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中国精品科技期刊2020
渠一聪,张绍绒,罗理勇,等. 基于人工神经网络耦合遗传算法(BP-GA)优化茶氨酸-葡萄糖美拉德反应的条件[J]. 食品工业科技,2023,44(24):183−192. doi: 10.13386/j.issn1002-0306.2023020165.
引用本文: 渠一聪,张绍绒,罗理勇,等. 基于人工神经网络耦合遗传算法(BP-GA)优化茶氨酸-葡萄糖美拉德反应的条件[J]. 食品工业科技,2023,44(24):183−192. doi: 10.13386/j.issn1002-0306.2023020165.
QU Yicong, ZHANG Shaorong, LUO Liyong, et al. Optimization of Theanine-Glucose Maillard Reaction Conditions Based on Artificial Neural Network Coupled Genetic Algorithm (BP-GA)[J]. Science and Technology of Food Industry, 2023, 44(24): 183−192. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023020165.
Citation: QU Yicong, ZHANG Shaorong, LUO Liyong, et al. Optimization of Theanine-Glucose Maillard Reaction Conditions Based on Artificial Neural Network Coupled Genetic Algorithm (BP-GA)[J]. Science and Technology of Food Industry, 2023, 44(24): 183−192. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023020165.

基于人工神经网络耦合遗传算法(BP-GA)优化茶氨酸-葡萄糖美拉德反应的条件

Optimization of Theanine-Glucose Maillard Reaction Conditions Based on Artificial Neural Network Coupled Genetic Algorithm (BP-GA)

  • 摘要: 为了对美拉德反应体系进行综合评价以及优化茶氨酸-葡萄糖美拉德反应条件,本研究构建了茶氨酸-葡萄糖美拉德反应综合评价值的人工神经网络耦联遗传算法(BP-GA)模型,优化得到了最佳反应条件。先通过熵值法求出荧光值、A294、A420、葡萄糖及茶氨酸剩余量五个评价指标之间的权重,再结合单因素实验及正交试验结果,建立输入为实验因素参数,输出为美拉德反应综合评价值的BP-GA人工神经网络模型,最后使用建立好的模型得到茶氨酸-葡萄糖美拉德反应的最优条件及相应的美拉德反应综合评价值。结果表明,通过建立的BP-GA模型进行全局优化得到茶氨酸-葡萄糖美拉德反应的最优条件为:反应温度117.6 ℃,反应时间1.8 h,pH7.3,羰基氨比1:2,此条件下美拉德反应的综合评价值为93.22。经过与正交试验得到的结果比较,发现BP-GA模型具有良好的预测性能。利用BP-GA模型,本研究得到了模型美拉德反应的最优条件,这将为美拉德反应模拟体系的构建及反应的预测提供参考。

     

    Abstract: In order to comprehensively evaluate the Maillard reaction system and optimize the conditions of theanine-glucose Maillard reaction, an artificial neural network coupled genetic algorithm (BP-GA) model for the comprehensive evaluation value of theamine-glucose Maillard reaction was herein constructed, and the best reaction conditions were optimized. Firstly, the weight among five evaluation indexes, fluorescence value, A294, A420, glucose and theanine residue were obtained by entropy method. Next, a BP-GA artificial neural network model with experimental factor parameter as the input and the comprehensive evaluation value of Maillard reaction as output was established in combination with the results of the single factor experiment and orthogonal experiment. Finally, the optimal condition for the theanine-glucose Maillard reaction and the corresponding comprehensive evaluation value of the Maillard reaction were obtained with the established model. The results showed that the optimal conditions for the theanine-glucose Maillard reaction obtained through the global optimization by the established BP-GA model were: Reaction temperature 117.6 ℃, reaction time 1.8 h, pH7.3, and carbonyl ammonia ratio 1:2. In such case, the comprehensive evaluation value of Maillard reaction was 93.22. Compared with the results obtained by the orthogonal experiment, it was found that the BP-GA model had good predictive performance. In this study, the optimum conditions for the model Maillard reaction was obtained by the BP-GA model, which would provide a reference for the establishment of the Maillard reaction simulation system and prediction of the reaction.

     

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