Simulating organ biomass variability and carbohydrate distribution in perennial fruit crops: a comparison between the common assimilate pool and phloem carbohydrate transport models

Abstract

Variability in fruit quality greatly impedes the profitability of an orchard. Modelling can help find the causes of quality variability. However, studies suggest that the common assimilate pool model is inadequate in terms of describing variability in organ biomass. The aim of the current study was to compare the performances of the common assimilate pool and phloem carbohydrate transport models in simulating phloem carbohydrate concentration and organ biomass variability within the whole-plant functional-structural grapevine (Vitis vinifera L.) model that we developed previously. A statistical approach was developed for calibrating the model with a detailed potted experiment that entails three levels of leaf area per vine during the fruit ripening period. Global sensitivity analysis illustrated that carbohydrate allocation changed with the amount of leaf area as well as the limiting factors for organ biomass development. Under a homogenous canopy architecture where all grape bunches were equally close to the carbohydrate sources, the common assimilate pool and phloem transport models produced very similar results. However, under a heterogeneous canopy architecture with variable distance between bunches and carbohydrate sources, the coefficient of variation for fruit biomass rose from 0.01 to 0.17 as crop load increased. These results indicate that carbohydrate allocation to fruits is affected by both the size of crop load and fruit distribution, which is not adequately described by the common assimilate pool model. The new grapevine model can also simulate dynamic canopy growth and be adapted to help optimise canopy architecture and quality variability of other perennial fruit crops.

Undirected Sucrose Efflux Mitigation by the FT-Like SP6A Preferentially Enhances Tuber Resource Partitioning

“…We further show that these effects are relevant in a much broader loading rate range compared to a study by Bancal and Soltani (2002) due to higher source concentrations. Our findings on the importance of pathway properties are supported by recent findings that source-sink distance differences drive divergence in yield between grapes ( Pallas et al, 2010 ; Zhu et al, 2021 ). Additionally, we observed that the previously reported phenomenon of weakest sink prioritization—the larger than expected sucrose allocation to the weaker sink for non-saturating sucrose loading—occurs not only for sinks differing in sink strength, but also for differences in sucrose affinity or pathway length.…”

“…Importantly, both the models used a simplified phenomenological description of pathway resistance and its effect on transport, rather than explicitly modeling the osmotically driven pressure gradient driving transport. A recent study, integrating biophysically detailed transport dynamics in a multisink FSP model, instead indicated that both the distance and sink strength determine sugar partitioning in grape ( Zhu et al, 2021 ). Thus, it remains unclear what the exact relevance of pathway properties is on resource partitioning and how this may depend on sink properties.…”

GrapevineXL reliably predicts multi-annual dynamics of vine water status, berry growth, and sugar accumulation in vineyards

“…2007, 2008, 2011, 2013, and 2014) with less stressed conditions. Although there is vessel segmentation among shoots and water flows in discrete xylem sectors along the trunk axis [ 62 ], the assumption of separated shoots ignores the possible exchange of resources between nearby vessels [ 24 ] and may increase the uncertainty of predicting plant water status. Detailed leaf growth and canopy structure need to be more precisely incorporated in the future version of the GrapevineXL.…”

Mobile tuberigen impacts tuber onset synchronization and canopy senescence timing in potato

“…Again, competition outcome depends on differences in sink strength, timing but also plant architecture, i.e. whether different sinks have different distances to sources (van den Herik & ten Tusscher, 2022; Zhu et al, 2021; Pallas et al, 2010). To what extent differences in tuber onset and growth timing merely reflect differences in prior stolon development, and to what extent regulation at the stage of tuberization onset may affect tuber size differences has not been systematically investigated.…”