Rapid detection of authenticity and adulteration of cold pressed black cumin seed oil: A comparative study of ATR–FTIR spectroscopy and synchronous fluorescence with multivariate data analysis

Comprehensive quality evaluation of dried boletus slices based on fingerprinting and chemometrics

Mushrooms not only serve as a source of a wide range of nutrients in the structure of the human diet, but they have also received a great deal of attention in the field of biopharmaceuticals because of their wide range of medicinal benefits. Rapid quality certification of boletus (porcini) mushrooms is particularly important as a health food and as a potential source of medicines before purchase and production. Infrared (IR) spectroscopy is commonly used for rapid qualitative and quantitative analyses of foods and herbs. The Ultra Performance Liquid Chromatography (UPLC) combined with systematic fingerprinting quantification was used to analyze the quality consistency of Boletus edulis (B. edulis) from different geographic sources, and a method based on Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy combined with chemometrics for origin traceability and rapid prediction of nucleoside quality marker content of B. edulis dried slices was developed with the aim of achieving rapid, lossless, high-throughput and green quality authentication of raw materials for pharmaceutical products.

Investigation of new analysis methods for simultaneous and rapid identification of five different microplastics using ATR-FTIR spectroscopy and chemometrics

Microplastic (MP) pollution in water has become one of the most important global problems of our time. The development of appropriate and rapid analysis techniques is of great importance at the beginning of the studies aimed at solving this problem. In the presented study, in order to perform the qualitative and quantitative analysis of MP forms of polyamide (PA), polyethylene (PE), polypropylene (PP), polystyrene (PS), and polyethylene terephthalate (PET), which are known to be most abundant in water, in a fast and easy way, new Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy methods were tried to be developed by utilizing chemometric methods. While principal component analysis (PCA) was applied for qualitative analyses, partial least squares (PLS) models were created for quantitative analyses. Raw, 1st, and 2nd order derivatives of all spectra and their spectra with different levels of smoothing points were taken and 24 different chemometric models were created for each MP. In interpreting the statistical performances of the developed PCA and PLS models, different parameters were used. According to the obtained results, the qualitative discrimination of all polymer types was successfully achieved. It was determined that the PLS models developed for the quantitative determination of mixtures consisting of different concentrations of MP types could not be at the desired level. However, it was determined that the PLS models developed for PA, PE, PP, and PET, where the normal spectrum was used, could give quantitatively accurate results, albeit partially.

Trends in authentication of edible oils using vibrational spectroscopic techniques

The authentication of edible oils has become increasingly important for ensuring product quality, safety, and compliance with regulatory standards. Some prevalent authenticity issues found in edible oils include blending expensive oils with cheaper substitutes or lower-grade oils, incorrect labeling regarding the oil's source or type, and falsely stating the oil's origin. Vibrational spectroscopy techniques, such as infrared (IR) and Raman spectroscopy, have emerged as effective tools for rapidly and non-destructively analyzing edible oils. This review paper offers a comprehensive overview of recent advancements in using vibrational spectroscopy for authenticating edible oils. The fundamental principles underlying vibrational spectroscopy are introduced and chemometric approaches that enhance the accuracy and reliability of edible oil authentication are summarized. Recent research trends highlighted in the review include authenticating newly introduced oils, identifying oils based on their specific origins, adopting handheld/portable spectrometers and hyperspectral imaging, and integrating modern data handling techniques into the use of vibrational spectroscopic techniques for edible oil authentication. Overall, this review provides insights into the current state-of-the-art techniques and prospects for utilizing vibrational spectroscopy in the authentication of edible oils, thereby facilitating quality control and consumer protection in the food industry.

