Correlation and selection gains in F6 wheat genotypes
Palabras clave:
Advanced generation, genetic divergence, Triticum aestivum L.Resumen
The agronomic traits have complex quantitative inheritance, wheat breeding has a highly cost and time expending to achieve advanced lines, and new cultivars. The objective of this work was to estimate the phenotypic (rp), genotypic (rg) and environmental (re) correlation coefficients and the genetic parameters, as well as to estimate the selection gains between agronomic traits in wheat using multivariate analysis. F6 generation was carried out in a randomized block experimental design, with fifteen wheat genotypes arranged in three replications. The traits measured were days of emergence to flowering, plant height, number of tillers, spike length, number of spikelets, kernel weight and thousand kernel weight. Correlation coefficients, variance components, genetic parameters, selection gain, Euclidiana’s distance, relative contribution of traits and canonical variables were estimated. Selection based on number of tillers, kernel weight and thousand kernel weight may result in expressive selection gains. The number of fertile tillers per plant showed a significant and positive intermediate association with kernel weight and positive correlation with number of spikelets. The cycle showed greater contribution to the genetic divergence among genotypes studied. Distinct groups highlighted the genetic variability among genotypes.
Citas
Ahmad B, Khalil IH, Iqbal M & Rahman HU (2010) Genotypic and phenotypic correlation among yield components in bread wheat under normal and late plantings. Sarhad Journal of Agriculture, 26:259-265.
Alvares CA, Stape JL, Sentelhas PC, Gonçalves JLM & Sparovek G (2013) Köppen’s climate classification map for Brazil. Meteorologische Zeitschrift, 22:711-728.
Bornhofen E, Benin G, Matei G, Silva CL, Beche E, Pagliosa ES, Hagemann TR & Pinnow C (2013) Combining ability of wheat parents in two generations. Semina: Ciências Agrárias, 34:3129-3140.
Carvalho IR, Souza VQD, Nardino M, Follmann DN, Schmidt D & Baretta D (2015) Correlações canônicas entre caracteres morfológicos e componentes de produção em trigo de duplo propósito. Pesquisa Agropecuária Brasileira, 50:690-697.
Cruz CD (2016) Genes Software - extended and integrated with the R, Matlab and Selegen. Acta Scientiarum Agronomy, 38:547-552.
Cruz CD, Regazzi AJ & Carneiro PCS (2004) Modelos biométricos aplicados ao melhoramento genético. 4a ed. Viçosa, Editora UFV. 480p.
Elhani S, Martos V, Rharrabti Y, Royo C & Garcýa del Moral LF (2007) Contribution of main stem and tillers to durum wheat (Triticum turgidum L. var. durum) grain yield and its components grown in Mediterranean environments. Field Crops Research, 103:25-35.
Falconer DS & Mackay TFC (1996) Introduction to quantitative genetics. London, Longman Malaysia. 463p.
Fellahi ZEA, Hannachi A & Bouzerzour H (2018) Analysis of Direct and Indirect Selection and Indices in Bread Wheat (Triticum aestivum L.) Segregating Progeny. International Journal of Agronomy, 2018:01-11.
Fioreze SL & Rodrigues JD (2012) Perfilhamento do trigo em função da aplicação de regulador vegetal. Revista Brasileira de Ciências Agrárias, 7:750-755.
Galton F (1888) Co-relations and their measurement, chiefly from anthropometric data. Proceedings of the Royal Society of London, 45:135-145.
Gurjar D & Marker S (2018) Evaluation of genetic divergence in wheat (Triticum aestivum L.) germplasm. Electronic Journal of Plant Breeding, 91:361-367.
Kefale H & Menzir A (2019) Genetic Variation of Bread Wheat (Triticum aestivum L.) Varieties Based on Phenological, Morphological and Quality Traits at Guay Kebele in Debre Elias District, East Gojjam Zone, Northwestern Ethiopia. Journal of Biology, Agriculture and Healthcare, 4:45-55.
Khan A, Alam A, Alam MK, Alam MJ & Sarker ZI (2013) Genotypic and phenotypic correlation and path analysis in durum wheat (Triticum turgidum L. var. durum). Bangladesh Journal of Agricultural Research, 38:219-225.
Laidig F, Piepho HP, Drobek T & Meyer U (2017) Breeding progress, variation, and correlation of grain and quality traits in winter rye hybrid and population varieties and national on-farm progress in Germany over 26 years. Theoretical and Applied Genetics, 130:981-998.
