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Phialophora gregata

About: Phialophora gregata is a research topic. Over the lifetime, 118 publications have been published within this topic receiving 3380 citations.


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TL;DR: Soybean disease loss estimates were compiled for the 1996 to 1998 harvested crops from all soybean-producing states in the United States based on field surveys, information from field workers and university extension staff, and research plot data.
Abstract: Soybean disease loss estimates were compiled for the 1996 to 1998 harvested crops from all soybean-producing states in the United States. Scientists from each state provided estimates of losses based on field surveys, information from field workers and university extension staff, and research plot data. Total yield losses caused by soybean cyst [Heterodera glycines Ichinohe] in the United States were greater than those caused by any other disease. Next in importance were phytophthora root and stem rot [Phytophthora sojae (Kaufman & Gerdemann)], brown stem rot [Phialophora gregata (Allington & Chamberlain) Gams], sclerotinia stem rot [Sclerotinia sclerotiorum (Lib.) de Bary], and seedling diseases. Yield loss estimates due to particular diseases varied by region and among years. The estimated soybean yield losses to diseases in the United States were 10.9 × 106 t in 1996, 11.9 × 106 t in 1997, and 14.0 × 106 t in 1998.

196 citations

Journal Article
TL;DR: Using ITS and 28S rDNA sequences, members of the genus Cadophora are shown to be anamorphs of the Helotiales (discomycetes) and distinct from the morphologically similar anamorph genus Phialophora.
Abstract: Using ITS and 28S (LSU) rDNA sequences, members of the genus Cadophora are shown to be anamorphs of the Helotiales (discomycetes) and distinct from the morphologically similar anamorph genus Phialophora. The rDNA sequences of Cadophora spp. were similar to those of the teleomorph genera Mollisia, Pyrenopeziza, and Tapesia (which have anamorphs in Ramulispora) and to the anamorph genera Phialocephala and Rhynchosporium. The type species of Cadophora is C. fastigiata, and C. malorum is another common species in the genus. Also included are C. finlandia comb. nov., the soybean pathogen C. gregata comb. nov., C. lagerbergii, C. luteo-olivacea comb. nov., and C. melinii. Phialophora atra and C. heteroderae are synonymized with C. malorum. Phialophora goidanichii is synonymized with C. luteo-olivacea.

111 citations

Journal ArticleDOI
TL;DR: Results demonstrate that composite interval mapping gives increased precision over interval mapping and is capable of distinguishing two linked QTL, the first example of a disease resistance QTL associated with a resistance gene analog.
Abstract: The objective of this study was to map the gene(s) conferring resistance to brown stem rot in the soybean cultivar BSR 101. A population of 320 recombinant inbred lines (RIL) was derived from a cross of BSR 101 and PI 437.654. Seedlings of each RIL and parent were inoculated by injecting stems with a suspension of spores and mycelia of Phialophora gregata, incubated in a growth chamber at 17 °C, and assessed for resistance by monitoring the development of foliar and stem symptoms. The population also was evaluated with 146 RFLPs, 760 AFLPs, and 4 probes for resistance gene analogs (RGAs). Regression analysis identified a significant association between resistance and several markers on Linkage Group J of the USDA-ARS molecular marker linkage map. Interval analysis with Mapmaker QTL identified a major peak between marker RGA2V-1 and AFLP marker AAGATG152M on Linkage Group J. A second peak, associated only with stem symptoms, was identified between the RFLP B122I-1 and RGA2V-1, also on Linkage Group J. When composite interval mapping with QTL Cartographer was used, two linked QTL were identified with both foliar and stem disease assessment methods: a major QTL between AFLP markers AAGATG152E and ACAAGT260, and a minor QTL between RGA3I-3 and RGA3I-2. These results demonstrate that composite interval mapping gives increased precision over interval mapping and is capable of distinguishing two linked QTL. The minor QTL associated with the cluster of RGA3I loci is of special interest because it is the first example of a disease resistance QTL associated with a resistance gene analog.

90 citations

Journal ArticleDOI
TL;DR: The prevalence of brown stem rot, H. glycines, and Phytophthora sojae in the north central United States was investigated during the fall of 1995 and 1996 and both the prevalence and population densities were consistently greater in tilled than in no-till fields in all states for which tillage information was available.
Abstract: The prevalence of brown stem rot (caused by Phialophora gregata), Heterodera glycines, and Phytophthora sojae in the north central United States was investigated during the fall of 1995 and 1996. Soybean fields were randomly selected using an area-frame sampling design in collaboration with the National Agricultural Statistics Service. Soil and soybean stem samples, along with tillage information, were collected from 1,462 fields in Illinois, Iowa, Minnesota, Missouri, and Ohio. An additional 275 soil samples collected from Indiana were assessed for H. glycines. For each field, the incidence and prevalence of brown stem rot was assessed in 20 soybean stem pieces. The prevalence and recovery (expressed as the percentage of leaf disks colonized) of P. sojae and the prevalence and population densities of H. glycines were determined from the soil samples. The prevalence of brown stem rot ranged from 28% in Missouri to 73% in Illinois; 68 and 72% of the fields in Minnesota and Iowa, respectively, showed symptomatic samples. The incidence of brown stem rot was greater in conservation-till than in conventional-till fields in all states except Minnesota, which had few no-till fields. P. sojae was detected in two-thirds of the soybean fields in Ohio and Minnesota, whereas 63, 55, and 41% of the fields in Iowa, Missouri, and Illinois, respectively, were infested with the pathogen. The recovery rates of P. sojae were significantly greater (P

88 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20201
20181
20161
20152
20141
20131