Research Article
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Year 2021, Volume: 26 Issue: 1, 71 - 78, 29.06.2021
https://doi.org/10.17557/tjfc.943928

Abstract

References

  • Akcura, M., Y. Kaya, S. Taner and R. Ayranci. 2006. Parametric stability analyses for grain yield of durum wheat. Plant Soil and Environment. 52: 254-261.
  • Ali, N., F. Javıdfar and A.A. Attary. 2002. Stability analysis of seed yield in winter type rapeseed (Brassica napus) varieties. Pak. J. Bot. 34: 151-155.
  • Ali, N., F. Javıdfar and M.Y. Mırza. 2003. Selection of stable rapeseed (Brassica napus L.) genotypes through regression analysis. Pak. J. Bot. 35: 175-180. Baker, R.J. 1969. Genotype-environment interactions in yield of wheat. Canadian Journal of Plant Sci. 49: 743-751.
  • Becker, H.C. and J. Leon. 1988. Stability analysis in plant breeding. Plant Breeding. 101: 1-23.
  • Comstock, R.E. and R.H. Moll. 1963. Genotyp × environment interactions. Statistical Genetics and Plant Breeding. No. REP-1173. CIMMYT Cullis, B.R., A.B. Smith, C.P. Beeck and W.A. Cowling. 2010. Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysis. Genome. 53(11): 1002-1016.
  • Eberhart, S.A. and W.A. Russell. 1966. Stability parameters for comparing varieties. Crops Sci. 6: 36-40. El-Nakhlawy, F.S. 2009. Performance of canola (Brassica napas L.) seed yield, yield components and seed quality under the effects of four genotypes and nitrogen fertilizer rates. Meteorology, Environment and Arid Land Agriculture Sciences. 20(2).
  • Escobar, M., M. Berti, I. Matus, M. Tapia and B. Johnson. 2011. Genotype × environment interaction in canola (Brassica napus L.) seed yield in Chile. Chilean Journal of Agricultural Research. 71: 175-186.
  • FAOSTAT. 2021. Data stat year 2021 Food Agriculture Organization, (http://www.fao.org/faostat/en/) verified 2 April 2021. Rome, Italy.
  • Finlay, K.W. and G.N. Wilkinson. 1963. The analysis of adaptation in a plant breeding programme. Aust. Journal of Agricultural Research. 14: 742-754.
  • Fox, P.N., B. Skovmand, B.K. Thompson, H.J. Braun and R. Cormier. 1990. Yield and adaptation of hexaploid spring triticale. Euphytica. 47: 57-64.
  • Francis, T.R. and W. Kannenberg. 1978. Yield stability studies in short-season ı.a. descriptive method for grouping genotypes. Can. J. Plant Sci. 58: 1029-1034.
  • George, N., K. Tungate, C. Beeck and M. Stamm. 2012. Exploring genotype by environment interaction in winter canola in North Carolina. Journal of Agricultural Sci. 2: 237-244.
  • Gunasekera, C.P., L.D. Martin, K.H.M. Siddique, and G.H. Walton, G.H. 2006. Genotype by environment interactions of Indian mustard (Brassica juncea L.) and canola (B. napus L.) in Mediterranean-type environments: 1. Crop growth and seed yield. European Journal of Agronomy. 25(1), 1-12.
  • Huehn, M. 1979. Beitrage zur erfassung der phanotypischen stabilitat. EDV Med Biol.10:112-117.
  • Huehn, M. 1990. Nonparametric measures of phenotypic stability. Part 1: Theory. Euphytica. 47(3): 189-194.
  • Huehn, M. 1996. Non-parametric analysis of genotype x environment interactions by ranks. Genotype by environment interaction. CRC Press, Boca Raton, FL, 213-228.
  • Kang, M.S. 1988. A rank-sum method for selecting high-yielding, stable corn genotypes. Cereal Research Communication. 16: 113-115. Kang, M.S. and H.G. Gauch. 1996.
  • Genotype-by-Environment Interaction. CRC press, Boca Raton, FL. Lima, L.H.D.S., A.L. Braccini, C.A. Scapim, G.G. Piccinin and R.M. Ponce. 2017. Adaptability and stability of canola hybrids in different sowing dates. Revista Ciência Agronomica. 48: 374-380.
  • Lin, C.S., M.R. Binns and L.P. Lefkovitch. 1986. Stability analysis: where do we stand? Crop Sci. 26: 894-900. Lu, H.Y. 1995. PC‐SAS program for estimating Hühn's nonparametric stability statistics. Agronomy journal. 87(5): 888-891.
  • Marjanovic-Jeromela, A., N. Nag, J. Gvozdanovic-Varga, N. Hristov, A. Kondic-Spica, M.V.R. Marinkovic. 2011. Genotype environment interaction for seed yield per plant in rapeseed using AMMI model. Pesq. Agropec. Bras. Brasilia. 46: 174-181.
  • Mashayekh, A., A. Mohamadi and S. Gharanjick. 2014. Evaluation of canola genotypes for yield stability in the four regions in Iran. Bulletin of Environment, Pharmacology and Life Sci. 3: 123-128.
