Rust Severity Research Articles

Integrated management of wheat stem rust (Puccinia graminis f. sp. tritici) through host resistance and inorganic salts foliar sprays

Wheat stem rust disease is threatening the production of wheat in Ethiopia. The experiment was conducted to evaluate the integrated effects of wheat varieties and inorganic salt foliar sprays to manage wheat stem rust on three wheat varieties, one susceptible (Morocco), one moderately resistant (Tay) and one resistant variety (Hoggana) at Adet and Aneded in 2018 cropping season. The experiment was laid out in a randomised complete block design with a factorial arrangement in three replications. Wheat stem rust caused by Puccinia graminis f. sp. tritici was significantly (p < 0.05) controlled by the sprays of potassium carbonate at the rate of 15 g l−1 concentration at both locations. The study results showed that the lowest rust severity, the area under the disease progress curve and slower disease progress rate occurred on the resistant and moderately resistant varieties sprayed with Tilt 250 EC and followed by potassium carbonate than on the susceptible variety with Tilt 250 EC, potassium carbonate and/or with potassium bicarbonate at both locations. Potassium carbonate reduced the disease severity without any significant difference to the recommended fungicide Tilt 250 EC at the rate of 1.5 l ha−1 on Hoggana variety at Aneded, which showed us potassium carbonate can be used as an alternative option to manage stem rust in wheat. Potassium carbonate foliar spray reduced relative grain yield loss by 36.05 and 3.9% at Adet whereas 28.5 and 2.03% at Aneded on the Hoggana compared to the varieties Morocco and Tay, respectively, which is comparable to Tilt 250 EC. In conclusion, when growing moderately resistant wheat varieties, potassium carbonate may be used in place of commercially recommended fungicide Tilt 250 EC yielding comparable results.

English

Production of wheat in Ethiopia is under danger from wheat stem rust, which is brought on by the disease Puccinia graminis f.sp. tritici and has resulted in a yield loss of 100%. An investigation was conducted in a hotspot area (Debere Zeit, Ethiopia) to evaluate the status of Ethiopian durum wheat cultivars for their level of stem rust resistance in the field. During the main seasons of 2017, 2020, and 2021, 34 durum wheat varieties with three susceptibility checks were examined. Terminal Rust Severity (TRS), Coefficient of Infection (CI) and Area under Disease Progress Curve (AUDPC) were used to measure stem rust field resistance. Analysis of all disease parameters was carried out using R studio. Due to their low levels of AUDPC, ACI, and TRS values combined with MR infection type, two commercial varieties (Oda and Tob-66) may have a significant resistance gene(s) and seven varieties (Boohie, Kilinto, Ginchi, Robe, Toltu, Lelisso, and Bekelcha) showed a moderate level of field resistance with MR to MRMS responses and may have adult plant resistance mediated by minor resistance genes. Stem rust was found to affect 73.5% of the Ethiopian durum cultivars. Therefore, this study suggests that the national breeding effort should focus on local durum cultivars rather than the ones that were imported. Key words: Field resistance, durum wheat, stem rust, Puccinia graminis f.sp tritici.

Advanced epidemiology of wheat stem rust: disease occurrence and progression

An advanced insight into wheat stem rust progress curves is mainly needed by breeders and pathologists to improve accuracy and specificity of estimates of disease occurrence and development. It is necessary to identify certain disease curve elements for characterization of high variations in stem rust progress across different wheat cropping systems. A number of standard curves were fitted to a four-season data on stem rust severity to determine more predictive disease progress curve elements for wheat cultivars sown at different times. Exponential curve provided the best fitted parameters to be used as wheat stem rust progress curve elements. Sowing date and cultivar resistance significantly affected area under disease progress curve (AUDPC), maximum disease severity, and exponential parameter b. Mean AUDPC for early and late sowing dates were greater in susceptible cultivars (Bahar, Chamran II, Parsi and Sivand) than in resistant (Baharan and Pishtaz) and semi-resistant (Pishgam and Sirwan) cultivars. In semi-resistant cultivars, AUDPC increased by 37.44% at late sowings. Principal component analysis detected contributions of AUDPC, disease onset, maximum disease severity, and two exponential parameters in disease progression. This new understanding helps to achieve more accurate outcomes for future disease measurements for wheat breeding and wheat stem rust management programs.

