Evaluation of Adult Plant Resistance in Bread Wheat (Triticum aestivum L.) Genotypes to Wheat Stem Rust (Puccinia graminis f. sp. tritici) Races in Ethiopia

Tamene Mideksa; Zerihun Eshetu

doi:doi:10.11648/j.ajpb.20251004.16

Research Article |

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Evaluation of Adult Plant Resistance in Bread Wheat (Triticum aestivum L.) Genotypes to Wheat Stem Rust (Puccinia graminis f. sp. tritici) Races in Ethiopia

Tamene Mideksa^*

, Zerihun Eshetu

Published in American Journal of Plant Biology (Volume 10, Issue 4)

Received: 8 November 2025 Accepted: 15 December 2025 Published: 29 December 2025

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Abstract

A field experiment was conducted during the 2021 main cropping season using an augmented design to evaluate adult plant resistance in bread wheat genotypes against wheat stem rust (Puccinia graminis f. sp. tritici) in Ethiopia. Final rust severity (FRS), coefficient of infection (CI), and relative area under the disease progress curve (rAUDPC) were used to identify slow rusting genotypes. These parameters proved reliable for assessing resistance. Eleven Pgt races were tested on 20 near-isogenic lines carrying single stem rust resistance genes. Greenhouse results showed seven lines were resistant to all races. Genotypes were grouped based on infection types: Group I (e.g., genotypes 40 and 56) showed low infection types (ITs); Group II (e.g., genotypes 2, 3, 12, 13, 43, 91, 98) showed high ITs; Group III included 68 lines with variable reactions. TTKTF and TKPTF caused the highest ITs, while TTKTT showed the lowest. Thirty slow rusting genotypes were identified based on field FRS (Trace MS to 25 MS) and seedling ITs (2+ to 4). These cultivars offer valuable genetic resources for wheat improvement programs targeting durable resistance to stem rust. These findings demonstrate the importance of combining field-based slow rusting parameters with greenhouse race-specific evaluations to obtain a comprehensive understanding of resistance. The identification of genotypes with stable resistance across multiple environments provides a strong foundation for breeding programs aimed at durable stem rust resistance. Such cultivars are particularly valuable in Ethiopia, where stem rust epidemics pose a recurring threat to wheat production and national food security. This study contributes to the global effort of developing improved wheat varieties by offering genetic resources that can be integrated into international breeding pipelines. By highlighting both race-specific and slow rusting resistance, the research underscores the need for continuous monitoring of pathogen variability and the deployment of diverse resistance genes to ensure long-term effectiveness.

Published in	American Journal of Plant Biology (Volume 10, Issue 4)
DOI	10.11648/j.ajpb.20251004.16
Page(s)	121-132
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2025. Published by Science Publishing Group

Keywords

Lines, Near-isogenic, Seedling, Slow Rusting, Races, Resistance

1. Introduction

Wheat rust diseases stem rust (Puccinia graminis f. sp. tritici), leaf rust (Puccinia triticina), and yellow rust (Puccinia striiformis f. sp. tritici) are major constraints to global wheat production. In Ethiopia, stem rust and yellow rust are particularly damaging to productivity. Recent studies estimate annual global losses from these rusts at 15.04 million tons, equivalent to US $2.9 billion

[8]

. Resistance to wheat rusts is broadly categorized into race-specific and race-non-specific types. Race-specific resistance is qualitative and often short-lived due to the rapid evolution of virulent pathogen races

[9, 25]

. In contrast, race-non-specific resistance commonly referred to as slow rusting is expressed at adult plant stages and governed by adult plant resistance (APR) genes. Though moderate when acting alone, APR genes contribute significantly to durable resistance when combined with major genes and minor QTLs

[12]

East Africa has been designated a hotspot for stem rust evolution. In 1998, race TTKSK (Ug99) was first identified in Uganda and later detected in Ethiopia in 2003

[17, 1]

. Ug99 is virulent to Sr31, a key resistance gene in many cultivars, rendering much of the Ethiopian germplasm susceptible

[15]

. In 2012, race TKTTF was first detected at trace levels in Ethiopia and reached epidemic levels by November 2013, causing 100% yield loss in cultivars like Digalu (SrTmp)

[3]

. Unlike Ug99, TKTTF is genetically distinct. Subsequent surveys in 2014–2015 identified nine additional Pgt races in Ethiopia, including TKTTF, TTTTF, TTKSK, TRTTF, PKTTF, TTTSF, SJPQC, JRCSF, and JRCQC

[6]

. In 2018, race TTKTT emerged, showing virulence to SrTmp, Sr24, and Sr31, and overcoming nearly all resistance genes except Sr36

[7]

Understanding the genetic basis of resistance to P. graminis f. sp. tritici is essential for effective breeding and deployment of resistant cultivars. Gene postulation is a rapid and widely used method for identifying resistance genes

[5, 4]

. Analysing the genetic background of resistant genotypes provides a foundation for strategic breeding and disease management. Therefore, this study aimed to evaluate advanced bread wheat lines for seedling resistance genes and identify slow rusting genotypes suitable for wheat improvement programs in Ethiopia.

