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Potentials and Limitations of Existing Forecasting Models for Alternaria on Potatoes: Challenges for Model Improvement

机译:马铃薯alteraria现有预测模型的潜力和限制:模型改进的挑战

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摘要

Alternaria species, including A. solani and A. alternata, are a serious threat to potato cultivation and cause necrotic leaf spots, leading to premature defoliation and yield losses. To reduce the impact of the disease, a timely prediction of a disease outbreak is important. Worldwide, modelling attempts have been made to predict the occurrence of Alternaria in order to take adequate measures. In the present paper, we made an effort to classify the existing prediction models and subdivided them into three categories: plant-based, pathogen-based and plant-pathogen-based models. Plant-based models predict the susceptibility of the host crop and presume that Alternaria inoculum is abundantly present and not the restrictive factor, whereas pathogen-based models consider one or more stages of the Alternaria life cycle and suppose that the host crop is always susceptible. The plant-pathogen-based models try to take into account the complete plant-pathogen-environment relationship. In this paper, a critical review of the described models for Alternaria leaf spot is presented. To illustrate the discrepancy between the predicted and the observed dates of the first Alternaria symptoms or the discrepancy between the suggested first treatment and necessity to treat Alternaria, the existing models were subjected to the Belgian weather conditions. It turns out that these models are not applicable in Belgium or similar regions. This can be partially attributed to the fact that most of the currently available models are too simplistic (only plant- or pathogen-based) for regions where the disease pressure highly fluctuates between growing seasons and between locations within one season. Finally, perspectives for model improvement are given taking into account both plant, pathogen and environment.
机译:链格孢菌(Alternaria)是一种严重威胁马铃薯栽培的物种,包括茄果链格孢菌(A.solani)和互生链格孢菌(A.alternata),会引起坏死叶斑,导致过早落叶和产量损失。为了减少疾病的影响,及时预测疾病暴发很重要。在世界范围内,为了采取适当的措施,已经进行了建模尝试来预测链格孢菌的发生。在本文中,我们对现有的预测模型进行了分类,并将其分为三类:基于植物的、基于病原体的和基于植物病原体的模型。基于植物的模型预测寄主作物的易感性,并假定Alternaria inoculum大量存在而不是限制性因素,而基于病原体的模型考虑了一个或多个阶段的链格孢的生命周期,并假设宿主作物总是易感的。基于植物病原的模型试图考虑完整的植物病原-环境关系。本文对链格孢菌叶斑病的描述模型进行了评述。为了说明首次链格孢菌症状的预测日期和观察日期之间的差异,或建议的首次治疗和治疗链格孢菌的必要性之间的差异,现有模型受到比利时天气条件的影响。事实证明,这些模型不适用于比利时或类似地区。这在一定程度上可以归因于这样一个事实,即对于疾病压力在生长季节之间和一个季节内的不同地点之间高度波动的地区,目前大多数可用的模型过于简单(仅基于植物或病原体)。最后,从植物、病原体和环境三个方面对模型的改进进行了展望。

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