Exploration of Phenotypic Dissimilarity for Drought Tolerance in Maize Inbred Line Collection

Abstract

Cluster analysis is a type of exploratory analysis that is used for classifying unknown individuals into groups of members that share certain similarity. Grouping breeding materials into different clusters based on their performances under a given condition allows plant breeders to select breeding lines more efficiently. This study aimed to group breeding materials based on their performance under water stress conditions using cluster analysis. The experiment was conducted in RCB design with 3 blocks. Fifty maize inbred lines were grown and exposed to water stress conditions. Twenty-four phenotypic traits were collected and some of them were subjected to cluster analysis. The Partitioning Around Medoid algorithm was used to cluster 50 inbred lines from chosen phenotypes. Cluster validation was then carried out in a subsequent experiment by testing the statistically significant differences between chosen inbred lines and tolerant and susceptible clusters. According to the analysis, 4 clusters with different numbers of inbred lines were obtained. Lines in cluster no. 3 showed the most tolerance compared with the other clusters. In contrast, individuals in cluster no. 1 were the most susceptible. The results of cluster validation in another year also supported this cluster result. Therefore, we concluded that the clustering method was an efficient way to differentiate tolerant and susceptible inbred lines. Furthermore, the results suggested that plant height, tassel size, spikelet density, days to silking, and anthesis-silking interval were secondary traits that could be used in selection for drought tolerance in maize.

RETRACTED: Variability among maize (Zea mays L.) inbred lines for agro- morphological traits

“…Four clusters of maize inbred lines were made in our study based on agro-morphological traits (Table 8,Fig 2), demonstrating that the evaluated inbred lines had enough genetic diversity. These results are similar to those reported by Anusha et al (2022), Matin et al (2017), Mounika et al (2018), andHannok et al (2023). Clusters 2 and 4 had the highest intra-cluster distance, showing genetic dissimilarity between the inbred lines in those clusters (Table 9).…”

Variability in drought stress response in a panel of 100 faba bean genotypes

“…Cluster analysis is a multivariate analysis that categorizes the genotypes into several subgroups according to their similarities, based on the capability and performance of the traits examined. This approach has been used to predict the best-performing genotypes under drought stress in other crops ( Hannok et al., 2021 ; Mutlu et al., 2022 ; Aslam et al., 2023 ). Grouping breeding materials using multivariate data under a given condition allows plant breeders to select breeding lines more efficiently.…”