Metabolomics for assessing safety and quality of plant-derived food

Metabolomics applications for plant-based foods origin tracing, cultivars identification and processing: Feasibility and future aspects

Metabolomics, the systematic study of metabolites, is dedicated to a comprehensive analysis of all aspects of plant-based food research and plays a pivotal role in the nutritional composition and quality control of plant-based foods. The diverse chemical compositions of plant-based foods lead to variations in sensory characteristics and nutritional value. This review explores the application of the metabolomics method to plant-based food origin tracing, cultivar identification, and processing methods. It also addresses the challenges encountered and outlines future directions. Typically, when combined with other omics or techniques, synergistic and complementary information is uncovered, enhancing the classification and prediction capabilities of models. Future research should aim to evaluate all factors affecting food quality comprehensively, and this necessitates advanced research into influence mechanisms, metabolic pathways, and gene expression.

Food authentication, current issues, analytical techniques, and future challenges: A comprehensive review

Food authentication and contamination are significant concerns, especially for consumers with unique nutritional, cultural, lifestyle, and religious needs. Food authenticity involves identifying food contamination for many purposes, such as adherence to religious beliefs, safeguarding health, and consuming sanitary and organic food products. This review article examines the issues related to food authentication and food fraud in recent periods. Furthermore, the development and innovations in analytical techniques employed to authenticate various food products are comprehensively focused. Food products derived from animals are susceptible to deceptive practices, which can undermine customer confidence and pose potential health hazards due to the transmission of diseases from animals to humans. Therefore, it is necessary to employ suitable and robust analytical techniques for complex and high-risk animal-derived goods, in which molecular biomarker-based (genomics, proteomics, and metabolomics) techniques are covered. Various analytical methods have been employed to ascertain the geographical provenance of food items that exhibit rapid response times, low cost, nondestructiveness, and condensability.

Genetically modified soybean lines exhibit less transcriptomic variation compared to natural varieties

Genetically modified (GM) soybeans provide a huge amount of food for human consumption and animal feed. However, the possibility of unexpected effects of transgenesis has increased food safety concerns. High-throughput sequencing profiling provides a potential approach to directly evaluate unintended effects caused by foreign genes. In this study, we performed transcriptomic analyses to evaluate differentially expressed genes (DEGs) in individual soybean tissues, including cotyledon (C), germ (G), hypocotyl (H), and radicle (R), instead of using the whole seed, from four GM and three non-GM soybean lines. A total of 3,351 DEGs were identified among the three non-GM soybean lines. When the GM lines were compared with their non-GM parents, 1,836 to 4,551 DEGs were identified. Furthermore, Gene Ontology (GO) analysis of the DEGs showed more abundant categories of GO items (199) among non-GM lines than between GM lines and the non-GM natural varieties (166). Results of Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that most KEGG pathways were the same for the two types of comparisons. The study successfully employed RNA sequencing to assess the differences in gene expression among four tissues of seven soybean varieties, and the results suggest that transgenes do not induce massive transcriptomic alterations in transgenic soybeans compared with those that exist among natural varieties. This work offers empirical evidence to investigate the genomic-level disparities induced by genetic modification in soybeans, specifically focusing on seed tissues.

The Framework for Responsible Research With Australian Native Plant Foods: A Food Chemist's Perspective

Australia is a rich source of biodiverse native plants that are mostly unstudied by western food science despite many of them being ethnofoods of Australian Indigenous people. Finding and understanding the relevant policy and legal requirements to scientifically assess these plants in a responsible way is a major challenge for food scientists. This work aims to give an overview of what the legal and policy framework is in relation to food chemistry on Australian native plant foods, to clarify the relationships between the guidelines, laws, policies and ethics and to discuss some of the challenges they present in food chemistry. This work provides the framework of Indigenous rights, international treaties, federal and state laws and ethical guidelines including key legislation and guidelines. It discusses the specific areas that are applicable to food chemistry: the collection of plant foods, the analysis of the samples and working with Indigenous communities. This brief perspective presents a framework that can be utilized by food chemists when developing responsible research involving plant foods native to northern Australia and can help them understand some of the complexity of working in this research area.

Food Metabolites as Tools for Authentication, Processing, and Nutritive Value Assessment

Secondary metabolites are molecules with unlimited applications that have been gaining importance in various industries and studied from many angles. They are mainly used for their bioactive capabilities, but due to the improvement of sensibility in analytical chemistry, they are also used for authentication and as a quality control parameter for foods, further allowing to help avoid food adulteration and food fraud, as well as helping understand the nutritional value of foods. This manuscript covers the examples of secondary metabolites that have been used as qualitative and authentication molecules in foods, from production, through processing and along their shelf-life. Furthermore, perspectives of analytical chemistry and their contribution to metabolite detection and general perspectives of metabolomics are also discussed.