2. Materials and Methods

2.1. Pathogen Materials

A total of eleven stem rust races were obtained from Ambo Agricultural Research Center. The races were initially identified at Ambo from samples collected from different wheat-growing areas in Ethiopia. The race designation was based on the letter code nomenclature system

[18, 19]

, modified to further delineate races in the TTKSK lineage

[11]

. All isolates were derived from a single pustule, increased in isolation, and stored at -80°C. To get sufficient fresh spores of each isolate was multiplied on the susceptible check McNair 701 (CItr 15288). The races were selected based on their prevalence and virulence spectra as indicated (Table 1).

Table 1. Virulence/Avirulence Spectra of Pgt Races Used in Seedling Tests of Bread Wheat Genotypes in the Greenhouse at Ambo Agricultural Research Center in 2021/22.

Race	Virulence	Avirulence
TKTTF	5, 21, 9e, 7b, 6, 8a, 9g, 36, 9b, 30, 17, 9a, 9d, 10, Tmp, 38, McN	11, 24, 31
TTTTF	5, 21, 9e, 7b, 11, 6, 8a, 9g, 36, 9b, 30, 17, 9a, 9d, 10, Tmp, 38, McN	24, 31,
TKPTF	5, 21, 9e, 7b, 6, 8a, 9g, 36, 30, 9g, 9a, 9d, 10, Tmp, 38, McN	11, 9b, 24, 31,
TRTTF	5, 21, 9e, 7b, 11, 6, 9g, 36, 9b, 30, 17, 9a, 9d, 10, Tmp, 38, McN	8a, 24, 31,
TKKTF	5, 21, 9e, 7b, 6, 8a, 9g, 9b, 30, 17, 9a, 9d, 10, Tmp, 38, McN	11, 36, 24, 31,
RRTTF	5, 21, 7b, 11, 6, 9g, 36, 9b, 30, 17, 9a, 9d, 10, Tmp, 38, McN	9e, 8a, 24, 31
TTRTF	5, 21, 9e, 7b, 11, 6, 8a, 9g, 36, 9b, 17, 9a, 9d, 10, Tmp, 38, McN	30, 24, 31,
JRCQC	21, 9e, 11, 6, 9g, 17, 9a, 9d, McN	5, 7b, 8a, 36, 9b, 30, 10, Tmp, 24, 31, 38
TTKSK	5, 21, 9e, 7b, 11, 6, 8a, 9g, 9b, 30, 17, 9a, 9d, 10, 31, 38, McN	36, Tmp, 24
TTKTF	5, 21, 9e, 7b, 11, 6, 8a, 9g, 9b, 30, 17, 9a, 9d, 10, Tmp, 38, McN	36, 24, 31
TTKSK	5, 21, 9e, 7b, 11, 6, 8a, 9g, 9b, 30, 17, 9a, 9d, 10, 31, 38, McN	36, Tmp, 24,
TTKTT	5, 21, 9e, 7b, 11, 6, 8a, 9g, 9b, 30, 17, 9a, 9d, 10, Tmp, 24, 31, 38, McN	36

2.2. Seedling Test Procedures

The experiment was conducted at Ambo Agricultural Research Center (AARC) following the inoculation and disease assessment protocols described by

[10]

. Five to seven seeds of each bread wheat genotype, including commercial varieties and a susceptible check, were planted in 3 cm diameter plastic pots filled with a soil, compost, and sand mixture in a 2:1:1 ratio. A set of stem rust differential lines was planted alongside the test genotypes. The experiment was arranged in a Completely Randomized Design (CRD) with two replications. The universally susceptible wheat cultivar McNair 701 (CItr 15288) was used as a control to monitor the virulence of each Pgt race. Seven days after sowing, when the first leaf was fully expanded, seedlings were inoculated with selected Pgt races. Spores derived from single pustules were suspended in mineral oil (Soltrol 170) and sprayed onto the seedlings. After allowing the oil to evaporate, a fine mist of water was applied to induce artificial dew and promote spore germination. To prevent cross-contamination, inoculated seedlings were enclosed in plastic bags (145 mm × 235 mm) and sealed at the base with rubber bands

[1]

. Seedlings were incubated in the dark for 18–24 hours at 18 °C and 95% relative humidity in a dew chamber. They were then exposed to fluorescent light for three hours, followed by gradual drying to acclimate them to the greenhouse environment. After drying, seedlings were transferred to the growth room or greenhouse for disease development. Fourteen days post-inoculation, plants were scored for infection types (ITs) using the 0–4 scale described by

[22]

. ITs of “0”, “;”, “;1”, “1”, “1+”, “2−”, “2”, and “2+” were classified as low infection types, while “3−”, “3”, “3+”, and “4” were considered high infection types (Figure 1).

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Figure 1. Infection Types of P. Graminis f. sp. Tritici and Host Response.

Table 2. Description of Infection Types Used in Classifying the Reactions of Stem Rust on Wheat Seedling Leaves

[19]

Host response	IT	Disease symptoms
Immune	0	No uredinia or other macroscopic sign of infection
Nearly immune	;	No uredinia, but hypersensitive necrotic or chlorotic flecks present
Very resistant	1	Small uredinia surrounded by necrosis
Moderately resistant	2	Small to medium uredinia are often surrounded by chlorosis or necrosis; green islands may be surrounded by chlorotic or necrotic border
Heterogeneous	X	Random distribution of variable-sized uredines on a single leaf
Moderately susceptible	3	Medium-sized uredinia that may be associated with chlorosis
Susceptible	4	Large uredinia without chlorosis

2.3. Host Materials

A total of 100 bread wheat genotypes, selected from breeding populations, were evaluated for adult plant resistance to stem rust. The commercial varieties Hachalu and Madda Walabu were included as resistant and susceptible checks, respectively.

