Formulation and characterization of a low-cost high-energy grain-based beverage premix: A multi-objective genetic algorithm approach

Abstract

There is a huge demand for low cost healthy energy drinks amongst the consumers. A novel multigrain beverage premix (MGBP) was formulated using barley, pearl millet, quinoa, and yellow split pea by multi-objective genetic algorithm (MOGA) technique. The effects of processing like roasting and malting on nutritional compositions and correlations were studied using principal component analysis (PCA). Malting had significant effect on almost all nutritional components (p < 0.05). Roasting increased the total carbohydrate content by 67.7% in yellow split pea and 77.2% in barley flours. The Pearson correlation coefficient demonstrated a strong correlation of energy content with carbohydrate and fat content. The optimum combination obtained from MOGA and validated by fuzzy analysis was 30, 28, 30 and 12 g of roasted yellow pea flour (RYPF), roasted pearled barley flour (RPBF), malted pearl millet flour (MPMF) and malted quinoa flour (MQF), respectively per 100 g of MGBP with an energy value of 345.8 kcal and cost Rs. 4.88. The processing triggered the protein-starch interaction and agglomeration as confirmed by scanning electron microscopy (SEM); however, the chemical structure remained intact as revealed by Fourier transform infrared (FTIR) spectroscopy.

Keywords

• Multigrain premix
• Genetic algorithm
• Fuzzy logic
• Principal component analysis
• SEM
• FTIR