Surveillance of wheat rust pathogens, including assessments of rust incidence and virulence characterization via either trap plots or race (pathotype) surveys, has provided information fundamental in formulating and adopting appropriate national and international policies, investments and strategies in plant protection, plant breeding, seed systems, and in rust pathogen research. Despite many successes from national and regional co-ordination of rust surveillance, few attempts were made to extend rust surveillance to international or even global levels. The Global Cereal Rust Monitoring System was established to address this deficiency. It is underpinned by an information platform that includes standardized protocols for methods and systems used in surveys, preliminary virulence testing, data, sample transmission and management at the field and national and global levels, and includes two web-based visualization tools. While considerable progress has been made towards a global system for monitoring variability in the wheat stem rust pathogen, and linking this to the threat posed by this pathogen to regional wheat production, some challenges remain, including ongoing commitment to support rust surveillance, and the ability to share and compare surveillance data.
When evaluating genotypes, it is efficient and resourceful to identify similar testing sites and group them according to similarity. Grouping sites ensures that breeders choose as many variable sites as possible to capture the effects of genotype-by-environment (GE) interactions. In order to exploit these interactions and increase testing efficiency and variety selection, it is necessary to group similar environments or mega-environments. The present megaenvironments in the Southern African Development Community (SADC) countries are confounded within each country, which limits the exchange of germplasm among them. The objective of this study was to revise and group similar maize-testing sites across the SADC countries that are not confounded within each country. The study was based on 3 years (1999-2001) of regional maize yield trial data and geographical information systems (GIS) parameters from 94 sites. Sequential retrospective (Seqret) pattern analysis methodology was used to stratify testing sites and group them according to their similarity and dissimilarity based on mean grain yield. The methodology used historical data, taking into account imbalances of data caused by changes over locations and years, such as additions and omission of genotypes and locations. Cluster analysis grouped regional trial sites into seven megaenvironments, mainly distinguished by GIS parameters related to rainfall, temperature, soil pH, and soil nitrogen with an overall R 2 = 0.70. This analysis provides a challenge and an opportunity to develop and deploy maize germplasm in the SADC region faster and more effectively.Abbreviations: SADC, Southern African Development Community; GIS, geographical information systems
Major changes have occurred in the global wheat-rust disease landscape over the last century. At
Crop improvement efforts have benefited greatly from advances in available data, computing technology, and methods for targeting genotypes to environments. These advances support the analysis of genotype by environment interactions (GEI) to understand how well a genotype adapts to environmental conditions. This paper reviews the use of spatial analysis to support crop improvement research aimed at matching genotypes to their most appropriate environmental niches. Better data sets are now available on soils, weather and climate, elevation, vegetation, crop distribution, and local conditions where genotypes are tested in experimental trial sites. The improved data are now combined with spatial analysis methods to compare environmental conditions across sites, create agro-ecological region maps, and assess environment change. Climate, elevation, and vegetation data sets are now widely available, supporting analyses that were much more difficult even 5 or 10 years ago. While detailed soil data for many parts of the world remains difficult to acquire for crop improvement studies, new advances in digital soil mapping are likely to improve our capacity. Site analysis and matching and regional targeting methods have advanced in parallel to data and technology improvements. All these developments have increased our capacity to link genotype to phenotype and point to a vast potential to improve crop adaptation efforts.
