Soybean is emerging as a very important food, market and oil crop in Ethiopia. However, its productivity in Western Ethiopia is constrained by several production constraints, of which soil acidity is one of the most important ones. On acidic soils the availability of several plant nutrients is limited; among which phosphorus is the least available. Thus, development of high yielding and low P tolerant soybean varieties need to be among the top priorities in areas with such problematic soils. Therefore, the objectives of the study were to: 1) conduct a Participatory Rural Appraisal (PRA) study to assess farmers’ perception on various soil fertility, soybean consumption and marketing issues, 2) evaluate soybean genotypes under low and high P regimes, and 3) conduct genetic analysis of soybean performance under low and high P conditions. The PRA was conducted to assess farmers’ perception on various soil fertility, soybean consumptions and market issues. A total of 186 soybean producing farmers across three locations of Western Ethiopia were interviewed using a semi-structured questionnaire. Results from the study indicated that the use of soybean for crop rotation and soil fertility improvement was more important to the farmers than household consumption and marketing of the crop. The study also revealed poor demand for soybean compared to other crops on the local market. The majority of respondent farmers’ recognized that soil fertility has been declining over time and obtaining inorganic fertilizers on time was difficult; mainly due to high price of fertilizer. Though farmers’ cooperative was identified as the major supplier of fertilizer, farmers rated the quality of its service in supplying fertilizer as poor. With deteriorating soil fertility and limited capacity to use inorganic fertilizers, farmers are producing soybean under low soil fertility conditions. Thus, breeding programs need to develop varieties that perform well under low fertility soil. Screening soybean genotypes for response to different P regimes was performed in a field experiment using a split plot design, where the main plots were three levels of applied P (0, 100 and 200 kg ha-1 P), and the sub plots were 36 soybean genotypes (G) planted across three locations (L) with two replications. The extent of genetic variation of the 36 soybean genotypes was assessed under low (0 kg ha-1) and high P (100 kg ha-1) conditions. The analysis of variance revealed significant differences among genotypes for all the traits, except pod number at low P; while all the traits, except root volume, pod number, and number of seeds per pod showed significant differences at high P. Plant fresh weight, root fresh weight and root volume exhibited high genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) under both P conditions. Both principal component and cluster analyses revealed variation in the population. The 100-seed weight, plant height, roots and plant fresh weight combined high heritability and genetic advance estimates indicating that the inheritance of such traits is controlled by additive gene action under both P conditions. In general, the study revealed high genetic variation in the population, which can be exploited to improve performance under both high and low P conditions. The analysis of variance revealed significant genotype X phosphorus (GXP) interaction for number of nodules and total nodule weight at Jimma, and Assossa, and for root weight and root volume at Mettu. Though the GXP and GXPXL interactions showed non-significant difference for across locations analysis, the genotypes displayed significant difference for root fresh weight, root volume, tap root length, and weight of effective nodule. Genotypes: Pr-142 (26), AGS-3-1, SCS-1, AGS 234, and H 3 were identified among the best for root and nodulation characteristics. Yield and yield related traits were also assessed separately in the screening program. The results revealed significant GXP interactions for grain yield only at one site; while the genotypes exhibited highly significant differences for most of the traits in all the sites. G and GXL interaction were significantly different for most the traits. Essex 1, IAC 11, and AGS-3-1 were the best performing genotypes at high P; while genotypes IAC 11, AA 7138, G 9945 and AGS-7-1 displayed tolerance to low P. Genotypes AA-7138, PR-142 (26) and H3 exhibited stable performance across the three P levels. These genotypes have paramount significance in breeding soybean for low P tolerance and stable performance in varying P conditions for resource poor subsistence farmers.The genetic control mechanism for the major quantitative traits for performance under high and low P condition was studied in a nine parent half diallel cross. The results revealed that the GCA effects were highly significant for grain yield, pod length, days to maturity and plant height under low-P conditions. GCA effects were highly significant for grain yield, 100-seed weight, days to maturity, plant height, pod number, and pod length under high P. GCA effects were also significant for number of seeds per pod under high P condition. In addition, the relative contribution of GCA was higher than SCA under both P conditions, except for 100-seed weight at low P. Variety Hardee-1 was the best general combiner for most of the quantitative traits under both P conditions, indicating that it can be used in breeding programs to improve soybean for better genetic response to low and high P. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2012.

