Rapid direct analysis to discriminate geographic origin of extra virgin olive oils by flash gas chromatography electronic nose and chemometrics

Effect of Chinese bayberry residue on quality of Chinese quinoa (Chenopodium quinoa Willd.) Rice wine

Chinese bayberry residue (CBR) is a by-product of processing, which can be used as an auxiliary material during the processing of quinoa rice wine. In this study, the effects of CBR on the chemical profile, bioactive function, taste traits, and flavor of Chinese quinoa rice wine (CQRW) were investigated. The results showed that adding CBR increased the total phenolics, the total flavonoids, and antioxidant capacity. Malic acid content was the highest in Chinese rice wine (CRW), while the total content of components detected in HPLC-MS/MS was the highest in 10%CBR + CQRW. The CQRW exhibited the highest amino acid content, followed by 20%CBR + CQRW. E-tongue analysis results showed that 10%CBR + CQRW, 20%CBR + CQRW, and CQRW had the closest taste traits. Moreover, GC-MS analysis identified 72 aroma compounds in 10%CBR + CQRW sample, more than other samples. In summary, adding 10% CBR significantly improved the quality of CQRW.

Multiple analyses of main flavor components in reconstituted tobacco and transfer behavior of their key substances during heating

Reconstituted tobacco (RT) is a product made by reprocessing tobacco waste, experiencing a growing demand for heat-not-burn products. The purpose of this study is to analyze the main flavor ingredients in RT aerosol, as well as the transfer behavior of key flavor substances from substrates to aerosol and the concentrations of these compounds in the substrate after heating. First, we demonstrated that the odor of four RT aerosol samples could be distinguished using an electronic nose. Through non-targeted analysis, 93 volatile compounds were detected by gas chromatography-mass spectrometry, and 286 non/semi-volatile compounds were identified by ultra-high-performance liquid electrophoresis chromatography-mass spectrometry in aerosol. Furthermore, we found that the formation of RT aerosol involves primarily evaporation and distillation, however, the total content delivered from unheated RT samples to aerosol remains relatively low due to compound volatility and cigarette filtration. Thermal reactions during heating indicated the pyrolysis of chlorogenic acid to generate catechol and resorcinol, while Maillard reactions involving glucose and proline produced 2,3-dihydro-3,5-dihydroxy-6-methyl-4h-pyran-4-one. The study highlighted that heating RT at approximately 300°C could mitigate the production of harmful substances while still providing a familiar sensory experience with combusted tobacco.

Volatilomics as a tool to ascertain food adulteration, authenticity, and origin

Over recent years, there has been an increase in the number of reported cases of food fraud incidents, whereas at the same time, consumers demand authentic products of high quality. The emerging volatilomics technology could be the key to the analysis and characterization of the quality of different foodstuffs. This field of omics has aroused the interest of scientists due to its noninvasive, rapid, and cost-profitable nature. This review aims to monitor the available scientific information on the use of volatilomics technology, correlate it to the relevant food categories, and demonstrate its importance in the food adulteration, authenticity, and origin areas. A comprehensive literature search was performed using various scientific search engines and "volatilomics," "volatiles," "food authenticity," "adulteration," "origin," "fingerprint," "chemometrics," and variations thereof as keywords, without chronological restriction. One hundred thirty-seven relevant publications were retrieved, covering 11 different food categories (meat and meat products, fruits and fruit products, honey, coffee, tea, herbal products, olive oil, dairy products, spices, cereals, and others), the majority of which focused on the food geographical origin. The findings show that volatilomics typically involves various methods responsible for the extraction and consequential identification of volatile compounds, whereas, with the aid of data analysis, it can handle large amounts of data, enabling the origin classification of samples or even the detection of adulteration practices. Nonetheless, a greater number of specific research studies are needed to unlock the full potential of volatilomics.

GC-MS Combined with Fast GC E-Nose for the Analysis of Volatile Components of Chamomile (Matricaria chamomilla L.)

Chamomile has become one of the world's most popular herbal teas due to its unique properties. Chamomile is widely used in dietary supplements, cosmetics, and herbal products. This study aimed to investigate the volatile aromatic components in chamomile. Two analytical techniques, gas chromatography-mass spectrometry (GC-MS) and an ultra-fast gas chromatography electronic nose, were employed to examine samples from Xinjiang (XJ), Shandong (SD), and Hebei (HB) in China, and imported samples from Germany (GER). The results revealed that all chamomile samples contained specific sesquiterpene compounds, including α-bisabolol, bisabolol oxide, bisabolone oxide, and chamazulene. Additionally, forty potential aroma components were identified by the electronic nose. The primary odor components of chamomile were characterized by fruity and spicy notes. The primary differences in the components of chamomile oil were identified as (E)-β-farnesene, chamazulene, α-bisabolol oxide B, spathulenol and α-bisabolone oxide A. Significant differences in aroma compounds included geosmin, butanoic acid, 2-butene, norfuraneol, γ-terpinene. This study demonstrates that GC-MS and the ultra-fast gas chromatography electronic nose can preliminarily distinguish chamomile from different areas, providing a method and guidance for the selection of origin and sensory evaluation of chamomile. The current study is limited by the sample size and it provides preliminary conclusions. Future studies with a larger sample size are warranted to further improve these findings.

