Literature DB >> 32584156

Epidemiological Criteria to Support Breeding Tactics Against the Emerging, High-Consequence Wheat Blast Disease.

M Fernández-Campos1, C Góngora-Canul1, S Das2, M R Kabir3, B Valent4, C D Cruz1.   

Abstract

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 (R2 = 0.70-0.96) fit the disease progress curve in all cultivars followed by Gompertz (R2 = 0.64-0.94), providing additional evidence of a polycyclic disease. Total area under disease progress curve (tAUDPC), final disease severity (Ymax), and logistic apparent infection rates (rL*) 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, Ymax, and rL* 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.

Entities:  

Keywords:  breeding; epidemiology; modeling; resistance; wheat blast

Year:  2020        PMID: 32584156     DOI: 10.1094/PDIS-12-19-2672-RE

Source DB:  PubMed          Journal:  Plant Dis        ISSN: 0191-2917            Impact factor:   4.438


  2 in total

1.  Studies of Evaluation Methods for Resistance to Fusarium Wilt Race 4 (Fusarium oxysporum f. sp. vasinfectum) in Cotton: Effects of Cultivar, Planting Date, and Inoculum Density on Disease Progression.

Authors:  Jinfa Zhang; Abdelraheem Abdelraheem; Yi Zhu; Heather Elkins-Arce; Jane Dever; Derek Whitelock; Kater Hake; Tom Wedegaertner; Terry A Wheeler
Journal:  Front Plant Sci       Date:  2022-06-13       Impact factor: 6.627

2.  Wheat Spike Blast Image Classification Using Deep Convolutional Neural Networks.

Authors:  Mariela Fernández-Campos; Yu-Ting Huang; Mohammad R Jahanshahi; Tao Wang; Jian Jin; Darcy E P Telenko; Carlos Góngora-Canul; C D Cruz
Journal:  Front Plant Sci       Date:  2021-06-17       Impact factor: 5.753

  2 in total

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