Multivariate Analysis Method Of Important Factors In Na₂CO₃ Pretreatment Of Corn Stover

The pretreatment process of lignocellulosic raw materials is an important part of the production of biomass energy and chemicals,because its high cost is a key technical problem that restricts the conversion of lignocellulosic raw materials into industrial production.In recent years,researchers have done a lot of research work on the methods of pretreatment of biomass raw materials,relevant mechanisms,and economic evaluations.Among them,the alkaline pretreatment is a kind of pretreatment method with extensive research,good pretreatment effect and good development prospect.However,a biomass pretreatment system is a complex system in which a large number of variables compose and interact with each other(in short,a change in one variable leads to a change in other variables as well),in which the correlation between important factors and the principle of interaction has not yet been clarified.Therefore,this paper aims at hydrogen peroxide-assisted sodium pretreatment system.This particular pretreatment system uses multivariate analysis methods(principal component analysis and partial least squares)to correlate the important process factors in the system.The research was conducted to reveal and quantify the comprehensive influences and interaction mechanisms of the main process factors on the pretreatment effect.Based on this,the established model was used to optimize the process of the alkali pretreatment system and the effect of the pretreatment was quick evaluation.The main research contents of this paper are as follows:First,hydrogen peroxide-assisted sodium pretreatment system was used as the research object,and a large amount of data was collected to obtain the data set.Principal component analysis(PCA)was used to establish a principal component analysis model based on raw material properties,pretreatment process parameters,raw material properties after pretreatment,and enzymatic hydrolysis evaluation parameters.From the principal component analysis model,the influence of various process parameters on the entire pretreatment system is known,of which the size of the raw material,the amount of sodium carbonate,the mechanical refining,and the enzymatic hydrolysis evaluation parameters have the greatest impact on the entire system.Secondly,on the basis of principal component analysis,PLS-pretreatment model was established by partial least squares method.This is based on the pretreatment of raw material properties as a dependent variable.The effects of pretreatment raw material parameters and pretreatment process parameters on the nature parameters of pretreated raw materials were studied.Thus,it can be obtained that the amount of sodium carbonate and the pretreatment temperature have a greater impact on the model.The raw material particle size parameters also have a positive influence on the properties of the raw material after pretreatment.Then,the enzymatic hydrolysis evaluation parameter was set as a Y variable and the other parameters were set as an X variable,resulting in a PLS-enzymatic model.The study found that the mechanical refining treatment(PFI)parameters,sodium carbonate dosage has a great role in the final enzymatic hydrolysis of sugar yield.The pretreatment temperature is negatively correlated with the final enzyme hydrolysis sugar yield.Finally,the newly collected dataset was subjected to enzymatic hydrolysis saccharification prediction using the PLS-enzymatic model obtained by partial least squares.Thus,under the condition of known parameters,the prediction of enzymatic hydrolysis of saccharification is realized.