New breeding frontiers: application of the CRISPR-cas9 system in grapevine (V. vinifera L.) and improvements in plant regeneration

In Washington State, the majority of winegrape (Vitis vinifera) vineyards are planted to their own roots. This practice is possible due to the lack of established phylloxera populations, and is preferred due to the ease of retraining after damaging winter cold events. However, own-rooted V. vinifera is generally susceptible to most plant parasitic nematodes that attack grape. In Washington State, management of nematodes is dominated by preplant soil fumigation. One practice that may mitigate economic loss due to nematodes is the adoption of nematode-“resistant” rootstocks.

In this video recording of the IVES science meeting 2025, Marine Morel (EGFV, Univ. Bordeaux, Bordeaux Sciences Agro, INRAE, ISVV, Villenave-d’Ornon, France) speaks about the role of rootstock and its genetic background in plant mineral status. This presentation is based on an original article accessible for free on OENO One.

Measurements of parameters spatialy positionned, with on line sensors mounted on classical machinery or airborne imagery is no more a problem in viticulture. In a short time, high resolution data dedicated to the assessment of the vine characteristics, the soil, the harvest, etc. will become a reality.

The photosynthetic characteristics of twenty varieties of grapevine (Vitis vinifera L.) from Mallorca (Balearic Islands, Spain) and two widespread varieties

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.