Nontargeted 1 H NMR fingerprinting and multivariate statistical analysis for traceability of Greek PDO Vostizza currants

In this study, non-targeted ¹ H NMR fingerprinting was used in combination with multivariate statistical analyses for the classification of Greek currants based on their geographical origins (Aeghion, Nemea, Kalamata, Zante, and Amaliada). As classification techniques, Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) were carried out. To elucidate different components according to PDO (Protected Designation of Origin), products from Aeghion (Vostizza) were statistically compared with each one of the four other regions. PLS-DA plots ensure that currants from Kalamata, Nemea, Zante, and Amaliada are well classified with respect to the PDO currants, according to differences observed in metabolites. Results suggest that composition differences in carbohydrates, amino, and organic acids of currants are sufficient to discriminate them in correlation to their geographical origin. In conclusion, currants metabolites which mostly contribute to classification performance of such discriminant analysis model present a suitable alternative technique for currants traceability. The study results contribute information to the currants' metabolite fingerprinting by NMR spectroscopy and their geographical origin. PRACTICAL APPLICATION: This study presents an analytical approach for a high nutritional value Greek PDO product, Vostizza currant. A further research and implementation of this method in food industry, can be the key to food fraud incidents. Thus, application of this work opens up posibilities to "farm to table" mission.

External parameter orthogonalization-support vector machine for processing of attenuated total reflectance-mid-infrared spectra: A solution for saffron authenticity problem

In the present work, a new approach based on external parameter orthogonalization combined with support vector machine (EPO-SVM) is proposed for processing of attenuated total reflectance-Fourier transform mid-infrared (ATR-FT-MIR) spectra with the goal of solving authentication problem in saffron, the most expensive spice in the world. First, one-hundred authentic saffron samples are clustered by principal component analysis (PCA) with EPO as the best preprocessing strategy. Then, EPO-SVM is used for the detection of four commonly used plant-derived adulterants (i.e. safflower, calendula, rubia, and style) in binary mixtures (saffron and each of plant adulterants) and its performance is compared with other common classification methods. The obtained results showed that the EPO-SVM approach has a much better classification accuracy (>95%) than other methods (accuracy<89.2%). Finally, two different sample sets including mixture of saffron and four plant adulterants and commercial saffron samples are used for validation of the developed EPO-SVM model. In this regard, classification figures of merit in terms of sensitivity, specificity and accuracy were respectively 96.6%, 97.1%, and 96.8% which showed good classification performance. It is concluded that the proposed EPO-PCA and EPO-SVM approaches can be considered as reliable tools for authentication and adulteration detection in saffron samples.

Phytochemical profile and biological activities of Sudanese baobab (Adansonia digitata L.) fruit pulp extract

The present work aimed to investigate the phytochemical profile and biological activities of Sudanese baobab (Adansonia digitata L.) fruit pulp extract. Baobab fruit pulp serves as food, and has been used in traditional medicine in Africa for the treatment of several diseases, and believed to possess many biological activities. The sample of baobab fruit was collected from Blue Nile State in Sudan. The fruit pulp was obtained from baobab pods, sieved, extracted with methanol (80%), and analysed for its antioxidant activity, and alpha-glucosidase and nitric oxide (NO) inhibitory activities. The phytochemical constituents of the pulp were determined by LC-MS and 1H-NMR techniques. The results for antioxidant activity evaluated by DPPH and FRAP for methanolic extract were 232.70 mg Ascorbic Acid Equivalent Antioxidant Capacity (AEAC)/g and 222.28 mmol/g of Fe2+, respectively. Baobab pulp extract showed greater capability in inhibiting the generation of NO from the stimulated RAW264.7 cells at 98.45% inhibition and IC50 of 36.55 µg/mL; and α-glucosidase enzyme activity at 97.94% inhibition and IC50 of 58.59 µg/mL. The LC-MS/MS analysis of the baobab extract showed that 52 compounds were found in the baobab pulp, including 19 flavonoids, ten phenolic acids, four lipids (glycero-3-phosphocholine derivative, 1,2-didodecanoyl-sn-glycero-3-phospho-(1'-sn-glycerol), 1-pentadecanoyl-2-(13Z,16Z-docosadienoyl)-glycero-3-phosphate, and glycero-3-hosphocholine derivative), sugars, organic acid, iridoids, adenosine, scopoletin, and taraxerone. The NMR detected 21 metabolites from baobab pulp extract including carbohydrates, organic acids, vitamin, amino acids, phenolic compounds, alkaloids, and fatty acids. The present work is the first of its kind in comprehensively analysing the Sudanese baobab fruit pulp, combined with qualitative characterisation of chemical components using NMR, LC-MS, α-glucosidase, and NO inhibitors. Baobab fruit pulp contains several beneficial phytochemicals and biological activities, and it has potential positive effect on general human’s health.

