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The inheritance and interrelationship of pod dehiscence and some other agronomic characters in soybeansZiegler, K. E. (Kenneth Edward) January 2010 (has links)
Digitized by Kansas Correctional Industries
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Soybean (Glycine max L. Merrill) nodulation, growth and grain yield as influenced by N fertilizer, population density and cultivar in southern QuebecChen, Zhengqi, 1959- January 1990 (has links)
Soybean growth with respect to N fertilizer rates, plant population densities and two cultivars was investigated on three Quebec soils at four sites. Soybean nodulation, growth, grain yields and nutrient uptake at three developmental stages were investigated. Soil nitrate levels after harvest were also studied. / N fertilizer application depressed soybean nodulation consistently, but improved soybean growth where initial soil nitrate levels were low. Grain yield was increased at one site with added N, where soybean growth was stressed by low initial soil nitrate levels (below 17 kg N/ha) and severe summer drought. Soybean N and K uptake were increased with increased N fertilizer but P uptake was not affected. Residual soil nitrate content in the 0-50 cm depth in the fall of the crop year increased linearly and this effect carried over to the following spring. / Plant population had little effect on individual plant nodulation but increased fresh nodule mass per unit area. Plant biomass, grain yield and nutrient uptake were increased with increased population densities. / The cultivar Apache had better nodulation potential and grain yield potential and was better adapted to intensive management practices with high plant populations than the cultivar Maple-Arrow.
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Soybean (Glycine max L. Merrill) nodulation, growth and grain yield as influenced by N fertilizer, population density and cultivar in southern QuebecChen, Zhengqi, 1959- January 1990 (has links)
No description available.
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COMPARATIVE STUDIES OF PHYSIOLOGICAL AND MITOCHONDRIAL PHOTORESPONSES IN SOYBEAN (GLYCINE MAX, L. MERR.) CULTIVARSMohamed-Osman, Ahmed Mutwakil, 1936- January 1973 (has links)
No description available.
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Factors affecting selection of double-crop soybean genotypesEggers, Dexter. January 1985 (has links)
Call number: LD2668 .T4 1985 E39 / Master of Science
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Responses of ten soybean [ glycine max (L.) merrill] genotypes for yield and nodulation to trichoderma and silicon applications.Jadoo, Shiksha. 01 November 2013 (has links)
A study was conducted to determine the responses of 10 selected soybean (Glycine max L.) genotypes to potassium silicate (KSi) and Trichoderma harzianum (Eco-T®) applications. Preliminary studies involving two independent experiments were conducted under controlled conditions at the University of KwaZulu-Natal during 2010. Potassium silicate at three concentrations (0, 200 and 250ppm) were applied twice weekly over a period of four months to the genotypes laid out in a randomized complete
block design. Subsequently, a field experiment was conducted at Ukulinga Research Farm of the University of KwaZulu-Natal, Pietermaritzburg during 2010/2011 to investigate the responses of the genotypes to KSi at 0 and 200ppm, with and without(Eco-T®) seed treatment. This experiment was set out in a randomized complete block design with three replications. Data collected included number of days to 50% flowering, number of days to 50% maturity, plant height, number of pods per plant, number of seeds per pod, 100 seed weight, root mass, shoot mass, seed yield and harvest index. The total number of root nodules formed and the number of active
nodules were determined at end of the field experiment. In most cases a decrease was noted in total nodule formation as well as a decrease in the number of active nodules that formed. In the controlled environments there was a significant interaction between genotype and KSi concentrations for all measured traits. In most cases KSi applied at 200ppm was more successful in enhancing growth, improving seed yield and resulted in high harvest indices. The genotypes that produced the highest seed yield and harvest index in these environments were Williams and Barc-2 at 200ppm KSi. Results from correlation analysis revealed that harvest index and seed yields were generally positively associated with plant height, number of pods per plant and 100 seed weight, which in turn were the traits that contributed to most of the variation to seed yield and harvest index as revealed in the principle component analysis (PCA). The field experiment revealed a significant interaction between genotype x KSi x Eco-T®.
