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Genetic and Genotype ✕ Environment Effects for Rough Rice and Head Rice Yields
Author(s) -
Gravois K. A.,
Moldenhauer K. A. K.,
Rohman P. C.
Publication year - 1991
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.2135/cropsci1991.0011183x003100040013x
Subject(s) - biology , oryza sativa , gene–environment interaction , agronomy , genotype , cultivar , population , genetic variation , oryza , loam , breeding program , microbiology and biotechnology , veterinary medicine , statistics , mathematics , soil water , ecology , demography , genetics , medicine , sociology , gene
High rough rice and head rice yields are important to U.S. rice ( Oryza sativa L.) producers for maintaining successful farming and milling operations. Unconfounded estimates of genetic and genotype ✕ environment (GE) variances for rough rice and head rice are lacking for U.S. rice breeding programs and would be useful aids to breeders in developing efficient programs. Our objectives were to estimate genetic and GE variance components for a rice population representative of a final testing stage in the Arkansas rice breeding program, to determine the relative importance of years, locations, and replicates in rice cultivar trials, and to demonstrate the usefulness of regression in genotypic stability analyses. Data were gathered on 19 genotypes at four locations in 1986, 1987, and 1988. Genotype ✕ year (GY) variance was the most important source of variation for head rice yield, whereas the genotype ✕ year ✕ location (GYL) variance was the most important source of variation for rough rice yield. The genotype ✕ location (GL) variance was the least important source of variation for both traits. An optimum experimental design in the Arkansas rice trials conducted on silt loam soils would include two locations replicated twice and repeated for a minimum of 3 yr. Regression techniques for estimating genotypic stability were most useful when regression was based on a year index, especially for head rice. The % Best statistic was significantly correlated with the mean and provided information on genotypes that consistently ranked in the top yield category [LSD (0.05)] across environments.