Spelling suggestions: "subject:"antidisease anda peut resistance."" "subject:"antidisease anda pet resistance.""
1 |
Phytophthora megasperma var. sojae race 4 : varietal reactions and inheritance of resistanceSim, Thomas January 2011 (has links)
Digitized by Kansas Correctional Industries
|
2 |
Seed-borne fungi of soybeans in KansasHabermehl, R. Wayne. January 1964 (has links)
Call number: LD2668 .T4 1964 H14 / Master of Science
|
3 |
Examination of the inheritance of resistance to Phytophthora megasperma var. sojae in two soybean plant introductionsKiser, John Allan. January 1978 (has links)
Call number: LD2668 .T4 1978 K55 / Master of Science
|
4 |
Lignin as a mechanism of field resistance to Phytophthora rot in soybeansCurry, Joseph Timothy. January 1984 (has links)
Call number: LD2668 .T4 1984 C87 / Master of Science
|
5 |
Towards marker assisted selection for nematode resistance in soybean.Mienie, Charlotte Maria Susanna. 19 December 2013 (has links)
Meloidogyne javanica is the most widely spread nematode pest on soybean in South Africa. Only a few registered cultivars have some resistance to this nematode and there is an urgent need for an efficient breeding programme for resistant cultivars of all maturity groups. However, breeding is hampered by
laborious screening procedures for selection of resistant lines. The objective of this study was to develop an economically viable molecular marker system for application in selection procedures. Three techniques of marker identification were investigated, i.e. RAPD, RFLP and AFLP analysis. The RAPD technique proved to be applicable in fingerprinting soybean varieties, but was too sensitive for interplant variation to
be used as an efficient system for identification of molecular markers linked to nematode resistance. Both RFLP and AFLP screening identified markers linked to gall index variation in a segregating population of 60 F₂ progeny from across between a resistant cultivar, Gazelle, and a highly susceptible variety, Prima. A codominant RFLP marker( B212) was linked significantly to resistance and explained 62% of the variation in gall index. Seven AFLP markers were linked significantly to the resistance trait, of which four were linked in repulsion phase and three in coupling phase. All seven AFLP markers mapped to LG-F on the public soybean molecular map. The QTL for resistance mapped between markers E-ACC/M-CTC2 linked in coupling phase, 8212 and E-AAC/M-CAT1, linked in repulsion phase. These two AFLP markers bracketing the major resistance QTL were successfully converted to SCARs. Marker E-ACC/M-CTC2 was converted to a codominant SCAR marker SOJA6, which acounted for 41% of variation in gall index in the
mapping population. Marker E-AAC/M-CAT1 was converted to a dominant SCAR marker (SOJA7) and explained 42% of gall index variation in the mapping population. These two markers mapped approximately 3.8 cM and 2.4 cM respectively from the resistance QTL. This study represents the first report of the development of PCR-based sequence specific markers linked to resistance to M. javanica in soybean. / Thesis (Ph.D.)-University of Natal, Pietermaritzburg, 2000.
|
6 |
A genetic and biochemical study of the antibiosis mechanism of host-plant resistance in soybeans to the Mexican bean beetle /Rufener, George Keith January 1987 (has links)
No description available.
|
7 |
The Relative Nitrogen Fixation Rate and Colonization of Arbuscular Mycorrhizal Fungi of Iron Deficient SoybeansPodrebarac, Frances Ann January 2011 (has links)
Soybeans (Glycine max L. Merr.) are a symbiont of two beneficial associations:
biological nitrogen fixation (BNF) with Bradyrhizobium japonicum, and arbuscular
mycorrhizal fungi (AMF). Within the Northern Great Plains of the USA, iron deficiency
chlorosis (IDC) of soybean is a yield-limiting factor. The effects of IDC on BNF and AMF
are not well defined. This study was conducted to determine the effects of IDC on BNF
and AMF. A laboratory study was performed to compare three methods of measuring
ureide-N, a product of BNF in soybeans. Field studies in soybean were performed at three
locations at eastern N011h Dakota. The experimental design was a factorial combination of
three cultivars and three treatments. The three cultivars, in order of decreasing chlorosis
susceptibility, were NuTech NT-0886, Roughrider Genetics RG 607, and Syngenta S01-C9
RR. The three treatments were control, Sorghum bicolor L. companion crop planted with
the soybean seed, and FeEDDHA applied with the soybean seed. Chlorosis severity was
the greatest and least for the NuTech and Syngenta cultivars, respectively. The FeEDDHA
treatment decreased chlorosis severity. Ureide levels were abnormally high in plants
severely stunted by JDC. The excess accumulation of ureides in IDC-stunted plants
suggests that plant growth was reduced more than the rate of nitrogen fixation. The AMF
population \vas at an adequate level at all locations and not affected by cultivar or
treatment, in general. In the laboratory study, the Patterson et al. method had greater ureide
concentrations due to the non-specific measuring of ammonium compounds compared to
the Vogels and Van der Drift and Goos methods. / North Dakota Soybean Council
|
8 |
Molecular genetic analysis of host resistance to soybean mosaic virusYu, Yong Gang 01 February 2006 (has links)
Soybean mosaic virus (SMV), a potyvirus detected worldwide, can cause serious diseases in soybean (Glycine max L. Merr.). Host resistance to SMV conferred by a single dominant gene, Rsvl, was studied as a model to gain insights of plant virus resistance genes, and to facilitate the breeding of resistant cultivars. DNA restriction fragment length polymorphisms (RFLPs) and microsatellites (or simple sequence repeats, SSRs) were used as genetic markers to identify the chromosomal location of Rsvl1 in a cross between PI 96983 (resistant) and a susceptible cultivar. Twenty five RFLP and three SSR loci polymorphic between the parental lines were analyzed in 107 F, individuals. Genotypes of Rsv1 were determined by inoculating F2.3 progeny with SMV-G1. Genetic analysis revealed that one SSR (HSP176L) and two RFLP (pA186 and pK644a) markers are closely linked to Rsv1, with a distance of 0.5, 1.5, and 2.1 cM, respectively. The tight linkages of the three markers to Rsv1 were confirmed by SSR and RFLP analysis of three near isogenic lines (NILs) of Rsv1 derived from PI 96983 or Marshall.