Crops are variously susceptible to biotic stresses-something expected to increase under climate change. In the case of staple crops, this potentially undermines household and national food security. We examine recent wheat rust epidemics and smallholders' coping mechanisms in Ethiopia as a case study. Wheat is a major food crop in Ethiopia widely grown by smallholders. In 2010/11 a yellow rust epidemic affected over one-third of the national wheat area. Two waves of nationally representative household level panel data collected for the preceding wheat season (2009/10) and three years after (2013/14) the occurrence of the epidemic allow us to analyze the different coping mechanisms farmers used in response. Apart from using fungicides as ex-post coping mechanism, increasing wheat area under yellow rust resistant varieties, increasing diversity of wheat varieties grown, or a combination of these strategies were the main ex-ante coping mechanisms farmers had taken in reducing the potential effects of rust re-occurrence. Large-scale dis-adoption of highly susceptible varieties and replacement with new, rust resistant varieties was observed subsequent to the 2010/11 epidemic. Multinomial logistic regression models were used to identify the key factors associated with smallholder ex-ante coping strategies. Household characteristics, level of specialization in wheat and access to improved wheat seed were the major factors that explained observed choices. There was 29-41% yield advantage in increasing wheat area to the new, resistant varieties even under normal seasons with minimum rust occurrence in the field. Continuous varietal development in responding to emerging new rust races and supporting the deployment of newly released resistant varieties could help smallholders in dealing with rust challenges and maintaining improved yields in the rustprone environments of Ethiopia. Given the global importance of both wheat and yellow rust and climate change dynamics study findings have relevance to other regions.
A wheat rust survey was conducted in Iraq in 2019 and collected 27 stem rust (caused by Puccinia graminis Pers.:Pers. f. sp. tritici Erikks. & E. Henn.) samples. Seven samples were viable, and they were tested for races of P. graminis f. sp. tritici at the Regional Cereal Rust Research Center (RCRRC) in Izmir, Turkey under strict quarantine procedures. Two 0.5 cm segments of each infected stem sheath were incubated in a petri dish at 20°C for three hours for re-hydration of urediniospores, which were multiplied on 10-day old seedlings of susceptible cultivar Morocco grown in a spore free growth chamber at 18°C and 16 hours light. Inoculated seedlings underwent a dew period at 18°C for 16 hours dark and 8 hours fluorescent light and 95% relative humidity. Three days after moving the pots to a growth chamber with eight hours dark at 18°C and 16 hours light (300 µmol m-2s-1), each pot was covered using a cellophane bag. Bulk urediniospores of each collection were collected 14 days post-inoculation from a cellophane bag using a mini cyclone spore collector connected to a gelatin capsule. One ml of 3M Novec™ oil was added to each capsule, and spores were inoculated onto 20 North American stem rust differential lines using the standard procedures (Jin et al. 2008). Pre-inoculation, inoculation, incubation, and post-inoculation conditions were the same as above. Seedling infection types (ITs) were recorded 14 days post-inoculation using 0 to 4 scale (Stakman et al. 1962). Race designation followed the five- letter code nomenclature described by Jin et al. (2008). Out of the seven samples, four were typed as TKKTF, two as TKTTF, and one collected from an advanced breeding bread wheat line “Shahoo 2” (Inqalab 91*2/Tukuru) in a trial site at Halabja governorate showed mixed ITs of 11+ and 3+ for lines carrying Sr11, Sr24, Sr36, and Sr31. Three single pustule (SP) isolates were developed from the IT of 3+ pustules collected from the Sr31 tester line, and one SP isolate was developed from the IT 11+ pustule collected from the Sr11 source. After spore multiplication, the SP-derived isolates were inoculated on the 20 North American differential lines. To confirm virulence/avirulence on Sr24, Sr31, and Sr36, cultivars Siouxland (PI 483469, Sr24+Sr31) and Sisson (PI 617053, Sr36+Sr31) were also inoculated. All seedling assays were repeated three times. The three SP isolates virulent on Sr31 were designated as race TTKTT, and the SP isolate virulent on Sr11 was designated as TKTTF. Seedling ITs of 3+ and 0; were recorded for Siouxland and Sisson against TTKTT, respectively, and both cultivars showed IT of 1+ against TKTTF. Race TKTTF was similar to TKKTF except for additional virulence on Sr36, and TTKTT differed from the other two races being virulent on Sr24 and Sr31. DNA analysis of three TTKTT isolates from Kenya and the TTKTT isolate from Iraq using a diagnostic qPCR assay developed by the USDA-ARS Cereals Disease Laboratory (Ug99 RG stage 1, Szabo unpublished) confirmed that all tested isolates belonged to the Ug99 lineage. Race TTKTT was first reported from Kenya in 2014 (Patpour et al. 2016), and in 2018 from Ethiopia (Hei et al. 2020). We report the first detection of TTKTT in Iraq and the Middle East region. This represents only the third instance of a member of the Ug99 race group outside of Africa since first detection of race TTKSK in Yemen in 2006, and Iran in 2007 (Nazari et al. 2009). The continued spread of stem rust races with complex virulence and the increasing frequency and early onset of stem rust infections in the Middle East is a cause for concern. Continuous support for rust surveillance and race typing in this region remains crucial. References: Hei, N. B., et al. 2020. Plant Dis. 104:982. Jin, Y., et al. 2008. Plant Dis. 92:923-926. Nazari, K., et al. 2009. Plant Dis. 93:317. Patpour, M., et al. 2016. Plant Dis. 100:522. Stakman, E. C., et al. 1962. Identification of physiological races of Puccinia graminis var. tritici. U. S. Dep. Agric. ARS E-617.
