He Han, Cai Yubin, Ren Yingying, Han Shuyan, Wang Liang, Yin Xuefeng, Ablat Ayzohra, Yili Abulimiti, Wali Ahmidin, Aisa HajiAkber
State Key Laboratory Basis of Xinjiang Indigenous Medicinal Plants Resource Utilization, Key Laboratory of Plant Resources and Chemistry in Arid Regions, Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi 830011, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Foods. 2025 Sep 2;14(17):3086. doi: 10.3390/foods14173086.
This study valorized camel milk residue (CMR) via optimized bacterial fermentation to produce bioactive peptides with hypoglycemic potential. Screening of eleven bacterial strains identified four optimal starters. Artificial neural network (ANN) simulation significantly outperformed response surface methodology (RSM) in modeling and prediction, as evidenced by its superior performance in key statistical metrics, including R, RMSE, and AAD(%), ultimately achieving a maximized yield of TCA-soluble nitrogen (TCA). Under optimized conditions, a TCA yield of 39.8% was achieved and experimentally validated. Ultrafiltration yielded a highly bioactive peptide fraction (<1 kDa), which exhibited significant inhibition of -amylase (80.7%) and -glucosidase (32.0%). The peptides exhibited high stability under various conditions, highlighting their industrial potential. This study explores the application of ANN-RSM optimization for the valorization of camel milk residue (CMR). Our findings provide a sustainable strategy for transforming CMR into a high-value anti-diabetic ingredient, which could contribute to extending the camel milk value chain.
本研究通过优化细菌发酵对骆驼奶残渣（CMR）进行增值利用，以生产具有降血糖潜力的生物活性肽。对11株细菌菌株进行筛选，确定了4种最佳发酵剂。人工神经网络（ANN）模拟在建模和预测方面明显优于响应面法（RSM），这在关键统计指标（包括R、RMSE和AAD(%)）中的卓越表现得到了证明，最终实现了三氯乙酸可溶性氮（TCA）产量的最大化。在优化条件下，实现了39.8%的TCA产量并通过实验验证。超滤得到了一种具有高生物活性的肽级分（<1 kDa），其对α-淀粉酶（80.7%）和α-葡萄糖苷酶（32.0%）表现出显著抑制作用。这些肽在各种条件下都表现出高稳定性，突出了它们的工业潜力。本研究探索了ANN-RSM优化在骆驼奶残渣（CMR）增值利用中的应用。我们的研究结果为将CMR转化为高价值抗糖尿病成分提供了一种可持续策略，这可能有助于延长骆驼奶价值链。
