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Genetic Correlations Among some Yield Components in Sugarcane in Kenya - Genetic and Phenotypic Relationships among some Yield Components of Sugarcane Clones Evaluated in Western Kenya

English, German · Paperback / Softback

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This study was conducted in three locations in western Kenya to determine phenotypic and genetic correlations among sugarcane yield and its components; estimate broad-sense heritabilities and expected genetic gain for sugarcane yield and quality traits among 13 promising sugarcane clones. Genotype × location (G×L) interactions were significant (p 0.01) for stalk length, stalk weight, sucrose content, fibre content, sugar yield, Brix yield and cane yield. Broad sense heritabilities (h2) were high for stalk diameter (0.928), number of millable cane (0.912), single stalk weight (0.907), number of internodes (0.907) and sucrose content (0.712) indicating that selection for these traits would be effective. Cane yield traits, except number of internodes, had low to moderate genetic correlations (rg = -0.299 to 0.586) with cane yield. Genetic correlation between refractometer Brix and sucrose content was high (rg = 0.998) was high. The study suggests that in the preliminary stages of selection, emphasis should be placed on multi-location testing of clones and selection of stalk weight, number of millable cane, Brix yield and sucrose content to improve cane and sugar yield.

About the author










Japheth Jamoza holds a PhD in Plant Breeding from Moi University, Kenya. Currently he is a Principal Research Scientist and Assistant Director at the Kenya Sugar Research Foundation where he has worked since 2001. His responsibility is to develop improved sugarcane production technologies. He has vast experience in sugarcane agriculture in Kenya.

Product details

Authors Japheth Jamoza
Publisher LAP Lambert Academic Publishing
 
Languages English, German
Product format Paperback / Softback
Released 17.10.2012
 
EAN 9783844390162
ISBN 978-3-8443-9016-2
No. of pages 128
Subject Natural sciences, medicine, IT, technology > Biology > Genetics, genetic engineering

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