Dataset on the Effects of Different Pre-Harvest Factors on the Metabolomics Profile of Lettuce (Lactuca sativa L.) Leaves

The study of the relationship between cultivated plants and environmental factors can provide information ranging from a deeper understanding of the plant biological system to the development of more effective management strategies for improving yield, quality, and sustainability of the produce. In this article, we present a comprehensive metabolomics dataset of two phytochemically divergent lettuce (Lactuca sativa L.) butterhead varieties under different growing conditions. Plants were cultivated in hydroponics in a growth chamber with ambient control. The pre-harvest factors that were independently investigated were light intensity (two levels), the ionic strength of the nutrient solutions (three levels), and the molar ratio of three macroelements (K, Mg, and Ca) in the nutrient solution (three levels). We used an untargeted, mass-spectrometry-based approach to characterize the metabolomics profiles of leaves harvested 19 days after transplant. The data revealed the ample impact on both primary and secondary metabolism and its range of variation. Moreover, our dataset is useful for uncovering the complex effects of the genotype, the environmental factor(s), and their interaction, which may deserve further investigation.

A rapid analysis method of safflower (Carthamus tinctorius L.) using combination of computer vision and near-infrared

The quality of safflower (Carthamus tinctorius L.) in the market is uneven due to the problems of dyeing and adulteration of safflower, and there is no perfect standard for the classification of quality grade of safflower at present. In this study, computer vision (CV) and near-infrared (NIR) were combined to realize the rapid and nondestructive analysis of safflower. First, the partial least squares discrimination analysis (PLS-DA) model was used to qualitatively identify the dyed safflower from 150 samples. Then the partial least squares (PLS) model was used for quantitative analysis of the hydroxy safflower yellow pigment A (HSYA) and water extract of undyed safflower. Herein, the discrimination rate of PLS-DA model reached 100%, and the residual predictive deviation (RPD) values of the PLS models for HSYA and water extract were 2.5046 and 5.6195, respectively. It indicated that the rapid analysis method combining CV and NIR was reliable, and its results can provide important reference for the formulation of safflower quality classification standards in the market.

NMR-Based Plant Metabolomics in Nutraceutical Research: An Overview

Few topics are able to channel the interest of researchers, the public, and industries, like nutraceuticals. The ever-increasing demand of new compounds or new sources of known active compounds, along with the need of a better knowledge about their effectiveness, mode of action, safety, etc., led to a significant effort towards the development of analytical approaches able to answer the many questions related to this topic. Therefore, the application of cutting edges approaches to this area has been observed. Among these approaches, metabolomics is a key player. Herewith, the applications of NMR-based metabolomics to nutraceutical research are discussed: after a brief overview of the analytical workflow, the use of NMR-based metabolomics to the search for new compounds or new sources of known nutraceuticals are reviewed. Then, possible applications for quality control and nutraceutical optimization are suggested. Finally, the use of NMR-based metabolomics to study the impact of nutraceuticals on human metabolism is discussed.

Volatile compounds associated with growth of Asaia bogorensis and Asaia lannensis-unusual spoilage bacteria of functional beverages

Acetic acid bacteria of the genus Asaia are recognized as common bacterial spoilage in the beverage industry. Their growth in contaminated soft drinks can be visible in the form of flocs, turbidity and flavor changes. Volatile profiles associated with the growth and metabolic activities of Asaia lannensis and As. bogorensis strains were evaluated using comprehensive gas chromatography-time of flight mass spectrometry (GC × GC-ToF MS). Based on obtained results, 33 main compounds were identified. The greatest variety of volatile metabolites was noted for As. lannensis strain W4. 2-Phenylethanol, 3-pentanone, 2-nonanol, 2-hydroxy-3-pentanone, and 2-nitro-1-butanol were detected as dominant volatile compounds. Additionally, As. lannensis strains formed 2-propenoic acid ethyl ester. As. bogorensis ISD1 was distinguished by the higher concentration of 2-hydroxy-3-pentanone and 3-methyl-1-butene but the lowest concentration of 2-phenylethanol. Based on these results, it was found that volatile profiles of Asaia spp. are unique among acetic acid bacteria. Moreover, obtained profiles depended not only on bacterial species and strains but also on the composition of culture media.