2.4. Data Collection

Stem rust severity was recorded six times at seven-day intervals, beginning at the onset of disease symptoms. Disease scoring was performed using the modified Cobb Scale

[16]

, which estimates the percentage of leaf area affected by rust pustules.

Table 3. Host Response and Constant Values Used in Disease Severity Assessment

[23]

Field response	Constant value
R	0.2
MR	0.4
M	0.6
MS	0.8
S	1.0

2.5. Average Coefficient of Infection (ACI)

The Average Coefficient of Infection (ACI) was calculated by multiplying the recorded percentage severity of stem rust by a constant value corresponding to the host response, as described by

[23]

. These constants reflect the degree of susceptibility or resistance and are presented in Table 1. ACI provides a more refined estimate of disease impact by integrating both severity and host reaction.

Area Under the Disease Progress Curve (AUDPC)

The Area Under the Disease Progress Curve (AUDPC) was computed to quantify disease development over time. It was calculated using the formula:

AUDPC = Σ [(yᵢ + yᵢ₊₁) / 2] × (tᵢ₊₁ - tᵢ)

The final Rust Severity (FRS): FRS is the last disease severity scores in modified Cobb’s scale.

Where:

y_i and y_i+1 are the disease severities at time points t_i and t_i+1, respectively.

n is the total number of observations.

t represents the time (in days) between disease assessments.

AUDPC provides a cumulative measure of disease intensity over the assessment period and is widely used to compare genotypes for partial resistance.

rAUDPC (%) : \frac{AUDPC value of a genotye}{AUDPC of local or the most susceptible genotype} \times 100

2.6. Agronomic Data

Days to 50% heading: the number of days from planting to the time when 50% of plants showed head on plot basis,

Thousand kernel weights (TKW): the weight of thousand kernels sampled at random from the total grains harvested from each experimental plot was measured.

Grain yield (GY): Grain yield in grams per plot was recorded and translated to Kg per ha.

2.7. Data Analysis

All measured quantitative parameters including Coefficient of infection (CI), Final Rust severity (FRS), Area Under Disease Progressive Curve (AUDPC), Disease progress rate (r-value), Relative of Area Under Disease Progressive curve (rAUDPC), yield and yield related parameters were subjected to descriptive analysis.

3. Results and Discussion

3.1. Seedling Response to Eleven Wheat Stem Rust Pathotypes

The infection responses of 100 bread wheat genotypes evaluated against eleven Puccinia graminis f. sp. tritici (Pgt) races are summarized in Figure 2. Across all seedling assays, the susceptible control cultivar McNair 701 consistently exhibited compatible infection types (ITs) ranging from 3 to 4 against all eleven Pgt races, confirming the effectiveness of the inoculation and the virulence of the pathotypes.

The high levels of infection achieved in each experiment enabled reliable scoring of ITs across all genotypes. A wide range of variation was observed in the genotypic responses to the stem rust races (Figure 3), indicating substantial genetic diversity in resistance.

Based on their IT scores, genotypes were classified into three categories: resistant, susceptible, and heterogeneous (Figure 2). The majority of genotypes displayed resistant reactions, with IT scores of 1 or 2. However, a significant number of genotypes were susceptible to race TTKTF, followed by TKPTF, which notably affected several popular wheat varieties.

Among the tested races, TTKTT induced the lowest infection types on some bread wheat genotypes, suggesting the presence of effective resistance genes against this race. Conversely, the highest ITs were recorded for other races, highlighting differential virulence patterns and genotype-specific responses.

Download: Download full-size image

Figure 2. Seedling Infection Responses of Bread Wheat Genotypes to Eleven Stem Rust Races.

Download: Download full-size image

Figure 3. Seedling Responses of Bread Wheat Genotypes to Multiple Stem Rust Pathotypes.

3.2. Classification of Stem Rust Resistance in Bread Wheat Genotypes

3.2.1. Group I: Genotypes Resistant to All Isolates

Two bread wheat genotypes demonstrated resistance to all eleven Puccinia graminis f. sp. tritici (Pgt) races evaluated at the seedling stage (Table 4). These genotypes consistently exhibited low infection types (ITs), indicating the presence of effective resistance mechanisms.

Table 4. Bread Wheat Genotypes Showing Resistance to All Eleven Pgt Races at Seedling Stage.

SN	TTKTT	TTTTF	TKTTF	TTKSK	JRCQC	TRTTF	TKKTF	TTRTF	TTKTF	TKPTF	RRTTF	Ag_sr	SIN_SR
40	;1	2	2-	;1	2-	;1	2+	;1+	;1+	2+	2+	Trs	5ms
56	;1	;1	2-	;1	;1	;1	;1+	;1+	2-	;1+	;1	Trs	5ms

To accurately postulate the underlying stem rust resistance genes in these lines, further testing with additional Pgt isolates exhibiting diverse virulence profiles is required. Moreover, the use of near-isogenic lines carrying known Sr genes would enhance the precision of gene postulation and help identify the specific resistance genes present in these genotypes.

