Authentication of Italian PDO lard using NIR spectroscopy, volatile profile and fatty acid composition combined with chemometrics

The activated CD36-Src axis promotes lung adenocarcinoma cell proliferation and actin remodeling-involved metastasis in high-fat environment

Obesity/overweight and lipid metabolism disorders have become increased risk factors for lung cancer. Fatty acid translocase CD36 promotes cellular uptake of fatty acids. Whether and how CD36 facilitates lung adenocarcinoma (LUAD) growth in high-fat environment is unknown. Here, we demonstrated that palmitic acid (PA) or high-fat diet (HFD) promoted LUAD cell proliferation and metastasis in a CD36-dependent manner. Mechanistically, CD36 translocated from cytoplasm to cell membrane and interacted with Src kinase upon PA stimulation in human LUAD cells. Akt and ERK, downstream of Src, were then activated to mediate LUAD cell proliferation and metastasis. Furthermore, PA treatment promoted CD36 sarcolemmal translocation, where it activated Rac1 and upregulated MMP-9 through Src-Akt/ERK pathway, resulting in redistribution of cortactin, N-WASP and Arp2/3, and finally led to occurrence of finger-like protrusions of actin on cell surface to enhance cell metastasis. Compared with normal-chew diet (NCD) mice, the HFD group exhibited higher level of blood free fatty acid (FFA) and cholesterol (TC), developed larger xenograft LUAD tumors and enhanced tumor cell metastatic potential, which were accompanied by obvious sarcolemmal actin remodeling and were blocked by simultaneous CD36 knockdown in LUAD cells. Consistently, xenografted and tail vein-injected scramble-RNA-A549 cells but not CD36-shRNA-A549 in HFD mice formed metastatic LUAD tumors on the lung. CD36 inhibitor SSO significantly inhibited LUAD cell metastasis to the lung. Collectively, CD36 initiates Src signaling to promote LUAD cell proliferation and actin remodeling-involved metastasis under high-fat environment. Our study provides the new insights that CD36 is a valid target for LUAD therapy.

Downregulation of mTORC1 and Mcl-1 by lipid-oversupply contributes to islet β-cell apoptosis and dysfunction

Pancreatic β-cell apoptosis is a key feature of diabetes and can be induced by chronic exposure to saturated fatty acids (FAs). However, the underlying mechanisms remain poorly understood. We presently evaluated the role of Mcl-1 and mTOR in mice fed with high-fat-diet (HFD) and β-cells exposed to the overloaded palmitic acid (PA). Compared with normal-chow-diet (NCD)-fed mice, HFD group showed impaired glucose tolerance after two months. Along with the diabetes progression, pancreatic islets first became hypertrophic and then atrophic, the ratio of β-cell:α-cell increased in the islets of four months HFD-fed mice while decreased after six months. This process was accompanied by significantly increased β-cell apoptosis and AMPK activity, and decreased Mcl-1 expression and mTOR activity. Consistently, glucose-induced insulin secretion dropped. In terms of mechanism, PA with lipotoxic dose could activate AMPK, which in turn inhibited ERK-stimulated Mcl-1Thr163 phosphorylation. Meanwhile, AMPK blocked Akt activity to release Akt inhibition on GSK3β, followed by GSK3β-initiated Mcl-1Ser159 phosphorylation. The context of Mcl-1 phosphorylation finally led to its degradation by ubiquitination. Also, AMPK inhibited the activity of mTORC1, resulting in a lower level of Mcl-1. Suppression of mTORC1 activity and Mcl-1 expression positively related to β-cell failure. Alteration of Mcl-1 or mTOR expression rendered different tolerance of β-cell to different dose of PA. In conclusion, lipid oversupply-induced dual modulation of mTORC1 and Mcl-1 finally led to β-cell apoptosis and impaired insulin secretion. The study may help further understand the pathogenesis of β-cell dysfunction in case of dyslipidemia, and provide promising therapeutic targets for diabetes.

