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- Armoniené, Rita, et al.
(författare)
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Affordable Imaging Lab for Noninvasive Analysis of Biomass and Early Vigour in Cereal Crops
- 2018
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Ingår i: BioMed Research International. - : Hindawi Limited. - 2314-6133 .- 2314-6141.
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Tidskriftsartikel (refereegranskat)abstract
- Plant phenotyping by imaging allows automated analysis of plants for various morphological and physiological traits. In this work, we developed a low-cost RGB imaging phenotyping lab (LCP lab) for low-throughput imaging and analysis using affordable imaging equipment and freely available software. LCP lab comprising RGB imaging and analysis pipeline is set up and demonstrated with early vigour analysis in wheat. Using this lab, a few hundred pots can be photographed in a day and the pots are tracked with QR codes. The software pipeline for both imaging and analysis is built from freely available software. The LCP lab was evaluated for early vigour analysis of five wheat cultivars. A high coefficient of determination (R-2 0.94) was obtained between the dry weight and the projected leaf area of 20-day-old wheat plants and R-2 of 0.9 for the relative growth rate between 10 and 20 days of plant growth. Detailed description for setting up such a lab is provided together with custom scripts built for imaging and analysis. The LCP lab is an affordable alternative for analysis of cereal crops when access to a high-throughput phenotyping facility is unavailable or when the experiments require growing plants in highly controlled climate chambers. The protocols described in this work are useful for building affordable imaging system for small-scale research projects and for education.
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| 2. |
- Edin, Eva, et al.
(författare)
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Genetic diversity and occurrence of the F129L substitutions among isolates of Alternaria solani in south-eastern Sweden
- 2016
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Ingår i: Hereditas. - : Springer Science and Business Media LLC. - 0018-0661 .- 1601-5223. ; 153
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Tidskriftsartikel (refereegranskat)abstract
- Background: Early blight, caused by the fungus Alternaria solani, occurs on potato mainly in the south-eastern part of Sweden, but also in other parts of the country. The aim of this study was to investigate the genetic diversity of A. solani populations from different potato growing regions in south-eastern Sweden using AFLP marker analysis. In addition, the cultured isolates were examined for substitutions in the gene encoding cytochrome b, associated with loss of sensitivity against QoI fungicides.Results: Nei's gene diversity index for the Swedish populations of A. solani revealed a gene diversity of up to 0.20. Also genetic differentiation was observed among populations of A. solani from different locations in south-eastern Sweden. The mitochondrial genotype of the isolates of A. solani was determined and both known genotypes, GI (genotype 1) and GII (genotype 2), were found among the isolates. The occurrence of the F129L substitution associated with a loss of sensitivity to strobilurins was confirmed among the GII isolates. In vitro conidial germination tests verified that isolates containing the F129L substitution had reduced sensitivity to azoxystrobin and, at a lower extent, to pyraclostrobin.Conclusions: Genetic diversity was relatively high among isolates of A. solani in south-eastern part of Sweden. F129L substitutions, leading to reduced sensitivity to strobilurins, have been established in field populations, which may have implications for the future efficacy of QoI fungicides.
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| 6. |
- Gustavsson, Larisa, et al.
(författare)
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Resistance to Neonectria ditissima in apple : insights from metabolomics and lipidomics analyses
- 2023
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Ingår i: Xxxi international horticultural congress (ihc2022). - : International Society for Horticultural Science. - 9789462613614 ; , s. 329-335, s. 329-336
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Konferensbidrag (refereegranskat)abstract
- European canker, caused by the necrotrophic fungus Neonectria ditissima, is the most serious disease in apple production in Sweden. The disease is favored by a relatively cool and rainy climate. The canker damages have a significant economic impact due to reduced bearing surface and increased orchard management costs. The possibilities for chemical and biological control are very limited. Therefore, directed breeding for new resistant cultivars is urgently needed. Knowledge of inheritance of canker resistance and understanding of molecular mechanisms involved in resistant and susceptible responses to fungal attacks would facilitate breeding. In this study, we evaluated the tempo-spatial differences in plant-pathogen interactions in a set of partially resistant and susceptible cultivars by conducting metabolomic and lipidomic analyses. The major trends in metabolomics and lipidomic profiles were common among cultivars, irrespective of the degree of susceptibility. Several metabolites and lipids varied with time point and cultivar under N. ditissima infection. Putative key metabolites such as suberic acid and jasmonic acid were upregulated in all cultivars upon infection. Additionally, several lipids exhibited changes 30 to 45 days post-inoculation. Thus, the approach used seems to have resulted in a rich data set to be further analyzed in light of ongoing QTL-mapping efforts.
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| 7. |
- Koc, Alexander, et al.
(författare)
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Predicting yellow rust in wheat breeding trials by proximal phenotyping and machine learning
- 2022
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Ingår i: Plant Methods. - : Springer Science and Business Media LLC. - 1746-4811. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 8. |
- Kushwaha, Sandeep Kumar, et al.
(författare)
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Differential Gene Expression Analysis of Wheat Breeding Lines Reveal Molecular Insights in Yellow Rust Resistance under Field Conditions
- 2020
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Ingår i: Agronomy. - : MDPI AG. - 2073-4395. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- The evolution of pathogens in the changing climate raises new challenges for wheat production. Yellow rust is one of the major wheat diseases worldwide, leading to an increased use of fungicides to prevent significant yield losses. The enhancement of the resistance potential of wheat cultivars is a necessary and environmentally friendly solution for sustainable wheat production. In this study, we aimed to identify the differentially expressed genes induced upon yellow rust infection in the field. Reference and de novo based transcriptome analysis was performed among the resistant and susceptible lines of a bi-parental population to study the global transcriptome changes in contrasting wheat genotypes. Based on the analysis, the de novo transcriptome analysis approach was found to be more supportive for field studies. Expression profiles, gene ontology, KEGG pathway analysis and enrichment studies indicated the relation between differentially expressed genes of wheat and yellow rust infection. The h0igh expression of genes related to non-race specific resistance along with pathogen-specific resistance might be a reason for the better resistance ability of a resistant wheat genotype in the field. The targeted metagenomic analysis of wheat samples revealed that Puccinia striiformis tritici was the most dominant pathogen along with other pathogens on the collected leaf material and validating the disease scoring carried out in the field and transcriptomics analyses.
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| 10. |
- Odilbekov, Firuz, et al.
(författare)
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GWAS-Assisted Genomic Prediction to Predict Resistance to Septoria Tritici Blotch in Nordic Winter Wheat at Seedling Stage
- 2019
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Ingår i: Frontiers in Genetics. - : Frontiers Media SA. - 1664-8021. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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