Diagrammatic scale for rust severity assessment in broad bean (Vicia faba)

&lt;p&gt;&lt;em&gt;Uromyces viciae-fabae&lt;/em&gt; has increased in economic importance in broad bean-producing regions of central Mexico. It is therefore convenient to have a standardized system to quantify its severity. The objective of this study was to generate and validate a diagrammatic scale to evaluate the severity of rust on broad bean leaves. We collected infected broad bean leaves with different degrees of damage from commercial crops in the Valle de Toluca and the southeastern region of Mexico State. One hundred and ten leaves representing the disease were taken and group discrimination was carried out to select the ranking visually. Then, the leaves were scanned and evaluated to obtain the real severity value for each leaf using the software ©ASSESS 2.0. A six-class diagrammatic scale was generated: 0 (0.0), 1 (&amp;gt;0.1-6.0), 2 (&amp;gt;6.1-12.0), 3 (&amp;gt;12.1-24.0), 4 (&amp;gt;24.1-56.0) y 5(&amp;gt;56.1-&amp;lt;100), and the exactitude, precision, and reproducibility of its estimations were verified. Fifty-eight leaves were evaluated by 20 evaluators without previous knowledge of the disease; the results obtained were analyzed using simple linear regression. In the initial selection evaluation, average r² values of 0.738 were obtained, without scale, while for the evaluation where the proposed scale was used, the average was 0.93, which confirms adequate levels of accuracy and reproducibility that the proposed scale can provide, for this disease.&lt;/p&gt;

DETERMINATION OF RELATIONSHIP OF ENVIRONMENTAL FACTORS WITH STRIPE RUST IN WHEAT

Changes in climate scenario affect natural conditions in farming system, hence affect plant pests and diseases development. Universally, adverse effects of climate changes namely failing the ecosystem apparatuses that control the balance of plant pests and diseases, failing the plant resistance and the development of environmental situation supportive plant pests and diseases growth in general. The disposed cultivars and favorable ecological circumstances play part towards rust diseases in epidemic form. In this study meteorological data and disease incidence data were correlated to establish relationship between environmental variables and stripe rust development. Linear correlation was established among minimum and maximum air temperature and development of rust was positive. Impact of relative humidity could not be assessed because variation in range between minimum and maximum mean relative humidity remained non-significant during the period under study. However, data generated seems insufficient to conclude authentic result to determine the role of relative humidity in stripe rust development. Three genotypes having different responses against stripe rust were studied to correlate the response of yellow rust with epidemiological factors (temperature, relative moisture, and precipitation). Impact of meteorological factors indicated that environment significantly affected disease incidence and severity of yellow rust through its impact on development rate of the pathogen. Same cultivars responded differentially under unlike meteorological conditions.

Application of thermal and visible imaging to estimate stripe rust disease severity in wheat using supervised image classification methods

Reliable and accurate estimation of plant disease severity at the field scale is a key factor for predicting yield losses, disease management and food security. A field experiment was designed and conducted during 2017–18 and 2018–19 with 24 wheat cultivars to estimate the stripe rust severity by supervised classification of thermal and visible images using parallelepiped, minimum distance, mahalanobis distance, maximum likelihood, support vector machine and neural network methods of image classification. Results demonstrated the potential of thermal and visible imaging techniques to estimate wheat stripe rust severity with good accuracy. For both visible and thermal images used in this study, support vector machine gave the best estimates of the rust severity, while the parallelepiped method was the worst-performing method. Support vector machine and neural network methods showed d-index, Nash-Sutcliffe efficiency and coefficient of determination values above 85%, with accuracies above 98% and kappa coefficient above 0.97 for both thermal and visible images. Comparison of thermal and visible image classification performance revealed that for all the methods except support vector machine, the estimated rust severity, overall accuracy and kappa coefficient of thermal images were better than visible images. The present study clearly showed that both thermal and visible image analysis can be applied as a rapid non-destructive technique to estimate the wheat rust severity under field conditions. The study also provided a comparative insight into thermal and visible image classification methods that have great potential for sustainable plant disease management in modern agriculture.

Integrating a Bacillus-based product with fungicides by foliar application to protect soybean: a sustainable approach to avoid exclusive use of chemicals.

