Characterization of oils and fats by 1H NMR and GC/MS fingerprinting: Classification, prediction and detection of adulteration

Changes in phenolic compounds of Phyllanthus emblica juice during different storage temperature and pH conditions

The aim of this experiment was to investigate the effect of storage temperature and pH on phenolic compounds of Phyllanthus emblica juice. Juice was stored at different temperatures and pH for 15 days and sampled on 2-day intervals. The browning index (BI, ABS420 nm), pH, centrifugal precipitation rate (CPR), and phenolic compounds were evaluated. The results showed 4°C and pH 2.5 could effectively inhibit browning and slow down pH drop of P. emblica juice. The result of orthogonal partial least square-discriminant analysis showed P. emblica juice stored at 4°C and pH 2.5 still had a similar phenolic composition, but at 20°C, 37°C, and pH 3.5, the score plots were concentrated only in the first 3 days. Additionally, gallic acid (GA) and ellagic acid (EA) were screened out to be the differential compounds for browning of P. emblica juice. The contents of GA, epigallocatechin (EGC), corilagin (CL), gallocatechin gallate (GCG), chebulagic acid (CA), 1,2,3,4,6-O-galloyl-d-glucose (PGG), and EA were more stable at 4°C and pH 2.5. Overall, during storage at 4°C and pH 2.5, it could inhibit the increase of GA and EA and decrease of CL, GCG, CA, and PGG, whereas EGC did not show significant difference between storage conditions. The CPR was higher at 4°C, while pH 2.5 could reduce the CPR. In conclusion, in order to maintain stability of phenolic compounds and extended storage period, the P. emblica juice could be stored at low temperature and adjust the pH to increase the stability of juice system.

Exploring the Impact of Various Wooden Barrels on the Aromatic Profile of Aceto Balsamico Tradizionale di Modena by Means of Principal Component Analysis

The study examines the unique production process of Aceto Balsamico Tradizionale di Modena PDO (ABTM), emphasizing its complex phases and the impact of raw materials and artisanal skill on its flavor characteristics. Analytical tests focused on the volatile composition of vinegars from different wood barrels at different aging stages, using solid-phase micro-extraction (SPME) coupled with gas chromatography, either with mass spectrometry (GC/MS) or flame ionization detector (FID). Multivariate analysis, including principal component analysis (PCA), was employed to investigate the presence of peculiarities among the volatile profiles of samples of different barrel origin. The research focuses on characterizing the volatile composition of vinegars sourced from individual wood barrels, such as Cherry, Chestnut, Mulberry, Juniper, and Oak. Although it was not possible to identify molecules directly connected to the woody essence, some similarities emerged between vinegar samples from mulberry and cherry barrels and between those of juniper and oak. The former group is characterized by analytes with high molecular weights, such as furfural and esters, while the latter group shows more intense peaks for ethyl benzoate. Moreover, ethyl benzoate appears to predominantly influence samples from chestnut barrels. Due to the highly complex production process of ABTM, where each battery is influenced by several factors, this study's findings are specific to the current experimental conditions.

Advances and challenges in conventional and modern techniques for halal food authentication: A review

Food is one of the most necessary needs since human civilization. For Muslims, it is mandatory to consume halal food. From a halal authentication perspective, adulteration of food products is an emerging challenge worldwide. The demand for halal food consumption has resulted in an ever-increasing need for halal product validity. In the market, there are several food products in which actual ingredients and their source are not mentioned on the label and cannot be observed by the naked eye. Commonly nonhalal items include pig derivatives like lard, pork, and gelatin derivatives, dead meats, alcohol, blood, and prohibited animals. Purposely, various conventional and modern methods offer precise approaches to ensure the halalness and wholesomeness of food products. Conventional methods are physiochemical (dielectric) and electrophoresis. At the same time, modern techniques include high-pressure liquid chromatography (HPLC), gas chromatography (GC), electronic nose (E-Nose), polymerase chain reaction (PCR), enzyme-linked immunosorbent assay (ELISA), differential scanning calorimetry (DSC), nuclear magnetic resonance (NMR), near-infrared (NIR) spectroscopy, and Fourier transform infrared (FTIR) spectroscopy. This review intends to give an extensive and updated overview of conventional and modern analytical methods for ensuring food halal authenticity.

