Gilligan C A, Brassett P R, Campbell A
Department of Applied Biology, University of Cambridge, Pembroke Street, Cambridge, CB2 3DX, U.K.
National Institute of Agricultural Botany, Huntingdon Road, Cambridge, CB3 OLE, U.K.
New Phytol. 1994 Nov;128(3):515-537. doi: 10.1111/j.1469-8137.1994.tb02999.x.
A stochastic model is constructed to simulate the spatial and temporal spread of infection of the take-all fungus, Gaeumannomyces graminis var. tritici (Sacc.) Arx & Olivier var. tritici Walker on seminal roots of wheat. The model is designed to synthesize information on the dynamics and spatial orientation of the growth of main seminal root axes of wheat and the dynamics of primary and secondary infection of the pathogen. Primary infection is initiated by the soil inoculum. Three types of secondary infection by runner hyphal growth are distinguished; re-infection of the same root, infection of another root on the same plant via the crown, and cross-infection between roots on different plants. There are nine pathogen parameters, 14 host parameters, as well as four system parameters in addition to the location and orientation of seedlings. The pathogen parameters comprise estimates for the size and density of inoculum, the rate of growth of the fungus on roots, and the mean distances and probability of occurrence for primary and secondary infection. The host parameters concern orientation, density, emergence, rates of growth and size of roots. The principal output variables are total and infected root length, numbers of infections, proportion of infected roots and the numbers of primary and cross infections. Results of sensitivity analysis of the output variables to selected input parameters are presented. The model is tested against independent data-sets from inoculum-density experiments for different soil temperatures and ranges of inoculum density. Statistical methods of response curve analysis are used to compare the behaviour of inoculum density-disease response curves for the simulated and experimental data. The model fitted the data satisfactorily for the majority of host and infection variables. Inclusion of secondary infection in the model improved the goodness-of-fit but the density of secondary infections was small relative to primary infections. Practical and conceptual problems in the validation of complex simulation models for fungal infection are discussed. The advantages and limitations of this and related models are critically assessed.
构建了一个随机模型，用于模拟全蚀病菌（禾顶囊壳小麦变种，学名：Gaeumannomyces graminis var. tritici (Sacc.) Arx & Olivier var. tritici Walker）在小麦种子根上的感染时空传播。该模型旨在综合有关小麦主要种子根轴生长的动态和空间取向以及病原体初次和二次感染动态的信息。初次感染由土壤接种物引发。区分了三种由匐匍菌丝生长引起的二次感染类型：同一根的再感染、通过冠部对同一植株上另一根的感染以及不同植株根之间的交叉感染。除了幼苗的位置和取向外，有九个病原体参数、14个宿主参数以及四个系统参数。病原体参数包括接种物大小和密度的估计值、真菌在根上的生长速率以及初次和二次感染的平均距离和发生概率。宿主参数涉及根的取向、密度、出土情况、生长速率和大小。主要输出变量为总根长和感染根长、感染数量、感染根的比例以及初次和交叉感染的数量。给出了输出变量对选定输入参数的敏感性分析结果。该模型针对不同土壤温度和接种物密度范围的接种物密度实验的独立数据集进行了测试。使用响应曲线分析的统计方法来比较模拟数据和实验数据的接种物密度 - 病害响应曲线的行为。对于大多数宿主和感染变量，该模型与数据拟合良好。模型中纳入二次感染提高了拟合优度，但相对于初次感染，二次感染的密度较小。讨论了真菌感染复杂模拟模型验证中的实际和概念性问题。对该模型及相关模型的优缺点进行了批判性评估。
