Virtualization and digital twins of the food supply chain for enhanced food safety

Meeting food safety requirements without jeopardizing quality attributes or sustainability involves adopting a holistic perspective of food products, their manufacturing processes and their storage and distribution practices. The virtualization of the food supply chain offers opportunities to evaluate, simulate, and predict challenges and mishaps potentially contributing to present and future food safety risks. Food systems virtualization poses several requirements: (1) a comprehensive framework composed of instrumental, digital, and computational methods to evaluate internal and external factors that impact food safety; (2) nondestructive and real-time sensing methods, such as spectroscopic-based techniques, to facilitate mapping and tracking food safety and quality indicators; (3) a dynamic platform supported by the Internet of Things (IoT) interconnectivity to integrate information, perform online data analysis and exchange information on product history, outbreaks, exposure to risky situations, etc.; and (4) comprehensive and complementary mathematical modeling techniques (including but not limited to chemical reactions and microbial inactivation and growth kinetics) based on extensive data sets to make realistic simulations and predictions possible. Despite current limitations in data integration and technical skills for virtualization to reach its full potential, its increasing adoption as an interactive and dynamic tool for food systems evaluation can improve resource utilization and rational design of products, processes and logistics for enhanced food safety. Virtualization offers affordable and reliable options to assist stakeholders in decision-making and personnel training. This chapter focuses on definitions and requirements for developing and applying virtual food systems, including digital twins, and their role and future trends in enhancing food safety.

Special Issue: Novel Approaches for the Analytical Evaluation of Food Quality and Authenticity

Verifying the quality and authenticity of agri-food products is essential to guaranteeing adequate food safety for consumers [...].

Recent Advances in Electrochemical Enzyme-Based Biosensors for Food and Beverage Analysis

Food analysis and control are crucial aspects in food research and production in order to ensure quality and safety of food products. Electrochemical biosensors based on enzymes as the bioreceptors are emerging as promising tools for food analysis because of their high selectivity and sensitivity, short analysis time, and high-cost effectiveness in comparison to conventional methods. This review provides the readers with an overview of various electrochemical enzyme-based biosensors in food analysis, focusing on enzymes used for different applications in the analysis of sugars, alcohols, amino acids and amines, and organic acids, as well as mycotoxins and chemical contaminants. In addition, strategies to improve the performance of enzyme-based biosensors that have been reported over the last five years will be discussed. The challenges and future outlooks for the food sector are also presented.

Bio-phenols determination in olive oils: Recent mass spectrometry approaches

Extra virgin olive oil (EVOO) is largely used in Mediterranean diet, and it is also worldwide apprised not only for its organoleptic properties but also for its healthy effects mainly attributed to the presence of several naturally occurring phenolic and polyphenolic compounds (bio-phenols). These compounds are characterized by the presence of multiple phenolic groups in more or less complex structures. Their content is fundamental in defining the healthy qualities of EVOO and consequently the analytical methods for their characterization and quantification are of current interest. Traditionally their determination has been conducted using a colorimetric assay based on the reaction of Folin-Ciocalteu (FC) reagent with the functional hydroxy groups of phenolic compounds. Identification and quantification of the bio-phenols in olive oils requires certainly more performing analytical methods. Chromatographic separation is now commonly achieved by HPLC, coupled with spectrometric devices as UV, FID, and MS. This last approach constitutes an actual cutting-edge application for bio-phenol determination in complex matrices as olive oils, mostly on the light of the development of mass analyzers and the achievement of high resolution and accurate mass measurement in more affordable instrument configurations. After a short survey of some rugged techniques used for bio-phenols determination, in this review have been described the most recent mass spectrometry-based methods, adopted for the analysis of the bio-phenols in EVOOs. In particular, the sample handling and the results of HPLC coupled with low- and high-resolution MS and MS/MS analyzers, of ion mobility mass spectrometry and ambient mass spectrometry have been reported and discussed.

Non-invasive authentication of mail packages using nuclear quadrupole resonance spectroscopy

The international postal network is one of the most widely used methods for correspondence throughout the world. Most postal traffic across the globe consists of legitimate interpersonal, business-consumer, and business-business communications. However, the global postal system is also utilized for criminal activity. In particular, it is often utilized to ship and distribute contraband, including illegal psychoactive drugs such as fentanyl and heroin, to consumers. Existing technological solutions are capable of identifying synthetic opioids and other illegal drugs within packages, but are accompanied by several disadvantages that make them unsuitable for large-scale authentication of international mail traffic. This paper presents a novel method for non-invasive authentication of mail packages that overcomes these challenges. The approach uses nuclear quadrupole resonance (NQR) spectroscopy to detect and quantify the presence of known active pharmaceutical ingredients (APIs) within the package. It has been experimentally demonstrated using a bench top prototype. Test results from a variety of package types demonstrate the effectiveness of the proposed authentication approach.

