VINESYM: an integrated vine and grapevine mathematical model for vegetative development and production quality forecast

Vittorio Faluomi,Iacopo Borsi,S Poni

doi:10.1051/bioconf/20191302005

Abstract

The present work deal with the development of a mathematical model able to predict, using time dependent meteorological data, soil and vine characteristics, the growing of a vine and grapevine in terms of leaf area, shoot length, fruit and vegetative mass and finally sugar and acid content of the berry. The model is based upon a source-sink relationship approach, integrated with a soil-atmosphere model, where water accumulation in soil, sap flow across vine are coupled with potential carbon demand functions to directly consider possible water and temperature stresses. The model includes also a N2 sink-source approach, limiting growth rate following N2 availability. Finally, a mechanistic model to evaluate sugar accumulation and a correlation-based model for acid concentration evaluation in the berry is coupled with vegetative growth, to provide the information required to manage vineyard operations and evaluate the impact to the potential wine quality. The primary distinctive trait of this model is then the integration and feedback among prediction of grapevine quality model (sugar an acid content) and vegetative growth model, using a common initial ad boundary conditions data set.

Highlights

Quality and production of vineyards (Vitis vinifera L.) are influenced by a great number of interrelated factors
The model developed allow to simulate the main parameters related to vine and grapevine growing with sufficient accuracy to be used to identify the impact of meteorological changes in the grapevine and wine quality
The feedback of water and nutrient balance, as well as the impact of proper calculation of leaf temperature into the source-sink model for organic matter increment show an interesting accuracy in predictions, as shown by comparison with measured data of both vine leaf area and fruit mass

Summary

Introduction

Quality and production of vineyards (Vitis vinifera L.) are influenced by a great number of interrelated factors. In the case of grapevines, there are models which accurately predict specific processes such as phenology [7], vegetative growth and yield [8], sugar accumulation [9], carbon assimilation and allocation [10] These models do not comprehend all the desirable features listed above. Grapevine in commercial production can be a difficult subject for modeling due to the extreme manipulations by growers such as variable pruning, training, shoot selection, canopy shoot positioning, leaf removal, hedging, cluster thinning, etc Those models often neglect fundamental phenomena like subsoil water balance, root-soil interaction, soil-plant atmosphere exchange and feedback on production quantity (fresh mass) and quality (sugar and berry pH). Limits and improvements of the model are discussed

Objectives

Methods

Results

Conclusion