Grapevine Yield Big-data for Soil and Climate Zoning. A case study in Languedoc-Roussillon, France

¹ UMR ABSys – Montpellier SupAgro; INRAE; CIRAD; U. Montpellier – Montpellier, France
² UMR EMMAH – INRAE; U. Avignon – Avignon, France
³ UMR Agronomie – AgroParisTech ; INRAE; Université Paris-Saclay – Thiverval-Grignon, France
⁴ UMR LISAH – INRAE; CIRAD; IRD – Montpellier, France
⁵ U. AgroClim – INRAE – Avignon, France
⁶ UMR Innovation – INRAE; CIRAD; Montpellier SupAgro; U. Montpellier – Montpellier, France
⁷ UMR MOISA – INRAE; CIRAD; Montpellier SupAgro; U. Montpellier – Montpellier, France

^* Corresponding author: hugo.fernandez-mena@supagro.fr

Abstract

New winegrower and resource datasets appear to be a great opportunity to understand which are the environmental factors involved in grapevine yield spatially. Such analysis can help regional label managers and winegrowers for the conception of local adaptation strategies to climate change, reducing yield gaps. In the present study, we aggregated yield a big dataset obtained from Pays d’Oc winegrowers (n = 96677) between 2010 and 2018 at the municipality level (n = 606), located in the Languedoc-Roussillon region, in the South of France. We used a backward stepwise model selection process using linear mixed-effect models to discriminate and select significant indicators capable of estimating grapevine yield at the municipality level, these include: Soil Available Water Capacity (SAWC), soil pH, Huglin Index, the Climate Dryness Index, the number of Very Hot Days and Days of Frost. We then determined spatial zones by creating clusters of municipalities with similar soil and climate characteristics. The seven zones presented two marked yield levels. Yet, all zones had municipalities with both high yield and high yield gaps. On each zone, grapevine yield was found to be driven by a combination of climate and soil factors, rather than just by a single environmental factor. Environmental factors at this scale largely explained yield variability across the municipalities, but they were not performant in terms of annual yield prediction. Further research is required on the interactions between environmental factors, plant material and farming practices.