A novel simultaneous quantitative method for differential volatile components in herbs based on combined near-infrared and mid-infrared spectroscopy

A novel method based on GC-MS, near-infrared (NIR) and mid-infrared (MIR) spectroscopy combined with chemometrics was established to simultaneously analyze differential volatile components (DVCs) of herb samples. Herein, Florists Chrysanthemum was adopted as the representative sample. Through the introduction of Automatic data analysis workflow (AntDAS) and one-class partial least squares discriminant analysis (O-PLSDA) model, five kinds of terpenes and five kinds of alcohols were efficiently screened as DVCs. By using the selected NIR-MIR spectra sections combined with O-PLSDA, it could achieve the accurate identification of Florists Chrysanthemum from Chrysanthemum morifolium Ramat. What's more, since the selected spectra sections were closely related to the structural and content of DVCs, they could be further used for simultaneous quantitative analysis of DVCs combined with optimized variable-weighted least-squares support vector machine based on particle swarm optimization (PSO-VWLS-SVM). This method only adopted the same NIR-MIR sections for multiple component accurate quantification, highlighting its convenience.

Discrimination and Evaluation of Wild Paris Using UHPLC-QTOF-MS and FT-IR Spectroscopy in Combination with Multivariable Analysis

Genus Paris has numerous bioactive constituents such as steroid saponins, flavonoids, and polysaccharose which are responsible for antitumor, hemostatic, and anthelmintic, etc. In this study, ultrahigh performance liquid chromatography coupled to time-of-flight mass spectrometer (UHPLC-QTOF-MS) and Fourier transform infrared (FT-IR) spectroscopy in combination with multivariable analysis were employed to discriminate the different species of Paris including P. polyphylla var. yunnanensis (PPY), P. polyphylla var. alba, P. mairei (PM), P. vietnamensis, and P. polyphylla var. stenophylla. Partial least square discriminate analysis based on UHPLC, FT-IR, and midlevel data fusion was used to distinguish 43 batches of Paris. Chemical constituents of different species Paris were determined by UHPLC-QTOF-MS. The result indicated that midlevel data fusion had a good performance in the classification compared to a single analytical technology. A total of 47 compounds were identified in different species Paris. The similar results indicated that PM could be treated as a proposal substitute of PPY.

Effect of Bovine Colostrum Dietary Supplementation on Rabbit Meat Quality

Bovine colostrum (BC) is rich in nutrients, antimicrobial, and antioxidant factors; for these reasons, it has been used as supplement in animal nutrition. However, its possible effects on meat quality have not been studied yet. Thirty-nine New Zealand White rabbits (n = 13/group) were assigned to three groups and fed until slaughter with a commercial standard diet, control group (C), and C supplemented with 2.5% and 5% (w/w) of BC (BC-2.5 and BC-5 groups, respectively). After slaughtering, the effect of dietary supplementation on microbiological and chemical characteristics of the rabbit loins was evaluated at 48 h postmortem (D0) and after 3 (D3) and 8 (D8) days of refrigerated storage. Results showed no difference in the microbiological parameters. In the supplemented groups, TBARS and TVBN values were lower and higher than in the C group, respectively (p < 0.01), and their fatty-acid profile was increased in SFA and decreased in MUFA (p < 0.05). In conclusion, research must continue to examine in depth the possible effects of BC byproduct reuse in animal nutrition on meat quality (e.g., antioxidant power, and physical and sensory characteristics).

Advanced Lipidomics in the Modern Meat Industry: Quality Traceability, Processing Requirement, and Health Concerns

