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TRANSGRESSIVE SEGREGATION, HETEROSIS AND HERITABILITY FOR YIELD-RELATED TRAITS IN A SEGREGATING POPULATION OF PISUM SATIVUM L.

Published online by Cambridge University Press:  04 June 2018

M. FERNANDA GUINDON ,
EUGENIA MARTIN ,
VANINA CRAVERO  and
ENRIQUE COINTRY
M. FERNANDA GUINDON*
Affiliation:
IICAR-CONICET, Instituto de Investigaciones en Ciencias Agrarias de Rosario, Campo Experimental Villarino, Zavalla, Santa Fe, Argentina
EUGENIA MARTIN
Affiliation:
IICAR-CONICET, Instituto de Investigaciones en Ciencias Agrarias de Rosario, Campo Experimental Villarino, Zavalla, Santa Fe, Argentina
VANINA CRAVERO
Affiliation:
IICAR-CONICET, Instituto de Investigaciones en Ciencias Agrarias de Rosario, Campo Experimental Villarino, Zavalla, Santa Fe, Argentina
ENRIQUE COINTRY
Affiliation:
IICAR-CONICET, Instituto de Investigaciones en Ciencias Agrarias de Rosario, Campo Experimental Villarino, Zavalla, Santa Fe, Argentina
*
†Corresponding author. Email: [email protected]
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Summary

Pea is a self-pollinated, diploid (2n = 14), annual crop produced worldwide for human consumption and animal feed. The exploitation of maximum genetic potential from available pea resources implies the knowledge of genetic parameters of yield components. Hence, the present study was conducted in a cross between two pea varieties, namely DDR14 and Explorer, its F2 progeny and F3 families to find out transgressive segregants and to determine the magnitude of narrow sense heritability and heterosis. The high narrow sense heritability values obtained indicated that rapid gain could be achieved through selection for the different traits; however, the presence of genotype x environment interaction could limit the correspondence of these estimated values with the observed ones. The selection of lines through their phenotypic values is influenced by environmental and error effects. Best linear unbiased prediction (BLUP) was used for the prediction of genotypic values using morphological data from different years, allowing the correction for environmental effects. These estimates were used for genetic analysis of the traits. Heterosis was observed for number of pods (27.1%) and number of seeds (23.3%), characters that have a direct effect on yield. The cross also showed high frequency of transgressive segregation for these characters in F3 generation (15.5% and 13.6%, respectively). There were 12.73% families transgressive for two or more characters, with genotypic values of 49.82–64.41 for number of pods and 153.75–189.59 for seed number. The crossing between Explorer and DDR14 provided a base for the selection of superior progeny.

Type
Research Article
Information
Experimental Agriculture , Volume 55 , Issue 4 , August 2019 , pp. 610 - 620
Copyright
Copyright © Cambridge University Press 2018 

