Elerakey Norhan, Rasmey Abdel-Hamied M, Mohammed Youseef M, Aboseidah Akram A, Hawary Heba
Department of Botany and Microbiology, Faculty of Science, Suez University, P.O. Box 43221, Suez, Egypt.
Department of Botany and Microbiology, Faculty of Science, Damanhour University, Damanhour, 22516, Egypt.
Biotechnol Biofuels Bioprod. 2025 May 14;18(1):54. doi: 10.1186/s13068-025-02652-3.
Biohydrogen production from agricultural waste is a promising strategy to address climate change and energy challenges. This study aimed to optimize the process parameters for biohydrogen production from watermelon peels (WMP) by Clostridium butyricum NE133 using statistical optimization techniques. Initial screening of eight significant variables influencing hydrogen production including, initial pH, incubation temperature, WMP concentration, inoculum volume, yeast extract, tryptone, sodium acetate, and ammonium acetate concentration was conducted by a Plackett-Burman (PB) design.
The results showed that four variables including, initial pH (P < 0.001), WMP concentration (P < 0.001), sodium acetate (P = 0.023), and ammonium acetate (P = 0.048) had statistically significant effects on hydrogen production. The model curvature (P = 0.040) indicated that it was significant. Box-Behnken (BB) design under response surface methodology (RSM) was employed to optimize the four selected variables to maximize hydrogen production. The optimal conditions for maximizing hydrogen production from WMP by C. butyricum were: initial pH of 8.98, WMP concentration of 44.75%, sodium acetate 4.49 gL, and ammonium acetate 1.15 gL at with predicted H of 4703.23 mLL. The determination coefficient R of the model was 0.9902 with the lack of fit F-value was 1.86.
The confirmation experiment revealed only a 0.59% difference between the predicted and experimental hydrogen production, indicating that the optimum conditions were actual with the least error. Improvement of about 103.25% in hydrogen production from WMP by C. butyricum NE133 was achieved after the optimization process.
利用农业废弃物生产生物氢是应对气候变化和能源挑战的一项有前景的策略。本研究旨在运用统计优化技术优化丁酸梭菌NE133利用西瓜皮（WMP）生产生物氢的工艺参数。通过Plackett-Burman（PB）设计对影响产氢的八个重要变量进行了初步筛选，包括初始pH值、培养温度、WMP浓度、接种量、酵母提取物、胰蛋白胨、醋酸钠和醋酸铵浓度。
结果表明，初始pH值（P＜0.001）、WMP浓度（P＜0.001）、醋酸钠（P = 0.023）和醋酸铵（P = 0.048）这四个变量对产氢具有统计学显著影响。模型曲率（P = 0.040）表明其具有显著性。采用响应面法（RSM）下的Box-Behnken（BB）设计对四个选定变量进行优化以实现产氢最大化。丁酸梭菌利用WMP产氢最大化的最佳条件为：初始pH值8.98、WMP浓度44.75%、醋酸钠4.49 g/L、醋酸铵1.15 g/L，预测产氢量为4703.23 mL/L。模型的决定系数R²为0.9902，失拟F值为1.86。
验证实验表明预测产氢量与实验产氢量之间仅相差0.59%，表明最佳条件实际误差最小。优化过程后，丁酸梭菌NE133利用WMP产氢提高了约103.25%。