Quality Control and Authentication of Argan Oils: Application of Advanced Analytical Techniques

In addition to the nutritional and therapeutic benefits, Argan oil is praised for its unique bio-ecological and botanic interest. It has been used for centuries to treat cardiovascular issues, diabetes, and skin infections, as well as for its anti-inflammatory and antiproliferative properties. Argan oil is widely commercialized as a result of these characteristics. However, falsifiers deliberately blend Argan oil with cheaper vegetable oils to make economic profits. This reduces the quality and might result in health issues for consumers. Analytical techniques that are rapid, precise, and accurate are employed to monitor its quality, safety, and authenticity. This review provides a comprehensive overview of studies on the quality assessment of Moroccan Argan oil using both untargeted and targeted approaches. To extract relevant information on quality and adulteration, the analytical data are coupled with chemometric techniques.

Lipid Profile Quantification and Species Discrimination of Pine Seeds through NIR Spectroscopy: A Feasibility Study

Pine seeds are known for their richness in lipid compounds and other healthy substances. However, the reference procedures that are commonly applied for their analysis are quite laborious, time-consuming, and expensive. Therefore, it is important to develop rapid, accurate, multi-parametric, cost-effective and, essentially, environmentally friendly analytical techniques that are easily implemented at an industrial scale. The viability of using near-infrared (NIR) spectroscopy to analyse the seed lipid content and profile of three different pine species (Pinus halepensis, Pinus brutia and Pinus pinaster) was investigated. Moreover, species discrimination using NIR was also attempted. Different chemometric models, namely partial least squares (PLS) regression, for lipid analysis, and partial least square-discriminant analysis (PLS-DA), for pine species discrimination, were applied. In relation to the discrimination of pine seed species, a total of 90.5% of correct classification rates were obtained. Regarding the quantification models, most of the compounds assessed yielded determination coefficients (R²_P) higher than 0.80. The best PLS models were obtained for total fat, vitamin E, saturated and monounsaturated fatty acids, C20:2, C20:1n9, C20, C18:2n6c, C18:1n9c, C18 and C16:1. Globally, the obtained results demonstrated that NIR spectroscopy is a suitable analytical technique for lipid analysis and species discrimination of pine seeds.

Adulteration detection technologies used for halal/kosher food products: an overview

In the Islamic and Jewish religions, there are various restrictions that should be followed in order for food products to be acceptable. Some food items like pork or dog meat are banned to be consumed by the followers of the mentioned religions. However, illegally, some food producers in various countries use either the meat or the fat of the banned animals during food production without being mentioned in the label on the final products, and this considers as food adulteration. Nowadays, halal or kosher labeled food products have a high economic value, therefore deceiving the consumers by producing adulterated food is an illegal business that could make large gains. On the other hand, there is an insistent need from the consumers for getting reliable products that comply with their conditions. One of the main challenges is that the detection of food adulteration and the presence of any of the banned ingredients is usually unnoticeable and cannot be determined by the naked eye. As a result, scientists strove to develop very sensitive and precise analytical techniques. The most widely utilized techniques for the detection and determination of halal/kosher food adulterations can be listed as High-Pressure Liquid Chromatography (HPLC), Capillary Electrophoresis (CE), Gas Chromatography (GC), Electronic Nose (EN), Polymerase Chain Reaction (PCR), Enzyme-linked Immuno Sorbent Assay (ELISA), Differential Scanning Calorimetry (DSC), Nuclear Magnetic Resonance (NMR), Near-infrared (NIR) Spectroscopy, Laser-induced Breakdown Spectroscopy (LIBS), Fluorescent Light Spectroscopy, Fourier Transform Infrared (FTIR) Spectroscopy and Raman Spectroscopy (RS). All of the above-mentioned techniques were evaluated in terms of their detection capabilities, equipment and analysis costs, accuracy, mobility, and needed sample volume. As a result, the main purposes of the present review are to identify the most often used detection approaches and to get a better knowledge of the existing halal/kosher detection methods from a literature perspective.

Practical Qualitative Evaluation and Screening of Potential Biomarkers for Different Parts of Wolfiporia cocos Using Machine Learning and Network Pharmacology