  • Moghaddam, M.J. and S.S. Pourdad. 2011. Genotype × environment interactions and simultaneous selection for high oil yield and stability in rainfed warm areas rapeseed (Brassica napus L.) from Iran. Euphytica. 180: 321-335.
  • Mortazavian, S.M.M. and S. Azıı-nıa. 2014. Nonparametric stability analysis in multi-environment trial of canola. Turkish Journal of Field Crops. 19: 108-117.
  • Nassar, R. and M. Huehn. 1987. Studies on estimation of phenotypic stability: Tests of significance for nonparametric measures of phenotypic stability. Biometrics. 45-53.
  • Nowosad, K., A. Liersch, W. Pop³awska and J. Bocianowski. 2016. Genotype by environment interaction for seed yield in rapeseed (Brassica napus L.) using additive main effects and multiplicative interaction model. Euphytica. 208(1): 187-194.
  • Oghan, H.A., N. Sabaghnia, V. Rameeh, H.R. Fanaee and E. Hezarjeribi. 2016. Univariate stability analysis of genotype × environment interaction of oilseed rape seed yield. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis. 64: 1625-1634.
  • Perkins, J.M. and J.L. Jinks. 1968. Environmental and genotype-environmental components of variability III. multiple lines and crosses. Heredity. 23: 339-356.
  • Pinthus, M.J. 1973. Estimate of genotypic value: a proposed method. Euphytica 22: 121-123. Sabaghnia, N., H. Dehghani, and S.H. Sabaghpour. 2006. Nonparametric methods for interpreting genotype× environment interaction of lentil genotypes. Crop Sci. 46(3): 1100-1106.
  • SAS Institute. 1999. SAS/STAT User’s Guide. 2nd edition. SAS Institute Inc. Cary. NC Shafii, B., K.A. Mahler, W.J. Price and D.L. Auld. 1992. Genotype×environment interaction effects on winter rapeseed yield and oil content. Crop Sci. 32: 922-927.
  • Sharma, P. and V. Sardana. 2016. Evaluating morpho-physiological and quality traits to compliment seed yield under changing climatic conditions in Brassicas. Journal of Environmental Biology. 37: 493-502.
  • Shojaei, S.H., K. Mostafavi, M. Khodarahmi and M. Zabet. 2011. Response study of canola (Brassica napus L.) cultivars to multi-environments using genotype plus genotype environment interaction (GGE) biplot method in Iran. African Journal of Biotechnology. 10: 10877-10881.
  • Shukla, G.K. 1972. Some statistical aspects of partitioning genotype-environmental components of variability. Heredity. 29: 237-245.
  • Si, P. and G.H. Walton. 2004. Determinants of oil concentration and seed yield in canola and Indian mustard in the lower rainfall areas of Western Australia. Aust. J. Agric. Res. 55: 367–377.
  • Si, P., R.J. Mailer, N. Galwey and D.W. Turner. 2003. Influence of genotype and environment on oil and protein concentrations of canola (Brassica napus L.) grown across southern Australia. Aust. J. Agric. Res. 54: 397–407.
  • Spearman, C. 1910. Correlation calculated from faulty data. British Journal of Psychology. 3: 271-295.
  • Steel, R.G.D. and J.H. Torrie. 1986. Principles and procedures of statistics: a biometrical approach. McGraw-Hill.
  • Tahira, R.A., M.A. Khan and M. Amjad. 2013. Stability analysis of canola (Brassica napus L.) genotypes in Pakistan. Global Advanced Research Journal of Agricultural Sci. 2: 270-275.
  • Wood, J.T. 1976. The use of environmental variablesin the interpretation of genotype-environment interaction. Heredity. 37: 1-7.
  • Wricke, G. 1962. Uber eine methode zur erfassung der ökologischen streubreite in feldversuchen Z. Pflanzenzüchtung. 47: 92-96.
  • Wright, P.R., J.M. Morgan, R.S. Jessop and A. Cass. 1995. Comparative adaptation of canola (Brassica juncea) to soil water deficits: yield and yield components. Field Crops Research. 42: 1-13.
  • Yan, W. and M.S. Kang 2002. GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists. CRC press. Yılmaz, H. and B. Avkıran 2020. Analysis of Canola (Rapeseed) Production Cost and Income in Context of Oilseeds Production Support Policies: A Case Study from Trakya Region of Turkey. Åêîíîìèêà ïîšîïğèâğåäå. 67(2).
  • Zhang, H., J.D. Berger and S.P. Milroy. 2011. Genotype× environment interaction of canola (Brassica napus L.) in multi-environment trials. Proceedings of the 17th Australian Research Assembly on Brassicas. 50-6.
  • Zhang, H., J.D. Berger and S.P. Milroy. 2013. Genotype× environment interaction studies highlight the role of phenology in specific adaptation of canola (Brassica napus) to contrasting Mediterranean climates. Field Crops Research. 144: 77-88.

