Search Results (249)

The fungal pathogen Puccinia striiformis f. sp. tritici, which causes yellow rust disease, poses a significant economic threat to wheat production not only in Uzbekistan but also globally, leading to substantial reductions in grain yield. This study aimed to develop yellow rust-resistance wheat lines by introgressing Yr10 and Yr15 genes into high-yielding cultivar Grom using the marker-assisted backcrossing (MABC) method. Grom was crossed with donor genotypes Yr10/6*Avocet S and Yr15/6*Avocet S, resulting in the development of F₁ generations. In the following years, the F₁ hybrids were advanced to the BC₂F₁ and BC₂F₂ generations using the MABC approach. Foreground and background selection using microsatellite markers (Xpsp3000 and Barc008) were employed to identify homozygous Yr10- and Yr15-containing genotypes. The resulting BC₂F₂ lines, designated as Grom-Yr10 and Grom-Yr15, retained key agronomic traits of the recurrent parent cv. Grom, such as spike length (13.0–11.9 cm) and spike weight (3.23–2.92 g). Under artificial infection conditions, the selected lines showed complete resistance to yellow rust (infection type 0). The most promising BC₂F₂ plants were subsequently advanced to homozygous BC₂F₃ lines harboring the introgressed resistance genes through marker-assisted selection. This study demonstrates the effectiveness of integrating molecular marker-assisted selection with conventional breeding methods to enhance disease resistance while preserving high-yielding traits. The newly developed lines offer valuable material for future wheat improvement and contribute to sustainable agriculture and food security. Full article

Yellow rust (Puccinia striiformis) is a common wheat disease that significantly reduces yields, particularly in seasons with cooler temperatures and frequent rainfall. Early detection is essential for effective control, especially in key wheat-producing regions such as Southern Dobrudja, Bulgaria. This study presents a UAV-based approach for detecting yellow rust using only RGB imagery and deep learning for pixel-based classification. The methodology involves data acquisition, preprocessing through histogram equalization, model training, and evaluation. Among the tested models, a UnetClassifier with ResNet34 backbone achieved the highest accuracy and reliability, enabling clear differentiation between healthy and infected wheat zones. Field experiments confirmed the approach’s potential for identifying infection patterns suitable for precision fungicide application. The model also showed signs of detecting early-stage infections, although further validation is needed due to limited ground-truth data. The proposed solution offers a low-cost, accessible tool for small and medium-sized farms, reducing pesticide use while improving disease monitoring. Future work will aim to refine detection accuracy in low-infection areas and extend the model’s application to other cereal diseases. Full article

Wheat leaf rust (Lr), caused by Puccinia triticina Eriks. (Pt), is one of the most important diseases affecting wheat production worldwide. Using resistant wheat cultivars is the most economic and environmentally friendly way to control leaf rust. The Chinese wheat cultivar Xinong1163-4 has shown good resistance to Lr in field trials. To identify the genetic basis of Lr resistance in Xinong1163-4, 195 recombinant inbred lines (RILs) from the Xinong1163-4/Thatcher cross were phenotyped for Lr severity in three environments: the 2017/2018, 2018/2019, and 2019/2020 growing seasons in Baoding, Hebei Province. Bulked segregant analysis and simple sequence repeat markers were then used to identify the quantitative trait loci (QTLs) for Lr adult plant resistance (APR) in the population. As a result, six QTLs were detected, designated as QLr.hbau-1BL.1, QLr.hbau-1BL.2, and QLr.hbau-1BL.3. These QTLs were predicted to be novel. QLr.hbau-4BL, QLr.hbau-4BL.1, and QLr.hbau-3A were identified at similar physical positions to previously reported QTLs. Based on chromosome positions and molecular marker testing, QLr.hbau-1BL.3 shares similar flanking markers with Lr46. Lr46 is a non-race-specific APR gene for leaf rust, stripe rust, and powdery mildew. Similarly, QLr.hebau-4BL showed resistance to multiple diseases, including leaf rust, stripe rust, Fusarium head blight, and powdery mildew. The QTLs identified in this study, as well as their closely linked markers, can potentially be used for marker-assisted selection in wheat breeding. Full article

