{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T05:25:49Z","timestamp":1777526749911,"version":"3.51.4"},"reference-count":99,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,9,12]],"date-time":"2022-09-12T00:00:00Z","timestamp":1662940800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Department of Agriculture and Agriculture and Animal Health, University of South Africa"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CIMB"],"abstract":"<jats:p>Global demand for soybean and its products has stimulated research into the production of novel genotypes with higher yields, greater drought and disease tolerance, and shorter growth times. Genetic research may be the most effective way to continue developing high-performing cultivars with desirable agronomic features and improved nutritional content and seed performance. Metabolomics, which predicts the metabolic marker for plant performance under stressful conditions, is rapidly gaining interest in plant breeding and has emerged as a powerful tool for driving crop improvement. The development of increasingly sensitive, automated, and high-throughput analytical technologies, paired with improved bioinformatics and other omics techniques, has paved the way for wide characterization of genetic characteristics for crop improvement. The combination of chromatography (liquid and gas-based) with mass spectrometry has also proven to be an indisputable efficient platform for metabolomic studies, notably plant metabolic fingerprinting investigations. Nevertheless, there has been significant progress in the use of nuclear magnetic resonance (NMR), capillary electrophoresis, and Fourier-transform infrared spectroscopy (FTIR), each with its own set of benefits and drawbacks. Furthermore, utilizing multivariate analysis, principal components analysis (PCA), discriminant analysis, and projection to latent structures (PLS), it is possible to identify and differentiate various groups. The researched soybean varieties may be correctly classified by using the PCA and PLS multivariate analyses. As metabolomics is an effective method for evaluating and selecting wild specimens with desirable features for the breeding of improved new cultivars, plant breeders can benefit from the identification of metabolite biomarkers and key metabolic pathways to develop new genotypes with value-added features.<\/jats:p>","DOI":"10.3390\/cimb44090287","type":"journal-article","created":{"date-parts":[[2022,9,12]],"date-time":"2022-09-12T20:52:25Z","timestamp":1663015945000},"page":"4181-4196","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Metabolomics as a Prospective Tool for Soybean (Glycine max) Crop Improvement"],"prefix":"10.3390","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6278-3774","authenticated-orcid":false,"given":"Efficient","family":"Ncube","sequence":"first","affiliation":[{"name":"Department of Agriculture and Animal Health, College of Agriculture and Environmental Sciences, University of South Africa, Science Campus, Private Bag x 6, Florida, Johannesburg 1710, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2259-6995","authenticated-orcid":false,"given":"Keletso","family":"Mohale","sequence":"additional","affiliation":[{"name":"Department of Agriculture and Animal Health, College of Agriculture and Environmental Sciences, University of South Africa, Science Campus, Private Bag x 6, Florida, Johannesburg 1710, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Noluyolo","family":"Nogemane","sequence":"additional","affiliation":[{"name":"Department of Agriculture and Animal Health, College of Agriculture and Environmental Sciences, University of South Africa, Science Campus, Private Bag x 6, Florida, Johannesburg 1710, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.jchromb.2013.02.036","article-title":"Metabolomic profiling of the response of susceptible and resistant soybean strains to foxglove aphid, Aulacorthum solani Kaltenbach","volume":"925","author":"Sato","year":"2013","journal-title":"J. Chromatogr. B"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Feng, Z., Ding, C., Li, W., Wang, D., and Cui, D. (2019). Applications of Metabolomics in the Research of Soybean Plant under Abiotic Stress, Elsevier Ltd.","DOI":"10.1016\/j.foodchem.2019.125914"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1007\/s00344-016-9654-6","article-title":"Metabolomics analysis reveals the salt-tolerant mechanism in Glycine soja","volume":"36","author":"Yang","year":"2017","journal-title":"J. Plant Growth Regul."