Zobrazeno 1 - 6
of 6
pro vyhledávání: '"E. O. Manyasa"'
Autor:
I Gatongi, N Lagat, B.K. Towett, L. Jeptanui, O Kiplagat, N Njogu, E O Manyasa, H. Ojulong, P Kimurto, M. Siambi
Publikováno v:
Journal of Experimental Agriculture International. 21:1-18
Thirty six pearl millet genotypes were evaluated in randomized complete block design with two replications during 2011/2012 at two locations to study the magnitude of genotype by environment interaction for yield and yield related traits and identify
Autor:
M. Thimma Reddy, Murali Krishna Gumma, Hari D. Upadhyaya, E O Manyasa, Mani Vetriventhan, Shailender Singh, M. Irshad Ahmed, K Narsimha Reddy
Publikováno v:
Australian Journal of Crop Science. 11:424-437
The aim of the investigation was to assess the geographical distribution, diversity and gaps in sorghum collection from East African countries conserved at the ICRISAT genebank. The collection represents a total of 12,750 accessions including 11,672
Autor:
B.K. Towett, E O Manyasa, H. Ojulong, L. Jeptanui, Paul Kimurto, M. Siambi, C. O. Oduori, C. M. Wekesa
Publikováno v:
Journal of Life Sciences. 13
Publikováno v:
Acta Horticulturae. :169-174
A total of 123 Pigeonpea landraces were collected from four major pigeonpea production areas in Tanzania. The accessions grown at Ilonga (Tanzania) and Kabete and Kampi ya Mawe (Kenya) were characterized for diversity using 16 qualitative and 14 quan
Publikováno v:
Genetic Resources and Crop Evolution. 55:379-387
A total of 123 pigeonpea landraces collected from farmers' fields in four pigeonpea growing regions of Tanzania were characterized and evaluated for 16 qualitative and 14 quantitative descriptors, and their response across three pigeonpea growing env
Autor:
J. K. Munyua, M. Mgonja, Patrick Rubaihayo, P. W. Muturi, N. Kiarie, E O Manyasa, J. K. Mwololo, S. W. Munyiri
Publikováno v:
Agriculture and Biology Journal of North America. 1:916-918
Biological sciences are experiencing an ongoing information revolution. Proteome-wide functional classification using bioinformatics approaches is becoming an important method for revealing unknown protein functions. Most successful computational app