Soil electrical resistivity, a new and revealing technique for precision viticulture

Global warming and increased frequency and/or severity of drought events are among the most threatening consequences of climate change for agricultural crops. In response to drought, grapevine (as many other plants) exhibits osmotic adjustment through active accumulation of osmolytes which in turn shift the leaf turgor loss point (TLP) to more negative values, allowing to maintain stomata opened at lower water potentials1. We investigated the capacity of Pinot noir leaves to modulate their osmotic potential as a function of: (i) time (seasonal osmoregulation), (ii) growing temperatures, and (iii) drought events, to enhance comprehension of the resilience of grapevines in drought conditions. We performed trails under semi-controlled field conditions, and in two different greenhouse chambers (20/15 °C vs 25/20 °C day/night). For two consecutive vegetative seasons, grafted potted grapevines (Pinot noir/SO4) were subjected to two different water regimes for at least 30 days: well-watered (WW) and water deficit (WD).

Different studies have demonstrated that the application of ultrasounds (US) to crushed grapes improves chromatic characteristics of the wines (1,2), increases their polysaccharide content (3) and some aroma compounds are also favored (4,5)

The prospective study of the French wine sector (Sebillotte et al., 2004) has identified “groups of micro-scenarios” at the end of the analysis of the characteristics of this wine sector.

The main innovation in the VINIoT service is the joint use of two technologies that are currently used separately: vineyard monitoring using multispectral imaging and deployed terrain sensors. One part of the system is based on the development of artificial intelligence algorithms that are feed on the images of the multispectral camera and IoT sensors, high-level information on water stress, grape ripening status and the presence of diseases. In order to obtain algorithms to determine the state of ripening of the grapes and avoid losing information due to the diversity of the grape berries, it was decided to work along the first year 2020 at berry scale in the laboratory, during the second year at the cluster scale and on the last year at plot scale. Different varieties of white and red grapes were used; in the case of Galicia we worked with the white grape variety Treixadura and the red variety Mencía. During the 2020 and 2021 campaigns, multispectral images were taken in the visible and infrared range of: 1) sets of 100 grapes classifying them by means of densimetric baths, 2) individual bunches. The images taken with the laboratory analysis of the ripening stage were correlated. Technological maturity, pH, probable degree, malic acid content, tartaric acid content and parameters for assessing phenolic maturity, IPT, anthocyanin content were determined. It has been calculated for each single image the mean value of each spectral band (only taking into account the pixels of interest) and a correlation study of these values with laboratory data has been carried out. These studies are still provisional and it will be necessary to continue with them, jointly with the training of the machine learning algorithms. Processed data will allow to determine the sensitivity of the multispectral images and select bands of interest in maturation.

In view of sustainability and zero-waste initiatives, the valorisation of sidestreams is a key emerging topic in the wine industry.