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"7226","DOI":"10.1021\/jf101221t","article-title":"Exogenous gibberellic acid reprograms soybean to higher growth and salt stress tolerance","volume":"58","author":"Muhammad","year":"2010","journal-title":"J. Agric. Food Chem."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1007\/s11104-020-04715-w","article-title":"Metabolomic analysis of night-released soybean root exudates under high- and low-K conditions","volume":"456","author":"Shinano","year":"2020","journal-title":"Plant Soil"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"110550","DOI":"10.1016\/j.plantsci.2020.110550","article-title":"Cover crops, hormones and herbicides: Priming an integrated weed management strategy","volume":"301","author":"Oliveira","year":"2020","journal-title":"Plant Sci."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Razzaq, A., Wishart, D.S., Wani, S.H., Hameed, M.K., Mubin, M., and Saleem, F. (2022). Advances in metabolomics-driven diagnostic breeding and crop improvement. Metabolites, 12.","DOI":"10.3390\/metabo12060511"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3082","DOI":"10.1038\/srep03082","article-title":"Assessment of genetically modified soybean in relation to natural variation in the soybean seed metabolome","volume":"3","author":"Clarke","year":"2013","journal-title":"Sci. Rep."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.chroma.2008.05.018","article-title":"Comparative metabolomic study of transgenic versus conventional soybean using capillary electrophoresis-time-of-flight mass spectrometry","volume":"1195","author":"Dinelli","year":"2008","journal-title":"J. Chromatogr. A"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Padgette, S.R., Re, D.B., Barry, G.F., Eichholtz, D.E., Xavier, D., Fuchs, R.L., Kishore, G.M., and Fraley, R.T. (2018). New weed control opportunities: Development of soybeans with a Roundup Ready\u2122 gene. Herbicide\u2013Resistant Crops, CRC Press.","DOI":"10.1201\/9781351073196-4"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.pestbp.2011.12.004","article-title":"Physiological effects of glyphosate over amino acid profile in conventional and transgenic soybean (Glycine max)","volume":"102","author":"Alberto","year":"2012","journal-title":"Pestic. Biochem. Physiol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4611","DOI":"10.1021\/jf073087h","article-title":"Composition of Grain, forage, and processed fractions from second-generation glyphosate-tolerant soybean, MON 89788, Is equivalent to that of conventional soybean (Glycine max L.)","volume":"2006","author":"Lundry","year":"2008","journal-title":"J. Agric. Food Chem."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Chaudhary, J., Deshmukh, R., Mir, Z.A., and Bhat, J.A. (2019). Metabolomics: An Emerging Technology for Soybean Improvement, Springer International Publishing.","DOI":"10.1007\/978-3-319-92399-4_12"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2367","DOI":"10.1038\/s41598-018-20919-8","article-title":"Impact of overexpression of cytosolic isoform of O-acetylserine sulfhydrylase on soybean nodulation and nodule metabolome","volume":"8","author":"Krishnan","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1007\/s11306-014-0640-3","article-title":"Metabolomics investigation of flavonoid synthesis in soybean leaves depending on the growth stage","volume":"10","author":"Hyung","year":"2014","journal-title":"Metabolomics"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.foodchem.2018.05.048","article-title":"Untargeted metabolite profiling for koji-fermentative bioprocess unravels the effects of varying substrate types and microbial inocula","volume":"266","author":"Seo","year":"2018","journal-title":"Food Chem."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Nahar, K., Hasanuzzaman, M., and Fujita, M. (2016). Heat Stress Responses and Thermotolerance in Soybean, Elsevier Inc.","DOI":"10.1016\/B978-0-12-801536-0.00012-8"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.foodchem.2016.08.113","article-title":"Mass-based metabolomic analysis of soybean sprouts during germination","volume":"217","author":"Gu","year":"2017","journal-title":"Food Chem."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Kwon, Y.S., Lee, S., Lee, S.H., Kim, H.J., and Lee, C.H. (2019). Comparative evaluation of six traditional fermented soybean products in East Asia: A metabolomics approach. Metabolites, 9.","DOI":"10.3390\/metabo9090183"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"5773","DOI":"10.1021\/acs.jafc.6b01675","article-title":"Distinctive metabolism of flavonoid between cultivated and semi-wild soybean unveiled through metabolomics approach","volume":"64","author":"Yun","year":"2016","journal-title":"J. Agric. Food Chem."