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Nondestructive detection of total acid content in vinegar based on NIR combined with partial least squares

Xia Rong

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Abstract

Rapid non-destructive testing of total acid content in vinegar Modeling.Using near infrared spectroscopy were combined with interval Partial Least Squares(iPLS),Backward interval Partial Last Squares(BiPLS),Synergy interval Partial Least Squares algorithm(SiPLS)to modeling,division of each algorithm in different intervals and the interval chosen to model the impact when compared.The results show that the BiPLS,SiPLS(2,3,4 joint interval) model is better on the model iPLSi,43 of them in the choice of sub-interval BiPLS,5 sub-range joint(3,4,6,7,16) best,the RMSECV and RMSEP were 0.2876 and 0.2726,calibration and the prediction correlation coefficient of 0.9343 and 0.938;SiPLS joint in the choice of three intervals,49 intervals(3,5,7 interval joint) best,the RMSECV and RMSEP were 0.2607 and 0.2802,calibration and the prediction correlation coefficient of

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Rapid non-destructive testing of total acid content in vinegar Modeling.Using near infrared spectroscopy were combined with interval Partial Least Squares(iPLS),Backward interval Partial Last Squares(BiPLS),Synergy interval Partial Least Squares algorithm(SiPLS)to modeling,division of each algorithm in different intervals and the interval chosen to model the impact when compared.The results show that the BiPLS,SiPLS(2,3,4 joint interval) model is better on the model iPLSi,43 of them in the choice of sub-interval BiPLS,5 sub-range joint(3,4,6,7,16) best,the RMSECV and RMSEP were 0.2876 and 0.2726,calibration and the prediction correlation coefficient of 0.9343 and 0.938;SiPLS joint in the choice of three intervals,49 intervals(3,5,7 interval joint) best,the RMSECV and RMSEP were 0.2607 and 0.2802,calibration and the prediction correlation coefficient of

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Available abstract

Rapid non-destructive testing of total acid content in vinegar Modeling.Using near infrared spectroscopy were combined with interval Partial Least Squares(iPLS),Backward interval Partial Last Squares(BiPLS),Synergy interval Partial Least Squares algorithm(SiPLS)to modeling,division of each algorithm in different intervals and the interval chosen to model the impact when compared.The results show that the BiPLS,SiPLS(2,3,4 joint interval) model is better on the model iPLSi,43 of them in the choice of sub-interval BiPLS,5 sub-range joint(3,4,6,7,16) best,the RMSECV and RMSEP were 0.2876 and 0.2726,calibration and the prediction correlation coefficient of 0.9343 and 0.938;SiPLS joint in the choice of three intervals,49 intervals(3,5,7 interval joint) best,the RMSECV and RMSEP were 0.2607 and 0.2802,calibration and the prediction correlation coefficient of

Key concepts: Partial least squares regression, Calibration, Interval (graph theory), Correlation coefficient, Mathematics, Analytical Chemistry (journal), Chemistry, Content (measure theory)

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