Discrimination of white wines by Raman spectroscopy coupled with chemometric methods

Less and less chemical plant protection products are approved by the E U. Plant pathogenic fungi become increasingly resistant to the active ingredients that have been around for a long time. Besides, there is a valid demand for effective products that can be applied in organic cultivation. We examined Metschnikowia strains under laboratory conditions in order to find effective strains against B. cinerea. The antimicrobial mechanism of these yeasts is based on the competition for the ferric ions from the environment. Metschnikowia cells release the pulcherriminic acid which chelates with Fe3+, forming the pigment pulcherrimin.

Context and purpose of the study. In regions where grapevines are grown under irrigation, like most regions in Argentina, the wine industry should adopt more sustainable strategies and production systems towards a higher water use efficiency and a reduction in no-renewable energy consumption.

Botrytis cinerea has more than 1200 host plants and is one of the most important plant pathogens in viticulture. Under certain environmental conditions, it can lead to the development of a noble rot, which results in a specific metabolic profile, altering physical texture and chemical composition. The other microbes involved in this process and their functional genes are poorly characterised. We have generated metatranscriptomic [1,2] and DNA metabarcoding data from three months of the Furmint grape variety, representing the four phases of noble rot, from healthy berries to completely dried berries.

The ‘Caiño’ cultivar was cultivated in Galicia (Northwestern Spain) before the invasion of grape phylloxera. Genetic diversity from this cultivar have been described and considered as originating in Galicia, ‘Caiño Tinto’, ‘Caiño Bravo’, ‘Caiño Redondo’, ‘Caiño Longo’ and ‘Caiño Blanco’.

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.