Wolfiporia cocos is a widely used traditional Chinese medicine and dietary supplement. Artificial intelligence algorithms use different types of data based on the different strategies to complete multiple tasks such as search and discrimination, which has become a trend to be suitable for solving massive data analysis problems faced in network pharmacology research. In this study, we attempted to screen the potential biomarkers in different parts of W. cocos from the perspective of measurability and effectiveness based on fingerprint, machine learning, and network pharmacology. Based on the conclusions drawn from the results, we noted the following: (1) exploratory analysis results showed that differences between different parts were greater than those between different regions, and the partial least squares discriminant analysis and residual network models were excellent to identify Poria and Poriae cutis based on Fourier transform near-infrared spectroscopy spectra; (2) from the perspective of effectiveness, the results of network pharmacology showed that 11 components such as dehydropachymic acid and 16α-hydroxydehydrotrametenolic acid, and so on had high connectivity in the “component-target-pathway” network and were the main active components. (3) From a measurability perspective, through orthogonal partial least squares discriminant analysis and the variable importance projection > 1, it was confirmed that three components, namely, dehydrotrametenolic acid, poricoic acid A, and pachymic acid, were the main potential biomarkers based on high-performance liquid chromatography. (4) The content of the three components in Poria was significantly higher than that in Poriae cutis. (5) The integrated analysis showed that dehydrotrametenolic acid, poricoic acid A, and pachymic acid were the potential biomarkers for Poria and Poriae cutis. Overall, this approach provided a novel strategy to explore potential biomarkers with an explanation for the clinical application and reasonable development and utilization in Poria and Poriae cutis.

Mass spectrometry in food authentication and origin traceability

Food authentication and origin traceability are popular research topics, especially as concerns about food quality continue to increase. Mass spectrometry (MS) plays an indispensable role in food authentication and origin traceability. In this review, the applications of MS in food authentication and origin traceability by analyzing the main components and chemical fingerprints or profiles are summarized. In addition, the characteristic markers for food authentication are also reviewed, and the advantages and disadvantages of MS-based techniques for food authentication, as well as the current trends and challenges, are discussed. The fingerprinting and profiling methods, in combination with multivariate statistical analysis, are more suitable for the authentication of high-value foods, while characteristic marker-based methods are more suitable for adulteration detection. Several new techniques have been introduced to the field, such as proton transfer reaction mass spectrometry, ambient ionization mass spectrometry (AIMS), and ion mobility mass spectrometry, for the determination of food adulteration due to their fast and convenient analysis. As an important trend, the miniaturization of MS offers advantages, such as small and portable instrumentation and fast and nondestructive analysis. Moreover, many applications in food authentication are using AIMS, which can help food authentication in food inspection/field analysis. This review provides a reference and guide for food authentication and traceability based on MS.

Geographical Origin Assessment of Extra Virgin Olive Oil via NMR and MS Combined with Chemometrics as Analytical Approaches

Geographical origin assessment of extra virgin olive oil (EVOO) is recognised worldwide as raising consumers’ awareness of product authenticity and the need to protect top-quality products. The need for geographical origin assessment is also related to mandatory legislation and/or the obligations of true labelling in some countries. Nevertheless, official methods for such specific authentication of EVOOs are still missing. Among the analytical techniques useful for certification of geographical origin, nuclear magnetic resonance (NMR) and mass spectroscopy (MS), combined with chemometrics, have been widely used. This review considers published works describing the use of these analytical methods, supported by statistical protocols such as multivariate analysis (MVA), for EVOO origin assessment. The research has shown that some specific countries, generally corresponding to the main worldwide producers, are more interested than others in origin assessment and certification. Some specific producers such as Italian EVOO producers may have been focused on this area because of consumers’ interest and/or intrinsic economical value, as testified also by the national concern on the topic. Both NMR- and MS-based approaches represent a mature field where a general validation method for EVOOs geographic origin assessment could be established as a reference recognised procedure.

A New Method for Olive Oil Screening Using Multivariate Analysis of Proton NMR Spectra

A new NMR-based method for the discrimination of olive oils of any grade from seed oils and mixtures thereof was developed with the aim of allowing the verification of olive oil authenticity. Ten seed oils and seven monovarietal and blended extra virgin olive oils were utilized to develop a principal component analysis (PCA) based analysis of ¹H NMR spectra to rapidly and accurately determine the authenticity of olive oils. Another twenty-eight olive oils were utilized to test the principal component analysis (PCA) based analysis. Detection of seed oil adulteration levels as low as 5% v/v has been shown using simple one-dimensional proton spectra obtained using a 400 MHz NMR spectrometer equipped with a room temperature inverse probe. The combination of simple sample preparation, rapid sample analysis, novel processing parameters, and easily interpreted results, makes this method an easily accessible tool for olive oil fraud detection by substitution or dilution compared to other methods already published.

