Traditional beers, such as palm wine, kombucha and others, are notable beverages consumed all over the globe. Such beverages historically contribute to food security on a global scale. Umqombothi is a South African traditional beer nutritionally packed with minerals, amino acids, B-group vitamins and much-needed calories. As a result, the production and consumption of this traditional beverage has been an integral part of South African’s social, economic and cultural prosperity. Unfortunately, difficulties in bioprocessing operations have limited its availability to household and small-scale production. It is at these micro-production scales that poor hygiene practices and the use of hazardous additives and contaminated raw materials continue to increase, posing serious health risks to the unassuming consumer. This study provides an overview of the processing steps and underlying techniques involved in the production of umqombothi, while highlighting the challenges as well as future developments needed to further improve its quality and global competitiveness with other alcoholic products.

Bioprocess development for umqombothi (a South African traditional beer) as with other traditional beer products can be complex. As a result, beverage bioprocess development is shifting towards new systematic protocols of experimentation. Traditional optimization methods such as response surface methodology (RSM) require further comparison with a relevant machine learning system. Artificial neural network (ANN) is an effective non-linear multivariate tool in bioprocessing, with enormous generalization, prediction, and validation capabilities. ANN bioprocess development and optimization of umqombothi were done using RSM and ANN. The optimum condition values were 1.1 h, 29.3 °C, and 25.9 h for cooking time, fermentation temperature, and fermentation time, respectively. RSM was an effective tool for the optimization of umqombothi’s bioprocessing parameters shown by the coefficient of determination (R2) closer to 1. RSM significant parameters: alcohol content, total soluble solids (TSS), and pH had R2 values of 0.94, 0.93, and 0.99 respectively while the constructed ANN significant parameters: alcohol content, TSS, and viscosity had R2 values of 0.96, 0.96, and 0.92 respectively. The correlation between experimental and predicted values suggested that both RSM and ANN were suitable bioprocess development and optimization tools.

Umqombothi (a South African indigenous beer) is an important dietary beverage for many undernourished, low-income consumers in rural, semi-urban and urban areas. Umqombothi was brewed using optimal conditions earlier obtained and compared to the customary beer brew (CB) and mixed raw ingredients (RI). The products were evaluated for proximate compositions, minerals, amino acids, B-group vitamins, and sugar compounds. The optimised beer brew (OPB) was relatively higher in energy (165 kcal), crude protein (8.6%), and ash content (1.0%). The CB had the highest concentration of sodium (299.8 mg/kg), magnesium (1170.5 mg/kg), potassium (2993.8 mg/kg), and phosphorus (2100.7 mg/kg). Glutamic acid was the highest detected amino acid, with concentrations of 1.5 g/100 g, 1.5 g/100 g, and 1.6 g/100 g in the RI, CB, and OPB, respectively. The OPB contained a higher concentration of the two forms of vitamin B3, nicotinamide (0.2 µg/g) and nicotinic acid (0.7 µg/g) in comparison to the CB. The concentration of the antioxidant, mannitol, was 0.4 mg/g, 0.2 mg/g, and 2.0 mg/g in the RI, CB, and OPB respectively. Overall, OPB displayed a desirable nutritional profile compared to the CB.

It is common to find different spoilage organisms occurring in the same food item, which usually requires food producers to utilize a mixture of synthetic preservatives to control spoilage. This study evaluated the interaction between mixtures of crude biopreservatives against consortia of common spoilage yeasts occurring in beverages. Crude biopreservatives produced from separate yeasts were formulated in different growth inhibition combinations (GICs), i.e., GIC1 (Candida pyralidae Y1117 and Pichia kluyveri Y1125), GIC 2 (C. pyralidae Y1117 and P. kluyveri Y1164), GIC3 (P. kluyveri Y1125 and P. kluyveri Y1164), and GIC4 (C. pyralidae, P. kluyveri Y1125 and P. kluyveri Y1164). The spoilage yeast consortia combinations, i.e., SC1 (Dekkera. anomala and D. bruxellensis), SC2 (D. anomala and Zygosaccharomyces bailii), SC3 (D. bruxellensis and Z. bailii), and SC4 (D. anomala, D. bruxellensis and Z. bailii), were also prepared. The highest growth inhibition activities of the crude biopreservatives were observed at a pH of 3.0 and 2.0 for C. pyralidae and P. kluyveri strains, respectively, while reduced activity was observed at a pH of 4.0 and 5.0. The growth inhibition proficiency depended on the spoilage yeast or the consortia of spoilage yeasts. Biocontrol agents from an individual yeast or mixtures can be used to prevent food and beverage spoilage.