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.

O elevado valor sócioeconômico da soja é atribuído, em grande parte, à combinação muito favorável de altos teores de proteína e óleo, juntamente com níveis adequados de produtividade de grãos. Porém, existe uma alta correlação negativa entre os teores de proteína e óleo, fato que dificulta o melhoramento simultâneo destes caracteres. Além disso, também existe tendência de correlação negativa e moderada entre o teor de proteína e a produtividade de grãos. Existem evidências de que a seleção para densidade da semente pode promover ganhos indiretos simultâneos no teor de proteína e na produtividade de grãos. Assim, os principais objetivos deste trabalho foram: a) estimar parâmetros genéticos relacionados com a herança da densidade da semente; b) avaliar a eficiência da seleção para densidade da semente no melhoramento do teor de proteína e da produtividade de grãos. Para o estudo de herança foram utilizados quatro cruzamentos diferentes: USP98-06.011.10 x Abura, MSOY 8001 x Abura, USP98-06.027.03 x Biloxi e USP98-06.009.01 x PI 239.235, sendo que os parentais e as plantas F2 foram avaliados durante a safra 2006/07. Já para avaliar as respostas correlacionadas à seleção para densidade da semente foram delineados três experimentos distintos: Experimento Inicial, no qual foram avaliadas 520 progênies F7:6, durante a safra 2005/06; Experimento Densidade, em que foram avaliadas 100 progênies F8:6 selecionadas para densidade da semente; Experimento Alimentos, em que foram avaliadas 100 progênies F8:6 selecionadas para soja tipo alimento. Os dois últimos experimentos foram realizados durante a safra 2006/07, e as progênies avaliadas neles foram selecionadas dentre as 520 progênies F7:6 do Experimento Inicial. Os resultados permitiram chegar as seguintes conclusões: a) existe ampla variabilidade genética para densidade da semente; b) a herdabilidade no sentido amplo para este caráter é baixa quando estimada na geração F2, mas em geração avançada de endogamia atinge valor alto; c) a herança genética é aditiva e, assim, o caráter não manifesta heterose; d) existe correlação moderada e positiva da densidade da semente com a produtividade de grãos e o teor de proteína e, por outro lado, a correlação entre a densidade da semente e o teor de óleo é negativa; e) é possível identificar genótipos tipo alimento com médias altas de produtividade de grãos e teor de proteína; f) a seleção para aumentar a densidade da semente é eficiente no melhoramento simultâneo do teor de proteína e da produtividade de grãos, permitindo a obtenção de genótipos com alta produtividade de proteína; g) a seleção para reduzir a densidade da semente não promove aumentos significativos do teor de óleo. / The high socioeconomic importance of soybean is mainly attributed to its much favorable combination of high protein and oil contents, together with appropriate levels of seed yield. However, there is a high negative correlation between protein and oil contents, fact that difficult the simultaneous breeding of these traits. Besides, also there is tendency of negative and moderate correlation between protein content and seed yield. There are evidences that the selection for seed density can promote indirect responses in protein content and seed yield, simultaneously. The main objectives of this work were: a) to estimate genetic parameters related to inheritance of seed density; b) to evaluate the efficiency of selection for seed density in breeding protein content and seed yield. In the inheritance study, four different crosses were used: USP98-06.011.10 x Abura, M-SOY 8001 x Abura, USP98-06.027.03 x Biloxi e USP98-06.009.01 x PI 239.235. The parents and F2 plants were evaluated during the 2006/07 season. For evaluating the correlated responses to selection for seed density three different experiments were designed: the Initial Experiment, in which were evaluated 520 F7:6 progenies, during the 2005/06 season; the Seed Density Experiment, in that were evaluated 100 F8:6 progenies selected for seed density; and the Food Soybean Experiment, in that were evaluated 100 F8:6 progenies selected for food type soybean. The last two experiments were accomplished during the 2006/07 season, and the progenies were selected among the 520 F7:6 progenies of the Initial Experiment. The results allowed the following conclusions: a) there is genetic variability for seed density; b) the broad sense heritability for seed density is low in F2 and high in advanced generations; c) the genetic inheritance is additive, because this, there is no heterosis for seed density; d) there is moderate and positive correlation of seed density with seed yield and protein content, but the correlation between seed density and oil content is negative; e) is possible to identify food type genotypes with high means of seed yield and protein content; f) the selection to increase seed density is efficient in breeding protein content and seed yield simultaneously, obtaining genotypes with high protein yield; g) the selection to reduce seed density promote no significant increases of oil content.

