Distribution and Pathogen Variability of Wheat Stem Rust (Puccinia Graminis f. sp. Tritici) in North Shewa of Ethiopia

International Journal of Emerging Science and Engineering (IJESE) ISSN: 2319–6378 (Online), Volume-13 Issue-12, November 2025 23 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number:100.1/ijese.C053912031125 DOI:10.35940/ijese.C0539.13121125 Journal Website: www.ijese.org Distribution and Pathogen Variability of Wheat Stem Rust (Puccinia Graminis f. sp. Tritici) in North Shewa of Ethiopia Webanchi Melkie Tilahun, Zelalem Bekako Erena Abstract: Wheat stem rust (Puccinia graminis f. sp. tritici) is the most destructive and devastating foliar disease of wheat, which causes considerable yield losses. The objective of this study was to assess the importance, distribution, and intensity (prevalence, incidence, and severity) of wheat stem rust disease, and to determine their associations with biophysical factors, pathogenic variability, and virulence spectrum in the North Shewa zone of Ethiopia. In 11 districts, 64 fields were assessed diagonally using 1 m × 1 m quadrats at five random spots. According to the survey results, 87.5% of the fields were infected with wheat stem rust. The highest mean disease incidence (95%) and severity (68.33%) were noted at Minjar Shenkora, whereas the lowest incidence (20%) and severity (13.69%) were at Basona Werana and Moretna Jiru, respectively. Almost all biophysical factors were significantly associated with wheat stem rust epidemics (P < 0.001). Especially, fungicide application plays a significant role in disease incidence and severity. From the 31 monopustules/isolates, six races (TKTTF, TTTTF, TTRTF, TKKTF, TTKTT and TTKTF) were identified; race TKKTF was the predominant one. Races TTKTT exhibited virulence to 95% of the stem rust resistance genes. Wheat stem rust was a severe disease of wheat in the zones. It may cause significant economic losses if susceptible local cultivars, Hidasse and Danda’a, were continued to be grown in the area. A national survey is recommended to develop a disease distribution map and generate a clear picture of the disease status for early warning and disease deployment. Implementing integrated disease management practices and creating or promoting resistant wheat varieties could be vital in mitigating the impact of the stem rust pathogen and other rust diseases of wheat. Developing and deploying stem rust-resistant wheat varieties through collaboration between breeders and pathologists is critical to protect smallholder farmers. Keywords: Disease intensity, Incidence, Race analysis, Virulence Spectrum. Nomenclature: DP: Disease Prevalence DS: Disease Severity Manuscript received on 29 October 2025 | First Revised Manuscript received on 31 October 2025 | Second Revised Manuscript received on 07 November 2025 | Manuscript Accepted on 15 November 2025 | Manuscript published on 30 November 2025. *Correspondence Author(s) Webanchi Melkie Tilahun*, Department of Crop and Horticulture Research Lead Executive, Addis Ababa, Ethiopia. Email ID: [email protected], ORCID ID: 0009-0008-9742-5190 Dr. Zelalem Bekako Erena, Department of School of Plant Science, Haramaya, Ethiopia, Dire Dawa, Ethiopia. Email ID: [email protected] © The Authors. Published by Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/ RH: Relative Humidity IT: Infection Type GIS: Geographic Information System I. INTRODUCTION Wheat (Triticum spp.) The most significant cereal crop takes up to 17% of all arable land worldwide [1] and [2]. It is cultivated on 240 million hectares, which is more land than is used for any other crop [3] and has a global production average of 775.4 million metric tons [4] Wheat worldwide increased 1.9% in 2022 compared to 2021[4] Ethiopia is Africa's secondlargest wheat producer, after Egypt [5]. Compared to other food crops, it provides the world's diet with more calories and protein [3] Moreover, more than 90 million Ethiopians rely on it as a staple food, accounting for almost 15% of their daily caloric intake [6] [7]. Thus, it ranks second after maize and somewhat ahead of tef, sorghum, and millet, each of which contributes 10– 12% [7]. Since the 1950s, 36 varieties of durum wheat and more than 90 kinds of bread have been made available for production in Ethiopia [8]. There are roughly 1,789,372.23 hectares of durum and bread wheat production areas, with an annual production of 5,315,270 tons [9]. The [10] Report states that the area used for wheat cultivation has increased to 1,897,405.05 hectares, and production has increased to 5,780,131 tons, with a productivity of 3.1 t ha-1. This is higher than the previous year, but still falls short of the global average of 3.51 t ha-1 [4] and far below the potential yields of 8 to 10 t ha-1 [11] It is one of the most extensively grown cereal crops in the North Shewa Zone, with a total production of 211,060.29 tons on 73,568.4 hectares, 2.87 tons per hectare, and 355,773 small-scale farmers involved [10] In contrast to other wheat-producing nations, Ethiopia's average yield has remained low despite the crop's immense economic and nutritional worth. Numerous biotic and abiotic variables have been implicated in this, including inadequate, excessive, or irregular