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Efficiency of tannase enzyme for degradation of tannin from cashew apple juice: Modeling and optimization of process using artificial neural network and response surface methodology
Journal of Food Process Engineering ( IF 2.7 ) Pub Date : 2020-07-28 , DOI: 10.1111/jfpe.13499 S. Abdullah 1 , Rama Chandra Pradhan 1 , Muhammed Aflah 1 , Sabyasachi Mishra 1
Journal of Food Process Engineering ( IF 2.7 ) Pub Date : 2020-07-28 , DOI: 10.1111/jfpe.13499 S. Abdullah 1 , Rama Chandra Pradhan 1 , Muhammed Aflah 1 , Sabyasachi Mishra 1
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The study was conducted on tannase‐assisted extraction of cashew apple juice at different combinations of tannase concentration (0.01–0.1% wt/wt), incubation time (20–120 min), and incubation temperature (30–50°C) for the maximum reduction of tannin from the juice. The modeling and optimization of process parameters were performed using response surface methodology (RSM) and artificial neural network (ANN). The RSM proposed an optimum process condition of 0.079% tannase concentration, 85 min incubation time, and 46°C incubation temperature, whereas the ANN model proposed 0.085% tannase concentration, 89 min incubation time, and 39°C incubation temperature as the optimum conditions. The reduction in tannin content achieved using the optimum conditions proposed by RSM and ANN models were 63.93 and 68.85%, respectively. Statistical parameters such as absolute average deviation (AAD), mean squared error (MSE), and determination coefficient (R2) indicated the superiority of the ANN model with high R2 and low AAD and MSE values.
中文翻译：
鞣酸酶降解腰果苹果汁中单宁的效率：使用人工神经网络和响应面方法进行建模和优化
该研究是在鞣酸浓度（0.01–0.1％wt / wt），温育时间（20–120分钟）和温育温度（30–50°C）的不同组合下，以鞣酸酶辅助提取腰果苹果汁的。从果汁中最大程度地减少单宁。使用响应表面方法（RSM）和人工神经网络（ANN）对过程参数进行建模和优化。RSM提出了最佳的工艺条件，其中鞣酸浓度为0.079％，孵育时间为85分钟，孵育温度为46°C，而ANN模型提出了鞣酸的浓度为0.085％，孵育时间为89min和39°C孵育温度为最佳条件。 。使用RSM和ANN模型提出的最佳条件，单宁含量减少分别为63.93和68.85％。R 2）表明了具有高R 2和低AAD和MSE值的ANN模型的优越性。
更新日期：2020-10-02
中文翻译：
鞣酸酶降解腰果苹果汁中单宁的效率：使用人工神经网络和响应面方法进行建模和优化
该研究是在鞣酸浓度（0.01–0.1％wt / wt），温育时间（20–120分钟）和温育温度（30–50°C）的不同组合下，以鞣酸酶辅助提取腰果苹果汁的。从果汁中最大程度地减少单宁。使用响应表面方法（RSM）和人工神经网络（ANN）对过程参数进行建模和优化。RSM提出了最佳的工艺条件，其中鞣酸浓度为0.079％，孵育时间为85分钟，孵育温度为46°C，而ANN模型提出了鞣酸的浓度为0.085％，孵育时间为89min和39°C孵育温度为最佳条件。 。使用RSM和ANN模型提出的最佳条件，单宁含量减少分别为63.93和68.85％。R 2）表明了具有高R 2和低AAD和MSE值的ANN模型的优越性。
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