Weather-based predictive modeling of orange rust of sugarcane in Florida

Chaulagain Bhim, Small Ian M., Shine James M., Fraisse Clyde W., Raid Richard Neil, Rott Philippe. 2020. Weather-based predictive modeling of orange rust of sugarcane in Florida. Phytopathology, 110 (3) : 626-632.

Quartile : Q1, Sujet : PLANT SCIENCES

Liste HCERES des revues (en SHS) : oui

Thème(s) HCERES des revues (en SHS) : Psychologie-éthologie-ergonomie

Résumé : Epidemics of sugarcane orange rust (caused by Puccinia kuehnii) in Florida are largely influenced by prevailing weather conditions. In this study, we attempted to model the relationship between weather conditions and rust epidemics as a first step toward development of a decision aid for disease management. For this purpose, rust severity data were collected from 2014 through 2016 at the Everglades Research and Education Center, Belle Glade, Florida, by recording percentage of rust-affected area of the top visible dewlap leaf every 2 weeks from three orange rust susceptible cultivars. Hourly weather data for 10- to 40-day periods prior to each orange rust assessment were evaluated as potential predictors of rust severity under field conditions. Correlation and stepwise regression analyses resulted in the identification of nighttime (8 PM to 8 AM) accumulation of hours with average temperature 20 to 22°C as a key predictor explaining orange rust severity. The five best regression models for a 30-day period prior to disease assessment explained 65.3 to 76.2% of variation of orange rust severity. Prediction accuracy of these models was tested using a case control approach with disease observations collected in 2017 and 2018. Based on receiver operator characteristic curve analysis of these two seasons of test data, a single-variable model with the nighttime temperature predictor mentioned above gave the highest prediction accuracy of disease severity. These models have potential for use in quantitative risk assessment of sugarcane rust epidemics.

Mots-clés Agrovoc : Pucciniales, Saccharum officinarum, épidémiologie, conditions météorologiques, modèle de simulation, écologie, mycologie, Puccinia kuehnii

Mots-clés géographiques Agrovoc : Floride

Mots-clés libres : Ecology, Epidemiology, Mycology

Classification Agris : H20 - Maladies des plantes
P40 - Météorologie et climatologie

Champ stratégique Cirad : CTS 4 (2019-) - Santé des plantes, des animaux et des écosystèmes

Auteurs et affiliations

• Chaulagain Bhim, University of Florida (USA)
• Small Ian M., University of Florida (USA)
• Shine James M., Sugar Cane Growers Cooperative of Florida (USA)
• Fraisse Clyde W., University of Florida (USA)
• Raid Richard Neil, University of Florida (USA)
• Rott Philippe, CIRAD-BIOS-UMR BGPI (FRA) ORCID: 0000-0001-6085-6159 - auteur correspondant

Source : Cirad-Agritrop (https://agritrop.cirad.fr/595214/)

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