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We have modelled here odor threshold properties (OTP) of various aroma components present in different types of wine using quantitative structure–property relationship (QSPR) studies employing both two-dimensional and three-dimensional descriptors. The aim has been to identify the molecular properties essential for lowering the OTP. We have applied different variable selection strategies to select the most relevant descriptors prior to the development of the final partial least squares (PLS) regression model, which was validated extensively using different validation metrics in terms of acceptability and predictivity of the model for enhancing confidence in QSPR predictions. Using the developed PLS model, we have also predicted the “composite” OTP of different types of wine using the “composite” descriptor values based on individual components according to the PLS model and the results were well corroborated with the observations reported by Wang et al. [Food Chem., 2017, 226, 41–50]. The developed model may guide us to understand the dependence of the odor quality of different types of wines obtained under different manufacturing conditions on their aroma constituents.

Chemometric modeling of odor threshold property of diverse aroma components of wine