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High-throughput Plant Metabolomics and Predictive Modelling

hal.structure.identifierPlateforme Bordeaux Metabolome
hal.structure.identifierBiologie du fruit et pathologie [BFP]
dc.contributor.authorBARROS SANTOS, Millena
hal.structure.identifierBiologie du fruit et pathologie [BFP]
dc.contributor.authorMIRANDE-NEY, Cathleen
hal.structure.identifierPontificia Universidad Católica de Chile [UC]
dc.contributor.authorDUSSARRAT, Thomas
hal.structure.identifierMetaToul Agromix
hal.structure.identifierLaboratoire de Recherche en Sciences Végétales [LRSV]
hal.structure.identifierMetaboHUB-MetaToul
dc.contributor.authorMARTI, Guillaume
hal.structure.identifierUniversité de Rennes - UFR Sciences de la vie et de l'environnement [UR SVE]
hal.structure.identifierPlateforme de Profilage Métabolique et de Métabolomique [P2M2]
hal.structure.identifierBiogenouest-Corsaire platform [Saint Gilles, France]
hal.structure.identifierMetaboHUB-Grand-Ouest
hal.structure.identifierInstitut de Génétique, Environnement et Protection des Plantes [IGEPP]
dc.contributor.authorBOUCHEREAU, Alain
hal.structure.identifierPlateforme de Profilage Métabolique et de Métabolomique [P2M2]
hal.structure.identifierInstitut de Génétique, Environnement et Protection des Plantes [IGEPP]
dc.contributor.authorDELLERO, Younès
hal.structure.identifierBiologie du fruit et pathologie [BFP]
hal.structure.identifierPlateforme Bordeaux Metabolome
dc.contributor.authorPRIGENT, Sylvain
hal.structure.identifierUniversité de Bordeaux [UB]
hal.structure.identifierInstitut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement [INRAE]
hal.structure.identifierPlateforme Bordeaux Metabolome
dc.contributor.authorPÉTRIACQ, Pierre
dc.date.issued2025-07-11
dc.description.abstractEnThis chapter explores advances and methodologies in high-throughput metabolic phenotyping through metabolomics and predictive modeling to enhance the understanding of plant metabolism. Key techniques, data analysis tools, and applications in plant science research are discussed. The potential of predictive modeling to identify new metabolic pathways and markers associated with plant performance and improve crop traits is highlighted. Future directions and challenges in the field are also examined.
dc.language.isoen
dc.publisherCABI
dc.publisher.locationGB
dc.source.titleHigh-Throughput Plant Metabolomics
dc.subject.enBioinformatics
dc.subject.endata science
dc.subject.enhigh-throughput phenotyping
dc.subject.enmetabolomics
dc.subject.enpredictive modeling
dc.title.enHigh-throughput Plant Metabolomics and Predictive Modelling
dc.typeChapitre d'ouvrage
dc.identifier.doi10.1079/9781800626911.0003
dc.subject.halSciences du Vivant [q-bio]
dc.subject.halInformatique [cs]
bordeaux.page38-66
bordeaux.title.proceedingHigh-Throughput Plant Metabolomics
hal.identifierhal-05191959
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-05191959v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.btitle=High-Throughput%20Plant%20Metabolomics&rft.date=2025-07-11&rft.spage=38-66&rft.epage=38-66&rft.au=BARROS%20SANTOS,%20Millena&MIRANDE-NEY,%20Cathleen&DUSSARRAT,%20Thomas&MARTI,%20Guillaume&BOUCHEREAU,%20Alain&rft.genre=unknown


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