Browsing by Author "Mwila, Natasha"
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Item Additive Main Effects and Multiplicative Interactions Analysis of Yield Performances in Cowpea Genotypes under Ugandan Environments(International Journal of Advanced Research (IJAR), 2017) Agbahoungba, Symphorien; Karungi, Jeninah; Talwana, Herbert; Badji, Arfang; Kumi, Frank; Mwila, Natasha; Edema, Richard; Gibson, Paul; Rubaihayo, PatrickYield in legumes is the result of many plant processes, which are usually expressed in yield and have been shown to be affected by management, genotype and environment. The objectives of this study were to assess the extent of genotype x environment interaction and to select the stable cowpea genotypes in Ugandan environments over seasons. Seventy-two cowpea genotypes were evaluated for yield in three locations and two seasons in Uganda. The yield data were subjected to analysis of variance and additive main effects and multiplicative interactions (AMMI) analysis. The results showed a highly significant (P<0.001) genotype by location and by year (season) interaction effects for grain yield, with 69.16% of the total variation attributable to environmental effects, 5.36% to genotypic effects and 12.74% to G x E interactions effects. Genotype MU9 had the highest yield (854.68 kgha-1) but was only adapted to specific environments (Arua 2015B and 2016A). Hence, genotypes WC 30, NE 45, NE 31, NE 51 which were equally high yielding, stable and adapted to the tested environments, and should be recommended for genetic improvement of cowpea germplasm in Uganda.Item Continuous Storage Root Formation and Bulking in Sweet potato(Gates Open Research, 2019) Bararyenya, Astere; Tukamuhabwa, Phinehas; Gibson, Paul; Grüneberg, Wolfgang; Ssali, Reuben; Low, Jan; Odong, Thomas; Ochwo-Ssemakula, Mildred; Talwana, Herbert; Mwila, Natasha; Mwanga, RobertSweetpotato (Ipomoea batatas (L.) Lam, family Convolvulaceae.) is one of the most important food crops worldwide, with approximately 106 million tons produced in almost 120 countries from an area of about 8 million ha and an average global yield of 11.1 tons/ha (FAO, 2016). Asia is the world’s largest sweetpotato producing continent, with 79 million tons, followed by Africa (FAOstat, 2016). About 75% of this global production is from China alone. A total of 21.3 million tons is produced in Africa, with 48% from the Great Lakes region. In East Africa, the crop is the second most important root crop after cassava and has played an important role as a famine-relief crop during its long history and has recently been reevaluated as a health-promoting food (Low et al., 2017). Uganda ranks as the fourth largest sweetpotato producer in the world after China, Nigeria and Tanzania, with a production of 2.1 million t. In Africa, Uganda is ranked third after Nigeria and Tanzania. Sweetpotato is one of the main staple crops in the food systems of Uganda, Rwanda, and Burundi with a per capita consumption of 50.9, 80.1 and 57.0 kg, respectivelyItem Factors Influencing Genomic Prediction Accuracies of Tropical Maize Resistance to Fall Armyworm and Weevils(Plants, 2021) Badji, Arfang; Machida, Lewis; Kwemoi, Daniel Bomet; Kumi, Frank; Okii, Dennis; Mwila, Natasha; Agbahoungba, Symphorien; Ibanda, Angele; Bararyenya, Astere; Ndapewa Nghituwamhata, Selma; Odong, Thomas; Wasswa, Peter; Otim, Michael; Ochwo-Ssemakula, Mildred; Talwana, Herbert; Asea, Godfrey; Kyamanywa, Samuel; Rubaihayo, PatrickGenomic selection (GS) can accelerate variety improvement when training set (TS) size and its relationship with the breeding set (BS) are optimized for prediction accuracies (PAs) of genomic prediction (GP) models. Sixteen GP algorithms were run on phenotypic best linear unbiased predictors (BLUPs) and estimators (BLUEs) of resistance to both fall armyworm (FAW) and maize weevil (MW) in a tropical maize panel. For MW resistance, 37% of the panel was the TS, and the BS was the remainder, whilst for FAW, random-based training sets (RBTS) and pedigree-based training sets (PBTSs) were designed. PAs achieved with BLUPs varied from 0.66 to 0.82 for MW-resistance traits, and for FAW resistance, 0.694 to 0.714 for RBTS of 37%, and 0.843 to 0.844 for RBTS of 85%, and these were at least two-fold those from BLUEs. For PBTS, FAWresistance PAs were generally higher than those for RBTS, except for one dataset. GP models generally showed similar PAs across individual traits whilst the TS designation was determinant, since a positive