Influence of feeding practices in the composition and functionality of infant gut microbiota and its relationship with health

Establishing the infant's gut microbiota has long-term implications on health and immunity. Breastfeeding is recognized as the best practice of infant nutrition in comparison with formula feeding. We evaluated the effects of the primary feeding practices by analyzing the infant growth and the potential association with gut diseases. A cross-sectional and observational study was designed. This study included 55 mothers with infants, who were divided according to their feeding practices in breastfeeding (BF), formula feeding (FF), and combined breast and formula feeding (CF). Anthropometric measurements of the participants were recorded. Additionally, non-invasive fecal samples from the infants were collected to analyze the microbiota by sequencing, immunoglobulin A (IgA) concentration (ELISA), and volatile organic compounds (gas chromatography with an electronic nose). Results showed that the microbiota diversity in the BF group was the highest compared to the other two groups. The IgA levels in the BF group were twice as high as those in the FF group. Moreover, the child´s growth in the BF group showed the best infant development when the data were compared at birth to the recollection time, as noted by the correlation with a decreased concentration of toxic volatile organic compounds. Interestingly, the CF group showed a significant difference in health status when the data were compared with the FF group. We conclude that early health practices influence children's growth, which is relevant to further research about how those infants' health evolved.

Determination of adulteration, geographical origins, and species of food by mass spectrometry

Food adulteration, mislabeling, and fraud, are rising global issues. Therefore, a number of precise and reliable analytical instruments and approaches have been proposed to ensure the authenticity and accurate labeling of food and food products by confirming that the constituents of foodstuffs are of the kind and quality claimed by the seller and manufacturer. Traditional techniques (e.g., genomics-based methods) are still in use; however, emerging approaches like mass spectrometry (MS)-based technologies are being actively developed to supplement or supersede current methods for authentication of a variety of food commodities and products. This review provides a critical assessment of recent advances in food authentication, including MS-based metabolomics, proteomics and other approaches.

Multi-stable isotope and multi-element origin traceability of rice from the main producing regions in Asia: A long-term investigation during 2017-2020

Stable isotope and multi-element analytical techniques with chemometrics were developed to trace the origin authenticity of rice in China market. In the long-term study from 2017 to 2020, a total of 115 batches of rice samples from 8 main producing areas of 7 Asian countries were determined 5 stable isotope ratios and 18 elemental contents. One-way analysis of variance (ANOVA) and various multivariate modeling methods were performed for the origin discrimination. Supervised multivariate modeling including partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) can realize more satisfactory identification of 8 rice origins than ANOVA comparison and unsupervised methods, their leave-one-out cross-validation accuracies approach 85.0 % and 90.9 %, respectively. δ²H, δ¹³C, Ba, Al, Mg, δ³⁴S, Pb and δ¹⁸O were screened as the most important variables for rice origin traceability (VIP > 1 or AUC > 0.5). This analytical strategy combining maybe promising to ensure the origin authenticity and combat illegal mislabeling in rice trade.

Comparative Study on the Volatile Organic Compounds and Characteristic Flavor Fingerprints of Five Varieties of Walnut Oil in Northwest China Using Using Headspace Gas Chromatography-Ion Mobility Spectrometry

Odor is an important characteristic of walnut oil; walnut oil aromas from different varieties smell differently. In order to compare the differences of volatile flavor characteristics in different varieties of walnut oil, the volatile organic compounds (VOCs) of walnut oil from five different walnut varieties in Northwest China were detected and analyzed using headspace gas chromatography–ion mobility spectrometry (HS–GC–IMS). The results showed that 41 VOCs in total were identified in walnut oil from five different varieties, including 14 aldehydes, 8 alcohols, 4 ketones, and 2 esters. Walnut oil (WO) extracted from the “Zha343” variety was most abundant in VOCs. The relative odor activity value (ROAV) analysis showed that aldehydes were the main aroma substances of walnut oil; specifically, hexanal, pentanal, and heptanal were the most abundant. Fingerprints and heat map analysis indicated that WO extracted from the “Xin2”, “185”, “Xin’guang”, and “Zha343” varieties, but not from the “Xinfeng” variety, had characteristic markers. The relative content differences of eight key VOCs in WO from five varieties can be directly compared by Kruskal–Wallis tests, among which the distribution four substances, hexanal (M), hexanal (D), pentanal (M), (E)-2-hexanal (M), presented extremely significant differences (P<0.01). According to the results of the principal component analysis (PCA), WO extracted from the “Zha343” variety was distinct from the other four varieties; in addition, WO extracted from the “Xin2” variety exhibited similarity to WO extracted from the “185” variety, and WO extracted from the “Xinfeng” variety showed similarity to WO extracted from the “Xin’guang” variety. These results reveal that there are certain differences in the VOCs extracted from five different WO varieties, making it feasible to distinguish different varieties of walnut oil or to rapidly detect walnut oil quality based on its volatile substances profile.

