in silico Plants · 2021 · 20 citations · 66 references
AgricultureAgronomyCrop SciencesCrop ModelingCrop PhysiologyGrapevine PhysiologyBerry DevelopmentBerry RipeningBud DormancyCanopy PhysiologyFruit Crop PhysiologyPhenology ModelingAgricultural Production ModelingBerry Composition VariationBerry Weight AccumulationCanopy Light InterceptionCrop Canopy MicroclimateFruit Crop Yield ComponentsGrape Berry CompositionReserve Carbohydrate Dynamics
Abstract A 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.
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