Fusarium head blight (FHB) is a devastating disease of wheat heads. It is caused by several species from the genus Fusarium. Several endophytic fungi also colonize wheat spikes asymptomatically. Pathogenic and commensal fungi share and compete for the same niche and thereby influence plant performance. Understanding the natural dynamics of the fungal community and how the pre-established species react to pathogen attack can provide useful information on the disease biology and the potential use of some of these endophytic organisms in disease control strategies. Fungal community composition was assessed during anthesis as well as during FHB attack in wheat spikes during 2016 and 2017 in two locations. Community metabarcoding revealed that endophyte communities are dominated by basidiomycete yeasts before anthesis and shift towards a more opportunistic ascomycete-rich community during kernel development. These dynamics are interrupted when Fusarium spp. colonize wheat spikes. The Fusarium pathogens appear to exclude other fungi from floral tissues as they are associated with a reduction in community diversity, especially in the kernel which they colonize rapidly. Similarly, the presence of several endophytes was negatively correlated with Fusarium spp. and linked with spikes that stayed healthy despite exposure to the pathogen. These endophytes belonged to the genera Cladosporium, Itersonillia and Holtermanniella. These findings support the hypothesis that some naturally occurring endophytes could outcompete or prevent FHB and represent a source of potential biological control agents in wheat.

Highlight Phs-A1 confers resistance to sprouting in wheat by delaying the rate of seed dormancy loss and is distinct from the previously proposed PM19 candidate genes.

Background Effective disease management depends on timely and accurate diagnosis to guide control measures. The capacity to distinguish between individuals in a pathogen population with specific properties such as fungicide resistance, toxin production and virulence profiles is often essential to inform disease management approaches. The genomics revolution has led to technologies that can rapidly produce high-resolution genotypic information to define individual variants of a pathogen species. However, their application to complex fungal pathogens has remained limited due to the frequent inability to culture these pathogens in the absence of their host and their large genome sizes. Results Here, we describe the development of Mobile And Real-time PLant disEase (MARPLE) diagnostics, a portable, genomics-based, point-of-care approach specifically tailored to identify individual strains of complex fungal plant pathogens. We used targeted sequencing to overcome limitations associated with the size of fungal genomes and their often obligately biotrophic nature. Focusing on the wheat yellow rust pathogen, Puccinia striiformis f.sp. tritici ( Pst ), we demonstrate that our approach can be used to rapidly define individual strains, assign strains to distinct genetic lineages that have been shown to correlate tightly with their virulence profiles and monitor genes of importance. Conclusions MARPLE diagnostics enables rapid identification of individual pathogen strains and has the potential to monitor those with specific properties such as fungicide resistance directly from field-collected infected plant tissue in situ. Generating results within 48 h of field sampling, this new strategy has far-reaching implications for tracking plant health threats. Electronic supplementary material The online version of this article (10.1186/s12915-019-0684-y) contains supplementary material, which is available to authorized users.

Powdery mildew is a common disease of field pea, Pisum sativum L., and is caused by the ascomycete fungus Erysiphe pisi. It can cause severe damage in areas where pea is cultivated. Today breeders want to develop new pea lines that are resistant to the disease. To make the breeding process more efficient, it is desirable to find genetic markers for use in a marker-assisted selection (MAS) strategy. In this study, microsatellites (SSR) were used to find markers linked to powdery mildew resistance. The resistant pea cultivar '955180' and the susceptible pea cultivar 'Majoret' were crossed and F2 plants were screened with SSR markers, using bulked segregant analysis. A total of 315 SSR markers were screened out of which five showed linkage to the powdery mildew resistance gene. No single marker was considered optimal for inclusion in a MAS program. Instead, two of the markers can be used in combination, which would result in only 1.6% incorrectly identified plants. Thus SSR markers can be successfully used in marker-assisted selection for powdery mildew resistance breeding in pea.

