Project Number: 5358-21000-041-32
Project Type: Grant

Start Date: Sep 01, 2011
End Date: Sep 30, 2013

Objective:
1. Determine if late season foliar N applications can increase grape berry N concentration, content fermented wine flavor compounds. 2. Compare conventional soluble synthetic N sources to soluble organic N sources for their suitability to supplement grapevine nutrition with late season foliar applications. 3. Evaluate the effect of late season foliar N application on plant N concentration (fruit, leaves, petioles) as well fruit amino acid concentrations and other secondary metabolites (e.g., phenolics) which may have health benefits to the consumer. 4. Evaluate the effect of late season foliar N application on canopy vigor.

Approach:
Two vineyards, Merlot (red) and Riesling (white), will be identified. The vineyards will be well established (>9 years old), managed with regulated deficit irrigation and trained to a bilateral cordon. Replicated plots will be established in each vineyard. Rows will be chosen so that there are no missing vines in each plot. A single rate of liquid urea will be used for the conventional N fertilizer, since it is readily absorbed, does not burn, and provides only N. Materials will be applied weekly for 5 different applications beginning at veraison and ending in mid-September. To evaluate any influence of nutrient solution run-off from plant leaves, pans will be placed under the canopy in a known area during the spray events and the amount of run off collected and extrapolated to the plot size. Blade and petiole samples will be collected, prior to foliar spraying, at bloom and veraison in the second year to determine if the previous year’s foliar treatments influenced plant N concentration. Yield, plant nitrogen measurements, and harvest fruit quality data will be analyzed using Analysis of Variance (ANOVA) as the plot design is a randomized complete block design. Fermentation rate data will be analyzed as a time series. For secondary metabolites and phenolic compounds, relationships to in field treatments will be evaluated through the use of traditional ANOVA and regression analysis as well as principle component analysis to evaluate any changes in composition related to N treatments.