Sequential path analysis of grain yield and its components in maize

The efficiency of a breeding programme depends mainly on the direction and magnitude of the association between yield and its components and also the relative importance of each factor involved in contributing to grain yield. The purpose of this research is to describe the application of causal path analysis to grain yield in maize (Zea mays L.) to lake into account the sequential development of yield components. Causal-admissible path analysis was performed assuming unidirectional causal relationships among yield components of eight maize populations Sequential path analysis of the five yield components studied revealed that cars per plant had the highest direct effect on grain yield. However, the indirect effects of component traits via number of grains per ear was maximum. It was concluded that the number of kernels per car, prolificacy, and grain size serve as potential characters in breeding for superior lines for grain yield in maize.