Application of Mass Spectrometry for Determining the Geographic Production Area of Wagyu Beef

Japanese Black cattle (Japanese Wagyu) beef is attracting attention for its aroma and marbling, and its handling is increasing worldwide. Here, we focused on the origin discrimination of Wagyu beef and analyzed the nutritional components of Japanese Wagyu (produced in multiple prefectures of Japan), Hybrid Wagyu (a cross between Angus and Wagyu cattle born in Australia and transported to Japan), and Australian Wagyu beef using mass spectrometry (MS). Triple-quadrupole liquid chromatography-MS was used to clarify the molecular species of lipids in Wagyu beef. Fourteen classes of lipids were separated, and 128 different triacylglycerides (TGs) were detected. A simple comparative analysis of these TGs using high-performance liquid chromatography revealed significantly higher levels of triolein (C18:1/C18:1/C18:1; abbreviated OOO) and C18:1/C18:1/C16:1 (OOPo) in Japanese Wagyu. Wagyu elements beef were comprehensively analyzed using inductively coupled plasma (ICP)-MS and ICP-optical emission spectrometry. We found significant differences in the rubidium, cesium, and lithium levels of Japanese and Australian Wagyu beef. On comparing metabolites using gas chromatography-MS, we identified significant differences in the levels of amino acids and other components of the Japanese and Australian Wagyu beef. These results suggest the possibility of determining the origin of Wagyu cattle breeds using MS and genetic discrimination.

Changes in Content of Bioactive Compounds and Antioxidant Activity Induced in Needles of Different Half-Sib Families of Norway Spruce (Picea abies (L.) H. Karst) by Seed Treatment with Cold Plasma

In order to ensure sufficient food resources for a constantly growing human population, new technologies (e.g., cold plasma technologies) are being developed for increasing the germination and seedling growth without negative effects on the environment. Pinaceae species are considered a natural source of antioxidant compounds and are valued for their pharmaceutical and nutraceutical properties. In this study, the seeds of seven different Norway spruce half-sib families were processed for one or two minutes with cold plasma (CP) using dielectric barrier discharge (DBD) plasma equipment. At the end of the second vegetation season, the total flavonoid content (TFC), DPPH (2,2- diphenyl-1-picryl-hydrazyl-hydrate), and ABTS (2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid)) antioxidant activity, and the amounts of six organic acids (folic, malic, citric, oxalic, succinic, and ascorbic) were determined in the needles of different half-sib families of Norway spruce seedlings. The results show that the TFC, antioxidant activity, and amounts of organic acids in the seedling needles depended on both the treatment duration and the genetic family. The strongest positive effect on the TFC was determined in the seedlings of the 477, 599, and 541 half-sib families after seed treatment with CP for 1 min (CP1). The TFC in these families increased from 118.06 mg g-1 to 312.6 mg g-1 compared to the control. Moreover, seed treatment with CP1 resulted in the strongest increase in the antioxidant activity of the needles of the 541 half-sib family seedlings; the antioxidant activity, determined by DPPH and ABTS tests, increased by 30 and 23%, respectively, compared to the control. The obtained results indicate that the CP effect on the amount of organic acids in the needles was dependent on the half-sib family. It was determined that treatment with CP1 increased the amount of five organic acids in the needles of the 541 half-sib family seedlings. The presented results show future possibilities for using cold plasma seed treatment in the food and pharmacy industries.

