Hyperspectral imaging and machine learning for monitoring grapevine physiology

Brettanomyces bruxellensis is an ubiquitous yeast associated with different fermentation media such as beer and kombucha, where its presence is beneficial to bring an aromatic typicity. However, it is a main spoilage yeast in wines, in which it produces volatile phenols responsible for organoleptic deviations causing significant economic losses (Chatonnet et al., 1992). Cellar and winery equipment’s are considered as the first source of contamination, during fermentation and wine ageing process (Connel et al., 2002). Indeed, it is possible to find B. bruxellensis in the air, on walls and floors of the cellars, on small materials, vats and barrels.

n 1997 and 1999, sixteen cultivation sites of cv. Muscat of Alexandria different for pedological conditions, altitude and exposition were selected through all Pantelleria isle. In 1997 in each site

Grapevine vigour, defined as the propensity to assimilate, store and/or use non-structural sugars for allowing fast growth of shoots and producing large canopies[1], is crucial to optimize vineyard management. Recently, a model has been proposed for predicting the vigor of young grapevines through the measurement of the vegetative growth and physiological parameters, such as water status and gas exchange[2]. Our objectives were (1) to explore the influence of the association of two grapevine varieties (Tempranillo and Cabernet Sauvignon, grafted onto R110 rootstocks) with arbuscular mycorrhizal fungi (AMF) on the vegetative vigour of young plants; and (2) to assess the effect of environmental factors linked to climate change on the vegetative vigour of Cabernet Sauvignon.

Viticulture is exposed to a range of new stressors, that are challenging its sustainability and disrupting famous and well-established production regions. Steady increase of average temperature, recurring heat waves, altered rainfall seasonal distribution, drought spells, increased pathogens pressure, they all mix up with increased frequency, making every growing season a special challenge and calling for new approaches to cope with worrying scenarios.

Happens too often in scientific papers to find the same harvesting period of a cultivar, although the used treatment influence a maturity curve of investigated thesis.
This inevitably leads to wrong conclusions when comparing the treatment effects, since obtained on maturity stages more or less far from those technologically correct.