Physical-mechanical berry skin traits as powerful indicators of resistance to botrytis bunch rot

For cool windy climates and/or lower vigor sites, delays in vine development during training can result in a greater number of growing seasons to achieve full crop yield potential.

During winemaking, some byproducts are obtained, such as grape pomace, which represent 13% of winery byproducts.

The northern root-knot nematode (Meloidogyne hapla) is one of the most prevalent plant-parasitic nematodes affecting Washington State Vitis vinifera vineyards. This nematode induces small galls on roots, restricting water and nutrient uptake. In new vineyards this can impede establishment. In existing vineyards, it can exacerbate decline in chronically stressed vines. While preplant fumigation is a common strategy for M. hapla management, its efficacy is temporary and relies on broad-spectrum chemicals that undergo frequent regulatory scrutiny. The trap crop litchi tomato (Solanum sisymbriifolium) showed promise in reducing plant-parasitic nematode densities in potato. This prompted field greenhouse experiments to evaluate its potential to reduce M. hapla in V. vinifera.

Trends already extended for more than 12 years show a decline in both consumption and international trade, particularly in volume. However, there are also positive signs in several categories of wine, segments and markets, as well as a better trend in terms of value. How are these trends affecting wine producers and distributors? Are they short or long term? do they mean radical and permanent changes to which a way of adaptation has to be found or are they just temporary changes that may only require some calm? How are companies adapting to these new trends? Which are their effects on wine regions?

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.