Abstract

Lipases are a class of triacylglycerol hydrolases which have found a lot of applications as a result of their unique characteristics such as stability, specificity, economic attractiveness etc. This study examined the effect of some microbial stimulants (olive oil, MgSO₄ and KH₂PO₄) on the production of lipase from waste cooking oil (WCO). The fermentation experiments were planned using a three-variable Box-Behnken design and the impact of the stimulants was optimized with response surface methodology (RSM) and artificial neural network (ANN). The results revealed that intermediate concentrations of olive oil, MgSO₄ and KH₂PO₄ were needed to maximize lipase activity. The ANN model predicted an optimal lipase activity of 177.19 U/mL and this was obtained at olive oil, MgSO₄ and KH₂PO₄ concentration of 0.58, 0.04 and 0.22 w/w% respectively while the RSM model predicted an optimal lipase activity of 176.52 U/mL at olive oil, MgSO₄ and KH₂PO₄ concentration of 0.63, 0.05 and 0.25 w/w% respectively. The ANN model was superior to the RSM model in predicting lipase production and this was reflected by better statistical metrics. Thus, biological stimulants can facilitate the fermentation process for optimal lipase production from WCO.

摘要

脂肪酶是一类甘油三酯水解酶，由于其独特的特性，如稳定性、特异性、经济吸引力等，已获得大量应用。本研究检验了一些微生物刺激剂（橄榄油、MgSO ₄和 KH ₂ PO ₄）关于从废弃食用油中生产脂肪酶（WCO）。使用三变量 Box-Behnken 设计计划发酵实验，并使用响应面法 (RSM) 和人工神经网络 (ANN) 优化刺激物的影响。结果表明，中等浓度的橄榄油、MgSO ₄和 KH ₂ PO ₄需要最大限度地提高脂肪酶活性。ANN 模型预测的最佳脂肪酶活性为 177.19 U/mL，这是在橄榄油、MgSO ₄和 KH ₂ PO ₄浓度分别为 0.58、0.04 和 0.22 w/w% 时获得的，而 RSM 模型预测的最佳脂肪酶活性为在橄榄油、MgSO ₄和 KH ₂ PO ₄浓度分别为 0.63、0.05 和 0.25 w/w% 时为 176.52 U/mL。ANN 模型在预测脂肪酶生产方面优于 RSM 模型，这反映在更好的统计指标上。因此，生物刺激物可以促进发酵过程，从而从 WCO 中获得最佳脂肪酶生产。