Optimizing high-altitude peach fermentation biochemistry across the Colorado front range via 2x3 mixed level full factorial design

Colorado produces ~ 15,000 tons of peaches annually, yet peach wine production on the Colorado Front Range is challenged by a high-altitude microclimate characterized by elevated solar radiation, a shortened growing season, and reduced atmospheric pressure that decreases oxygen mass transfer during fermentation. This study employed a 2 × 3 mixed-level full-factorial Design of Experiments (DOE) to optimize primary fermentation by evaluating two YAN levels (150 and 300 mg/L) and three aeration rates (0.0, 5.5, and 11.0 L/day). To minimize variation associated with indigenous microorganisms, peach musts were inoculated with a standardized Saccharomyces cerevisiae strain following fruit sanitization. Day-18 residual sugar and ethanol concentration were analyzed using analysis of variance (ANOVA), factorial regression modeling, and multi-response treatment evaluation. Both regression models demonstrated excellent performance, explaining 96.95% of the variation in residual sugar (p < 0.001) and 90.26% of the variation in ethanol concentration (p = 0.005). Significant YAN × aeration interactions were identified for both response variables, demonstrating that nitrogen supplementation and oxygen availability should be optimized jointly rather than independently. Multi-response evaluation identified 150 mg/L YAN and 11.0 L/day aeration as the best-performing tested treatment combination, producing an off-dry to semi-sweet wine with 12.3% (v/v) ethanol and 23.9 g/L residual sugar. These findings provide an evidence-based process optimization strategy for high-altitude peach wine fermentation and demonstrate the value of factorial experimental design for optimizing interacting fermentation variables.