Foodomics for agroecology: Differentiation of volatile profile in mint (Mentha × gracilis Sole) from permaculture, organic and conventional agricultural systems using HS-SPME/GC-MS

In the present study, foodomics approach was employed to investigate changes in the metabolism from the volatile terpenoids profile of mint(Mentha × gracillis Sole)from conventional, organic and permaculture (a type of agroecological agriculture system) farms using headspace solid-phase microextraction (HS-SPME) associated to gas chromatography coupled to mass spectrometry (GC-MS) and chemometric tools. The discrimination among the three types of mint was successfully achieved and demonstrated evidence of ecological interaction impact in the food metabolism. The agroecological mint presented as differential compounds: α-terpineol, bornyl formate, cis-carvyl propionate, cis-carveol, camphor, dihydrocarvyl acetate, dihydrocarveol, karahanaenone, nonanal, 3-octyl acetate, and trans-3-hexenyl-2 methylbutyrate. While organic and conventional mint presented as differential compounds: α-cedrene, β -pinene, γ-muurolene, δ-cadinene, germacrene, terpinolene, and elemol. The majority of differential metabolites from agroecological mint are oxygenated monoterpenes, which have more intense flavor and biological activities than hydrocarbons monoterpenes and sesquiterpenes found in organic and conventional mint. Furthermore, the discrimination between organic and conventional mint was effectively performed, which demonstrated different terpenoid profiles though without implying benefits for one or another agriculture system.

A Review on the Commonly Used Methods for Analysis of Physical Properties of Food Materials

The chemical composition of any food material can be analyzed well by employing various analytical techniques. The physical properties of food are no less important than chemical composition as results obtained from authentic measurement data are able to provide detailed information about the food. Several techniques have been used for years for this purpose but most of them are destructive in nature. The aim of this present study is to identify the emerging techniques that have been used by different researchers for the analysis of the physical characteristics of food. It is highly recommended to practice novel methods as these are non-destructive, extremely sophisticated, and provide results closer to true quantitative values. The physical properties are classified into different groups based on their characteristics. The concise view of conventional techniques mostly used to analyze food material are documented in this work.

Chip-based separation of organic and inorganic anions and multivariate analysis of wines according to grape varieties

This report describes the use of electrophoresis microchips integrated with contactless conductivity detection for the determination of organic acids and inorganic anions in wine samples and the subsequent classification based on the grape varieties. The best separation was achieved using a buffer composed of 30 mmol L^-1 2-(N-morpholino)ethanesulfonic acid, 15 mmol L^-1l-histidine and 0.05 mmol L^-1 cetyltrimethylammonium bromide (pH 5.8), allowing the determination of chloride, nitrate, sulfate, oxalate, tartrate, maleate, succinate, citrate, acetate, lactate, pyroglutamate and phosphate within ca. 100 s. The relative standard deviations obtained for the migration times were lower than 2%, while the obtained values for peak areas ranged from 2.5 to 8.4%. The limits of detection achieved for all compounds ranged between 3.0 and 12.6 μmol L^-1. A total of 18 wines from Brazil and Chile were successfully investigated, including red, white and rosé, and the anionic species were quantified with recovery values between 92 and 117%. A statistical difference has not been observed between the data obtained by using electrophoresis microchips integrated with contactless conductivity detection (ME-C⁴D) and capillary electrophoresis with ultra-violet detection (CE-UV) and thus the results from newly developed method is validated. Finally, similarities among the anionic profile of wines were investigated by using a multivariate approach, and it was possible to discriminate samples mainly by grapes varieties. Furthermore, the proposed methodology has provided instrumental simplicity and good analytical performance, demonstrating to be useful for routine quality control of wines.

Recent advances in NMR-based metabolomics of alcoholic beverages

Alcoholic beverages have a complex chemistry that can be influenced by their alcoholic content, origin, fermentation process, additives, and contaminants. The complex composition of these beverages leave them susceptible to fraud, potentially compromising their authenticity, quality, and market value, thus increasing risks to consumers' health. In recent years, intensive studies have been carried out on alcoholic beverages using different analytical techniques to evaluate the authenticity, variety, age, and fermentation processes that were used. Among these techniques, NMR-based metabolomics holds promise in profiling the chemistry of alcoholic beverages, especially in Asia where metabolomics studies on alcoholic beverages remain limited.

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.

Selected Instrumental Techniques Applied in Food and Feed: Quality, Safety and Adulteration Analysis

This review presents an overall glance at selected instrumental analytical techniques and methods used in food analysis, focusing on their primary food science research applications. The methods described represent approaches that have already been developed or are currently being implemented in our laboratories. Some techniques are widespread and well known and hence we will focus only in very specific examples, whilst the relatively less common techniques applied in food science are covered in a wider fashion. We made a particular emphasis on the works published on this topic in the last five years. When appropriate, we referred the reader to specialized reports highlighting each technique's principle and focused on said technologies' applications in the food analysis field. Each example forwarded will consider the advantages and limitations of the application. Certain study cases will typify that several of the techniques mentioned are used simultaneously to resolve an issue, support novel data, or gather further information from the food sample.

