A review of vibrational spectroscopic techniques for the detection of food authenticity and adulteration

Unscrambling the Provenance of Eggs by Combining Chemometrics and Near-Infrared Reflectance Spectroscopy

Issues related to food authenticity, traceability, and fraud have increased in recent decades as a consequence of the deliberate and intentional substitution, addition, tampering, or misrepresentation of food ingredients, where false or misleading statements are made about a product for economic gains. This study aimed to evaluate the ability of a portable NIR instrument to classify egg samples sourced from different provenances or production systems (e.g., cage and free-range) in Australia. Whole egg samples (n: 100) were purchased from local supermarkets where the label in each of the packages was used as identification of the layers’ feeding system as per the Australian legislation and standards. The spectra of the albumin and yolk were collected using a portable NIR spectrophotometer (950–1600 nm). Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to analyze the NIR data. The results obtained in this study showed how the combination of chemometrics and NIR spectroscopy allowed for the classification of egg albumin and yolk samples according to the system of production (cage and free range). The proposed method is simple, fast, environmentally friendly and avoids laborious sample pre-treatment, and is expected to become an alternative to commonly used techniques for egg quality assessment.

Detection of chicken and fat adulteration in minced lamb meat by VIS/NIR spectroscopy and chemometrics methods

Meat fraud has been changed to an important challenge to both industry and governments because of the public health issue. The main purpose of this research was to inspect the possibility of using VIS/NIR spectroscopy, combined with chemometric techniques to detect the adulteration of chicken meat and fat in minced lamb meat. 180 samples of pure lamb, chicken and fat and adulterated samples at different levels: 5, 10, 15 and 20% (w/w) were prepared and analyzed after pre-processing techniques. In order to remove additive and multiplicative effects in spectral data, derivatives and scatter-correction preprocessing methods were applied. Principle Component Analysis (PCA) as unsupervised method was applied to compress data. Moreover, Support Vector Machine (SVM) and Soft Independent Modeling Class Analogies (SIMCA) as supervised methods was applied to estimate the discrimination power of these models for nine and three class datasets. The best classification results were 56.15 and 80.70% for classification of nine class and three class datasets respectively with SVM model. This study shows the applicability of VIS/NIR combined with chemometrics to detect the type of fraud in minced lamb meat.

The use of multispectral imaging for the discrimination of Arabica and Robusta coffee beans

Arabica coffee beans are sold at twice the price, or more, compared to Robusta beans and consequently are susceptible to economically motivated adulteration by substitution. There is a need for rapid, non-destructive, and efficient analytical techniques for monitoring the authenticity of Arabica coffee beans in the supply chain. In this study, multispectral imaging (MSI) was applied to discriminate roasted Arabica and Robusta coffee beans and perform quantitative prediction of Arabica coffee bean adulteration with Robusta. The Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) model, built using selected spectral and morphological features from individual coffee beans, achieved 100% correct classification of the two coffee species in the test dataset. The OPLS regression model was able to successfully predict the level of adulteration of Arabica with Robusta. MSI analysis has potential as a rapid screening tool for the detection of fraud issues related to the authenticity of Arabica coffee beans.

Identification and quantification of adulterated honey by Raman spectroscopy combined with convolutional neural network and chemometrics

In this study, Raman spectroscopy combined with convolutional neural network (CNN) and chemometrics was used to achieve the identification and quantification of honey samples adulterated with high fructose corn syrup, rice syrup, maltose syrup and blended syrup, respectively. The shallow CNNs utilized to analyze honey mixed with single-variety syrup classified samples into four categories by the adulteration concentration with more than 97% accuracy, and the general CNN model for simultaneously detecting honey adulterated with any type of syrup obtained an accuracy of 94.79%. The established CNNs had the best performance compared with several chemometric classification algorithms. In addition, partial least square regression (PLS) successfully predicted the purity of honey mixed with single syrup, while coefficients of determination and root mean square errors of prediction were greater than 0.98 and less than 3.50, respectively. Therefore, the proposed methods based on Raman spectra have important practical significance for food safety and quality control of honey products.