A soja é um dos alimentos mais completos conhecidos pelo homem. A soja hortaliça ou \"edamame\" pertence à mesma espécie da soja cultivada para grãos, Glycine max (L.) Merrill. Edamame é um nome de origem japonesa usado para um tipo de soja consumida no estádio imaturo R6 e, também, caracterizada por terem vagens e grãos de tamanho grande, melhor textura e sabor. Apresenta grande potencial nutracêutico, favorecendo a manutenção da saúde e a redução dos riscos de diversas doenças crônicas. Os principais objetivos deste trabalho foram: a) estimar parâmetros genéticos úteis ao melhoramento, especialmente a interação genótipos x ambientes; b) avaliar adaptabilidade e estabilidade dos genótipos e a representatividade de ambientes; c) caracterizar os cruzamentos e suas progênies visando-se à extração de linhagens superiores. Os genótipos compreendem 42 progênies nas gerações F6:10 a F6:13 de 23 cruzamentos e três testemunhas (BRS 257, BRS 267 e IAC 100). As avaliações experimentais foram feitas em dois estádios de desenvolvimento, soja imatura R6 (dois anos agrícolas, 2011/12 e 2012/13) e soja matura R8 (quatro anos agrícolas, de 2009/10 a 2012/13). Os quatro anos agrícolas e três locais (Anhumas, Areão e ESALQ) foram combinados em nove ambientes. Em cada ambiente foram realizados dois experimentos envolvendo manejos distintos de fungicidas; no primeiro experimento foram feitas aplicações sucessivas de fungicidas para controle da ferrugem asiática da soja (FAS) e das doenças de final de ciclo (DFC), enquanto que no segundo experimento foram aplicados fungicidas para controle somente das DFC. Cada experimento foi delineado em blocos ao acaso, com três repetições. Cada repetição foi estratificada em dois conjuntos experimentais com testemunhas comuns, cada um deles conformando um bloco aumentado de Federer. A parcela experimental foi uma fileira com 5 metros x 0,50 m. As fontes de variação \"anos\", \"locais\" e \"fungicidas\" contribuíram significativamente na interação entre genótipos e ambientes, em ambos os estádios R6 e R8. Para a produtividade de vagens (PV) em R6, o método de Eberhart e Russell destacou quatro cruzamentos (19-005: USP 98-06.005 x J-75, 19-006: USP 98-06.005 x Hakucho, 19-045: USP 98-06.031 x Hakucho e 19-111: USP 98-06.029 x OCEPAR-4), gerando 15 progênies (destaques para 19-045-03-01 e 19-111-02-06) com alto potencial para uso como genitores e ou cultivares. A análise AMMI revelou que a grande maioria dos genótipos mostraram-se estáveis e com PV em torno de 150 g/2plantas. O maior destaque ficou com a progênie 19-111-01-09, com desempenho muito favorável para os caracteres de R6, alta produtividade de grãos (PG) e tolerância à ferrugem em R8. Para o estádio R8, o efeito de locais determinou que Areão foi o melhor local, para PG e peso de cem sementes (PSC). Para o estádio R6, o efeito de anos indicou que o ano agrícola 2012/13 foi o que mais favoreceu o desempenho das progênies para todos os caracteres. Foram detectadas correlações altas e significativas entre os caracteres PCS em R8 e peso de cem vagens em R6 (0,808**), bem como entre PCS e largura das vagens em R6 (0,725**). / Soybean is one of the most complete food known by the human being. The vegetable soybean or \"edamame\" belongs to the same species of the soybean cultivated as commodity, Glycine max (L.) Merrill. Edamame is a name with Japanese origin used for maintenance and reduction of the risks of several chronic diseases. The main objectives of this study were: a) to estimate useful genetic parameters to the breeding program of soybean vegetable, specially the genotype x environment interaction; b) to evaluate adaptability and stability of the genotypes and the representativeness of the environments; c) to characterize crosses and their progenies aiming the extraction of superior inbred lines. The genotypes corresponded to 23 crosses and their 42 progenies in advanced generations of inbreeding, that is from F6:10 to F6:13 generation, besides three common checks (BRS 257, BRS 267, and IAC 100). They were evaluated in two developmental stages, immature R6 and mature R8 soybean, during two (2011/12 