Optimized degradation of bisphenol A by immobilized laccase from Trametes versicolor using Box-Behnken design (BBD) and artificial neural network (ANN)

漆酶 Box-Behnken设计 云芝 双酚A 化学 降级(电信) 傅里叶变换红外光谱 色谱法 核化学 响应面法 有机化学 化学工程 计算机科学 环氧树脂 工程类 电信
作者
Abdul Latif,Ahsan Maqbool,Runzhan Zhou,Muhammad Arsalan,Kai Sun,Youbin Si
出处
期刊:Journal of environmental chemical engineering [Elsevier BV]
卷期号:10 (2): 107331-107331 被引量:27
标识
DOI:10.1016/j.jece.2022.107331
摘要

This study represents one of the first attempts towards bisphenol A (BPA) degradation by Trametes versicolor laccase immobilized on Ba-alginate beads. The effect of input variables including temperature (20–40 °C), BPA concentration (2–10 mg/L) and time (10–90 min) were studied using Box-Behnken design (BBD) and artificial neural network (ANN). The maximum BPA degradation of 84.34% was obtained when the temperature was 40 °C, BPA concentration 2 mg/L and time 50 min, which was accurately predicted by BBD (83.48%) and ANN (84.33%), proving the accuracy of prediction for both models. The values of R2 and MSE for BBD were found to be 0.98, 9.88, while for ANN were 0.97, 38.25, respectively. Based on higher R2 value and lower MSE, BBD was slightly better than ANN. The immobilized laccase showed higher storage stability than free laccase by retaining 68.64% and 44.62% of their activity at the same experimental conditions. Furthermore, BPA transformation was confirmed by Fourier-transform infrared spectroscopy (FTIR) analysis. GC-MS had detected the oxidative degradation products from BPA. Results showed that Ba-alginate immobilized laccase could be a promising biocatalyst in treating organic pollutants.
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