3.2.2. Group II: Bread Wheat Genotypes Lacking Effective Resistance Genes

Seedling evaluation revealed that all Puccinia graminis f. sp. tritici (Pgt) races produced high infection types on one particular bread wheat breeding line, comparable to the universally susceptible check cultivar McNair 701 (Table 5). This consistent susceptibility across all races indicates the absence of effective seedling resistance in this genotype.

In total, seven genotypes were classified in this group, all exhibiting high infection types to the eleven Pgt races tested. These lines are presumed to lack known stem rust resistance genes and may serve as susceptible checks or baselines in future resistance screening efforts (Table 2).

Table 5. Bread Wheat Genotypes Showing Susceptibility to all Pgt Races at Seedling Stage.

SN	TTKTT	TTTTF	TKTTF	TTKSK	JRCQC	TRTTF	TKKTF	TTRTF	TTKTF	TKPTF	RRTTF
2	3-	3-	3-	3-	3-	3	4	3	3-	3-	3
3	3-	3	3-	3-	3	2+	4	3-	3-	3-	3
12	3-	3-	3	3-	3	3	3+	3+	3-	3	3
13	3-	3-	3-	3-	3-	3	3	3-	3-	3	3
43	3	3-	3	3-	3-	3	3	3	3	3	3
91	3-	3	3	3-	3	3+	3	3	3	3	3+
98	3-	3-	3-	3	3-	3	3	3-	3-	3	3-

3.3. Slow Rusting of Wheat Stem Rust Resistance

The AUPC is one of the indicators of slow-wheat stem rusting at field conditions

[24]

. At Sinana tested site the tested wheat genotypes were categorized into two distinct groups for wheat stem rust slow-rusting resistance, based on the AUDPC values. Wheat genotypes that exhibited AUDPC values less than 300 ranging from 5 to 290 showed a high level of partial or slow-rusting resistance to wheat stem rust, consisting of 30 bread wheat genotypes. However, in this tested location, high AUDPC values of more than 300 ranged from 301 to 540, indicating low slow-rusting or low partial resistance. This study was similarly discussed with

[13]

the evaluation of wheat genotypes for slow-rusting resistance to leaf and stem rust diseases which distinguished into low partial resistance and high wheat slow stem rusting on the bases of AUDPC.

Table 6. The Identified High Partial Resistance of Wheat Stem Rust on 30 the Bread Wheat Genotypes During 2022 Main Cropping Season.

Geno	TTKTT	Sin_FRS	Ag_FRS	AUDPC	GY (Kg/ha)	Geno	TTKTT	Sin_FRS	Ag_FRS	AUDPC	GY (Kgha)
2	3-	5s	15s	94	2336.25	70	3	15s	20s	120	2530
3	3-	20s	25s	280	915	72	3-	5s	20s	116	2393.75
13	3-	10s	10s	175	1301.25	77	3-	10s	20s	120	3006.25
15	3-	10s	15s	139	1911.25	79	3-	5ms	20s	116	3408.75
17	2+	20s	20s	123	375	82	3-	5ms	25s	145	1791.25
22	3-	10s	25s	133	1765	84	3-	10s	15s	95	2087.5
35	3	5s	10ms	59	1126.25	86	3-	5s	25s	141	3283.75
37	3-	trs	10ms	58	1177.5	91	3-	5s	15s	91	1957.5
39	3-	trms	10ms	40	2298.75	92	3	5s	20s	124	1231.25
43	3	15s	20s	275	1983.75	93	3-	trmss	20s	108	1762.5
47	3-	15s	20s	100	2528.75	94	3-	trmss	15s	200	1830
51	2+	5s	10ms	61	3042.5	95	3-	5ms	15s	200	1597.5
55	3-	10s	15s	137	2007.5	96	3-	10mss	20s	225	1400
62	3-	15s	20s	108	1776.25	97	3-	trms	15s	180	1275
65	3-	15s	15s	94	1567.5	98	3-	5ms	10ms	65	2268.75

*Gntp= Genotype; TTKTT= Race; Sin_FRS= Sinana Final Rust Severity; Ag_FRS= Agarfa Final Rust Severity; AUDPC = Area under Disease Progress Curve; GY=Grain Yield

3.4. Relationship Between Wheat Stem Rust Traits and Yield Parameters

Pearson’s correlation analysis revealed a highly significant positive correlation (p < 0.001) among key slow-rusting parameters of wheat stem rust, as presented in Table 3. At the Agarfa site during the 2021/22 main cropping season, the correlation coefficient between Coefficient of Infection (CI) and Area Under Disease Progress Curve (AUDPC) was r = 0.80, indicating a strong and consistent association between these two epidemiological traits.

This strong correlation suggests that genotypes with higher CI values also tend to accumulate greater disease pressure over time, as reflected by higher AUDPC values. These findings align with the observations of

[14]

, who noted that slow-rusting parameters such as CI and AUDPC reliably reflect the rate of disease development and are associated with components of partial resistance, including low receptivity, longer latent periods, and smaller pustule size.