and 2012/13) and four (2009/10 to 2012/13) growing seasons, respectively. The four crop years and three locations (Anhumas, Areão and ESALQ) were combined in nine environments. In each environment, there were carried out two experiments involving two fungicide managements; in the first experiment, there were made successive fungicide applications for controlling Asian soybean rust (FAS) and late season leaf diseases (DFC), whereas in the second experiment there were made fungicide applications for controlling only DFC. Each experiment was designed in a randomized complete-block design with three replications. Each repetition was divided into two experimental sets with common checks, forming an augmented design (Federer). The experimental plot was a row with 5 m x 0.50 m. The \"crop years\", \"locations\" and \"fungicides\" contributed significantly to the genotypes x environments interactions in both R6 and R8 stages. For pod yield (PV) in the R6 stage, the Eberhart and Russell method highlighted four crossings (19-005: USP 98-06005 x J-75, 19- 006: USP 98-06005 x Hakucho, 19-045: USP 98-06031 x Hakucho and 19 -111: USP 98- 06029 OCEPAR-4), generating 15 progenies (especially the numbers 19-045-03-01 and 19- 111-02-06) with the highest potential to be used as parents and or as new cultivars. The biggest highlight was the progeny 19-111-01-09, with very favorable performance for R6 traits, high seed yield (PG) and tolerance to rust in R8. The AMMI analysis revealed that almost all genotypes were stable and with PV around 150 g/2plants. For the R8 stage, the location effect determined that Areão was the best location for PG and one hundred seed weight (PCS). For the R6 stage, the year effect indicated that the crop year 2012/13 was the most favorable for the progeny performance for all traits. There were estimated highly significant correlation between PCS in R8 and one hundred pod weight in R6 (0.808 **), as well as between PCS and pod width in R6 stage (0.725**).

A soja é um dos alimentos mais completos conhecidos pelo homem. A soja hortaliça ou \"edamame\" pertence à mesma espécie da soja cultivada para grãos, Glycine max (L.) Merrill. Edamame é um nome de origem japonesa usado para um tipo de soja consumida no estádio imaturo R6 e, também, caracterizada por terem vagens e grãos de tamanho grande, melhor textura e sabor. Apresenta grande potencial nutracêutico, favorecendo a manutenção da saúde e a redução dos riscos de diversas doenças crônicas. Os principais objetivos deste trabalho foram: a) estimar parâmetros genéticos úteis ao melhoramento, especialmente a interação genótipos x ambientes; b) avaliar adaptabilidade e estabilidade dos genótipos e a representatividade de ambientes; c) caracterizar os cruzamentos e suas progênies visando-se à extração de linhagens superiores. Os genótipos compreendem 42 progênies nas gerações F6:10 a F6:13 de 23 cruzamentos e três testemunhas (BRS 257, BRS 267 e IAC 100). As avaliações experimentais foram feitas em dois estádios de desenvolvimento, soja imatura R6 (dois anos agrícolas, 2011/12 e 2012/13) e soja matura R8 (quatro anos agrícolas, de 2009/10 a 2012/13). Os quatro anos agrícolas e três locais (Anhumas, Areão e ESALQ) foram combinados em nove ambientes. Em cada ambiente foram realizados dois experimentos envolvendo manejos distintos de fungicidas; no primeiro experimento foram feitas aplicações sucessivas de fungicidas para controle da ferrugem asiática da soja (FAS) e das doenças de final de ciclo (DFC), enquanto que no segundo experimento foram aplicados fungicidas para controle somente das DFC. Cada experimento foi delineado em blocos ao acaso, com três repetições. Cada repetição foi estratificada em dois conjuntos experimentais com testemunhas comuns, cada um deles conformando um bloco aumentado de Federer. A parcela experimental foi uma fileira com 5 metros x 0,50 m. As fontes de variação \"anos\", \"locais\" e \"fungicidas\" contribuíram significativamente na interação entre genótipos e ambientes, em ambos os estádios R6 e R8. Para a produtividade de vagens (PV) em R6, o método de Eberhart e Russell destacou quatro