Genetic diversity of oily sunflower lines under normal and salt stress conditions using multivariate statistical analysis methods

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Ahmadpour Soheila; SOFALIAN OMID; DARVISHZADEH REZA

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Iranian Journal of Field Crop Science Year:2017 | Volume:48 | Issue:2 Page(s): 399-411

Download Full-Text

Persian Verion

View:

549

Download:

Cites:

Information Journal Paper

Title

Genetic diversity of oily sunflower lines under normal and salt stress conditions using multivariate statistical analysis methods

Author(s)

Ahmadpour Soheila | SOFALIAN OMID | DARVISHZADEH REZA | Issue Writer Certificate

Keywords

Cluster analysisQ2

genetic correlationQ1

heritabilityQ2

salt stressQ3

sunflowerQ2

Abstract

To study genetic diversity of some agronomic traits and the effect of salt stress on these characters, 100 oily sunflower inbred lines coming from different regions of world was investigated under normal and salt (8 dS/m) stress conditions with randomized complete block design with three replications outside the greenhouse in an open air area. Analysis of variance showed significant differences among lines for all studied traits, indicating the existence of genetic variation among genotypes. The highest coefficient of genetic variation was observed for head dried weight, seed yield per plant and the lowest one for days to flowering in both stressed and non-stressed conditions. The results of correlation analysis revealed significant and positive correlation between seed yield per plant with most of the studied traits in both stressed conditions. Stepwise regression analysis revealed that under salt stress conditions, 40. 3 percent of seed yield per plant variation was determined by head diameter, 100 seed weight, bottom leaf length, leaf number, bottom petiole length, upper leaf width and chlorophyll rate and in normal conditions, 30. 3 of seed yield per plant variation was explained by head diameter, 100 seed weight and plant height. Cluster analysis grouped lines into 6 clusters in normal and 5 clusters in salt stress conditions but the distribution of lines within groups were different depending to stress environments that present the genetic variability for salt tolerance in sunflower lines. Lines 6, 11, 13 and 70 had the highest yield per plant under normal and salt stress conditions.

Cites

No record.

References

No record.

Cite

APA: Copy

Ahmadpour, Soheila, SOFALIAN, OMID, & DARVISHZADEH, REZA. (2017). Genetic diversity of oily sunflower lines under normal and salt stress conditions using multivariate statistical analysis methods. IRANIAN JOURNAL OF FIELD CROP SCIENCE (IRANIAN JOURNAL OF AGRICULTURAL SCIENCES), 48(2 ), 399-411. SID. https://sid.ir/paper/153396/en

Vancouver: Copy

Ahmadpour Soheila, SOFALIAN OMID, DARVISHZADEH REZA. Genetic diversity of oily sunflower lines under normal and salt stress conditions using multivariate statistical analysis methods. IRANIAN JOURNAL OF FIELD CROP SCIENCE (IRANIAN JOURNAL OF AGRICULTURAL SCIENCES)[Internet]. 2017;48(2 ):399-411. Available from: https://sid.ir/paper/153396/en

IEEE: Copy

Soheila Ahmadpour, OMID SOFALIAN, and REZA DARVISHZADEH, “Genetic diversity of oily sunflower lines under normal and salt stress conditions using multivariate statistical analysis methods,” IRANIAN JOURNAL OF FIELD CROP SCIENCE (IRANIAN JOURNAL OF AGRICULTURAL SCIENCES), vol. 48, no. 2 , pp. 399–411, 2017, [Online]. Available: https://sid.ir/paper/153396/en

Related Journal Papers