An information system for the control of Puccinia hordei: I—Design and operation

The design and operation of a farm-level computer-based management information system for advising farmers about the use of fungicide for the control of brown rust of barley are described. Once the disease has been observed in the field, epidemics are projected forward using simulation components to model key weather variables and the resultant progress of the rust. The strategies open to a farmer midway through the growing season are assessed using the criteria of expected monetary value and expected utility. The results of preliminary validation work are presented, and the usefulness of the information system is discussed.     

小麦条锈病在山东省的发生和发展动态

本文对近几年来山东省小麦产区的条锈病发生和发展动态进行了文献综述,结果表明：除2020年发生较重外,多个县市个别年份出现历史上较早发生的情况。对山东部分小麦主栽品种的抗条锈水平进行梳理,结果表明山东麦区小麦品种抗条锈水平有所提升,在29个主栽品种中有12个品种具有中抗及以上条锈病抗性,占比42.9%;对山东境内小麦条锈病春季流行的传播源头及传播路径进行了讨论,目前有两种推论,一是陇南、四川盆地的菌源经陕西中部向中原麦区传播,二是山东麦区的条锈菌可能来自鄂西北冬繁区。作为黄淮海麦区的重要小麦产区,建议相关单位对小麦条锈菌的基础研究如山东麦区条锈菌的优势生理小种、种群遗传结构和传播路径等问题进一步明确,并且建立山东省小麦条锈菌监测的长期机制,例如定期的生理小种监测,持续的品种的抗锈性监测等。     

Simulation of the barley leaf rust epidemic: Structure and validation of BARSIM—I

This paper, the second in a series outlining development of a management information system for barley leaf rust in New Zealand, describes the structure and biological logic of the skeleton model BARSIM—I. Validation of biological system models is discussed and results of two statistical tests with BARSIM—I presented. Using a parametric (regression) technique, nine out of fifteen simulated epidemics were found to agree with field observations. With a non-parametric (Smirnov) test, model output was found in all instances to agree with field data. The relationship of simulation modelling to mathematical modelling of plant diseases is discussed.     

融合GA与SVR算法的小麦条锈病特征优选与模型构建

为提高小麦条锈病遥感监测精度,综合利用反射率光谱在作物生化参数探测方面的优势和叶绿素荧光在光合生理诊断方面的优势,构建了冠层日光诱导叶绿素荧光(Solar induced chlorophyll fluorescence,SIF)协同反射率光谱吸收参量的初始特征集合,并基于融合遗传算法(Genetic algorithm,GA)和支持向量回归(Support vector regression,SVR)算法对初始特征集合与SVR参数进行联合优选,确定遥感监测小麦条锈病严重度的敏感因子,建立基于GA-SVR算法的小麦条锈病遥感监测模型,并将其与相关系数(Correlation coefficient,CC)分析法提取特征参量构建的CC-SVR模型精度进行对比。小区试验数据验证结果表明,融合GA和SVR算法优选特征参量构建的GA-SVR模型精度优于CC-SVR模型,3个样本组中GA-SVR模型预测病情指数(Disease index,DI)与实测DI间的决定系数R2比CC-SVR模型至少提高了2.7%,平均提高了17.8%,均方根误差(Root mean square error,RMSE)至少减少了10.1%,平均减少了32.1%。大田调查数据进一步验证了利用GA-SVR算法对小麦条锈病遥感监测的敏感因子进行优选及模型构建能够提高小麦条锈病遥感监测精度,研究结果为实现大面积高精度遥感监测作物健康状况提供了思路。     

Dynamic programming and the computation of economic injury levels for crop disease control

We explain how dynamic programming can be used to determine the optimal solutions to models for crop disease control. In many cases, these solutions are the sets of dynamic economic injury levels that make management of the diseases more efficient. Three different models of yellow rust and cereal aphids on wheat are solved with dynamic programming to demonstrate its advantages and limitations.     

