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dc.contributor.authorZhu, J.en
dc.contributor.authorParker, Amberen
dc.contributor.authorGou, F.en
dc.contributor.authorAgnew, R.en
dc.contributor.authorYang, L.en
dc.contributor.authorGreven, M.en
dc.contributor.authorRaw, V.en
dc.contributor.authorNeal, S.en
dc.contributor.authorMartin, D.en
dc.contributor.authorTrought, M. C. T.en
dc.contributor.authorHuth, N.en
dc.contributor.authorBrown, H. E.en
dc.date.accessioned2022-01-12T01:41:08Z
dc.date.available2021-07-22en
dc.date.issued2021-07-22en
dc.date.submitted2021-07-20en
dc.identifier.issn2517-5025en
dc.identifier.urihttps://hdl.handle.net/10182/14514
dc.description.abstractA new model for grapevines (Vitis vinifera) is the first perennial fruit crop model using the Agricultural Production System sIMulator (APSIM) Next Generation framework. Modules for phenology, light interception, carbohydrate allocation, yield formation and berry composition were adapted or added into APSIM Next Generation to represent the nature of fruit-bearing vines. The simulated grapevine phenological cycle starts with the dormancy phase triggered by a critical photoperiod in autumn, and then goes through the subsequent phenophases sequentially and finally returns to dormancy for a new cycle. The canopy microclimate module within APSIM Next Generation was extended to allow for row crop light interception. The carbohydrate arbitrator was enhanced to consider both sink strength and sink priority to reflect carbohydrate reserve as a concurrent competing sink. Weather conditions and source-sink ratio at critical developmental stages were used to determine potential grapevine yield components, e.g. bunch number, berry number and berry fresh weight. The model was calibrated and tested extensively using four detailed data sets. The model captured the variations in the timing of measured budburst, flowering and véraison over 15 seasons across New Zealand for five different varieties. The calculated seasonal dynamics of light interception by the row and alley were consistent with field observations. The model also reproduced the dynamics of dry matter and carbohydrate reserve of different organs, and the wide variation in yield components caused by seasonal weather conditions and pruning regimes. The modelling framework developed in this work can also be used for other perennial fruit crops.en
dc.format.extent23en
dc.language.isoenen
dc.publisherOxford University Press on behalf of the Annals of Botany Companyen
dc.relationThe original publication is available from - Oxford University Press on behalf of the Annals of Botany Company - https://doi.org/10.1093/insilicoplants/diab021en
dc.relation.urihttps://doi.org/10.1093/insilicoplants/diab021en
dc.rights© The Author(s) 2021. Published by Oxford University Press on behalf of the Annals of Botany Company.en
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectAPSIM Next Generationen
dc.subjectberry numberen
dc.subjectbunch numberen
dc.subjectcarbohydrate allocationen
dc.subjectgrapevineen
dc.subjectphenologyen
dc.subjectrow crop light interceptionen
dc.titleDeveloping perennial fruit crop models in APSIM Next Generation using grapevine as an exampleen
dc.typeJournal Article
lu.contributor.unitLincoln Universityen
lu.contributor.unitFaculty of Agriculture and Life Sciencesen
lu.contributor.unitDepartment of Wine, Food and Molecular Biosciencesen
dc.identifier.doi10.1093/insilicoplants/diab021en
dc.relation.isPartOfin silico Plantsen
pubs.issue2en
pubs.notesFunctional-Structural Plant Models special issueen
pubs.organisational-group/LU
pubs.organisational-group/LU/Agriculture and Life Sciences
pubs.organisational-group/LU/Agriculture and Life Sciences/WFMB
pubs.organisational-group/LU/Research Management Office
pubs.organisational-group/LU/Research Management Office/PE20
pubs.organisational-group/LU/Research Management Office/QE18
pubs.publication-statusPublisheden
pubs.volume3en
dc.identifier.eissn2517-5025en
dc.rights.licenceAttributionen
lu.identifier.orcid0000-0002-3601-0951
pubs.article-numberdiab021en
dc.subject.anzsrc2020300805 Oenology and viticultureen
dc.subject.anzsrc2020460207 Modelling and simulationen
dc.subject.anzsrc2020300207 Agricultural systems analysis and modellingen


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