Abstract Peptide fouling is a technological drawback in filtration membrane processes. The impact of membrane characteristics on fouling by peptides from a complex whey protein hydrolysate (WPH) fouling was assessed based on advanced statistical redundancy analysis. Six membranes were characterized and tested: PES, PVDF, CF55, S11, S11+ and S11-. Among the eight physicochemical characteristics analyzed, zeta-potential (ZP) and roughness (Rz) were highly correlated with total fouling quantity (TFQ), suggesting that peptide fouling was mainly due to electrostatic interactions over wider surfaces. Concerning peptide sequences, redundancy analysis indicated that at least one characteristic among ZP, Rz, contact angle and thickness contributed significantly to the fouling of ALMPHIR, LIVTQTMK, TKIPAVFK, VLVLDTDYK, TPEVDDEALEK, TPEVDDEALEFDK or SLAMAASDISLLDAQSAPLR. It appeared that membranes with hydrophilic surfaces were more likely to be fouled by WPH regardless the peptide hydrophilicity. Besides, wider surface would enable more contact area for peptides, increasing consequently fouling. The TFQ was described by a statistical predictive model using the combined effect of ZP and Rz, of the form: ln(TFQ) = 8.64 + 0.072.XRz + 0.088.XZP (R2 = 0.9098). Moreover, statistical models were also established for each peptide, enabling to predict their specific fouling on a variety of membranes with different physicochemical characteristics.

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确定过滤膜的主要理化特性的冗余分析，解释了它们被肽污染

摘要 肽污染是过滤膜工艺中的一个技术缺陷。基于高级统计冗余分析评估膜特性对复合乳清蛋白水解物 (WPH) 污染的肽污染的影响。对六种膜进行了表征和测试：PES、PVDF、CF55、S11、S11+ 和 S11-。在分析的八种物理化学特征中，zeta 电位 (ZP) 和粗糙度 (Rz) 与总污染量 (TFQ) 高度相关，表明肽污染主要是由于更宽表面上的静电相互作用。关于肽序列，冗余分析表明，ZP、Rz、接触角和厚度中至少有一个特征对 ALMPHIR、LIVTQTMK、TKIPAVFK、VLVLDTDYK、TPEVDDEALEK、TPEVDDEALEFDK 或 SLAMAASDISLLDAQSAPLR。无论肽的亲水性如何，具有亲水表面的膜似乎更容易被 WPH 污染。此外，更宽的表面将使肽有更多的接触面积，从而增加结垢。TFQ 由使用 ZP 和 Rz 的组合效应的统计预测模型描述，形式为：ln(TFQ) = 8.64 + 0.072.XRz + 0.088.XZP (R2 = 0.9098)。此外，还为每种肽建立了统计模型，从而能够预测它们在具有不同物理化学特征的各种膜上的特定污染。TFQ 由使用 ZP 和 Rz 的组合效应的统计预测模型描述，形式为：ln(TFQ) = 8.64 + 0.072.XRz + 0.088.XZP (R2 = 0.9098)。此外，还为每种肽建立了统计模型，从而能够预测它们在具有不同物理化学特征的各种膜上的特定污染。TFQ 由使用 ZP 和 Rz 的组合效应的统计预测模型描述，形式为：ln(TFQ) = 8.64 + 0.072.XRz + 0.088.XZP (R2 = 0.9098)。此外，还为每种肽建立了统计模型，从而能够预测它们在具有不同物理化学特征的各种膜上的特定污染。