MULTI-ENVIRONMENT TRIAL ANALYSIS BY PARAMETRIC AND NON-PARAMETRIC STABILITY PARAMETERS FOR SEED YIELD IN WINTER RAPESEED (Brassica napus L.) GENOTYPES

Year 2021, Volume: 26 Issue: 1, 71 - 78, 29.06.2021
https://doi.org/10.17557/tjfc.943928

Abstract

The objective of this study was to determine the stability of 11 different rapeseed genotypes in terms of seed yield, throughout 3 years (2014-2015-2016), 3 locations (Tekirdag, Kırklareli, Edirne), in total 8 environment in Thrace Region. The experiment was designed as a randomized complete block design with four replications. The aim of this study was to determine rapeseed genotypes having a high adaptation for seed yield. Parametric (Wi2, bi, Sdi2, Bi, σi2, ri2, Sxi2, CVi and Pi ) and non-parametric (Si(2), Si(3), Si(6), RS and TOP) stability statistics were used to determine stability of the genotypes. The analysis of variance for seed yield showed that genotypes, environments and genotype by environment interaction all were significant (P˂0,01). According to parametric and non-parametric (except TOP methods) stability analysis, genotype Wosry 142 was determined as a well-adapted genotype; genotype Wosry 144 poorly adapted genotype in across environments. Genotype Wosry 142 may be recommended for cultivation in the different environments tested.

