Application of partial least squares in vinegar discriminant analysis

Objective: To establish a new method with a combination of1H- NMR technique and multivariate analysis applied for the discrimination of different vinegars.Methods: The chemical information of the vinegar was obtained using1H- NMR spectroscopy, and the spectra were transformed to a matrix using MestRe Nova software.Then the data were analyzed by PLS method using SIMCA- P ( 13.0) software. Results: The pattern recognition analysis by PLS ( Partial Least Squares) showed clear separation of different vinegar, and the model was confirmed by internal and external validations. The obtained RMSEE and RMSEP values also suggested the PLS model had strong predictability for discriminating different vinegars.Conclusion: a combination between non- targeted1H- NMR data and chemometric information obtained by the PLS regression approach was proposed to provide a highly reliable and accurate prediction model for distinguishing different vinegars.