FoodOmicsGR_RI. A Consortium for Comprehensive Molecular Characterisation of Food Products

The national infrastructure FoodOmicsGR_RI coordinates research efforts from eight Greek Universities and Research Centers in a network aiming to support research and development (R&D) in the agri-food sector. The goals of FoodOmicsGR_RI are the comprehensive in-depth characterization of foods using cutting-edge omics technologies and the support of dietary/nutrition studies. The network combines strong omics expertise with expert field/application scientists (food/nutrition sciences, plant protection/plant growth, animal husbandry, apiculture and 10 other fields). Human resources involve more than 60 staff scientists and more than 30 recruits. State-of-the-art technologies and instrumentation is available for the comprehensive mapping of the food composition and available genetic resources, the assessment of the distinct value of foods, and the effect of nutritional intervention on the metabolic profile of biological samples of consumers and animal models. The consortium has the know-how and expertise that covers the breadth of the Greek agri-food sector. Metabolomics teams have developed and implemented a variety of methods for profiling and quantitative analysis. The implementation plan includes the following research axes: development of a detailed database of Greek food constituents; exploitation of "omics" technologies to assess domestic agricultural biodiversity aiding authenticity-traceability control/certification of geographical/genetic origin; highlighting unique characteristics of Greek products with an emphasis on quality, sustainability and food safety; assessment of diet's effect on health and well-being; creating added value from agri-food waste. FoodOmicsGR_RI develops new tools to evaluate the nutritional value of Greek foods, study the role of traditional foods and Greek functional foods in the prevention of chronic diseases and support health claims of Greek traditional products. FoodOmicsGR_RI provides access to state-of-the-art facilities, unique, well-characterised sample sets, obtained from precision/experimental farming/breeding (milk, honey, meat, olive oil and so forth) along with more than 20 complementary scientific disciplines. FoodOmicsGR_RI is open for collaboration with national and international stakeholders.

Classification of the botanical and geographical origins of Chinese honey based on 1H NMR profile with chemometrics

In this paper, we report a newly developed non-target ¹H NMR detection associated with chemometrics method to classify the botanical and geographical origins of the monofloral Chinese honey. ¹H NMR tests of 218 monofloral honey samples of 8 classes (Acacia, Jujube, Linden, Longan, Orange, Rape, Sunflower, Vitex) collected in 2017-2019 across China were conducted under the optimal sample preparation conditions and NMR acquisition parameters. The whole profiles of NMR spectra instead of individual or partial signals from specific components were processed and extracted, then fed to SIMCA-P to classify the botanical and geographical origins through non-target statistical analysis. For the botanical origins, most of them could be classified clearly according to Principal Component Analysis (PCA) with both R² and Q² close to 1. Orthogonal Partial Least Squares Discrimination Analysis (OPLS-DA) model could classify the honey floral types successfully with R²Y and Q² greater than 0.85. It is found that the integral bin for data extraction has no obvious influence on the classification. For the geographical origins, the classification at different geographical levels (providence and town) could be successfully distinguished by OPLS-DA model. The promising preliminary results with the geographical classification at 40 km level unambiguously demonstrate the application of this NMR-based multi-species non-targeted method for the honey authenticity. Successful result is obtained on a pilot prediction of the geographical classification. Comparing with the methods based on other techniques, the advantages of this reported one are less sample amount needed, simple preparation, short test time, and non-targeted multi-species detection.

First-principles identification of C-methyl-scyllo-inositol (mytilitol) - A new species-specific metabolite indicator of geographic origin for marine bivalve molluscs (Mytilus and Ruditapes spp.)

This study presents a level-1 identification of the seven carbon (7-C) sugar C-methyl-scyllo-inositol (mytilitol) in mussels and clams (Mytilus and Ruditapes spp., respectively) purchased in Denmark and Italy. For each sample, the hydrophilic extract of the soft tissue was analyzed by proton nuclear magnetic resonance (¹H NMR) spectroscopy using a 600 MHz NMR spectrometer. A first tentative identification of mytilitol was carried out by computing a statistical total correlation spectroscopy (STOCY) analysis of the ¹H NMR spectra, followed by a level-1 identification based on first-principles methods including chemical synthesis, structure elucidation and standard-addition experiments. Mytilitol was quantified in the ¹H NMR spectra and its average relative concentration turned out to be significantly lower in clams than in mussels (p-value < 0.001), with Danish mussels having the highest mytilitol concentration. Principal component analysis (PCA) of the NMR dataset brought further evidence to a species-specific and geographic-dependent content of mytilitol in mussels and clams.

