【摘要】 生物质糖化是生物质高值化利用的重要途径。以棉花秸秆为原料,研究NaOH浓度、反应温度、时间及固含量等因素对棉秆水解后还原糖含量和木质素含量的影响,并采用神经网络对棉秆在NaOH中的水解过程进行模拟与优化,建立棉秆在NaOH中水解过程的神经网络模型,得到棉秆在NaOH中水解的最佳条件为:10%NaOH、60℃、24h和5%固含量,预处理后棉秆的还原糖含量为74.80%,木质素含量为23.21%。通过试验及神经网络模型的预测和优化,提高了棉秆在NaOH中水解后的还原糖含量,为棉秆水解发酵生产燃料乙醇技术的研究奠定了基础。更多还原

【Abstract】 The saccharification of biomass is an important approach to the high value utilization of biomass.In this study,cotton stalk was selected as raw material,the effects of NaOH concentration,reaction temperature,time and solid content on the hydrolysis yield of the cotton stalk were investigated.Artificial neural network(ANN)was used to predict and optimize the process of hydrolysis of cotton stalk in NaOH.After training,testing and validation,the ANN model was established.The optimized condition of hydrolysis of cotton stalk in NaOH was obtained as:10% NaOH,60℃,24 hand 10% solid content,and 74.80% of reducing sugar content in the pretreated cotton stalk was achieved.The corresponding lignin content was23.21%.After simulation and optimization of hydrolysis of cotton stalk in NaOH solution by ANN model,the reducing sugar content was enhanced,which provided an important application basis for the effective utilization of cotton stalk.更多还原