Journal of Plant Pathology & Microbiology

Identification of Stripe Rust (Puccinia striiformis F. sp. Tritici) Resistance in the Ethiopian Wheat Landraces

Fikrte Yirga^1* and Ayele Badebo^{2 1}Ethiopian Institute of Agricultural Research (EIAR), Addis Ababa, Ethiopia
²CMMIYT-Ethiopia, ILRI Campus, Addis Ababa, Ethiopia
^*Correspondence: Fikrte Yirga, Ethiopian Institute of Agricultural Research (EIAR), Addis Ababa, Ethiopia, Tel: +251-9-2113-0322, Email:

Received: 16-Jun-2021 Published: 30-Jul-2021, DOI: 10.35248/2157-7471.21.12.566

Introduction

Ethiopia is the largest wheat producers in Sub-Saharan Africa (SSA). The crop ranks fourth in area coverage next to tef, maize and sorghum, respectively [1]. The area under wheat production is estimated to be about 1.7 million hectares of land with average productivity of 2.7 tons/ha. Wheat production is constrained by several biotic, a biotic and socio-economic factor in the country. The Ethiopian highlands are suitable for the wheat plant as well as for perpetuations wheat rust diseases [2]. Stripe rust caused by P. striiformis f. sp. tritici. Westend (Pst) is the most threatening wheat disease in the highlands of Ethiopia [1]. The disease was first reported in the early 1940’s, but it gained importance with the commercialization of wheat in the early 1980s [3]. Recurrent stripe rust epidemics have occurred since then; however, the 2010 epidemics was the most damaging. Most of the commercial bread wheat cultivars, including Kubsa and Galama scummbed to the new Yr27+ virulent race and caused 70 to 100% yield loss in major wheat producing areas of the country [4].

In the depletion of rust resistance in commercial cultivars, new sources often sought from landraces and close relatives of wheat. Landraces are grown by farm communities in remote villages using centuries’- old technologies, including hand planting and harvesting [5]. The main reasons for farmers to maintain these historic wheat landraces could be due to their specific adaptability and preferred quality for home use. Wheat landraces contribute important traits including disease resistance [6], tolerance to a biotic stresses [7], and protein content and gluten quality [8]. Wheat landraces have been successfully used by wheat breeders to improve agronomic traits, particularly disease and pest resistance [9]. Such genetic resources have been successfully used by plant breeders to improve agronomic traits, particularly disease and pest résistance. Landraces of wheat have resulted from selection within field populations by traditional agriculturists. Because they are agronomically adapted to field conditions, landraces may be more easily utilized as sources of novel genes or gene combinations than wild relatives [10]. Tetraploid and hexaploid wheat landraces have been evaluated to a limited extent for their potential use in modern plant breeding for disease resistance and landraces collections in general show a much higher level of genetic diversity than elite varieties.

In Ethiopia, a large number of wheat genotypes have been preserved in the Institute of Biodiversity Conservation (IBC), which could potentially serve as sources to stripe rust resistance. In this study a set of Ethiopian wheat landraces from IBCE have been characterized for their resistance to the prevailing Pst races under field and greenhouse conditions.

Materials and Methods

Description of the study area

The field study was conducted at Kulumsa and Meraro research stations in Arsi Zone of Oromia Region, Ethiopia. The greenhouse experiment was conducted at Kulumsa Agricultural Research Center. Meraro and Kulumsa are known to be hot spot areas for wheat stripe rust, although the disease pressure increases with altitude. Kulumsa represents mid highlands (2200 m.a.s.l.) and located at 39º 09’11’’E l and 08º 01’10’’N. It has average maximum 22.8ºC and minimum 10.5ºC temperatures and receives 832 mm rainfall annually. Meraro represents extreme highlands (2960 m.a.s.l.) and located at 39º 14’56’’E and 07º 24' 27’’N. Meraro receives 1196 mm annual rainfall with maximum and minimum temperatures of 18.1ºC and 5.7ºC, respectively.

Planting materials

A total of 197 bread wheat landrace accessions plus 3 checks were used in this study. The accessions and checks were obtained from the institute of biodiversity of Ethiopia (IBCE) and the wheat breeding program at Kulumsa research center, respectively. In 2017, all of the accessions were tested under field conditions whereas only selected entries were exposed to the prevailing races of Pst in the field and greenhouse during 2018.

