Donatelli M, Magarey R D, Bregaglio S, Willocquet L, Whish J P M, Savary S
CREA - Council for Agricultural Research and Economics, Research Center for Agriculture and Environment, via di Corticella 133, I-40128, Bologna, Italy.
Center for Integrated Pest Management, North Carolina State University, Raleigh, NC 27606, USA.
Agric Syst. 2017 Jul;155:213-224. doi: 10.1016/j.agsy.2017.01.019.
The improvement and application of pest and disease models to analyse and predict yield losses including those due to climate change is still a challenge for the scientific community. Applied modelling of crop diseases and pests has mostly targeted the development of support capabilities to schedule scouting or pesticide applications. There is a need for research to both broaden the scope and evaluate the capabilities of pest and disease models. Key research questions not only involve the assessment of the potential effects of climate change on known pathosystems, but also on new pathogens which could alter the (still incompletely documented) impacts of pests and diseases on agricultural systems. Yield loss data collected in various current environments may no longer represent a adequate reference to develop tactical, decision-oriented, models for plant diseases and pests and their impacts, because of the ongoing changes in climate patterns. Process-based agricultural simulation modelling, on the other hand, appears to represent a viable methodology to estimate the impacts of these potential effects. A new generation of tools based on state-of-the-art knowledge and technologies is needed to allow systems analysis including key processes and their dynamics over appropriate suitable range of environmental variables. This paper offers a brief overview of the current state of development in coupling pest and disease models to crop models, and discusses technical and scientific challenges. We propose a five-stage roadmap to improve the simulation of the impacts caused by plant diseases and pests; i) improve the quality and availability of data for model inputs; ii) improve the quality and availability of data for model evaluation; iii) improve the integration with crop models; iv) improve the processes for model evaluation; and v) develop a community of plant pest and disease modelers.
病虫害模型的改进与应用,以分析和预测产量损失,包括气候变化导致的损失,对科学界来说仍是一项挑战。作物病虫害的应用建模主要致力于开发支持能力,以安排巡查或农药施用。需要开展研究,以拓宽病虫害模型的范围并评估其能力。关键研究问题不仅涉及评估气候变化对已知病原系统的潜在影响,还涉及对可能改变病虫害对农业系统影响(仍记录不完整)的新病原体的评估。由于气候模式不断变化,在当前各种环境中收集的产量损失数据可能不再足以作为开发针对植物病虫害及其影响的战术性、面向决策的模型的参考。另一方面,基于过程的农业模拟建模似乎是估计这些潜在影响的可行方法。需要新一代基于最新知识和技术的工具,以实现系统分析,包括关键过程及其在适当环境变量范围内的动态变化。本文简要概述了将病虫害模型与作物模型耦合的当前发展状况,并讨论了技术和科学挑战。我们提出了一个五阶段路线图,以改进对植物病虫害造成的影响的模拟;i)提高模型输入数据的质量和可用性;ii)提高模型评估数据的质量和可用性;iii)改进与作物模型的整合;iv)改进模型评估过程;v)建立植物病虫害建模者群体。