Classification of edible oils and modeling of their physico-chemical properties by chemometric methods using mid-IR spectroscopy

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

Vegetable oils have been utilized for centuries in the food, cosmetic, and pharmaceutical industries, and they contribute beneficially to overall human health, to active skincare, and to effective treatments. Monitoring of the vegetable oils is carried out by the methods described in the European Pharmacopeia, which is time-consuming, has poor repeatability, and involves the use of toxic organic chemicals and expensive laboratory equipment. Many successful studies using IR spectroscopy have been carried out for the detection of geographical origin and adulteration as well as quantification of oxidation parameters. The aim of our research was to explore FT-IR spectroscopy for assessing the quality parameters and fatty acid composition of cranberry, elderberry, borage, blackcurrant, raspberry, black mustard, walnut, sea buckthorn, evening primrose, rosehip, chia, perilla, black cumin, sacha inchi, kiwi, hemp, and linseed oil. Very good models were obtained for the α-linolenic acid and linoleic acid contents, with R2 = 1.00; Rv2 values of 0.98, 0.92, 0.89, and 0.84 were obtained for iodine value prediction, stearic acid content, palmitic acid content, and unsaponifiable matter content, respectively. However, we were not able to obtain good models for all parameters, and the use of the same process for variable selection was found to be not suitable for all cases.

An overview of recent advances and applications of FT-IR spectroscopy for quality, authenticity, and adulteration detection in edible oils

Authenticity and adulteration detection are primary concerns of various stakeholders, such as researchers, consumers, manufacturers, traders, and regulatory agencies. Traditional approaches for authenticity and adulteration detection in edible oils are time-consuming, complicated, laborious, and expensive; they require technical skills when interpreting the data. Over the last several years, much effort has been spent in academia and industry on developing vibrational spectroscopic techniques for quality, authenticity, and adulteration detection in edible oils. Among them, Fourier transforms infrared (FT-IR) spectroscopy has gained enormous attention as a green analytical technique for the rapid monitoring quality of edible oils at all stages of production and for detecting and quantifying adulteration and authenticity in edible oils. The technique has several benefits such as rapid, precise, inexpensive, and multi-analytical; hence, several parameters can be predicted simultaneously from the same spectrum. Associated with chemometrics, the technique has been successfully implemented for the rapid detection of adulteration and authenticity in edible oils. After presenting the fundamentals, the latest research outcomes in the last 10 years on quality, authenticity, and adulteration detection in edible oils using FT-IR spectroscopy will be highlighted and described in this review. Additionally, opportunities, challenges, and future trends of FT-IR spectroscopy will also be discussed.

Comparison of Chemometric Problems in Food Analysis Using Non-Linear Methods

Food analysis is a challenging analytical problem, often addressed using sophisticated laboratory methods that produce large data sets. Linear and non-linear multivariate methods can be used to process these types of datasets and to answer questions such as whether product origin is accurately labeled or whether a product is safe to eat. In this review, we present the application of non-linear methods such as artificial neural networks, support vector machines, self-organizing maps, and multi-layer artificial neural networks in the field of chemometrics related to food analysis. We discuss criteria to determine when non-linear methods are better suited for use instead of traditional methods. The principles of algorithms are described, and examples are presented for solving the problems of exploratory analysis, classification, and prediction.

Study of the Quality Parameters and the Antioxidant Capacity for the FTIR-Chemometric Differentiation of Pistacia Vera Oils

The aim of this work was to characterize the pistachio oil of the Greek variety, "Aegina", evaluate its various quality indices, and investigate the potential use of FTIR as a tool to discriminate different oil qualities. For this purpose, the antioxidant capacity, the tocopherol content and the oxidation and degradation of fatty acids, as described by k, Δk, R-values, and free acidity were evaluated using 45 samples from eight different areas of production and two subsequent years of harvesting. The antioxidant capacity was estimated using 2,2'-azinobis(3-ethylbenzothiazoline-6-sulfonic acid diammonium salt (ABTS) and 2,2-diphenyl-1-(2,4,6-trinitrophenyl)hydrazine (DPPH) assays, and the tocopherol content was quantified through HPLC analysis. FTIR spectra were recorded for all samples and multivariate analysis was applied. The results showed significant differences between the oil samples of different harvesting years, which were successfully discriminated by a representative FTIR spectral region based on R-value, total antioxidant capacity, and scavenging capacity, through ABTS. A similar approach could not be confirmed for the other quality parameters, such as the free acidity and the tocopherol content. This research highlighted the possibility of developing a simple, rapid, economic, and environment friendly method for the discrimination of pistachio oils according to their quality profile, through FTIR spectroscopy and multivariate analysis.

