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The overall purpose of the project, of which this study is a part, was to examine the feasibility of onion waste as a support-substrate for the profitable production of food-grade products. This study focused on the efficient production of ethanol from worthless onions by transforming the onion juice into onion liquor via alcoholic fermentation with the yeast Saccharomyces cerevisiae. The onion bioethanol produced could be later used as a favorable substrate for acetic fermentation to finally obtain onion vinegar. Near-infrared spectroscopy (NIRS), coupled with the multivariate curve resolution-alternating least squares (MCR-ALS) method, has been used to reveal the compositional and spectral profiles for both substrates and products of alcoholic fermentation runs, that is, total sugars, ethanol, and biomass concentration. The ambiguity associated with the ALS calculation was resolved by applying suitable inequality and equality constraints. The quality of the results provided by the NIR-based MCR-ALS methodology adopted was evaluated by several performance indicators, including the variance explained by the model, the lack of fit and the agreement between the MCR-ALS achieved solution and the results computed by applying previously validated PLS reference models. An additional fermentation run was employed to test the actual predictive ability of the ALS model developed. For all the components resolved in the fermentation system studied (i.e., total sugars, ethanol, and biomass), the final model obtained showed a high predictive ability and suitable accuracy and precision, both in calibration and external validation, confirmed by the very good agreement between the ALS responses and the reference values (the coefficient of determination was, in all cases, very close to 1, and the statistics confirmed that no significant difference was found between PLS reference models and the MCR-ALS methodology applied). Thus, the proven reliability of the MCR-ALS model presented in this study, based only on NIR measurements, makes it suitable for monitoring of the key species involved in the alcoholic fermentation of onion juice, allowing the process to be modeled and controlled in real time.