Exploring zoxamide sensitivity in Plasmopara viticola populations: implications for fungicide management in precision agriculture

Aim: The main goal of this study was to find an efficient canopy management to limit the high temperature-related aroma losses of White Muscat grapes, and consequently to preserve the quality standards of Asti DOCG wines.

High power ultrasound has been recently recognized one of the most promising technologies in winemaking processes, especially after the recent OIV resolution, concerning the application of ultrasounds on crushed grapes to promote the extraction of skin compounds.

During red wine aging, numerous chemical reactions occur, contributing to the modification and enhancement of the wine sensory parameters over time [1].

The project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).

The research was carried out in the ‘Chianti Classico’ area and it was part of the ‘Chianti Classico 2000’ research project. The performances ‘Sangiovese’ grapevine