Anaerobic co-digestion of lignocellulose feedstock with livestock waste can assist in overcoming the challenges of digesting lignocellulose and balancing the nutrient contents of the process. This study investigated the optimum conditions for methane yield production from anaerobic co-digestion of alkali-pretreated groundnut shells and duck waste using Response Surface Methodology (RSM). A central composite design of the RSM model with three input variables of retention time, temperature, and substrate mixing ratio was used to set up the anaerobic digestion process. Individual and interactive influence of the three process parameters were examined. The result showed that all three process parameters considered are significant and determine the methane yield. The developed RSM model predicted a daily methane yield of 53.33 mL CH₄/g VS_added for optimal conditions of 11 days, 26 °C temperature, and 50: 50 mixing ratio, which is not the same as the optimum methane yield observed from the experiment (54.26 mL CH₄/g VS_added) and at different process conditions. Cumulative methane yields of 666.72 and 666.66 mL CH₄/g VS_added were predicted and observed, respectively, which shows a very close range. The RSM coefficient of determination (R²) value of 0.8251 (82.51%) was observed, indicating a close fit between the predicted and observed yields. Analysis of variance (ANOVA) p < 0.0001 indicates that the developed model could be helpful in anaerobic co-digestion of lignocellulose materials and livestock waste. This study can be replicated at the industrial scale.

中文翻译：

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使用响应面法优化碱预处理花生壳和鸭粪共消化的甲烷产量

木质纤维素原料与牲畜废物的厌氧共消化有助于克服消化木质纤维素和平衡该过程的营养成分的挑战。本研究采用响应面法 (RSM) 研究了碱预处理花生壳和鸭粪厌氧共消化产生甲烷产量的最佳条件。使用具有保留时间、温度和底物混合比三个输入变量的 RSM 模型的中心组合设计来建立厌氧消化过程。检查了三个工艺参数的单独影响和交互影响。结果表明，所考虑的所有三个工艺参数都很重要，并且决定了甲烷产量。开发的 RSM 模型预测，在 11 天、26 °C 温度和 50: 50 混合比的最佳条件下，每日甲烷产量为 53.33 mL CH ₄ /g VS_添加，这与从实验中观察到的最佳甲烷产量不同。实验（_{添加54.26 mL CH 4} /g VS ）并在不同的工艺条件下进行。预测和观察到的累积甲烷产量分别为666.72和666.66 mL CH ₄ /g VS_添加，这显示出非常接近的范围。观察到RSM 决定系数 (R ² ) 值为 0.8251 (82.51%)，表明预测产量和观测产量之间非常吻合。方差分析 (ANOVA) p < 0.0001 表明所开发的模型有助于木质纤维素材料和牲畜废物的厌氧共消化。这项研究可以在工业规模上复制。