Date of Award

8-1-2024

Degree Name

Master of Science

Department

Plant, Soil, and Agricultural Systems

First Advisor

Choudhary, Dr. Ruplal

Abstract

This thesis investigates the viability of mung bean-based yogurt enriched with protein isolates as a dairy yogurt alternative. Through extensive analysis, Treatment 1 (1.5% cassava flour with oil-based mung bean yogurt) emerged as a promising option, exhibiting similar lightness in color to dairy yogurt. Moreover, Treatment 4 (1.5% cassava flour without oil-based mung bean yogurt) demonstrated the longest shelf life of 91 days based on microbial analysis, indicating the potential of oil-free formulations to delay spoilage and enhance shelf life. Texture characteristics, particularly hardness, and adhesiveness, were comparable to dairy yogurt in Treatment 1 and Treatment 2 (2% cassava flour with oil-based mung bean yogurt), with Treatment 3 (2.5% cassava flour with oil-based mung bean yogurt) showing similar adhesiveness to control yogurt. However, observations revealed a cracking defect in yogurt samples prepared without oil, escalating with storage time, supported by SEM images highlighting irregular textures in Treatment 6 (1.5% cassava flour without oil-based mung bean yogurt).Furthermore, the study developed artificial neural network (ANN) models for predicting shelf life, with physicochemical parameters (acidity, pH, and color values) proving to be the most effective inputs, yielding an r2 value of 0.9984. In comparison, microbial and sensory-based ANN models exhibited lower r2 values of 0.9015 and 0.9064, respectively. This underscores the importance of incorporating comprehensive data in developing accurate prediction models, advocating for further research to delve into additional yogurt properties for enhanced model realism. In conclusion, this thesis contributes to the understanding of mung bean-based yogurt formulation and storage, highlighting the potential of oil-free formulations for prolonged shelf life and identifying key physicochemical parameters for precise shelf-life prediction. Future endeavors should focus on collecting real-world data to refine prediction models, aiding yogurt manufacturers in ensuring food safety and facilitating informed consumer decisions regarding product shelf life.

Available for download on Sunday, October 11, 2026

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