Path analysis and canonical variables of intervarietal maize hybrids

Abstract

Maize (Zea mays L.) is the cereal most produced in the world, due to its wide scope and utilization in human and animal diet. This study aims to evaluate the agronomic performance of intervarietal maize hybrids, as well as the linear associations, interrelations of cause and effect, and the genotypes dispersion through canonical variates. The experiment was conducted in the agricultural year of 2014/2015. The crosses that originated the hybrids were carried out on the growing season of 2013/2014 and hybrids evaluated on 2014/2015. The hybrids were arranged in randomized blocks, being 13 treatments with five repetitions. The measured characters were: plant height, spike insertion height, stem diameter, spike diameter, spike length, spike mass, number of rows of grains per spike, number of grains per row, cob diameter, cob mass, spike grains mass, mass of a thousand grains, grain length and grain yield. The data were submitted to analysis of variance and mean values compared by the Tukey test at 5% of probability. The Pearson’s linear correlation analysis and path analysis were performed using grain yield as a dependent character. Furthermore, the analysis of canonical variables was carried out. The hybrid H5: G3 X G4 revealed higher grain yield, spike grains mass, number of grains per row and spike diameter. Grain yield of intervarietal hybrids presented positive correlations with the traits such as stem diameter, spike diameter, spike length, number of grains per row, mass of a thousand grains, grain length and spike grains mass. Spike diameter and spike length presented higher direct effects on grain yield of intervarietal hybrids. The canonical variates revealed the formation of five phenotypically distinct groups of intervarietal hybrids.

Prediction of Corn Grain Productivity as a Function of Altitude and Plant Population

“…With the data exposed (Figure 2), it is evident that there were periods with lower rainfall, October and March, but in the other periods, the rainfall and temperatures were consistent for the corn crop. Pearson correlation analysis has been used in studies with corn (Carvalho et al, 2021;Barbosa et al, 2019) to show linear relationships between agronomic and meteorological characteristics. According to the Pearson correlation (Figure 3), in the association of 16 variables, it was possible to verify that for higher grain yields, there is a strong correlation (0.61) of altitude (AL) with grain yield (GY); similarly, the population (PO) obtained a medium magnitude correlation (0.43) with grain yield (GY).…”

Genetic Variability, Correlation and Path Coefficient Analysis in Hybrid Maize (Zea mays L.)

“…It is, therefore, of fundamental importance to identify the agronomic and nutritional traits of maize genotypes" [4]. "It is also the cereal that is most produced in the world, due to its wide scope and utilization in human and animal diet" [5].…”