Context and purpose of the study – Grape quality is a complex trait that mainly refers to berry chemical composition, including sugars, organic acids, phenolics, aroma and aroma precursor compounds. It is known that the composition and concentration of chemical compounds dynamically change along berry development and can be affected by genotypes (rootstock and scion), environment (light, temperature and water) and nutrient status (carbon and nitrogen). Moreover, the ongoing climate change is affecting the physiology of grapevine and ultimately wine quality and typicity. Therefore, a better understanding of the mechanisms controlling the accumulation of quality‐related metabolites (both primary and secondary) in grape berry is essential to choose grapevine cultivars and viticultural practices best adapted to a given growth region. Process‐based models can mechanistically integrate various processes involved in fruit growth and composition, and simulate the plant responses to weather and management practices, making them a promising tool to study the response of berry quality to those factors.
Material and methods – Three types of modeling approaches have been applied, including constraint‐ based flux balance analysis, process‐based models, and 3D structure‐functional models. These models were established, calibrated and validated based extensive experimental measurements in grapevines growing under contrast conditions, e.g. nitrogen limitation, modulation of leaf‐to‐fruit ratios, and light conditions. Fruit growth was measured in parallel with metabolite composition, enzyme activities, and whole plant growth processes, such as canopy photosynthesis, and transpiration. Moreover, in silico analysis was conducted to create virtual genotypes or to assess regulatory roles of model parameters.
Results– At cellular scale, we used constraint‐based flux balance analysis model to investigate the flux modifications responsible for biosynthesis of anthocyanins in response to nitrogen limitation. At organ scale, we developed process‐based models for sugar accumulation and anthocyanin composition in grape berries, which allowed us to determine the key processes responsible for these two important quality components. At the whole‐plant scale, a 3D structure‐functional model was developed to simulate water transport, leaf gas exchanges, carbon allocation, and berry growth in various genotype x environment scenarios. In the future, the interactions among the different scales of regulation will be further modelled to offer a model toolkit that allows more accurate predictions of grapevine growth and berry quality elaboration under changing environments and paving a way towards model‐assisted breeding.
Authors: Zhanwu DAI (1), Jinliang CHEN (1), Junqi ZHU (2), Michel GENARD (3), Bertrand BEAUVOIT (4), Stefano PONI (5), Sophie COLOMBIE (4), Gregory GAMBETTA (1), Philippe VIVIN (1), Nathalie OLLAT (1), Serge DELROT (1), Yves GIBON (4), Eric GOMES (1)
(1) EGFV, Bordeaux Sci Agro, INRA, Univ. Bordeaux, F-33882 Villenave d’Ornon, France.
(2) The New Zealand Institute for Plant & Food Research Limited (PFR) Marlborough, Blenheim 7240, New Zealand.
(3) INRA, UR 1115 Plantes et Systèmes de Culture Horticoles, Avignon, France.
(4) INRA, UMR 1332 Biologie du Fruit et Pathologie, F33883 Villenave d’Ornon, France.
(5) Department of Sustainable Crop Production, Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122 Piacenza, Italy.
Email: zhanwu.dai@inra.fr
Keywords: Environmental adaptation, Vitis vinifera, berry quality, modeling