Model-based analysis of sugar accumulation in response to source - sink ratio and water supply in grape (Vitis vinifera) berries

Abstract

The dynamics of sugar (hexose) concentration in ripening grape berries (Vitis vinifera L.) were simulated with a refined mechanistic model. Changes in sugar concentration were reproduced by the sum of sugar import (S), sugar metabolism (M) and water budget (W). S and W were derived from model inputs of fresh and dry mass, and M was simulated with a relative metabolism rate describing the depletion of hexose. The relative metabolism rate was associated with the relative growth rate of dry mass with a coefficient (k) that was constant for a given cultivar under various growth conditions (temperature, water supply, and source-sink ratio) but varied with genotype. The k value was~20% higher for cv. Merlot than for cv. Cabernet Sauvignon, indicating more imported sugars would be depleted by Merlot than Cabernet Sauvignon. The model correctly simulated the negative effect of lowered leaf-to-fruit ratio and the positive effect of water shortage on sugar concentration. Sensitivity analysis revealed that the present model was weakly sensitive to k because of sugar accumulation being predominantly controlled by S, with M relatively small (~20%) with respect to the increment of sugar concentration. Model simulation indicated that the decreasing leaf-to-fruit ratio reduced S more than M and W, causing a net decrease in sugar concentration. In contrast, the water shortage decreased S less than M and W, resulting in a net increase in sugar concentration.

Carotenoid responses to environmental stimuli: integrating redox and carbon controls into a fruit model

“…In addition, several models of fruit growth and carbohydrate accumulation, at the fruiting branch level, have been successfully developed and tested for grapevine, peach, mango and tomato (Génard et al , 2008Léchaudel et al 2005). These models have been used for various purposes, including simulation (Liu et al 2007;Génard et al 2010), analysis of the processes involved in quality (Dai et al 2009) and the interactions between genetic and environmental factors (Quilot et al 2005a), determination of quantitative trait loci (QTLs) for parameters of ecophysiological models of quality (Quilot et al 2004(Quilot et al , 2005bWu et al 2005;Bertin et al 2009Bertin et al , 2010, and modelling of the accumulation of organic acids (Lobit et al 2003(Lobit et al , 2006. While models of carbon gains and losses and allocation can be used to predict fruit carbohydrate concentrations, from the fruiting branch to the tree level (Génard et al 2008), such models can also be used to predict carbohydrate concentrations in leaves to analyse, for instance, the negative feedback effect of carbohydrate accumulation on photosynthesis (Franck et al 2006;Urban & Alphonsout 2007;Génard et al 2008).…”

“…), analysis of the processes involved in quality (Dai et al . ) and the interactions between genetic and environmental factors (Quilot et al . 2005a), determination of quantitative trait loci (QTLs) for parameters of ecophysiological models of quality (Quilot et al .…”

Metabolic profiling reveals coordinated switches in primary carbohydrate metabolism in grape berry (Vitis vinifera L.), a non-climacteric fleshy fruit

“…only one primary shoot axis with a single cluster per plant) were developed as a simplified experimental model system to overcome these difficulties (Mullins, 1966). Since its introduction, this model system has been improved and applied to many aspects of grape research, including the effects of water stress (Antolín et al ., 2010), climate-change scenarios (Salazar Parra et al ., 2010), abscisic acid treatment (Giribaldi et al ., 2010), source–sink ratio (Ollat and Gaudillere, 1998; Dai et al ., 2009), and nitrogen supply (Geny and Broquedis, 2002) on grape physiology. In addition, factors affecting inflorescence development, fruit set (Aziz, 2003), carbon allocation (Vaillant-Gaveau et al ., 2011), and transcriptome reprogramming (Lund et al ., 2008) have also been investigated using fruit-bearing cuttings.…”

Modelling the size and composition of fruit, grain and seed by process‐based simulation models

“…More recently, a modified version of SUGAR simulating developmental, growth and temperature-related variations in the relative rates of different sugar transformations has been developed for peach , and then adapted for tomato (Prudent et al, 2011) and grape (Dai et al, 2009). This shows the versatility of the approach when applied to fleshy fruit.…”