Volatilomics for food quality and authentication

A novel headspace solid-phase microextraction arrow method employing comprehensive two-dimensional gas chromatography-mass spectrometry combined with chemometric tools for the investigation of wine aging

BACKGROUND

Omics is used as an analytical tool to investigate wine authenticity issues. Aging authentication ensures that the wine has undergone the necessary maturation and developed its desired organoleptic characteristics. Considering that aged wines constitute valuable commodities, the development of advanced omics techniques that guarantee aging authenticity and prevent fraud is essential.

RESULTS

Α solid phase microextraction Arrow method combined with comprehensive two-dimensional gas chromatography-mass spectrometry was developed to identify volatiles in red wines and investigate how aging affects their volatile fingerprint. The method was optimized by examining the critical parameters that affect the solid phase microextraction Arrow extraction (stirring rate, extraction time) process. Under optimized conditions, extraction took place within 45 min under stirring at 1000 rpm. In all, 24 monovarietal red wine samples belonging to the Xinomavro variety from Naoussa (Imathia regional unit of Macedonia, Greece) produced during four different vintage years (1998, 2005, 2008 and 2015) were analyzed. Overall, 237 volatile compounds were tentatively identified and were treated with chemometric tools. Four major groups, one for each vintage year were revealed using the Hierarchical Clustering Analysis. The first two Principal Components of Principal Component Analysis explained 86.1% of the total variance, showing appropriate grouping of the wine samples produced in the same crop year. A two-way orthogonal partial least square - discriminant analysis model was developed and successfully classified all the samples to the proper class according to the vintage age, establishing 17 volatile markers as the most important features responsible for the classification, with an explained total variance of 88.5%. The developed prediction model was validated and the analyzed samples were classified with 100% accuracy according to the vintage age, based on their volatile fingerprint.

SIGNIFICANCE

The developed methodology in combination with chemometric techniques allows to trace back and confirm the vintage year, and is proposed as a novel authenticity tool which opens completely new and hitherto unexplored possibilities for wine authenticity testing and confirmation.

Enhancing Odor Analysis with Gas Chromatography-Olfactometry (GC-O): Recent Breakthroughs and Challenges

Gas chromatography-olfactometry (GC-O) has made significant advancements in recent years, with breakthroughs in its applications and the identification of its limitations. This technology is widely used for analyzing complex odor patterns. The review begins by explaining the principles of GC-O, including sample preparation, separation methods, and olfactory evaluation techniques. It then explores the diverse range of applications where GC-O has found success, such as food and beverage industries, environmental monitoring, perfume and aroma development, and forensic analysis. One of the major breakthroughs in GC-O analysis is the improvement in separation power and resolution of odorants. Techniques like rapid GC, comprehensive two-dimensional GC, and multidimensional GC have enhanced the identification and quantification of odor-active chemicals. However, GC-O also has limitations. These include the challenges in detecting and quantifying trace odorants, dealing with matrix effects, and ensuring the repeatability and consistency of results across laboratories. The review examines these limitations closely and discusses potential solutions and future directions for improvement in GC-O analysis. Overall, this review presents a comprehensive overview of the recent advances in GC-O, covering breakthroughs, applications, and limitations. It aims to promote the wider usage of GC-O analysis in odor analysis and related industries. Researchers, practitioners, and anyone interested in leveraging the capabilities of GC-O in analyzing complex odor patterns will find this review a valuable resource. The article highlights the potential of GC-O and encourages further research and development in the field.

Characterization of lipids and volatile compounds in boiled donkey meat by lipidomics and volatilomics

Lipids are crucial substances for the formation and retention of volatile compounds (VOCs). The lipid and VOC profiles of boiled donkey meat were investigated by lipidomics and volatilomics. In total, 4277 lipids belonging to 39 subclasses were identified, comprising 26.93% triglycerides (TGs), 15.74% phosphatidylcholins (PCs), and 9.40% phosphatidylethanolamines. The relative percentage of TG in the meat significantly decreases (p < 0.001) from 0 to 40 min, after which there is no significant change, whereas PCs, sphingomyelins, and methyl phosphatidylcholines (MePCs) show the opposite trend. TG(16:1_18:1_18:2) and TG(16:0_16:1_18:2) appear to be key lipids for retaining VOCs in boiled donkey meat. Furthermore, PC(18:3e_16:0) and MePC(31:0e) were found to be potential markers for discriminating donkey meat. A total of 83 VOCs were detected, including 25.30% aldehydes, 18.07% hydrocarbons, 14.46% ketones, and 13.25% alcohols. Eleven characteristic VOCs with relative odor activity values >1 were identified as the predominant flavor compounds in boiled donkey meat, mainly hexanal and 1-octen-3-ol. Of the 258 differential lipids, 72 of them, especially polyunsaturated-fatty acid-rich lipids, are the main contributors to the formation of VOCs. Together, the key lipids for retention and formation of VOCs in donkey meat were revealed, providing a theoretical basis for VOC regulation.