Differentiation of Transylvanian fruit distillates using supervised statistical tools based on isotopic and elemental fingerprint

BACKGROUND

The spirit drinks industry is one of the largest in the world. Fruit distillates require adequate analysis methods combined with statistical tools to build differentiation models, according to distinct criteria (geographical and botanical origin, producer's fingerprint, respectively). Over time a database of alcoholic beverage fingerprints can be generated, being very important for product safety and authenticity control.

RESULTS

To control the distillates' geographical origin, linear discriminant analysis (LDA) revealed that the cross-validation classification was correct for 88.2% of samples, but partial least squares discriminant analysis (PLS-DA) was slightly better suited for this purpose, with a correct classification rate of 91.2%. LDA effectiveness was proven for the trademark fingerprint differentiation, which was achieved at 93.5%, compared to 89.1% for PLS-DA. The principal predictors obtained by LDA were the same both for geographical origin and producer differentiation: B, δ¹³ C, Na, Cu, Ca and Be; highlighting the fact that in the production process of distillates each producer used fruits coming from the respective specific region. Through PLS-DA, some of the discrimination markers were the same for geographical origin and producer's identification, but others were completely specific: the rare earth elements Eu and Er only for geographical origin differentiation, and Cu solely as predictor for producer's identification. Regarding distillates' fruit variety, the correct discrimination rates of plum spirits from the rest were 84.2% for PLS-DA and 63% for LDA.

CONCLUSION

LDA and PLS-DA were suitable for differentiation models development of fruits spirits according to geographical region, producer and fruit variety based on isotopic and elemental fingerprint. © 2022 Society of Chemical Industry.

Analytical Methods for the Characterization of Vegetable Oils

The determination of the authenticity of extra virgin olive oils (EVOOs) has become more interesting in recent years. Italy is the first country in Europe in terms of number of Protected Designation of Origin (PDO) oils, which connects consumers to a feeling of tradition and thus to higher quality standards. This work focused on the consideration of the inorganic content as a possible marker of EVOOs. Ten vegetable oils (VOs), eight Italian EVOOs and seven not Italian EVOOs were analyzed. After pretreatment by acid mineralization, Al, Ba, Ca, Cu, Fe, K, Li, Mg, Mn, Na, P, Sb, Se and Zn were determined by ICP-OES. The electrochemical properties of a selected group of EVOOs and other vegetal oils of different botanical origin were investigated by voltammetry. Carbon paste electrodes (CPEs) were prepared. The features observed in the voltammograms reflect the reactions of electroactive compounds, which are present in the oils. A chemometric treatment of the results was performed to assess the possibility to distinguish (i) the region of provenience considering the inorganic profile; and (ii) the plant species from which each oil was obtained on the basis of the current profile registered during voltammetric analysis. Inorganic composition seems to be a useful marker for the assessment of the geographical origin of an EVOO. The EVOO-CPEs voltammetry seems to have a good ability to distinguish the plant species of origin. This method could be useful to monitor the conservation status of the oils, as the redox profile is linked to the oxidative degradation state.

Headspace GC/MS and fast GC e-nose combined with chemometric analysis to identify the varieties and geographical origins of ginger (Zingiber officinale Roscoe)

Food authenticity regarding different varieties and geographical origins is increasingly becoming a concern for consumers. In this study, headspace gas chromatography-mass spectrometry (HS-GC-MS) and fast gas chromatography electronic nose (fast GC e-nose) were used to successfully distinguish the varieties and geographical origins of dried gingers from seven major production areas in China. By chemometric analysis, a distinct separation between the two varieties of ginger was achieved based on HS-GC-MS. Furthermore, flavor information extracted by fast GC e-nose realized the discrimination of geographical origins, and some potential flavor components were selected as important factors for origin certification. Moreover, several pattern recognition algorithms were compared in varietal and regional identification, and random forest (RF) led to the highest accuracies for discrimination. Overall, a rapid and precise method combining multivariate chemometrics and algorithms was developed to determine varieties and geographical origins of ginger, and it could also be applied to other agricultural products.