Biological control is widely applied against soybean (Glycine max L.) soil-borne pathogens by furrow or seed treatments. The efficiency of bioproducts and timing of application by foliar sprays against soybean pathogens needs to be more fully understood. This work investigated the efficiency of foliar application with a Bacillus subtilis-based product (BBP) to protect soybean from multiple pathogens and the best moment to apply it considering its compatibility with fungicides. Foliar applications (from stages V6 to R4) with BBP, mancozeb (M) and systemic fungicides (S) applied against Asian rust (Phakopsora pachyrhizi), BBP followed by S (BBP-S), BBP along with S (S + BBP), S along with M (S + M) or water were carried out in a soybean field for two years. The treatments S + BBP, S + M and BBP-S reduced the severity of Asian rust by 82% compared to the control. Except for M, all treatments reduced the severity of other foliar diseases by >60%. The defoliation was reduced by BBP and BBP-S, whereas the yield was 25% higher than control by using BBP, S + M, S + BBP or BBP-S. Also, the incidence of Fusarium sp. was significantly reduced on seeds from treatments BBP and BBP-S. The compatibility tests in Petri dishes demonstrated that all fungicides decreased the bacterial growth when applied along with BBP, whereas previous applications of BBP did not reduce the bacterial growth. The BBP protected soybean against multiple pathogens, reduced defoliation and promoted soybean yield similarly to conventional fungicides, but in general, the early application of the BBP was the most efficient protection. © 2022 Society of Chemical Industry.

Epistatic interaction effect between chromosome 1BL (Yr29) and a novel locus on 2AL facilitating resistance to stripe rust in Chinese wheat Changwu 357-9.

Four stable QTL for adult plant resistance were identified in wheat line Changwu 357-9, including a new QTL on 2AL showing significant interaction with Yr29 to reduce stripe rust severity. Stripe rust (yellow rust) is a serious disease of bread wheat (Triticum aestivum L.) worldwide. Genetic resistance is considered the most economical, effective and environmentally friendly method to control the disease and to minimize the use of fungicides. The current study focused on characterizing the components of stripe rust resistance and understanding the interactions in Changwu 357-9 (CW357-9)/Avocet S RIL population. A genetic linkage map constructed using a new GenoBaits Wheat 16K Panel and the 660K SNP array had 5104 polymorphic SNP markers spanning 3533.11cM. Four stable QTL, consistently identified across five environments, were detected on chromosome arms 1BL, 2AL, 3DS, and 6BS in Changwu357-9. The most effective QTL QYrCW357-1BL was Yr29. The 6BS QTL was identified as Yr78, which has been combined with the 1BL QTL in many wheat cultivars and breeding lines. The novel QTL on 2AL with moderate effect showed a stable and significant epistatic interaction with Yr29. The QTL on 3DL should be same as QYrsn.nwafu-3DL and enriches the overall stripe rust resistance gene pool for breeding. Polymorphisms of flanking AQP markers AX-110020417 (for QYrCW357-1BL), AX-110974948 (for QYrCW357-2AL), AX-109466386 (for QYrCW357-3DL), and AX-109995005 (for QYrCW357-6BS) were evaluated in a diversity panel including 225 wheat cultivars and breeding lines. These results suggested that these high-throughput markers could be used to introduce QYrCW357-1BL, QYrCW357-2AL, QYrCW357-3DL, and QYrCW357-6BS into commercial wheat cultivars. Combinations of these genes with other APR QTL should lead to higher levels of stripe rust resistance along with the beneficial effects of multi-disease resistance gene Yr29 on improving resistance to other diseases.

Classification of Southern Corn Rust Severity Based on Leaf-Level Hyperspectral Data Collected under Solar Illumination

Maize is one of the most important crops in China, and it is under a serious, ever-increasing threat from southern corn rust (SCR). The identification of wheat rust based on hyperspectral data has been proved effective, but little research on detecting maize rust has been reported. In this study, full-range hyperspectral data (350~2500 nm) were collected under solar illumination, and spectra collected under solar illumination (SCUSI) were separated into several groups according to the disease severity, measuring height and leaf curvature (the smoothness of the leaf surface). Ten indices were selected as candidate indicators for SCR classification, and their sensitivities to the disease severity, measuring height and leaf curvature, were subjected to analysis of variance (ANOVA). The better-performing indices according to the ANOVA test were applied to a random forest classifier, and the classification results were evaluated by using a confusion matrix. The results indicate that the PRI was the optimal index for SCR classification based on the SCUSI, with an overall accuracy of 81.30% for mixed samples. The results lay the foundation for SCR detection in the incubation period and reveal potential for SCR detection based on UAV and satellite imageries, which may provide a rapid, timely and cost-effective detection method for SCR monitoring.

