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1.
固定化米曲霉菌体细胞光学拆分DL-丙氨酸   总被引:9,自引:0,他引:9       下载免费PDF全文
将米曲霉经液体培养生长成直径l~2mm的浅黄色菌球.用明胶.甲醛固定,得到拆分N-乙酰-DL-丙氨酸酶活力较高和反应性能较好的固定化细胞。考察了各种因素对固定化细胞酶活力的影响。当底物浓度小于0.15mol/I,底物抑制现象不明显,此时拆分反应速率符合Michaelis Menten方程。  相似文献   

2.
以海藻酸钠为载体,戊二醛为交联剂固定化米曲霉F-81产中性蛋白酶,研究了固定化条件及固定化酶的性质。结果表明,固定化的最佳条件为:固定化时间1 h、海澡酸钠浓度4%、戊二醛浓度9%、CaCl2浓度0.7 mol/L。在此条件下固定化的中性蛋白酶活力为游离酶活力的68%。固定化酶的最适作用温度为65℃,最适作用pH值为7.0。60℃下酶稳定性较好,80℃下处理60 min,粗酶中几乎检测不到酶活力;中性蛋白酶pH稳定范围为6.5-9.5。Km值为24.83 mg/mL,最大反应速率Vmax为0.043 12 mg/min。  相似文献   

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米曲霉在产脱氨酶过程中超微结构动态   总被引:1,自引:0,他引:1  
王程  严自正 《微生物学通报》1989,16(4):227-227,196,205
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5.
固定化啤酒酵母废菌体吸附Pd2+的研究   总被引:10,自引:0,他引:10  
用2%海藻酸钠与l%明胶混合为包埋剂固定啤酒酵母废菌体。SEM、X-射线能谱和TEN研究结果表明,该固定化啤酒酵母废菌体(ISCWB)颗粒中的菌体分布较均匀,ISCWB不仅能吸附Pd^2 ,而且能将Pd^2 还原成Pd^0。ISCWB吸附Pd^2 的最适pH值为3.5。在30℃~70℃范围内,吸附作用不受温度的影响。吸附作用是一个较快的过程,在最初的5min内吸附量可达最大吸附量的36%。吸附作用受ISCWB浓度、Pd^2 起始浓度和共存离子的影响。在起始Pd^2 浓度100mg/L,ISCWB浓度1.8g/L、pH3.5和30℃条件下振荡吸附90min,吸附量为40.6mg/g.以0.5mol/L盐酸作为解吸剂解吸率达98.7%。连续吸附与解吸附试验结果表明,ISCWB的最大饱和吸附量为46.3mg/g,解吸率为98%。  相似文献   

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分离到Aspergilusoryzae13个菌株,其曲酸产量变化幅度166—486mg/ml,从中选出4个高产菌株。在1%酵母提取物和15%蔗糖培养液中30℃发酵培养,8—10天菌体生长量和曲酸产量达到最大值,随后曲酸产量迅速下降。蔗糖浓度对菌体生长和曲酸产量影响甚大,最适蔗糖浓度为15%。天冬氨酸、甘氨酸、赖氨酸、谷氨酸、吡哆醇、叶酸和抗坏血酸有利于菌体生长并显著提高曲酸产量。将在YES培养液中培养10天的菌体重新悬浮于含15%蔗糖的YES培养液或02M磷酸缓冲液(pH65)中8—10天曲酸产量仍可达到45mg/ml以上。低温条件下制备的培养8—10天的Aoryzae菌体匀浆反应系统仅有痕量曲酸形成。  相似文献   

8.
分离到Aspergillus oryzae13个菌株,其曲酸产量变化幅度16.6-48.6mg/ml,从中选出4个高产菌株。在1%酵母提取物和15%蔗糖培养液中30℃发酵培养,8 ̄10天菌体生长量和曲酸产量达到最大值,随后曲酸产量迅速下降。蔗糖浓度对菌体生长和曲酸产量影响甚大,最适蔗糖浓度为15%。天冬氨酸、甘氨酸、赖氨酸、谷氨酸、吡哆醇、叶酸和抗坏血酸有利于菌体生长并显著提高曲酸产量。将在YES  相似文献   