Similar results have been reported by

[21, 20]

, and

[2]

, further supporting the utility of these parameters in identifying genotypes with durable, non-race-specific resistance.

Table 7. Pearson’s Correlation Coefficients Between Stem Rust Epidemiological Parameters and Yield-Related Traits at Agarfa (2022 Main Season).

	CI-II	CI-III	CI-IV	CI-V	AUDPC	DH	DM	Stand	PH	Yield	TKW
CI-II	1.00
CI-III	0.80	1.00
CI-IV	0.72	0.85	1.00
CI-V	0.08	0.24	0.30	1.00
AUDPC	0.57	0.74	0.79	0.80	1.00
DH	-0.31	-0.34	-0.25	0.13	-0.10	1.00
DM	-0.16	-0.07	-0.12	-0.03	-0.09	0.10	1.00
Stand	-0.22	-0.25	-0.20	0.06	-0.10	0.30	0.11	1.00
PH	0.13	0.24	0.12	0.00	0.11	-0.13	-0.03	-0.01	1.00
Yield	-0.21	-0.20	-0.21	-0.07	-0.18	0.28	0.16	0.48	-0.02	1.00
TKW	-0.02	-0.06	-0.14	-0.28	-0.24	-0.04	0.07	0.09	0.14	0.46	1.00

CI= correlation coefficients; DH=Days Heading; DM= Days Maturity; PH= plant height TKW=Thousand Kernel weighty; AUDPC = Area under Disease Progress Curve

Table 8. Pearson’s Correlations Between Stem Rust Epidemiological Parameters and Yield-Related Traits at Sinana (2022 Main Cropping Season).

	CIV	DH (no)	DM (no)	Std (no)	PH (cm)	Yld (kg)	TKW (g)	SL (cm)	SPS (no)	Tlr (no)	SP (no)
CIV	1
DH	-0.01	1
DM	-0.05	0.34	1
Stand	-0.06	0.21	0.01	1
PH	-0.02	-0.07	-0.03	0.31	1
Yield	-0.18	0.24	0.02	0.43	0.37	1
TKW	-0.27	0.09	-0.04	0.11	0.32	0.61	1
SL	0.02	0.15	0.05	-0.01	0.11	0.2	0.24	1
SS	-0.11	0.27	0.15	-0.03	0.02	0.04	-0.02	0.24	1
Tiller	0.07	0.05	-0.07	-0.03	-0.03	-0.07	0	0.04	0.09	1
SSP	0.11	0.25	0.08	0.28	0.14	0.33	0.17	0.21	0.2	-0.03	1

CI= correlation coefficients; DH=Days Heading; DM= Days

4. Conclusion and Recommendations

Seedling resistance was observed in several advanced wheat lines and cultivars. Seven lines showed resistance to all eleven races, while 68 lines had varied reactions. Lines with single-gene race-specific resistance are recommended for crossing programs. Those with high infection types should be used in adult plant resistance studies.

Abbreviations

AARC	Ambo Agricultural Research Center
CRD	Completely Randomized Design
Pgt	Puccinia Graminis Tritici
CI	Coefficient Infection
IT	Infection Iype
AUDPC	Area Under Disease Progress Curve
FRS	Final Rust Severity
LIT	Low Infection Type
HIT	High Infection Type

Acknowledgments

The author gratefully acknowledges the Oromia Agricultural Research Institute for financial support, and Sinana Agricultural Research Center for providing logistical assistance. Special thanks are extended to the Plant Pathology Research team and technical assistants for their valuable contribution to data collection.

Author Contributions

Tamene Mideksa: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Software, Writing – original draft

Zerihun Eshetu: Data curation, Formal Analysis, Investigation, Software

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix

Table A1. Plant Materials Used in the Study.Plant Materials Used in the Study.Plant Materials Used in the Study.