References

  • Akcura, M., Y. Kaya, S. Taner and R. Ayranci. 2006. Parametric stability analyses for grain yield of durum wheat. Plant Soil and Environment. 52: 254-261.
  • Ali, N., F. Javıdfar and A.A. Attary. 2002. Stability analysis of seed yield in winter type rapeseed (Brassica napus) varieties. Pak. J. Bot. 34: 151-155.
  • Ali, N., F. Javıdfar and M.Y. Mırza. 2003. Selection of stable rapeseed (Brassica napus L.) genotypes through regression analysis. Pak. J. Bot. 35: 175-180. Baker, R.J. 1969. Genotype-environment interactions in yield of wheat. Canadian Journal of Plant Sci. 49: 743-751.
  • Becker, H.C. and J. Leon. 1988. Stability analysis in plant breeding. Plant Breeding. 101: 1-23.
  • Comstock, R.E. and R.H. Moll. 1963. Genotyp × environment interactions. Statistical Genetics and Plant Breeding. No. REP-1173. CIMMYT Cullis, B.R., A.B. Smith, C.P. Beeck and W.A. Cowling. 2010. Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysis. Genome. 53(11): 1002-1016.
  • Eberhart, S.A. and W.A. Russell. 1966. Stability parameters for comparing varieties. Crops Sci. 6: 36-40. El-Nakhlawy, F.S. 2009. Performance of canola (Brassica napas L.) seed yield, yield components and seed quality under the effects of four genotypes and nitrogen fertilizer rates. Meteorology, Environment and Arid Land Agriculture Sciences. 20(2).
  • Escobar, M., M. Berti, I. Matus, M. Tapia and B. Johnson. 2011. Genotype × environment interaction in canola (Brassica napus L.) seed yield in Chile. Chilean Journal of Agricultural Research. 71: 175-186.
  • FAOSTAT. 2021. Data stat year 2021 Food Agriculture Organization, (http://www.fao.org/faostat/en/) verified 2 April 2021. Rome, Italy.
  • Finlay, K.W. and G.N. Wilkinson. 1963. The analysis of adaptation in a plant breeding programme. Aust. Journal of Agricultural Research. 14: 742-754.
  • Fox, P.N., B. Skovmand, B.K. Thompson, H.J. Braun and R. Cormier. 1990. Yield and adaptation of hexaploid spring triticale. Euphytica. 47: 57-64.
  • Francis, T.R. and W. Kannenberg. 1978. Yield stability studies in short-season ı.a. descriptive method for grouping genotypes. Can. J. Plant Sci. 58: 1029-1034.
  • George, N., K. Tungate, C. Beeck and M. Stamm. 2012. Exploring genotype by environment interaction in winter canola in North Carolina. Journal of Agricultural Sci. 2: 237-244.
  • Gunasekera, C.P., L.D. Martin, K.H.M. Siddique, and G.H. Walton, G.H. 2006. Genotype by environment interactions of Indian mustard (Brassica juncea L.) and canola (B. napus L.) in Mediterranean-type environments: 1. Crop growth and seed yield. European Journal of Agronomy. 25(1), 1-12.
  • Huehn, M. 1979. Beitrage zur erfassung der phanotypischen stabilitat. EDV Med Biol.10:112-117.
  • Huehn, M. 1990. Nonparametric measures of phenotypic stability. Part 1: Theory. Euphytica. 47(3): 189-194.
  • Huehn, M. 1996. Non-parametric analysis of genotype x environment interactions by ranks. Genotype by environment interaction. CRC Press, Boca Raton, FL, 213-228.
  • Kang, M.S. 1988. A rank-sum method for selecting high-yielding, stable corn genotypes. Cereal Research Communication. 16: 113-115. Kang, M.S. and H.G. Gauch. 1996.
  • Genotype-by-Environment Interaction. CRC press, Boca Raton, FL. Lima, L.H.D.S., A.L. Braccini, C.A. Scapim, G.G. Piccinin and R.M. Ponce. 2017. Adaptability and stability of canola hybrids in different sowing dates. Revista Ciência Agronomica. 48: 374-380.
  • Lin, C.S., M.R. Binns and L.P. Lefkovitch. 1986. Stability analysis: where do we stand? Crop Sci. 26: 894-900. Lu, H.Y. 1995. PC‐SAS program for estimating Hühn's nonparametric stability statistics. Agronomy journal. 87(5): 888-891.
  • Marjanovic-Jeromela, A., N. Nag, J. Gvozdanovic-Varga, N. Hristov, A. Kondic-Spica, M.V.R. Marinkovic. 2011. Genotype environment interaction for seed yield per plant in rapeseed using AMMI model. Pesq. Agropec. Bras. Brasilia. 46: 174-181.
  • Mashayekh, A., A. Mohamadi and S. Gharanjick. 2014. Evaluation of canola genotypes for yield stability in the four regions in Iran. Bulletin of Environment, Pharmacology and Life Sci. 3: 123-128.
  • Moghaddam, M.J. and S.S. Pourdad. 2011. Genotype × environment interactions and simultaneous selection for high oil yield and stability in rainfed warm areas rapeseed (Brassica napus L.) from Iran. Euphytica. 180: 321-335.