A Simple and Portable Screening Method for Adulterated Olive Oils Using the Hand-Held FTIR Spectrometer and Chemometrics Tools

Extra virgin olive oil has been one of the most common targets for economically motivated food adulteration. This research employed the hand-held FTIR spectrometer to develop the simple and portable screening methods for extra virgin olive oils adulterated with other cheaper vegetable oils. With the help of the ATR probe and chemometrics tools, oil samples can be measured directly without any pretreatment, then the spectra can be interpreted automatically to determine the possibility of adulteration and estimate the content of adulterant oil. A feasibility study of the hand-held FTIR screening method was carried out using olive oils adulterated with canola oil, peanut oil, corn oil, soybean oil, and sunflower oil. The SIMCA model using the hand-held FTIR spectra can identify different kinds of vegetable oils correctly and recognize olive oils with not less than 10% of adulterant oils. Meanwhile, the content of adulterant oil in the range of 5% to 45% can be estimated by the PLS model using the hand-held FTIR spectra within an error of 3%. This research shows the potential of the hand-held FTIR technique in the rapid and field screening of olive oils adulterated with some cheaper vegetable oils.

PRACTICAL APPLICATION

This research provide a rapid and automatic detection method for olive oils adulterated with other cheaper vegetable oils. An oil sample can be measured directly within one minute, and the hand-held instrument can be used anywhere needed.

A simplified FTIR chemometric method for simultaneous determination of four oxidation parameters of frying canola oil

Transmission Fourier transform infrared (FTIR) spectroscopic method using 100 μm KCl cell was applied for the determination of total polar compounds (TPC), carbonyl value (CV), conjugated diene (CD) and conjugated triene (CT) in canola oil (CLO) during potato chips frying at 180 °C. The calibration models were developed for TPC, CV, CD and CT using partial least square (PLS) chemometric technique. Excellent regression coefficients (R(2)) and root mean square error of prediction values for TPC, CV, CD and CT were found to be 0.999, 0.992, 0.998 and 0.999 and 0.809, 0.690, 1.26 and 0.735, respectively. The developed calibration models were applied on samples of canola oil drawn during potato chips frying process. A linear relationship was obtained between CD and TPC with a good correlation of coefficient (R(2)=0.9816). Results of the study clearly indicated that transmission FTIR-PLS method could be used for quick and precise evaluation of oxidative changes during the frying process without using any organic solvent.

Fourier transform infrared spectroscopy combined with chemometrics for discrimination of Curcuma longa, Curcuma xanthorrhiza and Zingiber cassumunar

Turmeric (Curcuma longa), java turmeric (Curcuma xanthorrhiza) and cassumunar ginger (Zingiber cassumunar) are widely used in traditional Indonesian medicines (jamu). They have similar color for their rhizome and possess some similar uses, so it is possible to substitute one for the other. The identification and discrimination of these closely-related plants is a crucial task to ensure the quality of the raw materials. Therefore, an analytical method which is rapid, simple and accurate for discriminating these species using Fourier transform infrared spectroscopy (FTIR) combined with some chemometrics methods was developed. FTIR spectra were acquired in the mid-IR region (4000-400 cm(-1)). Standard normal variate, first and second order derivative spectra were compared for the spectral data. Principal component analysis (PCA) and canonical variate analysis (CVA) were used for the classification of the three species. Samples could be discriminated by visual analysis of the FTIR spectra by using their marker bands. Discrimination of the three species was also possible through the combination of the pre-processed FTIR spectra with PCA and CVA, in which CVA gave clearer discrimination. Subsequently, the developed method could be used for the identification and discrimination of the three closely-related plant species.