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1752","DOI":"10.1021\/acsomega.9b03668","article-title":"Metabolomics to characterize adaptive and signaling responses in legume crops under abiotic stresses","volume":"5","author":"Bueno","year":"2020","journal-title":"ACS Omega"},{"key":"ref_22","unstructured":"Demers, L.C. (2020). Comparative functional genomics characterization of low phytic acid soybeans and virus resistant soybeans. [Ph.D. Dissertation, Virginia Polytechnic Institute and State University]."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Schmidt, M.A., and Herman, E.M. (2018). Characterization and functional biology of the soybean aleurone layer. BMC Plant Biol., 8.","DOI":"10.1186\/s12870-018-1579-8"},{"key":"ref_24","first-page":"17","article-title":"Recent advances in chemometric methods for plant metabolomics: A review","volume":"914","author":"Yi","year":"2014","journal-title":"Biotechnol. Adv."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.cbpa.2016.12.006","article-title":"Frontiers of high-throughput metabolomics","volume":"36","author":"Zampieri","year":"2017","journal-title":"Curr. Opin. Chem. Biol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"8909","DOI":"10.1007\/s00253-018-9261-5","article-title":"Characterization of oil-producing yeast Lipomyces starkeyi on glycerol carbon source based on metabolomics and 13C-labeling","volume":"102","author":"Maruyama","year":"2018","journal-title":"Appl. Microbiol. Biotechnol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1590\/sajs.2013\/20120005","article-title":"Plant metabolomics: A new frontier in phytochemical analysis","volume":"109","author":"Tugizimana","year":"2013","journal-title":"S. Afr. J. Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1111\/j.1469-8137.2005.01632.x","article-title":"Plant metabolomics: From holistic hope, to hype, to hot topic","volume":"169","author":"Hall","year":"2006","journal-title":"New Phytol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"508","DOI":"10.1016\/j.tplants.2006.08.007","article-title":"Plant metabolomics: Towards biological function and mechanism","volume":"11","author":"Schauer","year":"2006","journal-title":"Trends Plant Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1002\/cem.2624","article-title":"Chemometrics for the analysis of chromatographic data in metabolomics investigations","volume":"28","author":"Cook","year":"2014","journal-title":"J. Chemom."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Djande, C.Y.H., Pretorius, C., Tugizimana, F., Piater, L.A., and Dubery, I.A. (2020). Metabolomics: A Tool for Cultivar phenotyping and investigation of grain crops. Agronomy, 10.","DOI":"10.3390\/agronomy10060831"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"S13","DOI":"10.1186\/1477-5956-11-S1-S13","article-title":"Gaussian process regression model for normalization of LC-MS data using scan-level information","volume":"11","author":"Ranjbar","year":"2013","journal-title":"Proteome Sci."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.aca.2017.05.011","article-title":"Quantitative NMR analysis of intra- and extracellular metabolism of mammalian cells: A tutorial","volume":"980","author":"Kostidis","year":"2017","journal-title":"Anal. Chim. Acta"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Nandania, J., Peddinti, G., Pessia, A., Kokkonen, M., and Velagapudi, V. (2018). Validation and automation of a high-throughput multitargeted method for semiquantification of endogenous metabolites from different biological matrices using tandem mass spectrometry. Metabolites, 8.","DOI":"10.1101\/352468"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.copbio.2014.08.006","article-title":"High-throughput discovery metabolomics","volume":"31","author":"Fuhrer","year":"2015","journal-title":"Curr. Opin. Biotechnol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.trac.2018.02.005","article-title":"Trends in analytical chemistry recent advances in biological sample preparation methods coupled with chromatography, spectrometry and electrochemistry analysis techniques","volume":"102","author":"Niu","year":"2018","journal-title":"Trends Anal. Chem."