Determination of peroxide value in thermally oxidized crude palm oil by near infrared spectroscopy

Machine learning identification of edible vegetable oils from fatty acid compositions and hyperspectral images

Hyperspectral imaging analysis combined with machine learning was applied to identify eight edible vegetable oils, and its classification performance was compared with the chemical method based on fatty acid compositions. Furthermore, the degree of adulteration in vegetable oils was quantitatively investigated using machine learning-enabled hyperspectral approaches. The hyperspectral absorbance spectra of palm oil with a high degree of saturation were distinctly different from those of the other liquid oils. The flaxseed and olive oils exhibited the dominant hyperspectral intensities at 1170/1671 and 1212/1415 nm, respectively. Linear discriminant analysis demonstrated that two linear discriminants could explain a significant portion of the total variability, accounting for 96.0% (fatty acid compositions) and 98.9% (hyperspectral images). When the hyperspectral results were used as datasets for three machine learning models (decision tree, random forest, and k-nearest neighbor), several instances to incorrectly classify grapeseed and sunflower oils were detected, while olive, palm, and flaxseed oils were successfully identified. The machine learning models showed a great classification performance that exceeded 98.9% from the hyperspectral images of the vegetable oils, which was comparable to the fatty acid composition-based chemical method in identifying edible vegetable oils. In addition, the random forest model was the most effective in ascertaining adulteration levels in binary oil blends (R2 > 0.992 and RMSE < 2.75).

The influences of street food vendor frying equipment on the quality of frying oil

This study was initiated to determine the quality of fresh and used oil for street vendor fried food products in Harar City, Ethiopia. Using a purposive sample technique, 12 respondents were selected for the study. The study obtained a total of 12 oil samples, categorized as fresh, in-use, and discarded, from two distinct groups of respondents. Specifically, six samples were collected from vendors utilizing an electric fryer constructed from stainless steel, while the remaining six samples were acquired from vendors employing a pan heated by wood or charcoal.The moisture content of fresh, in-use, and discarded oil samples, among other physical characteristics of the samples obtained from two types of vendors, was examined and found to vary between 0.14 and 0.44%, 0.19 and 0.52%, and 0.25 and 0.75%, respectively. Comparably, the refractive indices of oil samples that were fresh, in use, and discarded were 1.4595-1.4686, 1.4670-1.4885, and 1.4810-1.4960, in that order. Furthermore, the ranges of viscosities for fresh oil, oil samples in use, and oil samples that were discarded were 57.15-76.94, 100-196.50, and 210.22-288.50 mPa, respectively. Chemical properties, including % free fatty acid for similar samples, range from 0.22 to 1.30, 1.12 2.54, and 1.38-3.66%, respectively. Peroxide values of fresh, in-use, and discarded oil samples, have a maximum value of 11.19 meq/kg, 42.90, and 57.60 meq/kg, respectively. The iodine value showed the highest value for the fresh oil sample, while the minimum was obtained under discarded oil sample. The result indicated that they used low-quality oil. The values obtained after frying for samples collected from vendors who used a pan fryer heated with charcoal or wood fire deviated significantly from the requirements, indicating that the palm oil used by those street vendors was unsafe to consume because it could endanger the consumers' health.

Detection and analysis of hyaluronic acid raw materials from different sources by NIR and aquaphotomics

Hyaluronic acid (HA), a polysaccharide, is widely used for its essential physiological functions. Although the structures of low molecular weight HA produced by both acid and enzyme degradation methods are extremely similar, there are still differences due to the different degradation principles. There is currently no clear way to distinguish between HA prepared by acidolysis and enzymatic hydrolysis. Based on near-infrared (NIR) spectroscopy and aquaphotomics technology, a method for distinguishing HA raw materials and their mixtures from different sources was proposed, and HA with different mixed ratios was accurately quantified. First, NIR spectra of the HA samples were collected. The spectra were then preprocessed to improve the spectral resolution. Spectral information was extracted based on wavelet transform and principal component analysis, resulting in a final selection of 12 characteristic wavelengths containing classification information. The discriminative and quantitative models were then constructed using the 12 wavelengths. The discriminative model achieved a 100% identification rate for HA from different sources. The correlation coefficient of calibration (Rc), validation (Rp), external test (Rt), root mean square error of cross validation (RMSECV), calibration (RMSEC), validation (RMSEP), and external test (RMSET) of the mixed proportion quantitative model were 0.9876, 0.9876, 0.9898, 0.0546, 0.0433, 0.0440, and 0.0347, respectively. In this study, the problem of structural similarity and non-identifiability of HA produced by acidolysis and enzymatic hydrolysis was addressed, and quality monitoring of HA feedstock in HA circulating links was achieved. This is the first time to achieve accurate quantification of solid mixtures using the aquaphotomics method.