The three Rsv1-linked markers were then used to screen 67 diverse soybean types. These marker loci showed a remarkably high level of polymorphism, indicating a possible association between disease resistance and rapid sequence divergence. At each Rsv1-linked marker locus, one SSR allele or RFLP haplotype is highly correlated with SMV resistance. These resistance markers, especially the SSR allele at HSP176L which can be detected by the polymerase chain reaction (PCR), may be useful for germplasm screening. The grouping of the 67 accessions according to their Rsv1-linked multilocus marker haplotypes agrees with available pedigree information. A set of differential cultivars known to contain Rsv1 clustered into putative Rsv1- carrying groups. Based on molecular marker analysis and previous inheritance studies, 37 of the 45 resistance accessions probably derive their resistance from Rsv1. The remaining eight accessions include Columbia (Rsv3), and the other potentially diverse resistance sources.
A heat shock protein (HSP) multigene family, HSP176L included, was analyzed for its positional proximity to the Rsv1 gene cluster. A technique termed amplified sequence length polymorphism (ASLP) was developed to convert known DNA sequences to PCR-based genetic markers. Among six pairs of HSP primers used, two (HSP175E and 185C) detected ASLPs between the parents, and segregated in the F₂ population with a size of 174. HSP175E was found to be closely-linked (0.7 cM) to HSP176L, both of which are Class I small HSP genes. HSP185C, however, was mapped to a different linkage group, suggesting that it may belong to another family. ADR11, a member of auxin down-regulated (ADR) multigene family, is known to be linked to HSP173B, also a Class I gene but not mappable in this population. ASLP analysis of ADR11 in a set of Rsv1 NILs indicates that it is linked to Rsv1, and ADR11 co-segregates with HSP175E in the F, population. Thus, the Class I small HSP multigene family including HSP176L, 175E, and 173B, and possibly a family of ADR genes, is located near the Rsvi resistance gene cluster. / Ph. D.
|
9 |
Genetic analyses for resistance to soybean rust (Phakopsora pachyrhiz) and yield stability among soybean genotypes in Kenya.Wanderi, Susan Wothaya. 31 October 2013 (has links)
Soybean (Glycine max (L.) Merr.) occupies an important position in the world economy of the feedstock of high quality protein and vegetable oils. However, its production is threatened by, Asian soybean rust (ASR), caused by the rust fungus Phakopsora pachyrhizi Syd. & P. Syd. This fungus is highly dependent on environmental conditions, has a wide range of hosts, and evolves rapidly into novel races, making it difficult to control. In addition, most commercial varieties are susceptible to rust, the rust has already developed resistance to triazole fungicides, and most small-scale farmers cannot afford expensive systemic fungicides to control the
disease. The use of resistant varieties is the most viable, long-term option to manage ASR, especially in the small-holder soybean farming sector. This study was therefore designed to undertake the following goals: (i) to identify farmers’ preferred varieties and desired traits, their knowledge of ASR, and other key constraints affecting soybean production in Kenya; (ii) to
evaluate soybean accessions for rust resistance, and to determine the correlation of rust resistance with other agronomic traits; (iii) to determine the mode of inheritance for ASR resistance and selected agronomic traits; and (iv) to determine yield stability of soybean advanced lines at multiple sites in Central and Eastern Kenya. To understand farmers’ preferred varietal characteristics, knowledge of ASR and other key constraints to soybean production, a survey was conducted using a structured questionnaire in the major soybean growing areas of Kenya. The farmers preferred local varieties because of their desirable characteristics, which included high yields, early maturity, drought tolerance and seed availability. Although the majority of the participating farmers expressed a willingness to grow improved varieties, financial limitations, seed unavailability and lack of information were the major barriers to their use of improved varieties. High yield, early maturity, adaptability and grain quality were the traits that most farmers sought in an ideal soybean variety. Knowledge of the cause of ASR was limited, and its occurrence was largely attributed to environmental factors, poor soil fertility conditions, poor agronomic practices, physiological maturity and specific species of weeds. Their investments in control methods were minimal due to a lack of technical knowledge, poor access to fungicides, and limited resources. Other constraints faced by soybean farmers included: lack of access to grain markets; lack of knowledge in processing and utilization of soybean grain; the unavailability of seeds; losses to pests and diseases; the lack of inputs such as fertilizers; frequent dry spells; and low yielding varieties. A total of 110 soybean accessions were evaluated for their rust reactions and correlations with selected agronomic traits. These included plant introductions possessing single rust resistant genes (Rpp1-4), tolerant lines, gene bank accessions, commercial varieties and advanced lines.
