Modeling viticultural landscapes: a GIS analysis of the viticultural potential in the Rogue Valley of Oregon

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.

Wine terroir describes the collectively recognized relation between a geographical area and the distinctive organoleptic characteristics of the wines produced in it. The overriding objective in terroir studies is therefore to provide scientific proof relating the properties of terroir components to wine quality and typicity. In scientific circles, the role of climate (macro-, meso- and micro-) on grape and wine characteristics is well documented and accepted as the most critical. Moreover, there has been increasing interest in recent years about new elements with possible importance in shaping wine terroir like berry/leaf/soil microbiology or even aromatic plants in proximity to the vineyard conferring flavors to the grapes. However, the actual effect of these factors is also dependent on complex interactions with plant material (variety/clone, rootstock, vine age) and with human factors.
The contribution of soil, although a fundamental component of terroir and extremely popular among wine enthusiasts, remains a much-debated issue among researchers. The role of geology is probably the one mostly associated by consumers with the notion of terroir with different parent rocks considered to give birth to different wine styles. However, the relationship between wine properties and the underlying parent material raises a lot of controversy especially regarding the actual existence of rock-derived flavors in the wine (e.g. minerality). As far as the actual soil properties are concerned, the effect of soil physical properties is generally regarded as the most significant (e.g sandy soils being associated with lighter wines while those on clay with colored and tannic ones) mostly through control of water availability which ultimately modifies berry ripening conditions either directly by triggering biosynthetic pathways, or indirectly by altering vigor and yield components. The role of soil chemistry seems to be weakly associated to wine sensory characteristic, although N, K, S and Ca, but also soil pH, are often considered important in the overall soil effect.
Recently, in the light of evidence provided by precision agriculture studies reporting a high variability of vineyard soils, the spatial scale should also be taken into consideration in the evaluation of the soil effects on wines. While it is accepted that soil effects become more significant than climate on a local level, it is not clear whether these micro-variations of vineyard soils are determining in the terroir effect. Moreover, as terroir is not a set of only natural factors, the magnitude of the contribution of human-related factors (irrigation, fertilization, soil management) to the soil effect still remains ambiguous. Lastly, a major shortcoming of the majority of works about soil effects on wine characteristics is the absence of connection with actual vine physiological processes since all soil effects on grape and wine chemistry and sensorial properties are ultimately mediated through vine responses.
This article attempts to breakdown the main soil attributes involved in the terroir effect to suggest an improved understanding about soil’s true contribution to wine sensory characteristics. It is proposed that soil parameters per se are not as significant determining factors in the terroir effect but rather their mutual interactions as well as with other natural and human factors included in the terroir concept. Consequently, similarly to bioclimatic indices, composite soil indices (i.e. soil depth, water holding capacity, fertility, temperature etc), incorporating multiple soil parameters, might provide a more accurate and quantifiable means to assess the relative weight of the soil component in the terroir effect.

The main innovation in the VINIoT service is the joint use of two technologies that are currently used separately: vineyard monitoring using multispectral imaging and deployed terrain sensors. One part of the system is based on the development of artificial intelligence algorithms that are feed on the images of the multispectral camera and IoT sensors, high-level information on water stress, grape ripening status and the presence of diseases. In order to obtain algorithms to determine the state of ripening of the grapes and avoid losing information due to the diversity of the grape berries, it was decided to work along the first year 2020 at berry scale in the laboratory, during the second year at the cluster scale and on the last year at plot scale. Different varieties of white and red grapes were used; in the case of Galicia we worked with the white grape variety Treixadura and the red variety Mencía. During the 2020 and 2021 campaigns, multispectral images were taken in the visible and infrared range of: 1) sets of 100 grapes classifying them by means of densimetric baths, 2) individual bunches. The images taken with the laboratory analysis of the ripening stage were correlated. Technological maturity, pH, probable degree, malic acid content, tartaric acid content and parameters for assessing phenolic maturity, IPT, anthocyanin content were determined. It has been calculated for each single image the mean value of each spectral band (only taking into account the pixels of interest) and a correlation study of these values with laboratory data has been carried out. These studies are still provisional and it will be necessary to continue with them, jointly with the training of the machine learning algorithms. Processed data will allow to determine the sensitivity of the multispectral images and select bands of interest in maturation.

Elevated temperature during the grape maturation period is a major threat for grape quality and thus wine quality. Therefore, characterizing the grape composition response to temperature at a larger scale would represent a crucial step towards adaptation to climate change. In response to changes in temperature, various physiological mechanisms regulate grape composition. Primary and secondary metabolisms are both involved in this response, with well-known effects, for example on anthocyanins, and lesser known effects, for example on aromas or aroma precursors. At the field scale or at the regional scale, however, numerous environmental or plant-specific factors intervene to make the effects of temperature difficult to distinguish from overall variability. In this study, it was attempted to overcome this difficulty by selecting well-characterized situations with differing temperatures.
A long-term study of air temperature variability across several Merlot vineyards in the Saint-Emilion and Pomerol wine producing area found significant temperature differences and gradients at various time scales linked to environmental factors. From this study area, a few sites were selected with similar age, soil and training system conditions, and with repeated and contrasted temperature differences during the maturation period. The average temperature difference during the maturation period was about 2°C between cooler and warmer sites, a difference similar to that expected under future climate change scenarios. In close vicinity to the temperature sensors at each site, grape berries were sampled at different times until full maturity during 2019 and 2020. Also, berries from bunches on either side of the row were analyzed separately, allowing an investigation of bunch exposure effect associated with the coupling of berry temperature and solar radiation. Four replicates of pooled berries for each time – site – bunch exposure combination were obtained and analyzed for biochemical composition. Analyses of variance of the biochemical composition data collected at different sampling times reveal significant effects associated with temperature, site, and bunch azimuth. For instance, anthocyanins in grape skins are clearly influenced by temperature and solar radiation exposure, with up to 30% reduction in warmer conditions.

Commercial grape production relies on training grapevine cultivars onto a variety of trellis systems. Training allows for well-lit leaves and clusters, maximizing fruit quality in addition to facilitating cultivation, harvesting, and diseases control. Although grapevines can be trained onto an infinite variety of trellis systems, most red and white cultivars are trained to the standard VSP (Vertical Shoot Positioning) system. However, red and white cultivars respond differently to VSP in fruit composition and growth characteristics, which are yet to be fully understood. Therefore, the objective of this study was to examine the influence of the VSP trellis system on fruit composition of three red, Cabernet Sauvignon, Merlot and Syrah, and three white, Chardonnay, Riesling, and Gewurztraminer cultivars grown under uniform growing conditions in the same vineyard. All cultivars were monitored for maturity and harvested at their physiologically maximum possible sugar concentration to compare various fruit quality attributes such as Brix, pH, TA, malic and tartaric acids, glucose and fructose, potassium, YAN, and phenolic compounds including total anthocyanins, anthocyanin profile, and tannins. A distinct pattern in fruit composition was observed in each cultivar. In regards to growth characteristics, Syrah grew vigorously with the highest cluster weight. Although all cultivars developed pyriform seeds, the seed size and weight varied among all cultivars. Also varied were mesocarp cell viability, brush morphology, and cane structure. This knowledge of the canopy architectural characteristics assessed by the widely employed fruit compositional attributes and growth characteristics will aid the growers in better management of the vines in varied situations.