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Model-assisted analysis for tuning anthocyanin composition in grape berries.

dc.rights.licenseopenen_US
dc.contributor.authorWANG, Yongjian
dc.contributor.authorSHANG, Boxing
dc.contributor.authorGÉNARD, Michel
hal.structure.identifierEcophysiologie et Génomique Fonctionnelle de la Vigne [UMR EGFV]
dc.contributor.authorHILBERT, Ghislaine
hal.structure.identifierEcophysiologie et Génomique Fonctionnelle de la Vigne [UMR EGFV]
dc.contributor.authorDELROT, Serge
IDREF: 058711503
hal.structure.identifierEcophysiologie et Génomique Fonctionnelle de la Vigne [UMR EGFV]
dc.contributor.authorGOMES, Eric
IDREF: 102208093
dc.contributor.authorPONI, Stefano
dc.contributor.authorKELLER, Markus
hal.structure.identifierEcophysiologie et Génomique Fonctionnelle de la Vigne [UMR EGFV]
dc.contributor.authorRENAUD, Christel
dc.contributor.authorKONG, Junhua
dc.contributor.authorCHEN, Jinliang
dc.contributor.authorLIANG, Zhenchang
dc.contributor.authorDAI, Zhanwu
dc.date.accessioned2024-02-05T13:38:30Z
dc.date.available2024-02-05T13:38:30Z
dc.date.issued2023-11-30
dc.identifier.issn1095-8290en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/187821
dc.description.abstractEnAnthocyanin composition is responsible for the red colour of grape berries and wines, and contributes to their organoleptic quality. However, anthocyanin biosynthesis is under genetic, developmental and environmental regulation, making its targeted fine-tuning challenging. We constructed a mechanistic model to simulate the dynamics of anthocyanin composition throughout grape ripening in Vitis vinifera, employing a consensus anthocyanin biosynthesis pathway. The model was calibrated and validated using six datasets from eight cultivars and 37 growth conditions. Tuning the transformation and degradation parameters allowed us to accurately simulate the accumulation process of each individual anthocyanin under different environmental conditions. The model parameters were robust across environments for each genotype. The coefficients of determination (R2) for the simulated versus observed values for the six datasets ranged from 0.92 to 0.99, while the relative root mean square errors (RRMSEs) were between 16.8 and 42.1 %. The leave-one-out cross-validation for three datasets showed R2 values of 0.99, 0.96 and 0.91, and RRMSE values of 28.8, 32.9 and 26.4 %, respectively, suggesting a high prediction quality of the model. Model analysis showed that the anthocyanin profiles of diverse genotypes are relatively stable in response to parameter perturbations. Virtual experiments further suggested that targeted anthocyanin profiles may be reached by manipulating a minimum of three parameters, in a genotype-dependent manner. This model presents a promising methodology for characterizing the temporal progression of anthocyanin composition, while also offering a logical foundation for bioengineering endeavours focused on precisely adjusting the anthocyanin composition of grapes.
dc.language.isoENen_US
dc.subject.enVitis
dc.subject.enAnthocyanins
dc.subject.enFruit
dc.subject.enWine
dc.title.enModel-assisted analysis for tuning anthocyanin composition in grape berries.
dc.title.alternativeAnn Boten_US
dc.typeArticle de revueen_US
dc.subject.halSciences du Vivant [q-bio]/Biologie végétale
dc.identifier.pubmed37850481en_US
bordeaux.journalAnnals of Botanyen_US
bordeaux.page1033-1050en_US
bordeaux.volume132en_US
bordeaux.hal.laboratoriesEcophysiologie et Génomique Fonctionnelle de la Vigne (EGFV) - UMR 1287en_US
bordeaux.issue5en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionBordeaux Sciences Agroen_US
bordeaux.institutionINRAEen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.import.sourcepubmed
hal.identifierhal-04563394
hal.version2
hal.date.transferred2024-04-30T23:04:00Z
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exporttrue
workflow.import.sourcepubmed
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Annals%20of%20Botany&rft.date=2023-11-30&rft.volume=132&rft.issue=5&rft.spage=1033-1050&rft.epage=1033-1050&rft.eissn=1095-8290&rft.issn=1095-8290&rft.au=WANG,%20Yongjian&SHANG,%20Boxing&G%C3%89NARD,%20Michel&HILBERT,%20Ghislaine&DELROT,%20Serge&rft.genre=article


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