Analytical and Structural Tools of Lipid Hydroperoxides: Present State and Future Perspectives

Mono- and polyunsaturated lipids are particularly susceptible to peroxidation, which results in the formation of lipid hydroperoxides (LOOHs) as primary nonradical-reaction products. LOOHs may undergo degradation to various products that have been implicated in vital biological reactions, and thus in the pathogenesis of various diseases. The structure elucidation and qualitative and quantitative analysis of lipid hydroperoxides are therefore of great importance. The objectives of the present review are to provide a critical analysis of various methods that have been widely applied, and more specifically on volumetric methods, applications of UV-visible, infrared, Raman/surface-enhanced Raman, fluorescence and chemiluminescence spectroscopies, chromatographic methods, hyphenated MS techniques, NMR and chromatographic methods, NMR spectroscopy in mixture analysis, structural investigations based on quantum chemical calculations of NMR parameters, applications in living cells, and metabolomics. Emphasis will be given to analytical and structural methods that can contribute significantly to the molecular basis of the chemical process involved in the formation of lipid hydroperoxides without the need for the isolation of the individual components. Furthermore, future developments in the field will be discussed.

Comparison of Spectroscopic Techniques for Determining the Peroxide Value of 19 Classes of Naturally Aged, Plant-Based Edible Oils

The peroxide value of edible oils is a measure of the degree of oxidation, which directly relates to the freshness of the oil sample. Several studies previously reported in the literature have paired various spectroscopic techniques with multivariate analyses to rapidly determine peroxide values using field portable and process instrumentation; those efforts presented "best-case scenarios" with oils from narrowly defined training and test sets. The purpose of this paper is to evaluate the use of near- and mid-infrared absorption and Raman scattering spectroscopies on oil samples from different oil classes, including seasonal and vendor variations, to determine which measurement technique or combination thereof is best for predicting peroxide values. Following peroxide value assays of each oil class using an established titration-based method, global and global-subset calibration models were constructed from spectroscopic data collected on the 19 oil classes used in this study. Spectra from each optical technique were used to create partial least squares regression calibration models to predict the peroxide value of unknown oil samples. A global peroxide value model based on near-infrared (8 mm optical path length) oil measurements produced the lowest RMSEP (4.9), followed by 24 mm optical path length near infrared (5.1), Raman (6.9) and 50 µm optical path length mid-infrared (7.3). However, it was determined that the Raman RMSEP resulted from chance correlations. Global peroxide value models based on low-level fusion of the NIR (8 and 24 mm optical path length) data and all infrared data produced the same RMSEP of 5.1. Global subset models, based on any of the spectroscopies and olive oil training sets from any class (pure, extra light, extra virgin), all failed to extrapolate to the non-olive oils. However, the near-infrared global subset model built on extra virgin olive oil could extrapolate to test samples from other olive oil classes. This work demonstrates the difficulty of developing a truly global method for determining peroxide value of oils.

Analytical methods for determining the peroxide value of edible oils: A mini-review

Edible oils are prone to oxidation during processing and storage that may negatively affect the oil quality and human health. Determining the peroxide value (PV) of edible oils is essential because PV is one of the most typically used quality parameters to monitor lipid oxidation and control oil quality. Many approaches have been developed to determine the PV of oils. Among them, iodometric titration is the commonly used method for PV determination. Considering the limitations related to titrimetric methods, such as time and environmental concerns, several instrumental techniques have been considered as reliable alternatives. The advantages and limitations of classical titration and instrumental methods are summarized in this review. The prospects and reformative aspects for the future applications of these approaches in PV determination are also discussed.

Detection of Lipid Oxidation in Infant Formulas: Application of Infrared Spectroscopy to Complex Food Systems