A biospectroscopic approach toward colorectal cancer diagnosis from bodily fluid samples via ATR-MIR spectroscopy combined with multivariate data analysis

In this study, a biospectroscopic approach was reported for the detection of spectral changes and biomarkers for the diagnosis of colorectal cancer (CC) cases from different bodily fluids (blood plasma, blood serum, saliva and colonoscopy disinfection/wash fluids) by using attenuated total reflection-mid infrared (ATR-MIR) spectroscopy. To recognize the molecular level changes in the spectral characteristics of CC and their healthy/control (CH) groups, different multivariate data analyses (HCA, LDA, PCA and SIMCA) were successfully performed over the data of ATR-MIR spectroscopy. Two hundred specimens were characterized in detail over the data of spectral regions (4000-650 cm-1 and regions V-XXII). The findings revealed that significant changes were clearly observed in the concentrations of lipid, protein, nucleic acid and carbohydrate biomolecules for cancer cases based upon their necessity to overcome energy requirements. Supervised multivariate data methodology SIMCA, presented an excellent classification for the studied groups; similarly 100% of the specimens from different bodily fluids were correctly classified by supervised methodology LDA. As a result, the developed ATR-MIR methodology for the classification of CC and their healthy groups highlighted a rapid cancer diagnosis approach from different bodily fluids; therefore, it could be guide to make well decision before histopathological assessment and to screen CC populations existing in society.

Successful combination of benchtop nuclear magnetic resonance spectroscopy and chemometric tools: A review

Low-field nuclear magnetic resonance (NMR) has three general modalities: spectroscopy, imaging, and relaxometry. In the last twelve years, the modality of spectroscopy, also known as benchtop NMR, compact NMR, or just low-field NMR, has undergone instrumental development due to new permanent magnetic materials and design. As a result, benchtop NMR has emerged as a powerful analytical tool for use in process analytical control (PAC). Nevertheless, the successful application of NMR devices as an analytical tool in several areas is intrinsically linked to its coupling with different chemometric methods. This review focuses on the evolution of benchtop NMR and chemometrics in chemical analysis, including applications in fuels, foods, pharmaceuticals, biochemicals, drugs, metabolomics, and polymers. The review also presents different low-resolution NMR methods for spectrum acquisition and chemometric techniques for calibration, classification, discrimination, data fusion, calibration transfer, multi-block and multi-way.

Oxidative Stability of Cottonseed Butter Products under Accelerated Storage Conditions

Cottonseed is a natural product of cotton (Gossypium spp.) crops. This work evaluated the oxidative stability of cottonseed butters through accelerated autoxidation by storage at 60 °C for 25 days. Three oxidative stability parameter values (peroxide value, p-anisidine value, and total oxidation value) were monitored over the storage time. These chemical measurements revealed that the storage stability of the butter products was dominated by primary oxidation of lipid (oil) components, while the secondary oxidation levels were relatively unchanged over the storage time. An analysis of the tocopherols (natural oxidants in cottonseed) suggested not only the protection function of the molecules against oxidation of the cottonseed butter during storage, but also the dynamic mechanism against the primary oxidation of lipid components. Attenuated total reflectance-Fourier-transform infrared spectroscopy (ATR-FTIR) data confirmed no changes in the major C functional groups of cottonseed butters over the storage time. On the other hand, characteristic minor peaks of conjugated dienes and trienes related to lipid oxidation were impacted by the accelerated storage. As each day of accelerated oxidation at 60 °C is equivalent to 16 days of storage at 20 °C, observations in this work should have reflected the oxidative stability behaviors of the cottonseed butters after about 13 months of shelf storage under ambient storage conditions. Thus, these data that were collected under the accelerated oxidation testing would be useful not only to create a better understanding of the autooxidation mechanism of lipid molecules in cottonseed butters, but also in developing or recommending appropriate storage conditions for cottonseed end products to prevent them from quality degradation.

