Search Results (176)

In this study, the reactions of 70 bread wheat varieties released in Türkiye to five prevalent Pst races, including the Yr5-virulent PSTr-27, were evaluated. Reaction tests of wheat varieties to all races revealed PSTr-27 as the most aggressive race, followed by PSTr-31, PSTr-28, PSTr-29, and PSTr-30. Notably, only seven varieties (Kıraç 66, İkizce 96, Dinç, Altındane, Ziyabey 98, Bayraktar 2000, and Shiro) exhibited moderately resistant reactions to PSTr-27, while the remaining varieties were susceptible. The presence of nine important resistance (Yr) genes in these varieties was also screened at the molecular level. Yr5, Yr15, and Yr26 genes were not detected in any of the varieties and Yr10 and YrSP genes were each detected in only one variety, while the other genes were detected in different ratios. Molecular screening showed that 19 varieties with no resistance genes used in this study displayed susceptible reactions; however, ten varieties that did not carry any resistance genes showed resistant reactions to one or more races, suggesting the presence of unknown or novel resistance sources. Furthermore, gene combinations, particularly Yr10 + Yr18, significantly provided resistance to all Pst races studied. These findings highlight that continual monitoring of PSTr-27, and other Pst races is needed, since it can be a serious threat to wheat production in Türkiye and neighboring countries. Full article

Accurate and timely assessment of crop disease severity is crucial for effective management strategies and ensuring sustainable agricultural production. Traditional visual disease scoring methods are subjective and labor-intensive, highlighting the need for automated, objective alternatives. This study evaluates the effectiveness of a model for field-based identification and quantification of stripe rust severity in wheat using red, green, blue RGB imaging. Based on crop reflectance hyperspectra (CRHS) acquired using a FieldSpec ASD spectroradiometer, two complementary approaches were developed. In the first approach, we estimate single leaf disease severity (LDS) under laboratory conditions, while in the second approach, we assess crop disease severity (CDS) from field-based RGB images. The high accuracy of both methods enabled the development of a predictive model for estimating LDS from CDS, offering a scalable solution for precision disease monitoring in wheat cultivation. The experiment was conducted on four winter wheat plots subjected to varying fungicide treatments to induce different levels of stripe rust severity for model calibration, with treatment regimes ranging from no application to three applications during the growing season. RGB images were acquired in both laboratory conditions (individual leaves) and field conditions (nadir and oblique perspectives), complemented by hyperspectral measurements in the 350–2500 nm range. To achieve automated and objective assessment of disease severity, we developed custom image-processing scripts and applied Random Forest classification and regression models. The models demonstrated high predictive performance, with the combined use of nadir and oblique RGB imagery achieving the highest classification accuracy (97.87%), sensitivity (100%), and specificity (95.83%). Oblique images were more sensitive to early-stage infection, while nadir images offered greater specificity. Spectral feature selection revealed that wavelengths in the visible (e.g., 508–563 nm and 621–703 nm) and red-edge/SWIR regions (around 1556–1767 nm) were particularly informative for disease detection. In classification models, shorter wavelengths from the visible range proved to be more useful, while in regression models, longer wavelengths were more effective. The integration of RGB-based image analysis with the Random Forest algorithm provides a robust, scalable, and cost-effective solution for monitoring stripe rust severity under field conditions. This approach holds significant potential for enhancing precision agriculture strategies by enabling early intervention and optimized fungicide application. Full article

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), represents a major global threat to wheat (Triticum aestivum. L). Planting varieties with adult-plant resistance (APR) is an effective approach for long-term management of this disease. The Chinese winter wheat variety Lantian 25 exhibits moderate-to-high APR against stripe rust under field conditions. To investigate the genetic basis of APR in Lantian 25, a set of 219 F₆ recombinant inbred lines (RILs) was created from a cross between Lantian 25 (resistant parent) and Huixianhong (susceptible parent). These RILs were assessed for maximum disease severity (MDS) in Pixian of Sichuan and Qingshui of Gansu over the 2020–2021 and 2021–2022 growing seasons, resulting in data from four different environments. Genotyping was performed on these lines and their parents using the wheat Illumina 50K single-nucleotide polymorphism (SNP) arrays. Composite interval mapping (CIM) identified six quantitative trait loci (QTL), named QYr.gaas-2BS, QYr.gaas-2BL, QYr.gaas-2DS, QYr.gaas-2DL, QYr.gaas-3BS and QYr.gaas-4BL, which were consistently found across two or more environments and explained 4.8–12.0% of the phenotypic variation. Of these, QYr.gaas-2BL, QYr.gaas-2DS, and QYr.gaas-3BS overlapped with previous studies, whereas QYr.gaas-2BS, QYr.gaas-2DS, and QYr.gaas-4BL might be novel. All the resistance alleles for these QTL originated from Lantian 25. Furthermore, four kompetitive allele-specific PCR (KASP) markers, Kasp_2BS_YR (QYr.gaas-2BS), Kasp_2BL_YR (QYr.gaas-2BL), Kasp_2DS_YR (QYr.gaas-2DS) and Kasp_2DL_YR (QYr.gaas-2DL), were developed and validated in 110 wheat diverse accessions. Additionally, we identified seven candidate genes linked to stripe rust resistance, including disease resistance protein RGA2, serine/threonine-protein kinase, F-box family proteins, leucine-rich repeat family proteins, and E3 ubiquitin-protein ligases. These QTL, along with their associated KASP markers, hold promise for enhancing stripe rust resistance in wheat breeding programs. 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

