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

Water scarcity, high air temperatures, high vapor pressure deficit, and increasing frequency and intensity of extreme climatic events, namely heat waves, exert huge pressure on viticulture, as is the case of Mediterranean climates. Therefore, farmers rely more and more on irrigation to overcome these constraints. Deficit irrigation is a proved strategy to optimize irrigation efficiency and wine quality. The present study intends to demonstrate the application of precision techniques, namely remote sensing derived vegetation indices (VI) and an open source software, SIMDualKc, to compute crop evapotranspiration using the dual crop coefficient approach (Kcb + Ke), for deficit irrigation management.

“The Human being has an excellent ability to detect and discriminate odors but typically has great difficulty in identifying specific odorants”(1). Furthermore, “from a cognitive point of view the mechanism used to judge wines is closer to pattern recognition than descriptive analysis.” Therefore, when one wants to reveal the volatile “wine-like feature” pattern recognition techniques are required. Sensomics is one of the most recent “omics”, i.e. a holistic perspective of a complex system, which deals with the description of substances originated from microorganism metabolism that are “active” to human senses (2). Depicting the relevant volatile fraction in wines has been an ongoing task in recent decades to which several research groups have allocated important resources. The most common strategy has been the “target approach” in order to identify the “key odorants” for a given wine varietal.

Produced since 1998, the De Martino Single Vineyard Carmenère is the first Carmenère Icon wine of Chile. The grapes are coming form a plot of 11 ha in Isla de Maipo, where the technicians of the winery have developed knowledge of their work, resulting in 3 levels of quality of the grapes.

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 aroma represents one of the most important quality parameter and it is influenced by various factors (viticulture and vinification techniques, climate or storage conditions etc.). Wines produced from conventionally and ecologically grown grapes of same variety have different chemical composition and aroma profile [1]. Aroma profile of wine can be also influenced by additional treatment of wine, such as concentration of wine by reverse osmosis (RO). Reverse osmosis represents a pressure-driven membrane separation technique that separates the initial wine on the retentate or concentrate that is retained on the membrane, and permeate that passes through it [2]. Wine permeate usually containes water, ethanol, acetic acid and several low molecular weight compounds that can pass through the membrane. This property enables the use of reverse osmosis membranes for wine concentration, partial dealcoholization, acetic acid or aroma correction [3,4].