Optimized protocol for high-quality RNA extraction from grape tissues using sorbitol pre-wash

Telomere length is emerging as a fast, sensitive, and cost-effective genomic biomarker for assessing stress exposure and physiological status in plants.

Fast, accurate, and non-destructive analytical techniques based on hyperspectral imaging (hsi) represent effective tools for food quality evaluation. A visible change in the appearance of a fresh product often negatively impacts the perceived quality from a consumer’s point of view.

The integration of digital social networks (DSN) has profoundly transformed communication practices within the wine industry, reorganizing the dynamics of prescription and marketing.

Volatile compounds play a significant role on the organoleptic properties defining wines quality. This particular role was exploited in several studies with the aim to differentiate wines from a more or less extensive production area, according to their sensory profile [1], as well as their chemical composition [2,3] (Di Paola-Naranjo et al., 2011; Kustos et al., 2020). Indeed, since aroma compounds development in grapes depends primarily on the environmental conditions of the vines and grapes (soil and climate), it is conceivable that these parameters craft the aromatic signature of the wine produced, in relation to its origin (Van Leeuwen et al., 2020). In this work, a general study on the aromatic and sensorial profile of wines produced in five sub-regions of the Corbières denomination, a renowned red grape varieties viticultural region in South France, was reported.

Aim: Through machine-learning modelling of plant water status from environmental characteristics, this work aims to develop a model able to predict grape phenolic composition in space and time to guide selective harvest decisions at the estate scale.