Comparative Metabolomics and Molecular Phylogenetics of Melon (Cucumis melo, Cucurbitaceae) Biodiversity

Advanced detection tools in food fraud: A systematic review for holistic and rational detection method based on research and patents

Modern food chain supply management necessitates the dire need for mitigating food fraud and adulterations. This holistic review addresses different advanced detection technologies coupled with chemometrics to identify various types of adulterated foods. The data on research, patent and systematic review analyses (2018-2023) revealed both destructive and non-destructive methods to demarcate a rational approach for food fraud detection in various countries. These intricate hygiene standards and AI-based technology are also summarized for further prospective research. Chemometrics or AI-based techniques for extensive food fraud detection are demanded. A systematic assessment reveals that various methods to detect food fraud involving multiple substances need to be simple, expeditious, precise, cost-effective, eco-friendly and non-intrusive. The scrutiny resulted in 39 relevant experimental data sets answering key questions. However, additional research is necessitated for an affirmative conclusion in food fraud detection system with modern AI and machine learning approaches.

Importance of Certain Varieties of Cucurbits in Enhancing Health: A Review

The Cucurbitaceae family is an extensive group of fruits and vegetables that exhibit common characteristics; for example, they are farmed on a global scale and exhibit a wide range of applications, including fresh consumption and use in various food and beverage products. As is frequent, many species or genera share a common name, and this can lead to some confusion when looking for information about a specific variety. In this review, we describe the findings about the biological activity, like antibacterial, antiviral, antidiabetic, and anticancer properties, of two genera of this family, Cucumis and Momordica, which have been characterized and evaluated in several research studies and regarding which information is readily accessible. Those activities rely on the various physicochemical qualities and nutritional content of each variety, including factors like β-carotene and polyphenols, among others. The goal of this review is to provide a rapid search for each activity examined in the literature, enabling future research on their potential uses in functional foods and nutraceutical supplements.

Regulation of climacteric fruit ripening in melon: recent advances and future challenges

Fruit ripening is a complex and highly regulated process where tomato and strawberry have been the model species classically used for studying climacteric and non-climacteric fleshy fruit ripening types, respectively. Melon has emerged as an alternative ripening model because climacteric and non-climacteric cultivars exist, which makes it possible to dissect the regulation of ripening using a genetic approach. Several quantitative trait loci that regulate climacteric fruit ripening have been identified to date, and their combination in both climacteric and non-climacteric genetic backgrounds resulted in lines with different ripening behaviors, demonstrating that the climacteric intensity can be genetically modulated. This review discusses our current knowledge of the physiological changes observed during melon climacteric fruit ripening such as ethylene production, fruit abscission, chlorophyll degradation, firmness, and aroma, as well as their complex genetic control. From pioneer experiments in which ethylene biosynthesis was silenced, to the recent genetic edition of ripening regulators, current data suggest that the climacteric response is determined by the interaction of several loci under quantitative inheritance. The exploitation of the rich genetic diversity of melon will enable the discovery of additional genes involved in the regulation of the climacteric response, ultimately leading to breeding aromatic melon fruits with extended shelf life.

Systems-level proteomics and metabolomics reveals the diel molecular landscape of diverse kale cultivars

Kale is a group of diverse Brassicaceae species that are nutritious leafy greens consumed for their abundance of vitamins and micronutrients. Typified by their curly, serrated and/or wavy leaves, kale varieties have been primarily defined based on their leaf morphology and geographic origin, despite having complex genetic backgrounds. Kale is a very promising crop for vertical farming due to its high nutritional content; however, being a non-model organism, foundational, systems-level analyses of kale are lacking. Previous studies in kale have shown that time-of-day harvesting can affect its nutritional composition. Therefore, to gain a systems-level diel understanding of kale across its wide-ranging and diverse genetic landscape, we selected nine publicly available and commercially grown kale cultivars for growth under near-sunlight LED light conditions ideal for vertical farming. We then analyzed changes in morphology, growth and nutrition using a combination of plant phenotyping, proteomics and metabolomics. As the diel molecular activities of plants drive their daily growth and development, ultimately determining their productivity as a crop, we harvested kale leaf tissue at both end-of-day (ED) and end-of-night (EN) time-points for all molecular analyses. Our results reveal that diel proteome and metabolome signatures divide the selected kale cultivars into two groups defined by their amino acid and sugar content, along with significant proteome differences involving carbon and nitrogen metabolism, mRNA splicing, protein translation and light harvesting. Together, our multi-cultivar, multi-omic analysis provides new insights into the molecular underpinnings of the diel growth and development landscape of kale, advancing our fundamental understanding of this nutritious leafy green super-food for horticulture/vertical farming applications.

