兔非特异性免疫力抗长角血蜱幼虫感染能力的研究

本实验以卡介苗作为免疫增强剂和以地塞米松与雷公藤擦剂作为免疫抑制剂,以此改变兔非特异性免疫功能,观察免疫力不同的动物抗长角血蜱幼虫感染的能力.结果发现非特异性免疫增强组兔对蜱抵抗力较强,而非特异性免疫抑制组相对较弱,提示在蜱活动季节灭蜱时,应该考虑动物体况,加强动物营养,对种用动物以免疫增强剂进行接种,减少疾病的发生。蜱作为多种病原体的生物性媒介和自身作为病原体对人和动物危害严重。通常采用的灭蜱措施主要有药物防治、生物防治等,但对不同体况动物自身抗蜱能力的研究尚缺,本实验对此进行了研究。     

盐胁迫对牧草种子萌发及其恢复的影响

观察了７种牧草种子在８个ＮａＣｌ浓度;０（０Ｍｐａ）,２１－９－０．１Ｍｐａ）,６６（－０．３Ｍｐａ）,１１ｐ（－０．５Ｍｐａ）,１５０（－０．７０Ｍｐａ）,２００（－０．９Ｍｐａ）,２６７（－１．２Ｍｐａ）,３３４（－１．９５Ｍｐａ）,４４５（－２．６０３Ｍｐａ）ｍｍｏｌ／Ｌ下的发芽率及胚根和胚芽的生长,将盐胁迫下未萌发种子移入营养液中,观测它们在解除发芽率呈下降趋势,但长穗偃麦草的发芽率几乎不     

基于虚拟仪器技术的温室监控系统

利用LabVIEW开发平台设计了基于虚拟仪器的温室监控系统,其基本思想是将传统的硬件仪器监控系统通过虚拟仪器技术来实现。为此,介绍了温室监控系统的组成及工作原理。该系统可完成温室内的温度、湿度、光照和CO2等参数的采集。通过监视温室历史与实时环境参数,对温室环境的调节进行必要的人为控制,实现温室环境参数优化管理。该系统具有分析效果好、投入成本低和功能易扩展等优点。     

紫花苜蓿干燥和茎叶分离效果预测模型与工艺优化

为研究新鲜切碎紫花苜蓿茎叶干燥分离过程中,入口温度、入口风速、转筒转速和喂料速度对出机叶料含水率、出机茎料含水率、茎叶分离率的影响,采用9GFQA-600型苜蓿干燥茎叶分离设备进行试验,设计了四因素二次正交旋转组合试验进行回归分析,建立了相应的数学模型并进行了优化。结果表明,得到的回归方程显著,具有较好的拟合度;4个因素对苜蓿茎叶干燥分离效果的影响大小依次为：入口温度、入口风速、转筒转速、喂料速度;最优参数组合为：入口温度400℃、入口风速14m/s、转筒转速为12r/min、喂料速度8kg/min,在此条件下出机叶料含水率为13.42%、出机茎料含水率为14.24%、茎叶分离率为     

红枣干燥技术与装备研究进展

为了探索开发适宜缩短红枣干燥时间、提高红枣干燥品质的技术与装备,综述了红枣单一与联合干燥发展现状与研究进展,并在此基础上进行了红枣干燥技术与装备的对比分析.同时,阐述了预处理对红枣干燥特性的影响,以期为在研究红枣干燥特性和干燥装备现状的基础上,对不同红枣干制品实施适宜的干燥加工技术与研制新型干燥装备提供理论依据与技术支...     

巨菌草高温快速干燥设备设计与试验

为了解决巨菌草含水率高、不易贮藏,以及自然晾晒中人工劳动强度大、营养损失大的问题,设计了一套大型高秆禾草高温快速干燥设备。基于传热传质理论,进行了关键参数计算与关键部件的设计,通过力学分析与FLUENT流体仿真进行优化,并对控制单元进行了设计。以最终含水率、水活度、色泽度、粗蛋白含量、酸性洗涤纤维含量和中性洗涤纤维含量为评价指标,进行了设备的干燥试验,并与新鲜物料、自然晾晒干燥进行对比分析。结果表明:高温快速干燥后,巨菌草的最终含水率为(16±1.82)%,水活度为0.564 8,生产率为2.73 t/h;与新鲜物料相比,亮度值L和蓝黄值b均无显著性差异,红绿值a增加了1.43;粗蛋白含量与酸洗中洗纤维含量均无显著性变化,粗蛋白质量分数较新鲜物料下降0.6个百分点。与自然晾晒相比,高温快速干燥后巨菌草的粗蛋白质量分数增加了0.63个百分点,且具有较好的表观质量。试验结果表明,该套设备改善了干燥后巨菌草的表观质量和品质,满足了巨菌草干燥的要求。     