A Review of Advanced Methods for the Quantitative Analysis of Single Component Oil in Edible Oil Blends

Edible oil blends are composed of two or more edible oils in varying proportions, which can ensure nutritional balance compared to oils comprising a single component oil. In view of their economical and nutritional benefits, quantitative analysis of the component oils in edible oil blends is necessary to ensure the rights and interests of consumers and maintain fairness in the edible oil market. Chemometrics combined with modern analytical instruments has become a main analytical technology for the quantitative analysis of edible oil blends. This review summarizes the different oil blend design methods, instrumental techniques and chemometric methods for conducting single component oil quantification in edible oil blends. The aim is to classify and compare the existing analytical techniques to highlight suitable and promising determination methods in this field.

Physical and chemical properties of nabak (Zizyphus spina-christi) seed kernel and sweet pepper (Capsicum annuum L.) seed oils

BACKGROUND

Nabak seed kernels and sweet pepper seeds, which are separated from the fruits and discarded as waste after processing or consumption, contain high levels of oils (30.19% and 19.57%, respectively). The chemical and thermal characteristics of nabak seed kernel oil (NSO) and sweet pepper seed oil (PSO) were investigated in this study.

RESULTS

The NSO and PSO contained high levels of unsaturated fatty acids (84.1% and 86.5%, respectively), and the major fatty acid was oleic acid (57.3%) in NSO, but it was linoleic acid (69.4%) in PSO. The triacylglycerol (TAG) profiles show that NSO contained ten TAG species, three of which represented 87.1%, namely C54:3, C52:2 and C54:4, and triolein was the dominant (OOO, 47.0%). Pepper seed oil contained nine TAG molecular species, four of which represented 93.6%, namely C54:6, C52:4, C54:4 and C52:5, and trilinolein was dominant (LLL, 44.0%). The differential scanning calorimetry (DSC) analysis of NSO revealed that three exothermal peaks were detected during cooling, two endothermal peaks were detected during melting, and the major peak occurred at a low temperature. For PSO, three exothermal peaks were detected during cooling, three peaks were detected (one of them was exothermal) during melting, and the major peaks were observed at low temperatures. Fourier transform infrared (FTIR) spectra indicated that NSO and PSO did not contain peroxides or trans fatty acids, but they did contain low concentrations of free fatty acids.

CONCLUSION

This study offers a scientific basis for the use of NSO and PSO as new sources of edible oils for food applications. © 2021 Society of Chemical Industry.

Evaluation of Portable Vibrational Spectroscopy Sensors as a Tool to Detect Black Cumin Oil Adulteration

Black cumin oil adulteration has become a concern because it has numerous health benefits and a high price. Therefore, a simple, non-destructive, and rapid method to identify adulterations in black seed oil is necessary to protect the quality of the oils. This study aimed to perform a non-invasive method to authenticate black cumin oil by portable FT-NIR, FT-MIR, and Raman spectrometers. Spectra were collected with portable devices and analyzed using Soft Independent Modelling of Class Analogy (SIMCA) to generate a classification model to identify pure black cumin oil and partial least squares regression (PLSR) to predict the adulterant levels. For confirmation, the fatty acid profile of the oils was determined by gas chromatography (GC). SIMCA and PLSR models provided a very high performance in detecting adulterated samples in all portable units. These portable units showed great potential for rapid and non-destructive monitoring to identify adulterated black cumin oils.

A rapid diagnostic approach for gastric and colon cancers via Fourier transform mid-infrared spectroscopy coupled with chemometrics from paraffin-embedded tissues

This paper describes the feasibility of Attenuated total reflection-Fourier transform mid-infrared (ATR-MIR) spectroscopy method coupled with chemometrics for the rapid diagnostic approach and screening spectral changes for gastric and colon cancers from paraffin-embedded tissues. A total number of 82 tissue samples were analyzed by a simple ATR-MIR method combined with PCA, HCA, SIMCA and LDA methodologies. Spectral analyses showed significant differences for the molecular contents particularly about the lipid, nucleic acid, protein and other biomolecules in the samples of gastric cancer (GC) and colon cancer (CC) groups from their control/healthy groups. Significant changes in the characteristic of these molecules were only observed for cancer groups based upon the increment in their biosynthesis, and they could be utilized as diagnostic spectral biomarkers. Under the optimum conditions, SIMCA provided excellent classification for diseased and control groups, with 5% significance level. As well, 97.75% of the studied tissue samples were correctly discriminated on the basis of their origin by LDA. Consequently, the findings of this study highlighted the rapid diagnosis of gastric and colon cancer cases from paraffin-embedded tissues via ATR-MIR spectroscopy complemented with chemometrics.

