TerroirV1, Main, Exploration, bibRecord, 000939

Prediction of the geographical origin of butters by partial least square discriminant analysis (PLS-DA) applied to infrared spectroscopy (FTIR) data

Identifieur interne : 000939 ( Main/Exploration ); précédent : 000938; suivant : 000940

Prediction of the geographical origin of butters by partial least square discriminant analysis (PLS-DA) applied to infrared spectroscopy (FTIR) data

Auteurs : M. Bassbasi [Maroc] ; M. De Luca [Italie] ; G. Ioele [Italie] ; A. Oussama [Maroc] ; G. Ragno [Italie]

Source :

Journal of food composition and analysis : (Print) [ 0889-1575 ] ; 2014.

RBID : Pascal:14-0094217

Descripteurs français

Pascal (Inist)
- Prédiction, Origine géographique, Beurre, Analyse discriminante, Spectrométrie IR, Transformation Fourier, Aliment, Classification, Analyse composante principale, Terroir, Agriculture, Nutrition, Régulation.
Wicri :
- topic : Beurre, Classification, Nutrition.

English descriptors

KwdEn :
- Agriculture, Butter, Classification, Discriminant analysis, Food, Fourier transformation, Geographical origin, Infrared spectrometry, Nutrition, Prediction, Principal component analysis, Regulation(control), Terroir.

Abstract

This study examined the potential of Fourier transform infrared spectroscopy (FTIR) in combination with chemometric methods to discriminate among butters of different regions from Morocco. Chemometric analysis of the data provided by FTIR analysis made it possible to establish links to the food origin of 54 butter samples produced in the Fkih Ben Saleh, Kssiba and Kalaa Sraghna areas. The data of calibration set provided a characteristic pattern, or 'fingerprint', relating to the origin of the samples, with good discriminant power. Two models using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were built. The PCA model was able to describe the studied system by using four principal components with a value of explained variance of 98%. The PLS-DA model accurately classified the butter samples of an external validation subset with prediction ability of 100%. The proposed methods, if compared to other techniques, have the main advantage in allowing very rapid measurements and results characterized by high accuracy and precision.

Affiliations:

Italie, Maroc

Links toward previous steps (curation, corpus...)

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Le document en format XML

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<front><div type="abstract" xml:lang="en">This study examined the potential of Fourier transform infrared spectroscopy (FTIR) in combination with chemometric methods to discriminate among butters of different regions from Morocco. Chemometric analysis of the data provided by FTIR analysis made it possible to establish links to the food origin of 54 butter samples produced in the Fkih Ben Saleh, Kssiba and Kalaa Sraghna areas. The data of calibration set provided a characteristic pattern, or 'fingerprint', relating to the origin of the samples, with good discriminant power. Two models using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were built. The PCA model was able to describe the studied system by using four principal components with a value of explained variance of 98%. The PLS-DA model accurately classified the butter samples of an external validation subset with prediction ability of 100%. The proposed methods, if compared to other techniques, have the main advantage in allowing very rapid measurements and results characterized by high accuracy and precision.</div>
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Prediction of the geographical origin of butters by partial least square discriminant analysis (PLS-DA) applied to infrared spectroscopy (FTIR) data

Prediction of the geographical origin of butters by partial least square discriminant analysis (PLS-DA) applied to infrared spectroscopy (FTIR) data

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri