Mechanisms involved in the heating of the environment by the aerodynamic action of a wind machine to protect a vineyard against spring frost

Atmospheric carbon dioxide (CO2) concentration has continuously increased since pre-industrial times from 280 ppm in 1750, and is predicted to exceed 700 ppm by the end of 21st century. For most of C3 plant species elevated CO2 (eCO2) improve photosynthetic apparatus results in an increased plant biomass production. To investigate the effects of eCO2 on morphological leaf characteristics the two Vitis vinifera L. cultivars, Riesling and Cabernet Sauvignon, grown in the Geisenheim VineyardFACE (Free Air Carbon dioxide Enrichment) system were used. The FACE site is located at Geisenheim University (49° 59′ N, 7° 57′ E, 94 m above sea level), Germany and was implemented in 2014 comparing future atmospheric CO2-concentrations (eCO2, predicted for the mid-21st century) with current ambient CO2-conditions (aCO2). Experiments were conducted under rain-fed conditions for two consecutive years (2015 and 2016). Six leaves per repetition of the CO2 treatment were sampled in the field and immediately fixed in a FAA solution (ethanol, H2O, formaldehyde and glacial acetic acid). After 24 h leaf samples were transferred and stored in an ethanol solution. Subsequently, leaf tissue was dehydrated using ethanol series and embedded in paraffin. By using a rotary microtomesections of 5 µm were prepared and fixed on microscopic slides. Subsequent the samples were stained using consecutive staining and washing solutions. Afterwards pictures of the leaf cross-sections were taken using a light microscope and consecutive measurements were conducted with an open source image software. Differences found in leaf cross-sections of the two CO2 treatments were detected for the palisade parenchyma. Leaf thickness, upper and lower epidermis and spongy parenchyma remained less affected under eCO2 conditions. The observed results within grapevine leaf tissues can provide first insights to seasonal adaptation strategies of grapevines under future elevated CO2 concentrations.

Soil is a reservoir of microorganisms playing important roles in biogeochemical cycles and interacting with plants whether in the rhizosphere or in the root endosphere. The composition of the microbial communities thus impacts the plant health. Rhizodeposits (such as sugar, organic and amino acids, secondary metabolites, dead root cells …) are released by the roots and influence the communities of rhizospheric microorganisms, acting as signaling compounds or carbon sources for microbes. The composition of root exudates varies depending on several factors including genotypes. As most of the cultivated grapevines worldwide are grafted plants, the aim of this study was to explore the influence of rootstock and scion genotypes on the microbial communities of the rhizosphere and the root endosphere. The work was conducted in the GreffAdapt plot (55 rootstocks x 5 scions), in which the 275 combinations have been planted into 3 blocks designed according to the soil resistivity. Samples of roots and rhizosphere of 10 scion x rootstock combinations were first collected in May among the blocks 2 and 3. The quantities of bacteria, fungi and archaea have been assessed in the rhizosphere by quantitative PCR, and by cultivable methods for bacteria and fungi. The communities of bacteria, fungi and arbuscular mycorrhizal fungi (AMF) was analyzed by Illumina sequencing of 16S rRNA gene, ITS and 28S rRNA gene, respectively. The level of mycorrhization was also evaluated using black ink coloration of newly formed roots harvested in October. The level of bacteria, fungi and archaea was dependent on rootstock and scion genotypes. A block effect was observed, suggesting that the soil characteristics strongly influenced the microorganisms from the rhizosphere and root endosphere. High-throughput sequencing of the different target genes showed different communities of bacteria, fungi and AMF associated with the scion x rootstock combinations. Finally, all the combinations were naturally mycorrhized. The root mycorrhization intensity was influenced by the rootstock genotype, but not by the scion one. Altogether, these results suggest that both rootstock and scion genotypes influence the rhizosphere and root endophytic microbiomes. It would be interesting to analyze the biochemical composition of the rhizodeposition of these genotypes for a better understanding of the processes involved in the modulation of these microbiomes. Moreover, crossing our data with the plant agronomic characteristics could provide insights into their roles on plant fitness.

Making high quality but affordable Pinot noir (PN) wine is challenging in most terroirs and New Zealand’s (NZ) situation is no exception. To increase the probability of making highly typical PN wines producers choose to grow grapes in cool climates on lower fertility soils while adopting labour intensive practices. Stringent yield targets and higher input costs necessarily mean that PN wine cost is high, and profitability lower, in line-priced varietal wine ranges. To understand the reasons why higher yielding vines are perceived to produce wines of lower quality we have undertaken an extensive study of PN in NZ. Since 2018, we established a network of twelve trial sites in three NZ regions to find individual vines that produced acceptable commercial yields (above 2.5kg per vine) and wines of composition comparable to “Icon” labels. Approximately 20% of 660 grape lots (N = 135) were selected from within a narrow juice Total Soluble Solids (TSS) range and made into single vine wines under controlled conditions. Principal Component Analysis of the vine, berry, juice and wine parameters from three vintages found grape berry mass to be most effective clustering variable. As berry mass category decreased there was a systematic increase in the probability of higher berry red colour and total phenolics with a parallel increase in wine phenolics, changed aroma fraction and decreased juice amino acids. The influence of berry size on wine composition would appear stronger than the individual effects of vintage, region, vineyard or vine yield. Our observations support the hypothesis that it is possible to produce PN wines that fall within an “Icon” benchmark composition range at yields above 2.5kg per vine provided that the Leaf Area:Fruit Weight ratio is above 12cm2 per g, mean berry mass is below 1.2g and juice TSS is above 22°Brix.

There is an urgent need in viticulture to adopt alternative herbicide-free soil management strategies to mitigate climate change, increase biodiversity, reduce plant protection products and improve soil quality while minimizing detrimental effects on grapevine’s stress tolerance and fruit quality. To propose sustainable solutions, adapted to different pedoclimatic conditions in Switzerland, we developed a multidisciplinary 4-year project, started in 2020. Objectives of the project are to a) evaluate the impact of green covers (spontaneous flora, winter cover crop and permanent ground cover) on environmental and agronomic parameters and b) develop subsequently innovative strategies for different viticultural contexts of Switzerland. The project is divided into 3 phases: 1) diagnosis, 2) on-farm and 3) on-station experiments. Phase 1) consisted in an assessment of 30 commercial vineyards all over Switzerland, where growers already use different herbicide-free soil management strategies. The most promising practices identified in this exploratory phase will be replicated in commercial vineyards across Switzerland (“on-farm”) as well as in a classical randomized block design in an experimental plot (“on-station”). For phase 1), measurements consisted in evaluation of soil status (compaction, structure, roots development), soil microbial diversity (metagenomics), plant diversity and biomass, vine physiology (water stress, vigor, leaf nitrogen) and berry quality (acidity, sugar, available nitrogen). Interestingly, the permanent ground cover resulted in a higher Shannon index thus a higher biodiversity as compared to the other itineraries. The winter cover crop increased vine nitrogen and vigor while deteriorating soil quality, leaving the soil more exposed and compacted likely due to more frequent tillage. The spontaneous flora led to higher berry sugar accumulation, less nitrogen and higher malic acid concentration putatively due to a higher water retention of the flora in a particularly wet vintage. Phases 2) and 3) are required to confirm those tendencies, over the 3 next vintages and different climatic conditions.

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.