溶性固形物[J].光学学报,2008,28(3):478-481.
[3]赵杰文,郭志明,陈全胜,等.近红外光谱法快速检测绿茶中儿茶素的含量[J].光学学报,2008,28(12):2302-2306.
[4]丁海泉,卢启鹏,朴仁官,等.土壤有机质近红外光谱分析组合波长的优选[J].光学精密工程,2007,15(12):1946-1951.
[5]刘飞,何勇,王莉.黄酒糖度预测的可见-近红外光谱方法研究[J].光学学报,2008,27(11):2054-2058.
[6]韩东海,王加华.水果内部品质近红外光谱无损检测研究进展[J].中国激光,2008,35(8):1123-1131.
[7]侯瑞锋,黄岚,王忠义,等.用近红外漫反射光谱检测肉品新鲜度的初步研究[J].光谱学与光谱分析,2007,26(12):2193-2196.
[8]CAI J,CHEN Q,WAN X,et al.Determination of total volatile basic nitrogen(TVB-N)content and Warner-Bratzler shear force(WBSF)in pork using fourier transform near infrared(FT-NIR)spectroscopy[J].Food Chemistry,2011,126(3):1354-1360.
[9]蔡健荣,万新民,陈全胜.近红外光谱法快速检测猪肉中挥发性盐基氮的含量[J].光学学报,2009,29(10):2808-2812.
[10]马世榜,彭彦昆,徐杨,等.可见/近红外光谱结合变量选择方法检测牛肉挥发性盐基氮[J].江苏大学学报(自然科学版),2013,34(1):44-48.
[11]JOLLIFFE I T.Discarding variables in a principal component analysis.I:artificial data[J].Applied Statistics,1972,21(2):160-173.
[12]ZHANG Z Y.Determination of hesperidin in Tangerine leaf by near-infrared spectroscopy with SPXY algorithm for sample subset partitioning and Monte Carlo cross validation[J].Spectroscopy and Spectral Analysis,2009,29(4):964-968.
[13]YANG H,KUANG B,MOUAZEN A.Quantitative analysis of soil nitrogen and carbon at a farm scale using visible and near infrared spectroscopy coupled with wavelength reduction[J].European Journal of Soil Science,2012,63(3):410-420.
[14]CAI W,LI Y,Sh AO X.A variable selection method based on uninformative variable elimination for multivariate calibration of nearinfrared spectra[J].Chemometrics and Intelligent Laboratory Systems,2008,90(2):188-194.
[15]PONTESMJ C,GALVARK H,ARAUJOMC U,et al.The successive projections algorithm for spectral variable selection in classification problems[J].Chemometrics and Intelligent Laboratory Systems,2005,78(1):11-18.
[16]GELADI P,KOWALSKI B R.Partial least-squares regression:a tutorial[J].Analytica Chimica Acta,1986,185:1-17.
[17]叶莺,陈崇帼,林熙.偏最小二乘回归的原理及应用[J].海峡预防医学杂志,2005,11(3):3-6.
[18]LEARDI R.Application of a genetic algorithm to feature selection under full validation conditions and to outlier detection[J].Journal of Chemometrics,1994,8(1):65-79.
[19]DU G,CAI W,SHAO X.A variable differential consensus method for improving the quantitative near-infrared spectroscopic analysis[J].Science China Chemistry,2012,55(9):1946-1952.
[20]HAO Y,SUN X,ZHANG H,et al.Application of effective wavelength selection methods to determine total acidity of navel orange[J].Sensor Letters,2011,9(3):1229-1234.
[21]ROSESEL R V,BEHRENS T.Using data mining to model and interpret soil diffuse reflectance spectra[J].Geoderma,2010,158(1):46-54.