Relationship Between Yield and Yield Components of Maize Hybrids under Different Irrigation

Subject Areas : Journal of Crop Ecophysiology

جمیله  Seyedzavar ¹ (Former MSc Student in Agronomy and Plant Breeding, Faculty of Agriculture, University of urmia, Iran)
M.  Norouzi ² (Assistant Prof., Dept. of Plant Breeding & Biotechnology, Faculty of agriculture, University of Tabriz, Iran)
S.  Aharizad ³ (Associate Prof., Dept. of Plant Breeding & Biotechnology, Faculty of agriculture, University of Tabriz, Iran)
A.  Bandehhagh ⁴ (Associate Prof., Dept. of Plant Breeding & Biotechnology, Faculty of agriculture, University of Tabriz, Iran.)

Received: 2014-08-11 Accepted : 2015-02-28 Published : 2015-04-21

Keywords: Path analysis, stepwise regression, principal component analysis, Seed yield, Water deficit stress, Maize hybrid,

Abstract :

To evaluation the response of some maize hybrids to water deficit stress, a field experiment in 2010 was conducted using a split-plot plan on the basis of complete randomized block design with four replications at the Agricultural Research Station, University of Tabriz (Khalatpoushan). Main plots consisted of three different irrigation regimes (non-stress, mid-stress and sever-stress) and sub plots of 14 maize hybrids. Results showed significant differences among hybrids and irrigation regimes for all traits studied. Analysis of variance revealed significant differences among hybrids and also irrigation levels for all traits except ear diameter. The best model for stepwise regression based on all traits at the average of conditions, indicated that four responsible traits like number of rows per ear, 300-grain weight, number of grains per row and number of leaves per plant remained in model, which justified 83 percent of the total variations in yield performance. The path analysis showed that the number of rows per ear had the highest direct effect on yield. Based on principal component analysis the first component had a major factor on the weight of 300 seeds, plant height, ear length, flag leaf area, ear diameter and corn cob diameter and the second component had a big factor on plant dry weight, number of kernels per row, number of leaves per plant, number of rows per ear and grain yield. Principal component analysis (PCA), based on all of traits studied determined two principal components that could justify the 78 percent of vaiations. In this research the first component named as the growth-morphological factor and second component named as the yield factor.