Yield losses in wheat genotypes caused by stripe rust (Puccinia striifarmis f. sp. tritici) in North Delta, Egypt

Stripe (yellow) rust disease caused by Puccinia striifarmis f. sp. tritici, is a catastrophic wheat disease in wheat-growing regions around the world. The objective of this study was to investigate potential sources of stripe rust resistance and the yield loss of forty local wheat varieties at four locations in Egypt (Sakha, Mutubas, Qillin and Biyala), under yellow rust disease pressure compared to ‘Morroco’ variety, as control. To determine slow rusting in the field, the following parameters were recorded: final rust severity (FRS%), average coefficient of infection (ACI), relative resistance index (RRI) and reduction % in the 1000 kernel weight. The severity was higher in the second season than in the first. Seven wheat genotypes (‘Shaka 62’, ‘Shaka 9, ‘Shaka 95’, ‘Gemmiza 7’, ‘Sids 14’ and ‘Misr 3’) showed the high level of resistance, and FRS% values ranged from 0 to 20 moderately resistant (MR) during first season and achieved the least value of loss in TKW (1.28%) with ‘Misr 3’. Meanwhile, four genotypes (‘Sakha 93’, ‘Sakha 95’, ‘Sids 14’ and ‘Gim. 7’) remained highly resistant during the second season and identified to have good level of slow rusting resistance, which these genotypes showed FRS% values ranged from 5R to 30 moderately resistant-moderately susceptible (MRMS), ACI values ≤12, RRI values ≥6 and the loss % in TKW not exceed 12.54%. On the other hand, the lines; ‘Shaka 69’, ‘Shaka 88’, ‘Shaka 92’, ‘Giza 160’, ‘Giza 163’, ‘Gem 11’, ‘Sids 2’ and ‘Sids 6’ exhibited complete susceptibility at the four tested sites, recorded FRS% values &gt;50. Meanwhile, cv. ‘Gem 11’ in 2018/2019 recorded the highest level of ACI ≥55, the lowest level of RRI≤4.05 and the highest loss% in TKW reached 40.69%. These findings could be used in the national wheat breeding program for stripe rust resistance in Egypt.

Interactions Between Lr67 or Lr34 and Other Leaf Rust Resistance Genes in Wheat (Triticum aestivum).

The wheat multi-pest resistance genes Lr67 and Lr34 are similar in that they both condition resistance to many diseases, in a non-race-specific manner, and code for cellular transporters. Lr34 plays a critical role in breeding wheat for disease resistance in large part because it interacts with other resistance genes to result in effective and durable resistance. To determine if Lr67 interacts with other resistance genes in a similar manner as Lr34 six different doubled haploid populations were developed which segregated for either Lr67 or Lr34 along with a second resistance gene, either Lr13, Lr16, or Lr32. The presence or absence of each of these genes in the progeny lines was determined by molecular marker analysis. These six populations were tested for leaf rust field resistance in the same environments to compare the effects of Lr34 and Lr67 alone, and in combination with Lr13, Lr16 or Lr32. Lr67 and Lr34 significantly reduced the levels of rust severity, Lr34 showed a significant interaction with Lr13 but Lr67 did not. Both genes interacted with Lr16, and Lr67 had a significant interaction with Lr32. This analysis demonstrates the similar effect of Lr67, as seen with Lr34, on the interaction with other resistance genes to give a better level of resistance than with single resistance genes. While Lr67 is not widely deployed in agriculture, it could play an important role in disease resistance in future wheat cultivars.

Elevated Ozone Concentration and Nitrogen Addition Increase Poplar Rust Severity by Shifting the Phyllosphere Microbial Community.