Soybean genotypes varied significantly in their reactions to rust severity, sporulation, lesion type and area under disease progress curve (AUDPC) values. Genotypes possessing Rpp4 (G10428) and Rpp2 (G8586) resistant genes, and non-characterized genotypes MAK BLD 11.3, GC 00138-29 and Namsoy 4M, were the most resistant accessions, as indicated by low rust
severity scores, low AUDPC values, red brown lesions and low sporulation scores. Other genotypes with known resistant genes including G7955 (Rpp3), G58 and Tainung 4 (Rpp1), a few tolerant lines, and one advanced line (BRS Sambaiba) were moderately resistant. All the other advanced lines, commercial varieties, gene bank accessions and collections from the
farmers’ fields were highly susceptible to rust. Rust severity was positively correlated with rust sporulation, indicating that reduction of sporulation made a significant contribution towards rust resistance. An F2 population was generated from a half diallel mating design, involving 4 resistant, 2
moderately resistant and 2 susceptible genotypes selected as parents. The F2 populations along with their parents were evaluated in two environments to determine the type of gene action for rust resistance and other quantitative traits in soybeans. The results revealed that both general combining ability (GCA) and specific combining ability (SCA) were significant for most of the traits studied, indicating that both additive gene action and non-additive gene action played a major role in the inheritance of rust resistance and selected agronomic traits. The GCA/SCA ratio was close to unity for rust severity, rust sporulation, days to flowering, days to
maturity and plant height. This indicated that additive gene action played a more significant role in the inheritance of these traits than non-additive gene action. Non-additive gene action was only predominant for soybean grain yield. Parental lines G10428, G8586 and Namsoy 4M were the best general combiners for improving rust resistance across the environments. The most promising parents for early flowering were G7955, G8586 and G58. Parent Maksoy 1N was the
best general combiner for early maturity while parents Maksoy 1N, G58, G7955 and Nyala contributed effectively towards reduced plant height.
Yield stability analysis was conducted for 30 genotypes in 6 environments, using additive main effects and multiplicative interaction (AMMI), genotype main effect and genotype x environment interaction (GGE) biplot analyses. Genotypes 916/5/19 and G7955 were identified as the high yielding and most stable across the environments. On the other hand, genotypes BRS MG46 and Sable were high yielding but unstable and specifically suitable for the environments EM2 and MW2, respectively (both environments have long rainy seasons). Environment EM2 was identified as the most discriminating and representative among the six environments.
Environments IG1 and MW1 (short rainy seasons) were less informative on genotypes tested, as confirmed by short environment vectors. Environment EM1 was better for discriminating genotypes but was a poor representative of the test environments, hence it should only be
utilized for developing specifically adapted genotypes. Further analysis using GGE biplot approach grouped the environments into three putative mega-environments in Central and Eastern Kenya. Overall, this study established the need to educate farmers on the cause of ASR, to develop
ASR resistant varieties, and to incorporate farmers’ desired traits in the breeding programme, especially by the use of participatory breeding approaches. The resistant and moderately resistant genotypes identified in this study could be used as sources of resistant genes to develop ASR resistant varieties in Kenya. This study also established that genetic improvement for ASR resistance and selected agronomic traits in soybeans is possible based on the use of recurrent selection breeding procedures that result in the accumulation of additive gene effects. Selection of late segregating generations would be effective for soybean grain yield
improvement. This study identified potential parents for ASR resistance and selected agronomic traits, but they require further breeding to improve on farmers’ desired traits. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2012.
|
10 |
Optimising aspects of a soybean breeding programme.January 2008 (has links)
Abstract not available. / Thesis (Ph.D)-University of KwaZulu-Natal, Pietermaritzburg, 2008.
|
Page generated in 0.0863 seconds