Multivariate Analysis of Maize Inbred Lines under Normal and Stressed Watering Regimes

Mohamed, A. M. El.; Darwish, D. S.; El-Karamity, A. El.; Al-Ashmoony, M. S.; Tantawy, A. A.

doi:10.21608/jpp.2020.95637

Multivariate Analysis of Maize Inbred Lines under Normal and Stressed Watering Regimes

Document Type : Original Article

Authors

¹ Agronomy Department, Faculty of Agriculture, Minia University, El-Minia

² Agronomy Department, Faculty of Agriculture, Cairo University, Giza 12613, Egypt.

³ Agronomy Department, Faculty of Agriculture, Minia University, El-Minia, 61517, Egypt.

10.21608/jpp.2020.95637

Abstract

Fifty S₃ lines along to ten S₁₀ of ARC maize inbreds were evaluated under normal and stressed watering regimes to explore their potentiality by using cluster and principal components analyses. Cluster analysis grouped the inbred lines under each of both conditions into three groups as lower (LP), medium (MP) and higher (HP) performed groups. The grouping of the investigated inbreds using their performance under normal regimes is conducted on flowering dates and grain yield attributes. However, the screening process of inbreds grown under stressed watering regime by cluster analysis greatly considered the level of tolerance/susceptibility in addition to flowering and grain yield. The extent of variation proved that there opportunities to upgrade the ASI, proline content, drought susceptibility and tolerance of higher performed inbreds. The most of tested lines are common between LP, MP and HP groups under both regimes which pointed out that effective selection could be expected either practiced under normal or stressed environments. Principal components analysis proved that drought stress tolerance index playing a great role with yield and yield components under either normal or stress conditions which considers it as the main factor contributing the higher value from total variations. The interrelationships among the traits within clustered groups are variable with common significantly positive correlation between grain yield and drought tolerance. Cluster analysis seems to be effective for classifying the maize inbred lines during the early generation of development. However, the per se distinct lines need to be reliable as components maize hybrid via testing GCA.

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