Estimating Breeding Value of Agronomic Traits in Oriental Tobacco Genotypes under Broomrape Stress and Normal Conditions

Tahmasbali, Maryam; Darvishzadeh, Reza; Fayaz Moghaddam, Amir

doi:10.52547/pgr.7.1.7

[Home ] [Archive]

[ فارسی ]

Main Menu

Home

Journal Information

Articles archive

For Authors

For Reviewers

Registration

Contact us

Site Facilities

Search in website

Receive site information

Volume 7, Issue 1 (2020)

pgr 2020, 7(1): 103-126

Back to browse issues page

Estimating Breeding Value of Agronomic Traits in Oriental Tobacco Genotypes under Broomrape Stress and Normal Conditions

Maryam Tahmasbali

, Reza Darvishzadeh ^*

, Amir Fayaz Moghaddam

Department of Plant Production and Genetics, Faculty of Agriculture and Natural Resources, Urmia University, Urmia, Iran , r.darvishzadeh@urmia.ac.ir

Abstract: (9040 Views)

In a breeding program, it is important to find out information about the genes action, because knowledge in this field could help the researchers in their crossing programs and realizing effective selection. In this study, breeding values of different agronomic traits in oriental tobacco were predicted using the best linear unbiased prediction (BLUP) procedure. For this purpose, 89 tobacco genotypes were evaluated in a randomized complete block design with three replications under normal (without broomrape) and stress (with broomrape) conditions at Urmia Tobacco Research Centre, during two successive years. Broomrape stress was applied by mixing 0.06 gr broomrape seed with soil in pots. C.H.T.209.12e × F.K.40-1 genotype had high yield under both normal and broomrape stress conditions and was one of the desirable genotypes in terms of yield tolerance and stability index. The Rustica genotype was the best genotype in terms of the breeding value of most of studied traits in both normal and broomrape stress conditions. The result from cluster analysis based on the breeding values of the studied traits showed that, tobacco genotypes were divided into 6 and 5 groups in normal and broomrape stress conditions, respectively; but the distribution of genotypes within the groups was different depending on the conditions. The highest heritability was observed for root fresh weight under normal condition and for leaf fresh weight under broomrape stress conditionss. The results showed that a genotype with good phenotypic performance may have low breeding value. Therefore, considering breeding value information along with phenotypic mean of traits can increase the efficiency of breeding programs.

Keywords: Breeding value, Broomrape, Heritability, Obligate parasite, Source of resistance, Tobacco

Full-Text [PDF 1211 kb] (1658 Downloads)

Type of Study: Research | Subject: Plant improvement

References

1. Abdulahi, A. and Mohammadi, R. (2008). Evaluating the Response of Bread Wheat Genotypes to Weed Interference under Dryland Conditions. Journal of Crop Production and Processing, 11(42): 93-102 (In Persian).

2. Akram-Ghaderi, F. and Soltani, A. (2012). Leaf area relationships to plant vegetative characteristics in cotton (Gossypium hirsutum L.) grown in a temperate sub-humid environment. International Journal of Plant Production, 1(1): 63-71.

3. Arslan, B. and Okunus, A. (2006). Genetic and geographic polymorphism of cultivated tobaccos (Nicotiana tabacum) in Turkey. Russian Journal of Genetics, 42: 667-671.

4. Bartlett, M.S. (1937). Properties of sufficiency and statistical tests. Proceedings of the Royal Statistical Society (Series A), 160: 268-282.

5. Bauer, A.M., Reetz, T.C. and Léon, J. (2006). Estimation of breeding values of inbred lines using best linear unbiased prediction (blup) and genetic similarities. Crop Science, 46(6): 2685-2691.

6. Bernardo, R. (1994). Prediction of maize single-cross performance using rflps and information from related hybrids. Crop Science, 34(1): 20-25.