A Review on Recent Advances in the Applications of Boron-Doped Diamond Electrochemical Sensors in Food Analysis

The usage of boron-doped diamond (BDD) material has found to be very attractive in modern electroanalytical methods and received massive consideration as perspective electrochemical sensor due to its outstanding (electro)chemical properties. These generally known facilities include large potential window, low background currents, ability to withstand extreme potentials and strong tendency to resist fouling compared to conventional carbon-based electrodes. As evidence of superiority of this material, couple of reviews describing the overview of various applications of BDD electrodes in the field of analytical and material chemistry has been reported in scientific literature during last decade. However, herein proposed review predominantly focuses on the most recent developments (from 2009 to 2020) dealing with the application of BDD as an advanced and environmental-friendly sensor platform in food analysis. The main method characteristics of analysis of various organic food components with different chemical properties, including additives, flavor and aroma components, phenolic compounds, flavonoids and pesticides in food matrices are described in more details. The importance of BDD surface termination, presence of sp² content and boron doping level on electrochemical sensing is discussed. Apart from this, a special attention is paid to the evaluation of main analytical characteristics of the BDD electrochemical sensor in single- and multi-analyte detection mode in food analysis. The recent achievements in the utilizing of BDD electrodes in amperometric detection coupled to flow injection analysis, batch injection analysis, and high-performance liquid chromatography are also commented. Moreover, actual trends in sample preparation techniques prior to electrochemical sensing in food analysis are referred.

Application of High Resolution Mass Spectrometric methods coupled with chemometric techniques in olive oil authenticity studies - A review

Extra Virgin Olive Oil (EVOO), the emblematic food of the Mediterranean diet, is recognized for its nutritional value and beneficial health effects. The main authenticity issues associated with EVOO's quality involve the organoleptic properties (EVOO or defective), mislabeling of production type (organic or conventional), variety and geographical origin, and adulteration. Currently, there is an emerging need to characterize EVOOs and evaluate their genuineness. This can be achieved through the development of analytical methodologies applying advanced "omics" technologies and the investigation of EVOOs chemical fingerprints. The objective of this review is to demonstrate the analytical performance of High Resolution Mass Spectrometry (HRMS) in the field of food authenticity assessment, allowing the determination of a wide range of food constituents with exceptional identification capabilities. HRMS-based workflows used for the investigation of critical olive oil authenticity issues are presented and discussed, combined with advanced data processing, comprehensive data mining and chemometric tools. The use of unsupervised classification tools, such as Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA), as well as supervised classification techniques, including Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Partial Least Square Discriminant Analysis (PLS-DA), Orthogonal Projection to Latent Structure-Discriminant Analysis (OPLS-DA), Counter Propagation Artificial Neural Networks (CP-ANNs), Self-Organizing Maps (SOMs) and Random Forest (RF) is summarized. The combination of HRMS methodologies with chemometrics improves the quality and reliability of the conclusions from experimental data (profile or fingerprints), provides valuable information suggesting potential authenticity markers and is widely applied in food authenticity studies.

Authentication of Greek PDO Kalamata Table Olives: A Novel Non-Target High Resolution Mass Spectrometric Approach

Food science continually requires the development of novel analytical methods to prevent fraudulent actions and guarantee food authenticity. Greek table olives, one of the most emblematic and valuable Greek national products, are often subjected to economically motivated fraud. In this work, a novel ultra-high-performance liquid chromatography–quadrupole time of flight tandem mass spectrometry (UHPLC-QTOF-MS) analytical method was developed to detect the mislabeling of Greek PDO Kalamata table olives, and thereby establish their authenticity. A non-targeted screening workflow was applied, coupled to advanced chemometric techniques such as Principal Component Analysis (PCA) and Partial Least Square Discriminant Analysis (PLS-DA) in order to fingerprint and accurately discriminate PDO Greek Kalamata olives from Kalamata (or Kalamon) type olives from Egypt and Chile. The method performance was evaluated using a target set of phenolic compounds and several validation parameters were calculated. Overall, 65 table olive samples from Greece, Egypt, and Chile were analyzed and processed for the model development and its accuracy was validated. The robustness of the chemometric model was tested using 11 Greek Kalamon olive samples that were produced during the following crop year, 2018, and they were successfully classified as Greek Kalamon olives from Kalamata. Twenty-six characteristic authenticity markers were indicated to be responsible for the discrimination of Kalamon olives of different geographical origins.