Insights in cyanobacteria lipidomics: A sterols characterization from Phormidium autumnale biomass in heterotrophic cultivation

Sterol profiles were obtained from cyanobacteria Phormidium autumnale, cultivated in a heterotrophic system using three distinct sources of carbon: glucose, sucrose, and agroindustrial slaughterhouse wastewater. A simultaneous saponification-extraction ultrasound-assisted method was performed to determine sterol and other non-saponified compounds in the dry biomasses. A total of 24 compounds were observed in the biomasses, including hope-22,29-en-3-one, squalene, and 22 other sterols. Using wastewater as a carbon source, the microalgae biomass produced a diversity of sterols such as stigmasterol (455.3 μg g^-1) and β-sitosterol (279.0 μg g^-1). However, with glucose it is possible to produce ergosterol (1033.3 μg g^-1). Squalene was found in all the cultures, with 1440.4 μg g^-1, 225.4 μg g^-1, and 425.6 μg g^-1 for glucose, sucrose, and slaughterhouse wastewater biomasses, respectively. Several intermediate compounds from those sterols were found. These data provide the construction of the sterol metabolism according to the literature for P. autumnale heterotrophically cultured.

Quality Changes of Orange Juice after DPCD Treatment

Dense phase carbon dioxide (DPCD) offers advantages of enhanced physical and nutritional qualities during the processing of juices. Here, freshly squeezed orange juice was treated with DPCD, and changes of physical properties and volatile components were investigated and compared with the original untreated and thermally treated samples. The correlations among physiochemical properties were also examined based on Pearson correlation, cluster analysis (CA), and principal component analysis (PCA). Significant correlations were found among the particle size, color parameters, and volatile compounds in the DPCD-treated samples. The 12 parameters were clustered into three groups using CA and PCA, and the eight volatile compounds were separated within the three groups. Nonanal and citronellol were clustered in group I, and they increased for a longer duration of more than 40 min with higher levels than the control. Parameters in group II included D (4,3), L∗, a∗, ethyl butyrate, and trans-2-hexenol, and they linearly decreased after 10–60 min DPCD treatment. The parameters of b∗ and monoterpenes were clustered in group III, and they decreased within 40 min of DPCD treatment and then increased to an intermediate level. In addition, PCA clearly showed that the orange juice samples under DPCD for 10–60 min formed a “U” shape on the two-dimensional plot and that the samples treated by DPCD for 10 min and 20 min were closer to freshly squeezed orange juice than the heat-treated orange juice. This indicated that the nonthermal DPCD process offers the potential to be used more extensively in juice products.

Integrated analytical assets aid botanical authenticity and adulteration management

This article reviews and develops a perspective for the meaning of authenticity in the context of quality assessment of botanical materials and the challenges associated with discerning adulterations vs. contaminations vs. impurities. Authentic botanicals are by definition non-adulterated, a mutually exclusive relationship that is confirmed through the application of a multilayered set of analytical methods designed to validate the (chemo)taxonomic identity of a botanical and certify that it is devoid of any adulteration. In practice, the ever-increasing sophistication in the process of intentional adulteration, as well as the growing number of botanicals entering the market, altogether necessitate a constant adaptation and reinforcement of authentication methods with new approaches, especially new technologies. This article summarizes the set of analytical methods - classical and contemporary - that can be employed in the authentication of botanicals. Particular emphasis is placed on the application of untargeted metabolomics and chemometrics. An NMR-based untargeted metabolomic model is proposed as a rapid, systematic, and complementary screening for the discrimination of authentic vs. potentially adulterated botanicals. Such analytical model can help advance the evaluation of botanical integrity in natural product research.