Watermelon domestication was shaped by stepwise selection and regulation of the metabolome

Although crop domestication has greatly aided human civilization, the sequential domestication and regulation of most quality traits remain poorly understood. Here, we report the stepwise selection and regulation of major fruit quality traits that occurred during watermelon evolution. The levels of fruit cucurbitacins and flavonoids were negatively selected during speciation, whereas sugar and carotenoid contents were positively selected during domestication. Interestingly, fruit malic acid and citric acid showed the opposite selection trends during the improvement. We identified a novel gene cluster (CGC1, cucurbitacin gene cluster on chromosome 1) containing both regulatory and structural genes involved in cucurbitacin biosynthesis, which revealed a cascade of transcriptional regulation operating mechanisms. In the CGC1, an allele caused a single nucleotide change in ClERF1 binding sites (GCC-box) in the promoter of ClBh1, which resulted in reduced expression of ClBh1 and inhibition of cucurbitacin synthesis in cultivated watermelon. Functional analysis revealed that a rare insertion of 244 amino acids, which arose in C. amarus and became fixed in sweet watermelon, in ClOSC (oxidosqualene cyclase) was critical for the negative selection of cucurbitacins during watermelon evolution. This research provides an important resource for metabolomics-assisted breeding in watermelon and for exploring metabolic pathway regulation mechanisms.

Multi-omics revolution to promote plant breeding efficiency

Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under increasing pressure from the rising food demand of the rapidly growing world population and changing climate. To address these issues, improving high-yield and climate-resilient related-traits in crop breeding is an effective strategy. In recent years, advances in omics techniques, including genomics, transcriptomics, proteomics, and metabolomics, paved the way for accelerating plant/crop breeding to cope with the changing climate and enhance food production. Optimized omics and phenotypic plasticity platform integration, exploited by evolving machine learning algorithms will aid in the development of biological interpretations for complex crop traits. The precise and progressive assembly of desire alleles using precise genome editing approaches and enhanced breeding strategies would enable future crops to excel in combating the changing climates. Furthermore, plant breeding and genetic engineering ensures an exclusive approach to developing nutrient sufficient and climate-resilient crops, the productivity of which can sustainably and adequately meet the world's food, nutrition, and energy needs. This review provides an overview of how the integration of omics approaches could be exploited to select crop varieties with desired traits.

Pan-genome and multi-parental framework for high-resolution trait dissection in melon (Cucumis melo)

Linking genotype with phenotype is a fundamental goal in biology and requires robust data for both. Recent advances in plant-genome sequencing have expedited comparisons among multiple-related individuals. The abundance of structural genomic within-species variation that has been discovered indicates that a single reference genome cannot represent the complete sequence diversity of a species, leading to the expansion of the pan-genome concept. For high-resolution forward genetics, this unprecedented access to genomic variation should be paralleled and integrated with phenotypic characterization of genetic diversity. We developed a multi-parental framework for trait dissection in melon (Cucumis melo), leveraging a novel pan-genome constructed for this highly variable cucurbit crop. A core subset of 25 diverse founders (MelonCore25), consisting of 24 accessions from the two widely cultivated subspecies of C. melo, encompassing 12 horticultural groups, and 1 feral accession was sequenced using a combination of short- and long-read technologies, and their genomes were assembled de novo. The construction of this melon pan-genome exposed substantial variation in genome size and structure, including detection of ~300 000 structural variants and ~9 million SNPs. A half-diallel derived set of 300 F₂ populations, representing all possible MelonCore25 parental combinations, was constructed as a framework for trait dissection through integration with the pan-genome. We demonstrate the potential of this unified framework for genetic analysis of various melon traits, including rind color intensity and pattern, fruit sugar content, and resistance to fungal diseases. We anticipate that utilization of this integrated resource will enhance genetic dissection of important traits and accelerate melon breeding.