Volatile Olfactory Profiles of Umbrian Extra Virgin Olive Oils and Their Discrimination through MOX Chemical Sensors

Extra virgin olive oil (EVOO) is the best vegetable oil worldwide but, at the same time, is one of the product victims of fraud in the agri-food sector, and the differences about quality within the extra-virgin olive oil category are often missed. Several scientific techniques were applied in order to guarantee the authenticity and quality of this EVOO. In the present study, the volatile compounds (VOCs) by gas chromatography-mass spectrometry with solid-phase micro-extraction detection (GC-MS SPME), organoleptic analysis by the official Slow Food panel and the detection by a Small Sensor System (S3) were applied. Ten EVOOs from Umbria, a central Italian region, were selected from the 2021 Slow Food Italian extra virgin olive oil official guide, which includes hundreds of high-quality olive oils. The results demonstrated the possibility to discriminate the ten EVOOs, even if they belong to the same Italian region, by all three techniques. The result of GC-MS SPME detection was comparable at the discrimination level to the organoleptic test with few exceptions, while the S3 was able to better separate some EVOOs, which were not discriminated perfectly by the other two methods. The correlation analysis performed among and between the three methodologies allowed us to identify 388 strong associations with a p value less than 0.05. This study has highlighted how much the mix of VOCs was different even among few and localized EVOOs. The correlation with the sensor detection, which is faster and chipper compared to the other two techniques, elucidated the similarities and discrepancies between the applied methods.

A Green Analytical Method Combined with Chemometrics for Traceability of Tomato Sauce Based on Colloidal and Volatile Fingerprinting

Tomato sauce is a world famous food product. Despite standards regulating the production of tomato derivatives, the market suffers frpm fraud such as product adulteration, origin mislabelling and counterfeiting. Methods suitable to discriminate the geographical origin of food samples and identify counterfeits are required. Chemometric approaches offer valuable information: data on tomato sauce is usually obtained through chromatography (HPLC and GC) coupled to mass spectrometry, which requires chemical pretreatment and the use of organic solvents. In this paper, a faster, cheaper, and greener analytical procedure has been developed for the analysis of volatile organic compounds (VOCs) and the colloidal fraction via multivariate statistical analysis. Tomato sauce VOCs were analysed by GC coupled to flame ionisation (GC-FID) and to ion mobility spectrometry (GC-IMS). Instead of using HPLC, the colloidal fraction was analysed by asymmetric flow field-fractionation (AF4), which was applied to this kind of sample for the first time. The GC and AF4 data showed promising perspectives in food-quality control: the AF4 method yielded comparable or better results than GC-IMS and offered complementary information. The ability to work in saline conditions with easy pretreatment and no chemical waste is a significant advantage compared to environmentally heavy techniques. The method presented here should therefore be taken into consideration when designing chemometric approaches which encompass a large number of samples.

Detection of soybean oil adulteration in cow ghee (clarified milk fat): an ultrafast study using flash gas chromatography electronic nose coupled with multivariate chemometrics

BACKGROUND

Cow ghee is one of the expensive edible fats in the dairy sector. Ghee is often adulterated with low-priced edible oils, like soybean oil, owing to its high market demand. The existing adulteration detection methods are time-consuming, requiring sample preparation and expertise in these fields. The possibility of detecting soybean oil adulteration (from 10% to 100%) in pure cow ghee was investigated in this study. The fingerprint information of volatile compounds was collected using a flash gas chromatography electronic nose (FGCEN) instrument. The classification results were studied using the pattern recognition chemometric models principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), and discriminant function analysis (DFA).

RESULTS

The most powerful fingerprint odor of all the samples identified from FGCEN analysis was acetaldehyde (Z)-4-heptenal, 2-propanol, ethyl propanoate, and pentan-2-one. The odor analysis investigation was accomplished with an average analysis time of 90 s. A clear differentiation of all the samples with an excellent classification accuracy of more than 99% was achieved with the PCA and DFA chemometric methods. However, the results of the SIMCA model showed that SIMCA could only be used to detect ghee adulteration at higher concentration levels (30% to 100%). The validation study shows good agreement between FGCEN and gas chromatography-mass spectrometry methods.

CONCLUSION

The methodology demonstrated coupled with PCA and DFA methods for adulteration detection in ghee using FGCEN apparatus has been an efficient and convenient technique. This study explored the capability of the FGCEN instrument to tackle the adulteration problems in ghee. © 2022 Society of Chemical Industry.

Rapid detection of neutralising acid adulterants in raw milk using a milk component analyser and chemometrics

This study focused on the development of a method for the rapid detection of acid-neutralising adulterants in raw milk using a milk composition analyser. Qualitative analysis for the discrimination of different acid-neutralising acid adulterants in raw milk and quantification of NaSCN in adulterated raw milk were conducted, combined with chemometrics. The results showed that the milk component analyser combined with principal component analysis (PCA) could judge whether raw milk samples were adulterated but cannot identify the types of adulterated substances. Although partial least squares discrimination analysis (PLS-DA) can distinguish some adulterated raw milk samples, the accuracy rate was only 56.3%; the random forest (RF) model could recognise most adulterated raw milk samples with an accuracy rate of 97.5% and the F1-score was 0.9638. In the prediction model of NaSCN adulteration concentration in raw milk constructed by RF, the coefficient of determination (R²) was 0.9889, and the root means square error (RMSE) was 3.28 × 10^-4, suggesting a high prediction performance of the model. The effectiveness of the method for the detection of real samples in practical production was also proved. Based on the above results, it could conclude that the milk component analyser, combined with chemometrics, effectively distinguished acid-neutralising adulterants in raw milk. These findings provide a reference for the rapid detection of adulterants and the quality control of raw milk.