correlation (R = 0.92***) between TS size and PAs was observed for RBTS, and for the PBTS, it was negative (R = 0.44**). This study pioneered the use of GS for maize resistance to insect pests in sub-Saharan Africa.Item Genetic diversity and population structure of Peronosclerospora sorghi isolates of Sorghum in Uganda(International Journal of Environment, Agriculture and Biotechnology (IJEAB), 2018) Kumi, Frank; Agbahoungba, Symphorien; Badji, Arfang; Mwila, Natasha; Ibanda, Angele; Anokye, Michael; Odong, Thomas; Wasswa, Peter; Ochwo- Ssemakula, Mildred; Tusiime, Geoffrey; Biruma, Moses; Kassim, Sadik; Rubaihayo, PatrickSorghum is the third most important staple cereal crop in Uganda after maize and millet. Downy mildew disease is one of the most devastating fungal diseases which limits the production and productivity of the crop. The disease is caused by an obligate fungus, Peronosclerospora sorghi (Weston & Uppal) with varying symptoms. Information on the genetic diversity and population structure of P.sorghi in sorghum is imperative for the screening and selection for resistant genotypes and further monitoring possible mutant(s) of the pathogen. Isolates of P. sorghi infecting sorghum are difficult to discriminate when morphological descriptors are used. The use of molecular markers is efficient, and reliably precise for characterizing P. sorghi isolates. This study was undertaken to assess the level of genetic diversity and population structure that exist in P. sorghi isolates in Uganda.Item Influence of environment on soybean [Glycine max (L.) Merr.] resistance to groundnut leaf miner, Aproaerema modicella (Deventer) in Uganda(Journal of Plant Breeding and Crop Science, 2018) Pembele Ibanda, Angele; Karungi, Jeninah; Malinga, Geoffrey Maxwell; Adjumati Tanzito, Georges; Ocan, David; Badji, Arfang; Mwila, Natasha; Lapaka Odong, Thomas; Tukamuhabwa, Phinehas; Rubaihayo, PatrickGroundnut leaf miner (GLM) [Aproaerema modicella (Deventer)] is a serious problem for soybean cultivation in Uganda causing yield losses of up to 100%. The use of soybean [Glycine max (L.) Merr.] cultivars resistant to GLM attack is an important strategy in the integrated pest management program. The aim of this study was to determine the environment × genotype interaction influence on the soybean resistance traits to GLM attack. Eighteen soybean genotypes were evaluated for resistance to GLM attack. The experiment was set up using randomized complete block design replicated three times under natural pest infestation in Budaka (Eastern) and Arua (Northern) districts in Uganda. Data were subjected to analysis of variance, Pearson’s phenotypic correlation and cluster analysis. Highly significant (p < 0.001) differences among the genotypes were recorded for all the studied traits, except the number of pupae per plant which was significant (p < 0.05). GLM incidence and severity had significant negative correlations with rainfall and relative humidity. However, there were significant positive correlations between minimum temperature and GLM incidence as well as severity for most of the genotypes. Soybean genotypes VI046160 and VI046167 could be used as parents in breeding for resistance to GLM pest. Areas with high rainfall and humidity would be recommended for soybean production to minimize infestation by GLM.Item Influence of environment on soybean [Glycine max (L.) Merr.] resistance to groundnut leaf miner, Aproaerema modicella (Deventer) in Uganda(Journal of Plant Breeding and Crop Science, 2018) Pembele Ibanda, Angele; Karungi, Jeninah; Malinga, Geoffrey Maxwell; Adjumati Tanzito, Georges; Ocan, David; Badji, Arfang; Mwila, Natasha; Lapaka Odong, Thomas; Tukamuhabwa, Phinehas; Rubaihayo, PatrickGroundnut leaf miner (GLM) [Aproaerema modicella (Deventer)] is a serious problem for soybean cultivation in Uganda causing yield losses of up to 100%. The use of soybean [Glycine max (L.) Merr.] cultivars resistant to GLM attack is an important strategy in the integrated pest management program. The aim of this study was to determine the environment × genotype interaction influence on the soybean resistance traits to GLM attack. Eighteen soybean genotypes were evaluated for resistance to GLM attack. The experiment was set up using randomized complete block design replicated three times under natural pest infestation in Budaka (Eastern) and Arua (Northern) districts in Uganda. Data were subjected to analysis of variance, Pearson’s phenotypic correlation and cluster analysis. Highly