Metabolic Responses to Low Temperature of Three Peach Fruit Cultivars Differently Sensitive to Cold Storage

Refrigerated storage is widely applied in order to maintain peach quality but it can also induce chilling injuries (CIs) such as flesh browning and bleeding, and mealiness. Peach fruit from three cultivars ('Red Haven', RH, 'Regina di Londa', RL, and 'Flaminia', FL) were stored for 4 weeks under low temperatures (0.5 and 5.5°C). GC-MS was employed to study changes in both metabolome and volatilome induced by cold storage in the mesocarp. CIs were assessed both at the end of each week of storage and after subsequent shelf-life (SL) at 20°C. Flesh browning and mealiness appeared to be more related to 5.5°C storage, while flesh bleeding revealed high incidence following 0.5°C storage. Compared to RL and FL, RH showed a marked lower incidence of CIs. Multivariate statistical analyses indicate that RH peaches indeed differ from RL and FL in particular when considering data from samples collected at the end of the cold storage. Common and divergent responses have been identified in terms of metabolic responses to the applied low temperatures. In all three cultivars raffinose, glucose-6P, fucose, xylose, sorbitol, GABA, epicatechin, catechin, and putrescine markedly increased during cold storage, while citramalic, glucuronic, mucic and shikimic acids decreased. Among volatile organic compounds (VOCs), aldehydes and alcohols generally accumulated more under low temperature conditions while esters and lactones evolved during subsequent SL. The main cultivar differences developed after cold storage during SL although some common responses (e.g., an increased production of ethyl acetate) were observed. The lower levels of flesh browning and bleeding displayed by RH peaches were related to compounds with antioxidant activity, or acting as osmotic protectants and membrane stabilizer. Indeed, RH showed higher levels of amino acids and urea, together with a marked increase in putrescine, sorbitol, maltitol, myoinositol and sucrose detected during storage and SL.

Proteomics integrated with metabolomics: analysis of the internal causes of nutrient changes in alfalfa at different growth stages

BACKGROUND

Alfalfa (Medicago sativa L.) is one of the most important forage resources in the world due to its high nutritive value. However, its nutritional quality decreases during the transition from budding to flowering. Previous research revealed a decreased crude protein content and increased fibre content in alfalfa forage harvested at later maturity stages, leading to a reduction in nutritional quality. However, the reasons for this phenomenon have not been explained at the molecular level.

RESULTS

In this study, leaves from the WL319HQ alfalfa cultivar were harvested at two developmental stages (budding and mid-flowering). The leaves were used to test the variable expression of proteins and metabolites during these stages. TMT-based quantitative proteomics and LC-MS/MS-based untargeted metabolomics methods were employed in this study. A total of 415 proteins and 49 metabolites showed at least a 1.2-fold difference in abundance during these stages. Most of the differentially expressed proteins and metabolites were involved in metabolic processes, including carbohydrate metabolism, starch and sucrose metabolism, phenylpropanoid biosynthesis, and biosynthesis of amino acids. Alfalfa leaves in mid-flowering contain less crude protein due to the decrease in L-glutamic acid content. Carbohydrate metabolism provides the raw material for the synthesis of hemicellulose, resulting in an increase in the hemicellulose content of the alfalfa leaves, leading to an increase in the NDF content. In addition, the increase in L-phenylalanine content could have provided the conditions necessary for lignin synthesis. These are the main factors leading to reductions in alfalfa relative feed value (RFV) and quality.

CONCLUSIONS

This study used joint proteomic and metabolomic analyses to elucidate the relationship between the reduction in the nutritional value of alfalfa and complex biological processes. This provides a theoretical basis for producing high-quality alfalfa hay and sets the stage for further research.

Phenolic Profiling for Traceability of Vanilla ×tahitensis

Vanilla is a flavoring recovered from the cured beans of the orchid genus Vanilla. Vanilla ×tahitensis is traditionally cultivated on the islands of French Polynesia, where vanilla vines were first introduced during the nineteenth century and, since the 1960s, have been introduced to other Pacific countries such as Papua New Guinea (PNG), cultivated and sold as "Tahitian vanilla," although both sensory properties and aspect are different. From an economic point of view, it is important to ensure V. ×tahitensis traceability and to guarantee that the marketed product is part of the future protected designation of the origin "Tahitian vanilla" (PDO), currently in progress in French Polynesia. The application of metabolomics, allowing the detection and simultaneous analysis of hundreds or thousands of metabolites from different matrices, has recently gained high interest in food traceability. Here, metabolomics analysis of phenolic compounds profiles was successfully applied for the first time to V. ×tahitensis to deepen our knowledge of vanilla metabolome, focusing on phenolics compounds, for traceability purposes. Phenolics were screened through a quadrupole-time-of-flight mass spectrometer coupled to a UHPLC liquid chromatography system, and 260 different compounds were clearly evidenced and subjected to different statistical analysis in order to enable the discrimination of the samples based on their origin. Eighty-eight and twenty three compounds, with a prevalence of flavonoids, resulted to be highly discriminant through ANOVA and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) respectively. Volcano plot analysis and pairwise comparisons were carried out to determine those compounds, mainly responsible for the differences among samples as a consequence of either origin or cultivar. The samples from PNG were clearly different from the Tahitian samples that were further divided in two different groups based on the different phenolic patterns. Among the 260 compounds, metabolomics analysis enabled the detection of previously unreported phenolics in vanilla (such as flavonoids, lignans, stilbenes and other polyphenols).