Field experimental design and testing procedures

The experiment was laid out in augmented design where the three check varieties; Digelu (susceptible), Pavon-76 (moderately resistant) and Enkoy (resistant) were replicated in each block. Each plot consisted of 2 rows of 1 m length with 20 cm between rows. To ensure uniform spread of inoculum and sufficient disease development, infector plants consisted of mixtures of different susceptible bread wheat varieties (Morocco, Digelu and Kubsa) bordered the plots in all direction. Fertilizer application and other agronomic practices were applied according to the recommendations for each location.

Field disease assessments

Different epidemiological parameters which include terminal rust severity (TRS), coefficient of infection (CI), area under disease progress curve (AUDPC) and disease progress rate (DPR) were used to determine stripe rust resistance in the wheat landraces.

Disease sverity

Disease severity notes were taken five times on plot bases starting from the onset of rust within 10 days intervals. Stripe rust severity was estimated visually as a proportion leaf area affected by stripe rust using the modified Cobb’sscale [11] and the host plant response (infection type) was noted according to Peterson, et al. [12]. The CI was calculated by multiplying the level of disease severity and the constant value of infection type. The constant values for infection types were used based on; R = 0.2, MR = 0.4, M= 0.6, MS = 0.8, S = 1 [11]. Head infection was noted using 0-5 scale and then converted to percentages for analysis: 0 = no infection, 1 = 20%, 3 = 60%, 4 = 80% and 5 = 100% severity.

Area under Disease Progress Curve (AUDPC)

AUDPC is an indicator of disease expression over time [13], and it was calculated for each experimental unit according to Wilcoxson, et al. [14]:

Where,

x_i = The average coefficient of infection of i^th record

x_i+1 = The average coefficient of infection of i+1^th record

t _i+1 - t_i = Number of days between the i^th record

i+1^th record and

n = Number of observations.

Disease Progress Rate (DPR)

Disease progress rate was estimated from the logistic model [12]: ln (Y/ (1-Y)) and Gompertz model: ln [-ln (Y)]; where y = the percent of severity divided by 100; t = time measured in days. In this study, Gompertz model was used for all assessment dates because of the higher values of coefficient of determination (R2) compared to the logistic model.

Field data analysis

Data on different epidemiological parameters were generated for each test material. The data have been transformed using before analysis. A standard analysis of variance was conducted to identify significance differences among the wheat landarces for each disease parameter. Correlation analysis was done among disease parameters and thousand kernel weight (TKW) using Minitab Software . The data were analyzed using SPAD and SPSS software’s [15,16].

Seedling test

One hundred three accessions were selected for seedling resistance tests based on their field performances in 2017. The experiment was conducted according to standard procedures [17] in the greenhouse at Kulumsa research center in 2018. Five to six seeds of each entry plus three checks were grown in 7×7×6 cm plastic pots filled with compost, soil and sand at a ratio of 1:2:1 (v/v/v) in spore-free greenhouse compartment under supplemental light. The first leaves of seven to eight days old seedlings were inoculated with spores of three Pst (PstS2 (v32), PstS11 and PstS11 (v25)) isolates suspended in light weight mineral oil (Soltrol 170) using atomizer. Inoculation was carried in an enclosed cage that was rinsed with water subsequently to avoid spore contamination. Inoculated seedlings were allowed to dry for 20 minutes and then incubated in a dew chamber for about 24 hrs at 9-10ºC with 100% relative humidity. Seedlings were kept in semi open plastic cubicles in a greenhouse compartment at 18-22ºC and 70 to 80% relative humidity. The seedlings were supplemented with 12 hrs light using florescent lamps. The experiment was replicated twice and repeated based on the infection type (IT) on susceptible variety (Morocco). Seedlings were evaluated 16-20 days post-inoculation using a 0-9 scale [18]. Entries with ITs 0-6 were considered as resistant and 7-9 susceptible [19].

Results and Discussion

Terminal rust severity on wheat leaves (TRS)

Stripe rust disease pressure was high in the study areas during 2017 and 2018. The disease severity went up to 100% on susceptible entries across locations and seasons. The landraces exhibited various reactions to stripe rust on wheat leaves and spikes. The disease pressure was more at Meraro (2900 masl) than at Kulumsa (2200 masl). In 2017, the mean severity scores on leaves of resistant, moderately resistant and susceptible checks were, 9.6%, 40% and 78% at Kulumsa and 20%, 59% and 94% at Meraro, respectively whereas the mean severity on spikes for the respective checks were 18%, 82% and 62% at Meraro (Table 1). The frequency distribution of landrace accession under different disease severity (TRS) classes at Kulumsa and Meraro during 2017 is depicted in Figure 1. The frequency of susceptible entries were more at Meraro than at Kulumsa. A total of 97 (49%) landraces at kulumsa and 75 (38.1%) and 97 (49%) at Meraro exhibited low (0-20%) severity on leaves and spikes, respectively whereas 40 (20%) landraces at Kulumsa and 17 (9%) and 14 (7%) at Meraro, respectively had moderate TRS (21-40%. A total of 43 (22%) and 69 (35%) exhibited immune reaction to stripe rust on leaves and spikes, respectively across locations (data not shown).