Wheat stripe rust (Puccinia striiformis f. sp. tritici, Pst) resistance and agronomic traits are crucial determinants of wheat yield. Elucidating the quantitative trait loci (QTLs) associated with these essential traits can furnish valuable genetic resources for improving both the yield potential and disease resistance in wheat. Lantian 31 is an excellent Chinese winter wheat cultivar; multi-environment phenotyping across three ecological regions (2022–2024) confirmed stable adult-plant resistance (IT 1–2; DS < 30%) against predominant Chinese Pst races (CYR31–CYR34), alongside superior thousand-kernel weight (TKW) and kernel morphology. Here, we dissected the genetic architecture of these traits using a total of 234 recombinant inbred lines (RILs) derived from a cross between Lantian 31 and the susceptible cultivar Avocet S (AvS). Genotyping with a 15K SNP array, complemented by 660K SNP-derived KASP and SSR markers, identified four stable QTLs for stripe rust resistance (QYrlt.swust-1B, -1D, -2D, -6B) and eight QTLs governing plant height (PH), spike length (SL), and kernel traits. Notably, QYrlt.swust-1B (1BL; 29.9% phenotypic variance) likely represents the pleiotropic Yr29/Lr46 locus, while QYrlt.swust-1D (1DL; 22.9% variance) is the first reported APR locus on chromosome 1DL. A pleiotropic cluster on 1B (670.4–689.9 Mb) concurrently enhanced the TKW and the kernel width and area, demonstrating Lantian 31’s dual utility as a resistance and yield donor. The integrated genotyping pipeline—combining 15K SNP discovery, 660K SNP fine-mapping, and KASP validation—precisely delimited QYrlt.swust-1B to a 1.5 Mb interval, offering a cost-effective model for QTL resolution in common wheat. This work provides breeder-friendly markers and a genetic roadmap for pyramiding durable resistance and yield traits in wheat breeding programs. Full article

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), threatens global wheat production. Breeding resistant varieties is a key to disease control. In this study, 198 modern wheat varieties were phenotyped with the prevalent Pst races CYR33 and CYR34 at the seedling stage and with mixed Pst races at the adult-plant stage. Seven stable resistance varieties with infection type (IT) ≤ 2 and disease severity (DS) ≤ 20% were found, including five Chinese accessions (Zhengpinmai8, Zhengmai1860, Zhoumai36, Lantian36, and Chuanmai32), one USA accession (GA081628-13E16), and one Pakistani accession (Pa12). The genotyping applied a 55K wheat single-nucleotide polymorphism (SNP) array. A genome-wide association study (GWAS) identified 14 QTL using a significance threshold of p ≤ 0.001, which distributed on chromosomes 1B (4), 1D (2), 2B (4), 6B, 6D, 7B, and 7D (4 for CYR33, 7 for CYR34, 3 for mixed Pst races), explaining 6.04% to 18.32% of the phenotypic variance. Nine of these QTL were potentially novel, as they did not overlap with the previously reported Yr or QTL loci within a ±5.0 Mb interval (consistent with genome-wide LD decay). The haplotypes and resistance effects were evaluated to identify the favorable haplotype for each QTL. Candidate genes within the QTL regions were inferred based on their transcription levels following the stripe rust inoculation. These resistant varieties, QTL haplotypes, and favorable alleles will aid in wheat breeding for stripe rust resistance. Full article

Wheat stripe (yellow) rust, caused by the fungus Puccinia striiformis f. sp. tritici (Pst), is one of the most threatening wheat diseases worldwide. Monitoring the virulence of Pst population is essential for managing wheat stripe rust. In this study, 18 wheat Yr single-gene lines were used to identify the virulence patterns of 67 isolates collected from 13 provinces in China in 2020, from which 33 Pst races were identified. The frequency of virulence to different Yr genes varied from 1.49% to 97.01%, with 4.48% to Yr1, 26.87% to Yr6, 11.94% to Yr7, 95.52% to Yr8, 19.40% to Yr9, 11.94% to Yr17, 2.99% to Yr24, 35.82% to Yr27, 38.81% to Yr43, 97.01% to Yr44, 8.96% to YrSP, 1.49% to Yr85, 95.52% to YrExp2, and 7.46% to Yr76. None of the isolates were virulent to Yr5, Yr10, Yr15, and Yr32. Among the 33 races, PstCN-062 (with virulence to Yr8, Yr44, and YrExp2) and PstCN-001 (with virulence to Yr8, Yr43, Yr44, and YrExp2) were the prevalent races, with frequencies of 28.36% and 11.94%, respectively. These results provide valuable information for breeding resistant wheat cultivars for controlling stripe rust. Full article