The migration of Ug99 variants of Puccinia graminis f. sp. tritici is of concern to global wheat production (1). Seven races have been characterized in the Ug99 lineage (3), three of which occur in South Africa (4). During surveys of wheat fields for Ug99 in Zimbabwe and Mozambique in August and September 2010, high stem rust severities were found at Chiredzi, Chisumbanje, and Birchenough in Zimbabwe and at Rotanda in Mozambique. Stem rust was widespread in the lowlands (<800 m above sea level) of Zimbabwe and trace amounts were present in the mid-altitude areas. In Mozambique, stem rust was only observed at Rotanda (sample Moz1001). Collections from Chiredzi (samples Zim1004 and Zim1005), Chisumbanje (Zim1006), and Birchenough (Zim1009 and Zim1010) yielded viable urediniospores for infection studies. According to race analysis conducted on seedlings of the North American stem rust differential set (2) in a greenhouse at 18 to 25°C, Zim1005 and Zim1006 were typed as PTKST and Zim1004 and Zim1009 as TTKSF. Both TTKSF and PTKST were detected in the Zim1010 sample. Race analysis experiments were conducted three times. Urediniospores of isolate Moz1001 were not viable in infection studies, but yielded fungal DNA for simple sequence repeat (SSR) analysis. Using eight selected SSR primer combinations (4), all six isolates clustered within the Ug99 lineage. Isolates Zim1005, Zim1006, Zim1009, Zim1010, and Moz1001 and the stem rust control races TTKSF, TTKSK, and PTKST grouped into two main clusters, with Zim1009 and Zim1010 clustering together and sharing 88% similarity with the rest of the isolates. Zim1005 and Zim1006 were identical to TTKSF and TTKSK, respectively. Zim1004 shared 96% genetic similarity with the TTKSP control, with these two sharing 74% genetic similarity with the remaining isolates. The SSR data correlated with the infection data, except for Zim1004, which was typed as TTKSF but clustered close to TTKSP. Wheat cvs. SC Nduna, SC Shine, SC Stallion, SC Smart, Kana, Insiza, and Dande are predominant in Zimbabwe. Cv. SC Stallion and other unidentified cultivars were susceptible to P. graminis f. sp. tritici in the field in Zimbabwe. In Mozambique, the tall, local cv. Sitsonko was susceptible to P. graminis f. sp. tritici but no infections were observed on SC Nduna or SC Shine. The similarity in P. graminis f. sp. tritici races in Zimbabwe, South Africa, and Mozambique suggests that inoculum is exchanged within the region and explains the detection of race PTKST in South Africa in 2009. Trajectory models showed winds originating at Birchenough in October 2009, where stem rust was observed, passing directly over KwaZulu-Natal, South Africa within 48 to 72 h. Race PTKST was confirmed from collections in KwaZulu-Natal in November 2009 (4). The confirmation of Sr31 virulence in race PTKST in Zimbabwe is important because it provides new geographical records for an Ug99-related race and puts Southern African cultivars with 1B.1R resistance at risk. References: (1) D. Hodson. Euphytica 179:93, 2011. (2) Y. Jin et al. Plant Dis. 92:923, 2008. (3) R. F. Park et al. Euphytica 179:109, 2011. (4) B. Visser et al. Euphytica 179:119, 2011.
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