Potassium silicate applied at 200ppm with Eco-T® usually promoted growth, seed yield and high harvest indices for all the genotypes. The PCA showed seed yield and harvest index were the traits that contributed to most of the variation. Genotypes Williams, LS6161R, Magoye and Barc-2 were the best seed yielders with the highest harvest indices that responded strongly to the combined use of KSi and Eco-T® under field
conditions. Genetic comparison of the ten soybean genotypes with eight microsatellite markers revealed the close genetic relationship between Williams, LS6161 R and Magoye. A link between Barc-2 and Williams was noted by the common parent Clark. Therefore, for these genotypes, the application of KSi at 200 ppm with Eco-T® under field conditions effectively increased seed yield, ranging from 0.45 to 65.26% for some genotypes when compared to the control. An increase was also noted for other
agronomic traits and harvest index. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2012.
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Breeding gains diversity analysis and inheritance studies on soybean (Glycine max (L.) Merrill) germplasm in Zimbabwe.Mushoriwa, Hapson. 09 May 2014 (has links)
The soybean programme in Zimbabwe is over seventy years old. However, there is lack of
information on breeding gains, genetic diversity, heritability, genetic advance, combining
ability, gene action and relationships between grain yield and secondary traits available for
breeding. Therefore, the aim of the present study was to characterise the genetic diversity of
the available germplasm, determine gene action conditioning grain yield and estimate the
breeding gains that have been realised since the inception of the breeding programme.
Evaluation of 42 soybean genotypes for genetic diversity conducted during 2010/11 and
2011/12 cropping seasons, using phenotypic and molecular characterisation approaches,
revealed evidence of wide diversity among the genotypes. The phenotypic traits and SSR
markers assigned the soybean genotypes to 8 and 15 clusters respectively. The SSR
marker technique was more polymorphic, informative and highly discriminatory. The
clustering pattern and relatedness from SSR data was in agreement with the pedigree data
while the phenotypic clustering was divorced from pedigree data. Genotypes, G41 and G7;
G41 and G1; G41 and G42 were the most divergent; therefore, they could be utilized as
source germplasm in cultivar development and commercial cultivars.
Investigations on breeding gains involving 42 cultivars (representing a collection of all the
varieties that were released in Zimbabwe from 1940 to 2013) showed that improvement in
grain yield was slowing down. However, annual genetic gain was estimated to be 47 kg ha-1
year-1 representing an annual gain of 1.67%. Furthermore, grain yield ranged from 2785 to
5020 kg ha-1. Genotypes, G16, G15, G17, G1 and G42 exhibited superior performance in
grain yield and other agronomic traits and are therefore, recommended for utilisation in the
hybridisation programme. Seed protein concentration decreased by 0.02 year-1 while oil
increased by 0.02, 100 seed weight increased by 0.21 g year-1 over time. In addition, number
of days to 95% pod maturity and pod shattering increased by 0.35 and 0.38 days year-1
respectively while lodging declined by 0.31%. Results indicated that emphasis should be
refocused on grain yield to restore the original linear increase.
Assessment of the magnitude of GEI and stability of 42 released cultivars was done over 13
environments and two seasons using additive main effects and multiplicative interaction,
cultivar superiority and rank analyses. Results showed that environment and GEI captured
larger portion of the total sum of squares, which reveals the influence of the two factors on
grain yield, hence, the need for evaluating soybean genotypes in multi-environment trials
and over years. Further, the data revealed that GEI was of a crossover type because of
differential yield ranking of genotypes. The three stability parameters selected two
genotypes, G1 and G15, as the most productive, consistent and stable, thus they could be produced in diverse environments while G2, G4, G5, G7, G16, G40, G17, G18 and G31 were identified as unstable and suitable for specific adaptation.
Correlation and path analyses showed that grain yield was positively and significantly correlated with number of branches per plant, number of nodes per plant, shelling percentage, and number of days from 95% pod maturity to first pod shattering, implying that breeding and selection for these traits probably improved grain yield. Number of nodes per plant, plant height and 100 seed weight exhibited highest direct effects on grain yield while, number of nodes per plant and plant height presented the highest indirect effects on grain yield. These results demonstrated that number of nodes per plant and plant height could be recommended as reliable selection traits for developing high yielding genotypes of soybean. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2013.
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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.
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