Characterization and Discrimination of Apples by Flash GC E-Nose: Geographical Regions and Botanical Origins Studies in China

Forty-one apple samples from 7 geographical regions and 3 botanical origins in China were investigated. A total of 29 volatile compounds have been identified by flash GC E-nose. They are 17 esters, 5 alcohols, 3 aldehydes, 1 ketone, and 3 others. A principal component analysis was employed to study the relationship between varieties and volatiles. A partial least squares discriminant analysis (PLS-DA), stepwise linear discriminant analysis (SLDA), and decision tree (DT) are used to discriminate apples from 4 geographical regions (34 apple samples) and 3 botanical origins (36 apple samples). The most influential markers identified by PLS-DA are 2-hexadecanone, methyl decanoate, tetradecanal, 1,8-cineole, hexyl 2-butenoate, (Z)-2-octenal, methyl 2-methylbutanoate, ethyl butyrate, dimethyl trisulfide, methyl formate, ethanol, S(-)2-methyl-1-butanol, ethyl acetate, pentyl acetate, butyl butanoate, butyl acetate, and ethyl octanoate. From the present work, SLDA reveals the best discrimination results in geographical regions and botanical origins, which are 88.2% and 88.9%, respectively. Although machine learning DT is attempted to classify apple samples, the results are not satisfactory.

Comparison of Different Drying Methods on the Volatile Components of Ginger (Zingiber officinale Roscoe) by HS-GC-MS Coupled with Fast GC E-Nose

Ginger (Zingiber officinale Roscoe) is one of the most popular spices in the world, with its unique odor. Due to its health benefits, ginger is also widely used as a dietary supplement and herbal medicine. In this study, the main flavor components of gingers processed by different drying methods including hot air drying, vacuum drying, sun-drying, and vacuum-freeze drying, were identified on the basis of headspace-gas chromatography coupled with mass spectrometry (HS-GC-MS) and fast gas chromatography electronic-nose (fast GC e-nose) techniques. The results showed that the ginger dried by hot air drying exhibited high contents of volatile compounds and retained the richest odor in comparison with those dried by other methods, which indicated that hot air drying is more suitable for the production of dried ginger. Sensory description by fast GC e-nose exhibited that ginger flavor was mainly concentrated in the spicy, sweet, minty, fruity, and herbaceous odor. The relative content of the zingiberene was significantly higher in the hot air drying sample than those by other methods, suggesting that dried ginger by hot air drying can retain more unique spicy and pungent odorants. Furthermore, the results of chemometrics analyses showed that the main variance components among the samples by different drying methods were α-naginatene, (+)-cyclosativene, and sulcatone in HS-GC-MS analysis, and α-terpinen-7-al, dimethyl sulfide, and citronellal in fast GC e-nose analysis. For comparison of fresh and dried gingers, terpinolene, terpinen-4-ol, 2,4-decadienal, (E, Z)-, and linalool were considered the main variance components. This study generated a better understanding of the flavor characteristics of gingers by different drying methods and could provide a guide for drying and processing of ginger.

Analysis of Volatile Components in Tremella fuciformis by Electronic Nose Combined with GC-MS

In order to quickly evaluate the quality of Tremella fuciformis, the volatile components of T. fuciformis from 4 provinces in China, including Hebei, Henan, Fujian, and Sichuan, were analyzed by electronic nose combined with gas chromatography-mass spectrometry (GC-MS), and the key aroma compounds were determined by relative odor activity value (ROAV). The results showed that the electronic nose combined with the principal component analysis method could distinguish the samples from four regions with good discrimination. At least 117 volatile components were detected in T. fuciformis by GC-MS and a total of 58, 59, 62, and 55 volatile components were identified from Hebei, Henan, Fujian, and Sichuan, respectively, of which there were 18 common components. The volatile components in T. fuciformis were mainly hydrocarbons, followed by aldehydes, acids, and esters, while acetic acid and hexanal were relatively rich in T. fuciformis. Based on the ROAV, 8 key components affecting the aroma of T. fuciformis strongly were found. Among them, hexanal, nonanal, and pentanal were the common components of T. fuciformis, while butyrolactone, 1-octen-3-ol, and 2-carene were the unique key aroma components of T. fuciformis in Hebei Province. Besides, octanal and butyrolactone were the special key components absent in the Sichuan and Henan samples, respectively.