Food Targeting: Geographical Origin Determination of Hazelnuts (Corylus avellana) by LC-QqQ-MS/MS-Based Targeted Metabolomics Application

A targeted metabolomics LC-ESI-QqQ-MS application for geographical origin discrimination based on 20 nonpolar key metabolites was developed, validated according to accepted guidelines and used for quantitation via stable isotope labeled internal standards in 202 raw authentic hazelnut samples from six countries (Turkey, Italy, Georgia, Spain, France, and Germany) of harvest years 2014 and 2015. Multivariate statistics were used for detection of significant variations in metabolite levels between countries and, moreover, a prediction model using support vector machine classification (SVM) was calculated yielding 100% training accuracy and 97% cross-validation accuracy, which was subsequently applied to 55 hazelnut samples for the confectionary industry gaining up to 80% correct classifications compared to declared origin. The present method demonstrates the great suitability for targeted metabolomics applications in the geographical origin determination of hazelnuts and their applicability in routine analytics.

Butia spp. (Arecaceae) LC-MS-Based Metabolomics for Species and Geographical Origin Discrimination

The metabolic variability of fruit from Butia spp. (Arecaceae) genotypes from different geographical locations was characterized using untargeted metabolomics by liquid chromatography-mass spectrometry (LC-MS) followed by multivariate data analyses. Principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) from LC-MS data sets showed a clear distinction among Butia catarinensis, Butia odorata, Butia paraguayensis, and Butia yatay. The major metabolites that contributed to species discrimination were primary metabolites including sugars and organic acids and specialized metabolites such as tetrahydroxy-trans-stilbene and rutin. B. odorata fruit from Tapes, RS, Brazil, showed a high content of organic acids and flavonoids, whereas B. odorata fruits from Capão do Leão, RS, Brazil, showed a high sugar content. The results demonstrate that LC-ESI-qToF-MS-based metabolic profiling coupled with chemometric analysis can be used to discriminate among Butia species and between geographical origins of B. odorata and to identify primary and specialized metabolites responsible for the discrimination.

Evaluation of different training systems on Annurca apple fruits revealed by agronomical, qualitative and NMR-based metabolomic approaches

Nine different training systems for "Annurca Rossa del Sud" apple fruits, including oblique palmette, free palmette, V-shaped, Tatura trellis, Bibaum®, modified Bibaum®, triple leader, slender spindle and Solaxe, were evaluated based on agronomic, qualitative and metabolomic traits. Fruits were analysed at harvest and after the reddening process. The slender spindle training system showed the highest cumulative efficiency yield compared to the others. Furthermore, an increase in the content of bioactive compounds in flesh and fruit peels was observed after the reddening process and was influenced by the different training systems. The metabolic variations in apple peel were measured and analysed. Changes in the metabolome highlight the influence of different training systems on apple quality. This multidisciplinary study expands our knowledge of the influence of training systems on a typical Italian apple cultivar.

Fortune telling: metabolic markers of plant performance

BACKGROUND

In the last decade, metabolomics has emerged as a powerful diagnostic and predictive tool in many branches of science. Researchers in microbes, animal, food, medical and plant science have generated a large number of targeted or non-targeted metabolic profiles by using a vast array of analytical methods (GC-MS, LC-MS, 1H-NMR….). Comprehensive analysis of such profiles using adapted statistical methods and modeling has opened up the possibility of using single or combinations of metabolites as markers. Metabolic markers have been proposed as proxy, diagnostic or predictors of key traits in a range of model species and accurate predictions of disease outbreak frequency, developmental stages, food sensory evaluation and crop yield have been obtained.

AIM OF REVIEW

(i) To provide a definition of plant performance and metabolic markers, (ii) to highlight recent key applications involving metabolic markers as tools for monitoring or predicting plant performance, and (iii) to propose a workable and cost-efficient pipeline to generate and use metabolic markers with a special focus on plant breeding.

KEY MESSAGE

Using examples in other models and domains, the review proposes that metabolic markers are tending to complement and possibly replace traditional molecular markers in plant science as efficient estimators of performance.

