4.5 Article

A process-based model to simulate sugarcane orange rust severity from weather data in Southern Brazil

期刊

INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
卷 65, 期 12, 页码 2037-2051

出版社

SPRINGER
DOI: 10.1007/s00484-021-02162-5

关键词

Puccinia kuehnii; Disease modeling; Process-based model; Severity index; Disease forecasting

资金

  1. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior-Brasil (CAPES) [001]
  2. Conselho Nacional de Desenvolvimento Cientifico e Tecnologico-Brasil (CNPQ) [141291/2017-6]
  3. AgriDigit-Agromodelli project - Italian Ministry of Agricultural, Food and Forestry Policies and Tourism [36502]
  4. MatHiLDE (Modelling pests and diseases impact on hazelnut production) project - Luxembourg National Research Fund-Industrial Fellowships (2019-1 call)

向作者/读者索取更多资源

Forecasting the severity of plant diseases is crucial for farmers and companies to optimize management actions and predict crop yields. A new simulation model called ARISE was developed to formalize the key phases of the life cycle of Puccinia kuenhii, the causal agent of orange rust on sugarcane, and it performed well in calibration and evaluation, accurately matching observations of orange rust severity. Further improvements will involve coupling ARISE with a sugarcane growth model to assess yield losses and develop a decision support system for sugarcane growers.
Forecasting the severity of plant diseases is an emerging need for farmers and companies to optimize management actions and to predict crop yields. Process-based models are viable tools for this purpose, thanks to their capability to reproduce pathogen epidemiological processes as a function of the variability of agro-environmental conditions. We formalized the key phases of the life cycle of Puccinia kuenhii (W. Kruger) EJ Butler, the causal agent of orange rust on sugarcane, into a new simulation model, called ARISE (Orange Rust Intensity Index). ARISE is composed of generic models of epidemiological processes modulated by partial components of host resistance and was parameterized according to P. kuenhii hydro-thermal requirements. After calibration and evaluation with field data, ARISE was executed on sugarcane areas in Brazil, India and Australia to assess the pathogen suitability in different environments. ARISE performed well in calibration and evaluation, where it accurately matched observations of orange rust severity. It also reproduced a large spatial and temporal variability in simulated areas, confirming that the pathogen suitability is strictly dependent on warm temperatures and high relative air humidity. Further improvements will entail coupling ARISE with a sugarcane growth model to assess yield losses, while further testing the model with field data, using input weather data at a finer resolution to develop a decision support system for sugarcane growers.

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