Advanced process analytical tools for identification of adulterants in edible oils - A review

This review summarizes the use of spectroscopic processes-based analytical tools coupled with chemometric techniques for the identification of adulterants in edible oil. Investigational approaches of process analytical tools such asspectroscopy techniques, nuclear magnetic resonance (NMR), hyperspectral imaging (HSI), e-tongue and e-nose combined with chemometrics were used to monitor quality of edible oils. Owing to the variety and intricacy of edible oil properties along with the alterations in attributes of the PAT tools, the reliability of the tool used and the operating factors are the crucial components which require attention to enhance the efficiency in identification of adulterants. The combination of process analytical tools with chemometrics offers a robust technique with immense chemotaxonomic potential. These involves identification of adulterants, quality control, geographical origin evaluation, process evaluation, and product categorization.

Chemical Composition and Thermogravimetric Behaviors of Glanded and Glandless Cottonseed Kernels

Common “glanded” (Gd) cottonseeds contain the toxic compound gossypol that restricts human consumption of the derived products. The “glandless” (Gl) cottonseeds of a new cotton variety, in contrast, show a trace gossypol content, indicating the great potential of cottonseed for agro-food applications. This work comparatively evaluated the chemical composition and thermogravimetric behaviors of the two types of cottonseed kernels. In contrast to the high gossypol content (3.75 g kg⁻¹) observed in Gd kernels, the gossypol level detected in Gl kernels was only 0.06 g kg⁻¹, meeting the FDA’s criteria as human food. While the gossypol gland dots in Gd kernels were visually observed, scanning electron microcopy was not able to distinguish the microstructural difference between ground Gd and Gl samples. Chemical analysis and Fourier transform infrared (FTIR) spectroscopy showed that Gl kernels and Gd kernels had similar chemical components and mineral contents, but the former was slightly higher in protein, starch, and phosphorus contents. Thermogravimetric (TG) processes of both kernels and their residues after hexane and ethanol extraction were based on three stages of drying, de-volatilization, and char formation. TG-FTIR analysis revealed apparent spectral differences between Gd and Gl samples, as well as between raw and extracted cottonseed kernel samples, indicating that some components in Gd kernels were more susceptible to thermal decomposition than Gl kernels. The TG and TG-FTIR observations suggested that the Gl kernels could be heat treated (e.g., frying and roasting) at an optimal temperature of 140–150 °C for food applications. On the other hand, optimal pyrolysis temperatures would be much higher (350–500 °C) for Gd cottonseed and its defatted residues for non-food bio-oil and biochar production. The findings from this research enhance the potential utilization of Gd and Gl cottonseed kernels for food applications.

Crystallization and melting properties studied by DSC and FTIR spectroscopy of goldenberry (Physalis peruviana) oil

The chemical and thermal characteristics of goldenberry pomace oil (GPO) and goldenberry seed oil (GSO) were investigated. GPO and GSO contained high levels of unsaturated fatty acids (90.1% and 85.1%, respectively), and the major fatty acid was linoleic (62.0% and 72.8%, respectively). Additionally, GPO contained eleven triacylglycerol (TAG) species, three of which represented 82.7%, namely C54:6, C54:4 and C52:4, and trilinolein was the dominant one (35.5%). GSO contained nine TAG species, two of which represented 80.3%, namely C54:6 and C52:4, and trilinolein was dominant (53.3%). The DSC analysis of GPO and GSO revealed that three exothermal peaks were detected during cooling. Three endothermal peaks (one of which is exothermal for GSO) were detected during melting, and the most significant peaks occurred at low temperatures. FTIR spectra indicated that GPO and GSO did not contain peroxides or trans fatty acids, but they did contain low concentrations of free fatty acids.