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2369","DOI":"10.1002\/pmic.201400255","article-title":"Le Basics of mass spectrometry based metabolomics","volume":"14","author":"Antignac","year":"2014","journal-title":"Proteomics"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"3808","DOI":"10.1002\/jssc.201700675","article-title":"Preparative isolation of flavonoid glycosides from Sphaerophysa salsula using hydrophilic interaction solid-phase extraction coupled with two-dimensional preparative liquid chromatography","volume":"40","author":"Jiao","year":"2017","journal-title":"J. Sep. Sci."},{"key":"ref_39","first-page":"23","article-title":"Proximate analysis, physicochemical properties and chemical constituents characterization of Moringa oleifera (Moringaceae) seed oil using GC-MS Analysis","volume":"6","author":"Adegbe","year":"2016","journal-title":"Am. J. Chem."},{"key":"ref_40","first-page":"1","article-title":"The effect of temperature on pressurised hot water extraction of pharmacologically important metabolites as analysed by UPLC-qTOF-MS and PCA. Evidence-based Complement","volume":"2014","author":"Khoza","year":"2014","journal-title":"Altern. Med."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Mohammed, N.K., Yazid, M., Manap, A., Tan, C.P., Muhialdin, B.J., Alhelli, A.M., Shobirin, A., and Hussin, M. (2016). The Effects of different extraction methods on antioxidant properties, chemical composition, and thermal behavior of black seed (Nigella sativa L.) oil. Evid. -Based Complementary Altern. Med., 2016.","DOI":"10.1155\/2016\/6273817"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Bragagnolo, F.S., Funari, C.S., Ib\u00e1\u00f1ez, E., and Cifuentes, A. (2021). Metabolomics as a tool to study underused soy parts: In search of bioactive compounds. Foods, 10.","DOI":"10.3390\/foods10061308"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Louie, K.B., Kosina, S.M., Hu, Y., Otani, H., de Raad, M., Kuftin, A.N., Mouncey, N.J., Bowen, B.P., and Northen, T.R. (2020). Mass spectrometry for natural product discovery. Comprehensive Natural Products III, Elsevier Ltd.","DOI":"10.1016\/B978-0-12-409547-2.14834-6"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1016\/j.phytol.2019.02.014","article-title":"Phytochemical analysis and biological activity of Lupinus luteus seeds extracts obtained by supercritical fluid extraction","volume":"30","author":"Buszewski","year":"2019","journal-title":"Phytochem. Lett."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2484","DOI":"10.1016\/j.chroma.2009.12.050","article-title":"Pressurized hot water extraction (PHWE)","volume":"1217","author":"Teo","year":"2010","journal-title":"J. Chromatogr. A"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1002\/mas.20108","article-title":"Mass spectrometry-based metabolomics","volume":"26","author":"Dettmer","year":"2007","journal-title":"Mass Spectrom. Rev."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1007\/s11306-013-0609-7","article-title":"Metabolite profiling and fingerprinting of Hypericum species: A comparison of MS and NMR metabolomics","volume":"10","author":"Porzel","year":"2014","journal-title":"Metabolomics"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fphar.2020.00219","article-title":"1H-NMR Metabolomics and LC-MS Analysis to determine seasonal variation in a cosmeceutical plant Leucosidea sericea","volume":"11","author":"Sehlakgwe","year":"2020","journal-title":"Front. Pharmacol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1002\/pca.1187","article-title":"An introduction to liquid chromatography\u2014mass spectrometry instrumentation applied in plant metabolomic analyses","volume":"21","author":"Allwood","year":"2010","journal-title":"Phytochem. Anal."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1038\/nprot.2013.004","article-title":"Liquid chromatography quadrupole time-of-flight mass spectrometry characterization of metabolites guided by the METLIN database","volume":"8","author":"Zhu","year":"2013","journal-title":"Nat. Protoc."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1038\/nrm.2016.25","article-title":"Metabolomics: Beyond biomarkers and towards mechanisms","volume":"17","author":"Johnson","year":"2016","journal-title":"Nat. Rev. Mol. Cell Biol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.jare.2014.10.003","article-title":"Two dimensional NMR spectroscopic approaches for exploring plant metabolome: A review","volume":"6","author":"Mahrous","year":"2015","journal-title":"J. Adv. Res."