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Create Wine Aging Optimization Systems for Quality Prediction

Wine aging remains largely empirical with limited ability to predict optimal aging periods or outcomes, leading to economic inefficiencies and quality inconsistencies. The challenge is developing systems that can monitor and predict aging progress, optimizing storage conditions and timing decisions for individual wines. This requires understanding aging chemistry, developing monitoring technologies, and creating predictive models for quality development. Current aging decisions rely on periodic tasting and general guidelines rather than objective measurement of aging progress. Technical barriers include developing non-invasive monitoring methods, understanding complex aging chemistry, and creating models that account for wine variability. Success would optimize aging decisions, reduce storage costs, improve quality consistency, prevent over- or under-aging, and provide aging management tools applicable to other fermented products requiring extended maturation periods for quality development.

Applied Sciences, Specialized Agriculture, Viticulture & Enology