Multi-platform metabolomic approach to discriminate ripening markers of black truffles (Tuber melanosporum)

Black truffle is characterized by a black ascocarp and white veins. This hypogeous fruit body is known for its aroma. Understanding metabolic variation during ripening can shed light on truffle biology. In this work, the comprehensive polar metabolome and the volatile organic compounds of T. melanosporum were studied at different ripening stages by means of a metabolomic approach using GC-MS. Multivariate statistical data analysis indicated that the metabolic profile changed during ripening and that the metabolites that mostly discriminated truffles in the early ripening stages belonged to the classes of carbohydrates, while free fatty acids and amino acids, among which precursors of VOCs, characterized the late stages of ripening. Principal component analysis of the volatilome indicated that dimethylsulfide and dimethyldisulfide characterized most of the samples collected in December-January, while 1-octen-3-ol samples collected in February-March.

Qualitative analysis of phospholipids and their oxidised derivatives - used techniques and examples of their applications related to lipidomic research and food analysis

Phospholipids (PLs) are important biomolecules that not only constitute structural building blocks and scaffolds of cell and organelle membranes but also play a vital role in cell biochemistry and physiology. Moreover, dietary exogenous PLs are characterised by high nutritional value and other beneficial health effects, which are confirmed by numerous epidemiological studies. For this reason, PLs are of high interest in lipidomics that targets both the analysis of membrane lipid distribution as well as correlates composition of lipids with their effects on functioning of cells, tissues and organs. Lipidomic assessments follow-up the changes occurring in living organisms, such as free radical attack and oxidative modifications of the polyunsaturated fatty acids (PUFAs) build in PL structures. Oxidised PLs (oxPLs) can be generated exogenously and supplied to organisms with processed food or formed endogenously as a result of oxidative stress. Cellular and tissue oxPLs can be a biomarker predictive of the development of numerous diseases such as atherosclerosis or neuroinflammation. Therefore, suitable high-throughput analytical techniques, which enable comprehensive analysis of PL molecules in terms of the structure of hydrophilic group, fatty acid (FA) composition and oxidative modifications of FAs, have been currently developed. This review addresses all aspects of PL analysis, including lipid isolation, chromatographic separation of PL classes and species, as well as their detection. The bioinformatic tools that enable handling of a large amount of data generated during lipidomic analysis are also discussed. In addition, imaging techniques such as confocal microscopy and mass spectrometry imaging for analysis of cellular lipid maps, including membrane PLs, are presented.

Stress and defense responses in plant secondary metabolites production

In the growth condition(s) of plants, numerous secondary metabolites (SMs) are produced by them to serve variety of cellular functions essential for physiological processes, and recent increasing evidences have implicated stress and defense response signaling in their production. The type and concentration(s) of secondary molecule(s) produced by a plant are determined by the species, genotype, physiology, developmental stage and environmental factors during growth. This suggests the physiological adaptive responses employed by various plant taxonomic groups in coping with the stress and defensive stimuli. The past recent decades had witnessed renewed interest to study abiotic factors that influence secondary metabolism during in vitro and in vivo growth of plants. Application of molecular biology tools and techniques are facilitating understanding the signaling processes and pathways involved in the SMs production at subcellular, cellular, organ and whole plant systems during in vivo and in vitro growth, with application in metabolic engineering of biosynthetic pathways intermediates.

Nontargeted Detection Methods for Food Safety and Integrity

Nontargeted workflows for chemical hazard analyses are highly desirable in the food safety and integrity fields to ensure human health. Two different analytical strategies, nontargeted metabolomics and chemical database filtering, can be used to screen unknown contaminants in food matrices. Sufficient mass and chromatographic resolutions are necessary for the detection of compounds and subsequent componentization and interpretation of candidate ions. Analytical chemistry–based technologies, including gas chromatography–mass spectrometry (GC-MS), liquid chromatography–mass spectrometry (LC-MS), nuclear magnetic resonance (NMR), and capillary electrophoresis–mass spectrometry (CE-MS), combined with chemometrics analysis are being used to generate molecular formulas of compounds of interest. The construction of a chemical database plays a crucial role in nontargeted detection. This review provides an overview of the current sample preparation, analytical chemistry–based techniques, and data analysis as well as the limitations and challenges of nontargeted detection methods for analyzing complex food matrices. Improvements in sample preparation and analytical platforms may enhance the relevance of food authenticity, quality, and safety.