  • Mortazavian, S.M.M. and S. Azıı-nıa. 2014. Nonparametric stability analysis in multi-environment trial of canola. Turkish Journal of Field Crops. 19: 108-117.
  • Nassar, R. and M. Huehn. 1987. Studies on estimation of phenotypic stability: Tests of significance for nonparametric measures of phenotypic stability. Biometrics. 45-53.
  • Nowosad, K., A. Liersch, W. Pop³awska and J. Bocianowski. 2016. Genotype by environment interaction for seed yield in rapeseed (Brassica napus L.) using additive main effects and multiplicative interaction model. Euphytica. 208(1): 187-194.
  • Oghan, H.A., N. Sabaghnia, V. Rameeh, H.R. Fanaee and E. Hezarjeribi. 2016. Univariate stability analysis of genotype × environment interaction of oilseed rape seed yield. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis. 64: 1625-1634.
  • Perkins, J.M. and J.L. Jinks. 1968. Environmental and genotype-environmental components of variability III. multiple lines and crosses. Heredity. 23: 339-356.
  • Pinthus, M.J. 1973. Estimate of genotypic value: a proposed method. Euphytica 22: 121-123. Sabaghnia, N., H. Dehghani, and S.H. Sabaghpour. 2006. Nonparametric methods for interpreting genotype× environment interaction of lentil genotypes. Crop Sci. 46(3): 1100-1106.
  • SAS Institute. 1999. SAS/STAT User’s Guide. 2nd edition. SAS Institute Inc. Cary. NC Shafii, B., K.A. Mahler, W.J. Price and D.L. Auld. 1992. Genotype×environment interaction effects on winter rapeseed yield and oil content. Crop Sci. 32: 922-927.
  • Sharma, P. and V. Sardana. 2016. Evaluating morpho-physiological and quality traits to compliment seed yield under changing climatic conditions in Brassicas. Journal of Environmental Biology. 37: 493-502.
  • Shojaei, S.H., K. Mostafavi, M. Khodarahmi and M. Zabet. 2011. Response study of canola (Brassica napus L.) cultivars to multi-environments using genotype plus genotype environment interaction (GGE) biplot method in Iran. African Journal of Biotechnology. 10: 10877-10881.
  • Shukla, G.K. 1972. Some statistical aspects of partitioning genotype-environmental components of variability. Heredity. 29: 237-245.
  • Si, P. and G.H. Walton. 2004. Determinants of oil concentration and seed yield in canola and Indian mustard in the lower rainfall areas of Western Australia. Aust. J. Agric. Res. 55: 367–377.
  • Si, P., R.J. Mailer, N. Galwey and D.W. Turner. 2003. Influence of genotype and environment on oil and protein concentrations of canola (Brassica napus L.) grown across southern Australia. Aust. J. Agric. Res. 54: 397–407.
  • Spearman, C. 1910. Correlation calculated from faulty data. British Journal of Psychology. 3: 271-295.
  • Steel, R.G.D. and J.H. Torrie. 1986. Principles and procedures of statistics: a biometrical approach. McGraw-Hill.
  • Tahira, R.A., M.A. Khan and M. Amjad. 2013. Stability analysis of canola (Brassica napus L.) genotypes in Pakistan. Global Advanced Research Journal of Agricultural Sci. 2: 270-275.
  • Wood, J.T. 1976. The use of environmental variablesin the interpretation of genotype-environment interaction. Heredity. 37: 1-7.
  • Wricke, G. 1962. Uber eine methode zur erfassung der ökologischen streubreite in feldversuchen Z. Pflanzenzüchtung. 47: 92-96.
  • Wright, P.R., J.M. Morgan, R.S. Jessop and A. Cass. 1995. Comparative adaptation of canola (Brassica juncea) to soil water deficits: yield and yield components. Field Crops Research. 42: 1-13.
  • Yan, W. and M.S. Kang 2002. GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists. CRC press. Yılmaz, H. and B. Avkıran 2020. Analysis of Canola (Rapeseed) Production Cost and Income in Context of Oilseeds Production Support Policies: A Case Study from Trakya Region of Turkey. Åêîíîìèêà ïîšîïğèâğåäå. 67(2).
  • Zhang, H., J.D. Berger and S.P. Milroy. 2011. Genotype× environment interaction of canola (Brassica napus L.) in multi-environment trials. Proceedings of the 17th Australian Research Assembly on Brassicas. 50-6.
  • Zhang, H., J.D. Berger and S.P. Milroy. 2013. Genotype× environment interaction studies highlight the role of phenology in specific adaptation of canola (Brassica napus) to contrasting Mediterranean climates. Field Crops Research. 144: 77-88.
There are 43 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Yasemin Erdogdu This is me

