A digital twin application for vineyards sustainable management

Abstract

Environmental protection and production sustainability are the key actions required to the farming activities, especially to those with higher add value as wine production. Vineyard are one of the most demanding activities in terms of water consumption and environmental impacts, which can be mitigated only with a systematic approach based on smart agriculture to support and optimize vineyard management. This paper proposes a vineyard digital twin (VDT) based on a mathematical model able to predict the vegetative and productive growth of a vineyard (leaf area, shoot length, crop and yield mass), qualitative product parameters (sugar and acid) and the water footprint associated with production. The model implements a soil-atmosphere source-sink model, where water balance across vine is coupled with potential carbon demand functions to estimate water and temperature stresses and, through a mechanistic model for sugar accumulation and acid concentration, will evaluate the expected grape quality. The distinctive trait of this model is the integration and feedback among prediction of grapevine quality and vegetative growth, using a common boundary data set and integrating the agronomical operations on vineyard seasonal development. The VDT prototype will help producers to systematize, formalize, and accumulate knowledge to improve and optimize management processes to achieve sustainable production, increasing products healthy and reducing environmental footprint.