 Fish- or algal oils have become a common component of infant formula products for their high docosahexaenoic acid (DHA) content. DHA is widely recognized to contribute to the normal development of the infant, and the European Commission recently regulated the DHA content in infant formulas. For many manufacturers of first-age early life nutrition products, a higher inclusion level of DHA poses various challenges. Long-chain polyunsaturated fatty acids (LC-PUFAs) such as DHA are very prone to oxidation, which can alter the organoleptic property and nutritional value of the final product. Traditional methods for the assessment of oxidation in complex systems require solvent extraction of the included fat, which can involve harmful reagents and may alter the oxidation status of the system. A rapid, efficient, non-toxic real-time method to monitor lipid oxidation in complex systems such as infant formula emulsions would be desirable. In this study, infrared spectroscopy was therefore chosen to monitor iron-induced oxidation in liquid infant formula, with conjugated dienes and headspace volatiles measured with GC-MS as reference methods. Infrared spectra of infant formula were recorded directly in mid- and near-infrared regions using attenuated total reflectance Fourier-transform (ATR-FTIR) and near-infrared (NIRS) spectrophotometers. Overall, good correlation coefficients (R2 > 0.9) were acquired between volatiles content and infrared spectroscopy. Despite the complex composition of infant formula containing proteins and sugars, infrared spectroscopy was still able to detect spectral changes unique to lipid oxidation. By comparison, near-infrared spectroscopy (NIRS) presented better results than ATR-FTIR: prediction error ATR-FTIR 18% > prediction error NIRS 9%. Consequently, NIRS demonstrates great potential to be adopted as an in-line or on-line, non-destructive, and sustainable method for dairy and especially infant formula manufacturers.

Fast, direct and in situ monitoring of lipid oxidation in an oil-in-water emulsion by near infrared spectroscopy

Lipid oxidation has implications on food, cosmetics and other fat containing products. Fatty acid autoxidation alters both the quality and safety of these products. Efficient and fast methods are needed to track lipid oxidation in complex systems. In this study, an oil-in-water emulsion (20% v/v of fish oil stabilized with high oleic sunflower lecithin) was subjected to iron-initiated oxidation. Conjugated dienes (CDs) were measured after fat extraction using a standardized method. Near infrared spectroscopy (NIRS) has been used to record chemical changes occurring during oxidation directly in the emulsion. Variations were noticed in different spectral regions. Partial least squares regression (PLSR) revealed correlations between conjugated diene values and NIRS spectra. High coefficients of determination (R2 = 0.967 and 0.996) were found for calibration and prediction respectively. The CD value was predicted from NIRS spectra with an error of 7.26 mmol eq. LH kg-1 oil (7.8% error). Limits of detection (LOD) and quantification (LOQ) of 4.65 and 15.5 mmol eq. LH kg-1 oil were estimated. NIRS is a rapid and simple method for measuring lipid oxidation (CD value) in an emulsion without prior fat extraction. NIRS can replace the reference methods that use hazardous solvents and consume time. Therefore, NIRS enables in-line monitoring for process and quality control.

Near-infrared spectroscopy as a potential non-invasive tool in the assessment of disease activity in vitiligo patients

Vitiligo is a common chronic depigmenting skin disease. We explored the utility of near-infrared (NIR) spectroscopy in the identification of spectral changes associated with disease activity in vitiligo patients. In vivo spectral measurements were performed directly on the perilesional skin of 70 vitiligo patients. Relative intensities (second derivative) at 1139, 1344, 1646 and 1839 nm appeared to be significantly lower in the perilesional region of patients with active vitiligo compared with stable disease, while the intensity at 1884 nm seemed to be significantly higher. A classification model based on the spectral ranges around those peaks generated a correct prediction in 82.9% of the cases. In conclusion, we can state that NIR spectroscopy could have potential in the assessment of disease activity. However, large-scale prospective studies are necessary to confirm our preliminary results.

Chemical Composition of Date Palm (Phoenix dactylifera L.) Seed Oil from Six Saudi Arabian Cultivars

This investigation aimed to evaluate the chemical composition and physicochemical properties of seed oils from 6 date palm (Phoenix. dactylifera L.) cultivars (Barhi, Khalas, Manifi, Rezeiz, Sulaj, and Sukkari) growing in Saudi Arabia and to compare them with conventional palm olein. The mean oil content of the seeds was about 7%. Oleic acid (48.67%) was the main fatty acid, followed by lauric acid (17.26%), stearic acid (10.74%), palmitic acid (9.88%), and linolenic acid (8.13%). The mean value for free fatty acids content was 0.5%. The P. dactylifera seed oil also exhibited a mean tocol content of 70.75 mg/100 g. α-Tocotrienol was the most abundant isomer (30.19%), followed by γ-tocopherol (23.61%), γ-tocotrienol (19.07%), and α-tocopherol (17.52%). The oils showed high thermal and oxidative stabilities. The findings indicate that date seed oil has the potential to be used in the food industry as an abundant alternative to palm olein.

PRACTICAL APPLICATION

This study showed that date seed had great nutritional value due to which it can be used for food applications especially as frying or cooking oil. In addition, date oil has also potential to be used in cosmetic and pharmaceutical practices as well. The extraction of oil from Phoenix dactylifera seed on large scale can create positive socioeconomic benefits especially for rural communities and could also assist to resolve the environmental issues generated by excess date production in large scale date-producing countries such as Saudi Arabia.