Aflatoxins: Occurrence, biosynthesis, mechanism of action and effects, conventional/emerging detection techniques

Aflatoxins (AFs) are toxic secondary metabolites prevalent in various food and agricultural products, posing significant challenges to global food safety. The detection and quantification of AFs through high-precision analytical techniques are crucial in mitigating AF contamination levels and associated health risks. Variousmethods,including conventional and emerging techniques, have been developed for detecting and quantifyingAFsinfood samples. This review provides an in-depth analysis of the global occurrence of AF in food commodities, covering their biosynthesis, mode of action, and effects on humans and animals. Additionally, the review discusses different conventional strategies, including chromatographic and immunochemical approaches, for AF quantification and identification in food samples. Furthermore, emerging AF detection strategies, such as solid-state gas sensors and electronic nose technologies, along with their applications, limitations, and future perspectives, were reviewed. Sample purification, along with their respective advantages and limitations, are also discussed herein.

A volatilomics analytical protocol employing solid phase microextraction coupled to GC × GC-MS analysis and combined with multivariate chemometrics for the detection of pomegranate juice adulteration

In this work, a solid-phase microextraction (SPME) method combined with two-dimensional gas chromatography coupled to mass spectrometry (GC × GC-MS) was optimized and used to assess the authenticity of pomegranate juice to prevent fraudulent practices. A divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber was used for the extraction of the volatiles. The critical parameters that affect the extraction process, such as the sample volume, and the extraction time were studied. The optimized protocol involved the addition of 15 mL of juice in 50 mL vial and saturation with 30% w/v NaCl.The extraction was carried out within 45 min under 1000 rpm stirring and was applied in the analysis of real juice samples to assess authenticity and detect low levels of pomegranate juice adulteration with grape and apple juice down to 1%. Commercially available pomegranate juice samples were acquired (n1 = 6) and adulterated with 1% of apple juice (n2 = 6), 1% of grape juice (n3 = 6), and a mixture of 1% apple juice and 1% grape juice (n4 = 6). Authentic pomegranate juice samples and adulterated mixtures were analyzed by SPME-GC × GC-MS. The analysis resulted in the identification of 123 volatile compounds that were further processed with chemometric tools. Principal component analysis (PCA) was employed to visualize the clustering of the samples, and a two-way orthogonal partial least squares discriminant analysis (O2PLS-DA) chemometric model was developed and successfully classified the samples to authentic pomegranate juice or adulterated with an explained total variance of 87.4%. The O2PLS-DA prediction model revealed characteristic volatile markers that could be used to detect pomegranate juice fraud.

Improved Detection and Quantification of Cyclopropane Fatty Acids via Homonuclear Decoupling Double Irradiation NMR Methods

Over the years, NMR spectroscopy has become a powerful analytical tool for the identification and quantification of a variety of natural compounds in a broad range of food matrices. Furthermore, NMR can be useful for characterizing food matrices in terms of quality and authenticity, also allowing for the identification of counterfeits. Although NMR requires minimal sample preparation, this technique suffers from low intrinsic sensitivity relative to complementary techniques; thus, the detection of adulterants or markers for authenticity at low concentrations remains challenging. Here, we present a strategy to overcome this limitation by the introduction of a simple band-selective homonuclear decoupling sequence that consists of double irradiation on 1H during NMR signal acquisition. The utility of the proposed method is tested on dihydrosterculic acid (DHSA), one of the cyclopropane fatty acids (CPFAs) shown to be a powerful molecular marker for authentication of milk products. A quantitative description of how the proposed NMR scheme allows sensitivity enhancement yet accurate quantification of DHSA is provided.

Cocoa quality: Chemical relationship of cocoa beans and liquors in origin identitation

In this study, HS-SPME-GC-MS was applied in combination with machine learning tools to the identitation of a set of cocoa samples of different origins. Untargeted fingerprinting and profiling approaches were tested for their informative, discriminative and classification ability provided by the volatilome of the raw beans and liquors inbound at the factory in search of robust tools exploitable for long-time studies. The ability to distinguish the country of origin on both beans and liquors is not so obvious due to processing steps accompanying the transformation of the beans, but this capacity is of particular interest to the chocolate industry as both beans and liquors can enter indifferently into the processing of chocolate. Both fingerprinting (untargeted) and profiling (targeted) strategies enable to decipher of the information contained in the complex dataset and the cross-validation of the results, affording to discriminate between the origins with effective classification models.

Spoilage markers for freshwater fish: A comprehensive workflow for non-targeted analysis of VOCs using DHS-GC-HRMS

Changes of volatile organic compounds (VOCs) patterns during 6 days of storage at +4 °C were investigated in different freshwater fish species, namely carp and trout, using dynamic headspace gas chromatography time-of-flight mass spectrometry (DHS-GC-TOFMS). DHS parameters were systematically optimized to establish optimum extraction and pre-concentration of VOCs. Moreover, different sample preparation methods were tested: mincing with a manual meat grinder, as well as mincing plus homogenization with a handheld homogenizer both without and with water addition. The addition of water during sample preparation led to pronounced changes of the volatile profiles, depending on the molecular structure and lipophilicity of the analytes, resulting in losses of up to 98 % of more lipophilic compounds (logP > 3). The optimized method was applied to trout and carp. Trout samples of different storage days were compared using univariate (Mann-Whitney U test, fold change calculation) and multivariate (OPLS-DA) statistics. 37 potential spoilage markers were selected; for 11 compounds identity could be confirmed via measurement of authentic standards and 10 compounds were identified by library spectrum match. 22 compounds were also found to be statistically significant spoilage markers in carp. Merging results of the different statistical approaches, the list of 37 compounds could be narrowed down to the 14 most suitable for trout spoilage assessment. This study comprises a systematic evaluation of the capabilities of DHS-GC coupled to high-resolution (HR) MS for studying spoilage in different freshwater fish species, including a comprehensive data evaluation workflow.

