Functional characterization of grapevine MLO genes to define their roles in Powdery mildew susceptibility by CRISPR/Cas9 genome editing

Rapid and accurate quantification of grape berry phenolics, anthocyanins and tannins, and identification of grape varieties are both important for effective quality control of harvesting and initial processing for wine making. Current reference technologies including High Performance Liquid Chromatography (HPLC) can be rate limiting and too complex and expensive for effective field operations

The protein haze formation in white and rosé wines during storage, shipping and commercialization has always been an important issue for winemakers. Among the various solutions industrially proposed, the use of bentonite is certainly the most widespread. However, the harmful effects of this treatment are known either in terms of wine volume loss and wine flavour and aroma.

AIM: Different factors affect the style and quality of wine and one of the most important are environmental factors of vineyard location.

Climate change is increasing the frequency of water deficit in many grape-growing regions. Grapevine varieties differ in their stomatal behavior during water deficit, and their ability to regulate water potential under dry soil conditions is commonly differentiated using the concept of isohydricity. It remains unclear whether stomatal behavior, water potential regulation, and the resulting degree of isohydricity has a relationship with changes to fruit growth during water deficit. This study was conducted on four varieties (`Cabernet Franc`, `Semillon`, `Grenache`, and `Riesling`) subjected to both short-term, severe water deficit and long-term, moderate water deficit applied at both pre- and post-veraison.

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.