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1039\/C8FD00227D","article-title":"An integrated approach for mixture analysis using MS and NMR techniques","volume":"218","author":"Kuhn","year":"2019","journal-title":"Faraday Discuss"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1007\/s11816-015-0350-y","article-title":"Metabolomics-derived insights into the manipulation of terpenoid synthesis in Centella asiatica cells by methyl jasmonate","volume":"9","author":"Tugizimana","year":"2015","journal-title":"Plant Biotechnol. Rep."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1318","DOI":"10.1007\/s11306-014-0666-6","article-title":"Metabolic profiling by ultra-performance liquid chromatography-mass spectrometry and parallel factor analysis for the determination of disease biomarkers in Eucalyptus","volume":"10","author":"Hantao","year":"2014","journal-title":"Metabolomics"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.jbiosc.2013.01.004","article-title":"Current metabolomics. Technological advances","volume":"116","author":"Putri","year":"2013","journal-title":"J. Biosci. Bioeng."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1039\/c3np70086k","article-title":"Mass spectrometry in plant metabolomics strategies: From analytical platforms to data acquisition and processing","volume":"31","author":"Ernst","year":"2014","journal-title":"Nat. Prod. Rep."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Gika, H.G., Wilson, I.D., and Theodoridis, G.A. (2014). The Role of Mass Spectrometry in Nontargeted Metabolomic, Elsevier. [1st ed.].","DOI":"10.1016\/B978-0-444-62651-6.00009-X"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.chroma.2014.10.091","article-title":"Current approaches and challenges for the metabolite profiling of complex natural extracts","volume":"1382","author":"Wolfender","year":"2015","journal-title":"J. Chromatogr. A"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Van Den Berg, R.A., Hoefsloot, H.C.J., Westerhuis, J.A., Smilde, A.K., and Van DerWerf, M.J. (2006). Centering, scaling, and transformations: Improving the biological information content of metabolomics data. BMC Genomics, 7.","DOI":"10.1186\/1471-2164-7-142"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.chemolab.2011.03.010","article-title":"Algorithms and tools for the preprocessing of LC\u2014MS metabolomics data","volume":"108","author":"Castillo","year":"2011","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"2273","DOI":"10.1021\/ac504118y","article-title":"Avoiding misannotation of in-source fragmentation products as cellular metabolites in liquid chromatography-mass spectrometry-based metabolomics","volume":"87","author":"Xu","year":"2015","journal-title":"Anal. Chem."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/B978-0-12-385118-5.00016-5","article-title":"Plant metabolomics and its potential for systems biology research","volume":"Volume 500","author":"Allwood","year":"2011","journal-title":"Methods in Systems Biology"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1021\/pr060594q","article-title":"Chemometrics in metabonomics","volume":"6","author":"Trygg","year":"2007","journal-title":"J. Proteome Res."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1111\/j.1399-3054.2007.01001.x","article-title":"Metabolomic technologies and their application to the study of plants and plant\u2013host interactions","volume":"132","author":"Allwood","year":"2008","journal-title":"Physiol. Plant."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1007\/s11306-013-0598-6","article-title":"Reflections on univariate and multivariate analysis of metabolomics data","volume":"10","author":"Saccenti","year":"2014","journal-title":"Metabolomics"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"5767","DOI":"10.1007\/s00216-017-0523-3","article-title":"Optimized experimental workflow for tandem mass spectrometry molecular networking in metabolomics","volume":"409","author":"Olivon","year":"2017","journal-title":"Anal. Bioanal. Chem."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"D590","DOI":"10.1093\/nar\/gky962","article-title":"New approach for understanding genome variations in KEGG","volume":"47","author":"Kanehisa","year":"2019","journal-title":"Nucleic Acids Res."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1002\/pro.3711","article-title":"KEGG Mapper for inferring cellular functions from protein sequences","volume":"29","author":"Kanehisa","year":"2020","journal-title":"Protein Sci."