Leaf elemental composition in a replicated hybrid grape progeny grown in distinct climates

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.

Over the past two decades, climate change has contributed to an increase in sugar content in grape must, and consequently, in the ethanol levels of wines.

Meta-analysis (MA) is a method that allows statistical synthesis of the results of several similar individual studies (Figure 1). This term was introduced by Glass in 1976 as a useful tool for the scientific community to pool and summarise the enormous amount of information collected in the literature.

Cabernet Sauvignon is the top red wine cultivar in CA, however, the hot climate in Fresno is not ideal for Cabernet Sauvignon, particularly for berry color development. Fruit-zone leaf removal and irrigation were studied previously to have the significant effect on grape yield performance and berry quality. But the timing of leaf removal and the timing of irrigation are still inconclusive. Also, mechanical fruit-zone leaf removal is relatively new in CA. Our study aims to identify the interactive effect of mechanical fruit-zone leaf removal and irrigation on Cabernet Sauvignon’s yield performance and fruit quality and find the ideal timing of leaf removal and irrigation to maximize the berry color while maintaining the sustainable yield level.

Berry texture and berry skin mechanical properties have high agronomic importance, related to quality and marketing requirements of wine, table and raisin grapes.