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Morphological parameters, heritability, yield component correlation, and multivariate analysis to determine secondary characters in selecting hybrid maize
- Source :
- ISSN: 1412-033X
- Publication Year :
- 2023
-
Abstract
- Fadhli N, Farid M, Azrai M, Nur A, Efendi R, Priyanto SB, Nasruddin AD, Novianti F. 2023. Morphological parameters, heritability, yield component correlation, and multivariate analysis to determine secondary characters in selecting hybrid maize. Biodiversitas 24: 3750-3757. Direct selection for grain yield traits in maize (Zea mays L.) is often inefficient under specific conditions, necessitating the accurate determination of secondary traits to facilitate implementation and enhance selection precision. This study aimed to examine the morphological parameters, heritability, yield component correlations, and multivariate analysis of hybrid maize for determining potential secondary traits through indirect selection. The experimental design employed a randomized complete block design (RCBD) comprising 17 genotypes, including 15 hybrid maize lines and 2 hybrid maize varieties (RK 457 and RK 57). The results revealed that weight of harvested cob character and yield traits demonstrated significant correlations with production. Correlation values were further analyzed using biplot analysis and path analysis to identify potential secondary traits. The principal component biplot analysis results indicated four characters as effective secondary traits for selection, namely weight of harvested cob, yield, weight of 1000 seeds, and moisture content. MSM53/BCY as a parent of JHD 05 displayed superior performance compared to the two commercial hybrid varieties. Based on path analysis results, the weight of harvested cob character exhibited the highest direct effect on production with a value of 0.93, indicating that weight of harvested cob is the best secondary trait for selection.
Details
- Database :
- OAIster
- Journal :
- ISSN: 1412-033X
- Notes :
- application/pdf, Biodiversitas 24 (2023) 7, ISSN: 1412-033X, ISSN: 1412-033X, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1415728893
- Document Type :
- Electronic Resource