Importance of the Terror Variability Map (TVM) in Precision viticulture (PV): choice of methodology for soil classification

In order to study the impact of climate change on Bordeaux grape varieties and to assess the adaptation capacities of candidates to the grape varieties of this wine region to the new climatic conditions, an experimental block design composed of 52 grape varieties was set up in 2009 at the INRAE Bordeaux Aquitaine center. Among the many parameters studied, the three main phenological stages of the vine (budburst, flowering and veraison) have been closely monitored since 2012. Observations for each year, stage and variety were carried out on four independent replicates. Precocity indices have been calculated from the data obtained over the 2012-2021 period (Barbeau et al. 1998). This work allowed to group the phenological behaviour of the grapevine varieties, not only based on the timing of the subsequent developmental stages, but also on the overall precocity of the cycle and the total length of the cycle between budburst and veraison. Results regarding the variability observed among the different grape varieties for these phenological stages are presented as heat maps.

The planet is warmer than at any time in our recorded past and increasing greenhouse emissions and persistence in the climate system means that continued warming is highly likely. Climate change has already altered the basic framework of growing grapes for wine production worldwide and will likely continue to do so for years to come. The wine sector can continue to play an important role in leading the agricultural sector in addressing climate change. From developing on…

Copper (Cu) is widely and historically used in viticulture as a fungicide against mildew. Cu has a strong affinity for soil organic matter and accumulates in topsoil horizons. Thus, Cu may negatively affect soil organisms and plants, consequently reducing soil fertility and productivity. The Bordeaux vineyards have the largest vineyard surfaces (26%) within French controlled appellation and a great proportion of French wine production (around 5 million hl per year). Considering the local context of vineyard surfaces decreasing (vine uprooting) and possible new crop plantation, the issue of Cu potential toxicity rises. Therefore, the aims of this work are firstly to evaluate the Cu contamination in vineyard soils of Bordeaux, secondly to produce a risk assessment map for new vine or crop plantation. We used soil analyses from several local studies to build a database with 4496 soil horizon samples. The database was enhanced by means of pedotransfer functions in order to estimate the bioaccessible (EDTA-extractable) Cu in soils of samples without measurements. From this database, 1797 georeferenced samples with CuEDTA concentrations in the topsoil (0-50 cm depth) were used for kriging interpolation in order to produce the spatial distribution map of CuEDTA in vineyard soils. Then, the spatial distribution of Cu was crossed with vine uprooting surfaces and municipality boundaries. CuEDTAconcentrations ranged from 0.52 to 459 mg/kg and showed clear anomalies. Our results from spatial analysis showed that almost 50% of vineyard soil surfaces have CuEDTA concentrations higher than 30 mg/kg (moderate risk for new plantation) and 20% with concentrations higher than 50 mg/kg (high risk for new plantation). A decision-support map based on municipalities was realised to provide a simple tool to stakeholders concerned by land use management.

Knowledge on the reflectance spectrum of soil is potentially useful since it carries information on soil chemical composition that can be used to the planning of agricultural practices. If compared with analytical methods such as conventional chemical analysis, reflectance measurement provides non-destructive, economic, near real-time data. This paper reports results from reflectance measurements performed by spectroradiometry on soils from two vineyards in south Brazil. The vineyards are close to each other, are on different geological formations, but were subjected to the same management. The objective was to detect spectral differences between the two areas, correlating these differences to variations in their chemical composition, to assess the technique’s potential to predict soil attributes from reflectance data.To that end, soil samples were collected from ten selected vine parcels. Chemical analysis yield data on concentration of twenty-one soil attributes, and spectroradiometry was performed on samples. Chemical differences significant to a 95% confidence level between the two studied areas were found for six soil attributes, and the average reflectance spectra were separated by this same level along most of the observed spectral domain. Correlations between soil reflectance and concentrations of soil attributes were looked for, and for ten soil traits it was possible to define wavelength domains were reflectance and concentrations are correlated to confidence levels from 95% to 99%. Partial Least Squares Regression (PLSR) analyses were performed comparing measured and predicted concentrations, and for fifteen out of 21 soil traits we found Pearson correlation coefficients r > 0.8. These preliminary results, which have to be validated, suggest that variations of concentration in the investigated soil attributes induce differences in reflectance that can be detected by spectroradiometry. Applications of these observations include the assessment of the chemical content of soils by spectroradiometry as a fast, low-cost alternative to chemical analytical methods.

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.