Septoria tritici blotch (STB) disease caused by Zymoseptoria tritici is one of the most damaging diseases of wheat causing significant yield losses worldwide. Identification and employment of resistant germplasm is the most cost-effective method to control STB. In this study, we characterized seedling stage resistance to STB in 175 winter wheat landraces and old cultivars of Nordic origin. The study revealed significant (p < 0.05) phenotypic differences in STB severity in the germplasm. Genome-wide association analysis (GWAS) using five different algorithms identified ten significant markers on five chromosomes. Six markers were localized within a region of 2 cM that contained seven candidate genes on chromosome 1B. Genomic prediction (GP) analysis resulted in a model with an accuracy of 0.47. To further improve the prediction efficiency, significant markers identified by GWAS were included as fixed effects in the GP model. Depending on the number of fixed effect markers, the prediction accuracy improved from 0.47 (without fixed effects) to 0.62 (all non-redundant GWAS markers as fixed effects), respectively. The resistant genotypes and single-nucleotide polymorphism (SNP) markers identified in the present study will serve as a valuable resource for future breeding for STB resistance in wheat. The results also highlight the benefits of integrating GWAS with GP to further improve the accuracy of GP.

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.

Section Key Message Using disease bioassays and transcriptomic analysis we show that intact SA-signalling is required for potato defences against the necrotrophic fungal pathogen Alternaria solani. AbstractSection Abstract Early blight, caused by the necrotrophic fungus Alternaria solani, is an increasing problem in potato cultivation. Studies of the molecular components defining defence responses to A. solani in potato are limited. Here, we investigate plant defence signalling with a focus on salicylic acid (SA) and jasmonic acid (JA) pathways in response to A. solani. Our bioassays revealed that SA is necessary to restrict pathogen growth and early blight symptom development in both potato foliage and tubers. This result is in contrast to the documented minimal role of SA in resistance of Arabidopsis thaliana against necrotrophic pathogens. We also present transcriptomic analysis with 36 arrays of A. solani inoculated SA-deficient, JA-insensitive, and wild type plant lines. A greater number of genes are differentially expressed in the SA-deficient mutant plant line compared to the wild type and JA- insensitive line. In wild type plants, genes encoding metal ion transporters, such as copper, iron and zinc transporters were upregulated and transferase-encoding genes, for example UDP-glucoronosyltransferase and Serine-glyoxylate transferase, were downregulated. The SA-deficient plants show upregulation of genes enriched in GO terms related to oxidoreductase activity, respiratory chain and other mitochondrial-related processes. Pathogenesis-related genes, such as genes encoding chitinases and PR1, are upregulated in both the SA-deficient and wild type plants, but not in the JA-insensitive mutants. The combination of our bioassays and the transcriptomic analysis indicate that intact SA signalling, and not JA signalling, is required for potato defences against the necrotrophic pathogen A. solani.

Background: High-throughput plant phenotyping (HTPP) methods have the potential to speed up the crop breeding process through the development of cost-effective, rapid and scalable phenotyping methods amenable to automation. Crop disease resistance breeding stands to benefit from successful implementation of HTPP methods, as bypassing the bottleneck posed by traditional visual phenotyping of disease, enables the screening of larger and more diverse populations for novel sources of resistance. The aim of this study was to use HTPP data obtained through proximal phenotyping to predict yellow rust scores in a large winter wheat field trial. Results: The results show that 40–42 spectral vegetation indices (SVIs) derived from spectroradiometer data are sufficient to predict yellow rust scores using Random Forest (RF) modelling. The SVIs were selected through RF-based recursive feature elimination (RFE), and the predicted scores in the resulting models had a prediction accuracy of r_s = 0.50–0.61 when measuring the correlation between predicted and observed scores. Some of the most important spectral features for prediction were the Plant Senescence Reflectance Index (PSRI), Photochemical Reflectance Index (PRI), Red-Green Pigment Index (RGI), and Greenness Index (GI). Conclusions: The proposed HTPP method of combining SVI data from spectral sensors in RF models, has the potential to be deployed in wheat breeding trials to score yellow rust.

Early blight in potato, caused by Alternaria solani, is mainly controlled by frequent applications of synthetic fungicides. Reducing the use of synthetic fungicides in agriculture is desired to reach an overall sustainable development since the active components can be harmful for humans and for the ecosystem. In integrated pest management, IPM, the idea is to combine various measures, including optimized crop management, crop rotation, use of resistant cultivars, biological control agents (BCAs), plant resistance inducers, and fertilizers, to decrease the dependence on traditional chemical fungicides. In this paper, we present the results from greenhouse and field trials where we evaluated the effect of strategies aimed at reducing our reliance on synthetic fungicides including treatments with biological control agents (BCAs) (Pythium oligandrum, Polygandron^®, and Bacillus subtilis, Serenade^®) and plant resistance inducers (silicon products HortiStar^® and Actisil^®) for early blight in potato. The agents were applied separately or in combination with each other or with synthetic fungicides. In the greenhouse, trials application of these agents resulted in 50–95% reduction of infection by A. solani, but their combination did not generally improve the outcome. However, the effects were much smaller in the hand-sprayed field trials, 20–25% disease reduction and almost disappeared in full-scale field trials where application was done with tractor sprayers. In this article, we discuss possible reasons behind the drop in efficacy from greenhouse trials to full-size field evaluation.

Early blight, caused by the fungus Alternaria solani, is a common foliar disease in potato. Quinone outside inhibitor (QoIs) fungicides have commonly been used against A. solani. To avoid or delay development of fungicide resistance it is recommended to alternate or combine fungicides with different modes of action. Therefore, we compared two different fungicide programs against early blight in field trials and studied within season changes in the pathogen population. An untreated control was compared with treatments using azoxystrobin alone and with a program involving difenoconazole followed by boscalid and pyraclostrobin combined. Isolates of A. solani were collected during the growing season and changes in the population structure was investigated. We also screened for the amino acid substitution in the cytochrome b gene and investigated changes in sensitivity to azoxystrobin. Treatment with azoxystrobin alone did not improve disease control in 2014 when the disease pressure was high. However, lower severity of the disease was observed after combined use of difenoconazole, boscalid and pyraclostrobin. The efficacy of both fungicide treatments were similar during the field trial in 2017. Two mitochondrial genotypes (GI and GII) were found among isolates, where all isolates, except two, were GII. All GII isolates had the F129 L substitution while the two GI isolates were wild type. Population structure analysis and principal component analysis (PCA) of amplified fragment length polymorphisms (AFLP) data revealed within season changes in the A. solani populations in response to fungicide application. Isolates with the F129 L substitution had reduced sensitivity to azoxystrobin in vitro and their sensitivity tended to decrease with time.