Electronic Noses and Their Applications for Sensory and Analytical Measurements in the Waste Management Plants-A Review

Waste management plants are one of the most important sources of odorants that may cause odor nuisance. The monitoring of processes involved in the waste treatment and disposal as well as the assessment of odor impact in the vicinity of this type of facilities require two different but complementary approaches: analytical and sensory. The purpose of this work is to present these two approaches. Among sensory techniques dynamic and field olfactometry are considered, whereas analytical methodologies are represented by gas chromatography–mass spectrometry (GC-MS), single gas sensors and electronic noses (EN). The latter are the core of this paper and are discussed in details. Since the design of multi-sensor arrays and the development of machine learning algorithms are the most challenging parts of the EN construction a special attention is given to the recent advancements in the sensitive layers development and current challenges in data processing. The review takes also into account relatively new EN systems based on mass spectrometry and flash gas chromatography technologies. Numerous examples of applications of the EN devices to the sensory and analytical measurements in the waste management plants are given in order to summarize efforts of scientists on development of these instruments for constant monitoring of chosen waste treatment processes (composting, anaerobic digestion, biofiltration) and assessment of odor nuisance associated with these facilities.

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.

Characterization and Discrimination of Key Aroma Compounds in Pre- and Postrigor Roasted Mutton by GC-O-MS, GC E-Nose and Aroma Recombination Experiments

The key aroma compounds in the pre- and postrigor roasted mutton were studied in this study. The results showed that 33 and 30 odorants were detected in the pre- and postrigor roasted mutton, respectively. Eight aroma compounds, including 3-methylbutanal, pentanal, hexanal, heptanal, octanal, nonanal, 1-octen-3-ol, and 2-pentylfuran, were confirmed as key odorants by aroma recombination and omission experiments. The aroma profiles of pre- and postrigor roasted mutton both presented great fatty, roasty, meaty, grassy, and sweet odors. Particularly, the concentrations of hexanal, heptanal, octanal, nonanal, 1-octen-3-ol, and 2-pentylfuran in postrigor roasted mutton were significantly higher (p < 0.05) than those in the prerigor roasted mutton. The postrigor back strap was more suitable for roasting than the prerigor back strap. The pre- and postrigor roasted mutton could be obviously discriminated based on the aroma compounds by orthogonal partial least squares discrimination analysis (OPLS-DA) and principal component analysis (PCA). Hexanal and 1-octen-3-ol might potential markers for the discrimination of the pre- and postrigor roasted mutton.

E-Nose and Olfactory Assessment: Teamwork or a Challenge to the Last Data? The Case of Virgin Olive Oil Stability and Shelf Life

Electronic nose (E-nose) devices represent one of the most trailblazing innovations in current technological research, since mimicking the functioning of the biological sense of smell has always represented a fascinating challenge for technological development applied to life sciences and beyond. Sensor array tools are right now used in a plethora of applications, including, but not limited to, (bio-)medical, environmental, and food industry related. In particular, the food industry has seen a significant rise in the application of technological tools for determining the quality of edibles, progressively replacing human panelists, therefore changing the whole quality control chain in the field. To this end, the present review, conducted on PubMed, Science Direct and Web of Science, screening papers published between January 2010 and May 2021, sought to investigate the current trends in the usage of human panels and sensorized tools (E-nose and similar) in the food industry, comparing the performances between the two different approaches. In particular, the focus was mainly addressed towards the stability and shelf life assessment of olive oil, the main constituent of the renowned “Mediterranean diet”, and nowadays appreciated in cuisines from all around the world. The obtained results demonstrate that, despite the satisfying performances of both approaches, the best strategy merges the potentialities of human sensory panels and technological sensor arrays, (i.e., E-nose somewhat supported by E-tongue and/or E-eye). The current investigation can be used as a reference for future guidance towards the choice between human panelists and sensorized tools, to the benefit of food manufacturers.

The use of analytical techniques coupled with chemometrics for tracing the geographical origin of oils: A systematic review (2013-2020)

The global market for imported, high-quality priced foods has grown dramatically in the last decade, as consumers become more conscious of food originating from around the world. Many countries require the origin label of food to protect consumers need about true characteristics and origin. Regulatory authorities are looking for an extended and updated list of the analytical techniques for verification of authentic oils and to support law implementation. This review aims to introduce the efforts made using various analytical tools in combination with the multivariate analysis for the verification of the geographical origin of oils. The popular analytical tools have been discussed, and scientometric assessment that underlines research trends in geographical authentication and preferred journals used for dissemination has been indicated. Overall, we believe this article will be a good guideline for food industries and food quality control authority to assist in the selection of appropriate methods to authenticate oils.