Table 1: The reaction of selected Ethiopian wheat landraceâ??s to stripe rust at seedling and adult plant growth stages.

Figure 1. Frequency distribution of landraces under different terminal rust severity classes at Kulumsa and Meraro in 2017.

The frequency of landraces under different stripe rust severity classes at Kulumsa and Meraro during 2018 is shown in Figure 2. Of the total 100 (50.8%) landraces, at Kulumsa and 57 (29%) and 89 (45%) at Meraro exhibited low (0-20) TRS on leaves and spikes, respectively.

Figure 2.Frequency distribution of landraces under different terminal stripe rust severity classes at Kulumsa and Meraro in 2018.

On highly infected wheat genotypes, the grains were shriveled and resulted in losses in yield, quality and thousand kernel weights (TKW). This result is consistent with the findings of Purdy LH and Allan RE [20] reported the negative effect of spike infection on yield and yield components. Trace to low levels of spike infection on the moderately resistant and resistant varieties did not affect thousand kernel weights (TKW), yield and yield components. Spike infection of wheat by stripe rust at higher altitudes result in 100% losses [1].

The present study identified considerable variations among the landraces in terminal rust severity (TRS) at both locations and seasons. The higher disease severity level was observed at Meraro compared to Kulumsa. This may be attributed mainly due to more favorable environmental condition. In this study, 100 (50.8%) and 57 (29%) accessions exhibited high level of slow rusting resistance at Kulumsa and Meraro, respectively. Resistance in these landrace accessions might be controlled by several minor genes which give long-lasting resistance.

Area under disease progress curve

The distribution of landraces under AUDPC values across locations in 2017 and 2018 seasons is shown in Figure 3. In 2017, of the total number of landraces, 77 (39%) and 28 (14%) showed lower AUDPC values than the resistant (Enkoy) and moderately resistant (Pavon-76) checks at Kulumsa and 68 (35%) and 37 (19%) at Meraro, respectively.

Figure 3.The distribution of AUDPC values of landraces across locations in 2017 and 2018.

The landrace accession with lower AUDPC values than the resistant check (Enkoy) is considered to possess slow rusting resistance. AUDPC is a good indicator of adult plant resistance under field condition [21]. It is directly related with grain yield loss [22] and provides critical information for designing effective disease management practices for lines with different types and levels of resistance.

Disease Progress Rate (DPR)

The frequency of landraces under different disease progress rate (DPR) classes at Kulumsa and Meraro during 2017 is shown in Figure 4. The DPR values ranged from 0 to 0.187 per unit time at Kulumsa and 0 to 0.159 at Meraro. Of the tested entries, 47 (24%) and 57 (29%) landraces exhibited no disease progress at Kulumsa and Meraro, respectively. However, 47 (24%) and 9 (5%) landraces had lower DPR value per unit time than the resistant check and moderately resistant checks each at Kulumsa and 58 (29%) and 2 (1%) at Meraro, respectively.

Figure 4. The frequency of wheat landraces under different disease progress rate classes at Kulumsa and Meraro, 2017.

Of the total 103 landraces, 23 (12%) and 31 (16%) showed no progress in disease severity in 2018. However, 30 (15%) and 13 (7%) had lower DPR value per unit time than the resistant and moderately resistant checks at Kulumsa and 39 (20%), 9 (5%) at Meraro, respectively (data not shown). Disease progress rate in terms of disease spread was lower in resistant varieties compared to the susceptible ones. In general, a low AUDPC value in an accession might not ensure low in DPR. Once the pathogen reaches its maximum infection level, the DPR value may decrease or remain constant as disease progresses [23]. Ethiopian wheat landrace accessions with low DPR value per unit time could be potential sources to be exploited in breeding program.

Correlation among disease parameters and thousand kernel weight

Highly significant (P<0.001) and positive correlations observed among the disease parameters across locations and seasons (Table 2). There was high correlations between terminal rust severity (TRS) with area under disease progress curve (AUDPC) and disease progress rate (DPR) at Kulumsa (r = 0.986 and 0.969) and Meraro (r = 0.985 and 0.965), respectively. Relatively lower correlations were noted between area under disease progress curve (AUDPC) and disease progress rate (DPR) compared to the other slow rusting parameters at Kulumsa (r = 0.870) and Meraro (r = 0.886). Despite the severity and AUDPC increase, the rate of infection could be slowed down over time because as the epidemics progresses less plant tissue could be available for further infection of the pathogen [24]. The thousand kernel weight (TKW) has negatively correlated at P<0.001 with all the disease parameters at both locations (Table 3).