水稻矮秆多分蘖突变体mz3的遗传分析和基因定位

通过EMS诱变粳稻品种中花11获得一个稳定遗传的矮秆多分蘖突变体mz3。遗传分析表明该突变性状受一对隐性基因控制,并利用mz3与籼稻品种南京11杂交建立的F2群体,将该基因定位在水稻第6染色体长臂上的SSR标记RM19353与RM510之间约747kb范围内。由于该区间包含控制水稻株高和分蘖的D3基因,结合表型分析,推测突变基因与D3可能为一对等位基因。设计7对引物分别对中花11与突变体mz3的基因进行测序,结果显示,与中花11相比,D3基因在mz3中第636位核苷酸由G突变为A,使得编码色氨酸的密码子TGG突变为终止密码子TGA,导致翻译提前终止。进一步对定位群体中10个隐性极端个体测序,结果显示所有极端个体都带有该突变位点。亚细胞定位结果表明,突变体编码的D3蛋白与野生型一样定位在细胞核中,荧光双分子互补试验结果表明,突变体D3蛋白不能与D14蛋白发生互作,推测突变体编码的D3截短蛋白缺少了与D14互作的氨基酸序列,从而阻碍了独脚金内酯信号传递。因此,mz3表型很可能由D3基因突变引起。     

Modeling spatio-temporal distribution of soil moisture by deep learning-based cellular automata model

Soil moisture content (SMC) is a key hydrological parameter in agriculture,meteorology and climate change,and understanding of spatio-temporal distributions of SMC in farmlands is important to address the precise irrigation scheduling.However,the hybrid interaction of static and dynamic environmental parameters makes it particularly difficult to accurately and reliably model the distribution of SMC.At present,deep learning wins numerous contests in machine learning and hence deep belief network (DBN) ,a breakthrough in deep learning is trained to extract the transition functions for the simulation of the cell state changes.In this study,we used a novel macroscopic cellular automata (MCA) model by combining DBN to predict the SMC over an irrigated corn field (an area of 22 km~2) in the Zhangye oasis,Northwest China.Static and dynamic environmental variables were prepared with regard to the complex hydrological processes.The widely used neural network,multi-layer perceptron (MLP) ,was utilized for comparison to DBN.The hybrid models (MLP-MCA and DBN-MCA) were calibrated and validated on SMC data within four months,i.e.June to September 2012,which were automatically observed by a wireless sensor network (WSN) .Compared with MLP-MCA,the DBN-MCA model led to a decrease in root mean squared error (RMSE) by 18%.Thus,the differences of prediction errors increased due to the propagating errors of variables,difficulties of knowing soil properties and recording irrigation amount in practice.The sequential Gaussian simulation (s Gs) was performed to assess the uncertainty of soil moisture estimations.Calculated with a threshold of SMC for each grid cell,the local uncertainty of simulated results in the post processing suggested that the probability of SMC less than 25% will be difference in different areas at different time periods.The current results showed that the DBN-MCA model performs better than the MLP-MCA model,and the DBN-MCA model provides a powerful tool for predicting SMC in highly non-linear forms.Moreover,because modeling soil moisture by using environmental variables is gaining increasing popularity,DBN techniques could contribute a lot to enhancing the calibration of MCA-based SMC estimations and hence provide an alternative approach for SMC monitoring in irrigation systems on the basis of canals.     

Simulating in situ ammonia volatilization losses in the North China Plain using a dynamic soil‐crop model

Ammonia (NH₃) volatilization is an important N loss pathway in intensive agriculture of the North China Plain (NCP). Simulation models can help to assess complex N and water processes of agricultural soil–crop systems. Four variations (Var) of a sub‐module for the deterministic, process‐based HERMES model were implemented ranging from simple empirical functions (Var 3 and 4) to process‐oriented approaches (Var 1 and 2) including the main processes of NH₃ volatilization, urea hydrolysis, nitrification from ammonium‐based N fertilizer, and changes in soil solution pH. Ammonia volatilization, plant growth, and changes in ammonium and nitrate pools in the soil over several winter wheat–summer maize double‐crop rotations at three locations in the NCP were simulated. Results were calibrated with two data sets (Dongbeiwang 1, Shunyi) and validated using two data sets (Dongbeiwang 2, Quzhou). They showed that the ammonia volatilization sub‐module of the HERMES model worked well under the climatic and soil conditions of N China. Although the simpler equations, Var 3 and 4, showed lower deviations to observed volatilization across all sites and treatments with a mean absolute error (MAE) of 1.8 and 1.4 in % of applied N, respectively, compared to process‐oriented approaches, Var 1 and 2, with a MAE of 2.2 and 1.9 in % of applied N, respectively. Environmental conditions were reflected better by the process‐oriented approaches. Generally, simulation results were satisfying but simulated changes in topsoil pH need further verification with measurements.     

退化草地复合体力学特性与影响因素研究

为采用机械手段有效打破高坚实度退化草地板结性土层形成的土壤-根系复合体结构,对退化草地形成的复合体结构基本力学特性进行了研究。通过测定退化草地复合体的紧实程度、容重、含水率、孔隙度和含根量分布,对退化草地形成的复合体的物理性状进行了分析;通过对复合体原状试样进行剪切、无侧限压缩和回弹模量试验,对复合体的抗剪、无侧限抗压和回弹等基本力学特性进行了研究,并在此基础上通过正交试验探讨了容重、含水率和含根量对上述力学特性的影响。研究发现,退化草地形成的复合体具有加剧土壤紧实程度、聚集根系向浅层分布等特征;复合体的抗剪强度、无侧限抗压强度和回弹模量因根系的存在与无根系分布的土层相比有很大变化;复合体容重、含水率和含根量均对其力学特性产生了影响,且各因素的影响存在交互作用,根系的存在可增强复合体结构的抗剪强度和无侧限抗压强度,但对于回弹模量的影响却表现出一定的差异性。