The Baltic Sea is one of the largest brackish water bodies in the world. Eutrophication is a major concern in the Baltic Sea due to the leakage of nutrients to the sea with agriculture being the primary source. Wheat (Triticum aestivum L.) is the most widely grown crop in the countries surrounding the Baltic Sea and thus promoting sustainable agriculture practices for wheat cultivation will have a major impact on reducing pollution in the Baltic Sea. This approach requires identifying and addressing key challenges for sustainable wheat production in the region. Implementing new technologies for climate-friendly breeding and digital farming across all surrounding countries should promote sustainable intensification of agriculture in the region. In this review, we highlight major challenges for wheat cultivation in the Baltic Sea region and discuss various solutions integrating transnational collaboration for pre-breeding and technology sharing to accelerate development of low input wheat cultivars with improved host plant resistance to pathogen and enhanced adaptability to the changing climate.Abbreviations -DDT, dichlorodiphenyltrichloroethane; DK, Denmark; ECPGR, European Cooperative Programme for Plant Genetic Resources; EE, Estonia; FI, Finland; HCB, hexachlorobenzene; HCH, hexachlorocyclohexane; ICM, Integrated Crop Management; IWYP, International wheat yield potential; LT, Lithuania; N, Nitrogen; NPPN, Nordic plant phenotyping network; NUE, nitrogen use efficiency; PL, Poland; PPP, plant protection product; SE, Sweden; STB, Septoria tritici Blotch; WUE, water use efficiency. † These authors contributed equally and are presented alphabetically by their last name. 442

Septoria tritici blotch (STB) caused by the fungal pathogen Zymoseptoria tritici and powdery mildew (PM) caused by Blumeria graminis f.sp tritici (Bgt) are among the forefront foliar diseases of wheat that lead to a significant loss of grain yield and quality. Resistance breeding aimed at developing varieties with inherent resistance to STB and PM diseases has been the most sustainable and environment-friendly approach. In this study, 175 winter wheat landraces and historical cultivars originated from the Nordic region were evaluated for adult-plant resistance (APR) to STB and PM in Denmark, Estonia, Lithuania, and Sweden. Genome-wide association study (GWAS) and genomic prediction (GP) were performed based on the adult-plant response to STB and PM in field conditions using 7,401 single-nucleotide polymorphism (SNP) markers generated by 20K SNP chip. Genotype-by-environment interaction was significant for both disease scores. GWAS detected stable and environment-specific quantitative trait locis (QTLs) on chromosomes 1A, 1B, 1D, 2B, 3B, 4A, 5A, 6A, and 6B for STB and 2A, 2D, 3A, 4B, 5A, 6B, 7A, and 7B for PM adult-plant disease resistance. GP accuracy was improved when assisted with QTL from GWAS as a fixed effect. The GWAS-assisted GP accuracy ranged within 0.53–0.75 and 0.36–0.83 for STB and PM, respectively, across the tested environments. This study highlights that landraces and historical cultivars are a valuable source of APR to STB and PM. Such germplasm could be used to identify and introgress novel resistance genes to modern breeding lines.

Phenotyping with proximal sensors allow high-precision measurements of plant traits both in the controlled conditions and in the field. In this work, using machine learning, an integrated analysis was done from the data obtained from spectroradiometer, infrared thermometer, and chlorophyll fluorescence measurements to identify most predictive proxy measurements for studying Septoria tritici blotch (STB) disease of wheat. The random forest (RF) models for chlorosis and necrosis identified photosystem II quantum yield (QY) and vegetative indices (VIs) associated with the biochemical composition of leaves as the top predictive variables for identifying disease symptoms. The RF model for chlorosis was validated with a validation set (R2: 0.80) and in an independent test set (R2: 0.55). Based on the results, it can be concluded that the proxy measurements for photosystem II, chlorophyll content, carotenoid, and anthocyanin levels and leaf surface temperature can be successfully used to detect STB. Further validation of these results in the field will enable application of these predictive variables for detection of STB in the field.

Fusarium head blight (FHB) is one of the economically important diseases of wheat as it causes severe yield loss and reduces grain quality. In winter wheat, due to its vernalization requirement, it takes an exceptionally long time for plants to reach the heading stage, thereby prolonging the time it takes for characterizing germplasm for FHB resistance. Therefore, in this work, we developed a protocol to evaluate winter wheat germplasm for FHB resistance under accelerated growth conditions. The protocol reduces the time required for plants to begin heading while avoiding any visible symptoms of stress on plants. The protocol was tested on 432 genotypes obtained from a breeding program and a genebank. The mean area under disease progress curve for FHB was 225.13 in the breeding set and 195.53 in the genebank set, indicating that the germplasm from the genebank set had higher resistance to FHB. In total, 10 quantitative trait loci (QTL) for FHB severity were identified by association mapping. Of these, nine QTL were identified in the combined set comprising both genebank and breeding sets, while two QTL each were identified in the breeding set and genebank set, respectively, when analyzed separately. Some QTLs overlapped between the three datasets. The results reveal that the protocol for FHB evaluation integrating accelerated growth conditions is an efficient approach for FHB resistance breeding in winter wheat and can be even applied to spring wheat after minor modifications.