First Report of the Ug99 Race Group of Wheat Stem Rust, <i>Puccinia graminis</i> f. sp. <i>tritici</i>, in Egypt in 2014

Patpour, Mehran; Hovmøller, Mogens S.; Shahin, Atef A.; Newcomb, Maria; Olivera, Pablo D.; Jin, Yue; Luster, Douglas G.; Hodson, David; Nazari, K.; Azab, Mohamed

doi:10.1094/pdis-08-15-0938-pdn

Cited by 44 publications

(30 citation statements)

References 3 publications

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“…Digalu in Ethiopia. Race TTKTK was also detected in Egypt, Rwanda and Uganda in 2014 [26] , indicating its rapid and possibly widespread dispersal. No new Ug99 variants have been identified since 2015, However, Terefe et al [28] reported the first occurrence of Ug99 race PTKSK in South Africa in 2017, that was previously identified in Ethiopia, Kenya and Yemen.…”

Section: Status Of Ug99 Race Groupmentioning

confidence: 99%

“…New races have continued to emerge and, by 2019, 13 had been identified (Table 1), all within the same 13 countries. Similarly, in 2014, five new variants of Ug99 were detected in Kenya [23,26,27] . Two of these, TTKTK and TTKTT, were highly significant because they had acquired virulence to stem rust gene SrTmp, a key resistance gene in popular eastern African bread wheat cultivars such as cv.…”

Section: Status Of Ug99 Race Groupmentioning

confidence: 99%

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Progress in breeding for resistance to Ug99 and other races of the stem rust fungus in CIMMYT wheat germplasm

Bhavani¹,

Hodson²,

Espino³

et al. 2019

Front. Agr. Sci. Eng.

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Section: Status Of Ug99 Race Groupmentioning

confidence: 99%

Section: Status Of Ug99 Race Groupmentioning

confidence: 99%

Progress in breeding for resistance to Ug99 and other races of the stem rust fungus in CIMMYT wheat germplasm

Bhavani¹,

Hodson²,

Espino³

et al. 2019

Front. Agr. Sci. Eng.

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“…Here, we use the term 'pest' to describe any herbivorous arthropod, pathogenic microbe or virus known to attack agricultural crops. Recently, for example, sub-Saharan Africa has suffered from the virulent Ug99 strain of the wheat stem rust fungus (Puccinia graminis tritici ;Patpour et al, 2015), the newly evolved maize lethal necrosis viral syndrome (Wangai et al, 2012), arrival of the Asian citrus psyllid (Diaphorina citri) which vectors citrus greening disease (Shimwela et al, 2016) and the appearance of Tropical Race 4 of Fusarium oxysporum f. sp. Recently, for example, sub-Saharan Africa has suffered from the virulent Ug99 strain of the wheat stem rust fungus (Puccinia graminis tritici ;Patpour et al, 2015), the newly evolved maize lethal necrosis viral syndrome (Wangai et al, 2012), arrival of the Asian citrus psyllid (Diaphorina citri) which vectors citrus greening disease (Shimwela et al, 2016) and the appearance of Tropical Race 4 of Fusarium oxysporum f. sp.…”

Section: Introductionmentioning

confidence: 99%

Many unreported crop pests and pathogens are probably already present

Bebber

Field

Gui

et al. 2019

Global Change Biology

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Invasive species threaten global biodiversity, food security and ecosystem function.Such incursions present challenges to agriculture where invasive species cause significant crop damage and require major economic investment to control production losses. Pest risk analysis (PRA) is key to prioritize agricultural biosecurity efforts, but is hampered by incomplete knowledge of current crop pest and pathogen distributions. Here, we develop predictive models of current pest distributions and test these models using new observations at subnational resolution. We apply generalized linear models (GLM) to estimate presence probabilities for 1,739 crop pests in the CABI pest distribution database. We test model predictions for 100 unobserved pest occurrences in the People's Republic of China (PRC), against observations of these pests abstracted from the Chinese literature. This resource has hitherto been omitted from databases on global pest distributions. Finally, we predict occurrences of all unobserved pests globally. Presence probability increases with host presence, presence in neighbouring regions, per capita GDP and global prevalence. Presence probability decreases with mean distance from coast and known host number per pest. The models are good predictors of pest presence in provinces of the PRC, with area under the ROC curve (AUC) values of 0.75-0.76. Large numbers of currently unobserved, but probably present pests (defined here as unreported pests with a predicted presence probability >0.75), are predicted in China, India, southern Brazil and some countries of the former USSR. We show that GLMs can predict presences of pseudoabsent pests at subnational resolution. The Chinese literature has been largely inaccessible to Western academia but contains important information that can support PRA. Prior studies have often assumed that unreported pests in a global distribution database represent a true absence. Our analysis provides a method for quantifying pseudoabsences to enable improved PRA and species distribution modelling. K E Y W O R D S agriculture, biogeography, food security, invasive species, observational bias, pest risk analysis, species distribution model

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“…Emerging CPPs can be extremely damaging to agricultural production and 45 the economy, through both pre-harvest and post-harvest losses (Bebber & Gurr, 2015;Paini et al, 2016;46 Savary et al, 2017). Recently, for example, sub-Saharan Africa has suffered from the virulent Ug99 47 strain of the wheat stem rust fungus (Puccinia graminis tritici) (Patpour et al, 2015), the newly-evolved 48…”

Section: Introduction 39mentioning

confidence: 99%

Many unreported crop pests and pathogens are probably already present

Bebber

Field

Gui

et al. 2019

Preprint

View full text Add to dashboard Cite

Invasive species threaten global biodiversity, food security and ecosystem function. Such incursions present challenges to agriculture where invasive species cause significant crop damage and require major economic investment to control production losses. Pest risk analysis (PRA) is key to prioritize agricultural biosecurity efforts, but is hampered by incomplete knowledge of current crop pest and pathogen distributions. Here, we develop predictive models of current pest distributions and test these models using new observations at subnational resolution. We apply generalized linear models (GLM) to estimate presence probabilities for 1,739 crop pests in the CABI pest distribution database. We test model predictions for 100 unobserved pest occurrences in the People's Republic of China (PRC), against observations of these pests abstracted from the Chinese literature. This resource has hitherto been omitted from databases on global pest distributions. Finally, we predict occurrences of all unobserved pests globally. Presence probability increases with host presence, presence in neighbouring regions, per capita GDP and global prevalence. Presence probability decreases with mean distance from coast and known host number per pest. The models are good predictors of pest presence in provinces of the PRC, with area under the ROC curve (AUC) values of 0.75–0.76. Large numbers of currently unobserved, but probably present pests (defined here as unreported pests with a predicted presence probability >0.75), are predicted in China, India, southern Brazil and some countries of the former USSR. We show that GLMs can predict presences of pseudoabsent pests at subnational resolution. The Chinese literature has been largely inaccessible to Western academia but contains important information that can support PRA. Prior studies have often assumed that unreported pests in a global distribution database represent a true absence. Our analysis provides a method for quantifying pseudoabsences to enable improved PRA and species distribution modelling.

show abstract

First Report of the Ug99 Race Group of Wheat Stem Rust, Puccinia graminis f. sp. tritici, in Egypt in 2014

Cited by 44 publications

References 3 publications

Progress in breeding for resistance to Ug99 and other races of the stem rust fungus in CIMMYT wheat germplasm

Progress in breeding for resistance to Ug99 and other races of the stem rust fungus in CIMMYT wheat germplasm

Many unreported crop pests and pathogens are probably already present

Many unreported crop pests and pathogens are probably already present

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