Cellular Aquaculture: Prospects and Challenges

Aquaculture plays an important role as one of the fastest-growing food-producing sectors in global food and nutritional security. Demand for animal protein in the form of fish has been increasing tremendously. Aquaculture faces many challenges to produce quality fish for the burgeoning world population. Cellular aquaculture can provide an alternative, climate-resilient food production system to produce quality fish. Potential applications of fish muscle cell lines in cellular aquaculture have raised the importance of developing and characterizing these cell lines. In vitro models, such as the mouse C2C12 cell line, have been extremely useful for expanding knowledge about molecular mechanisms of muscle growth and differentiation in mammals. Such studies are in an infancy stage in teleost due to the unavailability of equivalent permanent muscle cell lines, except a few fish muscle cell lines that have not yet been used for cellular aquaculture. The Prospect of cell-based aquaculture relies on the development of appropriate muscle cells, optimization of cell conditions, and mass production of cells in bioreactors. Hence, it is required to develop and characterize fish muscle cell lines along with their cryopreservation in cell line repositories and production of ideal mass cells in suitably designed bioreactors to overcome current cellular aquaculture challenges.

Vibrational Spectroscopy Combined with Chemometrics in Authentication of Functional Foods

Many foods have both edible and medical importance and are appreciated as functional foods, preventing diseases. However, due to unscrupulous vendors and imperfect market supervision mechanisms, curative foods are prone to adulteration or some other events that harm the interests of consumers. However, traditional analytical methods are unsuitable and expensive for a broad and complex application. Therefore, people urgently need a fast, efficient, and accurate detection method to protect self-interests. Recently, the study of target samples by vibration spectrum shows strong qualitative and quantitative ability. The model established by platform technology combined with the stoichiometric analysis method can obtain better parameters, which it has good robustness and can detect functional food efficiently, quickly and nondestructive. The review compared and prospect five different vibrational spectroscopic techniques (near-infrared, Fourier transform infrared, Raman, hyperspectral imaging spectroscopy and Terahertz spectroscopy). In order to better solve some of the actual situations faced by certification, we explore and through relevant research and investigation to appropriately highlight the applicability and importance of technology combined with chemometrics in functional food authentication. There are four categories of authentication discussed: functional food authenticated in source, processing method, fraud and ingredient ratio. This paper provides an innovative process for the authentication of functional food, which has a meaningful reference value for future review or scientific research of relevant departments.

Non-destructive assessment of vitamin C in foods: a review of the main findings and limitations of vibrational spectroscopic techniques

The constant increase in the demand for safe and high-quality food has generated the need to develop efficient methods to evaluate food composition, vitamin C being one of the main quality indicators. However, its heterogeneity and susceptibility to degradation makes the analysis of vitamin C difficult by conventional techniques, but as a result of technological advances, vibrational spectroscopy techniques have been developed that are more efficient, economical, fast, and non-destructive. This review focuses on main findings on the evaluation of vitamin C in foods by using vibrational spectroscopic techniques. First, the fundamentals of ultraviolet–visible, infrared and Raman spectroscopy are detailed. Also, chemometric methods, whose use is essential for a correct processing and evaluation of the spectral information, are described. The use and importance of vibrational spectroscopy in the evaluation of vitamin C through qualitative characterization and quantitative analysis is reported. Finally, some limitations of the techniques and potential solutions are described, as well as future trends related to the utilization of vibrational spectroscopic techniques.

Pixel-scale miniaturization of guided mode resonance transmission filters in short wave infrared

The effects of miniaturization on theoretically predicted performance of dual-period guided mode resonance (GMR) transmission filters, which demonstrate immense potential for multispectral imaging in short wave infrared (SWIR), have been compared with experimental findings. With reducing filter size from 112 periods (90 µm) to 12 periods (10 µm), peak transmittance (Tpeak) of simulated and measured filters reduced gradually from 84% to 55% and from 76% to 65%, respectively, with a moderate change of 1 - 3 nm in full width at half maximum (FWHM). For 6 period filters (5 µm), simulations predict drastically reduced Tpeak = 14% accompanied by increase in FWHM by 12 nm. The Tpeak value is theoretically shown to increase to 46% with FWHM reduced by 7 nm upon placing metal reflectors at the optimum positions to increase the optical path length. Our findings indicate that four 5 µm × 5 µm size filters with metal reflectors designed for different resonance wavelengths can be used to form a single, 20 µm × 20 µm mosaic pixel for SWIR multispectral imaging.