Over the latest decade, lipidomics has been extensively developed to give robust strength to the qualitative and quantitative information of lipid molecules derived from physiological animal tissues and edible muscle foods. The main lipidomics analytical platforms include mass spectrometry (MS) and nuclear magnetic resonance (NMR), where MS-based approaches [e.g., "shotgun lipidomics," ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), matrix-assisted laser desorption and ionization time-of-flight mass spectrometry (MALDI-TOF-MS)] have been widely used due to their good sensitivity, high availability, and accuracy in identification/quantification of basal lipid profiles in complex biological point of view. However, each method has limitations for lipid-species [e.g., fatty acids, triglycerides (TGs), and phospholipids (PLs)] analysis, and necessitating the extension of effective chemometric-resolved modeling and novel bioinformatic strategies toward molecular insights into alterations in the metabolic pathway. This review summarized the latest research advances regarding the application of advanced lipidomics in muscle origin and meat processing. We concisely highlighted and presented how the biosynthesis and decomposition of muscle-derived lipid molecules can be tailored by intrinsic characteristics during meat production (i.e., muscle type, breed, feeding, and freshness). Meanwhile, the consequences of some crucial hurdle techniques from both thermal/non-thermal perspectives were also discussed, as well as the role of salting/fermentation behaviors in postmortem lipid biotransformation. Finally, we proposed the inter-relationship between potential/putative lipid biomarkers in representative physiological muscles and processed meats, their metabolism accessibility, general nutritional uptake, and potency on human health.

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.

Mass spectrometry in food authentication and origin traceability

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

Chromatographic fingerprint application possibilities in food authentication

The aim of the study was to compare the effectiveness of the use of low-peak chromatographic fingerprints for the differentiation of various food products. Three groups of unprocessed products (mushrooms, hazelnuts and tomatoes), food preparations (bread, dried herbs and tomato juice) and alcoholic beverages (vodka and two types of blended whiskey) were examined. A commercial electronic nose based on ultrafast gas chromatography (acquisition time 90 s) with a flame ionization detector was used for the research. Static headspace was used as a green procedure to extract volatile compounds without modifying the food matrix. Individual extraction conditions were used for each product group. Similarities and differences between profiles were analyzed by simple Principal Components Analysis. The similarity rating was determined using the Euclidean distances. Global model was built for recognition chromatographic fingerprints of food samples. The best recognition results were 100% and 89% for tomato juices, spices, separate champignon elements and hazelnuts. On the other hand, the worst recognition results were 56% and 77% for breads and strong alcoholic beverages.

The Feasibility of Two Handheld Spectrometers for Meat Speciation Combined with Chemometric Methods and Its Application for Halal Certification

Handheld visible-near-infrared (Vis-NIR) and near-infrared (NIR) spectroscopy can be cost-effective, rapid, non-destructive and transportable techniques for identifying meat species and may be valuable for enforcement authorities, retail and consumers. In this study, a handheld Vis-NIR (400-1000 nm) and a handheld NIR (900-1700 nm) spectrometer were applied to discriminate halal meat species from pork (halal certification), as well as speciation of intact and ground lamb, beef, chicken and pork (160 meat samples). Several types of class modeling multivariate approaches were applied. The presented one-class classification (OCC) approach, especially with the Vis-NIR sensor (95-100% correct classification rate), was found to be suitable for the application of halal from non-halal meat-species discrimination. In a discriminant approach, using the Vis-NIR data and support vector machine (SVM) classification, the four meat species tested could be classified with accuracies of 93.4% and 94.7% for ground and intact meat, respectively, while with partial least-squares discriminant analysis (PLS-DA), classification accuracies were 87.4% (ground) and 88.6% (intact). Using the NIR sensor, total accuracies of the SVM models were 88.2% and 81.5% for ground and intact meats, respectively, and PLS-DA classification accuracies were 88.3% (ground) and 80% (intact). We conclude that the Vis-NIR sensor was most successful in the halal certification (OCC approaches) and speciation (discriminant approaches) for both intact and ground meat using SVM.

