Plant Breeding for Biotic Stress Resistance

Fritsche‐Neto, Roberto; Borém, Aluízio

doi:10.1007/978-3-642-33087-2

Cited by 7 publications

(1 citation statement)

References 240 publications

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“…Plant breeding studies are critical for improving crop yield, disease resistance, and environmental adaptation (Fritsche-Neto & Borém, 2012). However, the success of such studies relies heavily on the quality and quantity of data used.…”

Section: Introductionmentioning

confidence: 99%

SoilType: An R package to interplay soil characterization in plant science

Fritsche‐Neto

2023

Agronomy Journal

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Yield is a complex quantitative trait whose expression is sensitive to environmental stimuli. Therefore, soil‐related information can increase the predictive ability of genotype's performances across different locations. However, soil information is not always readily available worldwide or before the site or plot level growing season. Thus, in the current version, this tool has two functions. The first function retrieves soil samples and soil (from WoSIS Soil Profile Database) near your target location. Then it predicts 13 soil characteristics (physical and chemical). If the number of samples per location is greater than five, the function uses random forest to predict soil characteristics otherwise it averages the information. The output is a table with the target location and its latitude and longitude coordinates—the number of samples used, the root mean square error (RMSE), and the R‐square for each prediction. From a couple of instances in a trial (location), the second function predicts soil characteristics at the plot level via random forest. The output is a table with the plot IDs, coordinates, number of samples used to make predictions, the RMSE and R‐square for each prediction, the trait predicted, and the predicted value. As a proof‐of‐concept, we used the first function in the LSU Rice Breeding multi‐environmental trials (24 locations), identified the most important soil covariates to determine rice yield, and then clustered the locations. This tool can support breeders in better allocating trials in advance, borrow information from other regions, identify the best variety for each location, reduce costs, and increase accuracy.

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Section: Introductionmentioning

confidence: 99%

SoilType: An R package to interplay soil characterization in plant science

Fritsche‐Neto

2023

Agronomy Journal

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Studies of plant colonisation by closely related Bacillus amyloliquefaciens biocontrol agents using strain specific quantitative PCR assays

Johansson

Bejai

Niazi

et al. 2014

Antonie van Leeuwenhoek

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Certain strains of Bacillus amyloliquefaciens can colonize plants and improve growth and stress management. In order to study these effects, bacterial growth dynamics on plants and in the rhizosphere are of interest calling for specific analytical tools. For that purpose, quantitative real-time PCR (qPCR) assays were developed in order to differentiate among three closely related B. amyloliquefaciens subsp. plantarum strains (UCMB5033, UCMB5036, UCMB5113) and to determine their levels with high accuracy. Oligonucleotide primers were designed for strain unique gene sequences and used for SYBR green based qPCR analysis. Standard curves covered a wide linear range (10(6)) of DNA amounts with the lowest detection level at 50 fg. Post-reaction melting curve analysis showed only a single product. Accurate threshold cycles were obtained, even in the presence of high excess of related Bacillus strains and total bacterial DNA from soil. Analysis of Bacillus colonisation after seed treatment of two oilseed rape cultivars (Oase and Ritz) grown on agar support showed a time dependent effect but that the bacteria mostly were found on root tissues and little on green tissues. The colonisation on plants grown in soil varied among the Bacillus strains where Oase seemed to house more bacteria than Ritz. Applied as a mixture, all three Bacillus strains co-existed on the roots of plants grown in soil. The qPCR assay in combination with other techniques will be a powerful tool to study plant interactions of these B. amyloliquefaciens biocontrol agents to further understand the requirements for successful interactions and improvement of plant properties.

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Molecular markers for improving control of soil-borne pathogen Fusarium oxysporum in sugar beet

et al. 2017

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Fusarium spp. cause severe damage in many agricultural crops, including sugar beet, with Fusarium oxysporum historically being considered as the most damaging of all species. Sugar beet needs to be protected from this class of soil-borne pathogens in order to ensure an optimal sugar yield in the field. Genetic control of the disease is crucial in managing these pathogens. Identification of single nucleotide polymorphism (SNP) markers linked to resistance can be a powerful tool for the introgression of valuable genes needed to develop Fusarium-resistant varieties. A candidate gene approach was carried out to identify SNP markers linked to putative Fusarium resistance sources in sugar beet. Five resistant analogue genes (RGAs) were screened by means of high resolution melting (HRM) analysis in a set of sugar beet lines, considered as resistant and susceptible to Fusarium oxysporum. HRM polymorphisms were observed in 80% of amplicons. Two HRM polymorphisms were significantly associated with Fusarium resistance (P < 0.05). The amplicons that showed association were sequenced and two SNPs were identified. The association was further validated on 96 susceptible and 96 resistant plants using competitive allele-specific PCR (KASPar) technology. The selected SNPs could be used for marker-assisted breeding of Fusarium resistance in sugar beet

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Plant Breeding for Biotic Stress Resistance

Cited by 7 publications

References 240 publications

SoilType: An R package to interplay soil characterization in plant science

SoilType: An R package to interplay soil characterization in plant science

Studies of plant colonisation by closely related Bacillus amyloliquefaciens biocontrol agents using strain specific quantitative PCR assays

Molecular markers for improving control of soil-borne pathogen Fusarium oxysporum in sugar beet

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