GROUPING AND SELECTION OF 32 SINGLE CROSS SUNFLOWER HYBRIDS USING PRINCIPAL COMPONENT ANALYSIS

Year 2018, Volume: 2 Issue: 1, 4 - 12, 31.08.2018

Zia Ullah

Abstract

Principal
components analysis is one of the multivariate statistical methods and was used
to access the genetic diversity of 32 sunflower hybrids developed at the
Department of Plant Breeding and Genetics, University of Agriculture,
Faisalabad during 2014-15. Eight males were crossed with 32 females to produce
32 F₁ hybrids using North Carolina Mating Design-I. Data were
recorded on plant height, head diameter, percent filled achenes, 100-achene
weight, achene yield per plant, harvest index, oil content, palmitic acid,
stearic acid, oleic acid and linoleic acid. The first four principle components
with Eigen value greater than one contributed 69.28 % of the total variability.
The first principal component showed higher values for 100-achene weight
(0.860), achene yield per plant (0.903), harvest index (0.777), second had
higher values for oleic acid (-0.780) and linoleic acid (0.834), third had
higher values for head diameter (-0.749) and percent filled achenes (0.782),
whereas the fourth was associated with plant height (0.741). Four distinct
groups can be differentiated on the basis of biplot diagram. H-1 and H-32 were
the best hybrids having higher achene (94.63g, 91.45g)  and oil yield (46.24%, 44.08%) respectively.

Keywords

Genetic diversity, hybrid, principal components analysis, sunflower

References

• Amna Ahmad [e-mail]>
• Rao Sohail Ahmad Khan [e-mail]
• Imtiaz [e-mail]