Predicting provenance and grapevine cultivar implementing machine learning on vineyard soil microbiome data: implications in grapevine breeding

This study presents an investigation based on sensory analysis data of Spanish wines with geographical indications collected over a three-year period. Sensory analysis plays a crucial role in assessing the quality, characteristics, and perception of wines. The trained tasting panel at Dolmar Laboratory, accredited for objective sensory evaluation of wines since 2016, has been tasting over 5000 wines. However, it is since 2021, when a computer application for tastings was developed, that the digitalization of data allows for detailed statistical analysis of the results.

Grapevine (Vitis vinifera L.) exhibits a high level of genetic and phenotypic diversity among the approximately 6000 cultivars recorded. This perennial crop is highly vulnerable to numerous fungal diseases, including esca, which is a complex vascular pathology that poses a significant threat to the wine sector, as there is currently no cost-efficient curative method[1]. In this context, an effective approach to mitigate the impact of such diseases is by leveraging the crop’s genetic diversity. Indeed, susceptibility to esca disease appears to vary between cultivars, under artificial or natural infection. However, the mechanisms and varietal characteristics underlying cultivar susceptibility to esca are still unknown.

The wooden barrel is a key factor in enology, since wine chemical composition and sensory properties changes significantly in contact with the barrel[1]. Today’s highly competitive market constantly demands new differentiated products and wineries search innovations continuously.
Wood selection is crucial: barrels stability to keep constant their contribution and the result on products, and additional and differentiated wood contributions to impact their new products. Oak wood selection has traditionally been carried out using parameters such as specie, location and grain, however, it goes one step further nowadays. Large cooperage work with non-destructive techniques that allow classifying oak wood quickly and easily according to their organoleptic contribution[2].

This essay was aimed to describe the clonal diversity of Oenococcus oeni in the malolactic fermentation of the carbonic maceration (CM) winemaking. The free and the pressed liquids from CM were sampled and compared to the wine from a standard winemaking with previous destemming and crushing (DC) of grapes [1]. O. oeni strain typification was performed by PFGE as González-Arenzana et al. described (2014) [2]. Results showed that 13 genotypes, referred as to letters, were distinguished from the 49 isolated strains, meaning the genotype “a” the 27%, the “b” the 14%, the “c” the 12%, the “d and e” the 10 % each other, and the remaining ones less than the 8% each one.

Grapevine resilience to climate change has become one of the most pressing topics in the Viticulture & Enology field. Vineyard health demands understanding the mechanisms that explain the direct and indirect interactions between environmental stressors. The current climate change scenario, where drought and heat-wave are more frequent and intense, strongly demands improving our knowledge of environmental stresses. During a heatwave, the ambient temperature rises above the plant’s average tolerance threshold and, generally, above 35 oC plant’s adaptation to heat stress is activated.