Genetics underlying flaking grit yield from dry milled maize grain

A survey of U.S. corn germplasm was conducted to explore genetics underlying flaking grit yield (FGY) and evaluate the relationship between FGY and agronomic performance, with an aim to devise breeding strategies to simultaneously improve FGY and agronomic performance in the future. The survey used a broad-based set of inbreds that represent parentage of heterotic subgroups utilized in current commercial maize hybrids. The 12 inbreds were crossed in a diallel design without reciprocals to create 66 test hybrids which were evaluated for agronomic, dry milling, ear, and kernel properties over 3 years. The overall mean among test hybrids for FGY was 29.4 g grits/100g corn dry basis with a range from 24.0 to 36.0 g grits/100g corn dry basis. Narrow and broad sense heritability estimates for FGY were 0.53 and 0.65, respectively, indicating the importance of additive gene action for this trait. The general combining ability (GCA) variance for FGY was twice the size of the specific combining ability variance, indicating the importance of GCA. Heterosis is not a factor in expression of FGY. In most cases, FGY was not correlated with agronomic, ear, and kernel traits, but FGY was phenotypically correlated (p < 0.05) with both grain yield (r = -0.50) and test weight (r = 0.52). Grain yield and FGY were genetically correlated with an r = -0.43. A moderate amount (31%) of the variation in flaking grits per acre (FGA) was explained by multiple regression of several traits including grain yield as well as simple physical kernel characters: test weight, kernel depth, 100 kernel volume. Overall, the results of this study indicated presence of genetic variation for FGY in U.S. maize germplasm which could be exploited to develop new corn hybrids with improved FGY and FGA. Furthermore, performance for FGA may be predicted to some extent based on performance for some select agronomic and kernel characteristics. However, there is a need to explore additional options for improving predictions of FGA. Kernel characteristics such as kernel density and breakage susceptibility, implicated in previous reports to be highly correlated with FGY, may represent potential candidate traits for such a study