cruzamentos (19-005: USP 98-06.005 x J-75, 19-006: USP 98-06.005 x Hakucho, 19-045: USP 98-06.031 x Hakucho e 19-111: USP 98-06.029 x OCEPAR-4), gerando 15 progênies (destaques para 19-045-03-01 e 19-111-02-06) com alto potencial para uso como genitores e ou cultivares. A análise AMMI revelou que a grande maioria dos genótipos mostraram-se estáveis e com PV em torno de 150 g/2plantas. O maior destaque ficou com a progênie 19-111-01-09, com desempenho muito favorável para os caracteres de R6, alta produtividade de grãos (PG) e tolerância à ferrugem em R8. Para o estádio R8, o efeito de locais determinou que Areão foi o melhor local, para PG e peso de cem sementes (PSC). Para o estádio R6, o efeito de anos indicou que o ano agrícola 2012/13 foi o que mais favoreceu o desempenho das progênies para todos os caracteres. Foram detectadas correlações altas e significativas entre os caracteres PCS em R8 e peso de cem vagens em R6 (0,808**), bem como entre PCS e largura das vagens em R6 (0,725**). / Soybean is one of the most complete food known by the human being. The vegetable soybean or \"edamame\" belongs to the same species of the soybean cultivated as commodity, Glycine max (L.) Merrill. Edamame is a name with Japanese origin used for maintenance and reduction of the risks of several chronic diseases. The main objectives of this study were: a) to estimate useful genetic parameters to the breeding program of soybean vegetable, specially the genotype x environment interaction; b) to evaluate adaptability and stability of the genotypes and the representativeness of the environments; c) to characterize crosses and their progenies aiming the extraction of superior inbred lines. The genotypes corresponded to 23 crosses and their 42 progenies in advanced generations of inbreeding, that is from F6:10 to F6:13 generation, besides three common checks (BRS 257, BRS 267, and IAC 100). They were evaluated in two developmental stages, immature R6 and mature R8 soybean, during two (2011/12 and 2012/13) and four (2009/10 to 2012/13) growing seasons, respectively. The four crop years and three locations (Anhumas, Areão and ESALQ) were combined in nine environments. In each environment, there were carried out two experiments involving two fungicide managements; in the first experiment, there were made successive fungicide applications for controlling Asian soybean rust (FAS) and late season leaf diseases (DFC), whereas in the second experiment there were made fungicide applications for controlling only DFC. Each experiment was designed in a randomized complete-block design with three replications. Each repetition was divided into two experimental sets with common checks, forming an augmented design (Federer). The experimental plot was a row with 5 m x 0.50 m. The \"crop years\", \"locations\" and \"fungicides\" contributed significantly to the genotypes x environments interactions in both R6 and R8 stages. For pod yield (PV) in the R6 stage, the Eberhart and Russell method highlighted four crossings (19-005: USP 98-06005 x J-75, 19- 006: USP 98-06005 x Hakucho, 19-045: USP 98-06031 x Hakucho and 19 -111: USP 98- 06029 OCEPAR-4), generating 15 progenies (especially the numbers 19-045-03-01 and 19- 111-02-06) with the highest potential to be used as parents and or as new cultivars. The biggest highlight was the progeny 19-111-01-09, with very favorable performance for R6 traits, high seed yield (PG) and tolerance to rust in R8. The AMMI analysis revealed that almost all genotypes were stable and with PV around 150 g/2plants. For the R8 stage, the location effect determined that Areão was the best location for PG and one hundred seed weight (PCS). For the R6 stage, the year effect indicated that the crop year 2012/13 was the most favorable for the progeny performance for all traits. There were estimated highly significant correlation between PCS in R8 and one hundred pod weight in R6 (0.808 **), as well as between PCS and pod width in R6 stage (0.725**).

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.

Abstract not available. / Thesis (Ph.D)-University of KwaZulu-Natal, Pietermaritzburg, 2008.