Tropospheric ozone and nitrogen deposition are two major environmental pollutants. A great deal of research has focused on the negative impacts of elevated O3 and the complementary effect of soil N addition on the physiological properties of trees. However, it has been overlooked how elevated O3 and N addition affect tree immunity in face of pathogen infection, as well as of the important roles of phyllosphere microbiome community in host–pathogen–environment interplay. Here, we examined the effects of elevated O3 and soil N addition on poplar leaf rust [Melampsora larici-populina] severity of two susceptible hybrid poplars [clone ‘107’: Populus euramericana cv. ‘74/76’; clone ‘546’: P. deltoides Í P. cathayana] in Free-Air-Controlled-Environment plots, in addition, the link between Mlp-susceptibility and changes in microbial community was determined using Miseq amplicon sequencing. Rust severity of clone ‘107’ significantly increased under elevated O3 or N addition only; however, the negative impact of elevated O3 could be significantly mitigated when accompanied by N addition, likewise, this trade-off was reflected in its phyllosphere microbial α-diversity responding to elevated O3 and N addition. However, rust severity of clone ‘546’ did not differ significantly in the cases of elevated O3 and N addition. Mlp infection altered microbial community composition and increased its sensitivity to elevated O3, as determined by the markedly different abundance of taxa. Elevated O3 and N addition reduced the complexity of microbial community, which may explain the increased severity of poplar rust. These findings suggest that poplars require a changing phyllosphere microbial associations to optimize plant immunity in response to environmental changes.

Identification and Validation of a Major Quantitative Trait Locus for Adult Plant Resistance Against Leaf Rust From the Chinese Wheat Landrace Bai Qimai.

Leaf rust caused by Puccinia triticina Eriks. (Pt) is a common disease of wheat worldwide. The Chinese wheat landrace Bai Qimai (BQM) has shown high resistance to leaf rust for a prolonged period of time; the infected leaves of BQM displayed high infection types (ITs), but they showed low disease severities at the adult plant stage. To find quantitative trait loci (QTL) for resistance to leaf rust, 186 recombinant inbred lines from the cross Nugaines × BQM were phenotyped for leaf rust response in multiple field environments under natural Pt infections and genotyped using the 90K wheat single nucleotide polymorphism (SNP) chip and simple sequence repeat (SSR) markers. A total of 2,397 polymorphic markers were used for QTL mapping, and a novel major QTL (QLr.cau-6DL) was detected on chromosome 6DL from BQM. The effectiveness of QLr.cau-6DL was validated using the three additional wheat populations (RL6058 × BQM, Aikang58 × BQM, and Jimai22 × BQM). QLr.cau-6DL could significantly reduce leaf rust severities across all tested environments and different genetic backgrounds, and its resistance was more effective than that of Lr34. Moreover, QLr.cau-6DL acted synergistically with Lr34 to confer strong resistance to leaf rust. We believe that QLr.cau-6DL should have high potential value in the breeding of wheat cultivars with leaf rust resistance.

Adult plant leaf rust resistance QTL derived from wheat line CI13227 maps to chromosomes 2AL, 4BS, and 7AL.

The winter wheat (Triticum aestivum L.) line CI13227 has been characterized as having adult plant resistance to leaf rust caused by Puccinia triticina Eriks (Pt). Line CI13227 was crossed with the susceptible spring wheat 'Thatcher' (Tc) and a Tc*2/CI13227 F6 line with adult plant leaf rust resistance designated as 411A was derived. Line 411A was crossed with Tc to develop an F6 recombinant inbred line (RIL) population. The parents and 120 F6 lines were assessed for leaf rust severity at the flag leaf stage in five field plot tests from 2011 through 2015 and were genotyped for single-nucleotide polymorphism (SNP) markers with the Illumina iSelect 90K wheat bead array. A total of 2,384 SNP markers segregated among the RILs. Completely linked SNPs were removed, and 474 markers that covered 2,605 centimorgans (cM) were used for linkage map construction. Quantitative trait loci (QTL) on chromosome 2AL with logarithm of odds (LOD) values 2.34-7.88, on chromosome 4BS with LOD values 1.35- 4.66, and on chromosome 7AL with LOD values 2.92-7.81 were associated with significant reduction in leaf rust severity in the field plot tests. Recombinant inbred lines that had combinations of two or three of the QTL had significantly lower leaf rust severity than RILs that lacked any resistance QTL. Kompetitive allele specific polymerase chain reaction (KASP) markers were developed for the SNPs that were closely linked with the three QTL to facilitate marker-based selection of the leaf rust resistance in breeding programs.

Evaluation of Pakistani wheat germplasm for leaf rust resistance at various locations.