rainfall, insect pests, and severe plant diseases [12]. One of the main production barriers is stem rust, caused by Puccinia graminis f.sp. tritici. During epidemic years, yield losses might reach 100% [13] Because uredospores spread widely, epidemics can occur on a continental scale [14]. A large number of spores are dispersed by wind over long distances, and their capacity to undergo genetic change results in the production of new physiological races with increased aggression on resistant wheat cultivars [15]. Distribution and Pathogen Variability of Wheat Stem Rust (Puccinia Graminis f. sp. Tritici) in North Shewa of Ethiopia 24 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number:100.1/ijese.C053912031125 DOI:10.35940/ijese.C0539.13121125 Journal Website: www.ijese.org Wheat stem rust survey is regularly conducted in Ethiopia in areas where wheat is cultivated on a large scale, mainly in rainfed and central highland agro-ecologies, and pathogenic variability in terms of virulence and diversity across different parts of wheat-growing areas is being reported. However, new virulent stem rust races continue to evolve in the pathogen population in space and time. Therefore, monitoring pathogen distribution in time and space and maintaining records is crucial for the rust resistance breeding program. Although considerable wheat is also produced in some parts of western and southwestern Ethiopia and in irrigated wheat areas, the status of wheat stem rust intensity is poorly studied [16]. Under such circumstances, resistance breeding against an epidemic of stem rust races cannot target the actual problem. In addition, the absence of information about the pathogen across locations can lead to crop losses, and its spread to neighbouring districts can decrease the country's GDP. Furthermore, because pathogen races are constantly changing, it is impossible to prevent rust. Although host plant resistance can be used to prevent outbreaks, such preventive strategies cannot be applied when knowledge of the pathogen's distribution is lacking. Therefore, understanding the pathogen's distribution, intensity, and variability is very important for disease management. Hence, the purpose of this study was to assess the importance, distribution, and intensity (prevalence, incidence, and severity) of wheat stem rust disease, and to determine their associations with biophysical factors, pathogenic variability, and virulence spectrum in the North Shewa zone of Ethiopia. II. MATERIALS AND METHODS A. Descriptions of the Study Areas The study was conducted in the principal wheat-growing districts of the North Shewa zone, located in Ethiopia's Amhara and Oromia regions. The region, which has an average elevation of 2100–3000 meters above sea level, is situated between latitudes 9º–11ºN and longitudes 38º–40º E (Figure 1). The average rainfall is between 1400 and 1600 mm per year. [Fig.1: Survey Areas Affected by Wheat Stem Rust in the North Shewa Zone of Amhara and Oromia Regions During the 2019/2020 Cropping Season] B. Disease Assessment and Sample Collection A total of 64 fields and 11 districts (Angolalla Tara, Basona Werana, Hagere Mariam, Minjar Shenkora, Moretna Jiru, Siyadebrina Wayu, Abichu, Aleltu, Bereh, Fiche, and Kembibit) were covered from dough to flowering crop growth stages diagonally along each field using a 1 m*1 m quadrat at five spots randomly along 5-10 km intervals. The data on disease prevalence, incidence and severity were taken [17] Supplementary information, such as crop varieties, cropping system, plant growth stage, weed status, crop stand, previous crop and field history, was recorded (Appendix Table 1). GPS data on latitude, longitude, and elevation were collected. i. Disease Prevalence (DP): percentage of diseased fields over the total fields inspected. DP (%)=𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑖𝑛𝑓𝑒𝑐𝑡𝑒𝑑 𝑓𝑖𝑒𝑙𝑑𝑠 𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑎𝑠𝑠𝑒𝑠𝑠𝑒𝑑 𝑓𝑖𝑒𝑙𝑑𝑠 ∗100 ii. Disease Incidence (DI): plants within the quadrate were counted and recorded as diseased/infected DI (%)=𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑑𝑖𝑠𝑒𝑠𝑒𝑑 𝑝𝑙𝑎𝑛𝑡𝑠 𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑙𝑎𝑛𝑡𝑠 𝑖𝑛 𝑞𝑢𝑎𝑑𝑟𝑎𝑛𝑡 ∗100 iii. Disease Severity (DS): a percentage of stem/leaf area covered by rust disease according to Modified Cobb's scale [18]. DS (%)=𝐴𝑟𝑒𝑎 𝑜𝑓 𝑝𝑙𝑎𝑛𝑡 𝑡𝑖𝑠𝑠𝑢𝑒 𝑎𝑓𝑓𝑒𝑐𝑡𝑒𝑑 𝑇𝑜𝑡𝑎𝑙 𝑝𝑙𝑎𝑛𝑡 𝑡𝑖𝑠𝑠𝑢𝑒 𝑎𝑟𝑒𝑎 ∗100 C. Sample Collection, Single pustules isolation and Multiplication A total of 56 stem rust samples were collected from 64 randomly assessed farmers’ fields in North Shewa, Ethiopia, during the 2019/2020 cropping season. Freshly infected stems and/or leaf sheath samples were cut into pieces 5–10 cm in width and length with the required labelled information. Five seedlings were raised in suitable eight cm-diameter clay pots filled with a mixture of steam-sterilised soil, sand, and manure in a 2:1:1 ratio. The stem rust urediospores were collected in a capsule container using a motorised spore collector and diluted using a lightweight mineral oil (SolTrol 170). When the primary leaves were fully expanded and the second leaves began to grow, the leaves were gently rubbed with clean fingers. Greenhouse inoculations were performed