洋葱伯克霍尔德菌CF-66发酵动力学研究

研究在3.7 L发酵罐内分批培养洋葱伯克霍尔德菌CF-66过程中生物量、柠檬酸钠和产物CF66I含量的变化规律.利用MATLAB软件将实验数据非线性拟合,确定模型参数,建立洋葱伯克霍尔德菌CF-66分批发酵动力学模型.菌体生长、底物柠檬酸钠消耗以及产物CF661生长动力学模型分别为dx/dt=0.3220(1-x/4.2504)x、ds/dt=-(1/0.0278)dx/dt和dp/dt=0.1244x.将模型预测值与实验值比较,表明模型非常实用.     

基于SimBiology生物反应过程的模拟

过程模拟是生物工程过程设计的有效方法.SimBiology提供了一个为生物系统建模、模拟、分析生化路径的集成环境.以典型的酶反应和细胞反应为例,通过在SimBiology的图形用户界面输入反应式或模型公式、参与反应的物质种类、参数设置、动力学定律等,实现了对反应过程的建模及模拟.研究表明:该法操作简单,运行可靠,与其它需要繁琐编程的仿真软件相比,SimBiology是生物系统建模与仿真更为便利的工具.     

基于IBA-LSSVM的光合细菌发酵软测量

针对光合细菌(PSB)发酵过程活菌浓度难以在线检测,离线测量又存在很大延时及易染菌的问题,提出一种基于改进蝙蝠-最小二乘支持向量机(IBA-LSSVM)的软测量建模方法。本文先对BA的速度更新公式进行改进,且将差分进化算法(DE)的变异机制引入BA,增加了种群多样性,进而提升了BA算法的全局及局部搜索能力,然后构建了活菌浓度的IBA-LSSVM软测量模型,并与BA-LSSVM软测量模型进行对比。仿真结果表明,改进的模型相较于BA-LSSVM模型有着更好的学习能力和预测性能,测量误差为0.1358,可为光合细菌发酵过程的优化控制提供准确有效的指导,有一定的实际应用价值。     

宁康霉素对植物病原真菌的抑制作用

宁康霉素是由海洋细菌BAC-9912发酵获得的生物农药,对多种植物病原真菌有良好的抑制作用。本研究发现宁康霉素强烈抑制玉米纹枯病菌和苹果轮纹病菌的菌丝,可使玉米纹枯病菌菌丝枯萎和产生畸形。比较宁康霉素与农利灵和速克灵对玉米纹枯病菌的抑菌效果,结果显示宁康霉素的抑菌效果优于两种化学农药。     

花生四烯酸发酵过程的建模方法研究

对发酵法生产花生四烯酸的建模方法进行了初步研究,并基于四种温度下的试验数据,建立了发酵过程模型.比较分析了最小二乘支持向量机( LS-SVM)和广义回归神经网络(GRNN)这两种方法的特点.结果表明,这两种方法均能较好地建立该发酵过程的模型,LS-SVM建模的预测能力稍优于GRNN,为后续花生四烯酸发酵过程的优化及控制的研究奠定了基础.     

引力搜索算法在青霉素发酵模型参数估计中的应用

针对生物发酵过程难以精确估计模型参数的问题,提出一种利用引力搜索算法(GSA)对青霉素发酵非构造式动力学模型参数进行估计的方法。在分析发酵过程反应机理的基础上,选取合适的青霉素发酵非构造式动力学模型的状态方程式;然后利用GSA良好的全局搜索能力,对状态方程式的参数进行估计,从而得到精确的发酵模型。仿真结果表明：GSA实现了对青霉素发酵过程模型参数的准确估计,所得到的模型精度能够满足青霉素发酵过程的状态估计和控制需求。因此,GSA可有效地应用于模型参数估计。     

基于BP神经网络的pH对解淀粉芽孢杆菌Q-426发酵影响的研究

为控制解淀粉芽孢杆菌Q-426发酵过程,研究了在3.7 L发酵罐中pH对菌株Q-426发酵过程的影响。选取发酵时间、pH作为自变量,菌体浓度、底物浓度、发酵产物活性作为目标量,通过构建自变量矩阵和参考序列,构建了基于BP神经网络的菌株Q-426发酵过程的预测模型。通过运用MATLAB神经网络工具箱进行训练,得出优化网络模型,并根据建立的模型进行预测。将预测值与实测值对比,拟合及预测的平均相对误差均在4%以内,说明该模型有较好的适用性。     

氨基酸发酵过程优化控制

采用动力学模型描述苏氨酸发酵动态过程。对发酵过程进行优化控制,并建立了知识库系统。结果表明,缩短了发酵时间,提高了苏氨酸的产量和质量。     

基于混沌和SVM的青霉素发酵过程混合建模

就青霉素发酵过程难以建立理想模型,提出一种基于混沌支持向量机和动力学模型相结合的混合建模新方法.首先分析青霉素发酵过程动力学模型的特点,选择合适的状态变量,然后利用混沌算法优化支持向量机的参数,建立动态时变的混合模型.该模型不但能自动选择支持向量机的参数,而且能够预报一些不能在线测量的生化状态变量.通过实用,证明了此方法有效.     