Hopomics: Humulus lupulus Brewing Cultivars Classification Based on LC-MS Profiling and Nested Feature Selection

Omics approaches in plant analysis find many different applications, from classification to new bioactive compounds discovery. Metabolomics seems to be one of the most informative ways of describing plants’ phenotypes, since commonly used methods such as liquid chromatography–mass spectrometry (LC-MS) and nuclear magnetic resonance spectroscopy (NMR) could provide a huge amount of information about samples. However, due to high efficiency, many disadvantages arise with the complexity of the experimental design. In the present work, we demonstrate an untargeted metabolomics pipeline with the example of a Humulus lupulus classification task. LC-MS profiling of brewing cultivars samples was carried out as a starting point. Hierarchical cluster analysis (HCA)-based classification in combination with nested feature selection was provided for sample discrimination and marker compounds discovery. Obtained metabolome-based classification showed an expected difference compared to genetic-based classification data. Nine compounds were found to have the biggest classification power during nested feature selection. Using database search and molecular network construction, five of them were identified as known hops bitter compounds.

Conduction of a chemical structure-guided metabolic phenotype analysis method targeting phenylpropane pathway via LC-MS: Ginkgo biloba and soybean as examples

The phenylpropane pathway (PPP) is one of the most extensively investigated metabolic routes. This pathway biosynthesizes many important active ingredients such as phenylpropanoids and flavonoids that affect the flavor, taste and nutrients of food. How to elucidate the metabolic phenotype of PPP is fundamental in food research and development. In this study, we designed a structural periodical table filled with 103 metabolites produced from PPP. All of them especially the 62 structural isomers were qualified and quantified with high resolution and sensitivity via multiple reaction mode in liquid chromatography tandem triple quadrupole mass spectrometry. Ginkgo biloba and soybean were used as samples for the practical application of this method: The delicate spatial-temporal metabolic balance of PPP from ginkgo biloba has been first elucidated; It is first confirmed that the salt and draught stresses could redirect the biosynthesis trend of PPP to produce more isoflavones in soybean leaves.

Spanish Melon Landraces: Revealing Useful Diversity by Genomic, Morphological, and Metabolomic Analysis

Spain is a secondary centre of the diversification of the melon (Cucumis melo L.), with high diversity represented in highly appreciated landraces belonging to the Flexuosus and Ibericus groups. A collection of 47 accessions of Flexuosus, Chate, Piel de Sapo, Tendral, Amarillo, Blanco, and Rochet was analysed using a genotyping-by-sequencing (GBS) approach. A total of 66,971 quality SNPs were identified. Genetic analysis differentiated Ibericus accessions and exotic materials (Ameri, Momordica, Kachri, and Agrestis), while Flexuous accessions shared ancestry between them. Within the Ibericus group, no clear genomic distinction could be identified for the different landraces evaluated, with accessions of different landraces showing high genetic similarity. The morphological characterization confirmed that the external colour and fruit shape had been used as recognition patterns for Spanish melon landraces, but variability within a landrace exists. Differences were found in the sugars and acid and volatile profiles of the materials. Flexuosus and Chate melons at the immature commercial stage accumulated malic acid and low levels of hexoses, while Ibericus melons accumulated high contents of sucrose and citric acid. Specific trends could be identified in the Ibericus landraces. Tendral accumulated low levels of sugars and citric acid and high of malic acid, maintaining higher firmness, Rochet reached higher levels of sugars, and Amarillo tended to lower malic acid contents. Interestingly, high variability was found within landraces for the acidic profile, offering possibilities to alter taste tinges. The main volatile organic compounds (VOCs) in Flexuosus and Chate were aldehydes and alcohols, with clear differences between both groups. In the Ibericus landraces, general trends for VOC accumulation could be identified, but, again, a high level of variation exists. This situation highlights the necessity to develop depuration programs to promote on-farm in situ conservation and, at the same time, offers opportunities to establish new breeding program targets and to take advantage of these sources of variation.

