MORPHOLOGICAL AND AGRONOMIC CHARACTERIZATION OF SEVEN MAIZE RACES FROM THE HIGHLANDS OF MÉXICO

Abstract

Within the diversity of maize (Zea mays L.) in México, one of the most interesting genetic groups is the Mexican Pyramidal Complex grown in the Central highlands of the country. This study assessed the morphological and agronomic diversity in a large sample of populations of the seven races of maize most commonly cultivated in the highlands of Central México (Arrocillo Amarillo, Chalqueño, Cónico, Elotes Cónicos, Cacahuacintle, Palomero Toluqueño and Purépecha), and to register information of characteristics that describe the prevailing variation of the races under study. Field experiments were established during the 2010 Spring-Summer agricultural season with 119 representative accessions of the aforementioned races of maize, at Ciudad Serdán and San Mateo Capultitlán, Puebla, and at Montecillo, State of México, using an 11 × 11 simple lattice experimental design. Thirty-two quantitative traits were recorded and submitted to analysis of variance, and 13 of those traits were selected based on their repeatability and correlation coefficients, for applying multivariate analyses. Analysis of variance showed highly significant differences among genotypes for all the analyzed traits. The dispersion of accessions ended up as a continuum distributed throughout the Cartesian plane formed by the first two principal components, mainly influenced by traits related to ear and kernel size (ear length, kernel width and thickness, and the ratio kernel width/kernel length), as well as days to female flowering and number of leaves above the ear. The traits less affected by the environment were the most appropriate ones for grouping the accessions. Results of this study confirmed the grouping of the accessions of previously described races, as well as the interrelations among them as reported in previous studies; however, our result are more precise than the former studies in defining the groups and the interrelationships among the races because of the large sample sizes used.