Hyperspectral imaging and machine learning for monitoring grapevine physiology

Grapevine (Vitis spp.) is a globally significant fruit crop, and enhancing its agronomic and oenological traits is crucial to meet changing agricultural conditions and consumer demands. Conventional breeding has played a key role in domesticating grapevine varieties, but it is a time-consuming process to develop new cultivars with desirable traits for cultivation.
New plant breeding techniques (NpBTs) offer a potential revolution in grapevine cultivation, and genome editing has shown promise for targeted mutagenesis. The success of these biotechnological approaches relies on efficient in vitro regeneration protocols, particularly through somatic embryogenesis (SE).

Water scarcity, high air temperatures, high vapor pressure deficit, and increasing frequency and intensity of extreme climatic events, namely heat waves, exert huge pressure on viticulture, as is the case of Mediterranean climates. Therefore, farmers rely more and more on irrigation to overcome these constraints. Deficit irrigation is a proved strategy to optimize irrigation efficiency and wine quality. The present study intends to demonstrate the application of precision techniques, namely remote sensing derived vegetation indices (VI) and an open source software, SIMDualKc, to compute crop evapotranspiration using the dual crop coefficient approach (Kcb + Ke), for deficit irrigation management.

Chasselas is a refined grape variety renowned for its subtlety and its remarkable ability to reflect terroir characteristics [1]. Typically consumed young, it is appreciated for its low acidity and delicate fruity and floral aromas.

Wine biological aging is characterized by the development of yeast strains that form a biofilm on the wine surface after alcoholic fermentation. These yeasts, known as flor yeasts, form a velum that protects the wine from oxidation during aging. Thirty-nine velums aged from 1 to 6 years were sampled from “Vin jaune” from two different cellars. We show for the first time that these velums possess various aspects in term of color and surface aspects. Surprisingly, the heterogeneous velums are mostly composed of one species, S. cerevisiae. Scanning electron microscope observations of these velums revealed unprecedented biofilm structures and various yeast morphologies formed by the sole S. cerevisiae species.

The presence of grapevine trunk diseases (GTDs) related pathogens leads to severe economic losses in wine‐growing regions all over the world