Open AccessEpidemiological Criteria to Support Breeding Tactics Against the Emerging, High-Consequence Wheat Blast Disease
Author(s) -
Mariela Fernández-Campos,
Carlos GóngoraCanul,
Saikat Das,
Muhammad Rezaul Kabir,
Barbara Valent,
C. D. Cruz
Publication year - 2020
Publication title -
plant disease
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.663
H-Index - 108
eISSN - 1943-7692
pISSN - 0191-2917
DOI - 10.1094/pdis-12-19-2672-re
Subject(s) - cultivar , biology , epidemiology , gompertz function , selection (genetic algorithm) , plant disease resistance , microbiology and biotechnology , disease , resistance (ecology) , agronomy , veterinary medicine , statistics , mathematics , medicine , genetics , computer science , pathology , artificial intelligence , gene
Plant disease epidemiology can make a significant contribution for cultivar selection by elucidating the principles of an epidemic under different levels of resistance. For emerging diseases as wheat blast (WB), epidemiological parameters can provide support for better selection of genetic resources. Field experiments were conducted at two locations in Bolivia in 2018–2019 to characterize the temporal dynamics of the disease on 10 cultivars with different levels of reaction to WB. Logistic models best (R 2 = 0.70–0.96) fit the disease progress curve in all cultivars followed by Gompertz (R 2 = 0.64–0.94), providing additional evidence of a polycyclic disease. Total area under disease progress curve (tAUDPC), final disease severity (Y max ), and logistic apparent infection rates (r L* ) were shown to be appropriate epidemiological parameters for describing resistance and cultivar selection. Cultivars that showed a high spike AUDPC (sAUDPC) showed a high leaf AUDPC (lAUDPC). tAUPDC, Y max , and r L* were positively correlated among them (P < 0.01) and all were negatively correlated with grain weight (P < 0.01). Based on the epidemiological parameters used, cultivars that showed resistance to WB were Urubó, San Pablo, and AN-120, which were previously reported to have effective resistance against the disease under field conditions. The information generated could help breeding programs to make technical decisions about relevant epidemiological parameters to consider prior to cultivar release.