Enhancing the functionality of extruded snack (namkeen) using indigenous ingredients of Uttarakhand, India: A predictive modelling approach for shelf-life optimization

This study aimed to assess the impact of incorporating indigenous ingredients of Uttarakhand, India, on the properties of flour and the development of extruded snack (namkeen). Initially, the physico-chemical, pasting properties, surface morphology, techno-functional properties, and elemental composition of gram flour and composite flour were evaluated. The results revealed distinct properties that influenced their suitability for namkeen production. The developed namkeen had notable nutritional attributes included a protein content of 16.41%, fat content of 26.80%, and crude fiber content of 14.36%. Sensory evaluations of namkeen revealed that sample K (10% GF, 30% R, 10% HGR, 5% YRF, and 1% JP) was preferred over other variations (A-J). Sample A exhibited a hardness value of 3835.36 N, indicating a relatively firm texture, while sample E displayed the lowest hardness value of 2239.11 N, suggesting a softer consistency. The peroxide value of the namkeen increased from 3.1 mM peroxide/g to 7.54 and 4.23 mM peroxide g−1 in low density polyethylene (LDPE) and laminated aluminum pouches (LAP)-packaged namkeen, respectively, after two months, but the trend showed a decrease after six months at 37 °C. After 6 months, the acid value of LDPE-packaged namkeen was higher (0.65 mg KOH g−1) compared to LAP-packaged namkeen (0.47 mg KOH g−1) and the control (0.11 mg KOH g−1). Similarly, the FFA content of LDPE-packaged namkeen (0.33%) was similar to LAP-packaged namkeen (0.34%) but significantly higher than the control (0.06%). Despite some deterioration, LAP-packaged namkeen maintained relatively higher overall acceptability scores, with a score of 7.08 after 6 months, compared to polythene-packaged namkeen (5.93). The Baranyi equation showed R2 ≥ 0.9051 indicating good accuracy of the theoretical model for predicting quality and shell life. The study concluded that indigenous ingredients are effective for developing functional snacks, and predictive modeling accurately estimates shelf life. Highlights