Aroma Difference Analysis of Partridge Tea (Mallotus oblongifolius) with Different Drying Treatments Based on HS-SPME-GC-MS Technique

Partridge tea has high medicinal value due to its rich content of terpenoids, phenols, flavonoids, and other related bioactive components. In order to study the best drying method for partridge tea, four treatments, including outdoor sun drying (OD), indoor shade drying (ID), hot-air drying (HAD), and low-temperature freeze-drying (LTD), were performed. The results showed that the OD and HAD treatments favored the retention of the red color of their products, while the ID and LTD treatments were more favorable for the retention of the green color. The HS-SPME-GC-MS results showed that a total of 82 compounds were identified in the four drying treatments of partridge tea, and the most abundant compounds were terpenoids (88.34-89.92%). The HAD-treated tea had the highest terpenoid content (89.92%) and high levels of flavor compounds typical of partridge tea (52.28%). OPLS-DA and PCA showed that α-copaene, β-bourbonene, caryophyllene, α-guaiene, and δ-cadinene could be considered candidate marker compounds for judging the aroma quality of partridge tea with different drying treatments. This study will not only provide a basis for processing and flavor quality control but also for spice and seasoning product development in partridge tea.

The potential of metabolomics in assessing global compositional changes resulting from the application of CRISPR/Cas9 technologies

Exhaustive analysis of genetically modified crops over multiple decades has increased societal confidence in the technology. New Plant Breeding Techniques are now emerging with improved precision and the ability to generate products containing no foreign DNA and mimic/replicate conventionally bred varieties. In the present study, metabolomic analysis was used to compare (i) tobacco genotypes with and without the CRISPR associated protein 9 (Cas9), (ii) tobacco lines with the edited and non-edited DE-ETIOLATED-1 gene without phenotype and (iii) leaf and fruit tissue from stable non-edited tomato progeny with and without the Cas9. In all cases, multivariate analysis based on the difference test using LC-HRMS/MS and GC-MS data indicated no significant difference in their metabolomes. The variations in metabolome composition that were evident could be associated with the processes of tissue culture regeneration and/or transformation (e.g. interaction with Agrobacterium). Metabolites responsible for the variance included quantitative changes of abundant, well characterised metabolites such as phenolics (e.g. chlorogenic acid) and several common sugars such as fructose. This study provides fundamental data on the characterisation of gene edited crops, that are important for the evaluation of the technology and its assessment. The approach also suggests that metabolomics could contribute to routine product-based analysis of crops/foods generated from New Plant Breeding approaches.

Volatilome Analysis and Evolution in the Headspace of Packed Refrigerated Fish

Fresh fish is a perishable food in which chemical (namely oxidation) and microbiological degradation result in undesirable odor. Non-processed fish (i.e., raw fish) is increasingly commercialized in packaging systems which are convenient for its retailing and/or which can promote an extension of its shelf-life. Compared to fish sent to its retail unpackaged, fish packaging results in a modification of the gaseous composition of the atmosphere surrounding it. These modifications of atmosphere composition may affect both chemical and microbiological degradation pathways of fish constituents and thereby the volatile organic compounds produced. In addition to monitoring Total Volatile Basic Nitrogen (TVB-N), which is a common indicator to estimate non-processed fish freshness, analytical techniques such as gas chromatography coupled to mass spectrometry or techniques referred to as "electronic nose" allow either the identification of the entire set of these volatile compounds (the volatilome) and/or to selectively monitor some of them, respectively. Interestingly, monitoring these volatile organic compounds along fish storage might allow the identification of early-stage markers of fish alteration. In this context, to provide relevant information for the identification of volatile markers of non-processed packaged fish quality evolution during its storage, the following items have been successively reviewed: (1) inner atmosphere gaseous composition and evolution as a function of fish packaging systems; (2) fish constituents degradation pathways and analytical methods to monitor fish degradation with a focus on volatilome analysis; and (3) the effect of different factors affecting fish preservation (temperature, inner atmosphere composition, application of hurdle technology) on volatilome composition.

