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首页> 外文期刊>Bioresource Technology: Biomass, Bioenergy, Biowastes, Conversion Technologies, Biotransformations, Production Technologies >A new algorithm to characterize biodegradability of biomass during anaerobic digestion: Influence of lignin concentration on methane production potential
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A new algorithm to characterize biodegradability of biomass during anaerobic digestion: Influence of lignin concentration on methane production potential

机译:一种新的算法表征生物质生物降解性的厌氧消化过程中的生物降解性:木质素浓度对甲烷生产电位的影响

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摘要

We examined the influence of fibrous fractions of biomass on biochemical methane potential (BMP) with the objective of developing an economical and easy-to-use statistical model to predict BMP, and hence the biodegradability of organic material (BD) for biogas production. The model was developed either for energy crops (grass, maize, and straw) or for animal manures, or as a combined model for these two biomass groups. It was found that lignin concentration in volatile solids (VS) was the strongest predictor of BMP for all the biomass samples. The square of the sample correlation coefficient (R~2) from the BMP versus lignin was 0.908 (p<0.0001), 0.763 (p<0.001) and 0.883 (p<0.001) for animal manure, energy crops and the combined model, respectively. Validation of the combined model was carried out using 65 datasets from the literature.
机译:我们研究了生物质纤维分数对生物化学甲烷电位(BMP)的影响,目的是开发经济且易用的统计模型来预测BMP,因此为沼气生产的有机材料(BD)的生物降解性。 该模型是用于能量作物(草,玉米和稻草)或动物粪便,或者作为这两种生物质基团的组合模型开发。 发现挥发性固体(Vs)中的木质素浓度是所有生物质样品的BMP最强的预测因子。 来自BMP与木质素的样品相关系数(R〜2)的平方分别为0.908(p <0.0001),0.763(P <0.001)和0.883(P <0.001),分别用于动物粪物,能量作物和组合模型 。 使用来自文献的65个数据集进行组合模型的验证。

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