Drying process optimization in gummy confectionery production

Some issues related to jelly and gummy candies can be associated with errors or problems occurring in starch mogul processes. The main variables for this process include the properties of the starch used, as well as temperature and time. This process is critical for the final product quality and stability. For instance, gummy and jelly candies exhibit a wide range of textural properties, ranging from soft and easily bitten to hard and difficult to chew. Primarily, the characteristic textural properties of these candies are associated with the hydrocolloids used and the moisture content in the composition. The final product's moisture and texture can be directly influenced by mogul conditions. The type of hydrocolloid used for confectionery should also be considered in determination temperature and time. In this study, the changes over time (24, 28, 30, 32, and 36 hours for gelatine and starch gelatine, 24, 44 and 48 hours for starch samples) in some physicochemical (water activity, total solids, and pH), color (L*, a*, b*, chroma, hue angle), and texture (hardness, springiness, cohesiveness, gumminess, chewiness, and resilience) properties during the mogul process were investigated in samples prepared using different hydrocolloids (starch, gelatin-starch mixture and gelatin). No significant changes over time were determined in surface gloss (L*), pH, and water activity properties for the sample gropus. The critical values for characterization of gummy and jelly candies, hardness, and total dry matter, a* and v* values increased (P>0.05). The changes in springiness and gumminess properties were found to vary depending on the hydrocolloid used. Linear and/or polynomial models with high R2 (>0.900) values of 0th, 1st, and 2nd degree were determined particularly for springiness, hardness, and total dry matter properties in the kinetic modeling of these parameters. The models obtained from the study can be used in the production of jelly and gummy candies with different hardness and total dry matter amounts. Moreover, production efficiency can be increased by utilizing these models for optimization.