Proximal Phenotyping and Machine Learning Methods to Identify Septoria Tritici Blotch Disease Symptoms in Wheat.
Ontology highlight
ABSTRACT:
SUBMITTER: Odilbekov F
PROVIDER: S-EPMC5974968 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Producing quantitative and reliable measures of crop disease is essential for resistance breeding, but is challenging and time consuming using traditional phenotyping methods. Hyperspectral remote sensing has shown potential for the detection of plant diseases, but its utility for phenotyping large and diverse populations of plants under field conditions requires further evaluation. In this study, we collected canopy hyperspectral data from 335 wheat varieties using a spectroradiometer, and we investigated the use of canopy reflectance for detecting the Septoria tritici blotch (STB) disease and for quantifying the severity of infection. Canopy- and leaf-level infection metrics of STB based on traditional visual assessments and automated analyses of leaf images were used as ground truth data. Results showed (i) that canopy reflectance and the selected spectral indices show promise for quantifying STB infections, and (ii) that the normalized difference water index (NDWI) showed the best performance in detecting STB compared to other spectral indices. Moreover, partial least squares (PLS) regression models allowed for an improvement in the prediction of STB metrics. The PLS discriminant analysis (PLSDA) model calibrated based on the spectral data of four reference varieties was able to discriminate between the diseased and healthy canopies among the 335 varieties with an accuracy of 93% (Kappa = 0.60). Finally, the PLSDA model predictions allowed for the identification of wheat genotypes that are potentially more susceptible to STB, which was confirmed by the STB visual assessment. This study demonstrates the great potential of using canopy hyperspectral remote sensing to improve foliar disease assessment and to facilitate plant breeding for disease resistance.
| S-EPMC6108383 | biostudies-literature
Project description:Accurate, high-throughput phenotyping for quantitative traits is a limiting factor for progress in plant breeding. We developed an automated image analysis to measure quantitative resistance to septoria tritici blotch (STB), a globally important wheat disease, enabling identification of small chromosome intervals containing plausible candidate genes for STB resistance. 335 winter wheat cultivars were included in a replicated field experiment that experienced natural epidemic development by a highly diverse but fungicide-resistant pathogen population. More than 5.4 million automatically generated phenotypes were associated with 13,648 SNP markers to perform the GWAS. We identified 26 chromosome intervals explaining 1.9-10.6% of the variance associated with four independent resistance traits. Sixteen of the intervals overlapped with known STB resistance intervals, suggesting that our phenotyping approach can identify simultaneously (i.e., in a single experiment) many previously defined STB resistance intervals. Seventeen of the intervals were less than 5 Mbp in size and encoded only 173 genes, including many genes associated with disease resistance. Five intervals contained four or fewer genes, providing high priority targets for functional validation. Ten chromosome intervals were not previously associated with STB resistance, perhaps representing resistance to pathogen strains that had not been tested in earlier experiments. The SNP markers associated with these chromosome intervals can be used to recombine different forms of quantitative STB resistance that are likely to be more durable than pyramids of major resistance genes. Our experiment illustrates how high-throughput automated phenotyping can accelerate breeding for quantitative disease resistance.
| S-EPMC7706307 | biostudies-literature
Project description:BackgroundSeptoria tritici blotch is an important leaf disease of European winter wheat. In our survey, we analyzed Septoria tritici blotch resistance in field trials with a large population of 1,055 elite hybrids and their 87 parental lines. Entries were fingerprinted with the 9 k SNP array. The accuracy of prediction of Septoria tritici blotch resistance achieved with different genome-wide mapping approaches was evaluated based on robust cross validation scenarios.ResultsSeptoria tritici blotch disease severities were normally distributed, with genotypic variation being significantly (P < 0.01) larger than zero. The cross validation study revealed an absence of large effect QTL for additive and dominance effects. Application of genomic selection approaches particularly designed to tackle complex agronomic traits allowed to double the accuracy of prediction of Septoria tritici blotch resistance compared to calculation methods suited to detect QTL with large effects.ConclusionsOur study revealed that Septoria tritici blotch resistance in European winter wheat is controlled by multiple loci with small effect size. This suggests that the currently achieved level of resistance in this collection is likely to be durable, as involvement of a high number of genes in a resistance trait reduces the risk of the resistance to be overcome by specific pathogen isolates or races.