Instrumental Techniques to Classify Olive Oils according to Their Quality

This review includes an update of the publications on quality classification of olive oils into extra, virgin or lampante olive oil categories. Nowadays, the official method to carry out this classification is time-consuming and, sometimes, it is not systematic and/or objective. It is based on conventional physicochemical analysis and on a sensorial tasting of olive oils carried out by a panel of experts. The aim of this review was to explore and give value to the alternative techniques reported in the bibliography to complement the current official methods established for that classification of olive oils. Specifically considered were non-separation and separation analytical techniques which could contribute to correctly classify olive oils according to their physicochemical and/or sensorial characteristics. An in-depth description has been written on the methods used to differentiate these three types of olive oils and the main advantages and disadvantages of the proposed procedures. The techniques here reviewed could be a real and fast option to complement or even substitute some of the analysis included in the official method. Finally, general trends and detected difficulties found to address this issue have been discussed throughout the article.

Characterization of Basil Volatile Fraction and Study of Its Agronomic Variation by ASCA

Basil is a plant known worldwide for its culinary and health attributes. It counts more than a hundred and fifty species and many more chemo-types due to its easy cross-breeds. Each species and each chemo-type have a typical aroma pattern and selecting the proper one is crucial for the food industry. Twelve basil varieties have been studied over three years (2018–2020), as have four different cuts. To characterize the aroma profile, nine typical basil flavour molecules have been selected using a gas chromatography–mass spectrometry coupled with an olfactometer (GC–MS/O). The concentrations of the nine selected molecules were measured by an ultra-fast CG e-nose and Principal Component Analysis (PCA) was applied to detect possible differences among the samples. The PCA results highlighted differences between harvesting years, mainly for 2018, whereas no observable clusters were found concerning varieties and cuts, probably due to the combined effects of the investigated factors. For this reason, the ANOVA Simultaneous Component Analysis (ASCA) methodology was applied on a balanced a posteriori designed dataset. All the considered factors and interactions were statistically significant (p < 0.05) in explaining differences between the basil aroma profiles, with more relevant effects of variety and year.

Drupe Characters, Fatty Acids, Polyphenolic and Aromatic Profile of Olive Oil Obtained from "Oliva Bianca", Minor Autochthonous Cultivar of Campania

Campania, due to its pedo-climatic conditions and to its large varietal heritage, is able to produce oils with high typicity, each different from the other. In this study a “minor” autochthonous cultivar of Campania “Oliva Bianca” was analyzed. In autumn 2020, on drupes from trees belonging to the Campania germplasm collection a varietal characterization through physical, chemical and chromatic parameters at the harvest was carried out. Phenolic compounds profile, fatty acids composition and volatile organic compounds have been investigated in the resulting oil. Quality indices, organoleptic and sensory qualities (panel test) were also determined on the oil. Drupe weight was 4.31 g, flesh/pit ratio was 3.68 and the accumulation of oil content at harvest in drupes was 18.63% FW. The drupes showed high anthocyanins content equal to 116.10 mg/kg. In the oil studied, the secoiridoids represented the 82.25% of total phenolic compounds, the concentration of oleic acid was 74.82% and the most present volatile compound was trans-2-hexenal (72.30%). High secoiridoid derivatives concentrations such as oleuropein (85.93 mg/kg) and ligstroside (122.43 mg/kg) aglycones were showed. This study showed a good content of qualitative and quantitative parameters of “Oliva Bianca” oil and drupe, that can have important beneficial effects on human health.

Preliminary study on the potential application of Fourier-transform mid-infrared for the evaluation of overall quality and authenticity of Moroccan virgin olive oil

BACKGROUND

Olive oil provides a wide range of health-promoting compounds. The quality of olive oil is an even more complex concept as it is affected by several factors, such as variety, season, stage of maturation, extraction processing, and so on. The main objective of this study was to determine the potential of chemical and mid-infrared spectroscopy techniques to determine the quality and authenticity of virgin olive oil (VOO). For this, we studied 41 VOOs originating from five regions of Morocco (Fez/Meknes, Eastern, Northern, Beni-Mellal/Khenifra, and Marrakech/Safi) and produced using different agricultural and technological conditions during two successive crop seasons (2015-2016 and 2016-2017).

RESULTS

By applying principal component analysis and factorial discriminant analysis with leave-one-out validation to the mid-infrared spectroscopy, clear discrimination between VOO samples according to their geographic origin and variety was observed, with correct classification rates of 91.87% and 91.87% being observed respectively. The application of partial least-squares regression to mid-infrared and chemical data sets allowed excellent prediction of free acidity, peroxide value, k₂₇₀ , and chlorophyll level with R² of 0.99, 0.97, 0.98, and 0.93 respectively, and good prediction of k₂₃₂ (R² = 0.84).