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References

REFERENCES

Alvarado, G., López, M., Vargas, M., Pacheco, A., Rodríguez, F., Burgueño, J. and Crossa, J. (2015). META-R (Multi Environment Trail Analysis with R for Windows). Version 6.01. hdl:11529/10201, CIMMYT Research Data & Software Repository Network, V20.Google Scholar
Balzarini, M. and Di Renzo, J. (2003). Info-Gen: Software Para Análisis Estadístico de Datos Genéticos. Argentina: Facultad de Ciencia Agropecuarias, Universidad Nacional de Córdoba.Google Scholar
Cahaner, A. and Hillel, J. (1980). Estimating heritability and genetic correlation between traits from generations F2 and F3 of self-fertilizing species: A comparison of three methods. Theoretical and Applied Genetics 58:33–38.Google Scholar
Chahota, R. K., Kishore, N., Dhiman, K. C., Sharma, T. R. and Sharma, S. K. (2007). Predicting transgressive segregants in early generation using single seed descent method-derived micromacrosperma genepool of lentil (Lens culinaris Medikus). Euphytica 156:305–310.Google Scholar
Espósito, M. A., Bermejo, C., Gatti, I., Guindón, M. F., Cravero, V. and Cointry, E. L. (2014). Prediction of heterotic crosses for yield in Pisum sativum L. Scientia Horticulturae 177:53–62.Google Scholar
Espósito, M. A., Martin, E. A., Cravero, V. P., Liberatti, D., López Anido, F. S. and Cointry, E. L. (2009). Relationships among agronomic traits and seed yield in pea. Journal of Basic and Applied Genetics 20:1–8.Google Scholar
Hoffman, A. and Merilä, J. (1999). Heritable variation and evolution under favourable and unfavourable conditions. Trends in Ecology and Evolution 14:96–101.Google Scholar
Jambormias, E., Sutjahjo, S. H., Mattjik, A. A., Wahyu, Y., Wirnas, D., Siregar, A., Patty, J. R., Laisina, J. K., Madubun, E. L. and Ririhena, R. E. (2015). Transgressive segregation analysis of multiple traits in mungbean (Vigna radiata L. Wilczek). SABRAO Journal of Breeding and Genetics 47:201–213.Google Scholar
Joshi, D. J., Ravindrababu, Y., Patel, A. M. and Chauhan, S. S. (2015). Heterosis studies for grain yield and it's contributing traits in fieldpea [Pisum sativum (L.) var arvense]. Asian Journal of Biosciencie 10:158–161.Google Scholar
Khan, R. A., Mahbub, M., Reza, A., Shirazy, J. and Mahmud, F. (2016). Selection of field pea (Pisum sativum L.) Genotypes through multivariate analysis. Scientia Agriculturae 16:98–103.Google Scholar
Kosev, V., Pachev, I., Angelova, S. and Mikic, A. (2012). Inheritance of quantitative traits in crosses between two Pisum sativum subspecies with particular reference to their breeding value. Russian Journal of Genetics 48:50–55.Google Scholar
Kumar, M., Jeberson, M. S., Singh, N. B. and Sharma, R. (2017). Genetic analysis of seed yield and its contributing traits and pattern of their inheritance in fieldpea (Pisum sativum L). International Journal of Current Microbiology and Applied Sciences 6:172–181.Google Scholar
Kumari, J., Dikshit, H. K., Singh, B. and Singh, D. (2015). Combining ability and character association of agronomic and biochemical traits in pea (Pisum sativum L.). Scientia Horticulturae 2:26–33.Google Scholar
Lorenzana, R. E. and Bernardo, R. (2009). Accuracy of genotypic value predictions for marker-based selection in biparental plant populations. Theoretical and Applied Genetics 120:151–161.Google Scholar
Mather, K. and Jinks, J. L. (1982). Biometrical Genetics: The Study of Continuous Variation. London: Chapman and Hall.Google Scholar
Pattee, H. E., Isleib, T. G., Giesbrecht, F. G. and Cui, Z. (2002). Prediction of parental genetic compatibility to enhance flavor attributes of peanuts. In Crop Biotechnology, 217–230 (Eds Rajasekaran, K., Jacks, T. J. and Finley, J. W.). ACS Symposium Series 829, Washington: American Chemical Society.Google Scholar
Piepho, H. P., Möhring, J., Melchinger, A. E. and Büchse, A. (2008). BLUP for phenotypic selection in plant breeding and variety testing. Euphytica 161:209–228.Google Scholar
Rashwan, A. M. A. and El-Shaieny, A. H. (2016). Pedigree selection in pea (Pisum sativum L.). International Journal of Advanced Research 4:1366–1371.Google Scholar
Rieseberg, L., Archer, M. and Waynw, R. (1999). Transgressive segregation, adaptation and speciation. Heredity 83:363–372Google Scholar
Sarawat, P., Stoddard, F. L. and Marshal, D. R. (1994). Derivation of superior F5 lines from heterotic hybrids in pea. Euphytica 73:265–272.Google Scholar
Shapiro, S.S. and Wilk, M.B. (1965). An analysis of variance test for normality (complete samples). Biometrika 52:591–611.Google Scholar
Shreya, S., Ainmisha, S. and Vashanti, R. P. (2017). Transgressive segregation study in F3 population of four groundnut crosses. International Journal of Current Microbiology and Applied Sciences 6:2054–2059.Google Scholar
Smýkal, P., Aubert, G., Burstin, J., Coyne, C. J., Ellis, N. T. H., Flavell, A. J., Ford, R., Hýbl, M., Macas, J., Neumann, P., McPhee, K. E., Redden, R. J., Rubiales, D., Weller, J. L. and Warkentin, T. D. (2012). Pea (Pisum sativum L.) in the genomic era. Agronomy 2:74–115.Google Scholar
Timmerman-Vaughan, G. M., Mills, A., Whitfield, C., Frew, T., Butler, R., Murray, S., Lakeman, M., McCallum, J., Russell, A. and Wilson, D. (2005). Linkage mapping of QTL for seed yield, yield components, and developmental traits in pea. Crop Science 45:1336–1344.Google Scholar
Yadav, B., Tyagi, C. S. and Singh, D. (1998). Genetics of transgressive segregation for yield and yield components in wheat. Annals of Applied Biology 133:227–235.Google Scholar