Molecular Marker‐Facilitated Investigations of Quantitative Trait Loci in Maize. II. Factors Influencing Yield and its Component Traits¹

<jats:p>Because traits such as grain yield are polygenically inherited and strongly influenced by environment, determination of genotypic values from phenotypic expression is not precise and improvement strategies are frequently based on low heritabilities. Increased knowledge of the genetic factors involved in the expression of yield should enhance the improvement of this trait. The objectives of this study were to identify and locate genetic factors (i.e., quantitative trait loci, QTL's) associated with grain yield and 24 yield‐related traits in two F<jats:sub>2</jats:sub> populations of maize (<jats:italic>Zea mays</jats:italic> L.) using isozyme marker loci. (The populations were generated by selfing the F<jats:sub>1</jats:sub>, hybrids CO159 ✕ Tx303 and T232 ✕ CM37.) In addition, assessments of the types and magnitudes of gene effects expressed by these QTL's were made. About two‐thirds of the associations among 17 to 20 marker loci and the 25 quantitative traits were significant with a large proportion of these at P < 0.001. Proportions of variation accounted for by genetic factors associated with individual marker loci varied from less than 1% to more than 11%. Although individual marker loci accounted for relatively small proportions of the phenotypic variation for these yield‐related traits, differences between mean phenotypic values of the two homozygous classes at certain loci were occasionally more than 16% of the population mean. Also, different genomic regions contributed to yield through different subsets of the yield‐related traits. Predominant types of gene action varied among loci and among the 25 quantitative traits. For plant grain yield, top ear grain weight, and ear length, the gene action was primarily dominant or overdominant. However, mainly additive gene action was implicated for ear number, kernel row number, and second ear grain weight. Results from these studies should prove to be useful for manipulating QTL's in marker‐facilitated selection programs.</jats:p>