No	Cross Name
1	MUCUY
2	ATTILA2/PBW652//KACHU/6/BECARD #1/5/KIRITATI/4/2SERI.1B2/3/KAUZ*2/BOW//KAUZ
3	BORL14/ABLEU
4	BORL14/ABLEU
5	ABLEU//KACHU/DANPHE
6	SUP152*2/BECARD//KACHU/DANPHE
7	HUW234+LR34/PRINIA//INQALAB 912/KUKUNA/3/FRET22/SHAMA/4/2BECARD//ND643/2WBLL1
8	KACHU//WBLL12/BRAMBLING2/6/BECARD #1/5/KIRITATI/4/2SERI.1B2/3/KAUZ*2/BOW//KAUZ
9	KACHU//WBLL12/BRAMBLING2/6/BECARD #1/5/KIRITATI/4/2SERI.1B2/3/KAUZ*2/BOW//KAUZ
10	FRNCLN2/TECUE #12/3/ATTILA2/PBW652//MURGA
11	ABLEU*2/BORL14
12	ABLEU*2/BORL14
13	SUP1522/TECUE #1//2ABLEU
14	PAURAQ/VILLA JUAREZ F20092/4/WBLL1/FRET2//PASTOR2/3/MURGA
15	BECARD/CHYAK/3/2PBW3432/KUKUNA*2//FRTL/PIFED
16	ATTILA/3BCN//BAV92/3/PASTOR/4/TACUPETO F20012/BRAMBLING/5/PAURAQ2/6/FRNCLN2/TECUE #1
17	WBLL4/KUKUNA//WBLL1/3/WBLL12/BRAMBLING/4/2PCAFLR/KINGBIRD #1//KIRITATI/2*TRCH
18	BORL14//KACHU/KIRITATI
19	BORL14//KACHU/KIRITATI
20	KACHU/DANPHE//KFA/2*KACHU
21	KACHU/DANPHE//KFA/2*KACHU
22	KACHU/DANPHE//KFA/2*KACHU
23	KACHU//KIRITATI/2TRCH/3/KFA/2KACHU
24	ND643/2WBLL1/4/WHEAR/KUKUNA/3/C80.1/3BATAVIA//2*WBLL1/5/BORL14
25	SUP152/2*DANPHE #1//BORL14
26	SUP152/2*DANPHE #1//BORL14
27	KRONSTAD F2004/KENYA SUNBIRD//WHEAR/KRONSTAD F2004/3/WBLL12/BRAMBLING2//BAVIS
28	KENYA SUNBIRD/2KACHU/3/SWSR22T.B./2BLOUK #1//WBLL1*2/KURUKU
29	PFAU/MILAN/5/CHEN/AEGILOPS SQUARROSA (TAUS)//BCN/3/VEE#7/BOW/4/PASTOR/6/2*BAVIS #1/7/BORL14
30	WHEAR/KUKUNA/3/C80.1/3BATAVIA//2WBLL1*2/4/NIINI #1/5/KACHU/DANPHE
31	BECARD//ND643/2*WBLL1/3/KACHU/DANPHE
32	KFA/2KACHU2//MUTUS*2/CHONTE
33	KACHU//KIRITATI/WBLL1*2/3/TAITA
34	ATTILA/3BCN//BAV92/3/PASTOR/4/TACUPETO F20012/BRAMBLING/5/PAURAQ*2/6/SUP152/KENYA SUNBIRD
35	KACHU/BECARD//WBLL12/BRAMBLING2/3/VILLA JUAREZ F2009/DANPHE #1
36	ND643/2TRCH//BECARD/3/BECARD2/4/MUU/FRNCLN
37	WBLL12/BRAMBLING//WBLL12/SHAMA/3/WBLL12/BRAMBLING2/6/KAUZ//ALTAR 84/AOS/3/PASTOR/4/873.97/5/MUNAL #1
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Mideksa, T., Eshetu, Z. (2025). Evaluation of Adult Plant Resistance in Bread Wheat (Triticum aestivum L.) Genotypes to Wheat Stem Rust (Puccinia graminis f. sp. tritici) Races in Ethiopia. American Journal of Plant Biology, 10(4), 121-132. https://doi.org/10.11648/j.ajpb.20251004.16

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Mideksa, T.; Eshetu, Z. Evaluation of Adult Plant Resistance in Bread Wheat (Triticum aestivum L.) Genotypes to Wheat Stem Rust (Puccinia graminis f. sp. tritici) Races in Ethiopia. Am. J. Plant Biol. 2025, 10(4), 121-132. doi: 10.11648/j.ajpb.20251004.16

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AMA Style

Mideksa T, Eshetu Z. Evaluation of Adult Plant Resistance in Bread Wheat (Triticum aestivum L.) Genotypes to Wheat Stem Rust (Puccinia graminis f. sp. tritici) Races in Ethiopia. Am J Plant Biol. 2025;10(4):121-132. doi: 10.11648/j.ajpb.20251004.16

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@article{10.11648/j.ajpb.20251004.16,
  author = {Tamene Mideksa and Zerihun Eshetu},
  title = {Evaluation of Adult Plant Resistance in Bread Wheat (Triticum aestivum L.) Genotypes to Wheat Stem Rust (Puccinia graminis f. sp. tritici) Races in Ethiopia},
  journal = {American Journal of Plant Biology},
  volume = {10},
  number = {4},
  pages = {121-132},
  doi = {10.11648/j.ajpb.20251004.16},
  url = {https://doi.org/10.11648/j.ajpb.20251004.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajpb.20251004.16},
  abstract = {A field experiment was conducted during the 2021 main cropping season using an augmented design to evaluate adult plant resistance in bread wheat genotypes against wheat stem rust (Puccinia graminis f. sp. tritici) in Ethiopia. Final rust severity (FRS), coefficient of infection (CI), and relative area under the disease progress curve (rAUDPC) were used to identify slow rusting genotypes. These parameters proved reliable for assessing resistance. Eleven Pgt races were tested on 20 near-isogenic lines carrying single stem rust resistance genes. Greenhouse results showed seven lines were resistant to all races. Genotypes were grouped based on infection types: Group I (e.g., genotypes 40 and 56) showed low infection types (ITs); Group II (e.g., genotypes 2, 3, 12, 13, 43, 91, 98) showed high ITs; Group III included 68 lines with variable reactions. TTKTF and TKPTF caused the highest ITs, while TTKTT showed the lowest. Thirty slow rusting genotypes were identified based on field FRS (Trace MS to 25 MS) and seedling ITs (2+ to 4). These cultivars offer valuable genetic resources for wheat improvement programs targeting durable resistance to stem rust. These findings demonstrate the importance of combining field-based slow rusting parameters with greenhouse race-specific evaluations to obtain a comprehensive understanding of resistance. The identification of genotypes with stable resistance across multiple environments provides a strong foundation for breeding programs aimed at durable stem rust resistance. Such cultivars are particularly valuable in Ethiopia, where stem rust epidemics pose a recurring threat to wheat production and national food security. This study contributes to the global effort of developing improved wheat varieties by offering genetic resources that can be integrated into international breeding pipelines. By highlighting both race-specific and slow rusting resistance, the research underscores the need for continuous monitoring of pathogen variability and the deployment of diverse resistance genes to ensure long-term effectiveness.},
 year = {2025}
}