Volatomics-assisted characterization of aroma and off-flavor contributors in fresh and thermally treated kiwifruit juice

The distinctive aroma profile of kiwifruit juice was significantly changed during thermal treatment, however, the theoretical basis for clarifying and controlling the changes was deficient. In this study, we applied volatomics techniques to investigate the contributors of off-flavors in thermally treated kiwifruit juice. Sixteen aroma compounds were identified to be responsible for the typical "fruity", "grassy", and "cucumber-like" flavors of fresh kiwifruit by two different fused silica capillary columns coupled with chromatography-olfactometry/detection frequency (GC-O/DF) analysis and calculation of odor activity value (OAV). Thirty-one odor-active compounds were determined as important contributors to the sensory profile of thermally treated kiwifruit juice, 14 of which were common to all varieties investigated. The key aroma compounds on fresh kiwifruit significantly decreased after thermal treatment, while decanal, (E)-2-decenal, methional, β-damascenone, 1-octen-3-one, DMHF, and dimethyl sulfide which presented undesirable cooked cabbage/potato, roasted fruit, and sulfurous odors, were accumulated in a large amount. By applying PLSR analysis, (E)-2-decenal, methional, β-damascenone, DMHF, and dimethyl sulfide were further verified to have great contributions to the formation of the cooked off-flavor during thermal treatment. Moreover, XX was found to be more thermal-sensitive and more prone to forming cooked off-flavors after thermal treatment. This study could provide theoretical guidance for the regulation of thermal-induced off-flavors during the manufacturing of kiwifruit juice.

Molecular insights into quality and authentication of sheep meat from proteomics and metabolomics

Sheep meat (encompassing lamb, hogget and mutton) is an important source of animal protein in many countries, with a unique flavour and sensory profile compared to other red meats. Flavour, colour and texture are the key quality attributes contributing to consumer liking of sheep meat. Over the last decades, various factors from 'farm to fork', including production system (e.g., age, breed, feeding regimes, sex, pre-slaughter stress, and carcass suspension), post-mortem manipulation and processing (e.g., electrical stimulation, ageing, packaging types, and chilled and frozen storage) have been identified as influencing different aspects of sheep meat quality. However conventional meat-quality assessment tools are not able to elucidate the underlying mechanisms and pathways for quality variations. Advances in broad-based analytical techniques have offered opportunities to obtain deeper insights into the molecular changes of sheep meat which may become biomarkers for specific variations in quality traits and meat authenticity. This review provides an overview on how omics techniques, especially proteomics (including peptidomics) and metabolomics (including lipidomics and volatilomics) are applied to elucidate the variations in sheep meat quality, mainly in loin muscles, focusing on colour, texture and flavour, and as tools for authentication. SIGNIFICANCE: From this review, we observed that attempts have been made to utilise proteomics and metabolomics techniques on sheep meat products for elucidating pathways of quality variations due to various factors. For instance, the improvement of colour stability and tenderness could be associated with the changes to glycolysis, energy metabolism and endogenous antioxidant capacity. Several studies identify proteolysis as being important, but potentially conflicting for quality as the enhanced proteolysis improves tenderness and flavour, while reducing colour stability. The use of multiple analytical methods e.g., lipidomics, metabolomics, and volatilomics, detects a wider range of flavour precursors (including both water and lipid soluble compounds) that underlie the possible pathways for sheep meat flavour evolution. The technological advancement in omics (e.g., direct analysis-mass spectrometry) could make analysis of the proteins, lipids and metabolites in sheep meat routine, as well as enhance the confidence in quality determination and molecular-based assurance of meat authenticity.

Characterization of the Volatile Profiles of Insect Flours by (HS)-SPME/GC-MS: A Preliminary Study

The growing world population, combined with scarcities of agricultural land, water, forest, fisheries, and biodiversity resources, makes it necessary to search for alternative sources of nutrients. For this reason, in recent years, edible insects have been introduced into the diet, even in areas where entomophagy is not traditional. In light of this, the present study aims at characterizing the aromatic profile of three edible insects flours: cricket (Acheta domesticus, CP), buffalo worm (Alphitobius diaperinus, BW), and mealworm (Tenebrio molitor, MW). This goal has been achieved by means of an (HS)-SPME/GC-MS strategy. 67 compounds have been tentatively identified; of these, 27 are present only in the CP and BW flours, while 10 are common in all three flours. The compound with the highest peak's relative area in gas chromatograms of CP and BW flours is hexadecanoic acid, while in MW it is 1-heptylpyrrolidin-2-one. In general, we have observed that CP and BW flours have 37 compounds in common, and their volatile compositions along with their profiles are more similar to each other than to MW profile.

Widely targeted volatileomics analysis reveals the typical aroma formation of Xinyang black tea during fermentation

Xinyang black tea (XYBT) is characterized by the honey sugar-like aroma which is produced during the fermentation process. However, the formation of this typical aroma is still unclear. We here performed widely targeted volatileomics analysis combined with GC-MS and detected 116 aroma active compounds (AACs) with OAV > 1. These AACs were mainly divided into terpenoids, pyrazine, volatile sulfur compounds, esters, and aldehydes. Among them, 25 significant differences AACs (SDAACs) with significant differences in fermentation processes were identified, comprising phenylacetaldehyde, dihydroactinidiolide, α-damascenone, β-ionone, methyl salicylate, and so forth. In addition, sensory descriptions and partial least squares discriminant analysis demonstrated that phenylacetaldehyde was identified as the key volatile for the honey sugar-like aroma. We further speculated that phenylacetaldehyde responsible for the aroma of XYBT was probably produced from the degradation of L-phenylalanine and styrene. In conclusion, this study helps us better understand the components and formation mechanism of the honey sugar-like aroma of XYBT, providing new insight into improving the processing techniques for black tea quality.

