Quality aroma improvement of Muscat wine spirits: A new approach using first-principles model-based design and multi-objective dynamic optimisation through multi-variable analysis techniques

Abstract

This work proposes a model-based methodology to produce recipes for Muscat wine distillations in Charentais alembics. The recipes were obtained by dynamic multi-objective optimisation of a multi-component first-principles model. Two multi-objective functions were developed considering chemical markers that define the aromatic characteristic of the distillates. The first function included three chemical markers characteristic of each distillation cut (head, heart and tail). The second considered a principal component analysis (PCA) applied to the chemical profile of Chilean commercial distillates. The optimal recipes were experimentally validated in an automatic Charentais alembic using a synthetic Muscat wine consisting of ethanol and water, plus six congeners. The experimental results indicated that by using model-based optimisation techniques, it is possible to obtain spirits with a chemical composition like some Chilean commercial distillates. In addition, the chemical composition of many commercial distillates was close to a Pareto front that defines a compromise between linalool, a characteristic Muscat floral aroma, and acetaldehyde, a head contaminant marker.