Recent applications of metabolomics in plant breeding

Metabolites play a central role in maintaining organismal life and in defining crop phenotypes, such as nutritional value, fragrance, color, and stress resistance. Among the 'omes' in biology, the metabolome is the closest to the phenotype. Consequently, metabolomics has been applied to crop improvement as method for monitoring changes in chemical compositions, clarifying the mechanisms underlying cellular functions, discovering markers and diagnostics, and phenotyping for mQTL, mGWAS, and metabolite-genome predictions. In this review, 359 reports of the most recent applications of metabolomics to plant breeding-related studies were examined. In addition to the major crops, more than 160 other crops including rare medicinal plants were considered. One bottleneck associated with using metabolomics is the wide array of instruments that are used to obtain data and the ambiguity associated with metabolite identification and quantification. To further the application of metabolomics to plant breeding, the features and perspectives of the technology are discussed.

Comparative metabolite fingerprinting of chia, flax and sesame seeds using LC-MS untargeted metabolomics

Chia, flax, and sesame seeds are well known for their nutritional quality and are commonly included in bakery products. So far, the development of methods to verify their presence and authenticity in foods is a requisite and a raised need. In this work we applied untargeted metabolomics to propose authenticity markers. Seeds were analyzed by HPLC-MS/MS and 9938 features in negative mode and 9044 in positive mode were obtained by Mzmine. After isotopes grouping, alignment, gap-filling, filtering adducts, and normalization, PCA was applied to explore the dataset and recognize pre-existent classification patterns. OPLS-DA analysis and S-Plots were used as supervised methods. Twenty-five molecules (12 in negative mode and 13 in positive mode) were selected as discriminant for the three seeds, polyphenols and lignans were identified among them. To the best of our knowledge, this is the first approach using non-target HPLC-MS/MS for the authentication of chia, flax and sesame seeds.

Cantaloupe melon genome reveals 3D chromatin features and structural relationship with the ancestral cucurbitaceae karyotype

Cucumis melo displays a large diversity of horticultural groups with cantaloupe melon the most cultivated type. Using a combination of single-molecule sequencing, 10X Genomics link-reads, high-density optical and genetic maps, and chromosome conformation capture (Hi-C), we assembled a chromosome scale C. melo var. cantalupensis Charentais mono genome. Integration of RNA-seq, MeDip-seq, ChIP-seq, and Hi-C data revealed a widespread compartmentalization of the melon genome, segregating constitutive heterochromatin and euchromatin. Genome-wide comparative and evolutionary analysis between melon botanical groups identified Charentais mono genome increasingly more divergent from Harukei-3 (reticulatus), Payzawat (inodorus), and HS (ssp. agrestis) genomes. To assess the paleohistory of the Cucurbitaceae, we reconstructed the ancestral Cucurbitaceae karyotype and compared it to sequenced cucurbit genomes. In contrast to other species that experienced massive chromosome shuffling, melon has retained the ancestral genome structure. We provide comprehensive genomic resources and new insights in the diversity of melon horticultural groups and evolution of cucurbits.

