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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
Evaluating sugarcane families for yield potential and repeatability using random coefficient models
Crop Science, Volume 53, No. 6, Year 2013
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Description
Sugarcane (Saccharum species hybrid) is a clonally propagated crop but during variety development, the first stage of selection occurs among seedlings established from true seed. All subsequent stages are established from vegetative stem cuttings and evaluated as clones. During family selection, whole families of seedlings are selected or rejected based on the family mean performance. Individual seedling selection is restricted to selected families. Confounding due to "seed type" can occur when the relative performance of families or individual genotypes differ between the seedling and clonal stages. The objective of this study was to demonstrate the use of random coefficient models (RCMs) for estimating the potential of sugarcane families to produce elite progeny. Data were collected from 17 families evaluated as seedlings in 2002 and clones in 2003. The elite families selected using RCM analysis produced higher mean cane yield in both the seedling and clonal stages and a higher proportion of high yielding clones than those selected using analysis of covariance and analysis of variance. The slope was the most discriminating parameter for family repeatability and was associated with high within-family variability. © Crop Science Society of America.
Authors & Co-Authors
Zhou, Marvellous M.
United States, Baton Rouge
Lsu Agricultural Center
South Africa, Mount Edgecombe
South African Sugarcane Research Institute
Saudi Arabia, Bloemfontein
University of the Free State
Kimbeng, Collins A.
United States, Baton Rouge
Lsu Agricultural Center
Andru, S.
United States, Baton Rouge
Lsu Agricultural Center
Tew, Thomas L.
United States, Washington, D.c.
Usda Agricultural Research Service
Pontif, Michael J.
United States, Baton Rouge
Lsu Agricultural Center
Gravois, Kenneth A.
United States, Baton Rouge
Lsu Agricultural Center
Statistics
Citations: 6
Authors: 6
Affiliations: 4
Identifiers
Doi:
10.2135/cropsci2013.01.0052
ISSN:
0011183X
e-ISSN:
14350653