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Assessment of a Non-Destructive Method for Rapid Discrimination of Moroccan Date Palm Varieties via Mid-Infrared Spectroscopy Combined with Chemometric Models
Journal of AOAC INTERNATIONAL  (IF1.913),  Pub Date : 2021-04-30, DOI: 10.1093/jaoacint/qsab068
Elhamdaoui O, El Orche A, Cheikh A, et al.

Morocco is an important world producer and consumer of several varieties of date palm. In fact, the discrimination between varieties remains difficult and requires the use of complex and high-cost techniques.
We evaluated in this work the potential of mid-infrared spectroscopy (MIR) and chemometric models to discriminate eight date palm varieties.
Four chemometric models were applied for the analysis of the spectral data, including principal component analysis (PCA), support vector machine discriminant analysis (SVM-DA), linear discriminant analysis (LDA) and partial least squares (PLS). MIR spectroscopic data were recorded from the wavenumber range 4000 – 600 cm−1, with a spectral resolution of 4 cm−1.
The discriminant analysis was performed by LDA and SVM-DA with a 100% correct classification rate for the date mesocarp. Partial least-squares was applied as a complementary chemometric tool aimed at quantifying moisture content, the validation of this model shows a good predictive capacity with a regression coefficient of 84% and a root mean square error of cross-validation of 0.50.
The present study clearly demonstrates that MIR spectroscopy combined with chemometric approaches constitutes a promising analytical method to classify date palms according to their varietal origin and to establish a regression model for predicting moisture content.
Alternative analytical method to discriminate of date palm cultivars by FTIR-ATR spectroscopy coupled with chemometric approaches.