Consensual Regression of Soluble Solids Content in Peach by Near Infrared Spectrocopy

In order to reduce the uncertainty of the genetic algorithm (GA) in optimizing the near-infrared spectral calibration model and avoid the loss of spectral information of the unselected variables, a strategy of fusing consensus models is proposed to measure the soluble solids content (SSC) in peaches. A total of 266 peach samples were collected at four arrivals, and their interactance spectra were scanned by an integrated analyzer prototype, and then an internal index of SSC was destructively measured by the standard refractometry method. The near-infrared spectra were pre-processed with mean centering and were selected successively with a genetic algorithm (GA) to construct the consensus model, which was integrated with two member models with optimized weightings. One was the conventional partial least square (PLS) optimized with GA selected variables (PLS_GA), and the other one was the derived PLS developed with residual variables after GA selections (PLS_RV). The performance of PLS_RV models showed some useful spectral information related to peaches’ SSC and someone performed close to the full-spectral-based PLS model. Among these 10 runs, consensus models obtained a lower root mean squared errors of prediction (RMSEP), with an average of 1.106% and standard deviation (SD) of 0.0068, and performed better than that of the optimized PLS_GA models, which achieved a RMSEP of average 1.116% with SD of 0.0097. It can be concluded that the application of fusion strategy can reduce the fluctuation uncertainty of a model optimized by genetic algorithm, fulfill the utilization of the spectral information amount, and realize the rapid detection of the internal quality of the peach.

Species-Specific Gene, spt5, in the Qualitative and Quantitative Detection of Boletus reticulatus

Boletus reticulatus is a wild edible fungus with high nutritional value in Yunnan Province. In this study, B. reticulatus was used as the research object to diagnose the species characteristics. A commercial kit was used to extract the DNA of various fungi, and the quality of DNA was determined by using universal fungus primers. Through sequence alignment, the spt5 gene was selected as the species-specific gene of B. reticulatus. This gene was then qualitatively and quantitatively analyzed by PCR. In the qualitative detection, the spt5 amplification products were only found in B. reticulatus which proved its good specificity. Meanwhile, SYBR Green I based quantitative PCR results were highly sensitive, and the limit of detection was 0.04 ng of genomic DNA. These experiments illustrated that spt5 is an ideal species-specific gene for the quantitative and qualitative detection of B. reticulatus. This method is also suitable for the analysis of the processed samples of B. reticulatus and the determination of the adulteration of edible wild mushrooms.

Uses of FT-MIR Spectroscopy and Multivariate Analysis in Quality Control of Coffee, Cocoa, and Commercially Important Spices

Nowadays, coffee, cocoa, and spices have broad applications in the food and pharmaceutical industries due to their organoleptic and nutraceutical properties, which have turned them into products of great commercial demand. Consequently, these products are susceptible to fraud and adulteration, especially those sold at high prices, such as saffron, vanilla, and turmeric. This situation represents a major problem for industries and consumers’ health. Implementing analytical techniques, i.e., Fourier transform mid-infrared (FT-MIR) spectroscopy coupled with multivariate analysis, can ensure the authenticity and quality of these products since these provide unique information on food matrices. The present review addresses FT-MIR spectroscopy and multivariate analysis application on coffee, cocoa, and spices authentication and quality control, revealing their potential use and elucidating areas of opportunity for future research.

Recent Advances in Spectroscopic Techniques for the Analysis of Microplastics in Food

Microplastic pollution has become a worldwide concern in aquatic and terrestrial environments. Microplastics could also enter the food chain, causing potential harm to human health. To facilitate the risk assessment of microplastics to humans, it is critically important to have a reliable analytical technique to detect, quantify, and identify microplastics of various materials, sizes, and shapes from environmental, agricultural, and food matrices. Spectroscopic techniques, mainly vibrational spectroscopy (Raman and infrared), are commonly used techniques for microplastic analysis. This review focuses on recent advances of these spectroscopic techniques for the analysis of microplastics in food. The fundamental, recent technical advances of the spectroscopic techniques and their advantages and limitations were summarized. The food sample pretreatment methods and recent applications for detecting and quantifying microplastics in different types of food were reviewed. In addition, the current technical challenges and future research directions were discussed. It is anticipated that the advances in instrument development and methodology innovation will enable spectroscopic techniques to solve critical analytical challenges in microplastic analysis in food, which will facilitate the reliable risk assessment.

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.