7. Bernardo, R. (2010). Breeding for Quantitative Traits in Plants. Stemma Press, Woodbury, New York, USA.

8. Bindler, G., Plieske, J., Bakaher, N., Gunduz, I., Ivanov, N., Van der Hoeven, R., Ganal, M. and Donini, P. (2011). A high-density genetic map of tobacco (Nicotiana tabacum L.) obtained from large scale microsatellite marker development. Theoretical and Applied Genetics, 123: 219-230.

9. Bindler, G., Van der Hoeven, R., Gunduz, I., Plieske, J., Ganal, M., Rossi, L., Gadani, F. and Donini, P. (2007). A microsatellite marker-based linkage map of tobacco. Theoretical and Applied Genetics, 114: 341-349.

10. Bouslama, M. and Schapaugh, W. (1984). Stress tolerance in soybeans. I. Evaluation of three screening techniques for heat and drought tolerance 1. Crop Science, 24(5): 933-937.

11. Blum, A. (2011). Plant Breeding for Water-Limited Environments. Springer. New York, USA. [DOI:10.1007/978-1-4419-7491-4]

12. Bradbury, P.J., Zhang, Z., Kroon, D.E., Casstevens, T.M., Ramdoss, Y. and Buckler, E.S. (2007). TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics, 23: 2633-2635.

13. Butorac, A., Tursic, I., Mesic, M. Butorac, J., Basic, F., Vuletic, N., Kisic, I., Berdin, M. and Djakovic, Z. (2004). The effect of tobacco monoculture and crop rotation on tobacco leaf compositon. Bodenkultur-Wien Munchen, 55(3):129-134.

14. Chowdhry, M.A., Rasool, I., Khaliq, I., Mahmood, T. and Gilani, M.M. (1999). Genetics of some biometric traits in spring wheat under normal and drought environment. Barley and Wheat Newsletter, 18(1): 34-39.

15. Coates, S.T. and White, D.G. (1998). Inheritance of resistance to gray leaf spot in crosses involving selected resistant inberd lines of corn. Physiopathology, 88: 972-982.

16. Darvishzadeh, R., Alavi, S.R. and Sarafi, A. (2009). Genetic variability for chlorine concentration in oriental tobacco genotypes. Archives of Agronomy and Soil Science, 57: 167-177.

17. Davalieva, K., Maleva, L., Filiposki, K., Spiroski, O. and Efremov, G.D. (2010). Genetic variability of Macedonian tobacco varieties determined by microsatellite marker analysis. Diversity, 2: 439-449.

18. De Souza, V.A., Byrne, D.H. and Taylor, J.F. (2000). Predicted breeding values for nine plant and fruit characteristics of 28 peach genotypes. Journal of the American Society for Horticultural Science, 125(4): 460-465.

19. Ehdaei, B. and Ghadri, A. (1973). Diallel Method and Using in Plant Breeding. Shahid Chamran University of Ahvaz Press. Ahvaz, IR (In Persian).

20. El-Morsy, S.I., Dorra, M.D.M., Elham, A.A.E., Atef, A.A.H. and Ahmed, Y.M. (2009). Comparative studies on diploid and tetraploid levels of Nicotiana alata. Academic Journal of Plant Sciences, 2: 182-188.

21. Falconer, D.S. and Mackay, T.F.C. (1996). Introduction to Quantitative Genetics. Pearson, Harlow, UK.

22. Fehr, W. (1991). Principles of Cultivar Development: Theory and Technique. Macmillan Publishing, Equitable Building; New York, USA.

23. Fernandez, G.C. (1992). Effective selection criteria for assessing plant stress tolerance. Paper presented at the Proceeding of the International Symposium on Adaptation of Vegetables and other Food Crops in Temperature and Water Stress, Aug. 13-16, Shanhua, Taiwan.