341 entries comprising of 250 genotypes/lines and 91 gene differentials were tested for leaf rust (Puccinia triticina Erik) in different ecological zones of Punjab during 2016–17 and 2017–18. Each entry was planted in a single 1 m long row and Morocco was used as a spreader. Data on leaf rust severity was recorded once in 3rd week of March during both study years at all locations by following Modified Cobb Scale while the data was recorded three times on 2nd, 22nd and 29th March during 2018 at Faisalabad location to study rust development pattern. The disease severity ranged from 0-100S during 2016–17 and from 0-80S during 2017–18. The genotype HYT 60–5 and the genes Lr-19, Lr-26 and Lr 27+31 showed no disease symptoms at any location during both the study years. These genes can be used for future breeding material development. Area under disease progressive curve (AUDPC), calculated on the basis of periodical readings from Faisalabad, ranged from 0–550 and the susceptible check Morocco has AUDPC value of 600. 120 entries including HYT 60–5 have disease progression 0, which showed that there may be a major gene based resistance in these entries. Area under disease progressive curve/Day (AUDPC/DAY) was calculated for the rest of 130 genotypes to have an understanding of the disease progression pattern and out of which 43 entries have AUDPC/Day value ranging from 1–2 and 28 entries have AUDPC/Day value ranging from 2–3 which revealed that these entries are very useful for use in breeding for durable rust resistance and can be utilized as a parent in back cross and top cross breeding schemes. Material with AUDPC value less than 10 is the best source of resistance against the leaf rust. Varieties/advanced lines, Ujala-16, V-14154, and V-14124 have shown slow rust development and are very good sources of resistance. Similarly, HYT 60–5 has proven an excellent source of resistance. The advance line V-14154 has been approved as a commercial cultivar by the name “Akbar-19”.

Wheat Yellow Rust Severity Detection by Efficient DF-UNet and UAV Multispectral Imagery

Crop disease seriously affects production because of its highly destructive property. Wheat under different levels of disease infection should be treated by various chemical strategies to enable a precision plant protection. Therefore, a fast and robust algorithm for wheat yellow rust disease severity determination is highly desirable for its sustainable management. The recent use of remote sensing and deep learning is drawing increasing research interests in wheat yellow rust severity detection at leaf level. However, little reviews take field-scale rust severity detection into account by using UAV multispectral images and deep learning networks. As a result, by the means of UAV multispectral images, a real-time yellow rust detection algorithm named Efficient Dual Flow UNet (DF-UNet) to detect different levels of yellow rust is designed and proposed in this paper to meet practical requirements. First, pruning strategy is utilized to realize a lightweight structure. Second, the Sparse Channel Attention (SCA) Module is designed to increase the receptive field of the network and enhance the ability to distinguish each category. Third, by fusing SCA, a novel dual flow branch model with segmentation and ranking branch based on UNet is proposed to accomplish yellow rust severity determination at field scale. The comparative results show that the proposed method reduces more than half computation load and achieves the highest overall accuracy score among other state-of-the-art deep learning models. It is convinced that the proposed DF-UNet can pave the way for automated yellow rust severity detection at farmland scales in a robust way.

QTL mapping for adult plant field resistance to stripe rust in the AAC Cameron/P2711 spring wheat population

AbstractStripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a devastating disease of wheat (Triticum aestivum L.). Deployment of resistant wheat cultivars is one of the best strategies to mitigate disease‐associated risks. The genotype P2711 possesses effective stripe rust resistance under field conditions in western Canada, however, the genetic basis of this resistance is unknown. To identify resistance, a recombinant inbred line (RIL) population comprised of 252 RILs was developed from the cross AAC Cameron/P2711. This population was evaluated for stripe rust severity at the adult plant stage in Creston, BC (in 2018, 2019, and 2020) and Lethbridge, AB (in 2018 and 2020), and was genotyped using the wheat 90K iSelect single nucleotide polymorphism (SNP) assay. A high‐density genetic map comprised of 8,915 markers was constructed covering all the wheat chromosomes. Four resistance quantitative trait loci (QTLs) were contributed by P2711 and three from AAC Cameron. QYr.lrdc‐2A.1, corresponding to the Yr17 gene, was the most stable QTL and detected in four out of five environments, whereas QYr.lrdc‐2B was the second most stable QTL. These two QTL along with QYr.lrdc‐5A showed a significant reduction in stripe rust severity when present together. Where most of the QTLs detected in both locations, QYr.lrdc‐1A.1 and QYr.lrdc‐1A.2, both were detected only in Creston, BC. Stable QTLs on chromosome 2A, 2B, and 5A, and their closely associated markers identified in this study could be utilized in marker‐assisted selection for stripe rust resistant cultivar development.

