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Correlation and Path Coefficient Analysis for Morphological and Biochemical Parameters in Sunflower (Helianthus Annuus L.).
- Source :
-
Helia . Jul2019, Vol. 42 Issue 70, p61-72. 12p. - Publication Year :
- 2019
-
Abstract
- The aim of this study was to evaluate the best performing lines in sunflower on the basis of phenotypic and genotypic correlation so that we can find out the which trait directly or indirectly effect the yield and quality of the sunflower because being an breeder our main aim is yield and quality and the lines which are performing best can be further used in the breeding programs. Sunflower is a valuable oil producing crop because it contains good quality oil composition and can be grown twice in a year. There is scarcity of oil in our country so that there is requisite to heighten the yield of sunflower in order to exploit its share in oilseed sector. The study was conducted at the research field of Rajawala farm, University of Agriculture, Faisalabad during year 2015–16 to study the correlation among yield related traits, oil and protein content in Sunflower (Helianthus annuus L.). 20 sunflower lines were sown in randomized complete block design with three replications. Data was assessed at maturity for plant height, leaves per plant, leaf area, head diameter, internode length, 100-achene weight, achene yield per plant, oil contents and protein contents. Genotypic and phenotypic correlation was estimated among these traits. The recorded data was subjected to statistical analysis of variance, correlation and path coefficient analysis. The line G-16 showed best performance for leaf area, head diameter and achene yield per plant. Line G-20 was good in 100 achene weight. The above mentioned lines could be used in future breeding programs for effective improvement in yield of sunflower. This data was helpful to select superior lines and these lines may also be used in further hybridization program to get better yield, oil and protein contents. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10181806
- Volume :
- 42
- Issue :
- 70
- Database :
- Academic Search Index
- Journal :
- Helia
- Publication Type :
- Academic Journal
- Accession number :
- 137377872
- Full Text :
- https://doi.org/10.1515/helia-2018-0011