Evaluation of Elite Open-Pollinated Maize Lines in Two Contrasting Environments

Abstract

Selection environment affects plant behavior and response to selection. The objective of the present study was the evaluation of 17 quality and quantity phenotypic characteristics of six open-pollinated maize lines of fifth cycle of selection (C4), which was performed by the implementation of honeycomb breeding, in two contrasting environments (A and B) The soil chemical analysis revealed that the two environments were very diverse (A: SL, pH = 6.25, organic matter: 1.29%, B: SCL, pH = 8, organic matter: 2.4%). Our data suggest that moisture content, seed oil content, ear length, ear diameter, number of grain rows, spindle diameter and seed thickness exhibit inter-location high broad-sense heritability (over 0.9). Heritability estimations were highly depended on the environment, since GEI interaction was high indicating environmental interaction with genotype, especially environment B, which seems to favor heritability. Location affects strongly variation and genotype by environment interaction is significant in many cases. Seed width was the only characteristic to be depended on genetic variability. Descriptive statistics revealed a broad range of mean fluctuations, indicating satisfactory variability in many characteristics to be exploited by breeders. Some characteristics showed low CV (Coefficient of Variation) values (1.6 to 5.3), indicating stability of performance and low environmental effects. Significant correlations between the 17 quantity and quality traits found in our study may be a useful tool for indirect selection of certain characteristics, otherwise difficult to be selected due to non-additive effects. Cluster analysis and PCA showed contrasting results in classification of open-pollinated lines and this was attributed to strong environmental effects that distorted phenotypic expression of the characteristics studied.

Stability, the Last Frontier: Forage Yield Dynamics of Peas under Two Cultivation Systems

“…To provide a certain classification for the studied pea genotypes and cultivation systems, a heat map ( Figure 8 ) was carried out. Cluster analysis was previously used for classification purposes for various genetic materials (e.g., maize, sweet cherry), sometimes in combination with principal components analysis [ 54 , 55 , 56 ]. The available data were divided into groups of increasing dissimilarity.…”

Principal Component Analysis for Identification of Superior Castor Bean Hybrids

“…For instance, Oliveira, Gravina, and Oliveira (2018) applied multivariate analysis techniques (PCA and UPGMA) as a tool for selecting bean genotypes with desirable agronomic traits. PCA has also been applied to studies involving phenotypic divergence in corn genotypes (Greveniotis, Bouloumpasi, Tsakiris, Sioki, & Ipsilandis, 2018), to identify superior accessions of rice when subjected to below-optimum temperatures during the initial development phase (Moura et al, 2018), and to identify and group different soybean cultivars (Panero et al, 2018).…”