Glycosylated Aroma Compound Responses in ‘Riesling’ Wine Grapes to Cluster Exposure and Vine Yield

Abstract

Concentrations of aroma precursor compounds in ‘Riesling’ wine grapes (Vitis vinifera) are reported to correlate with fruit zone cluster exposure, although optimal cultural influences with respect to exposure timing and canopy assessment methods have not been established. To determine the impact of cluster exposure on concentrations of potential aroma compounds, correlations between light exposure metrics during the growing season and relative concentrations of eight representative aroma compounds at harvest were determined. The aroma compounds were carbon-13 (C13) norisoprenoids [1,1,6-trimethyl-1,2-dihydronaphthalene (TDN), β-damascenone, and vitispirane], monoterpenes (linalool oxide, α-terpineol), and phenolics (4-vinylguaiacol, vanillin and eugenol). Cluster exposure was determined using metrics of varying spatial precision [percent interior cluster (PIC), cluster exposure layer (CEL), ln(CEL), cluster exposure flux availability (CEFA), and the percent ambient photosynthetic photon flux (PPF)] at two sites and two phenological stages (fruit set and veraison) in two consecutive seasons (2008 and 2009). Pairwise combinations of cluster exposure metrics and compounds resulted in 360 permutations, of which 22 were significant. Response data suggested that none of the compounds studied respond to variable cluster exposure levels below 20% of ambient sunlight (CEFA < 0.2), and that low cluster exposure may be particularly effective in minimizing C13 norisoprenoid concentrations at harvest. Yield components were also tested but found to have lower R2 values compared with cluster exposure metrics. Active canopy management, in which vine vigor and fruit exposure are independently controlled, is likely to be more effective in influencing potential aroma compounds than selectively harvesting for naturally occurring variation in cluster exposure. In comparing the relative predictive strength among metrics, CEFA ≅ ln(CEL) > CEL > PIC ≅ percent PPF, suggesting that cluster exposure metrics with greater spatial sensitivity are more effective for establishing light response curves.