Metabolomics Provides Quality Characterization of Commercial Gochujang (Fermented Pepper Paste)

To identify the major factors contributing to the quality of commercial gochujang (fermented red pepper paste), metabolites were profiled by mass spectrometry. In principal component analysis, cereal type (wheat, brown rice, and white rice) and species of hot pepper (Capsicumannuum, C. annuum cv. Chung-yang, and C. frutescens) affected clustering patterns. Relative amino acid and citric acid levels were significantly higher in wheat gochujang than in rice gochujang. Sucrose, linoleic acid, oleic acid, and lysophospholipid levels were high in brown-rice gochujang, whereas glucose, maltose, and γ-aminobutyric acid levels were high in white-rice gochujang. The relative capsaicinoid and luteolin derivative contents in gochujang were affected by the hot pepper species used. Gochujang containing C. annuum cv. Chung-yang and C. frutescens showed high capsaicinoid levels. The luteolin derivative level was high in gochujang containing C. frutescens. These metabolite variations in commercial gochujang may be related to different physicochemical phenotypes and antioxidant activity.

Current Advances in the Metabolomics Study on Lotus Seeds

Lotus (Nelumbo nucifera), which is distributed widely throughout Asia, Australia and North America, is an aquatic perennial that has been cultivated for over 2,000 years. It is very stimulating that almost all parts of lotus have been consumed as vegetable as well as food, especially the seeds. Except for the nutritive values of lotus, there has been increasing interest in its potential as functional food due to its rich secondary metabolites, such as flavonoids and alkaloids. Not only have these metabolites greatly contributed to the biological process of lotus seeds, but also have been reported to possess multiple health-promoting effects, including antioxidant, anti-amnesic, anti-inflammatory, and anti-tumor activities. Thus, comprehensive metabolomic profiling of these metabolites is of key importance to help understand their biological activities, and other chemical biology features. In this context, this review will provide an update on the current technological platforms, and workflow associated with metabolomic studies on lotus seeds, as well as insights into the application of metabolomics for the improvement of food safety and quality, assisting breeding, and promotion of the study of metabolism and pharmacokinetics of lotus seeds; meanwhile it will also help explore new perspectives and outline future challenges in this fast-growing research subject.

Investigation of the effect of genotype and agronomic conditions on metabolomic profiles of selected strawberry cultivars with different sensitivity to environmental stress

Strawberry is one of the most economically important and widely cultivated fruit crops across the world, so that there is a growing need to develop new analytical methodologies for the authentication of variety and origin, as well as the assessment of agricultural and processing practices. In this work, an untargeted metabolomic strategy based on gas chromatography mass spectrometry (GC-MS) combined with multivariate statistical techniques was used for the first time to characterize the primary metabolome of different strawberry cultivars and to study metabolite alterations in response to multiple agronomic conditions. For this purpose, we investigated three varieties of strawberries with different sensitivity to environmental stress (Camarosa, Festival and Palomar), cultivated in soilless systems using various electrical conductivities, types of coverage and substrates. Metabolomic analysis revealed significant alterations in primary metabolites between the three strawberry cultivars grown under different crop conditions, including sugars (fructose, glucose), organic acids (malic acid, citric acid) and amino acids (alanine, threonine, aspartic acid), among others. Therefore, it could be concluded that GC-MS based metabolomics is a suitable tool to differentiate strawberry cultivars and characterize metabolomic changes associated with environmental and agronomic conditions.

Differential Metabolic Rearrangements after Cold Storage Are Correlated with Chilling Injury Resistance of Peach Fruits

Reconfiguration of the metabolome is a key component involved in the acclimation to cold in plants; however, few studies have been devoted to the analysis of the overall metabolite changes after cold storage of fruits prior to consumption. Here, metabolite profiling of six peach varieties with differential susceptibility to develop mealiness, a chilling-injury (CI) symptom, was performed. According to metabolic content at harvest; after cold treatment; and after ripening, either following cold treatment or not; peach fruits clustered in distinct groups, depending on harvest-time, cold treatment, and ripening state. Both common and distinct metabolic responses among the six varieties were found; common changes including dramatic galactinol and raffinose rise; GABA, Asp, and Phe increase; and 2-oxo-glutarate and succinate decrease. Raffinose content after long cold treatment quantitatively correlated to the degree of mealiness resistance of the different peach varieties; and thus, raffinose emerges as a candidate biomarker of this CI disorder. Xylose increase after cold treatment was found only in the susceptible genotypes, indicating a particular cell wall reconfiguration of these varieties while being cold-stored. Overall, results indicate that peach fruit differential metabolic rearrangements due to cold treatment, rather than differential metabolic priming before cold, are better related with CI resistance. The plasticity of peach fruit metabolism renders it possible to induce a diverse metabolite array after cold, which is successful, in some genotypes, to avoid CI.