F-T合成蜡油加氢裂化反应器模型算法的研究

以费托合成蜡油加氢裂化反应器为研究对象,根据文献报道的九集总动力学,结合Aspen虚拟物性组分功能和Fortran语言,关联了集总划分和油品计算方法,构建起新的模型算法,并用原文献报道数据进行了验证。结果表明,所建立的模型算法能较好反映加氢裂化过程,并在此基础上对温度、压力、重时空速和氢油比进行灵敏度分析,优化反应器操作条件,得到最佳操作条件为温度648 K,压力47.5 bar,氢油比0.105 wt/wt,重时空速2h~(-1)。在温度(553-633)K,空速(0.2-5)h~(-1)时,选用贵金属Pt作为加氢活性组分,β分子筛改性无定形硅铝作为催化剂载体,56#半炼蜡作为反应模型化合物,根据实际实验所测结果对比九集总和四集总反应模型,结果表明,2个集总模型计算值与实验值吻合都较好,九集总的在高温段模拟结果比四集总更精确。     

Q-Learning-Based Pesticide Contamination Prediction in Vegetables and Fruits

Pesticides have become more necessary in modern agricultural production. However, these pesticides have an unforeseeable long-term impact on people's wellbeing as well as the ecosystem. Due to a shortage of basic pesticide exposure awareness, farmers typically utilize pesticides extremely close to harvesting. Pesticide residues within foods, particularly fruits as well as veggies, are a significant issue among farmers, merchants, and particularly consumers. The residual concentrations were far lower than these maximal allowable limits, with only a few surpassing the restrictions for such pesticides in food. There is an obligation to provide a warning about this amount of pesticide use in farming. Previous technologies failed to forecast the large number of pesticides that were dangerous to people, necessitating the development of improved detection and early warning systems. A novel methodology for verifying the status and evaluating the level of pesticides in regularly consumed veggies as well as fruits has been identified, named as the Hybrid Chronic Multi-Residual Framework (HCMF), in which the harmful level of used pesticide residues has been predicted for contamination in agro products using Q-Learning based Recurrent Neural Network and the predicted contamination levels have been analyzed using Complex Event Processing (CEP) by processing given spatial and sequential data. The analysis results are used to minimize and effectively use pesticides in the agricultural field and also ensure the safety of farmers and consumers. Overall, the technique is carried out in a Python environment, with the results showing that the proposed model has a 98.57% accuracy and a training loss of 0.30.     

吡虫啉和代森锰锌的太赫兹光谱研究

为了解吡虫啉和代森锰锌两种农药在太赫兹波段的光谱特性,采用太赫兹时域光谱(THz-TDS)技术测量了室温下吡虫啉和代森锰锌在0.2-2.0 THz的高分辨率吸收谱和折射率谱.结果表明两种农药样品在此波段都有明显的特征吸收峰,且吸收谱存在显著差异.两种样品的平均折射率分别为1.65和1.32,随着频率的增加,吡虫啉的折射率增大,而代森锰锌的折射率减少.太赫兹时域光谱(THz-TDS)技术可以鉴别不同种的农药分子,这对进一步利用该技术检测农药残留有重要的意义.     

探测农药残留用量热式生物传感器微机监控处理系统

针对探测农药残留用量热式生物传感器，组建了微机监控处理系统，可以实时监控和处理多个参数。利用VisualBasic6．0开发了相应的数据采集和处理程序，采用智能算法对数据进行基线校正、信号峰识别和重叠峰分解等处理，能够得到信号峰的峰高、峰面积等数据，并可动态判断和显示农药残留是否超标。系统具有操作简便、功能强大等特点。     

监测氨基甲酸酯类农药的光纤荧光光谱仪的研究

根据西维因、克百威等氨基甲酸酯类农药的荧光性质，光谱仪采用氙灯作为激发光源，用光纤进行传光并结合CCD光谱探测技术，实现了对氨基甲酸酯类农药的快速测定。此仪器结构简单，操作灵活，线性度好，灵敏度高。实验结果表明，西维因和克百威的浓度线性范围为0—120ppb，最低检出限LOD分别为2．7ppb和7．0ppb。在实际取样的测量中，还要考虑到腐殖酸的猝灭作用，通过对仪器进行校正得到准确的测量值。     