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米曲霉氨基酰化酶的双水相萃取研究   总被引:2,自引:0,他引:2  
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11.
选择6种吸附树脂和离子交换树脂对D-泛解酸内酯水解酶进行固定化,筛选出了固定化效果较好的大孔弱碱性丙烯酸系阴离子交换树脂D-380为载体,用先吸附后交联的方法固定化.通过实验对固定化条件进行了优化,得出最佳的固定化条件为:加酶量6 U/g树脂、吸附pH7.5、吸附时间4h、吸附温度30℃、交联剂戊二醛终浓度0.1%、交联时间2h.实验表明在此条件下制得的固定化酶有很好的稳定性:固定化酶在连续20次的底物水解反应后,剩余酶活达到71%.当温度达到80℃时游离酶几乎失去酶活,而固定化酶剩余酶活为60%以上.游离酶的pH稳定性范围为pH7~8,而固定化酶为pH 6.5~8.5.  相似文献   

12.
从网络结构入手,提出了网络局域性的概念。作为网络结构的一种定量描述,探讨了网络结构与训练速度、预测精度间的对应关系。结果表明网络的训练速度随局域性的增加而增加,网络的预测精神在局域性0.55附近达到最高,任何偏离都会导致网络预测精度的下降。为在生化过程具体应用中选择合理的神经网络类型提供了理论依据。  相似文献   

13.
人工神经网络在发酵工业中的应用   总被引:2,自引:0,他引:2  
人工神经网络技术具有很强的非线性映射能力,用于系统的非线性建模,具有无可比拟的优势,广泛应用于发酵过程中培养基的优化和系统建模与控制方面,本主要介绍了人工神经网络的基本原理与使用方法,以及BP神经网络在非线性函数逼近的优点,详细介绍了其在发酵培养基优化,连续搅拌反应器神经网络估计,分批发酵及补料分批发酵过程建模与控制优化中的应用实例。  相似文献   

14.
Simulating biological olfactory neural system, KIII network, which is a high-dimensional chaotic neural network, is designed in this paper. Different from conventional artificial neural network, the KⅢ network works in its chaotic trajectory. It can simulate not only the output EEG waveform observed in electrophysiological experiments, but also the biological intelligence for pattern classification. The simulation analysis and application to the recognition of handwriting numerals are presented here. The classification performance of the KⅢ network at different noise levels was also investigated.  相似文献   

15.
A mild and reproducible method has been developed for the surface-immobilization of enzymes on glutaraldehyde crosslinked gelatin beads. In this method glutaraldehyde is used in a dual capacity, as crosslinking agent and as the enzyme coupling agent. Glucoamylase (exo-α-1,4-d-glucosidase, EC 3.2.1.3), β-d-fructofuranosidase (invertase, EC 3.2.1.26) and β-d-glucoside (cellobiase, β-d-glucoside glucohydrolase, EC 3.2.1.21) have been successfully immobilized by this method, on the surface of the crosslinked gelatin particles. The method can be combined with the existing technology for the production of gelatin-entrapped enzymes. Thus, dual immobilized enzyme conjugates of glucoamylase and invertase have been prepared using this method, by entrapment of one enzyme in, and surface-binding of the other to, the gelatin matrix. The coupling of glucoamylase onto cross-linked gelatin particles by precipitation with poly(hexamethylenebiguanide hydrochloride) was also tested.  相似文献   

16.
A new simple method for the preparation of chemically crosslinked chitosan beads is presented. It consists of the dropwise addition of 2-3% (w/v) low molecular weight chitosan solution containing 2% (w/v) glyoxal in 1% (w/v) tetrasodiumdiphosphate, pH 8.0. Immobilized viable baker's yeast (Saccharomyces cerevisiae) could be obtained via gel entrapment within the new beads when means preventing their direct contact with soluble chitosan were provided, "disguising" the cells until gelation and crosslinking were completed. Such means included cell suspension in castor oil or mixing with carboxymethyl-cellulose powder. Application of these means was shown to be necessary, as cells exposed to soluble chitosan immediately lost their viability and glycolytic activity. Yeast disguised in castor oil was also protected from bead reinforcement by glutaraldehyde treatment, significantly strengthening bead stability while operating under acidic conditions. This capability was demonstrated by continuous ethanol production by chitosan entrapped yeast. (c) 1994 John Wiley & Sons, Inc.  相似文献   