Application of spectroscopic techniques and chemometric methods to differentiate between true cinnamon and false cinnamon

The objective of this study was to identify useful chemical markers for the differentiation of true and false cinnamon; to develop a fast and efficient method of differentiation using MIR associated with chemometric methods. A total of 129 cinnamon samples from 3 countries (Brazil, Sri Lanka, and Paraguay) were purchased, being differentiated by visual analysis. The bioactive compounds, antioxidant activity, HPLC, and MIR analysis were performed. The data obtained were submitted to PCA and PLS-DA. The results showed that the samples of true cinnamon have a higher concentration of eugenol, cinnamaldehyde, and antioxidant capacity, as well as a lower coumarin content. The PCA showed the separation of two groups of cinnamon samples. PLS-DA was effective in differentiating the studied samples with an accuracy of 94.44% and 100% for the composition and MIR analysis, respectively. The MIR proved to be an alternative for the rapid differentiation of true and false cinnamon.

Dispersive liquid-liquid microextraction and diffuse reflectance-Fourier transform infrared spectroscopy for iodate determination in food grade salt and food samples

A novel method based on diffused reflectance Fourier-transform infrared spectroscopy (DRS-FTIR) was employed for iodate determination in food grade salt and food products. The method attained sensitivity that was comparable to or better than that in most of the contemporary spectrophotometric methods. This was realized through a combination of azo dye formation and dispersive liquid-liquid microextraction of dye when a 37-fold enrichment was obtained. FT-IR enabled integrating alternative target peak, and freedom in sample solvent composition relative to UV-visible spectrophotometry where the solvent polarity, pH, and presence of ions may affect the spectral properties of the measurable coloured species. Food samples containing iodide or covalently bonded iodine were oxidized with alkaline permanganate for mineralization and iodate formation. Optimization of both reaction conditions was carried out by means of response surface methodology. The method had a linear range 0.04-10 mg kg^-1 iodate and limit of detection of 4.4 µg kg^-1.

Highly Efficient Photothermal Reduction of CO2 on Pd2Cu Dispersed TiO2 Photocatalyst and Operando DRIFT Spectroscopic Analysis of Reactive Intermediates

The photocatalytic conversion of CO₂ to fuels using solar energy presents meaningful potential in the mitigation of global warming, solar energy conversion, and fuel production. Photothermal catalysis is one promising approach to convert chemically inert CO₂ into value-added chemicals. Herein, we report the selective hydrogenation of CO₂ to ethanol by Pd₂Cu alloy dispersed TiO₂ (P25) photocatalyst. Under UV-Vis irradiation, the Pd₂Cu/P25 showed an efficient CO₂ reduction photothermally at 150 °C with an ethanol production rate of 4.1 mmol g⁻¹ h⁻¹. Operando diffuse reflectance infrared Fourier transform (DRIFT) absorption studies were used to trace the reactive intermediates involved in CO₂ hydrogenation in detail. Overall, the Cu provides the active sites for CO₂ adsorption and Pd involves the oxidation of H₂ molecule generated from P25 and C–C bond formation.

PLS-R Calibration Models for Wine Spirit Volatile Phenols Prediction by Near-Infrared Spectroscopy

Near-infrared spectroscopic (NIR) technique was used, for the first time, to predict volatile phenols content, namely guaiacol, 4-methyl-guaiacol, eugenol, syringol, 4-methyl-syringol and 4-allyl-syringol, of aged wine spirits (AWS). This study aimed to develop calibration models for the volatile phenol’s quantification in AWS, by NIR, faster and without sample preparation. Partial least square regression (PLS-R) models were developed with NIR spectra in the near-IR region (12,500–4000 cm⁻¹) and those obtained from GC-FID quantification after liquid-liquid extraction. In the PLS-R developed method, cross-validation with 50% of the samples along a validation test set with 50% of the remaining samples. The final calibration was performed with 100% of the data. PLS-R models with a good accuracy were obtained for guaiacol (r² = 96.34; RPD = 5.23), 4-methyl-guaiacol (r² = 96.1; RPD = 5.07), eugenol (r² = 96.06; RPD = 5.04), syringol (r² = 97.32; RPD = 6.11), 4-methyl-syringol (r² = 95.79; RPD = 4.88) and 4-allyl-syringol (r² = 95.97; RPD = 4.98). These results reveal that NIR is a valuable technique for the quality control of wine spirits and to predict the volatile phenols content, which contributes to the sensory quality of the spirit beverages.