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"42478","DOI":"10.1038\/srep42478","article-title":"Metabolomic tool to identify soybean [Glycine max (L.) Merrill] germplasms with a high level of shade tolerance at the seedling stage","volume":"7","author":"Liu","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_71","first-page":"73","article-title":"Recent Progress in the development of metabolome databases for plant systems biology. Front","volume":"4","author":"Fukushima","year":"2013","journal-title":"Plant Sci."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/s11306-007-0082-2","article-title":"Proposed minimum reporting standards for chemical analysis: Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI)","volume":"3","author":"Sumner","year":"2007","journal-title":"Metabolomics"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1007\/s00299-005-0054-9","article-title":"Metabolomics and its role in understanding cellular responses in plants","volume":"24","author":"Bhalla","year":"2005","journal-title":"Plant Cell Rep."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1111\/tpj.14719","article-title":"Metabolite\/phytohormone\u2014gene regulatory networks in soybean organs under dehydration conditions revealed by integration analysis","volume":"103","author":"Maruyama","year":"2020","journal-title":"Plant J."},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Silvente, S., Sobolev, A.P., and Lara, M. (2012). Metabolite adjustments in drought tolerant and sensitive soybean genotypes in response to water stress. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0038554"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11738-019-2939-1","article-title":"Metabolomics reveals the drought - tolerance mechanism in wild soybean (Glycine soja)","volume":"41","author":"Wang","year":"2019","journal-title":"Acta Physiol. Plant."},{"key":"ref_77","first-page":"79","article-title":"A tale of survival: Molecular defense mechanisms of soybean to overcome soybean mosaic virus infection physiological and molecular plant pathology. A tale of survival: Molecular defense mechanisms of soybean to overcome Soybean Mosaic Virus infection","volume":"102","author":"Cassone","year":"2017","journal-title":"Physiol. Mol. Plant Pathol."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1080\/1343943X.2018.1488539","article-title":"Development and validation of a GC\u2013MS method for soybean organ-specific metabolomics","volume":"21","author":"Hu","year":"2018","journal-title":"Plant Prod. Sci."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.envexpbot.2018.05.018","article-title":"Flooded soybean metabolomic analysis reveals important primary and secondary metabolites involved in the hypoxia stress response and tolerance","volume":"153","author":"Coutinho","year":"2018","journal-title":"Environ. Exp. Bot."},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Kang, W., Chen, L., Wang, Y., Zhu, X., Liu, X., and Duan, Y. (2020). Bacillus simplex treatment promotes soybean defence against soybean cyst nematodes: A metabolomics study using GC-MS. PLoS ONE, 15.","DOI":"10.1371\/journal.pone.0237194"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1007\/s00726-010-0809-7","article-title":"Differential responses of microsomal proteins and metabolites in two contrasting cadmium (Cd -accumulating soybean cultivars under Cd stress","volume":"42","author":"Ahsan","year":"2012","journal-title":"Amino Acids"},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Rabara, R.C., Tripathi, P., and Rushton, P.J. (2017). Comparative metabolome profile between tobacco and soybean grown under water-stressed conditions. Biomed Res. Int., 2017.","DOI":"10.1155\/2017\/3065251"},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"Das, A., Rushton, P.J., and Rohila, J.S. (2017). Metabolomic profiling of soybeans (Glycine max L.) Reveals the Importance of Sugar and Nitrogen. Plants, 6.","DOI":"10.3390\/plants6020021"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1016\/j.ecoenv.2018.08.062","article-title":"Ecotoxicology and environmental safety metabolomics analysis reveals potential mechanisms of tolerance to excess molybdenum in soybean seedlings","volume":"164","author":"Xu","year":"2018","journal-title":"Ecotoxicol. Environ. Saf."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.jplph.2018.07.009","article-title":"Photosynthetic characteristics and metabolic analyses of two soybean genotypes revealed adaptive strategies to low-nitrogen stress","volume":"229","author":"Li","year":"2018","journal-title":"J. Plant Physiol."