24. Fresnedo-Ramirez, J., Frett, T.J., Sandefur, P.J., Salgado, A.A., Clark, J.R., Gasic, K., Peace, C., Anderson, N., Hartmann, T.P., Byrne, D.H., Bink, M., Van de Weg, E., Crisosto, C.H. and Gradziel, T.M. (2016). QTL mapping and breeding value estimation through pedigree-based analysis of fruit size and weight in four diverse peach breeding programs. Tree Genetics and Genomes, 12(2): 25. DOI 10.1007/s11295-016-0985-z [DOI:10.1007/s11295-016-0985-z]

25. Gavuzzi, P., Rizza, F., Palumbo, M., Campanile, R., Ricciardi, G. and Borghi, B. (1997). Evaluation of field and laboratory predictors of drought and heat tolerance in winter cereals. Canadian Journal of Plant Science, 77(4): 523-531.

26. Hallauer, A.R., Carena, M.J. and Miranda, F.J.B. (2010). Quantitative Genetics in Maize Breeding. Springer, New York, USA.

27. Hatami Maleki, M.H., Karimzadeh, G., Darvishzadeh, R. and Alavi, R. (2012). Genetic variation of oriental tobaccos using multivariate analysis. Iranian Journal of Field Crops Research, 10(1): 100-106 (In Persian).

28. Hatami Maleki, M.H., Darvishzadeh, R. and Mohseni, Z. (2014). Evaluation of genetic diversity and classification of advanced sunflower lines using ISSR markers. Agricultural Biotechnology Journal, 3: 33-44 (In Persian).

29. Henderson, C. (1990). Statistical Methods in Animal Improvement. Springer, New York, USA.

30. Hoseinpour, F., Darvishzadeh, R. and Abdollahi, B. (2019). Study on expression of transcription factors WRKY and AP2Domain in oily sunflower under salt stress. Genetic Engineering and Biosafety Journal, 8(2): 171-180 (In Persian).

31. Hosseinzadeh, F.N., Shahadati, M.Z., Kiani, G., Salavati, M.R., Zamani, P., Mahdavi, A. and Alinejad, R. (2015). Investigation of genetic diversity among different oriental tobacco (Nicotiana tabacum L.) varieties using multivariate methods. Journal of Crop Breeding, 7(15): 126-134 (In Persian).

32. Hayman, B.I. (1954). The theory and analysis of diallel crosses. Genetics, 39: 789-809.

33. Imai, A., Kuniga, T., Yoshioka, T., Nonaka, K., Mitani, N., Fukamachi, H., Hiehata, N., Yamamoto, M., Hayashi, T. (2016). Evaluation of the best linear unbiased prediction method for breeding values of fruit-quality traits in citrus. Tree Genetics and Genomes, 12(6): 119.

34. Isik, F., Holland, J. and Maltecca, C. (2017). Genetic Data Analysis for Plant and Animal Breeding. Springer, New York, USA. [DOI:10.1007/978-3-319-55177-7]

35. Johnson, R.A. and Wichern, D.W. (2007). Applied Multivariate Statistical Analysis. Prentice Hall International, INC. New Jersey, USA.

36. Kearsey, M.J. and Pooni, H.S. (1996). The genetical analysis of quantitativetraits. London: Chapman and Hall, London, UK. [DOI:10.1007/978-1-4899-4441-2]

37. Kiani, S., Babaeian, J.N., Ranjbar, G.A., Kazemitabar, S.K. and Nowrozi. M. (2015). The genetical evaluation of quantitative traits in rice (Oryza sativa L.) by generation mean analysis. Journal of Crop Breeding, 7(15): 105-114 (In Persian).

38. Lakshmish, K.J. and Shivanna, H. (1999). Correlation and path .analysis in FCV tobacco (Nicotiana tabacum L.). Mysore. Journal of Agricultural Sciences, 33(1): 45-48.

39. Laude, T.P. and Carena, M.J. (2015). Genetic diversity and heterotic grouping of tropical and temperate maize populations adapted to the northern U.S. corn belt. Euphytica, 204: 661-677.

