Emmanuel Mbeyagala

Dr. Emmanuel Mbeyagala

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Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 July 2023 in Critical Reviews in Plant Sciences
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Journal Article
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Abhay Kumar PandeyAbhay Kumar Pandey
Abhay Kumar Pandey
AKAbhishek Kumar
Abhishek Kumar
EMEmmanuel Mbeyagala
Emmanuel Mbeyagala
MBMartin BARBETTI
Martin BARBETTI
ABAshwani Basandrai
Ashwani Basandrai
JLJay Ram Lamichhane
Jay Ram Lamichhane

7 June 2021 in Agriculture
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Journal Article
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FMFrank Mmbando
Frank Mmbando
EMEmmanuel Mbeyagala
Emmanuel Mbeyagala
PBPapias Binagwa
Papias Binagwa
RKRael Karimi
Rael Karimi
HOHellen Opie
Hellen Opie
RNRamakrishnan Madhavan Nair
Ramakrishnan Madhavan Nair
This study analyzes the factors that influence the probability and extent of the adoption of mungbean production technologies in Tanzania, Kenya and Uganda, using multivariate probit and Poisson regression models. The results show that the probability and extent of the adoption of mungbean production technologies are influenced by gender of the household, household size, farm size, livestock size, household assets, access to extension services and access to credit. The study suggests that policy interventions that aimed at targeting women farmers, increasing household asset and information dissemination, such as field demonstrations and training programs, are crucial in enhancing technology adoption among smallholder farmers.

1 January 2021 in Cogent Food & Agriculture
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Journal Article
Open access
EMEmmanuel Mbeyagala
Emmanuel Mbeyagala
JAJ. B. Ariko
J. B. Ariko
AAA. O. Atimango
A. O. Atimango
EAE. S Amuge
E. S Amuge
Cowpea (Vigna unguiculata) is one of the important legume crops in Uganda especially in the eastern and northern regions. Its productivity in the country is, however, still low. Environmental constraints and occurrence of genotype × environment interactions (G × E) contribute greatly to the low production. In this study, an additive main effects and multiplicative interaction analysis (AMMI) model was used to assess the yield stability of 30 cowpea genotypes planted in five locations for three consecutive seasons. Also, the relationship of G × E interaction with genotypic/weather variables was analysed. AMMI analysis of variance indicated that environment had the highest contribution to the variation in grain yield. Postdictive success method indicated AMM1-3 as the best model since the first three interaction principal component axes (PCA1, PCA2, PCA3) were significant (p = 0.0000). Together, the first three PCAs explained 75.1% of the G × E interaction sum of squares. However, according to the predictive success method, AMMI-1 was the best model. The AMMI stability value (ASV) identified five genotypes; UCR 5279, Ayiyi, IT07K-257-33, ACC122*WC66 and IT06K-281-1 as being more stable. These are recommended for release as varieties after confirmation of their preference by farmers. Results in this study also showed that G × E interaction was associated with the interaction of temperature, rainfall, relative humidity, days to maturity, number of seeds per pod, number of pods per plant and yield per plant.

16 May 2019 in Microbiology Resource Announcements
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EMEmmanuel Mbeyagala
Emmanuel Mbeyagala
SMS. Maina
S. Maina
MMM. W. Macharia
M. W. Macharia
SMS. B. Mukasa
S. B. Mukasa
THT. Holton
T. Holton
Here, we present the first near-complete genome of Ugandan Passiflora virus (UPV) sequenced from a symptomatic sample of KH7 passion fruit ( Passiflora edulis Sims) variety. UPV had limited amino acid identity with other potyviruses known to cause passion fruit woodiness disease (PWD).

2 June 2017 in African Crop Science Journal
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Journal Article
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EMEmmanuel Mbeyagala
Emmanuel Mbeyagala
NKN. Kwikiriza
N. Kwikiriza
RAR. Amayo
R. Amayo
JOJ.R. Omadi
J.R. Omadi
DOD. Okwang
D. Okwang
JOJ.E.P. Obuo
J.E.P. Obuo
Production and utilisation of mungbean (Vigna radiata) in Uganda is constrained by unavailability of improved and farmer-preferred varieties. The objective of this study was to document and assess farmers’ preference for mungbean using eleven introduced genotypes. We captured twenty five traits during farmer interviews out of which six traits were identified (through group discussions) as the most often used by farmers when selecting the best mungbean genotypes. The traits were; yield, overall performance, seed size, seed colour, marketability and early maturity. Nine out of eleven introduced genotypes were selected during on-farm trials using the six traits. The selected genotypes were; Filsan, Mauritius, Sunshine, VC6137B14, VC61485012, VC6153B20, KPS1, VC6173B10 and VC63724560. The selected genotypes were early maturing (60-70 days), with large green or greenish yellow seeds. However, two late maturing (80-90 days) and small seeded genotypes; Blackgram and Yellowgram were rejected by farmers despite yielding higher (1459 and 1035 kg ha-1, respectively) than other genotypes. This study showed that farmers use a combination of traits when choosing a mungbean genotype for adoption and these should be considered in mungbean improvement. Chi square tests of independence showed that there were no significant differences in genotype choices based on gender (χ2 = 2.5419, P-value = 0.97). However, there were significant genotype preference differences between eastern and northern regions (χ2 = 22.34, P< 0.01). It is possible to develop new genotypes that are acceptable to both men and women since they have no specific trait preferences. Key Words: Gender, preferences, Vigna radiata

25 October 2023 in International Journal of Agronomy
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Journal Article
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EMEmmanuel Mbeyagala
Emmanuel Mbeyagala
RKRael. Karimi
Rael. Karimi
PBPapias Binagwa
Papias Binagwa
EAEsther S. Amuge
Esther S. Amuge
AVAnil Kumar. Vemula
Anil Kumar. Vemula
RNRamakrishnan M. Nair
Ramakrishnan M. Nair
Mungbean [Vigna radiata (L.) R. Wilczek var. radiata] also referred to as green gram is a key crop especially in the marginal areas of East Africa. It is rich in micronutrients and protein and thus can help ameliorate malnutrition if incorporated into diets. This study was conducted to evaluate the performance of 26 fixed elite mungbean breeding genotypes for yield and micronutrient composition across different locations in East Africa (Uganda, Kenya, and Tanzania). The genotypes displayed significant variability for nutritional, phenology, and yield-related traits across test environments. Significant genotype effects were observed for most of the traits except for average yield per plant and dry matter content ( < 0.05). Random effect of environment was significant for all traits, and significant GXE was observed for all traits except for dry matter and iron content ( < 0.05). Moderate to high broad-sense heritability (H2) was found among traits except for dry matter content which was low (H2 = 10.4%). There was a significant and positive correlation between Fe and Zn (r = 0.58), and Fe and Ca (r = 0.46), indicating the potential to enhance these traits simultaneously through breeding and/or selection. However, the correlation between yield and nutrients (iron, zinc, and calcium) was negative. Environments KAT_SR_2019, KYM_LR_2020, and KYM_LR_2020 were found to be discriminating (informative) and representative of grain yield, calcium, and zinc content, respectively. Genotypes AVMU 1679, AVMU 1685, and AVMU1686 combined both stability and high micronutrient content, while the high yielding and stable genotypes were AVMU 1689, AVMU 1681, and AVMU 16102. The identified genotypes need to be assessed for farmer preference in on-farm trials before they can be recommended for release as new varieties. Additionally, these genotypes will be useful in future breeding efforts as donors aimed at developing nutrient-dense and high yielding mungbean varieties.