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We provide a chromosome scale C. melo var. cantalupensis Charentais mono genome

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Epigenomic analysis revealed a widespread compartmentalization of the melon genome

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We reconstructed the ancestral Cucurbitaceae karyotype

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Melon has retained the ancestral Cucurbitaceae genome structure

Genome-Wide SNP Markers for Genotypic and Phenotypic Differentiation of Melon (Cucumis melo L.) Varieties Using Genotyping-by-Sequencing

Melon (Cucumis melo L.) is an economically important horticultural crop with abundant morphological and genetic variability. Complex genetic variations exist even among melon varieties and remain unclear to date. Therefore, unraveling the genetic variability among the three different melon varieties, muskmelon (C. melo subsp. melo), makuwa (C. melo L. var. makuwa), and cantaloupes (C. melo subsp. melo var. cantalupensis), could provide a basis for evolutionary research. In this study, we attempted a systematic approach with genotyping-by-sequencing (GBS)-derived single nucleotide polymorphisms (SNPs) to reveal the genetic structure and diversity, haplotype differences, and marker-based varieties differentiation. A total of 6406 GBS-derived SNPs were selected for the diversity analysis, in which the muskmelon varieties showed higher heterozygote SNPs. Linkage disequilibrium (LD) decay varied significantly among the three melon varieties, in which more rapid LD decay was observed in muskmelon (r² = 0.25) varieties. The Bayesian phylogenetic tree provided the intraspecific relationships among the three melon varieties that formed, as expected, individual clusters exhibiting the greatest genetic distance based on the posterior probability. The haplotype analysis also supported the phylogeny result by generating three major networks for 48 haplotypes. Further investigation for varieties discrimination allowed us to detect a total of 52 SNP markers that discriminated muskmelon from makuwa varieties, of which two SNPs were converted into cleaved amplified polymorphic sequence markers for practical use. In addition to these markers, the genome-wide association study identified two SNPs located in the genes on chromosome 6, which were significantly associated with the phenotypic traits of melon seed. This study demonstrated that a systematic approach using GBS-derived SNPs could serve to efficiently classify and manage the melon varieties in the genebank.

Investigation of the characteristics of different shrimps by species and habitat using gas chromatography/mass spectrometry based metabolomics

Approximately 6.5 million tons of shrimp are consumed annually worldwide. The price of shrimp is greatly influenced by species and habitat (e.g., farmed vs wild-caught). In recent years, false labeling has become a problem in the shrimp industry. False labeling can include species, habitat (whether farmed or wild-caught). This problem is motivated by the potential for economic benefit, and significantly reduces the consumer reliability of food. As a first step in establishing a detection method, we took a metabolomics approach to elucidate phenotypic diversity by assessing genetic differences and environmental factors. Metabolites identified by gas chromatography/mass spectrometry (GC/MS) analysis were subjected to multivariate analysis to identify metabolites that correlated with shrimp species and habitat. The characteristics based on species and habitat were observed respectively. For species, the classification approximately tended to be based on taxonomy. It suggests that species different have strong effect on metabolite profiles. In particular, the difference between Panaediae and Pandalidae was significantly observed, and some fatty acids such as palmitoleic acid and elaidic acid are abundant in Pandalidae. Among Pandalidae, Japanese tiger shrimp was characterized by metabolites related to purine metabolism. For habitat, farmed shrimp had a high amino acid content, and wild caught shrimp had a high fatty acid content. Habitat-based separation was observed in Indonesian black tiger shrimp samples, indicating that metabolites such as glycolic acid, phosphate, and pentadecanoic acid are characteristic components of natural black tiger shrimp.

Phenylpropanoid Metabolism in Astringent and Nonastringent Persimmon (Diospyros kaki) Cultivars Determines Sensitivity to Alternaria Infection

Fruits of nonastringent persimmon cultivars, as compared to astringent ones, were more resistant to Alternaria infection despite having lower polyphenol content. Metabolic analysis from the pulp of nonastringent "Shinshu", as compared to the astringent "Triumph", revealed a higher concentration of salicylic, coumaric, quinic, 5-o-feruloyl quinic, ferulic acids, β-glucogallin, gallocatechin, catechin, and procyanidins. Selected compounds like salicylic, ferulic, and ρ-coumaric acids inhibited in vitro Alternaria growth, and higher activity was demonstrated for methyl ferulic and methyl ρ-coumaric acids. These compounds also reduced in vivo Alternaria growth and the black spot disease in stored fruits. On the other hand, methyl gallic acid was a predominant compound in the "Triumph" pulp, as compared to the "Shinshu" pulp, and it augmented Alternaria growth in vitro and in vivo. Our results might explain the high sensitivity of the cultivar "Triumph" to Alternaria. It also emphasizes that specific phenolic compounds, and not the total phenol, affect susceptibility to fungal infection.

