Principal component (PCA) and cluster analyses for plant nutrient traits in baby corn (Zea mays L.)
2019
Magudeeswari, P. | Sastry, E.V Divakara | Devi, Th Renuka
The present study was conducted to evaluate the plant nutrient traits in 12 baby corn genotypes by using Principal component analysis and cluster analysis during rabi 2017. Analysis of variance depicted the genotypes differed significantly among themselves for all the traits except sugar content. Variability studies revealed that PCV was observed maximum for all the traits. Maximum GCV and PCV were recorded for yield without husk followed by iron content and sugar content. Medium heritability was observed for all the traits except sugar content. Calcium content and iron content was recorded for highest genetic advance. Principal component analysis revealed that the first three principal components together accounted for 87.49% of variability. The principal components (PC1, PC2) were highly positively influenced by sugar and iron contents, respectively. PC3 was negatively influenced by yield without husk. The 12 genotypes were grouped into three distinct clusters. The cluster-I were the largest cluster comprising of five genotypes and followed by Cluster-II (4 genotypes) and cluster-III (3 genotypes). The genotypes in cluster-I has higher iron content and yield without husk, while the genotypes in cluster-II having higher potassium, phosphorous and calcium contents. The genotypes in cluster-III exhibiting higher means for sugar and phosphorous contents.
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