Indirect selection for increased oil yield in peanut: comparison selection indices and biplot analysis for simultaneous improvement multiple traits

Paper Details

Research Paper 01/08/2013
Views (463) Download (11)
current_issue_feature_image
publication_file

Indirect selection for increased oil yield in peanut: comparison selection indices and biplot analysis for simultaneous improvement multiple traits

Parviz Safari, Rahim Honarnejad, Masoud Esfahani
Int. J. Biosci.3( 8), 87-96, August 2013.
Certificate: IJB 2013 [Generate Certificate]

Abstract

The objectives of this study were to exploit information on the nature of relationships between agronomic traits and oil yield for developing selection indices as well as to compare selection indices methodology and biplot analysis as methods of simultaneous improvement of genotypes for multiple traits. Selection indices revealed that an increase in efficiency was observed over direct selection for oil yield when four oil yield contributing traits were included along with oil yield and showed that correlation coefficients between genotypic worth and each of the base indices were less than that for the optimum indices. Applying biplot analysis to the multiple trait data revealed that genotype by trait (GT) biplot graphically facilitated visual comparison of genotypes and selection. Moreover, the identified superior genotypes in both types of analyses were nearly identical. So use of biplot analysis is recommended.

VIEWS 14

Anonymous. 1981. Groundnut Descriptors. IBGR and ICRISAT. AGP:IBGR/80/66.

Baker RJ. 1986. Selection Indices in Plant Breeding. CRC Press. Boca Raton, FL, USA. 218 p.

Brim CA, Johnson HW, Cockerham CC. 1959. Multiple selection criteria in soybeans. Agronomy Journal 51, 42-46.

Dewey DR, Lu KH. 1959. A correlation and path coefficient analysis of components of crested wheat grass grain production. Agronomy Journal 51, 515-518.

Hazel LN. 1943. Genetic basis for constructing selection indices. Genetics 28, 476-490.

Hoque MS, Mia FU, Nessa D, Azimuddin M. 1993. Correlation and path analysis in groundnut. Bangladesh Journal of Agricultural Research 18, 131-136.

Iroume RN, Knauft DA. 1987. Selection indices for simultaneous  selection  for  pod  yield  and  leafspot resistance in peanut (Arachis hypojaea L.). Peanut Science 14, 51-54. http://dx.doi.org/10.3146/i0095-3679-14-1-13

Jannink JL, Orf JH, Jordan NR, Shaw RG. 2000. Index selection for weed suppressive ability in soybean. Crop Science 46, 1764-1771. http://dx.doi.org/10.2135/cropsci2000.4041087x

Kang  MS.  1994.  Applied  Quantitative  Genetics. Louisiana State University, Baton Rouge, LA, USA. 157 p.

Pesek J, Bakar RJ. 1969. Desired improvements in relation to selection indices. Canadian Journal of Plant Science 49, 803-804.

Rabiei B, Valizdah M, Ghareyazie B, Moghaddam M. 2004. Evaluation of selection indices for improving rice grain shape. Field Crops Research 89, 359-367. http://dx.doi.org/10.1016/j.fcr.2004.02.016

Rezaei A, Soltani A. 2003. An introduction to applied regression analysis. Isfahan University of Technology Press.

Siddiquey MN, Haque MM, Ara MJF, Ahmed MR, Roknuzzaman M. 2006. Correlation and path analysis of Groundnut (Arachis hypogaea L.). International Journal of Sustainable Agricultural Technology 2(7), 06-10.

Simmonds N, Smart J. 1999. Principles of crop improvement, 2nd ed. Blackwell Science Ltd. Press, Oxford, UK.

Smith HF. 1936. A discriminant function for plant selection. Annals of Eugenics 7, 240-250. http://dx.doi.org/10.1111/j.1469-1809.1936.tb02143.x

Suvantaradon K, Eberhart SA, Mock JJ, Owens JC, Guthrie WD. 1975. Index Selection for several yield traits in BSSS2 maize population. Crop Science 15, 827-833.

Vikram A, Roy D. 2003. Selection of characters for constructing selection index in groundnut (A. hypogea L.). Legume Research 26(2), 137-139.

Wells WC, Kofoid KD. 1986. Selection indices to improve an intermating population of spring wheat. Crop Science 26, 1104-1109. http://dx.doi.org/10.2135/cropsci1986.0011183X002 600060003x

Williams JS. 1962. The evaluation of a selection index. Biometrics 18, 375-393. http://dx.doi.org/10.2307/2527479

Wright S. 1921. Correlation and causation. Journal of Agricultural Research 20, 557-587.

Yan W. 2001. GGEbiplot: A windows application for graphical analysis of multienvironment trial data and other types of two-way data. Agronomy Journal 93, 1111-1118. http://dx.doi.org/10.2134/agronj2001.9351111x

Yan  W,  Fregeau-Reid  J.  2008.  Breeding  line selection based on multiple traits. Crop Science 48, 417-423. http://dx.doi.org/10.2135/cropsci2007.05.0254

Yan W, Kang MS. 2003. GGE Biplot Analysis. A Graphical Tool for Breeders, Geneticists and Agronomists. CRC Press.

Yan W, Rajcan I. 2002. Biplot evaluation of test sites and trait relations of soybean in Ontario. Crop Science 42, 11-20. http://dx.doi.org/10.2135/cropsci2002.0011

Yan W, Wallace DH. 1995. Breeding for negatively associated traits. Plant Breeding Reviews 13, 141-177. http://dx.doi.org/10.1002/9780470650059.ch4

Yan w, Hunt LA, Sheng Q, Szlavnics Z. 2000. Cultivar evaluation and mega environment investigation based on GGE biplot. Crop Science 40(3), 597-605. http://dx.doi.org/10.2135/cropsci2000.403597x