Cross-Species Comparison of Metabolomics to Decipher the Metabolic Diversity in Ten Fruits

Fruits provide humans with multiple kinds of nutrients and protect humans against worldwide nutritional deficiency. Therefore, it is essential to understand the nutrient composition of various fruits in depth. In this study, we performed LC-MS-based non-targeted metabolomic analyses with ten kinds of fruit, including passion fruit, mango, starfruit, mangosteen, guava, mandarin orange, grape, apple, blueberry, and strawberry. In total, we detected over 2500 compounds and identified more than 300 nutrients. Although the ten fruits shared 909 common-detected compounds, each species accumulated a variety of species-specific metabolites. Additionally, metabolic profiling analyses revealed a constant variation in each metabolite’s content across the ten fruits. Moreover, we constructed a neighbor-joining tree using metabolomic data, which resembles the single-copy protein-based phylogenetic tree. This indicates that metabolome data could reflect the genetic relationship between different species. In conclusion, our work enriches knowledge on the metabolomics of fruits, and provides metabolic evidence for the genetic relationships among these fruits.

Genetic dissection of aroma biosynthesis in melon and its relationship with climacteric ripening

Aroma is an essential trait in melon fruit quality, but its complexity and genetic basis are still poorly understood. The aim of this study was the identification of quantitative trait loci (QTLs) underlying volatile organic compounds (VOCs) biosynthesis in melon rind and flesh, using a Recombinant Inbred Line (RIL) population from the cross 'Piel de Sapo' (PS) × 'Védrantais' (VED), two commercial varieties segregating for ripening behavior. A total of 82 VOCs were detected by gas chromatography-mass spectrometry (GC-MS), and 166 QTLs were identified. The main QTL cluster was on chromosome 8, collocating with the previously described ripening-related QTL ETHQV8.1, with an important role in VOCs biosynthesis. QTL clusters involved in esters, lipid-derived volatiles and apocarotenoids were also identified, and candidate genes have been proposed for ethyl 3-(methylthio)propanoate and benzaldehyde biosynthesis. Our results provide genetic insights for deciphering fruit aroma in melon and offer new tools for flavor breeding.

Transition of aromatic volatile and transcriptome profiles during melon fruit ripening

Melon (Cucumis melo L.) is an important diploid crop with a wide variety of flavors due to its distinct aromatic volatile organic compounds (VOC). To understand the development of VOC profiles during fruit development, we performed metabolomic and transcriptomic analysis of two cantaloupe varieties over the course of fruit development. A total of 130 metabolites were detected in fruit samples, and 449014207 reads were mapped to the melon genome. A total of 4469 differentially expressed genes in fruits were identified and used to visualize the transition of VOC and transcriptomic profiles during the fruit development. A shift of VOC profiles in both varieties was observed from early-fruit profiles enriched in C5-C8 lipid-derived VOCs to late-fruit profiles abundant in C9 lipid-derived VOCs, apocarotenoids, and esters. The shift coincided with the expression of specific isoforms of lipid and carotenoid metabolizing enzymes as well as transcription factors involved in fruit ripening, metabolite regulation, and hormone signaling.

Comparative Metabolomic Profiling of Citrullus spp. Fruits Provides Evidence for Metabolomic Divergence during Domestication