Enver Esendal This is me

Publication Date June 29, 2021
Published in Issue Year 2021 Volume: 26 Issue: 1

Cite

APA Erdogdu, Y., & Esendal, E. (2021). MULTI-ENVIRONMENT TRIAL ANALYSIS BY PARAMETRIC AND NON-PARAMETRIC STABILITY PARAMETERS FOR SEED YIELD IN WINTER RAPESEED (Brassica napus L.) GENOTYPES. Turkish Journal Of Field Crops, 26(1), 71-78. https://doi.org/10.17557/tjfc.943928
AMA Erdogdu Y, Esendal E. MULTI-ENVIRONMENT TRIAL ANALYSIS BY PARAMETRIC AND NON-PARAMETRIC STABILITY PARAMETERS FOR SEED YIELD IN WINTER RAPESEED (Brassica napus L.) GENOTYPES. TJFC. June 2021;26(1):71-78. doi:10.17557/tjfc.943928
Chicago Erdogdu, Yasemin, and Enver Esendal. “MULTI-ENVIRONMENT TRIAL ANALYSIS BY PARAMETRIC AND NON-PARAMETRIC STABILITY PARAMETERS FOR SEED YIELD IN WINTER RAPESEED (Brassica Napus L.) GENOTYPES”. Turkish Journal Of Field Crops 26, no. 1 (June 2021): 71-78. https://doi.org/10.17557/tjfc.943928.
EndNote Erdogdu Y, Esendal E (June 1, 2021) MULTI-ENVIRONMENT TRIAL ANALYSIS BY PARAMETRIC AND NON-PARAMETRIC STABILITY PARAMETERS FOR SEED YIELD IN WINTER RAPESEED (Brassica napus L.) GENOTYPES. Turkish Journal Of Field Crops 26 1 71–78.
IEEE Y. Erdogdu and E. Esendal, “MULTI-ENVIRONMENT TRIAL ANALYSIS BY PARAMETRIC AND NON-PARAMETRIC STABILITY PARAMETERS FOR SEED YIELD IN WINTER RAPESEED (Brassica napus L.) GENOTYPES”, TJFC, vol. 26, no. 1, pp. 71–78, 2021, doi: 10.17557/tjfc.943928.
ISNAD Erdogdu, Yasemin - Esendal, Enver. “MULTI-ENVIRONMENT TRIAL ANALYSIS BY PARAMETRIC AND NON-PARAMETRIC STABILITY PARAMETERS FOR SEED YIELD IN WINTER RAPESEED (Brassica Napus L.) GENOTYPES”. Turkish Journal Of Field Crops 26/1 (June 2021), 71-78. https://doi.org/10.17557/tjfc.943928.
JAMA Erdogdu Y, Esendal E. MULTI-ENVIRONMENT TRIAL ANALYSIS BY PARAMETRIC AND NON-PARAMETRIC STABILITY PARAMETERS FOR SEED YIELD IN WINTER RAPESEED (Brassica napus L.) GENOTYPES. TJFC. 2021;26:71–78.
MLA Erdogdu, Yasemin and Enver Esendal. “MULTI-ENVIRONMENT TRIAL ANALYSIS BY PARAMETRIC AND NON-PARAMETRIC STABILITY PARAMETERS FOR SEED YIELD IN WINTER RAPESEED (Brassica Napus L.) GENOTYPES”. Turkish Journal Of Field Crops, vol. 26, no. 1, 2021, pp. 71-78, doi:10.17557/tjfc.943928.
Vancouver Erdogdu Y, Esendal E. MULTI-ENVIRONMENT TRIAL ANALYSIS BY PARAMETRIC AND NON-PARAMETRIC STABILITY PARAMETERS FOR SEED YIELD IN WINTER RAPESEED (Brassica napus L.) GENOTYPES. TJFC. 2021;26(1):71-8.

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