AUTENTIKASI CEPAT MADU HUTAN KALIMATAN TIMUR DENGAN ATR-FTIR SPEKTROSKOPI KOMBINASI ANALISIS KEMOMETRIKA

Honey adulteration is mostly conducted by the addition of sucrose. In this study, the authentication of honey was conducted using ATR-FTIR and chemometrics. Pure honey samples (MA) were collected from nine regions in East Kalimantan. The ATR-FTIR spectra of these samples were then compared to sucrose-adulterated honey (MS), which were prepared in the sucrose concentration from 2.5 to 50% (v / v).The data analysis was performed using chemometrics techniques: 1) Principle Component Analysis (PCA) method, 2) classification with Discriminant Analysis (DA), and 3) regression with (PCR) and (PLS). As a result, PCA was able to visualize the differences between MS and MA. DA analysis was able to distinguish MS and MA at wave numbers from 1200 to 800 cm-1 with 92.5% performance index. Quantitative calibration models of the sucrose-adulterated honey could be obtained from PLS and PCR, while the best calibration model was obtained with the PLS method from the 2nd derivative spectra. In summary, sucrose-adulterated honey from East Kalimantan can be authenticated using ATR-FTIR method in combination with chemometric analysis.

Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy coupled with chemometric analysis for detection and quantification of adulteration in lavender and citronella essential oils

INTRODUCTION

The growing consumer interest in "naturals" led to an increased application of essential oils (EOs). The market outbreak induced the intensification of EO adulterations, which could affect their quality.

OBJECTIVES

Nowadays, little is known about the illegal practice of adulteration of EOs with vegetable oils. Therefore, the application of mid-infrared spectroscopy coupled with chemometrics was proposed for the detection of EO counterfeits.

MATERIALS AND METHODS

Two EOs, three seed oils, and their mixtures were selected to build the adulteration model. EO-adulterant mixtures for model calibration and validation were analyzed by attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy. The spectral data were analyzed with principal component analysis (PCA) and partial least-squares (PLS) regression.

RESULTS

PCA allowed the discrimination of the EO and adulterant percentages by explaining 97.47% of the total spectral variance with two principal components. A PLS regression model was generated with three factors explaining 97.73% and 99.69% of the total variance in X and Y, respectively. The root mean square error of calibration and the root mean square error of cross-validation were 0.918 and 1.049, respectively. The root mean square error of prediction value obtained from the external validation set was 1.588 and the coefficients of determination R² _CAL and R² _CV were 0.997 and 0.996, respectively.

CONCLUSIONS

The results highlighted the robustness of the developed method in quantifying counterfeits in the range from 0 to 50% of adulterants, disregarding the type of EO and adulterant employed. The present work offers a research advance and makes an important impact in phytochemistry, revealing an easily applicable method for EO quality assessment.

Chickpea (Cicer arietinum L.) as a Source of Essential Fatty Acids - A Biofortification Approach

Chickpea is a highly nutritious pulse crop with low digestible carbohydrates (40-60%), protein (15-22%), essential fats (4-8%), and a range of minerals and vitamins. The fatty acid composition of the seed adds value because fats govern the texture, shelf-life, flavor, aroma, and nutritional composition of chickpea-based food products. Therefore, the biofortification of essential fatty acids has become a nutritional breeding target for chickpea crop improvement programs worldwide. This paper examines global chickpea production, focusing on plant lipids, their functions, and their benefits to human health. In addition, this paper also reviews the chemical analysis of essential fatty acids and possible breeding targets to enrich essential fatty acids in chickpea (Cicer arietinum) biofortification. Biofortification of chickpea for essential fatty acids within safe levels will improve human health and support food processing to retain the quality and flavor of chickpea-based food products. Essential fatty acid biofortification is possible by phenotyping diverse chickpea germplasm over suitable locations and years and identifying the candidate genes responsible for quantitative trait loci mapping using genome-wide association mapping.

CRISPR-Cas12-Based Rapid Authentication of Halal Food

The halal food market is globally growing along with the increased risk of adulteration. We proposed an amplification-free and mix-to-read CRISPR-Cas12-based nucleic acid analytical strategy allowing rapid identification and analysis of pork components, thus enriching the toolbox for ensuring halal food authenticity. We designed and optimized guide RNA (gRNA) targeting the pork cytochrome b (Cyt b) gene. gRNA allowed specific identification of the target Cyt b gene from pork components followed by activation of Cas12 protein to abundantly cleave single-stranded DNA probes with terminally labeled fluorophore and quencher groups, thus turning on fluorescence. The presence of the pork Cyt b gene thus can be mix-and-read- and only-one-step-detected, which may indicate the risk of halal food adulteration. The method allowed specific discrimination of pork meat from beef, mutton, and chicken and yielded a detection limit of 2.7 ng/μL of total DNA from pork meat. The reliability of the method was tested using the following processed meat products: halal foods beef luncheon meat and spiced beef and non-halal foods sausage and dried pork slices. The CRISPR-Cas12-based nucleic acid test strategy is promising for rapid food authentication.

