Treated wastewater irrigation: how to manage water salinity without reducing its nutrients content?

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.

The Earth’s system is undergoing major changes through a wide range of spatial and temporal scales as a response to growing anthropogenic radiative forcing, which is pushing the whole system far beyond its natural variability. Sources of greenhouse gases largely exceed their sinks, thus leading to a strengthened greenhouse effect. More energy is thereby being supplied to the system, with inevitable shifts in climatic patterns and weather regimes. Over the last decades, these modifications have been manifested in the full statistical distributions of the atmospheric variables, with dramatic changes in the frequency and intensity of extremes. Natural hazards, such as severe droughts, floods, forest fires, or heatwaves, are being triggered by extreme atmospheric events worldwide, thus threatening human activities. Viticultculture is not only exposed to changing climates but is also highly vulnerable, as grapevine phenology and physiological development are strongly controlled by atmospheric conditions. Therefore, the assessment of climate change projections for a given region is critical for climate change adaptation and risk reduction in viticulture. By adopting timely and suitable measures, the future sustainability and resiliency of the sector can be fostered. Climate-grapevine chain modelling is an essential tool for better planning and management. However, the accuracy of the resulting projections is limited by many uncertainties that must be duly taken into account when transferring knowledge to stakeholders and decision-makers. Climate-smart viticulture will comprise ensembles of locally tuned strategies, envisioning both adaptation and mitigation, assisted by emerging technologies and decision-support systems.

The reproducibility of elemental profile in wines produced across multiple vintages has been previously reported using grapes from a single scion clone of Vitis vinifera L. cv. Pinot noir. The grapevines were grown on fourteen different vineyard sites, from Oregon to southern California in the U.S.A., which span distances from approximately hundreds of meters to 1450 km, while elevations range from near sea level to nearly 500 m. In addition, sensorial (i.e. aroma, taste, and mouthfeel) and chemical (i.e. polyphenolic and volatile) differences across the different vineyard sites have also been observed among these wines at two aging time points. While strong evidence exists to support that grapes grown in different regions can produce wines with unique chemical and sensorial profiles, even when a single clone is used, the understanding of growing site characteristics that result in this reproducible differentiation continues to emerge. One hypothesis is that the elemental profile that a vineyard site imparts to the grape berries and the resulting wine is an important contributor to this differentiation in chemistry and sensory of wines. For example, various classes of enzymes that catalyze the formation of key aroma compounds or their precursors require specific metals. In this work, we begin to report correlations between elemental and volatile aroma profiles of site-specific Pinot noir wines, made under standardized winemaking conditions, that have been previously shown to be distinguished separately by these chemical analyses.

The parameters that determine the grape quality, and therefore the optimal harvest time, suffer variations during berry ripening, related to climate change, with the widely known problem of the gap between technological and phenolic maturities. However, there are few studies about its incidence on grape nitrogen composition. For this reason, the use of an elicitor, methyl jasmonate (MeJ), alone or with urea, is proposed as a tool to reduce climatic decoupling, allowing to establish the harvest time in order to achieve the optimum grape quality. The aim was to study the effect of MeJ and MeJ+Urea foliar applications on the evolution of Tempranillo amino acids content throughout the grape maturation. Three treatments were foliarly applied, at veraison and 7 days later: control (water), MeJ (10 mM) and MeJ+Urea (10 mM+6 kg N/ha). Grape samples were taken at five stages of maturation: day before the first and second applications, 15 days after the second application (pre-harvest), harvest day, and 15 days after harvest (post-harvest). The amino acids analysis of the samples was carried out by HPLC. Results showed that the evolution of amino acids was similar regardless of the treatment; however, foliar applications influenced the nitrogen compounds content, i.e., there was no qualitative effect but quantitative one. Most of the amino acids reached their maximum concentration in pre-harvest, being higher in grapes from the treatments than in the control. In general, no differences in grape amino acids content were observed between MeJ and MeJ+Urea treatments. Foliar applications with MeJ and MeJ+Urea enhanced the grape amino acids content, without affecting their profile, helping to optimize their quality and allowing to establish a more complete grape ripening standard. Therefore, MeJ and MeJ+Urea foliar applications can be a simple agronomic practice, which has shown promising results in order to enhance the grape quality.

Late spring frost is a major challenge for various winegrowing regions across the world, its occurrence often leading to important yield losses and/or plant failure. Despite a significant increase in minimum temperatures worldwide, the spatial and temporal evolution of spring frost risk under a warmer climate remains largely uncertain. Recent projections of spring frost risk for viticulture in Europe throughout the 21st century show that its evolution strongly depends on the model approach used to simulate budburst. Furthermore, the frost damage modelling methods used in these projections are usually not assessed through comparison to field observations and/or frost damage reports.
The present study aims at comparing frost risk projections simulated using six spring frost models based on two approaches: a) models considering a fixed damage threshold after the predicted budburst date (e.g BRIN, Smoothed-Utah, Growing Degree Days, Fenovitis) and b) models considering a dynamic frost sensitivity threshold based on the predicted grapevine winter/spring dehardening process (e.g. Ferguson model). The capability of each model to simulate an actual frost event for the Vitis vinifera cv. Chadonnay B was previously assessed by comparing simulated cold thermal stress to reports of events with frost damage in Chablis, the northernmost winegrowing region of Burgundy. Models exhibited scores of κ > 0.65 when reproducing the frost/non-frost damage years and an accuracy ranging from 0.82 to 0.90.
Spring frost risk projections throughout the 21st century were performed for all winegrowing subregions of Bourgogne-Franche-Comté under two CMIP5 concentration pathways (4.5 and 8.5) using statistically downscaled 8×8 km daily air temperature and humidity of 13 climate models. Contrasting results with region-specific spring frost risk trends were observed. Three out of five models show a decrease in the frequency of frost years across the whole study area while the other two show an increase that is more or less pronounced depending on winegrowing subregion. Our findings indicate that the lack of accuracy in grapevine budburst and dehardening models makes climate projections of spring frost risk highly uncertain for grapevine cultivation regions.