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The aim of the present study was to comprehensively analyze and identify the metabolites of different varieties of raw peanut, as well as provide a reference for the utilization of different varieties of peanuts. In this study, three varieties of peanuts, namely ZKH1H, ZKH13H, and CFD, were investigated via ultrahigh-performance liquid chromatography (UPLC) and widely targeted metabolomics methods based on tandem mass spectrometry (MS) and solid-phase microextraction-gas chromatography–mass spectrometry (SPME-GC–MS). In total, 417 nonvolatile and 55 volatile substances were detected. The nonvolatile substances were classified into the following 10 categories: organic acids and derivatives (28.9%); organic oxygen compounds (21.9%); lipids and lipid-like molecules (12.6%); organoheterocyclic compounds (9.9%); nucleosides, nucleotides, and analogues (9.4%); benzenoids (7.8%); phenylpropanoids and polyketides (6.1%); organic nitrogen compounds (2.7%); lignans, neolignans, and related compounds (0.5%); and alkaloids and their derivatives (0.3%). The volatile compounds (VOCs) were classified into the following eight categories: organic oxygen compounds (24.1%); organic cyclic compounds (20.4%); organic nitrogen compounds (13%); organic acids and their derivatives (13%); lipids and lipid-like molecules (11.2%); benzenoids (11.1%); hydrocarbons (3.7%); and homogeneous non-metallic compounds (3.7%). Differentially abundant metabolites among the different peanut varieties (ZKH13H vs. CFD, ZKH1H vs. CFD, and ZKH1H vs. ZKH13H) were investigated via multivariate statistical analyses, which identified 213, 204, and 157 nonvolatile differentially abundant metabolites, respectively, and 12, 11, and 10 volatile differentially abundant metabolites, respectively. KEGG metabolic pathway analyses of the differential non-VOCs revealed that the most significant metabolic pathways among ZKH13H vs. CFD, ZKH1H vs. CFD, and ZKH1H vs. ZKH13H were galactose metabolism, purine metabolism, and aminoacyl-tRNA, while the nitrogen metabolism pathway was identified as a significant metabolic pathway for the VOCs. The present findings provide a theoretical foundation for the development and utilization of these three peanut species, as well as for the breeding of new peanut varieties. [ABSTRACT FROM AUTHOR]

The study investigated compounds present in the invasive grass Hordeum murinum L. subsp. murinum and tested the allelopathic potential of this plant against common meadow species Festuca rubra L. and Trifolium repens L. Gas chromatography–mass spectrometry (GC–MS) performed separately on the ears and stalks with leaves of wall barley revealed 32 compounds, including secondary metabolites, that may play an important role in allelopathy. Two compounds, N-butylbenzenesulfonamide (NBBS) and diphenylsulfone (DDS), were described for the first time for wall barley and the Poaceae family. The presence of 6,10,14-trimethylpentadecan-2-one (TMP) has also been documented. Aqueous extracts of H. murinum organs (ears and stalks with leaves) at concentrations of 2.5%, 5%, and 7.5% were used to evaluate its allelopathic potential. Compared to the control, all extracts inhibited germination and early growth stages of meadow species. The inhibitory effect was strongest at the highest concentration for both the underground and aboveground parts of the seedlings of the meadow species tested. Comparing the allelopathic effect, Trifolium repens proved to be more sensitive. In light of the results of the study, the removal of wall barley biomass appears to be important for the restoration of habitats where this species occurs due to its allelopathic potential. [ABSTRACT FROM AUTHOR]

The aim of the present study was to comprehensively analyze and identify the metabolites of different varieties of raw peanut, as well as provide a reference for the utilization of different varieties of peanuts. In this study, three varieties of peanuts, namely ZKH1H, ZKH13H, and CFD, were investigated via ultrahigh-performance liquid chromatography (UPLC) and widely targeted metabolomics methods based on tandem mass spectrometry (MS) and solid-phase microextraction-gas chromatography–mass spectrometry (SPME-GC–MS). In total, 417 nonvolatile and 55 volatile substances were detected. The nonvolatile substances were classified into the following 10 categories: organic acids and derivatives (28.9%); organic oxygen compounds (21.9%); lipids and lipid-like molecules (12.6%); organoheterocyclic compounds (9.9%); nucleosides, nucleotides, and analogues (9.4%); benzenoids (7.8%); phenylpropanoids and polyketides (6.1%); organic nitrogen compounds (2.7%); lignans, neolignans, and related compounds (0.5%); and alkaloids and their derivatives (0.3%). The volatile compounds (VOCs) were classified into the following eight categories: organic oxygen compounds (24.1%); organic cyclic compounds (20.4%); organic nitrogen compounds (13%); organic acids and their derivatives (13%); lipids and lipid-like molecules (11.2%); benzenoids (11.1%); hydrocarbons (3.7%); and homogeneous non-metallic compounds (3.7%). Differentially abundant metabolites among the different peanut varieties (ZKH13H vs. CFD, ZKH1H vs. CFD, and ZKH1H vs. ZKH13H) were investigated via multivariate statistical analyses, which identified 213, 204, and 157 nonvolatile differentially abundant metabolites, respectively, and 12, 11, and 10 volatile differentially abundant metabolites, respectively. KEGG metabolic pathway analyses of the differential non-VOCs revealed that the most significant metabolic pathways among ZKH13H vs. CFD, ZKH1H vs. CFD, and ZKH1H vs. ZKH13H were galactose metabolism, purine metabolism, and aminoacyl-tRNA, while the nitrogen metabolism pathway was identified as a significant metabolic pathway for the VOCs. The present findings provide a theoretical foundation for the development and utilization of these three peanut species, as well as for the breeding of new peanut varieties.