| S-EPMC4046654 | biostudies-literature
Project description:An association genetics analysis was conducted to investigate the genetics of resistance to Septoria tritici blotch, caused by the fungus Zymoseptoria tritici (alternatively Mycosphaerella graminicola), in cultivars and breeding lines of wheat (Triticum aestivum) used in the UK between 1860 and 2000. The population was tested with Diversity Array Technology (DArT) and simple-sequence repeat (SSR or microsatellite) markers. The lines formed a single population with no evidence for subdivision, because there were several common ancestors of large parts of the pedigree. Quantitative trait loci (QTLs) controlling Septoria resistance were postulated on 11 chromosomes, but 38% of variation was not explained by the identified QTLs. Calculation of best linear unbiased predictions (BLUPs) identified lineages of spring and winter wheat carrying different alleles for resistance and susceptibility. Abundant variation in Septoria resistance may be exploited by crossing well-adapted cultivars in different lineages to achieve transgressive segregation and thus breed for potentially durable quantitative resistance, whereas phenotypic selection for polygenic quantitative resistance should be effective in breeding cultivars with increased resistance. The most potent allele reducing susceptibility to Septoria, on chromosome arm 6AL, was associated with reduced leaf size. Genes which increase susceptibility to Septoria may have been introduced inadvertently into UK wheat breeding programmes from cultivars used to increase yield, rust resistance and eyespot resistance between the 1950s and 1980s. This indicates the need to consider trade-offs in plant breeding when numerous traits are important and to be cautious about the use of non-adapted germplasm.
| S-EPMC5297993 | biostudies-literature
Project description:During plant-pathogen interactions, pathogens secrete many rapidly evolving, small secreted proteins (SSPs) that can modify plant defense and permit pathogens to colonize plant tissue. The fungal pathogen Zymoseptoria tritici is the causal agent of Septoria tritici blotch (STB), one of the most important foliar diseases of wheat, globally. Z. tritici is a strictly apoplastic pathogen that can secrete numerous proteins into the apoplast of wheat leaves to promote infection. We sought to determine if, during STB infection, wheat also secretes small proteins into the apoplast to mediate the recognition of pathogen proteins and/or induce defense responses. To explore this, we developed an SSP-discovery pipeline to identify small, secreted proteins from wheat genomic data. Using this pipeline, we identified 6,998 SSPs, representing 2.3% of all proteins encoded by the wheat genome. We then mined a microarray dataset, detailing a resistant and susceptible host response to STB, and identified 141 Z. tritici- responsive SSPs, representing 4.7% of all proteins encoded by Z. tritici - responsive genes. We demonstrate that a subset of these SSPs have a functional signal peptide and can interact with Z. tritici SSPs. Transiently silencing two of these wheat SSPs using virus-induced gene silencing (VIGS) shows an increase in susceptibility to STB, confirming their role in defense against Z. tritici.
| S-EPMC7235427 | biostudies-literature
Project description:Septoria tritici blotch (STB) is a devastating fungal disease affecting durum and bread wheat cultivation worldwide. The identification, development, and employment of resistant wheat genetic material is the key to overcoming costs and limitations of fungicide treatments. The search for resistance sources in untapped genetic material may speed up the deployment of STB genetic resistance in the field. Ethiopian durum wheat landraces represent a valuable source of such diversity. In this study, 318 Ethiopian durum wheat genotypes, for the most part traditional landraces, were phenotyped for resistance to different aspects of STB infection. Phenology, yield and yield component traits were concurrently measured the collection. Here we describe the distribution of STB resistance traits in modern varieties and in landraces, and the relation existing between STB resistance and other agronomic traits. STB resistance sources were found in landraces as well as in modern varieties tested, suggesting the presence of alleles of breeding relevance. The genetic material was genotyped with more than 16 thousand genome-wide polymorphic markers to describe the linkage disequilibrium and genetic structure existing within the panel of genotypes, and a genome-wide association (GWA) study was run to allow the identification of genomic loci involved in STB resistance. High diversity and low genetic structure in the panel allowed high efficiency GWA. The GWA scan detected five major putative QTL for STB resistance, only partially overlapping those already reported in the wheat literature. We report four putative loci for Septoria resistance with no match in previous literature: two highly significant ones on Chr 3A and 5A, and two suggestive ones on Chr 4B and 5B. Markers underlying these QTL explained as much as 10% of the phenotypic variance for disease resistance. We found three cases in which putative QTL for agronomic traits overlapped marker trait association deriving from STB GWA. Our results show that the Ethiopian untapped allelic diversity bears a great value in studying the molecular basis of STB resistance and in breeding for resistance in local and international material.