Mechanism, indexes, methods, challenges, and perspectives of edible oil oxidation analysis

Edible oils are indispensable food components, because they are used for cooking or frying. However, during processing, transport, storage, and consumption, edible oils are susceptible to oxidation, during which various primary and secondary oxidative products are generated. These products may reduce the nutritional value and safety of edible oils and even harm human health. Therefore, analyzing the oxidation of edible oil is essential to ensure the quality and safety of oil. Oxidation is a complex process with various oxidative products, and the content of these products can be evaluated by corresponding indexes. According to the structure and properties of the oxidative products, analytical methods have been employed to quantify these products to analyze the oxidation of oil. Combined with proper chemometric analytical methods, qualitative identification has been performed to discriminate oxidized and nonoxidized oils. Oxidative products are complex and diverse. Thus, proper indexes and analytical methods should be selected depending on specific research objectives. Expanding the mechanism of the correspondence between oxidative products and analytical methods is crucial. The underlying mechanism, conventional indexes, and applications of analytical methods are summarized in this review. The challenges and perspectives for future applications of several methods in determining oxidation are also discussed. This review may serve as a reference in the selection, establishment, and improvement of methods for analyzing the oxidation of edible oil. HighlightsThe mechanism of edible oil oxidation analysis was elaborated.Conventional oxidation indexes and their limited values were discussed.Analytical methods for the determination of oxidative products and qualitative identification of oxidized and non-oxidized oils were reviewed.

High performance liquid chromatography fingerprint and headspace gas chromatography-mass spectrometry combined with chemometrics for the species authentication of Curcumae Rhizoma

Curcumae Rhizoma (Ezhu), a multi-origin Chinese medicine, originates from the dry rhizomes of C. kwangsiensis, C. phaeocaulis and C. wenyujin. The three species have great variation in chemical components and therapeutic effects. To improve safety and effectiveness in clinical use, a strategy integrating chromatographic analysis and chemometrics for the species authentication of Ezhu was proposed. Firstly, systematic analysis of chemical compositions in Ezhu was achieved using high performance liquid chromatography (HPLC) fingerprint and headspace gas chromatography-mass spectrometry (HS-GC-MS). HPLC fingerprints showed that seventeen peaks in common for C. kwangsiensis and eleven peaks in common for C. wenyujin both presented a good similarity (> 0.9, only several samples < 0.8). Eleven common peaks in C. phaeocaulis and the similarity values of most samples were higher than 0.700. Additionally, there were ten common peaks in all Ezhu samples and they had relatively poor similarity with the correlation coefficients ranging from 0.364 to 0.881. For HS-GC-MS, thirty-six volatile components were identified in the three species of Ezhu, mainly monoterpenes and sesquiterpenes. Subsequently, chemometrics including unsupervised principal component analysis (PCA), supervised linear discriminant analysis (LDA), K-nearest neighbors (KNN), back propagation neural network (BP-NN) and orthogonal partial least squares-discrimination analysis (OPLS-DA) was applied to extract useful information from chromatographic profiles. Based on HPLC fingerprint data, PCA could hardly differentiate Ezhu with the three species, and LDA, KNN and BP-NN models provided more than 85 % correct identification. With HS-GC-MS data, PCA could only distinguish C. wenyujin from the other two species, and LDA, KNN, BP-NN and OPLS-DA models achieved excellent classification with 100 % accuracy. Finally, five volatile components (eucalyptol, humulene, β-elemene, (+)-2-bornanone and linalool) with variable importance for the projection (VIP) values higher than 1 in the OPLS-DA model were selected as potential chemical markers for the species authentication of Ezhu. And the constructed OPLS-DA model using these markers obtained 100 % accuracy. Consequently, a rapid, precise and feasible strategy was established for the discrimination and quality control of Ezhu with different species.

Rapid and practical qualitative and quantitative evaluation of non-fumigated ginger and sulfur-fumigated ginger via Fourier-transform infrared spectroscopy and chemometric methods

A strategy was developed to distinguish and quantitate nonfumigated ginger (NS-ginger) and sulfur-fumigated ginger (S-ginger), based on Fourier transform near infrared spectroscopy (FT-NIR) and chemometrics. FT-NIR provided a reliable method to qualitatively assess ginger samples and batches of S-ginger (41) and NS-ginger (39) were discriminated using principal component analysis and orthogonal partial least squares discriminant analysis of FT-NIR data. To generate quantitative methods based on partial least squares (PLS) and counter propagation artificial neural network (CP-ANN) from the FT-NIR, major gingerols were quantified using high performance liquid chromatography (HPLC) and the data used as a reference. Finally, PLS and CP-ANN were deployed to predict concentrations of target compounds in S- and NS-ginger. The results indicated that FT-NIR can provide an alternative to HPLC for prediction of active components in ginger samples and was able to work directly on solid samples.

