1. Optimization of the Heat-Drying Conditions of Drone Pupae by Response Surface Methodology (RSM)
- Author
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SeungHee Baek, Agapito Sheryl Mae, and InSik Nam
- Subjects
edible insect ,drone pupae ,RSM ,color ,blanching ,heat-drying ,Chemical technology ,TP1-1185 - Abstract
Recent research has been conducted on various types of pre-processing methods for insects, including freeze-drying, microwave drying, hot air heat drying, and non-heat drying. This study aimed to identify the factors that have the greatest impact on heat drying conditions and establish the optimal heat drying conditions for drone pupae (Apis melifera L.) using response surface methodology (RSM) to minimize quality changes. Drone pupae were treated under various conditions, including blanching time (53–187 s) (X1), drying temperatures (41.6–58.4 °C) (X2), and drying time (266–434 min) (X3). The effect of these treatments on response variables, including the color parameter (WI, YI, BI, △E, and BD), AV, and TB of the dried drone pupae, was evaluated using a central composite design. The whole design consisted of 20 experimental points carried out in random order, which included eight factorial points, six center points, and six axial points. The optimal drying conditions for drone pupae were determined to be a blanching time of 58 s, a drying temperature of 56.7 °C, and a drying time of 298 min. The response variables were most affected by drying temperature and drying time and to a lesser extent by blanching time. The processed drone pupae using the optimized drying conditions resulted in the color parameters (WI, BI, YI, ΔE, and BD) being found to be 66.67, 21.33, 26.27, 31.27 and 0.13, respectively. And TB (log CFU/g) and AV (mg/g) values were found to be 3.12 and 4.33, respectively. The estimated and actual values for dried drone pupae showed no significant difference (p < 0.05). Comparing the physicochemical and microbiological properties of freeze-dried and optimal heat-dried drone pupae, the L and b value as well as PV were significantly lower in the heat-dried samples, while no significant difference was observed in the a value and AV (p < 0.05). Our study suggests that the model we developed can be applied to the large-scale production of drying conditions for use in the pharmaceutical and food industries.
- Published
- 2023
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