Comparative phytochemical analysis of Ferula assa-foetida with Ferula jaeschkeana and commercial oleo-gum resins using GC-MS and UHPLC-PDA-QTOF-IMS

Ferula assa-foetida is an important species of the genus Ferula, best known for its oleo-gum resin, mainly used as a flavoring agent. Ferula jaeschkeana is another Himalayan medicinal plant of this genus, known for its contraceptive effect but not used in food applications. This study aimed to do a detailed phytochemical analysis of F. assa-foetida growing under controlled conditions in India using GC-MS/headspace and UHPLC-PDA-QTOF-IMS. Further, a comparative analysis of F. assa-foetida was performed with F. jaeschkeana (collected from its natural habitat) and commercial samples of F. assa-foetida oleo-gum resin (collected from the local market). UHPLC-QTOF-IMS profiling of F. assa-foetida led to the identification of foetisulfide C, assafoetidnol A, gumosin, flabellilobin (A/B), and foetisulfide A. In total, 141 metabolites were identified, including vitamins, nucleosides, sulfur compounds, flavonoids, sugars derivatives, and others, using METLIN database. Serine, arginine, asparagine, isoleucine, and phenylalanine were major amino acids quantified among the samples for the nutritional aspect. Characteristic sulfurous compounds (n-propyl-sec-butyl disulfide, trans-propenyl-sec-butyl disulfide, cis-propenyl-sec-butyl disulfide, and bis[1-(methylthio)propyl] disulfide) were identified in all samples except F. jaeschkeana. PCA and cluster analysis showed a significant difference in the volatile constituents of rhizomes of both species. Metabolomics studies also revealed the association of sesquiterpenoid and triterpenoid biosynthesis, phenylpropanoid, flavon, and flavanol biosynthesis. The current study demonstrates, "why only F. assa-foetida is used in culinary applications instead of F. jaeschkeana"?

Volatilomics of raspberry fruit germplasm by combining chromatographic and direct-injection mass spectrometric techniques

The application of direct-injection mass spectrometric (DI-MS) techniques, like Proton Transfer Reaction Time of Flight Mass Spectrometry (PTR-ToF-MS) has been suggested as a reliable phenotyping tool for fruit volatilome assessment in both genetic and quality-related studies. In this study the complexity of raspberry aroma was investigated by a comprehensive untargeted VOC analysis, done by combining SPME-GC-MS and PTR-ToF-MS assessments with multi-block discriminant analysis using the DIABLO mixOmics framework. The aim was to acquire an exhaustive characterization of the raspberry volatilome according to different fruit ripening stages (pink, ripe, and overripe) and genetic variances (50 accessions), as well as to investigate the potential of PTR-ToF-MS as a rapid and high throughput VOC phenotyping tool to address issues related to raspberry fruit quality. Results of this study demonstrated the complementarity between SPME-GC-MS and PTR-ToF-MS techniques to evaluate the raspberry aroma composition. PTR-ToF-MS generates reliable raspberry VOC fingerprints mainly due to a reduced compound fragmentation and precise content estimation. In addition, the high collinearity between isomers of monoterpenes and norisoprenoids, discovered by GC analysis, reduces the main analytic limitation of PTR-ToF-MS of not being able to separate isomeric molecules. The high similarity between the VOC matrices obtained by applying PTR-ToF-MS and SPME-GC-MS confirmed the possibility of using PTR-ToF-MS as a reliable high throughput phenotyping tool for raspberry volatiolome assessment. In addition, results provided by the germplasm collection investigation enabled to distinguish the best performing accessions, based on VOCs composition, to be used as superior parental lines for future breeding programs.

Potential Aroma Chemical Fingerprint of Oxidised Coffee Note by HS-SPME-GC-MS and Machine Learning

This study examines the volatilome of good and oxidised coffee samples from two commercial coffee species (i.e., Coffea arabica (arabica) and Coffea canephora (robusta)) in different packagings (i.e., standard with aluminium barrier and Eco-caps) to define a fingerprint potentially describing their oxidised note, independently of origin and packaging. The study was carried out using HS-SPME-GC-MS/FPD in conjunction with a machine learning data processing. PCA and PLS-DA were used to extrapolate 25 volatiles (out of 147) indicative of oxidised coffees, and their behaviour was compared with literature data and critically discussed. An increase in four volatiles was observed in all oxidised samples tested, albeit to varying degrees depending on the blend and packaging: acetic and propionic acids (pungent, acidic, rancid), 1-H-pyrrole-2-carboxaldehyde (musty), and 5-(hydroxymethyl)-dihydro-2(3H)-furanone.