Table 2: Mean square variance of coefficient of infection, terminal rust severity, area under disease progress curve, disease progress rate and spike infection of stripe rust on Ethiopian wheat landraces at Kulumsa and Meraro, 2017.

Table 3: Pearson linear correlation coefficients among stripe rust disease parameters and thousand kernel weight in Ethiopian wheat landraces at Kulumsa and Meraro in 2017.

Highly significant and positive correlation observed between SI and the major disease parameters; however, the correlation with thousand kernel weight (TKW) was negative. The positive correlations among the disease parameters observed in this study are in agreement with the results of Safavi and Ashfari [25]. In the present study, all disease parameters were highly correlated and affected thousand kernel weight (TKW). Safavi, et al. [26] reported higher selection gains of slow rusting resistance using low terminal rating, area under disease progress curve (AUDPC) and coefficient of infection (CI) under field condition.

Seedling resistance

A total of 103 landrace accession were exposed to the three most virulent stripe rust isolates (YR28WAB16, YR80NWA17andYR39AD17) which were later designated as PstS2 (v32), (PstS11) and PstS11 (v25), respectively. Of these landraces, 79 (77%), 81 (79%) and 71 (69%) showed resistance reaction to PstS2(v32), (PstS11) and (PstS11 v25), respectively (Figure 5). Sixty one (59%) and 11 (11%) landraces showed resistance and susceptible reaction to all of the three isolates, respectively whereas 31 (30%) reacted differently.

Figure 5. Frequency distribution of resistant and susceptible wheat landrace accessions to three stripe rust races at seedling stage.

A total of 103 wheat landraces evaluated at adult plant growth stages and of these, 57 (29%) exhibited lower values for all disease parameters under field conditions. Thirty-two (16%) landraces exhibited resistance at seedling (to all isolates) and adult plant growth stage whereas 14 (7%) showed susceptible/intermediate reaction at seedling stage but had low disease level for all parameters under field conditions.

Wheat genotypes could be susceptible at seedling tests but exhibit moderate resistance to moderate susceptible reaction at adult plant stage and these lines with show slow rusting resistance parameters at adult plant stage could have durable resistance [27]. This kind of resistance can be kept for a long time even if pathogen changes its genotype, it is controlled by more than one gene [28]. Generally, the seedling resistance genes are also active during the adult plant stage and they are classified into race-specific resistance types [29].

Conclusion

Most of the commercial wheat cultivars in Ethiopia succumb to new races of stripe rust in hot spot areas. In the depletion of resistance in the cultivated wheat, new sources are sought from landraces. In this study, a total of 197 wheat landrace accessions (152 bread and 45 durum) obtained from the Ethiopian institute of biodiversity (IBC) have been tested to stripe rust during 2017 and 2018 whereas only selected 103 accessions were exposed to the prevailing Pst races both in the field and at seedling stage in the greenhouse 2018. Overall, 57 accessions exhibited resistance in the field across locations and seasons. Of these, 32 and 9 accessions showed resistant and susceptible reaction to the three PSt races at seedling stage, respectively. This study has shown that Ethiopian wheat landraces are potential sources of overall (seedling) and adult plant resistances (APR) to stripe rust.

Author Contribution

The 2nd authors have been engaged in initiation and supervision of the study. They were also involved in writing of this manuscript.

Funding

This study was funded by the Delivering Genetic Gain in Wheat (DGGW) project in Ethiopia through the Ethiopian Institute of Agricultural Research (EIAR)

Acknowledgements

The first author is grateful to delivering genetic gain in wheat (DGGW) project in Ethiopia for financial support and the Ethiopian Institute of Agricultural Research (EIAR) for facilitations and hosting of the experiment.

Conflict of Interest

No confict of interest to be declared.