基于高光谱成像的甘蔗叶片早期轮斑病与锈病识别技术

针对甘蔗叶片早期轮斑病与锈病发病症状相似,难以区分,导致在实际生产中不便对症施药的问题,以甘蔗早期轮斑病和锈病叶片为研究对象,探究利用高光谱成像技术来识别甘蔗叶片早期轮斑病与锈病的可行性。首先,利用高光谱成像系统在406～1 014 nm光谱范围内采集甘蔗健康叶片、早期轮斑病叶片和锈病叶片的高光谱图像,提取图像的感兴趣区域(Region of interest, ROI)并计算其平均光谱作为原始光谱数据,采用一阶导数(First derivative, FD)、Savitzky-Golay卷积平滑(Savitzky-Golay convolutional smoothing, SG)和标准正态变换(Standard normal variate, SNV)分别对原始光谱数据进行预处理。然后,在预处理的基础上采用主成分分析(Principal component analysis, PCA)算法、蚁群优化(Ant colony optimization, ACO)算法进行特征降维,并将降维后的特征作为后期建模的输入变量。最后,结合降维和不降维2种方式使用支持向量机(SVM)和随机森林(R...     

Modelling systems of disease and yield loss in cereals

Efforts to develop reliable models for predicting crop yield loss due to diseases have increased in recent years, in response to the demands for disease management and for resource allocation for research and extension. This paper outlines the statistical and physiological criteria that should be considered during the development of such models. Case studies from the literature are examined and discussed in relation to their use in providing regional crop loss estimates. A conceptual response surface of cereal yield loss to disease constraints is proposed and suggested as a guide for future disease-loss modelling. The limitations of empirical data for response surface models are illustrated using a barley leaf rust system.     

A framework for decision support related to infectious diseases in slaughter pig fattening units

This paper analyzes the problem faced by managers of pig fattening units when the pigs are subject to common epidemic diseases, such as respiratory diseases or Swine Influenza. The problem is defined as a simultaneous optimization of the delivery policy and control strategies for disease control. As some disease controls, such as vaccination, are implemented at the batch level and last through the lifetime of the vaccinated pigs, the problem requires that decisions are addressed at multiple timescales. Using the framework of multi-level hierarchic Markov processes a general framework was defined. The elements defining the framework were the decisions at the tactical (batch) level and the operational (daily) level. Decisions at the strategic level, e.g., decisions lasting longer than the length of a batch, were considered as constraints to the lower levels of the decision problem and not optimized. The major components of the general framework were a stochastic growth model, an epidemic model to handle within-batch spread of disease, a transition model to handle the between-batch spread of disease, and link between the growth model and the disease model and a general set of control measures. The model was illustrated using an example with Swine Influenza in an all-in-all-out production system. Results show that the optimal delivery policy and control strategies for disease interact. This suggests that decision support must adopt an integrated approach to modelling the decision complex in pig production in order to represent the full complexity of the system.     

基于平顺性仿真的农用运输车悬架CAD研究

在建立农用运输车整车多体动力学模型的基础上,借助于软件ＡＤＡＭＳ和笔者编制的软件研究了农用运输车平顺性仿真的方法。以平顺性为目标函数,在优化悬架系统的特性参数后,进行结构ＣＡＤ。针对具体车型设计出新的悬架系统,并装车试验。仿真和试验结果都表明在整车多体动力学仿真的基础上进行悬架ＣＡＤ,是提高整车性能的很好的途径。     

基于方向一致性特征的小麦条锈病与白粉病识别方法

针对小麦条锈病、白粉病这2种病斑颜色特征相近、形状特征不明显,但在方向分布的一致性上却存在较大差别这一特点,提出了一种方向一致性描述方法。通过不同的方向核与图像卷积得到多个方向图和边缘,对每个方向图依据边缘图进行统计得到图像的方向分布直方图;并计算方向分布直方图的标准差,作为图像方向分布的一致性特征。该方法能够较好地抑制噪声影响,得到的结果符合图像的实际分布情况。利用该方法对小麦病斑进行特征提取,并应用于小麦条锈病与白粉病的病斑识别实验中。实验结果表明,所提出的方向一致性特征使条锈病与白粉病的区别度较大,准确识别率达到99%。     

