Soybean rust (SBR) caused by Phakopsora pachyrhizi Syd. is an aggressive wind dispersed fungal disease which has spread around the world at an alarming rate in the last decade. The disease was first reported in South Africa (SA) in 2001. It has become well established in the province of KwaZulu-Natal. Reports are occasionally made from eastern Mpumalanga, late in the growing season, in years with good rainfall. Yield losses of 10 - 80% have been reported due to SBR infection. Literature was reviewed to better understand the pathogen in an attempt to find suitable disease management strategies. Many strategies involve delaying, rather than preventing, SBR infection. Of the two strategies to prevent infection, the use of fungicides was the only option for disease control in SA, as no resistant cultivars are available. Field trials were conducted to determine which fungicides are effective in controlling SBR. Further research was conducted to determine the timing, frequency and rate of fungicide applications for optimal control of SBR. Trials were evaluated for disease severity, seed yield and the effect of fungicides on seed quality. Fungicides from the triazole class of the sterol biosynthesis inhibiting group of fungicides were found to be the most effective in controlling SBR. A fungicide from the strobilurin group was found to be less effective than the triazoles at the suggested rate, but was found to be as effective when evaluated at higher dosage rates. Triazoles premixed with fungicides from the benzimidazole and strobilurin groups were also effective in controlling SBR. Timing of application was found to be critical for strobilurin fungicides, but not for triazole fungicides, which have a curative ability, unlike strobilurins. Strobilurin fungicides applied preventatively, before the appearance of disease symptoms were as effective as triazole fungicides applied after disease symptoms, but before infection levels had reached 10%. Across both wet and dry seasons two fungicide applications applied at 21d intervals at the R2 growth stage resulted in effective disease control. In wet seasons, a third fungicide application resulted in yields that were higher, albeit not statistically significant, than two fungicide applications. Assessments of individual fungicides for optimal dosage rate found that registered rates were already optimal for some fungicides, but for others it appeared as if alterations were necessary to the rate suggested for registration. This study was one of the first to extensively evaluate the efficacy of the new triazole and strobilurin fungicides on SBR control. The results have been shared globally, but particularly with newly affected countries in South and North America. Although this research has been groundbreaking, there are still many aspects of fungicide control which need to be studied in order to further optimise chemical control of SBR. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2005

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.

Soybean rust (SBR), caused by the fungus Phakopsora pachyrhizi Syd., is a real threat to soybean crops in South Africa. Its ability to spread rapidly and its potential to severely reduce yields have earned it the reputation as the most destructive foliar disease of soybeans. SBR has been reported in South Africa every year since its arrival in 2001. While extensive research had been done on the epidemiology and fungicide application requirements in South Africa, no work into the long term climatic vulnerability of soybean production areas to SBR had been done. This meant soybean producers do not know whether SBR is a threat in their areas. Through this research a SBR algorithm was developed using readily available climate data, viz. temperature and rainfall, to create a daily index specifying the climatic vulnerability of SBR infection. The algorithm was applied to a 50 year historical climate database, and a series of maps was created illustrating the long term vulnerability of different areas to SBR infection. These maps allow soybean producers to understand the climatic vulnerability of their area to SBR infection. Time series graphs were created for selected key soybean production areas to allow soybean producers to distinguish periods of high and low climatic risk during the season. This may help with decisions regarding the planting times, the maturation rate of different cultivars as well as the timing and application of fungicides. The framework for a near real time forecasting system was created outlining how the system could amalgamate recently recorded and forecasted weather data, run it through the SBR algorithm and provide a near real time, as well as forecasted vulnerability, based on the climatic conductivity for SBR infection. Anticipated limitations and difficulties on developing the forecasting system are also outlined. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2009.

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