Plant modeling uses mathematical and computational methods to simulate plant structures, physiological processes, and interactions with various environments. In precision agriculture, it enables the digital monitoring and prediction of crop growth, supporting better management and efficient resource use. Wheat, as a major global staple, is vital for food security. However, wheat stripe rust, a widespread and destructive disease, threatens yield stability. The paper proposes wheat cultivation suitability evaluation with stripe rust disease using an agriculture group consensus framework (WCSE-AGC) to tackle this issue. Assessing stripe rust severity in regions relies on wheat pathologists’ judgments based on multiple criteria, creating a multi-attribute, multi-decision-maker consensus problem. Limited regional coverage and inconsistent evaluations among wheat pathologists complicate consensus-reaching. To support wheat pathologist participation, this study employs artificial-intelligence-generated content (AIGC) techniques by using Claude 3.7 to simulate wheat pathologists’ scoring through role-playing and chain-of-thought prompting. WCSE-AGC comprises three main stages. First, a graph neural network (GNN) models trust propagation within wheat pathologists’ social networks, completing missing trust links and providing a solid foundation for weighting and clustering. This ensures reliable expert influence estimations. Second, integrating secretary bird optimization (SBO), K-means, and three-way clustering detects overlapping wheat pathologist subgroups, reducing opinion divergence and improving consensus inclusiveness and convergence. Third, a two-stage optimization balances group fairness and adjustment cost, enhancing consensus practicality and acceptance. The paper conducts experiments using publicly available real wheat stripe rust datasets from four different locations, Ethiopia, India, Turkey, and China, and validates the effectiveness and robustness of the framework through comparative and sensitivity analyses. Full article

Leaf rust (LR) is a devastating foliar disease that impacts common wheat (Triticum aestivum L.) globally. For optimal disease protection, wheat cultivars should possess adult plant resistance (APR) to leaf rust. In the current study, the objective was to map quantitative trait loci (QTL) related to leaf rust resistance. This was achieved by using 193 recombinant inbred line (RIL) populations which were developed from the cross between N. Strampelli and Huixianhong. Four trials were conducted in China (three in Baoding, Hebei province, and one in Zhoukou, Henan province) to assesses the leaf rust response of the RILs and parental lines. The wheat 660K SNP array and additional SSR markers were used to genotype the RIL populations. Through inclusive composite interval mapping (ICIM), three QTL related to leaf rust (LR) resistance were detected. ICIM was also employed to reevaluate previously published data in order to identify QTL with pleiotropic effects. To determine the physical positions, the flanking sequences of all SNP probes were compared against the Chinese Spring wheat reference sequence through BLAST searches. Three leaf rust resistance loci, two on chromosome 2A and 5B, were contributed by N. Strampelli. QLr.hbau-2AL.1 was detected in three leaf rust environments with phenotypic variance explained (PVE of 12.2–17%); QLr.hbau-2AL.2 was detected in two environments with 12.5–13.2% of the PVE; and QLr.hbau-5BL was detected in all leaf rust environments with phenotypic variance explained (PVE) of 17.8–19.1%. QLr.hbau-5BL exhibited potentially pleiotropic responses to multiple diseases. The QTL and the associated flanking markers discovered in this study could prove valuable for purposes such as fine mapping, the exploration of candidate genes, and marker-assisted selection (MAS). Full article

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a destructive disease of wheat worldwide. William Som (WS), an Argentinian spring wheat landrace, has consistently exhibited high-level resistance to stripe rust for over 20 years in our field evaluations in Washington state, USA. A previous study showed high-temperature adult-plant (HTAP) resistance in WS. To map the HTAP resistance quantitative trait loci (QTL) in WS, 114 F_5-8 recombinant inbred lines (RILs) from the cross AvS/WS were evaluated for their stripe rust response in seven field environments in Washington. The RILs and parents were genotyped with the Infinium 90K SNP chip. Four stable QTL, QYrWS.wgp-1BL on chromosome 1B (669–682 Mb), QyrWS.wgp-2AL on 2A (611–684 Mb), QyrWS.wgp-3AS on 3A (9–13 Mb), and QyrWS.wgp-3BL on 3B (476–535 Mb), were identified, and they explained 10.0–19.0%, 10.2–16.7%, 7.0–15.9%, and 12.0–27.8% of the phenotypic variation, respectively. The resistance in WS was found to be due to additive interactions of the four QTL. For each QTL, two Kompetitive allele-specific PCR (KASP) markers were developed, and these markers should facilitate the introgression of the HTAP resistance QTL into new wheat cultivars. Full article