Monitoring Volatile Organic Compounds in Different Pear Cultivars during Storage Using HS-SPME with GC-MS

Aroma, which plays an essential role in food perception and acceptability, depends on various mixture of volatile organic compounds (VOCs). Meanwhile, as a field of metabolomics, VOC analysis is highly important for aroma improvement and discrimination purposes. In this work, VOCs in pear fruits were determined via headspace solid-phase micro-extraction (HS-SPME) combined with gas chromatography-mass spectrometry (GC-MS) to study variations among different cultivars and storage stages. In 12 cultivars of pear fruits, a total of 121 VOCs were quantified, including 40 esters, 32 alcohols, 16 aldehydes, 13 alkenes, 11 ketones, 4 acids, and 5 other compounds. The types and amounts of VOCs in different cultivars varied dramatically, which were in the range of 13-71 and 3.63-55.65 mg/kg FW (fresh weight), respectively. The Dr. Guyot cultivar showed the highest level of VOCs, both in type and amount. After 21 days storage at 4 °C, total concentration of VOCs increased from initial levels of 50.76 to 101.33 mg/kg FW. Storage at 20 °C made a larger contribution to production for VOCs than that at 4 °C, resulting in the maximum content of VOCs (117.96 mg/kg FW) in fruit after 14 days storage at 4 °C plus 7 days at 20 °C. During storage, the content of esters showed a gradual increase, while the content of alcohols and aldehydes decreased. Based on the results presented, related alcohols were recognized as the intermediates of conversion from aldehydes to esters.

Authenticity and Typicity of Traditional Cheeses: A Review on Geographical Origin Authentication Methods

Food fraud, corresponding to any intentional action to deceive purchasers and gain an undue economical advantage, is estimated to result in a 10 to 65 billion US dollars/year economical cost worldwide. Dairy products, such as cheese, in particular cheeses with protected land- and tradition-related labels, have been listed as among the most impacted as consumers are ready to pay a premium price for traditional and typical products. In this context, efficient food authentication methods are needed to counteract current and emerging frauds. This review reports the available authentication methods, either chemical, physical, or DNA-based methods, currently used for origin authentication, highlighting their principle, reported application to cheese geographical origin authentication, performance, and respective advantages and limits. Isotope and elemental fingerprinting showed consistent accuracy in origin authentication. Other chemical and physical methods, such as near-infrared spectroscopy and nuclear magnetic resonance, require more studies and larger sampling to assess their discriminative power. Emerging DNA-based methods, such as metabarcoding, showed good potential for origin authentication. However, metagenomics, providing a more in-depth view of the cheese microbiota (up to the strain level), but also the combination of methods relying on different targets, can be of interest for this field.

Volatile compounds, texture, and color characterization of meatballs made from beef, rat, wild boar, and their mixtures

The purpose of this research was to characterize the volatile compounds, texture, and color profile of meatballs made from beef, rat, wild boar, and their combinations. Volatile compounds were analyzed using SPME/GC-MS and multivariate data analysis (PCA, PLS-DA). Additionally, several textural features such as hardness, gumminess, chewiness, cohesiveness, and colour (L, a∗, b∗, C, and h) were also analyzed. The findings revealed that texture and color characteristics can only be used to differentiate meatballs based on their raw meat materials when meat adulterants are used in high concentrations (≥50%). PLS-DA analysis of volatile data revealed distinct groupings among various types of meatballs, including meatballs adulterated with rat or wild boar meat at the lowest percentage used in this study (20%). By using VIP and correlation coefficient, the strongest markers in beef, rat, and wild boar meatballs were identified as (Z)-2-amino-5-methyl-benzoic acid, 2-heptenal, and cyclobutanol, respectively. Nonanal was consistently found as a significant marker in the meatballs made from a mixture of beef-rat and beef-wild boar at different ratios. This study demonstrated that the volatile profile of meat is more reliable than physicochemical profiles for developing an analytical tool for quickly identifying undesired meat in meat-derived products.

Valorization of Traditional Italian Walnut (Juglans regia L.) Production: Genetic, Nutritional and Sensory Characterization of Locally Grown Varieties in the Trentino Region

Juglans regia (L.) is cultivated worldwide for its nutrient-rich nuts. In Italy, despite the growing demand, walnut cultivation has gone through a strong decline in recent decades, which led to Italy being among the top five net importing countries. To promote the development of local high-quality Italian walnut production, we devised a multidisciplinary project to highlight the distinctive traits of three varieties grown in the mountainous region Trentino (northeast of Italy): the heirloom ‘Bleggiana’, a second local accession called local Franquette and the French cultivar ‘Lara’, recently introduced in the local production to increase yield. The genetic characterization confirmed the uniqueness of ‘Bleggiana’ and revealed local Franquette as a newly described autochthonous variety, thus named ‘Blegette’. The metabolic profiles highlighted a valuable nutritional composition of the local varieties, richer in polyphenols and with a lower ω-6/ω-3 ratio than the commercial ‘Lara’. ‘Blegette’ obtained the highest preference scores from consumers for both the visual aspect and tasting; however, the volatile organic compound profiles did not discriminate among the characterized cultivars. The described local varieties represent an interesting reservoir of walnut genetic diversity and quality properties, which deserve future investigation on agronomically useful traits (e.g., local adaptation and water usage) for a high-quality and sustainable production.

Effect of the Dispersion Process and Nanoparticle Quality on Chemical Sensing Performance

On the surface of chemiresistive films, the scarce heterogeneity of a molecularly capped gold nanoparticle (MCGNP) colloidal dispersion and uneven evaporation of the MCGNP-contained drying drop applied to this surface are among the main factors that affect reproducibility, and repeatable fabrication of thin films of MCGNPs. This article shows that an increase in reproducibility and repeatability is possible using a dispersant and a surfactant during the deposition and annealing processes of the MCGNP. The results show higher sensitivity and accuracy of the sensors for the detection of volatile organic compounds in air and an increased limit of detection. These simple and practical additions might serve as a launching pad for fabrication of other types of thin-film-based sensors.

