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Optimization of the production and chemical evaluation of cassava-based cookies supplemented with mungbean flour and coconut pomace flour using optimal design model of response surface methodology was investigated. The variables were cassava flour, mungbean flour, and coconut pomace flour while responses were sensory and physical properties. The results of the ANOVA, R-square and adjusted R-square for sensory and physical properties were significant (p <.05). Three cookie samples (run 6, run14 and run 16) were selected from optimization results and compared with control (100% wheat flour cookies). Mungbean flour supplementation significantly (p <.05) increased crude protein and caloric value of cookies (run 14). A higher percentage of coconut pomace flour-enhanced ash, crude fiber, carbohydrate and total dietary fiber contents of cookies (run 16). The anti-nutrient contents of cookie samples were significantly higher than control but within the acceptable limits. [ABSTRACT FROM AUTHOR]

Background. Indigenous crops are known to help people in the tropics improve their food security. However, due to a lack of knowledge about their compositions, these advantages are not completely realized. Cocoyam and green gram are examples of underutilized crops rich in carbohydrate and protein content, respectively. This research looked at the functional characteristics, nutritional and antinutrient composition, and pasting properties of composite flours made from cocoyam and green gram. Materials and methods. A red variety of cocoyam tubers were processed into dried slices, milled, sieved, and packaged. The experimental design was performed by applying the response surface methodology. Eight (8) runs were formulated for the cocoyam and green gram flour blends. The independent variables were cocoyam flour and green gram flour with design constraints of 85.00-100.00% and 0.00-15.00%, respectively, while the dependent variables are the functional characteristics. Results. The addition of green gram flour significantly (p < 0.05) increases the bulk density, foaming capacity, gelation temperature, and oil absorption capacity of the blends. The proximate composition also showed that the addition of green gram flour enhanced the nutritional value, with run 2 having the overall best proximate composition of 18.29% crude protein, 1.44% crude fat, and 2.85% ash. Flour blends showed low antinutrient contents, while run 3 competes favorably with 100% cocoyam flour for pasting properties. Conclusion. The selected flour blends revealed a potential for value-added products like snacks and complementary foods. [ABSTRACT FROM AUTHOR]

Starch from cardaba banana is modified using octenyl succinic anhydride (OSA), the modification process is modeled using response surface methodology and partial least square regression analysis with the aim of optimizing the starch modification process to produce low digestibility starch. The modified starch is analyzed for digested starch (DS) as well as the starch digestibility index (SDI). The starch digestogram of the optimized starch, as well as the native, is also investigated using a multiphasic approach. The modeling revealed that both the response surface methodology (RSM) and partial least square regression (PLS‐R) model predict with high accuracy (r2 [coefficient of determinant] > 0.9) the dependent variables. According to the statistical indices, the RSM model makes a better prediction when compared to the PLS‐R model. The optimized conditions for the production of modified starch with low starch digestibility are an OSA concentration of 3.98%, reaction time of 47.45 min, and pH of 10 with a predicted DS of 45.99% and SDI value of 29.86%. Modeling the optimized and native starch digestogram reveals the digestogram follows a multiphasic digestogram with the digestion occurring in three (3) segments. The digestion rate of the starch follows a rapid‐slow and slow‐rapid in vitro starch digestion rate. [ABSTRACT FROM AUTHOR]