Soil management of interrow spacing as an important factor to protect the vineyard soils from runoff and erosion under the Mediterranean climate

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.

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 use of resistant varieties is a long-term but promising solution to reduce chemical input in viticulture. Several important breeding programs in Europe and abroad are now releasing a range of new hybrids performing well regarding fungi susceptibility and producing good quality wines. Unfortunately, insufficient attention is paid by the breeders to the adaptation of these varieties to climatic changes, notably to the increased climatic demand and water deficit (WD). Thus, prior to the adoption of such varieties by the wine industry in Mediterranean regions, there is a need to consider their suitability to WD. This study aimed to characterize the different drought-strategies adopted by 6 new resistant varieties selected by INRAE in comparison to Syrah. To allow the assessment of long-term impacts of WD, field-grown vines were exposed to contrasted WD from 2018 to 2021 under a semi-arid Mediterranean climate. A gradient of WD was applied in the field and controlled through plant measurements at the single plant level. Grape development was non-destructively monitored to determine the arrest of berry phloem unloading. The impacts of WD on berry composition, including water, primary metabolites (sugars, organic acids), secondary metabolites (anthocyanins, thiols precursors) and main cations contents, were assessed at this specific stage. Results showed different varietal responses during the year and inter-annual acclimation in terms of plant water use efficiency, biomass accumulation, as well as yield components and berry composition. WD differentially reduced the accumulation of primary metabolites at plant and berry levels, but it little changed their concentrations in the fruits at the ripe stage. Moreover, WD differentially impacted the accumulation of secondary metabolites and major cations between the varieties. In the talk, we’ll present the main results regarding the WD impacts on fruit metabolites and enlarge the reflection about the practical assessment of the grapevine acclimation to WD.

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.

Probably one of the most counterintuitive impacts of climate change on vine is the increased frequency of late frost. Champagne, due to its septentrional position is historically and regularly affected by this meteorological hazard. Champagne has therefore developed a strong experience in frost protection with first experiments dating from the end of 19th century. Frost protection can be divided in two parts: passive and active. Passive protection includes all the methods that do not seek to modify the vine’s environment or resistance at the time of frost. The most iconic passive protection in Champagne is the establishment of the individual reserve. This reserve allows to stock a certain quantity of clear wine during a surplus year to compensate a meteorological hazard like frost during the following years. Other common passive methods are the control of planting area (walls, bushes, topography), the choice of grape variety, late pruning, or the impact of grass cover and tillage. Active frost protection is also divided in two parts. Most of the existing techniques tend to modify vine’s environment. Most of the time they provide warmth (candles, heaters, windmills, heating cables…), or stabilise bud’s temperature above a lethal threshold (water sprinkling). The other way to actively fight is to enhance the resistance of buds to frost (elicitors). The Comité Champagne evaluates frost protection methods following three main axes: the efficiency, the profitability, and the environmental impact through a lifecycle assessment. This study will present the results on both passive and active protection following these three axes.