Detection of camellia oil adulteration using chemometrics based on fatty acids GC fingerprints and phytosterols GC-MS fingerprints

The fatty acid, squalene, and phytosterols, coupled to chemometrics were utilized to detect the adulteration of camellia oil (CAO) with palm superolein (PAO), refined olive oil (ROO), high oleic- sunflower oil (HO-SUO), sunflower oil (SUO), corn oil (COO), rice bran oil (RBO), rice oil (RIO), peanut oil (PEO), sesame oil (SEO), soybean oil (SOO), and rapeseed oil (RAO). CAO was characterized with higher triterpene alcohols, thus differentiated from other vegetable oils in principle component analysis (PCA). Using partial least squares-discriminant analysis (PLS-DA), CAO adulterated with PAO, ROO, HO-SUO, SUO, COO, RBO, RIO, PEO, SEO, SOO, RAO (5%-100%, w/w), could be classified, especially higher than 92.31% of the total discrimination accuracy, at an adulterated ratio above 30%. With less than 22 potential key markers selected by the variable importance in projection (VIP), the optimized PLS models were confirmed to be accurate for the adulterated level prediction in CAO.

Fatty Acid Profile of Lipid Fractions of Mangalitza (Sus scrofa domesticus) from Northern Romania: A GC-MS-PCA Approach

Mangalitza pig (Sus scrofa domesticus) becomes more popular in European countries. The goal of this study was to evaluate the fatty acid profile of the raw and thermally processed Mangalitza hard fat from Northern Romania. For the first time, the gas chromatography-mass spectrometry-Principal component analysis technique (GC-MS-PCA)—was applied to evaluate the dissimilarity of Mangalitza lipid fractions. Three specific layers of the hard fat of Mangalitza from Northern Romania were subjected to thermal treatment at 130 °C for 30 min. Derivatized samples were analyzed by GC-MS. The highest relative content was obtained for oleic acid (methyl ester) in all hard fat layers (36.1–42.4%), while palmitic acid was found at a half (21.3–24.1%). Vaccenic or elaidic acids (trans) were found at important concentrations of 0.3–4.1% and confirmed by Fourier-transform infrared spectroscopy. These concentrations are consistently higher in thermally processed top and middle lipid layers, even at double values. The GC-MS-PCA coupled technique allows us to classify the unprocessed and processed Mangalitza hard fat specific layers, especially through the relative concentrations of vaccenic/elaidic, palmitic, and stearic acids. Further studies are needed in order to evaluate the level of degradation of various animal fats by the GC-MS-PCA technique.

Rapid and non-destructive approach for the detection of fried mustard oil adulteration in pure mustard oil via ATR-FTIR spectroscopy-chemometrics

Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy integrated with chemometrics was effectively applied for the rapid detection and accurate quantification of fried mustard oil (FMO) adulteration in pure mustard oil (PMO). PMO was adulterated with FMO in the range of 0.5-50% v/v. Principal component analysis (PCA) elucidated the studied adulteration using two components with an explained variance of 97%. The linear discriminant analysis (LDA) was adopted to classify the adulterated PMO samples with FMO. LDA model showed 100% accuracy initially, as well as when cross-validated. To enhance the overall quality of models, characteristic spectral regions were optimized, and principal component regression (PCR) and partial least square regression (PLS-R) models were constructed with high accuracy and precision. PLS-R model for the 2nd derivative of the optimized spectral region 1260-1080 cm^-1 showed best results for prediction sample sets in terms of high R² and residual predictive deviation (RPD) value of 0.999 and 31.91 with low root mean square error (RMSE) and relative prediction error (RE %) of 0.53% v/v and 3.37% respectively. Thus, the suggested method can detect up to 0.5% v/v of adulterated FMO in PMO in a short time interval.

Detection of Peanut Adulteration in Food Samples by Nuclear Magnetic Resonance Spectroscopy

The addition of cheap and also readily available raw materials, such as peanut powder, to visually and chemically similar matrices is a common problem in the food industry. When peanuts are used as an adulterant, there is an additional risk of potential health hazard to consumers as a result of allergy-induced anaphylaxis. In this study, different series of peanut admixtures to visually similar food products, such as powdered hazelnuts, almonds, and walnuts, were prepared and analyzed by ¹H nuclear magnetic resonance (NMR) spectroscopy. For identification, an isolated signal at 3.05 ppm in the ¹H NMR spectrum of polar peanut extract was used as an indicator of peanut adulteration. The chemical marker was identified as (2S,4R)-N-methyl-4-hydroxy-l-proline by resynthesis of the compound and used as an internal standard. The signal-to-noise ratio and the integral of the signal of the marker can both be used to detect peanut impurities. Overall, an approximate limit of detection of 4% admixtures of peanut in various food products was determined using a 400 MHz spectrometer. With regard to food fraud, we present a viable screening method for detection of economic-relevant peanut adulteration.