Wheat (Triticum aestivum L.) is the world’s most indispensable staple crop and a vital source of food for human diet. Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), constitutes a severe threat to wheat production and in severe cases, the crop fails completely. Anmai1350 (AM1350) is moderately resistant to leaf rust and powdery mildew, and highly susceptible to sheath blight and fusarium head blight. We found that the length and area of mycelium in AM1350 cells varied at different time points of Pst infection. To investigate the molecular mechanism of AM1350 resistance to Pst, we performed transcriptome sequencing (RNA-seq). In this study, we analyzed the transcriptomic changes of the seedling leaves of AM1350 at different stages of Pst infection at 0 h post-infection (hpi), 6 hpi, 24 hpi, 48 hpi, 72 hpi, and 120 hpi through RNA-seq. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) was used to validate RNA-seq data. It was determined that there were differences in the differentially expressed genes (DEGs) of AM1350, and the upregulation and downregulation of the DEGs changed with the time of infection. At different time points, there were varying degrees of enrichment in the response pathways of AM1350, such as the ”MAPK signaling pathway–plant”, the “plant–pathogen interaction” pathway and other pathways. After Pst infected AM1350, the reactive oxygen species (ROS) content gradually increases. The ROS is toxic to Pst, promotes the synthesis of phytoalexins, and inhibits the spread of Pst. As a result, AM1350 shows resistance to Pst race CYR34. The main objective of this study is to provide a better understanding for resistance mechanisms of wheat in response to Pst infections and to avoid production loss. 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

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

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

The segmentation of plant disease images enables researchers to quantify the proportion of disease spots on leaves, known as disease severity. Current deep learning methods predominantly focus on single diseases, simple lesions, or laboratory-controlled environments. In this study, we established and publicly released image datasets of field scenarios for three diseases: soybean bacterial blight (SBB), wheat stripe rust (WSR), and cedar apple rust (CAR). We developed Plant Disease Segmentation Networks (PDSNets) based on LinkNet with ResNet-18 as the encoder, including three versions: ×1.0, ×0.75, and ×0.5. The ×1.0 version incorporates a 4 × 4 embedding layer to enhance prediction speed, while versions ×0.75 and ×0.5 are lightweight variants with reduced channel numbers within the same architecture. Their parameter counts are 11.53 M, 6.50 M, and 2.90 M, respectively. PDSNetx0.5 achieved an overall F1 score of 91.96%, an Intersection over Union (IoU) of 85.85% for segmentation, and a coefficient of determination (R²) of 0.908 for severity estimation. On a local central processing unit (CPU), PDSNetx0.5 demonstrated a prediction speed of 34.18 images (640 × 640 pixels) per second, which is 2.66 times faster than LinkNet. Our work provides an efficient and automated approach for assessing plant disease severity in field scenarios. Full article

Wheat (Triticum aestivum L.) is a primary crop globally. Among the numerous pathogens affecting wheat production, Puccinia striiformis f. sp. tritici (Pst) is a significant biotic stress agent and poses a major threat to world food security by causing stripe rust or yellow rust disease. Understanding the molecular basis of plant–pathogen interactions is crucial for developing new means of disease management. It is well established that the effector proteins play a pivotal role in pathogenesis. Therefore, studying effector proteins has become an important area of research in plant biology. Our previous work identified differentially expressed candidate secretory effector proteins of stripe rust based on transcriptome sequencing data from susceptible wheat (Avocet S) and resistant wheat (Avocet YR10) infected with Pst. Among the secreted effector proteins, PSTG_14090 contained an ancient double-psi beta-barrel (DPBB) fold, which is conserved in the rare lipoprotein A (RlpA) superfamily. This study investigated the role of PSTG_14090 in plant immune responses, which encodes a protein, here referred to as Pst-DPBB, having 131 amino acids with a predicted signal peptide (SP) of 19 amino acids at the N-terminal end, and the DNA sequence of this effector is highly conserved among different stripe rust races. qRT-PCR analysis indicated that expression levels are upregulated during the early stages of infection. Subcellular localization studies in Nicotiana benthamiana leaves and wheat protoplasts revealed that it is distributed in the cytoplasm, nucleus, and apoplast. We demonstrated that Pst-DPBB negatively regulates the immune response by functioning in various compartments of the plant cells. Based on Co-IP and structural predictions and putative interaction analyses by AlphaFold 3, we propose the probable biological function(s). Pst-DPBB behaves as a papain inhibitor of wheat cysteine protease; Pst-DPBB has high structural homology to kiwellin, which is known to interact with chorismate mutase, suggesting that Pst-DPBB inhibits the native function of the host chorismate mutase involved in salicylic acid synthesis. The DPBB fold is also known to interact with DNA and RNA, which may suggest its possible role in regulating the host gene expression. Full article