Rate of stripe rust (Puccinia striiformis) on wheat in the highland and lowland area

Stripe (Yellow) rust caused by Puccinia striiformis f.sp. tritici (Pst) is a crucial wheat disease causing severe damage to cultivated susceptible wheat varieties. The wheat yellow rust assessment was conducted during the primary rainy season of 2018/19 at Ada’a, Lume, and Gimbichu using the zigzag disease assessment method. Disease data, agro-ecological data, and other essential parameters were recorded. The disease was prevalent in all districts by diverse incidence and severity ranges. This implies that yellow rust is distributed wheat disease at all surveyed potential districts. The highest yellow rust prevalence, 62.5% was recorded at Gimbichu district; conversely, the lowest prevalence 31.25% was recorded at Ada’a district. The highest severity and incidence of yellow rust 60% and 100%, respectively, was recorded at Ada’a district with susceptible reaction. In comparison, the lowest severity and incidence (30% and 5%) respectively were recorded at Lume districts with moderately sensitive responses. Many distributions and occurrences govern yellow rust. The highest incidence of yellow rust, namely 100% on land cultivated with kakaba and kubsa wheat bread varieties, occurred at the milk growth stage to the ripe stage. The local cultivar has shown the lowest incidence and severity percentage with moderately susceptible responses than improved varieties.

Losses caused by stem rust (Puccinia graminis f.sp tritici) on durum wheat in Ethiopia

Stem rust caused by Puccinia graminis f.sp. tritici is one of the major biotic constraints of wheat production. The disease may cause substantial quantitative and qualitative yield losses but much of the work in Ethiopia on this pathosystem focuses on quantitative yield loss of durum wheat. This work was carried out at Debre Zeit Agriculture Research Centre during 2015/16 and 2016/17 main and off-seasons. Hence the current study was conducted with the objectives to quantify the amount of loss in grain yield due to stem rust and assess the relationship between disease parameters, grain yield, and physical quality parameters of improved durum wheat varieties grown in Ethiopia. Artificial inoculation was performed using a mixture of different dominant stem rust races. There were treated and untreated plots by fungicide that serves as protected and unprotected plots, respectively. Disease severity was recorded each 10 days interval and area under disease progress curve (AUDPC), terminal severity, and coefficient of infection were calculated. The tested cultivars exhibited different disease severity levels, having a mean value of 6.7-76%. High values of area under disease progress curve (AUDPC) were detected on Hitossa, Utuba (1225.7, 585.9). Whereas the lowest values of yield loss were recorded on CVS. Mangudo and Utuba have the mean value of yield loss of 40.2 and 44.8%, respectively. The highest yield loss was observed on susceptible variety Hitosa showing the mean value of 70%. Correlation coefficients were tested between yield losses and values of AUDPC, final stem rust severity, coefficient of infection, and rate of infection of the tested cultivars. There were strong correlation coefficients among disease parameters (r=0.72-0.99). There was also a moderately strong negative correlation coefficient among disease parameters and yield, hectoliter weight, and 1000-kernel weight of the test cultivars (r= -0.53 to -0.81). The current study indicated that the application of Rex Duo can be used in minimizing yield losses caused by the stem rust disease of durum wheat. Therefore, supporting the released durum wheat cultivars with fungicide application is the most pertinent issue in Ethiopia as most of the durum wheat cultivars in farmers' hands were moderately susceptible to susceptible cultivars Pgt races.

Biocontrol of wheat leaf rust with redworm (Eisenia fetida) and its extracts: enhancing sustainable crop production

Leaf rust caused by Puccinia triticina is an important disease of wheat worldwide. Different experiments were conducted to determine efficacy of redworm and its extracts against leaf rust on wheat seedlings. The first experiment involved the use of vermicast and artificial soil as planting substrates, and living worms were introduced into soil for four months. This significantly influenced leaf rust severity, with the lowest severity recorded among inoculated plants grown in vermicast (12% severity), followed by soil pulverised with 30 worms (30%) and 20 worms (40%), while control had the highest rust severity (>70%). Second experiment watered the inoculated seedlings with the extracts (vermicast and vermiwash) which resulted into significant lower leaf rust severity of 35% and 53%, respectively while untreated plants had >85% disease severity. Vermicast, which had the highest leaf rust suppression, was further tested, whereby it reduced leaf rust infection up to 30% with increase in seedling shoot and root growth of 21% and 17%, respectively. Redworm enhances resistance to leaf rust infection on inoculated plant via increase in growth that suppresses rust development.