In this study, a dual-chamber microbial fuel cell (MFC) fed with actual potato chips’ processing wastewater (PCPW) was tested as a biosensor. The performance of MFC-based biosensor was evaluated in terms of the current measurement range, toxicity detection and sensitivity, and the operational stability. The results revealed that the MFC can simply be converted to an online biosensor unit to detect the harmful effect of suspended solids and acidic content in the actual PCPW on the anodic attached biofilm and the values of the generated current as well. A notable decrease in the current values was observed indicating the adverse effects of the harmful matters in the PCPW fed to the biosensor unit. The results proposed a competition between the harmful components and the favorable substrate in binding to the redox complex. An excellent fitting was obtained between the experimental and predicted results by \( I_{{K_{m} }} \) model with determination coefficient (R²) and mean-square-error values of 0.927 and 0.363, respectively. Additionally, a new approach was developed based on direct measurement of actual field data to replace the conventional statistical methods.

中文翻译：

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基于微生物燃料电池的生物传感器在监测实际薯片加工废水质量中的新应用

在这项研究中，以实际的薯片加工废水（PCPW）为燃料的双室微生物燃料电池（MFC）作为生物传感器进行了测试。根据当前的测量范围，毒性检测和灵敏度以及操作稳定性，评估了基于MFC的生物传感器的性能。结果表明，MFC可以简单地转换成在线生物传感器单元，以检测实际PCPW中悬浮的固体和酸性成分对阳极附着的生物膜的有害影响，以及产生的电流值。观察到电流值显着降低，表明进料到生物传感器单元的PCPW中有害物质的不利影响。结果提出了有害组分和有利底物在与氧化还原复合物结合中的竞争。\（I _ {{K_ {m}}} \）模型的确定系数（R ²）和均方误差值分别为0.927和0.363。另外，基于对实际现场数据的直接测量，开发了一种新方法来代替传统的统计方法。