"Sfogliatella Riccia Napoletana": Realization of a Lard-Free and Palm Oil-Free Pastry

"Sfogliatella riccia napoletana" is a typical pastry from Naples (Italy), traditionally produced using lard. In the bakery industry, palm oil is widely used to replace lard in order to obtain products without cholesterol, but it is currently under discussion, which is mostly related to the sustainability of its cultivation. Therefore, in this work, lard was replaced with palm oil-free vegetable blends composed of sunflower oil, shea butter, and coconut oil in different percentages. Traditional pastries produced with lard and pastries produced with palm oil were used as controls. Moisture, aw, free acidity, peroxide value, fatty acids, total polar compounds, and global acceptability were determined in the obtained pastries. The results indicated that the use of a vegetable oil blend composed of 40% sunflower oil, 40% shea butter, and 20% coconut oil minimized the formation of oxidized compounds (peroxides and total polar compounds) during cooking and produced a product with a moisture content very similar to that of the traditional pastry that was appreciated by consumers.

Quali-quantitative monitoring of chemocatalytic cellulose conversion into lactic acid by FT-NIR spectroscopy

Chemocatalytic conversion of cellulose into lactic acid is a valuable alternative to simple sugar fermentation. Nevertheless, the procedures still need optimization to be translated to the industrial scale. Such translation would benefit by on-line monitoring of reaction parameters by fast, inexpensive, direct spectroscopic techniques. In this work, we propose the application of FT-NIR spectroscopy as a suitable analytical tool for monitoring the chemocatalytic conversion of cellulose into lactic acid. Comparison between different FT-NIR spectra at different reaction temperatures and times was exploited to qualitatively indicate the feasibility of the reaction. Besides, an FT-NIR prediction model was proposed for rapidly estimating the molar distribution of cellulose catalytic degradation components in the reaction mixtures. The calibration model was based on reference samples analysed by HPLC. The model was validated by an external validation set. Relevant statistical values of Ratio Performance to Deviations (RPD) referred to both calibration and external validation were obtained, thus demonstrating the potential of such analytical technique in process monitoring.

Discrimination between Fresh and Frozen-Thawed Fish Involved in Food Safety and Fraud Protection

This study aims to discriminate fresh fish from frozen/thawed by identification of the key metabolites that are altered during the freezing/thawing processing. Atlantic salmon (Salmo salar) and bullet tuna (Auxis rochei) were selected as they are representative of broad consumption, and susceptible to pathogen contamination. Atlantic salmon samples were subjected to the following regimes: −20 °C (24h) and −35 °C (15 h) freezing, then thawed respectively in the blast chiller and in the cold room and analyzed immediately or after 10 days; (2) bullet tuna samples were frozen at −18 °C and thawed after 15, 30 and 90 days. High resolution mass spectrometry based on untargeted metabolomic analyses and statistical data treatment confirmed significant variations in the quantity of certain metabolites: the amount of l-phenylalanine in salmon increased immediately after thawing while that of anserine decreased. The concentration of l-arginine and its metabolites was altered at the 10th day after thawing rendering them promising markers of salmon freezing/thawing. As regards bullet tuna, compounds resulting from lipid degradation (l-α-Glyceryl-phosphoryl-choline and N-methyl-ethanolamine phosphate) increased notably during the storage period. This approach could be used to reveal common fraudulent incidents such as deliberate replacement of fresh fish with frozen/thawed, with food safety risks as the primary implication.

The Use of Stable Isotope Ratio Analysis to Trace European Sea Bass (D. labrax) Originating from Different Farming Systems

Simple Summary

European sea bass is one of the most economically important fish species in the Mediterranean area. The potential effects of farming systems on the final quality of this product and the recent popular demand for labels to certify the animal rearing origin, which is increasingly used as a marketing tool, have raised the use of analytical techniques that make it possible to differentiate this fish product according to the rearing farming system and authenticate their geographical origin. The aim of this study was to determine whether isotopic ratio mass spectrometry (IRMS) can discriminate farmed European sea bass according to different farming systems (concrete tank inland, sea cages, and extensive methods in valleys or salt works) and geographic origins (different locations scattered throughout Italy). The results of this study showed the viability of δ¹³C and δ¹⁵N to discriminate cultured sea bass from different farming systems (extensive vs. intensive) reared at different geographical sites in Italy. Meanwhile, the measurement of δ¹⁸O and δ²H made it possible to distinguish the geographical origin of the sea bass farmed extensively and intensively (in cages).