轴流泵模型多叶片安放角的数值计算

在同一轴流泵模型0°安放角数值计算结果的基础上,应用ANSYS CFX软件,选择标准k-ε湍流模型和可伸缩壁面函数,在不同的叶片安放角下,采用全六面体网格和经网格无关性分析的网格数,分别在定常和非定常条件下进行了多工况的数值模拟和外特性计算,并将计算结果与试验结果进行对比.在规范使用工具软件的条件下,分析了CFD数值模拟技术预估轴流泵性能的精度及其误差的特点.结果表明,非定常计算扬程值略高于试验值,而定常计算扬程值低于试验值,非定常计算的总体精度高于定常计算,且误差可控制在5%以内;定常和非定常预测的效率误差可控制在7%以内,且非定常计算的效率与试验效率存在一相对固定幅度的偏差,据此可用于修正同类模型效率的预测值.基于非定常计算的结果,进一步分析了叶轮和导叶圆柱面上流线分布、叶片截线压力分布和轴流泵过流部件各部分水力损失随叶轮叶片安放角和流量的变化规律,发现在小流量工况,靠近轮毂位置存在旋涡堵塞现象;在计算工况范围内,导叶段和出水段水力损失随流量的增大呈现先减小后增大的趋势.     

内燃机喷雾模型的研究现状

喷雾模型是内燃机CFD软件中重要的组成部分,而喷雾模型是由多种子模型组成的。正确设定喷嘴出口的边界条件和选择恰当的喷雾破碎模型成为成功分析和优化内燃机喷雾过程的先决条件。本文着重介绍了孔式喷嘴流动模型和基于表面波不稳定性理论的WAVE模型、KH—RT模型、Huh—Gosman模型和LISA模型,以及它们在CFD软件中的应用。这些模型的应用从理论上讲可以大大提高内燃机喷雾多维模拟的计算精度。     

A simulation model to study land use strategies in swidden agriculture systems

Development has ended isolation in many parts of Kalimantan, Indonesia, and provides previously isolated communities with the opportunity for greater involvement in a market economy. This paper describes the use of a simulation model to study the possible impacts of greater involvement in cash cropping in swidden agricultural systems. The model uses both individual-based and rule-based modelling approaches. The model formulation is based on a previous report of the social structure, culture and agricultural production system of the Kantu’ in West Kalimantan [Dove, M.R., 1985. Swidden Agriculture in Indonesia: The Subsistence Strategies of the Kalimantan Kantu’. Mouton Publishers, Berlin]. The model simulates: (1) births, deaths, marriage, household formation and dissolution; (2) land use decisions on the type, number and location of swidden cultivation; and (3) tracks the consequences of those decisions at a landscape level as well as the economic welfare of the households. The model deals with swidden cultivation of rice and the planting and tapping of rubber. The paper presents a simulation ‘experiment’ that compares different land use strategies under a scenario of fluctuating rubber price. An important finding is that maintaining swidden cultivation as ‘an option’ in the farming system, rather than permanently replacing swidden cultivation with cash cropping, appears to be a safer strategy to moderate the impact of commodity price fluctuations.     

Influence of likelihood function choice for estimating crop model parameters using the generalized likelihood uncertainty estimation method

Proper estimation of model parameters is required for ensuring accurate model predictions and good model-based decisions. The generalized likelihood uncertainty estimation (GLUE) method is a Bayesian Monte Carlo parameter estimation technique that makes use of a likelihood function to measure the closeness-of-fit of modeled and observed data. Various likelihood functions and methods of combining likelihood values have been used in previous studies. This research was conducted to determine the effects of using previously reported likelihood functions in a GLUE procedure for estimating parameters in a widely-used crop simulation model. A factorial computer experiment was conducted with synthetic measurement data to compare four likelihood functions and three methods of combining likelihood values using the CERES-Maize model of the Decision Support System for Agrotechnology Transfer (DSSAT). The procedure used an arbitrarily-selected parameter set as the known “true parameter set” and the CERES-Maize model to generate true output values. Then synthetic observations of crop variables were randomly generated (four replicates) by using the simulated true output values (dry yield, anthesis date, maturity date, leaf nitrogen concentration, soil nitrate concentration, and soil moisture) and adding a random observation error based on the variances of corresponding field measurements. The environmental conditions were obtained from a sweet corn (Zea mays L.) experiment conducted in 2005 in northern Florida. Results showed that the method of combining likelihood values had a strong influence on parameter estimates. The combination method based on the product of the likelihoods associated with each set of observations reduced the uncertainties in posterior distributions of parameter estimates most significantly. It was also found that the likelihood function based on Gaussian probability density function was the best among those tested. This combination accurately estimated the true parameter values, suggesting that it can be used when estimating CERES-Maize model parameters for real experiments.     