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.

Surface and Thermal Characterization of Cotton Fibers of Phenotypes Differing in Fiber Length

Cotton is one of the most important and widely grown crops in the world. Understanding the synthesis mechanism of cotton fiber elongation can provide valuable tools to the cotton industry for improving cotton fiber yield and quality at the molecular level. In this work, the surface and thermal characteristics of cotton fiber samples collected from a wild type (WT) and three mutant lines (Li1, Li2-short, Li2-long, Li2-mix, and liy) were comparatively investigated. Microimaging revealed a general similarity trend of WT ≥ Li2-long ≈ Li2-mix > Li1 > Li2 short ≈ liy with Ca detected on the surface of the last two. Attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy and thermogravimetric measurements also showed that Li2-short and liy were more similar to each other, and Li2-long and Li2-mix closer to WT while Li1 was quite independent. FT-IR results further demonstrated that wax and amorphous cellulose were co-present in fiber structures during the fiber formation processes. The correlation analysis found that the FT-IR-based maturity parameter was well correlated (p ≤ 0.05) to the onset decomposition temperature and all three weight-loss parameters at onset, peak, and end decomposition stages, suggesting that the maturity degree is a better parameter than crystallinity index (CI) and other FT-IR parameters that reflect the thermal stability of the cotton fiber. In summary, this work demonstrated that genetic mutation altered the surface and thermal characteristics in the same way for Li2-short and liy, but with different mechanisms for the other three mutant cotton fiber samples.

Prediction of chemical parameters and authentication of various cold pressed oils with fluorescence and mid-infrared spectroscopic methods

It was aimed to compare the performances of two spectroscopic methods, fluorescence and mid-infrared spectroscopy, in terms of their adulteration detection and estimation of several chemical properties for various cold pressed seed oils. Spectroscopic profiles, fatty acid, free fatty acid and total phenol contents of pumpkin seed, grape seed, black cumin oil, and sesame seed oils were determined and these oils were mixed with sunflower oil at 1-50% (v/v). Both spectroscopic techniques provided comparable results for determination of adulteration of each oil type and the most successful prediction was obtained for pumpkin seed oil at levels >%1. Combined data set of oils resulted in successful quantification of their free fatty acid value, total phenol and major fatty acids contents with both spectroscopic methods regardless of oil type. Both techniques could be used as reliable, fast and environmentally friendly alternatives in the analyses of different types of seed oils.

Identification of species-specific peptide markers in cold-pressed oils

In recent years, cold-pressed vegetable oils have become very popular on the global market. Therefore, new versatile methods with high sensitivity and specificity are needed to find and combat fraudulent practices. The objective of this study was to identify oilseed species-specific peptide markers, using proteomic techniques, for authentication of 10 cold-pressed oils. In total, over 380 proteins and 1050 peptides were detected in the samples. Among those peptides, 92 were found to be species-specific and unique to coconut, evening primrose, flax, hemp, milk thistle, nigella, pumpkin, rapeseed, sesame, and sunflower oilseed species. Most of the specific peptides were released from major seed storage proteins (11 globulins, 2S albumins), and oleosins. Additionally, the presence of allergenic proteins in the cold-pressed oils, including pumpkin Cuc ma 5, sunflower Hel a 3, and six sesame allergens (Ses i 1, Ses i 2, Ses i 3, Ses i 4, Ses i 6, and Ses i 7) was confirmed in this study. This study provides novel information on specific peptides that will help to monitor and verify the declared composition of cold-pressed oil as well as the presence of food allergens. This study can be useful in the era of widely used unlawful practices.