Fingerprinting of Volatile Organic Compounds for the Geographical Discrimination of Rice Samples from Northeast China

Rice’s geographic origin and variety play a vital role in commercial rice trade and consumption. However, a method for rapidly discriminating the geographical origins of rice from a different region is still lacking. Therefore, the current study developed a volatile organic compound (VOC) based geographical discrimination method using headspace gas chromatography-mass spectrometry (HS-GC-MS) to discriminate rice samples from Heilongjiang, Jilin, and Liaoning provinces. The rice VOCs in Heilongjiang, Liaoning, and Jilin were analyzed by agglomerative hierarchical clustering (AHC), principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). The results show that the optimum parameters for headspace solid phase microextraction (HS-SPME) involved the extraction of 3.0 g of rice at 80 °C within 40 min. A total of 35 VOCs were identified from 30 rice varieties from Northeast China. The PLS-DA model exhibited good discrimination (R² = 0.992, Q² = 0.983, and Accuracy = 1.0) for rice samples from Heilongjiang, Liaoning, and Jilin. Moreover, K-nearest neighbors showed good specificity (100%) and accuracy (100%) in identifying the origin of samples. In conclusion, the present study established VOC fingerprinting as a highly efficient approach to identifying rice’s geographical origin. Our findings highlight the ability to discriminate rice from Heilongjiang, Liaoning, and Jilin provinces rapidly.

Assessing food authenticity through protein and metabolic markers

This chapter aims to address an issue of ancient origins, but more and more topical in a globalized world in which consumers and stakeholders are increasingly aware: the authenticity of food. Foods are systems that can also be very complex, and verifying the correspondence between what is declared and the actual characteristics of the product is often a challenging issue. The complexity of the question we want to answer (is the food authentic?) means that the answer is equally articulated and makes use of many different analytical techniques. This chapter will consider the chemical analyses of foods aimed at guaranteeing their authenticity and will focus on frontier methods that have been developed in recent years to address the need to respond to ever-increasing guarantees of authenticity. Targeted and non-targeted approaches will be considered for verifying the authenticity of foods, through the study of different classes of constituents (proteins, metabolites, lipids, flavors). The numerous approaches available (proteomics, metabolomics, lipidomics) and the related analytical techniques (LC-MS, GC-MS, NMR) are first described from a more general point of view, after which their specific application for the purposes of authentication of food is addressed.

Headspace Solid-Phase Microextraction Followed by Gas Chromatography-Mass Spectrometry as a Powerful Analytical Tool for the Discrimination of Truffle Species According to Their Volatiles

This study provides the first assessment of the volatile metabolome map of Tuber Aestivum and Tuber Borchii originating from Greece using headspace solid-phase micro-extraction (HS-SPME) coupled to gas chromatography-mass spectrometry (GC-MS). For the extraction of the volatile fraction, the SPME protocol was optimized after examining the effects of sample mass, extraction temperature, and extraction time using the one-variable at-a-time approach (OVAT). The optimum parameters involved the extraction of 100 mg of homogenized truffle for 45 min at 50°C. Overall, 19 truffle samples were analyzed, and the acquired data were normalized and further processed with chemometrics. Agglomerative hierarchical clustering (HCA) was used to identify the groups of the two species. Partial least squares-discriminant analysis (PLS-DA) was employed to develop a chemometric model that could discriminate the truffles according to the species and reveal characteristic volatile markers for Tuber Aestivum and Tuber Borchii grown in Greece.

Anthocyanin-sensitized gelatin-ZnO nanocomposite based film for meat quality assessment

Meat is considered a highly perishable food, and the interest in developing tools to monitor meat quality products has increased these years. A novel gelatin-ZnO-anthocyanin ternary nanocomposite film is proposed as a sensitive layer to meat quality monitoring in the present work. The incorporation of anthocyanin (ATH) on gelatin-ZnO (G-ZnO) film induced a sensitivity improvement of films towards ammonia vapor according to impedance measurements. G-ZnO-ATH film presented a good response (38.69 %) to the presence of ammonia vapor at 300 ppm. Also, good selectivity for ammonia was observed in the films. G-ZnO-ATH, applied to minced meat's quality monitoring at different storage conditions, showed a good performance, with a significant (p < 0.05) non-linear Spearman correlation between the response and the total volatile basic nitrogen released during meat spoilage for both storage conditions. The results suggest new perspectives in the developed film as a promising nanocomposite material for meat quality monitoring.

Volatile fingerprint of food products with untargeted SIFT-MS data coupled with mixOmics methods for profile discrimination: Application case on cheese

Volatile organic compounds (VOCs) emitted by food products are decisive for the perception of aroma and taste. The analysis of gaseous matrices is traditionally done by detection and quantification of few dozens of characteristic markers. Emerging direct injection mass spectrometry technologies offer rapid analysis based on a soft ionisation of VOCs without previous separation. The recent increase of selectivity offered by the use of several precursor ions coupled with untargeted analysis increases the potential power of these instruments. However, the analysis of complex gaseous matrix results in a large number of ion conflicts, making the quantification of markers difficult, and in a large volume of data. In this work, we present the exploitation of untargeted SIFT-MS volatile fingerprints of ewe PDO cheeses in a real farm model, using mixOmics methods allowing us to illustrate the typicality, the manufacturing processes reproducibility and the impact of the animals' diet on the final product.