Abstract

This study aimed to determine whether isotopic ratio mass spectrometry (IRMS) can discriminate farmed European sea bass according to different farming systems and geographic origins. Dicentrarchus labrax of commercial size from three different rearing systems (concrete tank inland, sea cages, and extensive methods in valleys or salt works) were collected at the trading period (autumn–winter). For each farming type, different locations spread over Italy were monitored. Once the fish were harvested, the muscle and feed were sampled. For both muscle and feed, δ¹³C and δ¹⁵N were measured by continuous flow elemental analyzer isotope ratio mass spectrometry (CF-EA-IRMS) with the goal of discriminating samples based on the rearing system. Additional δ²H and δ¹⁸O measurements of fish samples were performed by continuous flow total combustion elemental analyzer isotope ratio mass spectrometry (CF-TC/EA-IRMS) to track the geographical origin. The measurements of δ¹³C and δ¹⁵N made it possible to discriminate cultured sea bass from different farming systems (extensive vs. intensive) reared at different geographical sites in Italy. Additional information was obtained from δ¹⁸O and δ²H, which enabled the geographical areas of origin of the sea bass farmed extensively and intensively (in cages) to be distinguished.

Nondestructive monitoring of polyphenols and caffeine during green tea processing using Vis-NIR spectroscopy

Increasing consumption of green tea is attributed to the beneficial effects of its constituents, especially polyphenols, on human health, which can be varied during leaf processing. Processing technology has the most important effect on green tea quality. This study investigated the system dynamics of eight catechins, gallic acid, and caffeine in the processing of two varieties of tea, from fresh leaves to finished tea. It was found that complex biochemical changes can occur through hydrolysis under different humidity and heating conditions during the tea processing. This process had a significant effect on catechin composition in the finished tea. The potential application of visible and near-infrared (Vis-NIR) spectroscopy for fast monitoring polyphenol and caffeine contents in tea leaves during the processing procedure has been investigated. It was found that a combination of PCA (principal component analysis) and Vis-NIR spectroscopy can successfully classify the two varieties of tea samples and the five tea processing procedures, while quantitative determination of the constituents was realized by combined regression analysis and Vis-NIR spectra. Furthermore, successive projections algorithm (SPA) was proposed to extract and optimize spectral variables that reflected the molecular characteristics of the constituents for the development of determination models. Modeling results showed that the models had good predictability and robustness based on the extracted spectral characteristics. The coefficients of determination for all calibration sets and prediction sets were higher than 0.862 and 0.834, respectively, which indicated high capability of Vis-NIR spectroscopy for the determination of the constituents during the leaf processing. Meanwhile, this analytical method could quickly monitor quality characteristics and provide feedback for real-time controlling of tea processing machines. Furthermore, the study on complex biochemical changes that occurred during the tea processing would provide a theoretical basis for improving the content of quality components and effective controlling processes.

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.

Lipid oversupply induces CD36 sarcolemmal translocation via dual modulation of PKCζ and TBC1D1: an early event prior to insulin resistance

Lipid oversupply may induce CD36 sarcolemmal translocation to facilitate fatty acid transport, which in turn causes dyslipidemia and type 2 diabetes. However, the underlying mechanisms of CD36 redistribution are still yet to be unraveled.

Methods: High fat diet fed mice and palmitate/oleic acid-treated L6 cells were used to investigate the initial events of subcellular CD36 recycling prior to insulin resistance. The regulation of CD36 sarcolemmal translocation by lipid oversupply was assessed by insulin tolerance test (ITT), oral glucose tolerance test (OGTT), glucose/fatty acid uptake assay, surface CD36 and GLUT4 detection, and ELISA assays. To elucidate the underlying mechanisms, specific gene knockout, gene overexpression and/or gene inhibition were employed, followed by Western blot, co-immunoprecipitation, immunostaining, and kinase activity assay.