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TY - JOUR
T1 - Evaluation of Adult Plant Resistance in Bread Wheat (Triticum aestivum L.) Genotypes to Wheat Stem Rust (Puccinia graminis f. sp. tritici) Races in Ethiopia
AU - Tamene Mideksa
AU - Zerihun Eshetu
Y1 - 2025/12/29
PY - 2025
N1 - https://doi.org/10.11648/j.ajpb.20251004.16
DO - 10.11648/j.ajpb.20251004.16
T2 - American Journal of Plant Biology
JF - American Journal of Plant Biology
JO - American Journal of Plant Biology
SP - 121
EP - 132
PB - Science Publishing Group
SN - 2578-8337
UR - https://doi.org/10.11648/j.ajpb.20251004.16
AB - A field experiment was conducted during the 2021 main cropping season using an augmented design to evaluate adult plant resistance in bread wheat genotypes against wheat stem rust (Puccinia graminis f. sp. tritici) in Ethiopia. Final rust severity (FRS), coefficient of infection (CI), and relative area under the disease progress curve (rAUDPC) were used to identify slow rusting genotypes. These parameters proved reliable for assessing resistance. Eleven Pgt races were tested on 20 near-isogenic lines carrying single stem rust resistance genes. Greenhouse results showed seven lines were resistant to all races. Genotypes were grouped based on infection types: Group I (e.g., genotypes 40 and 56) showed low infection types (ITs); Group II (e.g., genotypes 2, 3, 12, 13, 43, 91, 98) showed high ITs; Group III included 68 lines with variable reactions. TTKTF and TKPTF caused the highest ITs, while TTKTT showed the lowest. Thirty slow rusting genotypes were identified based on field FRS (Trace MS to 25 MS) and seedling ITs (2+ to 4). These cultivars offer valuable genetic resources for wheat improvement programs targeting durable resistance to stem rust. These findings demonstrate the importance of combining field-based slow rusting parameters with greenhouse race-specific evaluations to obtain a comprehensive understanding of resistance. The identification of genotypes with stable resistance across multiple environments provides a strong foundation for breeding programs aimed at durable stem rust resistance. Such cultivars are particularly valuable in Ethiopia, where stem rust epidemics pose a recurring threat to wheat production and national food security. This study contributes to the global effort of developing improved wheat varieties by offering genetic resources that can be integrated into international breeding pipelines. By highlighting both race-specific and slow rusting resistance, the research underscores the need for continuous monitoring of pathogen variability and the deployment of diverse resistance genes to ensure long-term effectiveness.
VL - 10
IS - 4
ER -

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Tamene Mideksa

Sinana Agricultural Research Center, Bale Robe, Ethiopia

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http://orcid.org/0000-0003-1001-6076
Zerihun Eshetu

Sinana Agricultural Research Center, Bale Robe, Ethiopia

http://orcid.org/0000-0002-3958-5339

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Mideksa, T., Eshetu, Z. (2025). Evaluation of Adult Plant Resistance in Bread Wheat (Triticum aestivum L.) Genotypes to Wheat Stem Rust (Puccinia graminis f. sp. tritici) Races in Ethiopia. American Journal of Plant Biology, 10(4), 121-132. https://doi.org/10.11648/j.ajpb.20251004.16

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Mideksa, T.; Eshetu, Z. Evaluation of Adult Plant Resistance in Bread Wheat (Triticum aestivum L.) Genotypes to Wheat Stem Rust (Puccinia graminis f. sp. tritici) Races in Ethiopia. Am. J. Plant Biol. 2025, 10(4), 121-132. doi: 10.11648/j.ajpb.20251004.16

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AMA Style

Mideksa T, Eshetu Z. Evaluation of Adult Plant Resistance in Bread Wheat (Triticum aestivum L.) Genotypes to Wheat Stem Rust (Puccinia graminis f. sp. tritici) Races in Ethiopia. Am J Plant Biol. 2025;10(4):121-132. doi: 10.11648/j.ajpb.20251004.16