Data Science in the Food Industry

Food safety is one of the main challenges of the agri-food industry that is expected to be addressed in the current environment of tremendous technological progress, where consumers' lifestyles and preferences are in a constant state of flux. Food chain transparency and trust are drivers for food integrity control and for improvements in efficiency and economic growth. Similarly, the circular economy has great potential to reduce wastage and improve the efficiency of operations in multi-stakeholder ecosystems. Throughout the food chain cycle, all food commodities are exposed to multiple hazards, resulting in a high likelihood of contamination. Such biological or chemical hazards may be naturally present at any stage of food production, whether accidentally introduced or fraudulently imposed, risking consumers' health and their faith in the food industry. Nowadays, a massive amount of data is generated, not only from the next generation of food safety monitoring systems and along the entire food chain (primary production included) but also from the Internet of things, media, and other devices. These data should be used for the benefit of society, and the scientific field of data science should be a vital player in helping to make this possible.

Exploring the volatile metabolome of conventional and organic walnut oils by solid-phase microextraction and analysis by GC-MS combined with chemometrics

It is challenging to establish a correlation between the agronomical practices and the volatile profile of high-value agricultural products. In this study, the volatile metabolome of walnut oils from conventional and organic farming type was explored by HS-SPME-GC-MS. The SPME protocol was optimized after evaluating the effects of extraction time, extraction temperature, and sample mass. The optimum parameters involved the extraction of 0.500 g walnut oil at 40 °C within 60 min. Twenty Greek walnut oils produced with conventional and organic farming were analyzed and 41 volatile compounds were identified. The determined compounds were semi-quantified, and further processed with chemometrics. Agglomerative hierarchical clustering (AHC) and principal component analysis (PCA) were used. A robust classification model was developed using sparse partial least squares-discriminant analysis (sPLS-DA) for the discrimination of walnut oils into conventional and organic, establishing volatile markers that could be used to guarantee the type of farming.

High Glucosinolate Content in Rocket Leaves (Diplotaxis tenuifolia and Eruca sativa) after Multiple Harvests Is Associated with Increased Bitterness, Pungency, and Reduced Consumer Liking

Rocket (Diplotaxis tenuifolia and Eruca sativa) leaves delivered to the UK market are variable in appearance, taste, and flavour over the growing season. This study presents sensory and consumer analyses of rocket produce delivered to the UK over the course of one year, and evaluated the contribution of environmental and cultivation factors upon quality traits and phytochemicals called glucosinolates (GSLs). GSL abundance was positively correlated with higher average growth temperatures during the crop cycle, and perceptions of pepperiness, bitterness, and hotness. This in turn was associated with reduced liking, and corresponded to low consumer acceptance. Conversely, leaves with greater sugar content were perceived as more sweet, and had a higher correlation with consumer acceptance of the test panel. First cut leaves of rocket were favoured more by consumers, with multiple leaf cuts associated with low acceptance and higher glucosinolate concentrations. Our data suggest that the practice of harvesting rocket crops multiple times reduces consumer acceptability due to increases in GSLs, and the associated bitter, hot, and peppery perceptions some of their hydrolysis products produce. This may have significant implications for cultivation practices during seasonal transitions, where leaves typically receive multiple harvests and longer growth cycles.

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance. Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud. It is the aim of the present manuscript to review the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions will also be discussed.

Metabolomics fingerprint of Philippine coffee by SPME-GC-MS for geographical and varietal classification

Volatile metabolites of Philippine Arabica and Robusta coffee beans in both forms standard (not-eaten by the Asian palm civet) and civet coffee grown in different Philippine regions were identified using the hyphenated technique headspace-solid phase microextraction-gas chromatography-mass spectrometry. A great number of volatile metabolites with a wide variety of functional groups were extracted and forty-seven prominent compounds were identified. The volatile metabolomics (volatilomics) fingerprint of Arabica coffees considerably differed from Robusta coffee and geographical origin slightly altered the fingerprint profile of coffee samples. Chemometric analysis such as principal component analysis (PCA) displayed a good classification between Arabica and Robusta coffee samples. Although Arabica coffee samples from different geographical origins were clustered separately from each other, the proximity of clusters between Arabica coffee samples which could be classified into one large group, indicated their close similarity of headspace metabolites. The distinction between Arabica samples and Robusta coffees was attributed through the PCA to several key volatile metabolites, in particular, higher quantities of acetic acid, furfural, 5-methylfurfural, 2-formylpyrrole and maltol and lower concentrations of 4-ethylguaiacol and phenol. These discriminating metabolites could represent useful quality markers to differentiate Arabica from Robusta coffee. Results revealed that the headspace metabolites in coffee provide significant information on its inherent aroma quality. Also, the findings suggested that the overall quality of Philippine coffee is variety and region-specific.