Development of an immunosensor based on the measurement of fluorescence

Consumers concern about the presence of pesticides in food is increasing. However current techniques for detecting pesticide residues in olive oil are very expensive and slow, which make them difficult to apply in commercial conditions. For this reason, the Instituto Valenciano de Investigaciones Agrarias (IVIA) and Universidad Politécnica de Valencia (UPV) have decided to develop an immunosensor as an alternative, fast and cheap method to measure the concentration of some pesticides in olive oil. This work shows the developed transducer by IVIA based on a photovoltaic sensor that transforms the fluorescent radiation to an electrical signal. The immunosensor is based on an immunologic reaction which causes fluorescence on the sample. The intensity of the fluorescence is related with the concentration of marked antibodies. The performed tests with two types of immunoassays and fluorescent markers (FITC and ELF97) have demonstrated the robustness and reliability of the developed transducer. The immunosensor is able to discriminate different concentrations of marked antibodies. This study has demonstrated the possibility of applying this immunosensor to detect chemical residues from pesticide treatments in olive oil samples. These results validate the sensor for future commercial applications.     

基质中农药回收率与超声空化效应的关系

通过超声动力学分析与实验相结合的研究方法,阐述了超声波促进农药溶解和引发农药分解两种效应的内在机理和相互制约关系。首先,基于Rayleigh-Plesset方程,利用数值迭代法(龙格-库塔算法)计算不同能量和频率组合下超声波的空化效应类型及强度;然后,进行纯溶剂中农药的分解率实验和菠菜基质中农药的回收率实验。研究结果表明:超声波的瞬态空化效应一方面通过破坏植物组织,促进被吸附的农药的释放,另一方面产生羟自由基(-OH)等游离子,导致农药被氧化分解。瞬态空化效应的强弱可通过单位时间内空化泡崩溃释放的压力值(Pmax/t)直观表示,当Pmax/t≤2.1×107atm/s时,溶解效应强于分解效应,农药回收率随Pmax/t增大而增大;当Pmax/t>2.1×107atm/s时,分解效应大于溶解效应,回收率降低;9种农药的平均回收率在Pmax/t=2.1×107atm/s时达最高值(此时超声波的频率和能量分别为45kHz和400W),可实现菠菜中多残留农药高溶解、低分解的超声萃取。     

星座聚类法的改进及其在有机氟农药构效关系识别中的应用

星座图法是对复杂模式作聚类分析的一种简便有效方法，作者提出用拉格朗日乘子法对星座路径参数进行优化改进，比较了改进前后的聚类效果，证实了改进后的星座图法不仅具有理论优势，也具有应用价值．最后将星座图法应用于有机氟农药构效关系识别，取得了良好的活性分类结果。     

A micro-machined thin film electro-acoustic biosensor for detection of pesticide residuals§

Increasing awareness concerning food safety problems has been driving the search for simple and efficient bio-chemical analytical methods. In this paper, we develop a portable electro-acoustic biosensor based on a film bulk acoustic reso-nator for the detection of pesticide residues in agricultural products. A shear mode ZnO film bulk acoustic resonator with a mi-cro-machining structure was fabricated as a mass-sensitive transducer for the real-time detection of antibody-antigen reactions in liquids. In order to obtain an ultra-low detection level, the artificial antigens were immobilized on the sensing surface of the resonator to employ a competitive format for the immunoassays. The competitive immunoreactions can be observed clearly through monitoring the frequency changes. The presence of pesticides was detected through the diminution of the frequency shift compared with the level without pesticides. The limit of detection for carbaryl （a widely used pesticide for vegetables and crops） is 2′10-10 M. The proposed device represents a potential alternative to the complex optical systems and electrochemical methods that are currently being used, and represents a significant opportunity in terms of simplicity of use and portability for on-site food safety testing.     

CPEST: An expert system for the management of pests and diseases in the Jamaican coffee industry

Over the last few years, environmental concerns have led to the emergence of the integrated management of pest and pesticides (IMPP) as a new way to deal with pests and pesticides in agriculture. Although the environmental and economic benefits of IMPP are beyond doubt, its use has been somewhat limited. One reason is the sheer amount of knowledge required of such things as climate, topography, soil type of the farm, agronomic practices, crop phenology, biology and damage potential of the pests and options available for suppressing their population below the economic injury levels. Unfortunately, such knowledge typically resides within a few experts and is not easily available to farmers. In order to make this knowledge more widely available, we developed CPEST, an expert system for managing pest and diseases of coffee in a developing country. The paper describes the architecture and development of CPEST, gives examples of the interface that a farmer would use to enter information and provides an evaluation of the quality of the advice that CPEST provides.