using methods developed by [19]. The spore mix was sprayed on “McNair” seedlings from a distance using a clean motorized stem rust inoculator. The inoculated plants were moistened with fine distilled water droplets using an atomiser. After 20 min of inoculation, the cells were incubated in a dark dew chamber at 18-22 °C for 18 h, followed by exposure to light for four h to provide favourable conditions for stem rust infection. Seedlings were allowed to dry/remove their dew/moisture for about 3-4 hours. Following this, seedlings were transferred to glass compartments in the greenhouse at 18-25 °C and a relative humidity (RH) of 60-70%, with a 12-h photoperiod. After seven days of inoculation (when the flecks/symptoms were clearly visible), leaves containing single flecks that produced single pustules were selected from the base of the leaves, and the remaining seedlings within the pots were eliminated using hand scissors. Only 2-3 leaves International Journal of Emerging Science and Engineering (IJESE) ISSN: 2319–6378 (Online), Volume-13 Issue-12, November 2025 25 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number:100.1/ijese.C053912031125 DOI:10.35940/ijese.C0539.13121125 Journal Website: www.ijese.org with single pustules were left, and each was covered with a cellophane bag (145 × 235 mm) and tied at the base with a rubber band to avoid cross-contamination [20]. After two weeks of inoculation (when the mono-pustules were well-developed), each mono-pustule was sucked using an electric power-operated vacuum pump, and spores from each pustule were collected separately in gelatin capsules. A suspension was prepared by mixing uredospores with a lightweight mineral oil (Soltrol 170). Seven-day-old seedlings of the susceptible variety “McNair” were inoculated for each pustule on separate pots for multiplication. Soon after inoculation, the seedlings were placed in a humid chamber in the dark at 18-22°C for 18 h, exposed to light for four h, and transferred to the greenhouse [19]. The seedlings were placed in the dew chamber in the dark 14-15 days after inoculation. The spores of each mono-pustule/isolate were collected in gelatin, aided by a power-driven motor pump, and inoculated on differential lines. D. Race Analysis Five seedlings of differentials and host lines (Table 1) with known resistance genes, and one susceptible variety (McNair), were grown separately in 10 cm diameter pots in the greenhouse. The single pustule-derived spores (3-5 mg of spores) were suspended with lightweight mineral oil and sprayed onto seven-day-old seedlings. After inoculation, plants were moistened with fine droplets of distilled water and placed in an incubation chamber for an 18-hour dark period at 18-22 °C, followed by 4 hours of light, and seedlings were allowed to dry for about 3-4 hours. Upon removal from the dew chamber, plants were placed in separate glass compartments in a greenhouse (at 18 and 25 °C) to avoid contamination and produce infection. Natural daylight was supplemented for an additional 4 hours per day with photosynthetically active radiation at 120 µmol m⁻² s⁻¹, provided by cool-white fluorescent tubes positioned directly above the plants in the greenhouse. Table I: List of Wheat Stem Rust Differential Lines and Corresponding Resistance Genes Used for Race [21] No Test/differential Lines Stem Rust Genes No Test/differential Lines Stem Rust Genes 1 BtSr24Agt 24 11 Combination VII 13+17 2 W2691SrTt-1 36 12 ISr5-Ra 5 3 ISr7b-Ra 7b 13 ISr6-Ra 6 4 ISr8a-Ra 8a 14 W2691Sr9b 9b 5 CnSSrTmp Tmp 15 Vernsteine 9e 6 Sr31(Benno)/6*LM PG 31 16 W2691Sr10 10 7 CnS-T-. monoderiv 21 17 BtSr30Wst 30 8 Trident 38 18 CnsSr9g 9g 9 ISr9a-Ra 9a 19 ISr11-Ra 11 10 ISr9d-Ra 9d 20 McNair 701 McN Stem rust infection types were scored 14 days after inoculation using the 0-4 scale. Low (resistance) = incompatibility (infection type 0, (fleck), 1, (small uredia with necrosis), and 2 (small to medium uredia with chlorosis or necrosis). [Fig.2: Different Infection types of P. Graminis f.sp. Tritici on Wheat [19]] The variations were refined by modifying characters like -, uredinia slightly smaller than usual for the infection type; +, uredinia slightly larger than usual for the infection type and High (susceptible) = compatibility (infection type, 3-, 3+ and 4). The IT readings of 3 (medium-sized uredia with/without chlorosis) and 4 (large uredia without chlorosis or necrosis) were regarded as susceptible (Figure 2). Race designation was done by grouping 20 stem rust differential lines into five subsets (Table 2). Each isolate was assigned a five-letter race code based on its reaction to the differential lines [20]. Each isolate was assigned using a combination of a three-letter code and an additional two-letter race code employed by [21] This finally yielded a five-letter designation based on their reactions to the differential lines (Table 2). For instance, low infection type (IT) is assigned the letter B, while high IT is assigned T on the four hosts. The frequency, dominance, and virulence spectrum of each race were identified. Distribution and Pathogen Variability of Wheat Stem Rust (Puccinia Graminis f. sp. Tritici) in North Shewa of Ethiopia 26 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number:100.1/ijese.C053912031125 