High-throughput foodomics strategy for screening flavor components in dairy products using multiple mass spectrometry

A reliable Fisher discriminant model was established which was able to analyze the aroma component in milk, dairy products, flavors and fragrance, and applied on its variety identification. Foodomics was applied on screening of flavor components in 1093 dairy products and flavor samples in this study. Stepwise discrimination was used to screen the components of the dairy products and flavor samples that had a significant effect on the classification results, and discriminant function analysis. Then nine principal components were used for established the Fisher discriminant model. The three-dimensional coordinate distance of the sample was calculated and as the gist. The result showed that samples and flavors were distributed in eight different sites. The separation and clustering effects are better. The objective of the present study was to effectively determine whether or not flavors were added to dairy products.

Foodomics for human health: current status and perspectives

INTRODUCTION

In the post-genomic era, the opportunity to combine and integrate cutting-edge analytical platforms and data processing systems allowed the birth of foodomics, 'a discipline that studies the Food and Nutrition domains through the application of advanced omics technologies to improve consumer's well-being, health, and confidence'. Since then, this discipline has rapidly evolved and researchers are now facing the daunting tasks to meet consumers' needs in terms of food traceability, sustainability, quality, safety and integrity. Most importantly, today it is imperative to provide solid evidence of the mechanisms through which food can promote human health and well-being. Areas covered: In this review, the complex relationships connecting food, nutrition and human health will be discussed, with emphasis on the relapses for the development of functional foods and nutraceuticals, personalized nutrition approaches, and the study of the interplay among gut microbiota, diet and health/diseases. Expert commentary: Evidence has been provided supporting the role of various omic platforms in studying the health-promoting effects of food and customized dietary interventions. However, although associated to major analytical challenges, only the proper integration of multi-omics studies and the implementation of bioinformatics tools and databases will help translate findings from clinical practice into effective personalized treatment strategies.

Investigating the organic and conventional production type of olive oil with target and suspect screening by LC-QTOF-MS, a novel semi-quantification method using chemical similarity and advanced chemometrics

The discrimination of organic and conventional production has been a critical topic of public discussion and constitutes a scientific issue. It remains a challenge to establish a correlation between the agronomical practices and their effects on the composition of olive oils, especially the phenolic composition, since it defines their organoleptic and nutritional value. Thus, a liquid chromatography-electrospray ionization-quadrupole time of flight tandem mass spectrometric method was developed, using target and suspect screening workflows, coupled with advanced chemometrics for the identification of phenolic compounds and the discrimination between organic and conventional extra virgin olive oils. The method was optimized by one-factor design and response surface methodology to derive the optimal conditions of extraction (methanol/water (80:20, v/v), pure methanol, or acetonitrile) and to select the most appropriate internal standard (caffeic acid or syringaldehyde). The results revealed that extraction with methanol/water (80:20, v/v) was the optimum solvent system and syringaldehyde 1.30 mg L^-1 was the appropriate internal standard. The proposed method demonstrated low limits of detection in the range of 0.002 (luteolin) to 0.028 (tyrosol) mg kg^-1. Then, it was successfully applied in 52 olive oils of Kolovi variety. In total, 13 target and 24 suspect phenolic compounds were identified. Target compounds were quantified with commercially available standards. A novel semi-quantitation strategy, based on chemical similarity, was introduced for the semi-quantification of the identified suspects. Finally, ant colony optimization-random forest model selected luteolin as the only marker responsible for the discrimination, during a 2-year study. Graphical abstract Investigation of the organic and conventional production type of olive oil by LC-QTOF-MS.

