Recognition of terroir in american viticultural areas

Making high quality but affordable Pinot noir (PN) wine is challenging in most terroirs and New Zealand’s (NZ) situation is no exception. To increase the probability of making highly typical PN wines producers choose to grow grapes in cool climates on lower fertility soils while adopting labour intensive practices. Stringent yield targets and higher input costs necessarily mean that PN wine cost is high, and profitability lower, in line-priced varietal wine ranges. To understand the reasons why higher yielding vines are perceived to produce wines of lower quality we have undertaken an extensive study of PN in NZ. Since 2018, we established a network of twelve trial sites in three NZ regions to find individual vines that produced acceptable commercial yields (above 2.5kg per vine) and wines of composition comparable to “Icon” labels. Approximately 20% of 660 grape lots (N = 135) were selected from within a narrow juice Total Soluble Solids (TSS) range and made into single vine wines under controlled conditions. Principal Component Analysis of the vine, berry, juice and wine parameters from three vintages found grape berry mass to be most effective clustering variable. As berry mass category decreased there was a systematic increase in the probability of higher berry red colour and total phenolics with a parallel increase in wine phenolics, changed aroma fraction and decreased juice amino acids. The influence of berry size on wine composition would appear stronger than the individual effects of vintage, region, vineyard or vine yield. Our observations support the hypothesis that it is possible to produce PN wines that fall within an “Icon” benchmark composition range at yields above 2.5kg per vine provided that the Leaf Area:Fruit Weight ratio is above 12cm2 per g, mean berry mass is below 1.2g and juice TSS is above 22°Brix.

Air temperature is the key driver of grapevine phenology and a significant environmental factor impacting yield and quality for a winegrape growing region. In this study the optimal downscaled CMIP5 ensemble for computing thegrowing season average temperature (GST) viticulture climate classification index was determined to spatially compute on a decadal basis predictions of the GST climate index and the grapevine sugar ripeness (GSR) model for Pinot Noir throughout the Willamette Valley (WV) American Viticultural Area (AVA). Forecasts for average temperature and a 220 g/L target sugar concentration level were computed using daily Localized Constructed Analogs (LOCA) downscaled CMIP5 historic and Representative Concentration Pathways (RCP) future climate projections of minimum and maximum daily temperature. We explore spatiotemporal trends of the GST climate classification index and Pinot Noir specific applications of the GSR phenology model for the WV AVA. Spatiotemporal computations of the GST climate index and Pinot Noir specific applications of the GSR model enable the opportunity to explore relationships between their computed values with one intent being to provide updated GST ranges that better align with current temperature-based modeling understanding of Pinot Noir grapevine phenology and the viticultural application of LOCA CMIP5 climate projections for the WV AVA. The Pinot Noir specific applications of the GSR model or the GST index with updated bounds indicate that the percent of the WV AVA area suitable for Pinot Noir production is currently at or near its peak value in the upper 80s to lower 90s of this century.

The use of selected cultures of the species Lactiplantibacillus plantarum in Oenology has grown in prominence in recent years. While initial applications of this species centred very much around malolactic fermentation (MLF), there is strong evidence to show that certain strains can be harnessed for their bio-protective effects. Unwanted spontaneous MLF during alcoholic fermentation (AF), driven by rogue Oenococcus oeni, is a winemaking deviation that is very difficult to manage when it occurs. This work set out to determine the efficacy of one particular strain of Lactiplantibacillus plantarum(Viniflora® NoVA™ Protect), against this problem in Cabernet Sauvignon must. The work was carried out at commercial scale and in a winery environment and compared the bio-protective culture with the more traditional approach of reducing must pH by the addition of tartaric acid. The combination of both was also investigated. The concentration of both Oenococcus oeni and Lactiplantibacillus plantarum was determined using qPCR. The adventitious Oenococcus oeni showed the most growth during AF in the control wine, whereas in the wines treated with Lactiplantibacillus plantarum a bacteriostatic effect against this species was observed. This effect was comparable to the wines treated with tartaric acid. This has particular commercial relevance for controlling the flora in musts with high pH, or when the addition of tartaric acid is either not permitted or is prohibitive for other reasons.

There is currently a trend towards the production of wines with low alcohol content. To achieve this, grapes with low sugar content must be used. There are techniques at the vineyard level that can delay ripening and avoid excessive sugar accumulation without, a priori, affecting the final polyphenol content. Postveraison shoot trimming (PVST) is experimentally evaluated for these purposes, but its impact under Uruguayan climatic conditions with high interannual variability is not known. The aim of this work is to assess the PVST in Tannat and Merlot cultivars and their impact on yield components, plant balance and berry primary composition. In this study, two commercial vineyards of 10 years old Tannat and Merlot (grafted on SO4) at Canelones Department were selected. During the 2020-201 growing season, grapevines were submitted to PVST when grapes reached 15º Brix. In a randomized block, trimmed (T) and control (C) plants were evaluated with three repetitions each cultivar. Evaluation of the evolution of primary berry composition during ripening, measurement of yield components and plant balance were performed. For both cultivars, PVST did not affect yield components. Merlot reached 5.4 kg per plant and Tannat 7.1 kg, with not statistical significance between treatments. However, statistical differences were observed in terms of plant balance. In Merlot Ravaz Index reached a difference of 5.3 (12.0 in T and 6.7 in C) meanwhile Tannat reached 3.5 of statistical difference (13.7 in T and 10.2 in C). The tendency to imbalance for the treated plants had an impact on the final grape composition. Merlot grapes showed statistical difference in final total acidity (0.3 g of difference between treatments) while treatments impact final sugar content on Tannat grapes (10.0 g of difference between treatments). Further studies are needed to assess the impact of different canopy management techniques in our conditions.

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.