Current Trends of Food Analysis, Safety, and Packaging

Food is a basic necessity for life, growth, survival, and maintaining a proper body function. Rising food demand leads both producers and consumers to search for alternative food sources with high nutritional value. However, food products may never be completely safe. The oxidation reaction may alter both the physicochemical and immunological properties of food products. Maillard and caramelization nonenzymatic browning reactions can play a pivotal role in food acceptance through the ways they influence quality factors such as flavor, color, texture, nutritional value, protein functionality, and digestibility. There is a multitude of adulterated foods that portray adverse risks to the human condition. To maintain food safety, the packaging material is used to preserve the quality and freshness of food products. Food safety is jeopardized by plenty of pathogens by the consumption of adulterated food resulting in multiple foodborne illnesses. Though different analytical tools are used in the analysis of food products, yet, adulterated food has repercussions for the community and is a growing issue that adversely impairs human health and well-being. Thus, pathogenic agents' rapid and effective identification is vital for food safety and security to avoid foodborne illness. This review highlights the various analytical techniques used in the analysis of food products, food structure, and quality of food along with chemical reactions in food processing. Moreover, we have also discussed the effect on health due to the consumption of adulterated food and focused on the importance of food safety, including the biodegradable packaging material.

Advanced techniques in edible oil authentication: A systematic review and critical analysis

Adulteration of edible substances is a potent contemporary food safety issue. Perhaps the overt concern derives from the fact that adulterants pose serious ill effects on human health. Edible oils are one of the most adulterated food products. Perpetrators are adopting ways and means that effectively masks the presence of the adulterants from human organoleptic limits and traditional oil adulteration detection techniques. This review embodies a detailed account of chemical, biosensors, chromatography, spectroscopy, differential scanning calorimetry, non-thermal plasma, dielectric spectroscopy research carried out in the area of falsification assessment of edible oils for the past three decades and a collection of patented oil adulteration detection techniques. The detection techniques reviewed have some advantages and certain limitations, chemical tests are simple; biosensors and nuclear magnetic resonance are rapid but have a low sensitivity; chromatography and spectroscopy are highly accurate with a deterring price tag; dielectric spectroscopy is rapid can be portable and has on-line compatibility; however, the results are susceptible to variation of electric current frequency and intrinsic factors (moisture, temperature, structural composition). This review paper can be useful for scientists or for knowledge seekers eager to be abreast with edible oil adulteration detection techniques.

Authentication of berries and berry-based food products

Berries represent one of the most important and high-valued group of modern-day health-beneficial "superfoods" whose dietary consumption has been recognized to be beneficial for human health for a long time. In addition to being delicious, berries are rich in nutrients, vitamins, and several bioactive compounds, including carotenoids, flavonoids, phenolic acids, and hydrolysable tannins. However, due to their high value, berries and berry-based products are often subject to fraudulent adulteration, commonly for economical gain, but also unintentionally due to misidentification of species. Deliberate adulteration often comprises the substitution of high-value berries with lower value counterparts and mislabeling of product contents. As adulteration is deceptive toward customers and presents a risk for public health, food authentication through different methods is applied as a countermeasure. Although many authentication methods have been developed in terms of fast, sensitive, reliable, and low-cost analysis and have been applied in the authentication of a myriad of food products and species, their application on berries and berry-based products is still limited. The present review provides an overview of the development and application of analytical chemistry methods, such as isotope ratio analysis, liquid and gas chromatography, spectroscopy, as well as DNA-based methods and electronic sensors, for the authentication of berries and berry-based food products. We provide an overview of the earlier use and recent advances of these methods, as well as discuss the advances and drawbacks related to their application.

Recent developments in vibrational spectral analyses for dynamically assessing and monitoring food dehydration processes

Dehydration is one of the most widely used food processing techniques, which is sophisticated in nature. Rapid and accurate prediction of dehydration performance and its effects on product quality is still a difficult task. Traditional analytical methods for evaluating food dehydration processes are laborious, time-consuming and destructive, and they are not suitable for online applications. On the other hand, vibrational spectral techniques coupled with chemometrics have emerged as a rapid and noninvasive tool with excellent potential for online evaluation and control of the dehydration process to improve final dried food quality. In the current review, the fundamental of food dehydration and five types of vibrational spectral techniques, and spectral data processing methods are introduced. Critical overtones bands related to dehydration attributes in the near-infrared (NIR) region and the state-of-the-art applications of vibrational spectral analyses in evaluating food quality attributes as affected by dehydration processes are summarized. Research investigations since 2010 on using vibrational spectral technologies combined with chemometrics to continuously monitor food quality attributes during dehydration processes are also covered in this review.