基于虚拟现实技术的喷灌机试验研究

随着仿真技术的发展与应用,虚拟试验也越来越得到广泛应用。为此,以喷灌机的虚拟试验为例,讨论了基于MultiGen-Creator如何建立地形模型以及建立复杂机械模型的原理与方法;同时,利用Vega Prime进行了场景驱动和漫游,解决了VC开发虚拟场景驱动参数和编程环境设置问题。     

传动系新型节能试验系统动态仿真

简要介绍了一种用于传动系试验的新型试验系统及其工作原理和特点,建立了该试验系统的数学模型,利用MATLAB/S imu link构建了该系统的仿真模型,并对其动态特性进行了仿真分析。讨论了主要参数对系统性能的影响,得出了系统参数变化的特性曲线及相应有益的结论。     

土方机械落物保护结构动态仿真及试验

简述了土方机械落物保护结构的特点及性能要求,建立了落物保护结构受瞬态冲击响应的有限元结构动力学方程并提出了求解算法。以某装载机落物保护结构为例,建立了落物保护结构的非线性有限元模型,讨论了有限元网格划分及载荷施加方法,分析了落物保护结构的主要设计参数对冲击点最大位移及落锤速度和加速度的影响,并给出了更合理的结构。在试验台上对该装载机落物保护结构进行了落物冲击试验,试验结果和仿真结果吻合较好。落物保护结构的动态仿真为结构的设计提供了依据。     

基于改进ResNet18的苹果叶部病害多分类算法研究

针对传统苹果叶部病害分类方法精准性差、效率低等问题,提出了一种基于改进ResNet18的苹果叶部病害多分类算法。通过在原始ResNet18网络的基础上增加通道与空间注意力机制分支,强化网络对叶部病害区域的特征提取能力,提高病害的识别精度和实时性。为更好地引导网络学习到零散分布的病害斑点的特征,引入特征图随机裁剪分支,不仅实现有限样本空间的扩充,还进一步优化网络结构,提高训练速度。试验以苹果5类常见的叶部病害(黑星病、黑腐病、雪松锈病、灰斑病、白粉病)为主要研究对象,并与主流分类算法模型进行对比。试验结果表明,所提ResNet18-CBAM-RC1模型病害分类准确率可达98.25%,高于ResNet18(93.19%)和VGG16(96.13%),能够有效提取叶片病害特征,增强对多类病害的识别,提高识别准确率。此外,模型内存占用量仅为37.44 MB,单幅图像推理时间为9.11 ms,可满足嵌入式设备上果园病害识别的实时性要求。     

晾晒谷物收集小车的设计

通过对现有晒场收谷机械性能进行分析比较,提出从广西实际出发,在现有晒场收谷机械的基础上,利用吸尘器抽吸的原理,设计出一种晾晒谷物收集小车。介绍了晾晒谷物收集小车整体结构、工作原理及关键零部件的设计。同时,利用仿真软件ANSYS对相应部件三维模型进行仿真分析,验证了该晾晒谷物收集小车的应力分布和变形均在标准规定范围内,进一步确定了设计的可靠性。研究结果表明:该晾晒谷物收集小车结构简单、操作方便,减轻了晒场谷物收集装袋工作的负担,能满足接地工作的要求。     

基于改进型C—V模型的植物病斑图像分割

针对植物病斑图像背景复杂且分割难问题,提出一种基于水平集和加权颜色信息的C-V模型。借助水平集方法对病斑图像的R、G、B分量图像颜色信息取加权值,以差分图像能量作为能量函数最终值,以适应不同的病害种类。试验结果表明,经过R、G、B加权的黄瓜红粉病病斑图像使用4R-G图像模型、苹果锈病病斑图像使用3R-G-B图像模型自动分割的效果较好,比传统C-V模型分割性能好,抗噪性好,可扩展性好。