Modeling and optimization of quality indicators of blanched and dried cowpea leaves by Response Surface Methodology (RSM)

This study focused on modeling and optimizing the quality attributes of blanched and dried cowpea leaves using Response Surface Methodology (RSM). Cowpea leaves were subjected to varying blanching durations (0-4 min), blanching temperatures (70-90 °C), and drying temperatures (50-70 °C) to assess their effects on key quality indicators. A Box-Behnken design was employed to conduct the experiments. Responses measured included color parameters ( L ∗ , a ∗ , b ∗ , hue, chroma , total color difference, and browning index), ascorbic acid, and mineral contents (iron, zinc, and calcium). The data were fitted to second-order regression models, and a desirability function was used for optimization using Design Expert Version 13 (Stat-Ease Inc., USA). The fitted models for color attributes and iron content showed good predictive power, with R 2 values ranging from 0.7480 to 0.9442. Increases in blanching time and temperature generally reduced the color parameters ( L ∗ , a ∗ , b ∗, and chroma) and iron content, as well as the total color difference and browning index. Drying temperature had minimal effect, except on greenness ( a ∗). The optimized conditions—4 minutes of blanching at 90 °C and drying at 50 °C—resulted in minimal color degradation and maximum nutrient retention. The optimized dried cowpea leaves exhibited favorable nutritional quality and appearance, indicating their potential contribution to food security.