Ziniolide, xantholide B (11α-dihydroziniolide), and 11β-dihydroziniolide, three sesquiterpene lactones with 12,8-guaianolide skeletons, were identified as volatile metabolites from the roots of Xanthium spinosum L., an invasive plant harvested in Corsica. Essential oil, as well as hydrosol and hexane extracts, showed the presence of guaianolide analogues. The study highlights an analytical strategy involving column chromatography, GC-FID, GC-MS, NMR (1D and 2D), and the hemi-synthesis approach, to identify compounds with incomplete or even missing spectral data from the literature. Among them, we reported the 1H- and 13C-NMR data of 11β-dihydroziniolide, which was observed as a natural product for the first time. As secondary metabolites were frequently involved in the dynamic of the dispersion of weed species, the allelopathic effects of X. spinosum root's volatile metabolites were assessed on seed germination and seedling growth (leek and radish). Essential oil, as well as hydrosol- and microwave-assisted extracts inhibited germination and seedling growth; root metabolite phytotoxicity was demonstrated. Nevertheless, the phytotoxicity of root metabolites was demonstrated with a more marked selectivity to the benefit of the monocotyledonous species compared to the dicotyledonous species. Ziniolide derivatives seem to be strongly involved in allelopathic interactions and could be the key to understanding the invasive mechanisms of weed. [ABSTRACT FROM AUTHOR]

Ziniolide, xantholide B (11α-dihydroziniolide), and 11β-dihydroziniolide, three sesquiterpene lactones with 12,8-guaianolide skeletons, were identified as volatile metabolites from the roots of Xanthium spinosum L., an invasive plant harvested in Corsica. Essential oil, as well as hydrosol and hexane extracts, showed the presence of guaianolide analogues. The study highlights an analytical strategy involving column chromatography, GC-FID, GC-MS, NMR (1D and 2D), and the hemi-synthesis approach, to identify compounds with incomplete or even missing spectral data from the literature. Among them, we reported the 1H- and 13C-NMR data of 11β-dihydroziniolide, which was observed as a natural product for the first time. As secondary metabolites were frequently involved in the dynamic of the dispersion of weed species, the allelopathic effects of X. spinosum root’s volatile metabolites were assessed on seed germination and seedling growth (leek and radish). Essential oil, as well as hydrosol- and microwave-assisted extracts inhibited germination and seedling growth; root metabolite phytotoxicity was demonstrated. Nevertheless, the phytotoxicity of root metabolites was demonstrated with a more marked selectivity to the benefit of the monocotyledonous species compared to the dicotyledonous species. Ziniolide derivatives seem to be strongly involved in allelopathic interactions and could be the key to understanding the invasive mechanisms of weed.

Saccharomycopsis fibuligera KJJ81 isolated from nuruk is an amylolytic yeast that is widely used as a microbial starter in various fermented foods. Volatile and nonvolatile metabolites of S. fibuligera KJJ81 were investigated according to different carbon sources and cultivation times using a nontargeted metabolomic approach. Partial-least-squares discriminant analysis was applied to determine the major metabolites, which were found to be closely related to the clustering and discrimination of S. fibuligera KJJ81 samples. Some volatile metabolites derived from phenylalanine, such as 2-phenylethanol, 2-phenylethyl acetate, and ethyl phenylacetate, were predominantly found in cultivation medium containing glucose (YPD medium). In addition, the level of 2-phenylethanol increased continuously with the cultivation time. In terms of nonvolatile metabolites, carbohydrates (mannose, arabitol, and mannitol), fatty acids (palmitic acid and stearic acid), organic acids (oxalic acid and succinic acid), and amino acids (isoleucine, serine, alanine, glutamic acid, glycine, proline, phenylalanine, and threonine) were the main contributors to S. fibuligera KJJ81 samples cultivated in YPD medium according to cultivation time. These results show that the formation of volatile and nonvolatile metabolites of S. fibuligera KJJ81 can be significantly affected by both the carbon sources and the cultivation time.

Saccharomycopsis fibuligera KJJ81 isolated from nuruk is an amylolytic yeast that is widely used as a microbial starter in various fermented foods. Volatile and nonvolatile metabolites of S. fibuligera KJJ81 were investigated according to different carbon sources and cultivation times using a nontargeted metabolomic approach. Partial-least-squares discriminant analysis was applied to determine the major metabolites, which were found to be closely related to the clustering and discrimination of S. fibuligera KJJ81 samples. Some volatile metabolites derived from phenylalanine, such as 2-phenylethanol, 2-phenylethyl acetate, and ethyl phenylacetate, were predominantly found in cultivation medium containing glucose (YPD medium). In addition, the level of 2-phenylethanol increased continuously with the cultivation time. In terms of nonvolatile metabolites, carbohydrates (mannose, arabitol, and mannitol), fatty acids (palmitic acid and stearic acid), organic acids (oxalic acid and succinic acid), and amino acids (isoleucine, serine, alanine, glutamic acid, glycine, proline, phenylalanine, and threonine) were the main contributors to S. fibuligera KJJ81 samples cultivated in YPD medium according to cultivation time. These results show that the formation of volatile and nonvolatile metabolites of S. fibuligera KJJ81 can be significantly affected by both the carbon sources and the cultivation time. [ABSTRACT FROM AUTHOR]