Comparative performance analysis of enzyme inactivation of soy milk by using RSM and ANN,Journal of Food Process Engineering

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Comparative performance analysis of enzyme inactivation of soy milk by using RSM and ANN
Journal of Food Process Engineering ( IF 2.7 ) Pub Date : 2020-09-11 , DOI: 10.1111/jfpe.13530
Rahul Kumar ₁ , P. Srinivasa Rao ₂ , Sandeep Singh Rana ₃ , Payel Ghosh ₃

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The presence of antinutritional factors as trypsin inhibitors (TIA) and lipoxygenase (LOX) in soy milk produces indigestion and off‐flavor due to oxidation of linoleic acid to hyperoxide. The objective of the study was to determine the prediction capacity of response surface methodology (RSM) and artificial neural network (ANN) for enzyme inactivation of soy milk. The microwave and thermo‐sonication method were used to prepare and treat the sample. Statistical parameters like NRMSE and %MAE were used to compare and evaluate the final result. NRMSE value had shown five times better results in the case of ANN (0.015) compared to RSM (0.082). Similarly, the % MAE value was also fivefold better in the case of ANN. In the case of RSM, Chi‐square values for TIA and LOX were 317.32 and 146.73, respectively. Whereas for ANN, the value was 4.68 and 2.69, respectively. So, it can be concluded that the prediction capacity of ANN is better than RSM.

中文翻译：

用RSM和ANN进行豆浆酶灭活的比较性能分析。

豆浆中存在抗营养因子，如胰蛋白酶抑制剂（TIA）和脂氧合酶（LOX），由于亚油酸氧化成高氧化物而导致消化不良和异味。这项研究的目的是确定响应面方法（RSM）和人工神经网络（ANN）对豆浆酶失活的预测能力。微波和热超声方法用于制备和处理样品。统计参数（如NRMSE和％MAE）用于比较和评估最终结果。在ANN（0.015）的情况下，NRMSE值显示的结果是RSM（0.082）的五倍。同样，在人工神经网络的情况下，％MAE值也提高了五倍。对于RSM，TIA和LOX的卡方值分别为317.32和146.73。而对于ANN，该值为4.68和2.69，分别。因此，可以得出结论，人工神经网络的预测能力要优于RSM。

更新日期：2020-11-09

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