Literature DB >> 25977045

Near and mid infrared spectroscopy and multivariate data analysis in studies of oxidation of edible oils.

Krzysztof Wójcicki1, Igor Khmelinskii2, Marek Sikorski3, Ewa Sikorska4.   

Abstract

Infrared spectroscopic techniques and chemometric methods were used to study oxidation of olive, sunflower and rapeseed oils. Accelerated oxidative degradation of oils at 60°C was monitored using peroxide values and FT-MIR ATR and FT-NIR transmittance spectroscopy. Principal component analysis (PCA) facilitated visualization and interpretation of spectral changes occurring during oxidation. Multivariate curve resolution (MCR) method found three spectral components in the NIR and MIR spectral matrix, corresponding to the oxidation products, and saturated and unsaturated structures. Good quantitative relation was found between peroxide value and contribution of oxidation products evaluated using MCR--based on NIR (R(2) = 0.890), MIR (R(2) = 0.707) and combined NIR and MIR (R(2) = 0.747) data. Calibration models for prediction peroxide value established using partial least squares (PLS) regression were characterized for MIR (R(2) = 0.701, RPD = 1.7), NIR (R(2) = 0.970, RPD = 5.3), and combined NIR and MIR data (R(2) = 0.954, RPD = 3.1).
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Chemometrics; Infrared; Olive oil; Rapeseed oil; Spectroscopic techniques; Sunflower oil

Mesh:

Substances:

Year:  2015        PMID: 25977045     DOI: 10.1016/j.foodchem.2015.04.046

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  8 in total

1.  Biochemical Alterations in White Matter Tracts of the Aging Mouse Brain Revealed by FTIR Spectroscopy Imaging.

Authors:  Kendra L Furber; R J Scott Lacombe; Sally Caine; Merlin P Thangaraj; Stuart Read; Scott M Rosendahl; Richard P Bazinet; Bogdan F Popescu; Adil J Nazarali
Journal:  Neurochem Res       Date:  2021-11-24       Impact factor: 3.996

2.  Statistical FT-IR Spectroscopy for the Characterization of 17 Vegetable Oils.

Authors:  Meta Kokalj Ladan; Nina Kočevar Glavač
Journal:  Molecules       Date:  2022-05-17       Impact factor: 4.927

3.  Terahertz time-domain spectroscopy of edible oils.

Authors:  Alex Dinovitser; Dimitar G Valchev; Derek Abbott
Journal:  R Soc Open Sci       Date:  2017-06-28       Impact factor: 2.963

4.  Comparison of Individual and Integrated Inline Raman, Near-Infrared, and Mid-Infrared Spectroscopic Models to Predict the Viscosity of Micellar Liquids.

Authors:  Kiran Haroon; Ali Arafeh; Stephanie Cunliffe; Philip Martin; Thomas Rodgers; Ćesar Mendoza; Michael Baker
Journal:  Appl Spectrosc       Date:  2020-05-29       Impact factor: 2.388

5.  Improving Prediction of Peroxide Value of Edible Oils Using Regularized Regression Models.

Authors:  William E Gilbraith; J Chance Carter; Kristl L Adams; Karl S Booksh; Joshua M Ottaway
Journal:  Molecules       Date:  2021-11-30       Impact factor: 4.411

6.  Monitoring the Shelf Life of Refined Vegetable Oils under Market Storage Conditions-A Kinetic Chemofoodmetric Approach.

Authors:  Sandra Martín-Torres; Juan Antonio Tello-Jiménez; Rafael López-Blanco; Antonio González-Casado; Luis Cuadros-Rodríguez
Journal:  Molecules       Date:  2022-10-02       Impact factor: 4.927

7.  Rapid detection of talcum powder in tea using FT-IR spectroscopy coupled with chemometrics.

Authors:  Xiaoli Li; Yuying Zhang; Yong He
Journal:  Sci Rep       Date:  2016-07-29       Impact factor: 4.379

8.  N-Way NIR Data Treatment through PARAFAC in the Evaluation of Protective Effect of Antioxidants in Soybean Oil.

Authors:  Larissa Naida Rosa; Thays Raphaela Gonçalves; Sandra T M Gomes; Makoto Matsushita; Rhayanna Priscila Gonçalves; Paulo Henrique Março; Patrícia Valderrama
Journal:  Molecules       Date:  2020-09-23       Impact factor: 4.411

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.