Your browser doesn't support javascript.
loading
Chemometrics Methods for Specificity, Authenticity and Traceability Analysis of Olive Oils: Principles, Classifications and Applications.
Messai, Habib; Farman, Muhammad; Sarraj-Laabidi, Abir; Hammami-Semmar, Asma; Semmar, Nabil.
Afiliación
  • Messai H; Laboratory of Biomedical Genomics and Oncogenetics, Institut Pasteur de Tunis, University of Tunis El Manar, 1002 Tunis, Tunisia. habib.messai@gmail.com.
  • Farman M; Department of Chemistry, Quaid-i-Azam University, 45320 Islamabad, Pakistan. farmanpk@yahoo.com.
  • Sarraj-Laabidi A; Laboratory of Bioinformatics, Biomathematics and Biostatistics (BIMS), Institut Pasteur de Tunis, University of Tunis El Manar, 1002 Tunis, Tunisia. sarraj.abir@live.fr.
  • Hammami-Semmar A; National Institute of Applied Sciences and Technology (INSAT), University of Carthage, 1080 Tunis, Tunisia. asma.hamami@gmail.com.
  • Semmar N; Laboratory of Bioinformatics, Biomathematics and Biostatistics (BIMS), Institut Pasteur de Tunis, University of Tunis El Manar, 1002 Tunis, Tunisia. nabilsemmar@yahoo.fr.
Foods ; 5(4)2016 Nov 17.
Article en En | MEDLINE | ID: mdl-28231172
ABSTRACT

BACKGROUND:

Olive oils (OOs) show high chemical variability due to several factors of genetic, environmental and anthropic types. Genetic and environmental factors are responsible for natural compositions and polymorphic diversification resulting in different varietal patterns and phenotypes. Anthropic factors, however, are at the origin of different blends' preparation leading to normative, labelled or adulterated commercial products. Control of complex OO samples requires their (i) characterization by specific markers; (ii) authentication by fingerprint patterns; and (iii) monitoring by traceability analysis.

METHODS:

These quality control and management aims require the use of several multivariate statistical tools specificity highlighting requires ordination methods; authentication checking calls for classification and pattern recognition methods; traceability analysis implies the use of network-based approaches able to separate or extract mixed information and memorized signals from complex matrices.

RESULTS:

This chapter presents a review of different chemometrics methods applied for the control of OO variability from metabolic and physical-chemical measured characteristics. The different chemometrics methods are illustrated by different study cases on monovarietal and blended OO originated from different countries.

CONCLUSION:

Chemometrics tools offer multiple ways for quantitative evaluations and qualitative control of complex chemical variability of OO in relation to several intrinsic and extrinsic factors.
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: Foods Año: 2016 Tipo del documento: Article País de afiliación: Túnez

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: Foods Año: 2016 Tipo del documento: Article País de afiliación: Túnez