Results: Upon lipid/fatty acid overload, PKCζ activity and TBC1D1 phosphorylation were enhanced along with increased sarcolemmal CD36. The inhibition of PKCζ or TBC1D1 was shown to block fatty acid-induced CD36 translocation and was synergistic in impairing CD36 redistribution. Mechanically, we revealed that AMPK was located upstream of PKCζ to control its activity whereas Rac1 facilitated PKCζ translocation to the dorsal surface of the cell to cause actin remodeling. Furthermore, AMPK phosphorylated TBC1D1 to release retained cytosolic CD36. The activated PKCζ and phosphorylated TBC1D1 resulted in a positive feedback regulation of CD36 sarcolemmal translocation.

Conclusion: Collectively, our study demonstrated exclusively that lipid oversupply induced CD36 sarcolemmal translocation via dual modulation of PKCζ and TBC1D1, which was as an early event prior to insulin resistance. The acquired data may provide potential therapy targets to prevent lipid oversupply-induced insulin resistance.

Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing

In the last decade, the use of multivariate statistical techniques developed for analytical chemistry has been adopted widely in food science and technology. Usually, chemometrics is applied when there is a large and complex dataset, in terms of sample numbers, types, and responses. The results are used for authentication of geographical origin, farming systems, or even to trace adulteration of high value-added commodities. In this article, we provide an extensive practical and pragmatic overview on the use of the main chemometrics tools in food science studies, focusing on the effects of process variables on chemical composition and on the authentication of foods based on chemical markers. Pattern recognition methods, such as principal component analysis and cluster analysis, have been used to associate the level of bioactive components with in vitro functional properties, although supervised multivariate statistical methods have been used for authentication purposes. Overall, chemometrics is a useful aid when extensive, multiple, and complex real-life problems need to be addressed in a multifactorial and holistic context. Undoubtedly, chemometrics should be used by governmental bodies and industries that need to monitor the quality of foods, raw materials, and processes when high-dimensional data are available. We have focused on practical examples and listed the pros and cons of the most used chemometric tools to help the user choose the most appropriate statistical approach for analysis of complex and multivariate data.

Protected Designation of Origin (PDO), Protected Geographical Indication (PGI) and Traditional Speciality Guaranteed (TSG): A bibiliometric analysis

Despite the importance of the literature on food quality labels in the European Union (PDO, PGI and TSG), our search did not find any review joining the various research topics on this subject. This study aims therefore to consolidate the state of academic research in this field, and so the methodological option was to elaborate a bibliometric analysis resorting to the term co-occurrence technique. Analysis was made of 501 articles on the ISI Web of Science database, covering publications up to 2016. The results of the bibliometric analysis allowed identification of four clusters: "Protected Geographical Indication", "Certification of Olive Oil and Cultivars", "Certification of Cheese and Milk" and "Certification and Chemical Composition". Unlike the other clusters, where the PDO label predominates, the "Protected Geographical Indication" cluster covers the study of PGI products, highlighting analysis of consumer behaviour in relation to this type of product. The focus of studies in the "Certification of Olive Oil and Cultivars" cluster and the "Certification of Cheese and Milk" cluster is the development of authentication methods for certified traditional products. In the "Certification and Chemical Composition" cluster, standing out is analysis of the profiles of fatty acids present in this type of product.

Geographical identification of saffron (Crocus sativus L.) by linear discriminant analysis applied to the UV-visible spectra of aqueous extracts

We attempted geographical classification of saffron using UV-visible spectroscopy, conventionally adopted for quality grading according to the ISO Normative 3632. We investigated 81 saffron samples produced in L'Aquila, Città della Pieve, Cascia, and Sardinia (Italy) and commercial products purchased in various supermarkets. Exploratory principal component analysis applied to the UV-vis spectra of saffron aqueous extracts revealed a clear differentiation of the samples belonging to different quality categories, but a poor separation according to the geographical origin of the spices. On the other hand, linear discriminant analysis based on 8 selected absorbance values, concentrated near 279, 305 and 328nm, allowed a good distinction of the spices coming from different sites. Under severe validation conditions (30% and 50% of saffron samples in the evaluation set), correct predictions were 85 and 83%, respectively.