A comparative study of ATR-FTIR, UV-visible and fluorescence spectroscopy combined with chemometrics for quantification of squalene in extra virgin olive oils

Attenuated total reflectance-Fourier transform infrared (ATR-FTIR), ultraviolet-visible (UV-Vis), and fluorescence (FL) spectroscopic techniques, combined with partial least-square (PLS) regression with various spectral derivatization methods were tested for the quantitative determination of squalene content of extra virgin olive oils (EVOOs). A set of 90 calibration standards covering a wide range of squalene (3.25-12.54 mg/kg) was used to build up the calibration models. The root mean square error of calibration (RMSEC), the root mean square error of cross-validation (RMSECV), and the root mean square error of prediction (RMSEP) were calculated for evaluation of 18 different calibration models. 50 different brands of EVOOs, which are also analyzed in terms of quality indexes, fatty acid composition, and squalene concentration (3.25-12.54 g/kg) were used for checking the predictive capacities of the calibration models. The best predictions were achieved using normal spectra in FL spectroscopy with the lowest RMSEC of 0.1065, RMSEV of 0.1310, and RMSEP of 0.1500 in the spectral region 250-730 nm. Thus, FL spectroscopy combined with PLS regression is proposed as a fast, accurate, and environmentally friendly approach that can be efficiently used in determining squalene in EVOOs.

Rapid Classification and Quantification of Camellia (Camellia oleifera Abel.) Oil Blended with Rapeseed Oil Using FTIR-ATR Spectroscopy

Currently, the authentication of camellia oil (CAO) has become very important due to the possible adulteration of CAO with cheaper vegetable oils such as rapeseed oil (RSO). Therefore, we report a Fourier transform infrared (FTIR) spectroscopic method for detecting the authenticity of CAO and quantifying the blended levels of RSO. In this study, two characteristic spectral bands (1119 cm^-1 and 1096 cm^-1) were selected and used for monitoring the purity of CAO. In combination with principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares regression (PLSR) analysis, qualitative and quantitative methods for the detection of camellia oil adulteration were proposed. The results showed that the calculated I₁₁₁₉/I₁₀₉₆ intensity ratio facilitated an initial check for pure CAO and six other edible oils. PCA was used on the optimized spectral region of 1800-650 cm^-1. We observed the classification of CAO and RSO as well as discrimination of CAO with RSO adulterants. LDA was utilized to classify CAO from RSO. We could differentiate and classify RSO adulterants up to 1% v/v. In the quantitative PLSR models, the plots of actual values versus predicted values exhibited high linearity. Root mean square error of calibration (RMSEC) and root mean square error of cross validation (RMSECV) values of the PLSR models were 1.4518%-3.3164% v/v and 1.7196%-3.8136% v/v, respectively. This method was successfully applied in the classification and quantification of CAO adulteration with RSO.

Collaborative Analysis on the Marked Ages of Rice Wines by Electronic Tongue and Nose based on Different Feature Data Sets

Aroma and taste are the most important attributes of alcoholic beverages. In the study, the self-developed electronic tongue (e-tongue) and electronic nose (e-nose) were used for evaluating the marked ages of rice wines. Six types of feature data sets (e-tongue data set, e-nose data set, direct-fusion data set, weighted-fusion data set, optimized direct-fusion data set, and optimized weighted-fusion data set) were used for identifying rice wines with different wine ages. Pearson coefficient analysis and variance inflation factor (VIF) analysis were used to optimize the fusion matrixes by removing the multicollinear information. Two types of discrimination methods (principal component analysis (PCA) and locality preserving projections (LPP)) were used for classifying rice wines, and LPP performed better than PCA in the discrimination work. The best result was obtained by LPP based on the weighted-fusion data set, and all the samples could be classified clearly in the LPP plot. Therefore, the weighted-fusion data were used as independent variables of partial least squares regression, extreme learning machine, and support vector machines (LIBSVM) for evaluating wine ages, respectively. All the methods performed well with good prediction results, and LIBSVM presented the best correlation coefficient (R² ≥ 0.9998).