| S-EPMC5603693 | biostudies-literature
Project description:The poverty of disease resistance gene reservoirs limits the breeding of crops for durable resistance against evolutionary dynamic pathogens. Zymoseptoria tritici which causes Septoria tritici blotch (STB), represents one of the most genetically diverse and devastating wheat pathogens worldwide. No fully virulent Z. tritici isolates against synthetic wheats carrying the major resistant gene Stb16q have been identified. Here, we use comparative genomics, mutagenesis and complementation to identify Stb16q, which confers broad-spectrum resistance against Z. tritici. The Stb16q gene encodes a plasma membrane cysteine-rich receptor-like kinase that was recently introduced into cultivated wheat and which considerably slows penetration and intercellular growth of the pathogen.
| S-EPMC7815785 | biostudies-literature
Project description:Zymoseptoria tritici causes Septoria tritici blotch (STB) of wheat, an economically important disease causing yield losses of up to 10% despite the use of fungicides and resistant cultivars. Z. tritici infection is symptomless for around 10 days, during which time the fungus grows randomly across the leaf surface prior to entry through stomata. Wounded leaves show faster, more extensive STB, suggesting that wounds facilitate fungal entry. Wheat leaves also host epiphytic bacteria; these include ice-nucleating (INA+) bacteria, which induce frost damage at warmer temperatures than it otherwise occurs. Here, STB is shown to be more rapid and severe when wheat is exposed to both INA+?bacteria and sub-zero temperatures. This suggests that ice-nucleation-induced wounding of the wheat leaf provides additional openings for fungal entry. INA+?bacterial populations are shown to benefit from the presence of Z. tritici, indicating that this microbial interaction is mutualistic. Finally, control of INA+?bacteria is shown to reduce STB.
| S-EPMC7575590 | biostudies-literature
Project description:Zymoseptoria tritici is the causative fungal pathogen of septoria tritici blotch (STB) disease of wheat (Triticum aestivum L.) that continuously threatens wheat crops in Ireland and throughout Europe. Under favorable conditions, STB can cause up to 50% yield losses if left untreated. STB is commonly controlled with fungicides; however, a combination of Z. tritici populations developing fungicide resistance and increased restrictions on fungicide use in the EU has led to farmers relying on fewer active substances. Consequently, this serves to drive the emergence of Z. tritici resistance against the remaining chemistries. In response, the use of resistant wheat varieties provides a more sustainable disease management strategy. However, the number of varieties offering an adequate level of resistance against STB is limited. Therefore, new sources of resistance or improved stacking of existing resistance loci are needed to develop varieties with superior agronomic performance. Here, we identified quantitative trait loci (QTL) for STB resistance in the eight-founder "NIAB Elite MAGIC" winter wheat population. The population was screened for STB response in the field under natural infection for three seasons from 2016 to 2018. Twenty-five QTL associated with STB resistance were identified in total. QTL either co-located with previously reported QTL or represent new loci underpinning STB resistance. The genomic regions identified and the linked genetic markers serve as useful resources for STB resistance breeding, supporting rapid selection of favorable alleles for the breeding of new wheat cultivars with improved STB resistance.
| S-EPMC7465482 | biostudies-literature
Project description:Hyperspectral remote sensing holds the potential to detect and quantify crop diseases in a rapid and non-invasive manner. Such tools could greatly benefit resistance breeding, but their adoption is hampered by i) a lack of specificity to disease-related effects and ii) insufficient robustness to variation in reflectance caused by genotypic diversity and varying environmental conditions, which are fundamental elements of resistance breeding. We hypothesized that relying exclusively on temporal changes in canopy reflectance during pathogenesis may allow to specifically detect and quantify crop diseases while minimizing the confounding effects of genotype and environment. To test this hypothesis, we collected time-resolved canopy hyperspectral reflectance data for 18 diverse genotypes on infected and disease-free plots and engineered spectral-temporal features representing this hypothesis. Our results confirm the lack of specificity and robustness of disease assessments based on reflectance spectra at individual time points. We show that changes in spectral reflectance over time are indicative of the presence and severity of Septoria tritici blotch (STB) infections. Furthermore, the proposed time-integrated approach facilitated the delineation of disease from physiological senescence, which is pivotal for efficient selection of STB-resistant material under field conditions. A validation of models based on spectral-temporal features on a diverse panel of 330 wheat genotypes offered evidence for the robustness of the proposed method. This study demonstrates the potential of time-resolved canopy reflectance measurements for robust assessments of foliar diseases in the context of resistance breeding.
| S-EPMC6824235 | biostudies-literature