Waterless Urinals Remove Select Pharmaceuticals from Urine by Phase Partitioning

We investigated the potential for waterless urinal sealants fluids to remove pharmaceuticals from urine. ¹H NMR, FTIR, and GC/MS characterization of the fluids indicated that they are mostly composed of aliphatic compounds. Removal of ethinyl estradiol was >40% for two of the three sealant fluids during simulated urination to a urinal cartridge but removal of seven other compounds with greater hydrophilicity was <30%. At equilibrium with Milli-Q water, ≥ 89% partitioning to the sealant phase was observed for three compounds with pH adjusted log K_ow (log D_ow) > 3.5. At equilibrium with synthetic urine, removal ranged widely from 2% to 100%. K_ow was poorly correlated with removal for both matrices at equilibrium, but D_ow was correlated with removal from synthetic urine for two of the three sealants, indicating that ionization and hydrophilicity control partitioning between the urine and sealant phases. To improve removal during urination, where equilibrium is not achieved, we increased the hydraulic retention time 100-fold over that of typical male urination. Removal of specific hydrophobic compounds increased, indicating that both hydrophobicity and kinetics control removal. Removal of ethinyl estradiol was ≥90% for all sealants in the increased hydraulic retention time experiment, demonstrating the potential for implementation to female urinals.

Effect of bound water on the quality of dried Lentinus edodes during storage

BACKGROUND

Water absorption is the dominant factor affecting the quality deterioration of dried Lentinus edodes. We therefore analyzed the effect of moisture content and dynamic water status on physical properties of the mushroom stored at water activity (a_w ), 0.33, 0.43, 0.67, 0.76, and 0.84 for 50 days. Moisture mobility and water status were analyzed using low-field nuclear magnetic resonance, while hardness and microstructure were determined as texture characteristics. Meanwhile, an electronic nose and headspace solid-phase micro-extraction combined with gas chromatography-mass spectrometry (HS-SPME-GC-MS) were used to analyze the flavor properties of dried L. edodes.

RESULTS

The results showed that bound water was the dominant water status in dried L. edodes. The content and molecular mobility of bound water increased at a_w = 0.67, 0.76, and 0.84. This contributed to discoloration, hardness loss, and microstructure sparsity of dried L. edodes. The increasing content and molecular mobility of bound water aggravated the deterioration of characteristic flavor by reducing acid, aldehyde, and ketone content.

CONCLUSION

Unlike immobilized or free water, bound water had a critical influence on the quality deterioration of dried L. edodes during storage. © 2019 Society of Chemical Industry.

Compositional identification and authentication of Chinese honeys by 1H NMR combined with multivariate analysis

Honey authentication has been becoming more and more important and necessary to the honey producers, the consumers and the market regulatory authority due to its favorite organoleptic and healthy properties, high value and increasing export but prevalent falsification practice for economic motivation in China and the potential health risk of adulterated honey. In this study, we obtained the spectral profiles of 90 authentic and 75 adulterated Chinese honey samples by means of high resolution nuclear magnetic resonance (NMR) spectroscopy, and 65 kinds of major and minor components in honey were identified and quantified from their NMR spectra. Combining with the multivariate statistical analyses including principal component analysis (PCA), linear discriminant analysis (LDA), and orthogonal partial least squared-discriminant analysis (OPLS-DA), the discrimination models were successfully established to identify the adulterated honeys from the authentic ones with an accurate rate of 97.6%. Furthermore, the corresponding volcano plot was used to screen out 8 components including proline, xylobiose, uridine, β-glucose, melezitose, turanose, lysine and an unknown component, which are responsible for the differentiation between the authentic and adulterated honeys and will help to control Chinese domestic honey market.