DOI:10.35940/ijese.C0539.13121125 Journal Website: www.ijese.org Table II: Letter Code Designations for Races of Puccinia Graminis F.Sp. Titici Using 20 Differential Single Pgt-Gene Lines in Five Ordered Subsets of Four Lines Wheat Pgt Gene Differential Sets and Infection Phenotype Coding Set Differential Lines Identified by the Pgt Resistance Gene Set 1 5 21 9e 7b Set 2 11 6 8a 9g Set 3 36 9b 30 17 Set 4 9a 9d 10 Tmp Set 5 24 31 38 McN Infection Phenotype: High = Virulent Reaction (Susceptible) Pgt-code Low = Avirulent Reaction (Resistant) B Low Low Low Low C Low Low Low High D Low Low High Low F Low Low High High G Low High Low Low H Low High Low High J Low High High Low K Low High High High L High Low Low Low M High Low Low High N High Low High Low P High Low High High Q High High Low Low R High High Low High S High High High Low T High High High High Source[21]. E. Data Analysis Survey data and race analysis were examined across districts, crop growth phases, and varieties using descriptive statistics. The SAS routines GENMOD were used to assess the disease incidence and severity using the logistic regression model developed by [22] The coordinates of the collecting sites were used to construct the study area map in the Geographic Information System (GIS) program ArcMap 10.3. III. RESULTS A. Status and Distribution of Wheat Stem Rust in North Shewa From 64 total surveyed fields 56 (87.5%) were infected by the wheat stem rust. The prevalence was 88.37% and 85.71% in the North Shewa Zone, Amhara Region, and the Oromia Region, respectively (Tables 3 and 4). The disease prevalence was high (100%) in six districts, while the lowest (50%) was recorded in two districts. Three durum wheat varieties (Kokor, Mangudo, and Utuba), seven bread wheat types (Danda'a, Digalu, Enkoy, Hidasse, Hora, Kakaba, and Kubsa), and two unknown bread wheat varieties were investigated, and all varieties were infested (Appendix Table 2). Among the varieties, Danda'a was cultivated predominantly (62.5%), followed by Hidasse (17.19%). The intensity varied among the growth stages, including flowering 20 (31.25%), milking 19 (29.69%), dough 14 (21.88%), and stiff dough 11 (17.19%). The hard dough had the highest disease prevalence (100%), and the flowering stage had the lowest (75%). Regarding weed status: 43.75% weedfree, 14.06% with few weeds found, and 42.19% without weeds. Fungicide application was common in the surveyed areas: 51 fields (79.69%) were sprayed, and 13 fields (20.31%) were non-sprayed. Table III: Prevalence of Wheat Stem Rust Across the North Shewa Zone at Different Districts in the 2019/2020 Primary Cropping Season Regions Zone District Altitude Ranges (m. a.s.l.) No of Fields Assessed Infected Fields Stem rust Prevalence (%) Amhara North Shewa Angolalla Tara 2795-2866 4 4 100 Basona Werana 2760-2822 2 1 50 Hagere Mariam 2821-2829 2 2 100 Minjar Shenkora 2139-2251 3 3 100 Moretna Jiru 2618-2673 13 12 93 Siyadebrina Wayu 2600-2695 19 16 84.21 Subtotal 2139-2866 43 38 88.37 Oromia North Kembibit 2932 2 2 100 Abichu 2611-2810 4 4 100 Shewa Aleltu 2577-2831 9 8 89 Bereh 2289-2620 4 2 50 Fiche Town 2651-2749 2 2 100 Subtotal 2289-2932 21 18 85.71 Overall 2139-2932 64 56 87.5 B. Incidence and Severity of Wheat Stem Rust The distribution of wheat stem rust incidence and severity differed across districts, with biophysical factors (Figures 3 and 4). The highest (95%) mean incidence and (68.33%) mean severity were recorded in Minjar Shenkora, whereas the lowest (20%) mean incidence and (13.69%) mean severity were International Journal of Emerging Science and Engineering (IJESE) ISSN: 2319–6378 (Online), Volume-13 Issue-12, November 2025 27 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number:100.1/ijese.C053912031125 DOI:10.35940/ijese.C0539.13121125 Journal Website: www.ijese.org recorded in Basona Werana and Moretna Jiru, respectively. Regarding the crop stages, the highest mean incidence (73%) and severity (47.86%) were observed at the stiff dough stage, while the lowest mean incidence (8.5%) and severity (6.94%) were recorded at the flowering stage. Based on this altitude classification, [23] From the total fields inspected, 5 (7.81%) of the fields assessed were located in mid altitudes (1500-2300 m), midlands ranging from 2139 to 2298 m.a.s.l while the remaining 59 fields (92.19%) were located in the high altitude (2300-3200 m), ranging from 2530 to 2932 m.a.s.l. The disease incidence (71%) and severity (51%) were high in the midlands, while the lower mean incidence (27.73%) and severity (18.86%) were observed in the highlands (Table 5). The highest mean disease incidence (59.15%) and the highest severity (39.07%) were observed in plots without weed management practices. The highest and lowest mean wheat stem rust incidence was recorded in fields previously sown with onion (100%) and an unknown variety (10%), respectively, and the highest and lowest mean severity was recorded in fields previously planted with onion (60%) and lentil (8.89%), respectively. Among the varieties, Kokor and Mangudo (100%) had the highest mean incidence, and Utuba (75%) had the highest mean severity of stem rust. The lowest mean incidence was recorded in Kubsa (20%), and the lowest mean severity was in Digalu and Kubsa (15%). Regarding the field size, the highest mean incidence (50.63%) and severity (28.57%) were observed in the large field size (≥0). 