Assessing opportunities for selective winery vintage with a market-driven composite index

An opportunity index (OISV) is proposed for selective vine harvest management to ensure vineyard sustainability making use of precision farming technologies. Vigour maps derived from remote sensors are the basis of the method. In terms of validation, the index was applied in 36 vineyard fields of different varieties in Raimat (Lleida, northeast Spain). The OISV is based on three components: (i) the spatial variability in vine vigour (to ensure variability in the quality of grapes), (ii) the spatial structure or pattern of vigour (to facilitate harvesting operations), and (iii) the availability of a minimum productive quality area within the plot (to ensure that benefits derived from the differentiation of the final product will compensate for the expenses of differential management). The results suggest that only few plots were suitable for selective vintage, although an acceptable agreement was obtained when comparing the plots harvested selectively by the winery and those classified as favourable by the OISV. The method is reliable and also allows varying the parameter specifications according to the logistics of each winery and/or actual market conditions. However, currently, the OISV can only be applied at plot level and future versions should address application at the whole vineyard scale.This study was possible thanks to the collaboration between the University of Lleida and Codorníu Winery in Raimat (Lleida, Spain

Vine vigor, yield and grape quality assessment by airborne remote sensing over three years: Analysis of unexpected relationships in cv. Tempranillo

The prediction of grape composition is becoming more important due to the need of reducing the current levels of alcohol and pH of the wines, a problem that is exacerbated by climate change. This work presents a 3-year study of the spatial variability of grape composition in a rainfed Tempranillo vineyard located in Rioja (Spain). It is based on the acquisition of multispectral imagery at véraison (start of the ripening process); and zoning based on NDVI, to assess its performance for zonal management. The results reveal a high spatial variability within the plot, with a stable pattern over the years, even with very different climate conditions. NDVI was a good predictor of vegetative growth variables. However, the prediction of grape composition was more complex. Unexpectedly, anthocyanins were found to be higher in the highest vigor zone, which is probably related to the effects of climate change. This unexpected relationship is particularly discussed in the article