The impacts of brewing in glass tumblers and thermos vacuum mugs on the aromas of green tea (Camellia sinensis)

This study investigated the effect of brewing apparatus on the aromatic feature of tea infusion. Huangshan Maofeng tea infusion was brewed under glass tumblers (GT) or thermos vacuum mugs (TVM) for up to 180 min. Tea infusion sensory attributes were evaluated using quantitative descriptive analysis and the composition of volatiles were analyzed using headspace solid phase microextraction coupled with gas chromatography-mass spectrometry. Results showed that GT tea infusion at each brewing duration possessed stronger 'Pure', 'Fresh' and 'Grassy' attributes than TVM tea infusion, whereas TVM tea infusion showed a higher intensity on 'Steamed' aroma. A total of 74 volatiles were detected in tea infusion, and aldehydes and alcohols appeared to be the major volatiles. Total aldehydes concentration percentage decreased in tea infusion with brewing process, whereas an increase on total alcohol percentage was found. Principal component analysis indicated that brewing duration and apparatus played vital roles in altering the volatile composition in tea infusion, whereas orthogonal partial least squares discriminant analysis (OPLS-DA) revealed that GT tea infusion samples were separated from TVM tea infusion samples. OPLS-DA also screened 20 volatiles that significantly contributed to the differentiation of GT and TVM tea infusion.

Chemometric tools for the authentication of cod liver oil based on nuclear magnetic resonance and infrared spectroscopy data

Cod liver oil is a popular dietary supplement marketed as a rich source of omega-3 fatty acids as well as vitamins A and D. Due to its high market price, cod liver oil is vulnerable to adulteration with lower priced vegetable oils. In this study, ¹H and ¹³C nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy, and gas chromatography (coupled to a flame ionization detector) were used in combination with multivariate statistics to determine cod liver oil adulteration with common vegetable oils (sunflower and canola oils). Artificial neural networks (ANN) were able to differentiate adulteration levels based on infrared spectra with a detection limit of 0.22% and a root mean square error of prediction (RMSEP) of 0.86%. ANN models using ¹H NMR and ¹³C NMR data yielded detection limits of 3.0% and 1.8% and RMSEPs of 2.7% and 1.1%, respectively. In comparison, the ANN model based on fatty acid profiles determined by gas chromatography achieved a detection limit of 0.81% and an RMSEP of 1.1%. The approach of using spectroscopic techniques in combination with multivariate statistics can be regarded as a promising tool for the authentication of cod liver oil and may pave the way for a holistic quality assessment of fish oils. Graphical abstract.

Assessment of Virgin Olive Oil Adulteration by a Rapid Luminescent Method

The adulteration of virgin olive oil with hazelnut oil is a common fraud in the food industry, which makes mandatory the development of accurate methods to guarantee the authenticity and traceability of virgin olive oil. In this work, we demonstrate the potential of a rapid luminescent method to characterize edible oils and to detect adulterations among them. A regression model based on five luminescent frequencies related to minor oil components was designed and validated, providing excellent performance for the detection of virgin olive oil adulteration.

Stimulated Brillouin scattering in combination with visible absorption spectroscopy for authentication of vegetable oils and detection of olive oil adulteration

Vegetable oils provide high nutritional value in the human diet. Specifically, extra virgin olive oil (EVOO) possesses a higher price than that of other vegetable oils. Adulteration of pure EVOO with other types of vegetable oils has attracted increasing attentions. In this work, a stimulated Brillouin scattering (SBS) combined with visible absorption spectroscopy method is proposed for authentication of vegetable oils and detection of olive oil adulteration. The results provided here have demonstrated that the different vegetable oils and adulteration oils exhibit significant differences in normalized absorbance values of two relevant wavelengths (455 and 670 nm) and frequency shifts of SBS. The normalized absorbance values of all spectra at the two relevant wavelengths of 670 nm and 455 nm linearly decrease with the increase of the adulteration concentration. The Brillouin frequency shifts exponentially increase with the increase of the adulteration concentration. Due to non-destructive and requiring no sample pretreatment procedure, this method can be effectively employed for authentication and detection of oils adulteration.

NMR-based and chemometric approaches applicable to adulteration studies for assessment of the botanical origin of edible oils

The health benefits of edible oils, especially promoted by ω3 and ω9 fatty acids, have been associated with their botanical origin. In order to investigate fatty acid profiles, we assessed Brazil nut, chia, linseed, sesame (toasted and raw), and soybean oils by ¹H nuclear magnetic resonance (¹H NMR) and chemometrics. PCA plots revealed important relationships between chemical composition and botanical origin for reference and commercial samples. Strong evidence of commercial Brazil nut oil adulteration was confirmed using a spiking procedure. Our findings show that NMR and chemometrics are successful tools for correlating fatty acid profile with botanical origin, which can be suitable for detecting sample adulteration.