40. Mackay, T.F.C. (2001). The genetic architecture of quantitative traits. Annual Review of Genetics, 35: 303-339.

41. Martinez-Garcia, P.J., Famula, R., Leslie, C.A., Mcgranahan, G.H., Famula, T.R. and Neale, D.B. (2017). Predicting breeding values and genetic components using generalized linear mixed models for categorical and continuous traits in walnut (Juglans regia). Tree Genetics and Genomes, 13(5): 109. DOI 10.1007/s11295-017-1187-z [DOI:10.1007/s11295-017-1187-z]

42. Mather, K. and Jinks, J.L. (1982). Biometrical Genetics. Chapman & Hall, London, UK. [DOI:10.1007/978-1-4899-3406-2]

43. Mohammadi, S.A. and Prasanna, B.M. (2003) Review and interpretation analysis of genetic diversity in crop plants-salient statistical tools. Crop Science, 43: 1235-1248. [DOI:10.2135/cropsci2003.1235]

44. Moon, H., Nifong, J., Nicholson, J., Heineman, A., Lion, K., Van der Hoeven, R., Hayes, A. and Lewis, R. (2009). Microsatellite-based analysis of tobacco (Nicotiana tabacum L.) genetic resources. Crop Science, 49(6): 2149-2159.

45. Moro, J. and Denis, J.B. (1997). selecting genotyps by clustering, for qualitative genotype by environment using a non-symetric inferiority score. Agronomie, 17(5): 283-289.

46. Parand, M., Yamchi, A., Soltanloo, H., Zaynalinejad, K. (2019). Study of morphological traits and genetic diversity of low molecular wight glutenin subunits in some bread wheat cultivars using SRAP markers. Journal of Crop Breeding, 10(28): 38-49 (In Persian).

47. Patterson, H.D. and Thompson, R. (1971). Recovery of inter-block information when block sizes are unequal. Biometrika, 58(3): 545-554.

48. Piepho, H., Möhring, J., Melchinger, A. and Büchse, A. (2008). BLUP for phenotypic selection in plant breeding and variety testing. Euphytica, 161(1-2): 209-228.

49. Pour‐Aboughadareh, A., Yousefian, M., Moradkhani, H., Moghaddam Vahed, M., Poczai, P. and Siddique, K.H. (2019). iPASTIC: An online toolkit to estimate plant abiotic stress indices. Applications in Plant Sciences, 7(7): 11278.

50. Quddus, M.R., Rahman, M.A., Jahan, N., Debsharma, S.K., Disha, R.F., Hasan, M.M., Aditya, T.L., Iftekharuddaula, K.M. and Collard, B.C. (2019). Estimating pedigree-based breeding values and stability parameters of elite rice breeding lines for yield under salt stress during the boro season in Bangladesh. Plant Breeding and Biotechnology, 7(3): 257-271.

51. Quintal, S.S.R., Viana, A.P., Campos, B., Vivas, M. and Amaral Junior, A.T. (2017). Selection via mixed models in segregating guava families based on yield and quality traits. Revista Brasileira de Fruticultura, 39(2): Doi.org/10.1590/0100-29452017866.

52. Ramos, H.C.C., Pereira, M.G., Viana, A.P., da Luz, L.N., Cardoso, D.L. and Ferreguetti, G.A. (2014). Combined selection in backcross population of papaya (Carica papaya L.) by the mixed model methodology. American Journal of Plant Sciences, 5(20): 2973.

53. Redhu, A.S., Singh, R.K. and Luthara, O.P. (1986). Genetic analysis of grain yield and its components in some leaf rust resistance genotypes of wheat. Haryana Agricultural University Journal of Research, 16(3): 228-232.

54. Resende, R.M.S., Jank, L., Valle, C.B.D. and Bonato, A.L.V. (2004). Biometrical analysis and selection of tetraploid progenies of Panicum maximum using mixed model methods. Pesquisa Agropecuária Brasileira, 39(4): 335-341.

55. Rispail, N., Dita, M.A. González‐Verdejo, C., Pérez‐de‐Luque, A., Castillejo, M.A., Prats, E., Román, B., Jorrín, J. and Rubiales, D. (2007). Plant resistance to parasitic plants: molecular approaches to an old foe. New Phytologist, 173(4): 703-712.

