Browsing by Author "Obua, Tonny"

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    Genetic Diversity and Population Structure Analysis of Tropical Soybean (Glycine Max (L.) Merrill) using single Nucleotide Polymorphic Markers
    (Global Journal of Science Frontier Research, 2020) Obua, Tonny; Sserumaga, Julius P.; Opiyo, Stephen O.; Tukamuhabwa, Phinehas; Odong, Thomas L.; Mutuku, Josiah; Yao, Nasser
    Soybean (Glycine max (L.) Merrill) is among the most important crops worldwide due to its numerous uses in feed, food, biofuel, and significant atmospheric nitrogen fixation capability. To understand the genetic diversity and population structure of tropical soybean germplasm, 89 genotypes from diverse sources were analyzed using 7,962 SNP markers. The AMOVA results showed low diversity among and high within the populations, while the polymorphism information content (PIC) was 0.27. Both phylogenetic and principal component analysis grouped the 89 soybean genotypes into three major clusters, while population structure grouped the soybean genotypes into two subpopulations. On the other, the average Roger genetic distances within the study population was 0.34. The low diversity reported in the studied soybean germplasm pool is particularly worrying, considering the new trends of climate change and the emergence of new pests and diseases of soybean. Therefore, in order to address these challenges and develop soybean varieties with desirable traits, there is a need to broaden the genetic base of tropical soybean through the importation of germplasm from other countries.
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    Multi-Environmental Evaluation of Protein Content and Yield Stability among Tropical Soybean Genotypes Using GGE Biplot Analysis
    (Agronomy, 2021) Obua, Tonny; Sserumaga, Julius Pyton; Awio, Bruno; Nganga, Fredrick; Odong, Thomas L.; Tukamuhabwa, Phinehas; Tusiime, Geoffrey; Mukasa, Settumba B.; Nabasirye, Margaret
    The yield and protein performance in a soybean genotype result from its interaction with the prevailing environmental conditions. This makes selecting the best genotypes under varied target production environments more complex. This study’s objectives were to determine protein content and protein stability of 30 elite soybean genotypes in major soybean-growing areas of Uganda, assess the yield performance and stability in soybeans and determine the relationship between the protein content and grain yield in soybeans. The genotypes were planted in a randomized complete block design of three replications for six seasons across eight locations in Uganda. Genotype and genotypeby- environment (GGE) biplot analyses classified the test locations into three mega-environments for soybean protein and grain yields. Genotype NII X GC 20.3 had the highest mean protein content of 43.0%, and BSPS 48A-9-2 and BSPS 48A-28 were superior for the mean grain yield (1207 kg ha􀀀1). Bulindi was the most discriminating and representative test environment for soybean yield. A weak and negative correlation (r = 􀀀0.1**, d.f. = 29) was detected between the protein content (%) and yield (kg ha􀀀1). The highest-yielding genotypes BSPS 48A-9-2, BSPS 48A-31, and Nam II GC 44.2 are recommended for further evaluation under farmers’ production conditions for selection and release as new soybean varieties in Uganda.
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    Nutrient Profiling of Tropical Soybean (Glycine Max) Core Collection
    (Global Journal of Science Frontier Research, 2020) Obua, Tonny; Sserumaga, Julius P.; Nganga, Fredrick; Tukamuhabwa, Phineas; Odong, Thomas L.; Mutuku, Josiah; Yao, Nasser
    Soybean (Glycine max (L.) Merrill) is a highly nutritious legume with enormous potential to improve dietary quality for humans and livestock. However, the development of varieties with improved nutritional traits has been affected by the negative correlation that exists among the different traits and the high cost of the phenotypic assessment. The objectives of this study were: (1) to quantify the total protein, total oil and fatty acids of 52 soybean genotypes from different sources, (2) to identify correlations among total protein, total oil content and fatty acids. The total protein content was determined using the Modified Folin-Lowry Method. In contrast, the total oil and fatty acids methyl esters were determined using the chloroform/methanol gravimetric method and Gas Chromatography–Mass Spectrometry. The analysis of variance revealed that the studied traits varied significantly depending on genotypes and origin.