农业工程学报
農業工程學報
농업공정학보
2015年
5期
280-286
,共7页
岳国君%刘文信%刘劲松%杨晓光%丁乾坤%董红星%宋启龙%关晓男
嶽國君%劉文信%劉勁鬆%楊曉光%丁乾坤%董紅星%宋啟龍%關曉男
악국군%류문신%류경송%양효광%정건곤%동홍성%송계룡%관효남
乙醇%发酵%动力学%葡萄糖%玉米淀粉%Logistic模型
乙醇%髮酵%動力學%葡萄糖%玉米澱粉%Logistic模型
을순%발효%동역학%포도당%옥미정분%Logistic모형
ethanols%fermentation%dynamics%glucose%corn starch%Logistic model
乙醇发酵产物动力学的研究有助于更好的认识发酵过程,为其工业放大及生产操作条件的优化提供理论基础。基于 Logistic 方程的菌体生长动力学模型可较好的描述细胞生长期及细胞自身抑制作用,但由于该模型方程中的比例参数与积分常数没有明显的生物学意义,使其应用受到了限制。该文从生物学与化学工程学结合角度对 Logistic 模型方程重新参数化,将发酵产物乙醇生成动力学与酵母生长动力学方程类比,给出了乙醇浓度的显式函数模型,模型中不再出现酵母菌浓度变量,大大简化了模型,并且赋予参数其物理意义;在研究了以葡萄糖和玉米淀粉为原料乙醇质量浓度、总糖质量浓度在不同底物质量浓度和料液比条件下随发酵时间的变化规律的基础上运用该模型拟合了以葡萄糖和玉米淀粉为原料进行乙醇发酵的试验数据,结果表明:模型值与试验数据具有较好一致性,拟合度均大于0.97,可见该重新参数化的 Logistic 模型可以描述发酵生产乙醇过程中产物乙醇的动力学行为,具有预测工业上实际发酵过程中乙醇浓度的潜力。
乙醇髮酵產物動力學的研究有助于更好的認識髮酵過程,為其工業放大及生產操作條件的優化提供理論基礎。基于 Logistic 方程的菌體生長動力學模型可較好的描述細胞生長期及細胞自身抑製作用,但由于該模型方程中的比例參數與積分常數沒有明顯的生物學意義,使其應用受到瞭限製。該文從生物學與化學工程學結閤角度對 Logistic 模型方程重新參數化,將髮酵產物乙醇生成動力學與酵母生長動力學方程類比,給齣瞭乙醇濃度的顯式函數模型,模型中不再齣現酵母菌濃度變量,大大簡化瞭模型,併且賦予參數其物理意義;在研究瞭以葡萄糖和玉米澱粉為原料乙醇質量濃度、總糖質量濃度在不同底物質量濃度和料液比條件下隨髮酵時間的變化規律的基礎上運用該模型擬閤瞭以葡萄糖和玉米澱粉為原料進行乙醇髮酵的試驗數據,結果錶明:模型值與試驗數據具有較好一緻性,擬閤度均大于0.97,可見該重新參數化的 Logistic 模型可以描述髮酵生產乙醇過程中產物乙醇的動力學行為,具有預測工業上實際髮酵過程中乙醇濃度的潛力。
을순발효산물동역학적연구유조우경호적인식발효과정,위기공업방대급생산조작조건적우화제공이론기출。기우 Logistic 방정적균체생장동역학모형가교호적묘술세포생장기급세포자신억제작용,단유우해모형방정중적비례삼수여적분상수몰유명현적생물학의의,사기응용수도료한제。해문종생물학여화학공정학결합각도대 Logistic 모형방정중신삼수화,장발효산물을순생성동역학여효모생장동역학방정류비,급출료을순농도적현식함수모형,모형중불재출현효모균농도변량,대대간화료모형,병차부여삼수기물리의의;재연구료이포도당화옥미정분위원료을순질량농도、총당질량농도재불동저물질량농도화료액비조건하수발효시간적변화규률적기출상운용해모형의합료이포도당화옥미정분위원료진행을순발효적시험수거,결과표명:모형치여시험수거구유교호일치성,의합도균대우0.97,가견해중신삼수화적 Logistic 모형가이묘술발효생산을순과정중산물을순적동역학행위,구유예측공업상실제발효과정중을순농도적잠력。
Ethanol plays an important role in the national economy, and is widely used in the raw materials of food, medicine, and the chemical industry. In recent years, with the challenge facing the world’s energy security, more and more attention has been devoted to the conversion of biomass into fuel ethanol. Ethanol is considered to be a renewable and clean fuel, which can be an alternative to fossil fuels. So far, compared with other ethanol production methods, the fermentation method to produce ethanol has so many advantages, such as green environmental protection and low cost, that attracts lots of researchers’ attention. There are many influence factors in the fermentation process, which make the fermentation process so complicated that it is hard to be controlled. The variation of the ethanol concentration with different fermentation times is directly related to the fermentation results. How to get higher ethanol concentration by a fermentation method has become the hot and difficult issue of the fermentation field. The research of ethanol fermentation kinetic is beneficial for understanding the fermentation process. It provides a theoretical basis for the amplification and optimization of fermentation industry. A bacteria growth dynamics model based on a Logistic equation can better describe the cell growth and inhibition; however, because the parameters and the integral constant of the model equation have no obvious biological significance, its application is limited. To establish a practical product kinetic model of ethanol fermentation, in this article, a reparameterized Logistic model was applied to correlate the ethanol concentration and time in the fermentation process, which was obtained by the analogy of the yeast growth. That is, an explicit function of ethanol concentration is given, which can combine biology and chemical engineering. As there was no yeast concentration in the model, the model was simplified so much and the parameters of it have an immediate physical interpretation that can be conveniently applied in industry. Through the research on glucose and corn starch as the raw material for ethanol fermentation, we studied the variation of ethanol concentration, total sugar concentration with time under the condition of different substrate quality, and the ratio of material to water. Then the experimental data were correlated by the reparameterized Logistic model in ethanol fermentation with glucose and corn starch. The model parameters and the consistency were good between the model and the experiments, the degree of fitting R2, was greater than 0.97. The results showed that the model can be used to represent the kinetics behavior of ethanol concentration in fermentation, which has the potential to predict ethanol concentration in industrial fermentation.