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.plaphy.2018.03.002","article-title":"Metabolomics and its physiological regulation process reveal the salt- tolerant mechanism in Glycine soja seedling roots","volume":"126","author":"Jiao","year":"2018","journal-title":"Plant Physiol. Biochem."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.3389\/fpls.2017.01101","article-title":"Comparison of salt tolerance in Soja Based on metabolomics of seedling roots","volume":"8","author":"Li","year":"2017","journal-title":"Front. Plant Sci."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/j.plaphy.2016.07.025","article-title":"Effects of growth temperature and carbon dioxide enrichment on soybean seed components at different stages of development","volume":"108","author":"Xu","year":"2016","journal-title":"Plant Physiol. Biochem."},{"key":"ref_89","doi-asserted-by":"crossref","unstructured":"Copley, T.R., Aliferis, K.A., Kliebenstein, D.J., and Jabaji, S.H. (2017). An integrated RNAseq- 1 H NMR metabolomics approach to understand soybean primary metabolism regulation in response to Rhizoctonia foliar blight disease. BMC Plant Biol., 17.","DOI":"10.1186\/s12870-017-1020-8"},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"3723","DOI":"10.1007\/s12161-017-0929-8","article-title":"Metabolomic strategies based on High-Resolution Mass Spectrometry as a tool for recognition of GMO (MON 89788 Variety) and Non-GMO Soybean: A critical assessment of two complementary methods","volume":"10","author":"Hrbek","year":"2017","journal-title":"Food Anal. Methods"},{"key":"ref_91","first-page":"472","article-title":"Changes in the metabolome of two soybean genotypes under drought stress. Russ","volume":"67","author":"Fu","year":"2020","journal-title":"J. Plant Physiol."},{"key":"ref_92","doi-asserted-by":"crossref","unstructured":"Yang, A., Kong, L., Wang, H., Yao, X., Xie, F., and Wang, H. (2020). Response of soybean root to phosphorus deficiency under sucrose feeding: Insight from morphological and metabolome characterizations. BioMed Res. Int., 2020.","DOI":"10.1155\/2020\/2148032"},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.plaphy.2019.03.012","article-title":"Identifying the metabolomics and physiological differences among Soja in the early flowering stage","volume":"139","author":"Li","year":"2019","journal-title":"Plant Physiol. Biochem."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1007\/s00572-019-00909-y","article-title":"Metabolic responses to arbuscular mycorrhizal fungi are shifted in roots of contrasting soybean genotypes","volume":"29","author":"Salloum","year":"2019","journal-title":"Mycorrhiza"},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"2225","DOI":"10.1074\/mcp.RA119.001704","article-title":"Enhanced salt tolerance of rhizobia-inoculated soybean correlates with decreased phosphorylation of the transcription factor GmMYB183 and altered flavonoid biosynthesis enhanced salt tolerance of rhizobia- inoculated soybean correlates with decreased phos","volume":"18","author":"Pi","year":"2019","journal-title":"Mol. Cell. Proteom."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"e12404","DOI":"10.1111\/jfbc.12404","article-title":"Proteomic and metabolomic analysis of minimax and Williams 82 soybeans grown under two different conditions","volume":"41","author":"John","year":"2017","journal-title":"J. Food Biochem."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.envexpbot.2012.02.013","article-title":"Primed plants do not forget","volume":"94","author":"Pastor","year":"2012","journal-title":"Environ. Exp. Bot."},{"key":"ref_98","first-page":"714","article-title":"Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism","volume":"46","author":"Chen","year":"2014","journal-title":"Nat. Publ. Gr."},{"key":"ref_99","doi-asserted-by":"crossref","unstructured":"Yadav, C.B., Srivastava, R.K., Mur, L.A.J., and Yadav, R.S. (2021). Metabolite diversity and metabolic genome-wide marker traits in pearl millet grains. Cells, 10.","DOI":"10.3390\/cells10113076"}],"container-title":["Current Issues in Molecular Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1467-3045\/44\/9\/287\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:29:46Z","timestamp":1760142586000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1467-3045\/44\/9\/287"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,12]]},"references-count":99,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["cimb44090287"],"URL":"https:\/\/doi.org\/10.3390\/cimb44090287","relation":{},"ISSN":["1467-3045"],"issn-type":[{"value":"1467-3045","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,12]]}}}