significant (p < 0.001) differences among the genotypes were recorded for all the studied traits, except the number of pupae per plant which was significant (p < 0.05). GLM incidence and severity had significant negative correlations with rainfall and relative humidity. However, there were significant positive correlations between minimum temperature and GLM incidence as well as severity for most of the genotypes. Soybean genotypes VI046160 and VI046167 could be used as parents in breeding for resistance to GLM pest. Areas with high rainfall and humidity would be recommended for soybean production to minimize infestation by GLM.Item Maize Combined Insect Resistance Genomic Regions and Their Co-localization With Cell Wall Constituents Revealed by Tissue-Specific QTL Meta-Analyses(Plant Science, 2018) Badji, Arfang; Otim, Michael; Machida, Lewis; Odong, Thomas; Bomet Kwemoi, Daniel; Okii, Dennis; Agbahoungba, Symphorien; Mwila, Natasha; Kumi, Frank; Ibanda, Angele; Mugo, Stephen; Kyamanywa, Samuel; Rubaihayo, PatrickCombinatorial insect attacks on maize leaves, stems, and kernels cause significant yield losses and mycotoxin contaminations. Several small effect quantitative trait loci (QTL) control maize resistance to stem borers and storage pests and are correlated withsecondary metabolites. However, efficient use of QTL in molecular breeding requires a synthesis of the available resistance information. In this study, separate meta-analyses of QTL of maize response to stem borers and storage pests feeding on leaves, stems, and kernels along with maize cell wall constituents discovered in these tissues generated 24 leaf (LIR), 42 stem (SIR), and 20 kernel (KIR) insect resistance meta-QTL (MQTL) of a diverse genetic and geographical background. Most of these MQTL involved resistance to several insect species, therefore, generating a significant interest for multiple-insect resistance breeding. Some of the LIR MQTL such as LIR4, 17, and 22 involve resistance to European corn borer, sugarcane borer, and southwestern corn borer.Item New sources of sorghum resistant genotypes to downy mildew disease in Uganda(BIODIVERSITAS, 2019) Kumi, Frank; Badji, Arfang; Mwila, Natasha; Odong, Thomas; Ochwo-Ssemakula, Mildred; Tusiime, Geoffrey; Gibson, Paul; Biruma, Moses; Prom, Louis K.; Cuevas, Hugo E.; Agbahoungba, Symphorien; Rubaihayo, PatrickKumi F, Badji A, Mwila N, Odong T, Ochwo-Ssemakula M, Tusiime G, Gibson P, Biruma M, Prom KL, Cuevas HE, Agbahoungba S, Rubaihayo P. 2019. New sources of sorghum resistant genotypes to downy mildew disease in Uganda. Biodiversitas 20: 3391-3397. Sorghum downy mildew (SDM) disease is still prevalent in Uganda at varying levels of incidence and severity. In this study, a total of 100 sorghum genotypes, five (5) from (U.SA, India, and Sudan) and 95 genotypes from Uganda were evaluated for resistance to downy mildew and other agronomic traits during the second growing season of 2016 (August-December). The experiment was conducted in two locations at Makerere University Agricultural Research Institute at Kabanyolo (MUARIK) and Abi-Zonal Agricultural Research and Development Institute (Abi-ZARDI) research station at Arua. The experimental design used was 10 x 10 alpha lattice design with three replicates. Data were collected on plant disease incidence (PDI), plant disease severity (PDS), area under disease progress curve (AUDPC), days to 50% flowering, plant height, 1000 seed weight, and grain yield. Results for analysis of variance showed highly significant differences (P < 0.001) in genotypes, location, and AUDPC, yield and yield components. Disease incidence varied significantly (P < 0.001) between locations, and Arua recorded highest disease incidence and severity of 80.6 and 2.8, respectively. Results from correlation analysis showed a highly significant (P < 0.001) positive association of downy mildew disease incidence with AUDPC (0.835) which suggests that the severity of SDM disease increased with disease incidence, whiles significant (P < 0.001) negative correlation was recorded for days to 50 % flowering (-0.302), 1000 seed weight (-0.471), and grain yield (-0.585), suggesting that grain yield and yield component decreased significantly with increase in SDM incidence and severity. Two resistant (PI 656061 and PI 533831) and four moderately resistant (E 40, MAKSO 8, PI 655990 and Epuripur) genotypes were identified from this study. These genotypes were recommended for sorghum breeding program against downy mildew disease.