Watermelon (Citrullus lanatus) is one of the most nutritional fruits that is widely distributed in the whole world. The nutritional compositions are mainly influenced by the genotype and environment. However, the metabolomics of different domestication status and different flesh colors watermelon types is not fully understood. In this study, we reported an extensive assessment of metabolomic divergence in the fruit flesh among Citrullus sp. and within Citrullus sp. We demonstrate that metabolic profiling was significantly different between the wild and cultivated watermelons, the apigenin 6-C-glucoside, luteolin 6-C-glucoside, chrysoeriol C-hexoside, naringenin C-hexoside, C-pentosyl-chrysoeriol O-hexoside, and sucrose are the main divergent metabolites. Correlation analysis results revealed that flavonoids were present in one tight metabolite cluster. The main divergent metabolites in different flesh-colored cultivated watermelon fruits are p-coumaric acid, 2,3-dihydroflavone, catechin, N-(3-indolylacetyl)-l-alanine, 3,4-dihydroxycinnamic acid, and pelargonidin o-hexoside. A total of 431 differentially accumulated metabolites were identified from pairwise comparative analyses. C. lanatus edible-seed watermelon (cultivars) and C. mucosospermus (wild) have similar fruit metabolic profiles and phenotypic traits, indicating that edible-seed watermelon may be a relative of wild species and a relatively primitive differentiation type of cultivated watermelon. Our data provide extensive knowledge for metabolomics-based watermelon improvement of Citrullus fruits meet their enhanced nutritive properties or upgraded germplasm utility values.

Towards superior plant-based foods using metabolomics

Metabolomics is proving a useful approach for many of the main future goals in agronomy and food production such as sustainability/crop resilience, food quality, safety, storage, and nutrition. Targeted and/or untargeted small-molecule analysis, coupled to chemometric analysis, has already unveiled a great deal of the complexity of plant-based foods, but there is still 'dark matter' to be discovered. Moreover, state-of-the-art food metabolomics offers insights into the molecular mechanisms underlying sensorial and nutritional characteristics of foods and thus enables higher precision and speed. This review describes recent applications of food metabolomics from fork to farm and focuses on the opportunities these bring to continue food innovation and support the shift to plant-based foods.

Melon Genetic Resources Characterization for Rind Volatile Profile

A melon core collection was analyzed for rind volatile compounds as, despite the fact that they are scarcely studied, these compounds play an important role in consumer preferences. Gas chromatography coupled to mass spectrometry allowed the detection of 171 volatiles. The high volatile diversity found was analyzed by Hierarchical Cluster Analysis (HCA), giving rise to two major clusters of accessions. The first cluster included climacteric and aromatic types such as Cantalupensis, Ameri, Dudaim and Momordica, rich in esters; the second one mainly included non-climacteric non-aromatic types such as Inodorus, Flexuosus, Acidulus, Conomon and wild Agrestis, with low volatiles content, specifically affecting esters. Many interesting accessions were identified, with different combinations of aroma profiles for rind and flesh, such as Spanish Inodorus landraces with low aroma flesh but rind levels of esters similar to those in climacteric Cantalupensis, exotic accessions sharing high contents of specific compounds responsible for the unique aroma of Dudaim melons or wild Agrestis with unexpected high content of some esters. Sesquiterpenes were present in rinds of some Asian Ameri and Momordica landraces, and discriminate groups of cultivars (sesquiterpene-rich/-poor) within each of the two most commercial melon horticultural groups (Cantalupensis and Inodorus), suggesting that the Asian germplasm is in the origin of specific current varieties or that this feature has been introgressed more recently from Asian sources. This rind characterization will encourage future efforts for breeding melon quality as many of the characterized landraces and wild accessions have been underexploited.

Special Issue on "Fruit Metabolism and Metabolomics"

Over the past 10 years, knowledge about several aspects of fruit metabolism has been greatly improved. Notably, high-throughput metabolomic technologies have allowed quantifying metabolite levels across various biological processes, and identifying the genes that underly fruit development and ripening. This Special Issue is designed to exemplify the current use of metabolomics studies of temperate and tropical fruit for basic research as well as practical applications. It includes articles about different aspects of fruit biochemical phenotyping, fruit metabolism before and after harvest, including primary and specialized metabolisms, and bioactive compounds involved in growth and environmental responses. The effect of genotype, stages of development or fruit tissue on metabolomic profiles and corresponding metabolism regulations are addressed, as well as the combination of other omics with metabolomics for fruit metabolism studies.