A feasibility quantitative analysis of free fatty acids in polished rice by fourier transform near-infrared spectroscopy and chemometrics

Free fatty acids (FFAs) are an important indicator of the freshness and quality of rice. In this study, the vibration response of C-H chemical bonds (-CH₃ , -CH₂ , H-C = C-H) of FFAs in the near-infrared region was determined by analyzing the standard reagent. In addition, the spectral data of different physical forms of rice and chemometrics, such as partial least squares (PLS), synergy interval-PLS, and competitive adaptive reweighted sampling (CARS), were applied to develop an optimal regression model for rice FFAs determination. The performance of the FFAs model established by using the polished rice granule spectrum (PRG) combined with CARS was the best, the correlation coefficients of the calibration set and prediction set were 0.99 (root mean squared errors of the calibration = 2.00 mg/100 g) and 0.98 (root mean squared errors of the prediction = 3.21 mg/100 g), respectively, and the ratio of performance-to-deviation was 4.50. Compared with the rice powder spectral, the PRG spectral can better retain the information of FFAs. The result shows that NIRS can rapidly, non-destructively, and accurately detect FFAs in rice granules, which will help rice business and food regulatory authorities to establish an early warning mechanism of rice aging. PRACTICAL APPLICATION: Free fatty acids (FFAs) in rice are an important indicator for evaluating the freshness of rice, and their high responsiveness to the deterioration of rice quality. The real-time detection of FFAs in rice can timely adjust the parameters of the rice storage environment, which is very meaningful to ensure the quality of rice.

Molecular Approaches to Agri-Food Traceability and Authentication: An Updated Review

In the last decades, the demand for molecular tools for authenticating and tracing agri-food products has significantly increased. Food safety and quality have gained an increased interest for consumers, producers, and retailers, therefore, the availability of analytical methods for the determination of food authenticity and the detection of major adulterations takes on a fundamental role. Among the different molecular approaches, some techniques such as the molecular markers-based methods are well established, while some innovative approaches such as isothermal amplification-based methods and DNA metabarcoding have only recently found application in the agri-food sector. In this review, we provide an overview of the most widely used molecular techniques for fresh and processed agri-food authentication and traceability, showing their recent advances and applications and discussing their main advantages and limitations. The application of these techniques to agri-food traceability and authentication can contribute a great deal to the reassurance of consumers in terms of transparency and food safety and may allow producers and retailers to adequately promote their products.

Wheat authentication：An overview on different techniques and chemometric methods

Wheat (Triticum aestivum L.) is one of the most important cereal crops and is consumed as a staple food around the globe. Wheat authentication has become a crucial issue over the last decades. Recently, many techniques have been applied in wheat authentication including the authentication of wheat geographical origin, wheat variety, organic wheat, and wheat flour from other cereals. This paper collected related literature in the last ten years, and attempted to highlight the recent studies on the discrimination and authentication of wheat using different determination techniques and chemometric methods. The stable isotope analysis and elemental profile of wheat are promising tools to obtain information regarding the origin, and variety, and to differentiate organic from conventional farming of wheat. Image analysis, genetic parameters, and omics analysis can provide solutions for wheat variety, organic wheat, and wheat adulteration. Vibrational spectroscopy analyses, such as NIR, FTIR, and HIS, in combination with multivariate data analysis methods, such as PCA, LDA, and PLS-DA, show great potential in wheat authenticity and offer many advantages such as user-friendly, cost-effective, time-saving, and environment friendly. In conclusion, analytical techniques combining with appropriate multivariate analysis are very effective to discriminate geographical origin, cultivar classification, and adulterant detection of wheat.

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.

Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral Model

Simple Summary

Moisture content is an important parameter for monitoring the quality of feed and feed materials as its established ranges serve as markers for safe storage, mixing, and feeding animals. The moisture content of feed materials changes very rapidly and necessitates rapid measurement. Current moisture content measurement methods are time-consuming, destructive, and require specialized skills. This often causes reduced and/or delayed testing, which results in the spoilage of feed and feed materials. Additionally, the improper balance of dry matter intake which is inversely proportional to moisture content often causes metabolic diseases for animals consuming the diet. To solve these, we have developed a rapid and non-destructive global hyperspectral model that could quantify moisture content in feed materials. Our results show that the developed model is robust, could provide a method to measure the distribution of moisture in feed, and has potential for implementation in a commercial setting.

Abstract

The dry matter (DM) content of feed is vital in cattle nutrition and is inversely correlated with moisture content. The established ranges of moisture content serve as a marker for factors such as safe storage limit and DM intake. Rapid changes in moisture content necessitate rapid measurements. A rapid and non-destructive global model for the measurement of moisture content in total mixed ration feed and feed materials was developed. To achieve this, we varied and measured the moisture content in the feed and feed materials using standard methods and captured their images using a hyperspectral imaging (HSI) system in the spectral range of 1000–2500 nm. The spectral data from the samples were extracted and preprocessed using seven techniques and were used to develop a global model using partial least squares regression (PLSR) analysis. The range preprocessing technique had the best prediction accuracy (R² = 0.98) and standard error of prediction (2.59%). Furthermore, the visual assessment of distribution in moisture content made possible by the generated PLSR-based moisture content mapped images could facilitate precise formulation. These applications of HSI, when used in commercial feed production, could help prevent feed spoilage and resultant health complications as well as underperformance of the animals from improper DM intake.

Fraud Detection of Herbal Medicines Based on Modern Analytical Technologies Combine with Chemometrics Approach: A Review

Fraud in herbal medicines (HMs), commonplace throughout human history, is significantly related to medicinal effects with sometimes lethal consequences. Major HMs fraud events seem to occur with a certain regularity, such as substitution by counterfeits, adulteration by addition of inferior production-own materials, adulteration by chemical compounds, and adulteration by addition of foreign matter. The assessment of HMs fraud is in urgent demand to guarantee consumer protection against the four fraudulent activities. In this review, three analysis platforms (targeted, non-targeted, and the combination of non-targeted and targeted analysis) were introduced and summarized. Furthermore, the integration of analysis technology and chemometrics method (e.g., class-modeling, discrimination, and regression method) have also been discussed. Each integration shows different applicability depending on their advantages, drawbacks, and some factors, such as the explicit objective analysis or the nature of four types of HMs fraud. In an attempt to better solve four typical HMs fraud, appropriate analytical strategies are advised and illustrated with several typical studies. The article provides a general workflow of analysis methods that have been used for detection of HMs fraud. All analysis technologies and chemometrics methods applied can conduce to excellent reference value for further exploration of analysis methods in HMs fraud.

MALDI-TOF Mass Spectrometry Applications for Food Fraud Detection

Chemical analysis of food products relating to the detection of the most common frauds is a complex task due to the complexity of the matrices and the unknown nature of most processes. Moreover, frauds are becoming more and more sophisticated, making the development of reliable, rapid, cost-effective new analytical methods for food control even more pressing. Over the years, MALDI-TOF MS has demonstrated the potential to meet this need, also due to a series of undeniable intrinsic advantages including ease of use, fast data collection, and capability to obtain valuable information even from complex samples subjected to simple pre-treatment procedures. These features have been conveniently exploited in the field of food frauds in several matrices, including milk and dairy products, oils, fish and seafood, meat, fruit, vegetables, and a few other categories. The present review provides a comprehensive overview of the existing MALDI-based applications for food quality assessment and detection of adulterations.

Real wine or not? Protecting wine with traceability and authenticity for consumers: chemical and technical basis, technique applications, challenge, and perspectives

Wine is a high-value alcoholic beverage welcomed by consumers because of its flavor and nutritional value. The key information on wine bottle label is the basis of consumers' choice, which also becomes a target for manufacturers to adulterate, including geographical origin, grape variety and vintage. With the improvement of wine adulteration technology, modern technological means are needed to solve the above mentioned problems. The chemical basis of wine determines the type of technique used. Detection technology can be subdivided into four groups: mass spectrometry techniques, spectroscopic techniques, chromatography techniques, and other techniques. Multivariate statistical analysis of the data was performed by means of chemometrics methods. This paper outlines a series of procedures for wine classification and identification, and classified the analytical techniques and data processing methods used in recent years with listing their principles, advantages and disadvantages to help wine researchers choose appropriate methods to meet the challenge and ensure wine traceability and authenticity.