Broadband quantitative NQR for authentication of vitamins and dietary supplements

We describe hardware, pulse sequences, and algorithms for nuclear quadrupole resonance (NQR) spectroscopy of medicines and dietary supplements. Medicine and food safety is a pressing problem that has drawn more and more attention. NQR is an ideal technique for authenticating these substances because it is a non-invasive method for chemical identification. We have recently developed a broadband NQR front-end that can excite and detect ¹⁴N NQR signals over a wide frequency range; its operating frequency can be rapidly set by software, while sensitivity is comparable to conventional narrowband front-ends over the entire range. This front-end improves the accuracy of authentication by enabling multiple-frequency experiments. We have also developed calibration and signal processing techniques to convert measured NQR signal amplitudes into nuclear spin densities, thus enabling its use as a quantitative technique. Experimental results from several samples are used to illustrate the proposed methods.

Differentiation of commercial ground beef products and correlation between metabolites and sensory attributes: A metabolomic approach

Three traditional grinds (commodity products) and 7 non-traditional grinds (branded products) were obtained to investigate the metabolites in ground beef associated with beef flavor or off-flavor. Three packaging methods were used: traditional overwrap, modified atmosphere package, and clear plastic retail chub. Samples were collected for sensory evaluation and metabolic profiling utilizing LC/MS. Principal component analysis was conducted for classification of grind source or packaging method. Partial least squares regression was applied to investigate the relationship between metabolic data and sensory data. Grass-fed beef and natural beef products were clearly separated from the other grinds. A total of 576 metabolites were registered. Thirty-three compounds were selected as the most important ones differentiating beef grinds. Twenty-two compounds were selected as the most important ones associated with beef flavor and off-flavor. In conclusion, metabolomic approach was effective to determine the most important compounds associated with certain quality characteristics of beef.

Olive oil authenticity studies by target and nontarget LC-QTOF-MS combined with advanced chemometric techniques

Food analysis is continuously requiring the development of more robust, efficient, and cost-effective food authentication analytical methods to guarantee the safety, quality, and traceability of food commodities with respect to legislation and consumer demands. Hence, a novel reversed-phase ultra high performance liquid chromatography-electrospray ionization quadrupole time of flight tandem mass spectrometry analytical method was developed that uses target, suspect, and nontarget screening strategies coupled with advanced chemometric tools for the investigation of the authenticity of extra virgin olive oil. The proposed method was successfully applied in real olive oil samples for the identification of markers responsible for the sensory profile. The proposed target analytical method includes the determination of 14 phenolic compounds and demonstrated low limits of detection ranging from 0.015 μg mL^-1 (apigenin) to 0.039 μg mL^-1 (vanillin) and adequate recoveries (96-107 %). A suspect list of 60 relevant compounds was compiled, and suspect screening was then applied to all the samples. Semiquantitation of the suspect compounds was performed with the calibration curves of target compounds having similar structures. Then, a nontarget screening workflow was applied with the aim to identify additional compounds so as to differentiate extra virgin olive oils from defective olive oils. Robust classification-based models were built with the use of supervised discrimination techniques, partial least squares-discriminant analysis and counterpropagation artificial neural networks, for the classification of olive oils into extra virgin olive oils or defective olive oils. Variable importance in projection scores were calculated to select the most significant features that affect the discrimination. Overall, 51 compounds were identified and suggested as markers, among which 14, 26, and 11 compounds were identified by target, suspect, and nontarget screening respectively. Retrospective analysis was also performed and identified 19 free fatty acids. Graphical Abstract Development of a novel RP-LC-ESI-QTOFMS analytical method employing target, suspect and non-target screening strategies coupled to advanced chemometric tools for the investigation of markers responsible for the sensory profile of extra virgin olive oil and guarantee authenticity.

Bioelectronic nose: Current status and perspectives

A characteristic feature of human and animal organs of smell is the ability to identify hundreds of thousands of odours. It is accompanied by particular smell sensations, which are a basic source of information about odour mixture. The main structural elements of biological smell systems are the olfactory receptors. Small differences in a structure of odorous molecules (odorants) can lead to significant change of odour, which is due to the fact that each of the olfactory receptors is coded with different gene and usually corresponds to different type of odour. Discovery and characterisation of the gene family coding the olfactory receptors contributed to the elaboration and development of the electronic smell systems, the so-called bioelectronic noses. The olfactory receptors are employed as a biological element in this type of instruments. An electronic system includes a converter part, which allows measurement and processing of generated signals. A suitable data analysis system is also required to visualise the results. Application potentialities of the bioelectronic noses are focused on the fields of economy and science where highly selective and sensitive analysis of odorous substances is required. The paper presents a review of the latest achievements and critical evaluation of the state of art in the field of bioelectronic noses.