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a highly destructive disease prevalent across most wheat-growing regions globally. The most effective strategy for combating this disease is through the exploitation of durable and robust resistance genes from the relatives of wheat. Thinopyrum intermedium (Host) Barkworth and D.R. Dewey has been widely hybridized with common wheat and has been shown to be a valuable source of genes, conferring resistance and tolerance against both the biotic and abiotic stresses affecting wheat. In this study, a novel wheat–Th. intermedium 2StS.2J^SL addition line, named Th93-1-6, which originated from wheat–Th. intermedium partial amphidiploid line, Th24-19-5, was comprehensively characterized using nondenaturing-fluorescence in situ hybridization (ND-FISH) and Oligo-FISH painting techniques. To detect plants with the transfer of resistance genes from Th93-1-6 to wheat chromosomes, 2384 M₁-M₃ plants from the cross between Th93-1-6 and the susceptible wheat cultivar MY11 were studied by ND-FISH using multiple probes. A total of 37 types of 2StS.2J^SL chromosomal aberrations were identified. Subsequently, 12 homozygous lines were developed to construct a cytological bin map. Ten chromosomal bins on the 2StS.2J^SL chromosome were constructed based on 84 specific molecular markers. Among them, eight alien chromosome aberration lines, which all contained the bin 2StS-3, showed enhanced stripe rust resistance. Consequently, the gene(s) for stripe rust resistance was physically mapped to the 92.88-155.32 Mb region of 2StS in Thinopyrum intermedium reference genome sequences v2.1. Moreover, these newly developed wheat–Th. intermedium 2StS.2J^SL translocation lines are expected to serve as valuable genetic resources in the breeding of rust-resistant wheat cultivars. Full article

Yellow rust is one of the most destructive fungal diseases affecting wheat, significantly reducing yield and grain quality. Early detection is crucial for effective plant protection and disease management. This study aims to develop and validate a methodology for early diagnosis of yellow rust using the Normalized Difference Vegetation Index (NDVI) derived from UAV-acquired spectral data. This research was conducted in an experimental wheat field near General Toshevo, Bulgaria, which is owned by the Dobrudja Agricultural Institute (DAI). A widely cultivated winter wheat variety, Enola, was monitored using UAV-based imaging, and the NDVI values were analyzed to assess the correlation between spectral reflectance and infection severity. The NDVI showed a moderate correlation as an indicator of pathogen-induced stress, with moderate predictive capability (R² = 51.4%) for assessing yellow rust infection severity. The results demonstrated that UAV-based NDVI analysis could effectively detect early-stage infections and monitor the spatial spread of the disease. The proposed methodology enables large-scale, non-invasive monitoring of wheat health, facilitating early disease detection. This approach can help optimize disease management strategies, although ground-based validation remains essential to distinguish between different stress factors affecting vegetation. Full article

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), poses a significant threat to wheat production in China. Previous epidemic studies have demonstrated the potential of high genetic diversity in the southwest regions of China. Among this epidemic region, the eastern Xizang (Tibet) region holds particular significance, as both wheat and barley crops are susceptible to Pst. However, limited information exists regarding the level of population genetic diversity, reproduction model, and migration patterns of the rust in eastern Xizang. The present study seeks to address this gap by analyzing 146 Pst isolates collected from the Basu, Zuogong, and Mangkang regions, genotyping by the 20K target Gene Array (Genobait). Our results showed relatively low genotypic diversity in the Basu region, while the highest genetic diversity was observed in the Mangkang area. Structural analysis revealed the abundance of admixed groups in Mangkang, which exhibited this population occurred due to sexual recombination between two different ancestor groups. Gene flow was observed between Zuogong and Basu populations, but it almost did not occur between Mangkang and Zuogong/Basu populations. This region is the world’s highest-altitude epidemic area, thus facilitating the evolution of the rust and possessing the potential to transmit newly evolved Pst races to lower wheat-growing regions. Implementing disease management strategies in this area is of potential importance to prevent the transmission of Pst races to other parts of Xizang, even neighboring regions possibly. This study facilitates our understanding of epidemiological and population genetic knowledge and the evolution of Pst in Xizang. Full article

