Browsing by Author "Kiarie, N."

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    Additive main effects and multiplicative interaction analysis of genotype x environmental interaction among sweetpotato genotypes
    (2009-04-08) Mwololo, J.K.; Muturi, Phyllis W.; Mburu, M.K.; Njeru, R.W.; Kiarie, N.; Munyua, J.K.; Ateka, E.M.; Muinga, R.W.; Kapinga, R.E.; Lemaga, B.
    Sweetpotato is an important food, feed and cash crop in Eastern Africa. Highly stable and adaptable genotypes are important in sweetpotato productivity and evaluation across sites would form a basis for breeding varieties that are stable. Seventeen sweetpotato genotypes were evaluated for two seasons in three sites which have differentials in sweetpotato virus disease prevalence and climatic conditions in the coastal region of Kenya to determine their stability and adaptability in the region. The experimental design was randomized complete block design. Harvesting was done at four and half months after planting and tuber yield was determined. Data was analysed using the additive main effects and multiplicative interaction model (AMMI) to establish the genotype x environmental interactions (GEI). There was wide variation across the environments in the two seasons. Stability and adaptability was identified among sweetpotato genotypes. Varities Jonathan, Exshimba, SPK 004 and Kemb 10 were highly adapted across all the environments whereas Ejumula, Jewel, Jubilee, Bungoma, and sponge were stable. The highly adapted genotypes can be used as a basis for further improvement through breeding by crossing with the stable genotypes.
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    A perspective on proteomics: current applications, challenges and potential uses
    (Academic Journals, 2010-08) Muturi, Phyllis W.; Mwololo, J.K.; Munyiri, S.W.; Rubaihayo, P.; Munyua., J.K.; Mgonja, M.; Manyasa, E.; Kiarie, N.
    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 approaches for protein function prediction integrate multiple genomics and proteomics data sources to make inferences about the function of unknown proteins. Research into gene expression and proteomics enable scientists to decipher the functions of genes and their protein products, and to get a clearer picture of the complex regulatory networks that control fundamental biological processes. The global study of cellular proteins by proteomics may be able to provide the complete picture. Use of proteins to study gene function and genetic information is possibly the most reliable method but costly and labour intensive. Analysis of gene-expression patterns is no less powerful concept than proteomics when it comes to identification of the characteristics of signalling pathways or disease states. This review discusses current applications of proteomics, challenges and potential uses.