75. In the broadcast planting system, there was a high disease incidence (40.95%) and severity (27.95%). The highest mean incidence (81.15%) and severity (52.69%) were recorded in fungicide-unsprayed fields. The incidence and severity of stem rust ranged from 0 - 100% and 0-75S, respectively. The assessed wheat plants showed susceptible (S), moderately susceptible (MS), moderately resistant (MR), and resistant (R) responses to stem rust infection (Appendix Table 2). Table IV: Categorization Of Variables Used in Analysis for the Distribution of Wheat Stem Rust Epidemics in Eleven Districts (N = 64) of North Shewa Zone, Amhara and Oromia Regional States, Ethiopia, During the 2019/2020 Primary Growing Season Variable s Variable Class No of Fields Assessed Intensity of wheat Stem Rust Incidence Severity (%) (%) >31 <31 >20 <20 Variable s Variable Class No of Fields Assesse d Intensity of wheat Stem Rust Incidence Severity (%) (%) >31 <31 >20 <20 Districts Angolalla Tara 4 2 2 3 1 Previous Onion 1 1 0 1 0 Basona Werana 2 1 1 1 1 Crop Tef 27 8 19 10 17 Hagere Mariam 2 2 0 2 0 Wheat 5 1 4 2 3 Minjar Shenkora 3 3 0 3 0 Barely 4 3 1 3 1 Moretna Jiru 13 2 11 3 10 Fallow 4 3 1 3 1 Siyadebrina Wayu 19 3 16 6 13 Lathyrus 2 0 2 2 0 Kembibit 2 2 0 2 0 Faba bean 8 3 5 3 5 Abichu 4 2 2 3 1 Lentil 9 1 8 3 6 Aleltu 9 2 7 2 7 Field pea 1 1 0 1 0 Bereh 4 1 3 2 2 Unknown 3 0 3 0 3 Fiche Town 2 1 1 1 1 Varieties Mangudo 1 1 0 1 0 Utuba 1 1 0 1 0 Stage of Crop Flowering 20 0 20 1 19 Digalu 2 1 1 1 1 Milky 19 5 14 7 12 Kokor 1 1 0 1 0 Dough 11 3 8 7 4 Danda’a 40 8 32 15 25 Hard Dough 14 13 1 13 1 Hidase 11 3 8 3 8 Altitude >2300 59 17 42 24 35 Enkoye 2 2 0 2 0 <2300 5 4 1 4 1 Hora 1 1 0 1 0 Crop system Broadcast 44 20 24 27 17 Kakaba 2 2 0 2 0 Row planting 20 1 19 1 0 Kubsa 1 0 1 0 1 Field size (ha) >0.75 35 21 14 27 8 unknown 2 1 1 1 1 <0.75 29 0 29 1 28 Weed Good 28 0 28 0 28 Fungicide Sprayed 51 8 43 15 36 Status Fair 9 0 9 2 7 unsprayed 13 13 0 13 0 Bad 27 21 6 26 1 Crop Good 20 0 20 0 20 Stand Fair 14 2 12 6 8 Bad 30 19 11 22 8 Good, fair and bad weed status: weed-free, few weeds and no weeds during observation. Altitudes: 500-1500 m lowlands, 1501-2300 m midlands, and 2301-3200 m as highlands classified in Ethiopian Agro-ecologies. Based on this classification, the survey area ranged from 1500 to 2300 m in the midlands and above 2300 m in the highlands. Distribution and Pathogen Variability of Wheat Stem Rust (Puccinia Graminis f. sp. Tritici) in North Shewa of Ethiopia 28 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number:100.1/ijese.C053912031125 DOI:10.35940/ijese.C0539.13121125 Journal Website: www.ijese.org [Fig.3: Distribution of Wheat Stem Rust Incidence in the Survey Areas of North Shewa Zone, Amhara and Oromia Regions in the 2019/2020 Primary Cropping Season] [Fig.4: Distribution of Wheat Stem Rust Severity in the Survey Areas in North Shewa Zone, Amhara and Oromia Regions in the 2019/2020 Primary Cropping Season] Table V: Mean Incidence and Severity of Wheat Stem Rust in North Shewa Zone, Amhara and Oromia Regional States, Ethiopia, During The 2019 Primary Growing Season Variable s Variable Class Intensity of wheat Stem Rust Mean Mean Variables Variable Class Intensity of wheat Stem Rust Mean Mean Incidence ±SE Severity ±SE Incidence ±SE Severity ±SE Districts Angolalla Tara 37.5± 0.64 27.5±0.66 Previous Onion 100± 0.66 60±0.36 Basona Werana 20± 0.76 15±0.65 Crop Teff 29.11± 0.18 22.04±0.19 Hagere Mariam 52.5± 0.57 27.5±0.51 Wheat 33± 0.00 25.83±0.00 Minjar Shenkora 95± 0.49 68.33±0.46 Barely 50± 0.50 28.75±0.45 Moretna Jiru 20.31± 0.19 13.69±0.16 Fallow 41.25± 0.47 27.5±0.44 Siyadebrina Wayu 24.74± 0.00 18.16±0.00 Laythurus 30± 0.52 22.5±0.42 Kembibit 70± 0.54 45±0.49 Faba bean 31.25± 0.28 21.25±0.21 Abichu 40.5±0.30 27.5±0.26 Lentil 21.67± 0.24 8.89±0.25 Aleltu 22.78± 0.19 14.44±0.19 Field pea 40± 0.67 30±0.64 Bereh 25± 0.29 17.5±0.32 Unknown 10± 0.34 10±0.29 Fiche Town 35± 0.39 22.5±0.40 Varieties Mangudo 100± 0.00 60±0.00 Utuba 85±0.00 75±0.00 Stage of Crop Flowering 8.5±0.16 6.94±0.17 Digalu 22.5± 0.56 15±0.51 Milky 25.21±0.00 14.29±0.00 Kokor 100± 0.66 70±0.37 Dough 29.09± 0.20 25.83± 0.19 Danda’a 24.65± 0.31 17.08±0.28 Hard Dough 73±0.29 47.86±0.30 Hidase 23.64±0.32 15.45±0.29 Altitude >2300 27.73± 0.00 18.86±0.00 Enkoy 50±0.71 35±0.61 <2300 71± 0.47 51±0.46 Hora 70± 0.00 50±0.00 Crop system Broadcast 40.95±0.17 27.95±0.16 Kakaba 70± 0.00 45±0.00 Row planting 9.45±0.00 6.9±0.00 Kubsa 20±0.78 15± 0.74 Field size (ha) >0.75 50.63±0.00 28.57±0.00 unknown 42.5±0.00 27.5±0.00 <0.75 7.55±0.40 6.31±0.39 Crop Good 7.7 ±0.00 4.9±0.00 Weed Good 6.75±0.00 5.64±0.00 Stand Fair 19.64±0.23 14.69±0.21 Status Fair 22.78±0.51 17.22±0.46 Bad 52.07±0.26 36.96±0.25 Bad 59.15±0.50 39.07±0.48 Fungicide Sprayed 18.35±0.00 13.39±0.00 unsprayed 81.15±0.23 52.69±0.26 SE = Standard error, weed status: Good, fair and bad weed status: weed-free, few weeds, and no weeds during observation. Altitudes: 500-1500 m lowlands, 1501-2300 m midlands, and 2301-3200 m as highlands classified in the Ethiopian AgroEcologies