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@article{10.11648/j.ajpb.20251004.16,
  author = {Tamene Mideksa and Zerihun Eshetu},
  title = {Evaluation of Adult Plant Resistance in Bread Wheat (Triticum aestivum L.) Genotypes to Wheat Stem Rust (Puccinia graminis f. sp. tritici) Races in Ethiopia},
  journal = {American Journal of Plant Biology},
  volume = {10},
  number = {4},
  pages = {121-132},
  doi = {10.11648/j.ajpb.20251004.16},
  url = {https://doi.org/10.11648/j.ajpb.20251004.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajpb.20251004.16},
  abstract = {A field experiment was conducted during the 2021 main cropping season using an augmented design to evaluate adult plant resistance in bread wheat genotypes against wheat stem rust (Puccinia graminis f. sp. tritici) in Ethiopia. Final rust severity (FRS), coefficient of infection (CI), and relative area under the disease progress curve (rAUDPC) were used to identify slow rusting genotypes. These parameters proved reliable for assessing resistance. Eleven Pgt races were tested on 20 near-isogenic lines carrying single stem rust resistance genes. Greenhouse results showed seven lines were resistant to all races. Genotypes were grouped based on infection types: Group I (e.g., genotypes 40 and 56) showed low infection types (ITs); Group II (e.g., genotypes 2, 3, 12, 13, 43, 91, 98) showed high ITs; Group III included 68 lines with variable reactions. TTKTF and TKPTF caused the highest ITs, while TTKTT showed the lowest. Thirty slow rusting genotypes were identified based on field FRS (Trace MS to 25 MS) and seedling ITs (2+ to 4). These cultivars offer valuable genetic resources for wheat improvement programs targeting durable resistance to stem rust. These findings demonstrate the importance of combining field-based slow rusting parameters with greenhouse race-specific evaluations to obtain a comprehensive understanding of resistance. The identification of genotypes with stable resistance across multiple environments provides a strong foundation for breeding programs aimed at durable stem rust resistance. Such cultivars are particularly valuable in Ethiopia, where stem rust epidemics pose a recurring threat to wheat production and national food security. This study contributes to the global effort of developing improved wheat varieties by offering genetic resources that can be integrated into international breeding pipelines. By highlighting both race-specific and slow rusting resistance, the research underscores the need for continuous monitoring of pathogen variability and the deployment of diverse resistance genes to ensure long-term effectiveness.},
 year = {2025}
}

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SN	TTKTT	TTTTF	TKTTF	TTKSK	JRCQC	TRTTF	TKKTF	TTRTF	TTKTF	TKPTF	RRTTF	Ag_sr	SIN_SR
40	;1	2	2-	;1	2-	;1	2+	;1+	;1+	2+	2+	Trs	5ms
56	;1	;1	2-	;1	;1	;1	;1+	;1+	2-	;1+	;1	Trs	5ms

SN	TTKTT	TTTTF	TKTTF	TTKSK	JRCQC	TRTTF	TKKTF	TTRTF	TTKTF	TKPTF	RRTTF
2	3-	3-	3-	3-	3-	3	4	3	3-	3-	3
3	3-	3	3-	3-	3	2+	4	3-	3-	3-	3
12	3-	3-	3	3-	3	3	3+	3+	3-	3	3
13	3-	3-	3-	3-	3-	3	3	3-	3-	3	3
43	3	3-	3	3-	3-	3	3	3	3	3	3
91	3-	3	3	3-	3	3+	3	3	3	3	3+
98	3-	3-	3-	3	3-	3	3	3-	3-	3	3-

SN	TTKTT	TTTTF	TKTTF	TTKSK	JRCQC	TRTTF	TKKTF	TTRTF	TTKTF	TKPTF	RRTTF	Ag_sr	SIN_SR
40	;1	2	2-	;1	2-	;1	2+	;1+	;1+	2+	2+	Trs	5ms
56	;1	;1	2-	;1	;1	;1	;1+	;1+	2-	;1+	;1	Trs	5ms

SN	TTKTT	TTTTF	TKTTF	TTKSK	JRCQC	TRTTF	TKKTF	TTRTF	TTKTF	TKPTF	RRTTF
2	3-	3-	3-	3-	3-	3	4	3	3-	3-	3
3	3-	3	3-	3-	3	2+	4	3-	3-	3-	3
12	3-	3-	3	3-	3	3	3+	3+	3-	3	3
13	3-	3-	3-	3-	3-	3	3	3-	3-	3	3
43	3	3-	3	3-	3-	3	3	3	3	3	3
91	3-	3	3	3-	3	3+	3	3	3	3	3+
98	3-	3-	3-	3	3-	3	3	3-	3-	3	3-

SN	TTKTT	TTTTF	TKTTF	TTKSK	JRCQC	TRTTF	TKKTF	TTRTF	TTKTF	TKPTF	RRTTF	Ag_sr	SIN_SR
40	;1	2	2-	;1	2-	;1	2+	;1+	;1+	2+	2+	Trs	5ms
56	;1	;1	2-	;1	;1	;1	;1+	;1+	2-	;1+	;1	Trs	5ms

SN	TTKTT	TTTTF	TKTTF	TTKSK	JRCQC	TRTTF	TKKTF	TTRTF	TTKTF	TKPTF	RRTTF
2	3-	3-	3-	3-	3-	3	4	3	3-	3-	3
3	3-	3	3-	3-	3	2+	4	3-	3-	3-	3
12	3-	3-	3	3-	3	3	3+	3+	3-	3	3
13	3-	3-	3-	3-	3-	3	3	3-	3-	3	3
43	3	3-	3	3-	3-	3	3	3	3	3	3
91	3-	3	3	3-	3	3+	3	3	3	3	3+
98	3-	3-	3-	3	3-	3	3	3-	3-	3	3-