17.
以新型白腐真菌——粗毛栓菌Trametes gallica为材料,研究了优化后的该菌菌丝球在非灭菌条件下对直接染料、中性染料、三苯甲烷类染料以及蒽醌类染料共12种染料的脱色能力、脱色机制,以及pH、温度、染料初始浓度等参数对该菌菌丝球脱色效果的影响。结果表明,优化条件下制备的粗毛栓菌菌丝球脱色活力良好,4℃下保存20d后仍保持有原脱色活力的95%;活菌丝球比死菌丝球对染料具有更强的耐受性和更好的脱色效果;非灭菌条件下活菌丝球对12种染料的适宜脱色条件为pH 3.0–5.0、25℃、染料浓度为50mg/L、处理36–60h,该条件下粗毛栓菌菌丝球在60h内脱色率均在55%以上,其中粗毛栓菌菌丝球对亚甲基蓝脱色率最高可达到96.40%。紫外可见光谱分析和显微观察结果表明,48h内粗毛栓菌菌丝球在非灭菌条件下对12种染料的脱色是由吸附引起,无二次污染物的产生。粗毛栓菌的这些优良特性显示了其在工业染料废水处理中的广阔应用前景。  相似文献   

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To predict rice blast, many machine learning methods have been proposed. As the quality and quantity of input data are essential for machine learning techniques, this study develops three artificial neural network (ANN)-based rice blast prediction models by combining two ANN models, the feed-forward neural network (FFNN) and long short-term memory (LSTM), with diverse input datasets, and compares their performance. The Blast_Weather_FFNN model had the highest recall score (66.3%) for rice blast prediction. This model requires two types of input data: blast occurrence data for the last 3 years and weather data (daily maximum temperature, relative humidity, and precipitation) between January and July of the prediction year. This study showed that the performance of an ANN-based disease prediction model was improved by applying suitable machine learning techniques together with the optimization of hyperparameter tuning involving input data. Moreover, we highlight the importance of the systematic collection of long-term disease data.  相似文献   

19.
旱区生态环境质量的综合定量评价模型   总被引:18,自引:3,他引:18       下载免费PDF全文
宋松柏  蔡焕杰 《生态学报》2004,24(11):2509-2515
生态环境质量是社会经济可持续发展的基础。因此 ,建立旱区生态环境质量的定量评价是区域可持续发展的主要依据。现有的评价方法大多是通过根据评价区评价指标量化值与评价等级标准来建立评价模型 ,评价区不同 ,评价模型也不相同 ,计算工作量较大。根据给定的生态环境质量评价等级标准 ,采用随机技术模拟生成足够数量的评价指标序列 ,应用人工神经网络模型 (artificial neural network,ANN) ,以评价指标生成序列与其所属的评价等级值进行网络训练。网络训练后 ,以评价区的评价指标为网络的输入 ,通过计算 ,可获得相应的生态环境质量评价等级值。并以甘肃省石羊河流域生态环境脆弱的民勤县为研究对象 ,应用 1975~ 2 0 0 0年资料进行了实例研究。结果表明 ,民勤县 1975~ 2 0 0 0年生态环境质量效应评价值分别为 2 .95 0 1,4 .0 0 90 ,4 .1342 ,4 .16 37,4 .9736 ,5 .0 12 8,说明该地区的生态环境质量是持续下降的 ,与以往采用的模糊综合评价等级值 3,4 ,4 ,4 ,5 ,5一致。文中 ANN模型建立后 ,对于不同评价区 ,只要给定相应的评价指标值 ,通过 ANN模型计算 ,可直接得出生态环境质量评价等级值。因此 ,模型具有实用、可操作性强的特点 ,大大减少了评价区的计算工作量 ,可以用于生态环境质量效应评价  相似文献   

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Although previous research has focused on phenol removal efficiencies using polyphenol oxidase in nonimmobilized and immobilized forms, there has been little consideration of the use of polyphenol oxidase in a biotransformation system for the production of catechols. In this study, polyphenol oxidase was successfully immobilized on various synthetic membranes and used to convert phenolic substrates to catechol products. A neural network model was developed and used to model the rates of substrate utilization and catechol production for both nonimmobilized and immobilized polyphenol oxidase. The results indicate that the biotransformation of the phenols to their corresponding catechols was strongly influenced by the immobilization support, resulting in differing yields of catechols. Hydrophilic membranes were found to be the most suitable immobilization supports for catechol production. The successful biocatalytic production of 3-methylcatechol, 4-methylcatechol, catechol, and 4-chlorocatechol is demonstrated.  相似文献   

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