56. Roudbari, Z., Mohammadi-Nejad, G. and Shahsavand-Hassani, H. (2017). Field screening of primary and secondary tritipyrum genotypes using selection indices based on blup under saline and normal conditions. Crop Science, 57(3):1495-1503.

57. Redhu, A.S., Singh, R.K. and Luthara, O.P. (1986). Genetic analysis of grain yield and its components in some leaf rust resistance genotypes of wheat. Haryana Agricultural University Journal of Research, 16(3): 228-232.

58. Rezvani Moghaddam, P., Mohammad Abadi, A. and Moradi, R. (2010). Effects of chemical and organic fertilizers on yield and components yield of sesame (Sesamum indicum L.) under different plant density. Journal of Agroecology, 2(2): 256-265.

59. Rubiales, D., Pérez-de-Luque, A., Cubero, J. and Sillero, J. (2003). Crenate broomrape (orobanche crenata) infection in field pea cultivars. Crop Protection, 22(6): 865-872.

60. Sadeghi, F. and Rahimi, M. (2017). The use of cluster analysis for best lines selection in Maize at S6 generation. Journal of Crop Breeding, 8(20): 91-98 (In Persian).

61. Saeidi, M.S., Torabi, A. and Aghabeygi, F. (2010). Notes on the genus orobanche (Orobanchaceae) in iran. The Iranian Journal of Botany, 16(1): 107-113 (In Persian).

62. Salavati Meybodi, M.R., Ranjbar, G.A. Kazemitabar, S.K. and Najafi Zarrini, H. (2017). Investigation of heritability and genetic diversity among tobacco genotypes using issr markers and morpho-physiological traits. Plant Genetic Researches, 4(1): 75-88 (In Persian).

63. SAS-Institute-Inc. (2014). Base SAS 9.4 Procedures Guide: Statistical Procedures, Third Edition. SAS Institute Inc., Cary, North Carolina, USA.

64. Schneeweiss, G.M., Palomeque, T., Colwell, A.E. and Weiss‐Schneeweiss, H. (2004). Chromosome numbers and karyotype evolution in holoparasitic orobanche (Orobanchaceae) and related genera. American Journal of Botany, 91(3): 439-448.

65. Searle, S.R., Casella, G. and McCulloch, C.E. (2009). Variance Components. John Wiley & Sons, New Jersey, USA.

66. Shapiro, S.S. and Wilk, M.B. (1965). An analysis of variance test for normality. Biometrika, 52: 591-599.

67. Sillero, J.C., Villegas-Fernández, A.M., Thomas, J., Rojas-Molina, M.M., Emeran, A.A., Fernández-Aparicio, M. and Rubiales, D. (2010). Faba bean breeding for disease resistance. Field Crops Research, 115(3): 297-307.

68. Vaghari, A.E., Hatami, M.H., Basirnia, A., Ahmadi, D. and Darvishzadeh, R. (2015). Evaluation of genetic variation in some Iranian oriental and semi oriental tobacco germplasms by using simple sequence repeat markers. Modern Genetics Journal, 9(4): 517-523 (In Persian).

69. Villumsen, T.M. and Janss, L. (2009). Bayesian genomic selection: The effect of haplotype length and priors. BMC Proceedings, 3: PMC2654492, Doi: 10.1186/1753-6561-3-s1-s11. [DOI:10.1186/1753-6561-3-S1-S11]

Send email to the article author

‎ 10.52547/pgr.7.1.7

‎ 20.1001.1.23831367.1399.7.1.4.1

Mendeley

Zotero

RefWorks

Tahmasbali M, Darvishzadeh R, Fayaz Moghaddam A. Estimating Breeding Value of Agronomic Traits in Oriental Tobacco Genotypes under Broomrape Stress and Normal Conditions. pgr 2020; 7 (1) :103-126
URL: http://pgr.lu.ac.ir/article-1-164-en.html

Rights and permissions
	This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Volume 7, Issue 1 (2020)

Back to browse issues page

Persian site map - English site map - Created in 0.06 seconds with 38 queries by YEKTAWEB 4657