Department of Plant Sciences

Permanent URI for this collectionhttps://repository.chuka.ac.ke/handle/123456789/150

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Browsing Department of Plant Sciences by Subject "Path coefficient analysis"

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    Multivariate analysis techniques reveal significant morphogenetic variability in pumpkin landraces in Kenya
    (International journal of bioscience, 2018) Kiramana,James Kirimi, Isutsa,Dorcas Khasungu
    Documentedinformation on naturalizedpumpkin landraces inKenyatoidentifyusefulvariabilityis insufficient. The present study assessed variability using quantitative characters of 155 accessions, with 70 and 85 from Kakamega and Nyeri regions, respectively. The accessions were grown in one farm in a completely randomized design with three replications. Analysis of variance showed significant (P<0.05) variation in all characters. Lowest andhighest variablesinmeanandrangewereleaflength/width ratioandseednumber that were0.8 and 0.4, and 837 and 4,111, respectively. Eight factors accounted for 79.4% of total variation. The highly variable factors were fruit flesh thickness, length, width and length/width ratio, size, total weight, average weight and number, as well as seed number, 100-seeds weight, length, width, and thickness. Phenotypic coefficients of variation (PCV) were slightly higher or equal to genotypic ones (GCV). High GCV and PCV, heritability and genetic gain resulted for fruit size, total fruit weight, fruits and seeds. Over 70 positive correlations in fruit size, number and seeds with total fruit weight were observed in genotypic and phenotypic variabilities. Maximum positive direct effects on total fruit weight were observed in seeds, fruit average weight, length, and size, while indirect effects were observed in fruit number, flesh thickness, length, peduncle length and days to first flower. Multivariate analysis revealed fruit size, number, total weight, and seeds were characters of great genetic variability,whichshouldbeconsideredasprimarycomponentsforachievinghighyieldsinpumpkinswhen screeningaccessionsforselectionandimprovement