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Barley yellow dwarf disease risk assessment based on Bayesian modelling of aphid population dynamics

机译:基于蚜虫种群动态的贝叶斯模型的大麦黄矮病风险评估

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摘要

A stochastic population dynamics model is proposed to improve integrated pest management strategies against the aphid Rhopalosiphum padi, the main Barley yellow dwarf virus (BYDV) vector in winter cereals during autumn in Europe. The model is based on a temperature-dependent simulation of R. padi population dynamics. The model requires a single early assessment of the proportion of plants infested by aphids. To account for sampling errors and for uncertainty caused by the numerous factors acting on aphid population dynamics under field conditions, Bayesian statistical inference was used. The model allows assessment of the probability distribution of the area under the curve of the percentage of plants infested by R. padi during autumn, a predictor of the need for insecticide sprays against BYDV vectors. The accuracy of model predictions was tested on an independent data set collected from 1995 to 1998 in the main French small grain production areas. The use of this model as a basis for a user-friendly decision support system improving BYDV management is discussed. (C) 2005 Elsevier B.V. All rights reserved.
机译:提出了一种随机种群动态模型,以改善针对欧洲秋冬谷物中主要的大麦黄矮病毒(BYDV)蚜虫Rhoopalosiphum padi的病虫害综合防治策略。该模型基于R. padi种群动态的温度相关模拟。该模型要求对蚜虫侵染的植物比例进行单一的早期评估。为了解决田间条件下采样误差和由影响蚜虫种群动态的众多因素引起的不确定性,使用了贝叶斯统计推断。该模型可以评估在秋季被R. padi侵染的植物所占百分比曲线下面积的概率分布,这是对BYDV载体喷洒杀虫剂的预测指标。 1995年至1998年在法国主要的小谷物产区收集的独立数据集测试了模型预测的准确性。讨论了使用该模型作为改进BYDV管理的用户友好型决策支持系统的基础。 (C)2005 Elsevier B.V.保留所有权利。

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