Lo Valvo PJ, Miralles DJ & Serrago RA (2018) Genetic progress in Argentine bread wheat varieties released between 1918 and 2011: Changes in physiological and numerical yield components. Field Crops Research, 221:314-321.
Mangi AS, Sial MA, Ansari BA, Arain MA, Laghari KA & Mirbahar AA (2010) heritability studies for grain yield and yield components in f3 segregating generation of spring wheat. Pakistan Journal of Botany, 42:1807-1813.
Maechler M, Rousseeuw P, Struyf A, Hubert M & Hornik K (2018) Cluster: Cluster Analysis Basics and Extensions. Version 2.0.7-1. Available at: https://svn.r-project.org/R-packages/trunk/cluster. Accessed on: June 14th, 2020.
McFerrin L (2013) HDMD: Statistical Analysis Tools for High Dimension Molecular Data (HDMD). Version 1.2. Available at: <https://CRAN.Rproject.org/package=HDMD>. Accessed on: May 20th, 2020.
Meira D, Meier C, Olivoto T, Nardino M, Klein LA, Moro ED, Fassini F, Marchioro VS & Souza VQD (2019) Estimates of genetic parameters between and within black oat populations. Bragantia, 78:43-51.
Mohammadi M, Karimizadeh R, Shefazadeh MK & Sadeghzadeh B (2011) Statistical analysis of durum wheat yield under semi-warm dryland condition. Australian Journal of Crop Science, 5:1292-1297.
Mojena R (1977) Hierarchical grouping methods and stopping rules: an evaluation. The Computer Journal, 20:359-363.
Ni F, Qi J, Hao Q, Lyu B, Luo MC, Wang Y, Chen F, Wang S, Zhang C, Epstein L, Zhao X, Wang H, Zhang X, Chen C, Sun L & Fu D (2017) Wheat Ms2 encodes for an orphan protein that confers male sterility in grass species. Nature Communications, 8:15121.
Olivoto T, Souza VQ, Nardino M, Carvalho IR, Ferrari M, Pelegrin AJ, Szareski VJ & Schmidt D (2017) Multicollinearity in Path Analysis: A Simple Method to Reduce Its Effects. Agronomy journal, 109:131-142.
Pearson K (1920) Notes on the History of Correlation. Biometrika, 13:25-45.
R Development Core Team (2016) R: A language and environment for statistical computing. Available at: https://www.R-project.org/. Accessed on: July 11th, 2020.
Resende MDVD & Duarte JB (2007) Precisão e controle de qualidade em experimentos de avaliação de cultivares. Pesquisa Agropecuária Tropical, 37:182-194.
Rigatti A, Meira D, Olivoto T, Meier C, Nardino M, Lunkes A, Klein LA, Fassini F, Moro ED, Marchioro VS & Souza VQ (2019) Grain Yield and Its Associations With Pre-harvest Sprouting in Wheat. Journal of Agricultural Science, 11:142-150.
Silva AHD, Camargo CEDO & Júnior EUR (2010) Potencial de genótipos de trigo duro para produtividade e caracteres agronômicos no Estado de São Paulo. Bragantia, 69:535-546.
Singh D (1981) The relative importance of characters affecting genetic divergence. The Indian Journal of Genetic and Plant Breeding, 41:237-245.
Ali T, Singh MK, Bharadwaj DN & Singh L (2016) Analysis of genetic divergence in wheat (Triticum aestivum L.). Environment and Ecology, 35:2081-2083.
Steel RGD & Torrie JH (1980) Principles and procedures of statistics: A biometrical approach. 2º ed. New York, McGraw-Hill. p.20-90.
Wiersma JJ, Busch RH, Fulcher GG & Hareland GA (2001) Recurrent Selection for Kernel Weight in Spring Wheat. Crop Science, 41:999-1005.
Woyann LG, Zdziarski AD, Zanella R, Rosa AC, Castro RL, Caierão E, Toigo MC, Storck L, Wu J & Benin G (2019) Genetic gain over 30 years of spring wheat breeding in Brazil. Crop Science, 59:2036-2045.
Xiao D & Tao F (2014) Contributions of cultivars, management and climate change to winter wheat yield in the North China Plain in the past three decades. European Journal of Agronomy, 52:112-122.
Yao Y, Lv L, Zhang L, Yao H, Dong Z, Zhang J, Ji J, Jia X & Wang H (2012) Genetic gains in grain yield and physiological traits of winter wheat in Hebei Province of China, from 1964 to 2007. Field Crops Research, 239:114-123.