Holistic Analysis Enhances the Description of Metabolic Complexity in Dietary Natural Products

In the field of food and nutrition, complex natural products (NPs) are typically obtained from cells/tissues of diverse organisms such as plants, mushrooms, and animals. Among them, edible fruits, grains, and vegetables represent most of the human diet. Because of an important dietary dependence, the comprehensive metabolomic analysis of dietary NPs, performed holistically via the assessment of as many metabolites as possible, constitutes a fundamental building block for understanding the human diet. Both mass spectrometry (MS) and nuclear magnetic resonance (NMR) are important complementary analytic techniques, covering a wide range of metabolites at different concentrations. Particularly, 1-dimensional 1H-NMR offers an unbiased overview of all metabolites present in a sample without prior knowledge of its composition, thereby leading to an untargeted analysis. In the past decade, NMR-based metabolomics in plant and food analyses has evolved considerably. The scope of the present review, covering literature of the past 5 y, is to address the relevance of 1H-NMR–based metabolomics in food plant studies, including a comparison with MS-based techniques. Major applications of NMR-based metabolomics for the quality control of dietary NPs and assessment of their nutritional values are presented.

Integrated pathway-based and network-based analysis of GC-MS rice metabolomics data under diazinon stress to infer affected biological pathways

Diazinon insecticide is widely applied in rice (Oryza sativa L.) fields in Iran. However, concerns are now being raised about its potential adverse impacts on rice. In this study, a time-course metabolic change in rice plants was investigated after diazinon treatment using gas chromatography-mass spectrometry (GC-MS) and subsequently three different methods, MetaboAnalyst, MetaboNetwork, and analysis of reporter reactions, as a potential multivariate method were used to find the underlying changes in metabolism with stronger evidence in order to link differentially expressed metabolites to biological pathways. Results clearly showed the similarity of acetylcholinesterase (AChE) of rice plants to that of animals in terms of its inhibitability by diazinon and emphasized that subsequent accumulation of AChE mainly affects the metabolism of osmolites and tricarboxylic acid intermediates subsequent accumulation of ACh mainly affects the metabolism of osmolites and TCA intermediates.

Chemotaxonomic Metabolite Profiling of 62 Indigenous Plant Species and Its Correlation with Bioactivities

Chemotaxonomic metabolite profiling of 62 indigenous Korean plant species was performed by ultrahigh performance liquid chromatography (UHPLC)-linear trap quadrupole-ion trap (LTQ-IT) mass spectrometry/mass spectrometry (MS/MS) combined with multivariate statistical analysis. In partial least squares discriminant analysis (PLS-DA), the 62 species clustered depending on their phylogenetic family, in particular, Aceraceae, Betulaceae, and Fagaceae were distinguished from Rosaceae, Fabaceae, and Asteraceae. Quinic acid, gallic acid, quercetin, quercetin derivatives, kaempferol, and kaempferol derivatives were identified as family-specific metabolites, and were found in relatively high concentrations in Aceraceae, Betulaceae, and Fagaceae. Fagaceae and Asteraceae were selected based on results of PLS-DA and bioactivities to determine the correlation between metabolic differences among plant families and bioactivities. Quinic acid, quercetin, kaempferol, quercetin derivatives, and kaempferol derivatives were found in higher concentrations in Fagaceae than in Asteraceae, and were positively correlated with antioxidant and tyrosinase inhibition activities. These results suggest that metabolite profiling was a useful tool for finding the different metabolic states of each plant family and understanding the correlation between metabolites and bioactivities in accordance with plant family.

Studying the effect of storage conditions on the metabolite content of red wine using HILIC LC-MS based metabolomics

The main aim of this work was to develop an untargeted normal phase LC-MS method, starting from a targeted method already validated for the analysis of 135 polar metabolites. Since the LC instrument and column were the same, most of the chromatographic conditions remained identical, while the adaptations focused on maintaining the ionic strength of the eluents constant. The sample preparation was simplified and the effectiveness of LC-MS for long batches was evaluated, in order to record the maximum number of metabolites with good chromatographic resolution and the best MS stability and accuracy. The method was applied to study the influence of storage conditions on wine composition. Slightly sub-optimum storage conditions had a major impact on the polar metabolite fingerprint of the red wines analysed and the markers revealed included phenolics, vitamins and metabolites indentified in wine for the first time (4-amino-heptanedioic acid and its ethyl ester).