Free Radical Scavenging Capacity, Carotenoid Content, and NMR Characterization of Blighia sapida Aril Oil

Blighia sapida aril oil is rich in monounsaturated fatty acids but is however currently not utilized industrially. The oil was characterized utilizing nuclear magnetic resonance (NMR) and Fourier Transform Infrared Spectroscopy (FTIR). A spectrophotometric assay was conducted to determine the free radical scavenging properties and carotenoid content of the oil. Chemical shifts resonating between δ 5.30 and 5.32 in the ¹H NMR are indicative of olefinic protons present in ackee aril oil which are due to the presence of oleic acid. A peak at 3006 cm⁻¹ in the FTIR spectra confirms the high levels of monounsaturation. The oil has a free radical scavenging activity of 48%  ± 2.8% and carotenoid content of 21 ± 0.2 ppm.

Discrimination and classification of extra virgin olive oil using a chemometric approach based on TMS-4,4'-desmetylsterols GC(FID) fingerprints of edible vegetable oils

A single out-line HPLC-GC (FID) analytical method is applied to acquire the chromatographic fingerprint characteristic of the TMS-4,4'-desmetylsterol derivative fraction of several marketed edible vegetable oils in order to identify and discriminate the most valuable extra-virgin olive oils from the other vegetal oils (canola, corn, grape seed, linseed, olive pomace, peanut, rapeseed, soybean, sesame, seeds (non-specified composition but usually a blend of corn and sunflower) and sunflower). The natural structure of the preprocessed data undergoes a preliminary exploration using principal component analysis and heat map-based cluster analysis. A partial least squares-discriminant model is first trained from 53 oil samples (only 3 latent variables) and externally validated from 18 test oil samples. No classification errors are found and all the test samples are correctly classified. Additional classification models are also built in order to discriminate among vegetables-oil families and excellent results have been also achieved.

Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis Hypogaea) Oils

The intake of adulterated and unhealthy oils and trans-fats in the human diet has had negative health repercussions, including cardiovascular disease, causing millions of deaths annually. Sadly, a significant percentage of all consumable products including edible oils are neither screened nor monitored for quality control for various reasons. The prospective intake of adulterated oils and the associated health impacts on consumers is a significant public health safety concern, necessitating the need for quality assurance checks of edible oils. This study reports a simple, fast, sensitive, accurate, and low-cost chemometric approach to the purity analysis of highly refined peanut oils (HRPO) that were adulterated either with vegetable oil (VO), canola oil (CO), or almond oil (AO) for food quality assurance purposes. The Fourier transform infrared spectra of the pure oils and adulterated HRPO samples were measured and subjected to a partial-least-square (PLS) regression analysis. The obtained PLS regression figures-of-merit were incredible, with remarkable linearity (R² = 0.994191 or better). The results of the score plots of the PLS regressions illustrate pattern recognition of the adulterated HRPO samples. Importantly, the PLS regressions accurately determined percent compositions of adulterated HRPOs, with an overall root-mean-square-relative-percent-error of 5.53% and a limit-of-detection as low as 0.02% (wt/wt). The developed PLS regressions continued to predict the compositions of newly prepared adulterated HRPOs over a period of two months, with incredible accuracy without the need for re-calibration. The accuracy, sensitivity, and robustness of the protocol make it desirable and potentially adoptable by health departments and local enforcement agencies for fast screening and quality assurance of consumable products.

Recent developments in the food quality detected by non-invasive nuclear magnetic resonance technology

Nuclear magnetic resonance (NMR) is a rapid, accurate and non-invasive technology and widely used to detect the quality of food, particularly to fruits and vegetables, meat and aquatic products. This review is a survey of recent developments in experimental results for the quality of food on various NMR technologies in processing and storage over the past decade. Following a discussion of the quality discrimination and classification of food, analysis of food compositions and detection of physical, chemical, structural and microbiological properties of food are outlined. Owing to high cost, low detection limit and sensitivity, the professional knowledge involved and the safety issues related to the maintenance of the magnetic field, so far the practical applications are limited to detect small range of food. In order to promote applications for a broader range of foods further research and development efforts are needed to overcome the limitations of NMR in the detection process. The needs and opportunities for future research and developments are outlined.

Modern analytical methods for the detection of food fraud and adulteration by food category

This review provides current information on the analytical methods used to identify food adulteration in the six most adulterated food categories: animal origin and seafood, oils and fats, beverages, spices and sweet foods (e.g. honey), grain-based food, and others (organic food and dietary supplements). The analytical techniques (both conventional and emerging) used to identify adulteration in these six food categories involve sensory, physicochemical, DNA-based, chromatographic and spectroscopic methods, and have been combined with chemometrics, making these techniques more convenient and effective for the analysis of a broad variety of food products. Despite recent advances, the need remains for suitably sensitive and widely applicable methodologies that encompass all the various aspects of food adulteration. © 2017 Society of Chemical Industry.