classification. Based on this classification, survey areas ranged from 1500 to 2300 m in the midlands and above 2300 m in the highlands. C. Association of Stem Rust Intensity with Biophysical Factors Except for the cropping system and crop performance, all independent variables, including distrip (P ≤ 0.0013), growth stage, weeding, status, varieties, previous crop, field size, and fungicide application International Journal of Emerging Science and Engineering (IJESE) ISSN: 2319–6378 (Online), Volume-13 Issue-12, November 2025 29 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number:100.1/ijese.C053912031125 DOI:10.35940/ijese.C0539.13121125 Journal Website: www.ijese.org showed a very highly significant (P ≤ 0.0001) association with disease incidence. However, the cropping system (p≤ 0.) showed very highly significant (P ≤ 0.0001) associations associated with disease incidence. All biophysical factors (variables), such as district, altitude, growth stage, weeding status, varieties, previous crop, field size, and fungicide application, showed a very highly significant (P ≤ 0.0001) association with severity. Besides, cropping system (P≤0.0010) and crop status (P ≤0.0015) showed 15 highly significant associations with disease severity (Table 6). When all variables were entered last into the regression model, most factors, including district, weed status, varieties, previous crop, field size, and fungicide application, showed a highly significant association (P ≤ 0.0001) with wheat stem rust severity. However, the growth stage was not significant in this context. For disease incidence, all independent variables (district, altitude, growth stage, weeding status, varieties, previous crop, field size, cropping system, crop performance, and fungicide application) were important when entered first into the model. When entered last, most of these variables remained significant, except for the cropping system, which lost significance in the reduced model. Regarding disease severity, all variables were initially important when entered first; however, in the reduced model, cropping system, crop performance, altitude, and growth stage lost significance. Except for growth stage, altitude, cropping system, and crop stand, the other variables —district, weeding status, variety, previous crop, field size, and fungicide application —remained strongly associated with wheat stem rust severity when entered last into the model. These important variables were further tested in reduced multiple variable models, confirming their key roles in disease incidence and severity. The deviation analysis of these variables in reduced multiplevariable models showed varying levels of association with wheat stem rust incidence and severity. The parameter estimates, standard errors, odds ratios, and analyses of deviation for variables and variable classes are tabulated hereunder (Tables 7 and 8). The probability of wheat stem rust incidence of >31% was highly associated with districts Minjar Shenkora (23.5), Hagere Mariam (22.4), Kembibit (5.7), Moretna Jiru (3.5), Fiche town (2.1), and Bereh (1.6), the presence of wheat stem rust along with greater. The dough (1.9) and stiff dough (4.5) stages showed a higher probability of association with mean incidence than the flowering and milky stages. High incidence was associated with mid altitude (18.7), poor weed status (3.7), unsprayed fungicide field (10.2), Digalu (5.9), Kubsa (7.1), and Enkoy (22.9) varieties. The probability of high incidence was highly associated with previous crop planting: barley (13.0), Lathyrus (11.9), and unknown crops (3.4) (Table 7). Foul and fair crop performance were more likely to be associated with higher mean incidence than good performance. At the same time, the probability of severity >20% was strongly associated with the districts of Minjar Shenkora (22.3), Hagere Mariam (2.8), Kembibit (2.6), and Fiche town (2.2). Stiff dough stage severity, previous crop Lathyrus (2.8), unknown crop (3.2), Digalu (2.3), Kubsa (2.2) and Enkoy (4.1) varieties, bad performance (2.1), and fair crop performance (1.67) showed a high probability of association. Fungicide applications were also tested in reduced multiple models. High wheat stem rust severity (>20%) was associated with an unsprayed field, with a 2.708 times greater probability of wheat stem rust severity than in other fields (Table 8). Table VI: Logistic Regression Model for Wheat (Triticum Turgidum Subsp. Durum (Desf.) Husn.) Stem Rust Incidence and Severity, And Likelihood Ratio Test on Independent Variables in North Shewa Zone, Amhara and Oromia Regional States, Ethiopia, During 2019/2020 Primary Cropping Season Incidence of Stem Rust of Wheat LRT Severity of Stem Rust of Wheat LRT Independent Variable DF Type 1 Analysis (VEF) Type 3 Analysis (VEL) Type 1 Analysis (VEF) Type 3 Analysis (VEL) DR Pr>χ2 DR Pr>χ2 DR Pr>χ2 DR Pr>χ2 Districts 10 913.48 <0.0001 104.88 <0.0001 480.23 <0.0001 34.19 <0.0001 Altitude 1 21.81 <0.0001 8.20 0.0042 16.01 <0.0001 4.90 0.0268 Growth stage 3 1212.41 <0.0001 35.69 <0.0001 519.38 <0.0001 3.07 0.3817 Weeding status 2 21.88 <0.0001 19.41 <0.0001 24.11 <0.0001 11.30 0.0035 Variety 10 283.96 <0.0001 83.04 <0.0001 104.30 <0.0001 24.43 0.0010 Previous crop 9 99.39 <0.0001 95.01 <0.0001 89.57 <0.0001 45.52 <0.0001 Field size 1 200.35 <0.0001 26.31 <0.0001 118.97 <0.0001 9.98 0.0016 Cropping system 1 13.70 0.0002 5.59 0.0181 10.87 0.0010 5.41 0.0200 Crop performance 2 13.26 0.0013 12.58 0.0019 13.04 0.0015 8.46 0.0146 Fungicide application 1 117.69 <0.0001 117.69 <0.0001 16.15 <0.0001 16.15 <0.0001 Distribution and Pathogen Variability of Wheat Stem Rust (Puccinia Graminis f. sp. Tritici) in North Shewa of Ethiopia 30 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number:100.1/ijese.C053912031125 DOI:10.35940/ijese.C0539.13121125 Journal Website: www.ijese.org Table VII: Analysis Of Deviance, Natural Logarithms of Odds Ratios and Standard Error of Per Cent of Durum Wheat Stem Rust Incidence and Likelihood Ratio Test on Independent Variables in Reduced Model in North Shewa Zone, Amhara and Oromia Regional States, Ethiopia, For The 2019/2020 Main Cropping Seasons Variables Residual Deviance a Df Pgt incidence (LRT)b Variable Class Estimate Loge (odds ratio) c SE Odds ratio) d DR Pr>χ2 Districts 2107.8156 10 0.00 0.9675 Angolalla Tara 0.0260 0.6373 1.0263 2.51 0.1128 Basona Werana -1.2122 0.7644 0.2975 29.56 <0.0001 Hagere Mariam 3.1089 0.5718 22.3964 1968.39 <0.0001 Minjar Shenkora 3.15789 0.4864 23.5209 14.70 <0.0001 Moretna Jiru 0.7220 0.1883 2.0585 . . Siyadebrina Wayu 0.0000 0.00 1 10.54 0.0012 Kembibit 1.7385 0.5355 5.6888 4.63 0.0314 Abichu -0.6357 0.2953 0.5296 3.13 0.0770 Aleltu -0.3282 0.1856 0.7202 2.69 0.1011 Bereh 0.4801 0.2928 1.6162 10.44 0.0012 Fiche Town 1.2633 0.3911 3.5371 Growth Stage 490.2435 3 0.29 0.5895 Flowering -0.0853 0.1580 0.9182 . . Milking 0.00 0.00 1 9.45 0.0021 Dough 0.6149 0.2001 1.8495 25.83 <0.0001 Hard dough 1.4935 0.2939 4.4527 Altitude 2086.0097 1 . 0.00 >2300 0.0000 0.00 1 2202.25 <0.0001 <2300 2.9310 0.4673 18.7463 Weeding status 254.3078 2 . . Good 0.0000 0.00 1 0.0003 Fair -1.8562 0.5090 0.1563 <0.0001 Bad 1.2988 0.4997 3.6649 Previous Crop 1986.6148 9 0.00 0.9993 Onion -23.1087 0.66 0.00 0.13 0.7203 Tef -0.0651 0.1817 0.9370 . . Wheat 0.00 0.00 1 25.99 <0.0001 Barley 2.5656 0.5033 13.0085 54.70 <0.0001 Fallow -3.4427 0.4655 0.0320 22.47 <0.0001 Lathyrus 2.4776 0.5227 11.9126 0.17 0.6834 Faba bean -0.1156 0.2834 0.8908 0.08 0.7758 Lentil -0.0673 0.2362 0.9349 0.11 0.7409 Field pea 0.2221 0.6716 1.2487 12.93 0.0003 Unknown 1.2166 0.3383 3.3757 Varieties 1702.6557 10 . . Mangudo 0.00 0.00 1 . . Utuba 0.00 0.00 1 10.17 0.0014 Digalu 1.7861 0.5599 5.9661 0.00 0.9993 Kokor -23.1087 0.66 0.00 1.69 0.1938 Danda’a 0.3981 0.3064 1.4890 0.02 0.8784 Hidase 0.0492 0.3218 1.0504 19.38 <0.0001 Enkoy 3.1322 0.7116 22.9244 . . Hora -24.0297 0.00 0.00 . . Kakaba 0.00 0.00 1 6.40 0.0114 Kubsa 1.9612 0.7750 7.1079 . . Unknown 0.00 0.00 1 Cropping system 276.1858 1 5.57 <0.0001 Broadcast 0.3893 0.1650 1.4759 . . Row planting 0.00 0.00 1 Field size 289.8899 1 . . >0.75 0.00 0.00 1 27.77 <0.0001 <0.75 -2.0985 0.3982 0.1226 Crop stand 241.0459 2 . . Good 0.00 0.00 1 12.39 0.0004 Fair 0.8078 0.2295 2.2430 10.38 0.0013 Bad 0.8475 0.2630 2.3338 Fungicide 123.3588 1 . . Sprayed 0.00 0.00 1 99.71 <0.0001 Unsprayed 2.3248 0.2328 10.2246 International Journal of Emerging Science and Engineering (IJESE) ISSN: 2319–6378 (Online), Volume-13 Issue-12, November 2025 31 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number:100.1/ijese.C053912031125 DOI:10.35940/ijese.C0539.13121125 Journal Website: www.ijese.org Table VIII: Analysis of Deviance, Natural Logarithms of Odds Ratios and Standard Error of Per Cent of Durum Wheat Stem Rust Severity and Likelihood Ratio Test on Independent Variables in Reduced Model in North Shewa Zone, Amhara and Oromia Regional States, Ethiopia, The 2019/2020 Main Cropping Seasons Variables Residual Deviance a Df Pgt incidence (LRT)b Variable Class Estimate Loge (odds ratio) c SE Odds ratio) d DR Pr>χ2 Districts 984.9613 10 0.17 0.6827 Angolalla Tara 0.2699 0.6603 1.3098 1.69 0.1931 Basona Werana -0.8461 0.6501 0.4291 3.99 0.0457 Hagere Mariam 1.0131 0.5069 2.7541 2123.80 <0.0001 Minjar Shenkora 3.10358 0.4565 22.2776 1.28 0.2581 Moretna Jiru 0.1819 0.1608 The Amhara and Oromia regions in the . . Siyadebrina Wayu 0.00 0.00 1 3.71 0.0540 Kembibit 0.9481 0.4921 2.5808 2.77 0.0961 Abichu -0.4313 0.2592 0.6497 8.41 0.0037 Aleltu -0.5499 0.1896 0.5770 0.07 0.7981 Bereh -0.0830 0.3245 0.9204 4.12 0.0423 Fiche Town 0.8075 0.3978 2.2423 Growth Stage 255.7060 3 0.01 0.9409 Flowering 0.0123 0.1654 1.0124 . . Milking 0.00 0.00 1 0.92 0.3363 Dough 0.1806 0.1879 The North Shewa Zone of Amhara and Oromia Regions in the 3.00 <0.0001 Hard dough 0.5279 0.3048 1.6954 Altitude 968.9474 1 . . >2300 0.00 0.00 1 1928.51 <0.0001 <2300 -20.3482 0.4634 0.00 Weeding status 101.7593 2 . . Good 0.00 0.00 1 2.91 <0.0001 Fair -0.7888 0.4625 0.4544 0.21 0.6430 Bad -0.2216 0.4783 0.8012 Previous Crop 879.3782 9 4.15 0.0417 Onion -0.7333 0.3601 0.4803 0.05 0.8293 Tef -0.0401 0.1862 0.9607 . . Wheat 0.00 0.00 1 11.15 0.0008 Barley -1.5067 0.4512 0.2216 14.59 0.0001 Fallow -1.6941 0.4435 0.1838 5.78 0.0162 Lathyrus 1.0180 0.4235 2.7677 0.74 0.3883 Faba bean 0.1825 0.2116 1.2002 0.61 0.4335 Lentil -0.1983 0.2532 0.8201 0.06 0.8103 Field pea -0.1528 0.6366 0.8583 16.31 <0.0001 Unknown 1.1734 0.2906 3.2330 Varieties 775.0825 10 . . Mangudo 0.00 0.00 1 . . Utuba 0.00 0.00 1 2.85 0.0911 Digalu 0.8637 0.5112 2.3719 0.63 0.4287 Kokor -0.2915 0.3683 0.7471 0.07 0.7943 Danda’a -0.0721 0.2764 0.9304 0.00 0.9648 Hidase -0.0128 0.2903 0.9873 5.34 0.0209 Enkoy 1.4135 0.6119 4.1103 . . Hora -21.5443 0.00 0.00 . . Kakaba 0.00 0.00 1 1.11 0.2916 Kubsa 0.7800 0.7396 2.1815 . . Unknown 0.00 0.00 1 Cropping system 125.8741 1 5.36 0.0206 Broadcast 0.3594 0.1552 1.4325 . . Row planting 0.00 0.00 1 Field size 136.7404 1 . . >0.75 0.000 0.00 1 10.83 0.0010 <0.75 -1.2898 0.3919 0.2753 Crop performance 88.7144 2 . . Good 0.00 0.00 1 6.16 0.0130 Fair 0.5128 0.2065 1.6700 8.52 0.0035 Bad 0.7185 0.2461 2.0514 Fungicide 72.5628 1 . . Sprayed 0.00 0.00 1 15.15 <.0001 Unsprayed 0.9962 0.2560 2.7080 LRT likelihood ratio test; VEF variable entered first in the model; VEL variable entered last in the model; DR deviance reduction; Pr probability of a χ2 value exceeding the deviance reduction; χ2= chi square; DF degrees of freedom. a Unexplained variations after Distribution and Pathogen Variability of Wheat Stem Rust (Puccinia Graminis f. sp. Tritici) in North Shewa of Ethiopia 38 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number:100.1/ijese.C053912031125 DOI:10.35940/ijese.C0539.13121125 Journal Website: www.ijese.org SUPPLEMENTARY INFORMATION Appendix Table 1. Data sheet for wheat stem rust assessment in North Shewa Zone, Oromia and Amhara regions. Part I: Data Collector Information Surveyor name: _______ Institution: _______ Email: _________ Field code: ________ Date (dd/mm/yy): _______ Region ______ Zone _______ District; _____ Location _________ Part II: Field and Crop Management Information 1. Field information: 1.1 Size of the wheat field (in ha): ____________ 1.2 GPS data: Latitude (N) __________ 1.3 Longitude (E) __________ 1.4 Altitude (m) __________ 1.5 Variety_____________ 1.6 Growth stage Milky Flowering Dough Hard dough 2. Crop Management: 2.1 Frequency of tillage/plough before sowing: ________________ 2.2 Sowing date (dd/mm/yy): __________________ 2.3 Planting/sowing methods: Row Broadcast 2.4 Field history (previous crop): ____________________________ 2.5 Field sanitation: Good Fair Bad 2.6 Crop stand/performance: Good Fair Bad 3. %SR Prevalence: ________________ 4. %SR Incidence: _________________ 5. %SR Severity: __________________ Appendix Table 2: Incidence and Severity of Stem Rust on Wheat Varieties Assessed in North Shewa Zones, Amhara and Oromia Regions, 2019/2020 Main Cropping Season Wheat Assessed Infected Ranges Variety response Varieties fields fields Prevalence (%) Incidence (%) Severity (%) at fields Danda‟a 40 36 90 0-100 0-60 0-S Digalu 2 1 50 0-45 0-30 0-MS Enkoy 2 2 100 40-60 30-40 MS Hidasse 11 8 72.73 0-80 0-60 0-S Hora 1 1 100 70 50 MR Kakaba 2 2 100 60-80 40-50 MS-S Kokor 1 1 100 100 70 S Kubsa 1 1 100 20 15 S Mangudo 1 1 100 100 60 S unknown 2 2 100 5-80 5-50 R-S Utuba 1 1 100 85 75 S R=Resistant, MR=Moderately-Resistance, MR-MS= Moderately -Resistance Moderately -Susceptible MS= Moderately - Susceptible, MS-S= Moderately SusceptibleSusceptible and S=Susceptible field reaction of wheat. International Journal of Emerging Science and Engineering (IJESE) ISSN: 2319–6378 (Online), Volume-13 Issue-12, November 2025 39 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number:100.1/ijese.C053912031125 DOI:10.35940/ijese.C0539.13121125 Journal Website: www.ijese.org Appendix Table 3: Stem Rust Races Identified from North Shewa Zone, Amhara and Oromia Regions, During 2019/2020 Main Cropping Season S. No Region Zones District Altitude (M.A.S.L) Wheat Spp Type Variety Race Analysis Result 1 Amhara N/Shewa Minjar Shenkora 2139 DW Utuba TTKTF 2 Amhara N/Shewa Minjar Shenkora 2167 DW Kokor TTKTT 3 Amhara N/Shewa Basona Werana 2760 BW Digalu TKKTF 4 Amhara N/Shewa Moretna Jiru 2654 BW Danda'a TKTTF 5 Amhara N/Shewa Siyadeberina Wayu 2660 BW Danda'a TKKTF 6 Amhara N/Shewa Moretna Jiru 2618 BW Danda'a TTRTF 7 Amhara N/Shewa Moretna Jiru 2657 BW Hidasse TKKTF 8 Amhara N/Shewa Moretna Jiru 2652 BW Danda'a TKKTF 9 Amhara N/Shewa Moretna Jiru 2669 BW Danda'a TKKTF 10 Amhara N/Shewa Moretna Jiru 2668 BW Danda'a TKKTF 11 Amhara N/Shewa Moretna Jiru 2673 BW Danda'a TTKTT 12 Amhara N/Shewa Siyadeberina Wayu 2673 BW Hidasse TKKTF 13 Amhara N/Shewa Siyadeberina Wayu 2674 BW Danda'a TKKTF 14 Amhara N/Shewa Siyadeberina Wayu 2662 BW Hidasse TKKTF 15 Amhara N/Shewa Siyadeberina Wayu 2651 BW Hidasse TTTTF 16 Amhara N/Shewa Moretna Jiru 2648 BW Hidasse TKKTF 17 Amhara N/Shewa Siyadebrina Wayu 2658 BW Danda'a TKKTF 18 Amhara N/Shewa Siyadberina Wayu 2683 BW Danda'a TKKTF 19 Amhara N/Shewa Siyadberina Wayu 2661 BW Hidasse TKKTF 20 Amhara N/Shewa Siyadberina Wayu 2662 BW Danda'a TKKTF 21 Amhara N/Shewa Abichu 2614 BW Danda'a TTTTF 22 Amhara N/Shewa Siyadberina Wayu 2695 BW Danda'a TKKTF 23 Amhara N/Shewa Siyadberina Wayu 2689 BW Hidasse TTTTF 24 Amhara N/Shewa Angolellana Tara 2843 BW Danda'a TKTTF 25 Oromia N/Shewa Aleltu 2577 BW Danda'a TKKTF 26 Oromia N/Shewa Aleltu 2629 BW Danda'a TKKTF 27 Oromia N/Shewa Aleltu 2591 BW Danda'a TKKTF 28 Oromia N/Shewa Aleltu 2586 BW Danda'a TKTTF 29 Oromia N/Shewa Bereh 2620 BW Danda'a TKKTF 30 Oromia N/Shewa Bereh 2289 BW Hora TTKTF 31 Oromia N/Shewa Fiche Town 2659 BW Danda'a TTTTF