Simgi® platform as a tool for the study of wine active compounds in the  gastrointestinal tract

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.

Climate change will require the adaptation of agricultural systems and among the different means of adaptation, changing plant material is a promising strategy. In viticulture, different levels of diversity are currently exploited: clonal and varietal diversity for rootstocks and scions. A huge quantity of research aims to evaluate different genotypes in different environmental conditions to identify which ones are the best adapted and the most tolerant to future environmental conditions.

Extraction of anthocyanins and tannins have been studied for two grape varieties, Carignan and Grenache, two maturation levels and two vintages, in model solutions and in wines, using UHPLC-MS/MS in the MRM mode  and HPSEC.

In table grapes seedlessness is a crucial breeding target, mainly results from stenospermocarpy, linked to the Thompson Seedless variety. Several studies investigated the genetic control of seedlessness identifying AGL11, a MADS-box transcription factor, as a crucial gene.
We performed a deep investigation of the whole AGL11 gene sequence in a collection of grapevine varieties revealing three different promoter-CDS combinations. By investigating the expression of the three AGL11 alleles and evaluating their ability to activate the promoter region, we show that AGL11 regulates its transcription in a specific promoter-CDS manner. By a multi-AGL11 co-expression analysis we identified a methyl jasmonate esterase, an indole-3-acetate beta-glucosyltransferase, and an isoflavone reductase as top AGL11 candidate targets. In vivo experiments further confirmed AGL11 role in regulating these genes, demonstrating its significant influence in seed development and thus in seedlessness trait.

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