1- Department of Food Science and Technology. College of Agriculture. University of Zabol. Zabol. Iran , s.soleimanifard@uoz.ac.ir
2- Department of Food Science and Technology, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
3- Department of Food Science and Technology. College of Agriculture. University of Zabol, Zabol, Iran
2- Department of Food Science and Technology, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
3- Department of Food Science and Technology. College of Agriculture. University of Zabol, Zabol, Iran
Abstract: (20 Views)
The present study investigates the effect of baking temperatures (140, 160, 180, 200, and 220℃) on texture kinetics. It also explores a statistical classification meta-algorithm, called Adaptive Boosting (AdaBoost), to predict texture changes during conventional cake baking. The experimental results indicated that texture properties were significantly affected by baking temperature and time. As time and temperature increased, there was an increase in hardness, cohesiveness, gumminess, and chewiness and a decrease in springiness. However, the impact of time and temperature on resilience was inconsistent, as it was maximum in the last quarter of the process. The predicted results revealed that the AdaBoost algorithm accurately predicted the texture properties with a high coefficient of determination (R2 > 0.989) and minimal root mean square error (RMSE < 0.0019) across all textural properties. Therefore, it can serve as an efficient tool for predicting the texture properties of cakes during baking. Furthermore, the proposed methodology can be extended to predict the texture properties of other baked goods.
Article Type: Original Research |
Subject:
Food Engineering
Received: 2023/10/25 | Accepted: 2024/01/1
Received: 2023/10/25 | Accepted: 2024/01/1
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