REFERENCES

1. Badebo A, Fehrmann H, Yahyaoui A. Status of wheat stripe rust (Puccinia striiformis) races and their virulence in major wheat growing areas of Ethiopia. J Pest Manag. 2008;12:1-7.
2. Hulluka M, Woldeab G, Adnew Y, Desta R, Badebo A. Wheat pathology research in Ethiopia. In: Gebremariam, H., Tanner D.G., and Hulluka, M. (Eds.). Wheat research in Ethiopia: A historical perspective. 1991;173-217.
3. Mariam HG. Bread wheat breeding and genetics research in Ethiopia. 1991.
4. Abeyo B, Hodson D, Hundie B, Woldeab G, Girma B, Badebo A, et al. Cultivating success in Ethiopia: The contrasting stripe rust situations in 2010 and 2013. In: Abstr. BGRI. 2014.
5. Feuillet C, Langridge P, Waugh R. Cereal breeding takes a walk on the wild side. Trends in genetics. 2008;24(1):24-32.
6. Lopes MS, Dreisigacker S, Peña RJ, Sukumaran S, Reynolds MP. Genetic characterization of the wheat association mapping initiative (WAMI) panel for dissection of complex traits in spring wheat. Theoretical and applied genetics. 2015;128(3):453-64.
7. Olmstead AL, Rhode PW. The red queen and the hard reds: Productivity growth in American wheat, 1800–1940. J Econ Hist. 2002;62(4):929-66.
8. Zhang H, Wang C, Cheng Y, Chen X, Han Q, Huang L, et al. Histological and cytological characterization of adult plant resistance to wheat stripe rust. Plant Cell Reports. 2012;31(12):2121-37.
9. Nevo E, Payne PI. Wheat storage proteins: diversity of HMW glutenin subunits in wild emmer from Israel. Theor Appl Genet. 1987;74(6):827-36.
10. Damania AB, Jackson MT, Porceddu E. Variation in wheat and barley landraces from Nepal and the Yemen Arab Republic. Z Pflanzenzucht. 1985;94(1):13-24.
11. Roelfs AP. Rust diseases of wheat: Concepts and methods of disease management. Cimmy. 1992.
12. Peterson RF, Campbell AB, Hannah AE. A diagrammatic scale for estimating rust intensity on leaves and stems of cereals. Canadian Journal of Research. 1948;26(5):496-500.
13. Plank JE. Plant Diseases-Epidemics and Control Academic Press New York. 1963;17-27.
14. Wilcoxson RD, Skovmand B, Atif AH. Evaluation of wheat cultivars for ability to retard development of stem rust. Ann Appl Biol. 1975;80(3):275-81.
15. Minitab. Getting Started with Minitab 2017. 2017.
16. Statistical Package for Augmented Design (SPAD). 2002.
17. Statistical Package for the Social Sciences (SPSS. 2005.
18. Hovmøller MS, Rodriguez-Algaba J, Thach T, Sørensen CK. Race typing of Puccinia striiformis on wheat. In: Wheat Rust Diseases 2017;29-40.
19. McNeal FH, Konzak CF, Smith EP, Tate WS, Russell TS. A uniform system for recording and processing cereal research data. 1971;34-112.
20. Purdy LH, Allan RE. A stripe rust race pathogenic to 'Suwon 92' wheat. Plant Disease Reporter. 1966;50:205-7.
21. Wang ZL, Li LH, He ZH, Duan XY, Zhou YL, Chen XM, et al. Seedling and adult plant resistance to powdery mildew in Chinese bread wheat cultivars and lines. Plant Disease. 2005;89(5):457-63.
22. Subba Rao KV, Snow JP, Berggren GT. Effect of growth stage and Initial inoculum Level on the Leaf Rut Development and Yield loss caused by P. recondita f. sp. tritici.J Phytopathology. 2008.
23. Ali S, Shah SJ, Raman IK, Maqbool K, Ullah W. Partial resistance to yellow rust in introduced winter wheat germplasm at the north of Pakistan. Aust J Crop Sci. 2009;3(1):37-43.
24. Freedman J, Mackenzie DR. Disease progress curves, their mathematical description and analysis to formulate predictors for loss equations. 1992;37-48.
25. Afshari F. Identification of resistance to Puccinia striiformis f. sp. tritici in some elite wheat lines. J Crop Prot. 2012;1(4):293-302.
26. Safavi SA, Ahari AB, Afshari F, Arzanlou M. Slow rusting resistance in Iranian barley cultivars to Puccinia striiformis f. sp. hordei. J Plant Prot Res. 2013:53;2-7.
27. Singh RP, Huerta-Espino JU, William HM. Genetics and breeding for durable resistance to leaf and stripe rusts in wheat. Turk J Agric For. 2005;29(2):121-7.
28. Dehghani H, Moghaddam M. Genetic analysis of the latent period of stripe rust in wheat seedlings. J Phytopathology. 2004;152(6):325-30.
29. Lagudah ES. Molecular genetics of race non-specific rust resistance in wheat. InBGRI 2010 technical workshop oral presentations. Borlaug Global Rust Initiative (BGRI). 2010;183-96.