Wheat stem rust, caused by Puccinia graminis f. sp. tritici, is a major disease that severely affects safe wheat production. The Huanghuai region plays a vital role in China’s wheat production and the wheat stem rust epidemic across China. However, due to China’s effective control measures, wheat stem rust rarely occurs in the region, resulting in little research on this disease, including the determination of resistance genes in cultivars and elite lines. For this purpose, this study utilized two predominant races (21C3CTHQM and 34MKGQM) of P. graminis f. sp. tritici to determine the resistance levels of 64 wheat cultivars in the Huanghuai wheat region. Additionally, molecular markers linked with Sr24, Sr25, Sr26, Sr31, and Sr38 were used to analyze the presence of these genes. The results indicated that among the 62 wheat cultivars and elite lines, 13 cultivars contained Sr31, four cultivars were detected to contain Sr38, and none contained Sr24, Sr25, or Sr26. Field tests in 2023 showed that three (4.8%) cultivars exhibited immunity to both races, while 20 (32.3%) and 23 (37.1%) cultivars showed resistance to moderate resistance, and 39 (62.9%) and 36 (58.1%) cultivars were moderately susceptible to susceptible. In 2024, one (1.6%) and four (6.5%) cultivars demonstrated immunity to both races, 22 (35.5%) and 23 (37.1%) cultivars showed resistance to moderate resistance, and 39 (62.9%) and 35 (56.5%) cultivars were moderately susceptible to susceptible. With over 50% of the cultivars displaying susceptibility, the overall resistance level was relatively low, indicating that stem rust outbreaks could recur if a sufficient inoculum is present. It is crucial to explore new resistance sources, discover novel resistance genes, and breed wheat cultivars with durable resistance and desirable agronomic traits to enhance the overall resistance to stem rust in Chinese wheat-growing regions. Full article

Lesion mimic phenotypes, characterized by leaf spots formed in the absence of pathogens or pests, are often associated with reactive oxygen species (ROS) accumulation and cell necrosis. This study identified a novel and stable homozygous spotted phenotype (HSP) from the F₈ population of common wheat (XN509 × N07216). The yellow spots that appeared at the booting stage were light-sensitive, and accompanied by cell necrosis and H₂O₂ accumulation. Compared with homozygous normal plants (HNPs), HSPs exhibited enhanced resistance to stripe rust and powdery mildew without compromising yield. RNA-Seq analysis at three stages revealed that differentially expressed genes (DEGs) between HSPs and HNPs were significantly enriched in KEGG pathways related to photosynthesis and photosynthesis-antenna proteins. GO analysis highlighted chloroplast and light stimulus-related down-regulated DEGs. Fine mapping identified TaSpl1 within a 0.91 Mb interval on chromosome 3DS, flanked by the markers KASP188 and KASP229, using two segregating populations comprising 1117 individuals. The candidate region contained 42 annotated genes, including 14 DEGs based on previous BSR-Seq data. PCR amplification and qRT-PCR verification identified the expression of TraesCS3D02G022100 was consistent with RNA-Seq data. Gene homology analysis and silencing experiments confirmed that TraesCS3D02G022100 was associated with stay-green traits. These findings provide new insights into the genetic regulation of lesion mimics, photosynthesis, and disease resistance in wheat. Full article

In an effort to enhance wheat’s resilience against rust diseases, our research explores the genetic underpinnings of resistance in a diverse collection of winter bread wheat accessions. Leaf rust (Puccinia triticina), yellow rust (Puccinia striiformis f. sp. tritici), and stem rust (Puccinia graminis f. sp. tritici) are significant threats to global wheat production. By leveraging host genetic resistance, we can improve disease management strategies. Our study evaluated 55 wheat accessions, including germplasm from Kazakhstan, from Uzbekistan, from Russia, from Kyrgyzstan, France, and CIMMYT under field conditions in southern Kazakhstan from 2022 to 2024. The results showed a robust resistance profile: 49.1% of accessions exhibited high to moderate resistance to leaf rust, 12.7% to yellow rust, and 30.9% to stem rust. Notably, ten accessions demonstrated resistance to multiple rust species, while seven showed resistance to two rusts. Twenty accessions were selected for further seedling resistance and molecular analysis. Three accessions proved resistant to six isolates of P. triticina, two to four isolates of P. striiformis, and four to five isolates of P. graminis. Although no genotypes were found to be universally resistant to all rust species at the seedling stage, two accessions—Bezostaya 100 (Russia) and KIZ 90 (Kazakhstan)—displayed consistent resistance to leaf and stem rust in both seedling and field evaluations. Molecular analysis revealed the presence of key resistance genes, including Lr1, Lr3, Lr26, Lr34, Yr9, Yr18, Sr31, Sr57, and the 1AL.1RS translocation. This work provides valuable insights into the genetic landscape of wheat rust resistance and contributes to the development of new wheat cultivars that can withstand these diseases, enhancing global food security. Full article