CONCLUSION

The results demonstrate that mid-infrared spectroscopy coupled with chemometric tools could be used as a rapid screening tool for evaluating the overall quality and authenticity of VOO. © 2020 Society of Chemical Industry.

Virgin Olive Oil Volatile Compounds: Composition, Sensory Characteristics, Analytical Approaches, Quality Control, and Authentication

Volatile organic compounds strongly contribute to both the positive and negative sensory attributes of virgin olive oil, and more and more studies have been published in recent years focusing on several aspects regarding these molecules. This Review is aimed at giving an overview on the state of the art about the virgin olive oil volatile compounds. Particular emphasis was given to the composition of the volatile fraction, the analytical issues and approaches for analysis, the sensory characteristics and interaction with phenolic compounds, and the approaches for supporting the Panel Test in virgin olive oil classification and in authentication of the botanical and geographic origin based on volatile compounds. A pair of detailed tables with a total of approximately 700 volatiles identified or tentatively identified to date and tables dealing with analytical procedures, sensory characteristics of volatiles, and specific chemometric approaches for quality assessment are also provided.

State-of-the-Art of Analytical Techniques to Determine Food Fraud in Olive Oils

The benefits of the food industry compared to other sectors are much lower, which is why producers are tempted to commit fraud. Although it is a bad practice committed with a wide variety of foods, it is worth noting the case of olive oil because it is a product of great value and with a high percentage of fraud. It is for all these reasons that the authenticity of olive oil has become a major problem for producers, consumers, and legislators. To avoid such fraud, it is necessary to develop analytical techniques to detect them. In this review, we performed a complete analysis about the available instrumentation used in olive fraud which comprised spectroscopic and spectrometric methodology and analyte separation techniques such as liquid chromatography and gas chromatography. Additionally, other methodology including protein-based biomolecular techniques and analytical approaches like metabolomic, hhyperspectral imaging and chemometrics are discussed.

Discrimination of Zanthoxylum bungeanum Maxim through volatile aroma compounds analysis with artificial neural network

Zanthoxylum bungeanum Maxim (ZBM), a special spice from Chinese different areas, have a widespread variation in quality and price. To avoid the commercial adulteration of ZBM, it is necessary to discriminate them from different areas. As volatile aroma compounds (VAC) have the potential to discriminate ZBM, electronic nose (E-nose) was used to preliminarily discriminate the VAC through sensor response analysis, radar chart analysis, and principal component analysis. Then, Gas chromatography-mass spectrometry (GC-MS) was utilized to identify VAC through hierarchical cluster analysis and quantitative analysis. Finally, artificial neural network (ANN) was employed to assess the accuracy of the discrimination of ZBM. As a result, we found that ZBM could be successfully discriminated between Chinese Sichuan and the other areas. Our findings would provide guidance for evaluating and predicting the variation of VAC of ZBM from different areas in further study. PRACTICAL APPLICATIONS: Zanthoxylum bungeanum Maxim (ZBM) is a traditional and important spice used in Sichuan cuisine especially hotpot, which are famous all over overseas. However, the ZBM from different producing areas bring various flavors, hampering the quality of Sichuan cuisine developing toward to standardization. Therefore, the authors in this work pursuit an effective way to distinguish the ZBM produced in Sichuan rather than in other province. According to the results of the present study, ZBM could be successfully discriminated between Chinese Sichuan and the other producing areas by using E-nose and GC-MS through artificial neural network. These findings would provide the guidance for evaluating the producing areas of ZBM to be whether or not Sichuan, which could offer the practical help in the purchase of the raw material in the supply chain. Besides, these also can be applied to predict the variation of volatile aroma compounds of the ZBM in the further study.

Analysis of Volatile Components of Auricularia auricula from Different Origins by GC-MS Combined with Electronic Nose

Auricularia auricula is a kind of nutrient-rich edible fungus, which has the reputation of “king of vegetarians.” In this paper, the electronic nose combined with GC-MS technology was used to analyze the volatile components of A. auricula in Heilongjiang, Jilin, Shanghai, and Sichuan provinces to investigate the differences and characteristics of A. auricula in different origins. The results showed that the electronic nose could obviously distinguish the samples from Jilin and Shanghai with a high degree of discrimination, while it was inappropriate to distinguish the samples from Heilongjiang and Sichuan Province. GC-MS was used to further analyze the volatile compounds in A. auricula qualitatively and quantitatively. The results showed that 98 volatile components were detected and 23 of them were common components, including alcohols, aldehydes, acids, esters, hydrocarbons, and other volatile components. The relative content of acetic acid and diethyl azodicarboxylate in A. auricula from the four origins was relatively high. According to the relative odor activity value (ROAV), it was found that the key compounds that caused the aroma difference between different origins were 1-octene-3-ol, cis-3-nonene-1-ol, (E)-2-octenal, (E)-2-nonenal, (E,E)-2,4-nonadienal, and 3-methyl butanal.