Evaluation of SIMCA and PLS algorithms to detect adulterants in canola oil by FT‐IR-Reference-Cited by-同舟云学术

Evaluation of SIMCA and PLS algorithms to detect adulterants in canola oil by FT‐IR

Published:2020-11-09 Issue:6 Volume:56 Page:2596-2603
ISSN:0950-5423
Container-title:International Journal of Food Science & Technology
language:en
Short-container-title:Int. J. Food Sci. Technol.

Author:

Gagneten Maite¹²^ORCID,Buera María del Pilar¹²^ORCID,Rodríguez Silvio D.²³^ORCID

Affiliation:

1. Instituto de Tecnología de Alimentos y Procesos Químicos (ITAPROQ) CONICET – Universidad de Buenos Aires Intendente Güiraldes 2160, Pabellón de Industrias Buenos AiresC1428EGAArgentina

2. Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Intendente Güiraldes 2160 Buenos AiresC1428EGAArgentina

3. Instituto de Biodiversidad y Biología Experimental y Aplicada (IBBEA) CONICET – Universidad de Buenos Aires Intendente Güiraldes 2160, Pabellón 2, 4to Piso Buenos AiresC1428EGAArgentina

Funder

Universidad de Buenos Aires

Agencia Nacional de Promoción Científica y Tecnológica

Publisher

Wiley

Subject

Industrial and Manufacturing Engineering,Food Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/ijfs.14866

Reference17 articles.

1. Classification tools in chemistry. Part 1: linear models. PLS-DA

2. Qualitative analysis of pure and adulterated canola oil via SIMCA