Accurate and rapid determination of nitrite contents is an important step for guaranteeing sausage quality.This study attempted to mine hyperspectral data in the range of 900-1700 nm for non-destructive and rapid pred...Accurate and rapid determination of nitrite contents is an important step for guaranteeing sausage quality.This study attempted to mine hyperspectral data in the range of 900-1700 nm for non-destructive and rapid prediction of nitrite contents in sausages.The average spectra of 156 samples were collected to relate to the measured nitrite values by partial least squares(PLS)regression.Optimal wavelengths were respectively selected by successive projections algorithm(SPA)and regression coefficients(RC)to simplify the PLS model.The results indicated that PLS model established with 15 optimal wavelengths(900.5 nm,907.1 nm,908.8 nm,912.1 nm,915.4 nm,920.3 nm,922.0 nm,941.7 nm,979.6 nm,1083.2 nm,1213.2 nm,1353.0 nm,1460.2 nm,1595.6 nm and 1699.9 nm)selected by SPA had better performance with r C,r CV,r P of 0.92,0.89,0.89 and RMSEC,RMSECV,RMSEP of 0.41 mg/kg,0.89 mg/kg,0.49 mg/kg,respectively,for calibration set,cross-validation and prediction set.It was concluded that hyperspectral data could be mined by PLS&SPA for realizing the rapid evaluation of nitrite content in ham sausages.展开更多
基金The authors acknowledge that this work was financially supported by the Key Scientific and Technological Project of Henan Province(Grant No.212102310491,No.182102310060)Major Scientific and Technological Project of Henan Province(No.161100110600)+2 种基金China Postdoctoral Science Foundation(No.2018M632767)Henan Postdoctoral Science Foundation(No.001801021)Youth Talents Lifting Project of Henan Province(No.2018HYTP008).
文摘Accurate and rapid determination of nitrite contents is an important step for guaranteeing sausage quality.This study attempted to mine hyperspectral data in the range of 900-1700 nm for non-destructive and rapid prediction of nitrite contents in sausages.The average spectra of 156 samples were collected to relate to the measured nitrite values by partial least squares(PLS)regression.Optimal wavelengths were respectively selected by successive projections algorithm(SPA)and regression coefficients(RC)to simplify the PLS model.The results indicated that PLS model established with 15 optimal wavelengths(900.5 nm,907.1 nm,908.8 nm,912.1 nm,915.4 nm,920.3 nm,922.0 nm,941.7 nm,979.6 nm,1083.2 nm,1213.2 nm,1353.0 nm,1460.2 nm,1595.6 nm and 1699.9 nm)selected by SPA had better performance with r C,r CV,r P of 0.92,0.89,0.89 and RMSEC,RMSECV,RMSEP of 0.41 mg/kg,0.89 mg/kg,0.49 mg/kg,respectively,for calibration set,cross-validation and prediction set.It was concluded that hyperspectral data could be mined by PLS&SPA for realizing the rapid evaluation of nitrite content in ham sausages.
