Use of the Gower algorithm in determining genetic divergence among genotypes of Carthamus tinctorius L.

Authors

DOI:

https://doi.org/10.33448/rsd-v11i8.30044

Keywords:

Safflower; Multivariate analysis; Genetic improvement.

Abstract

Safflower is a crop with a high capacity to develop and produce satisfactorily under adverse environmental conditions. Thus, the analysis of genetic diversity in gene banks is an important component in the selection of genotypes with desirable characteristics that promote genetic gain in the offspring. Given the above, the present work aimed to estimate the genetic divergence between safflower genotypes using the Gower algorithm for the joint study of quantitative and qualitative data. The experiment was developed in the experimental area of the Mato Grosso Company for Research, Assistance and Rural Extension, in the city of Cáceres-MT. We evaluated 124 genotypes of Carthamus tinctorius L. through their agronomic and morphological characteristics. The divergence among the genotypes was estimated by multivariate analysis, based on Gower's algorithm for the 21 characteristics.  Variability among individuals was detected, demonstrating the effective Gower method to estimate the divergence between genotypes.

References

Anicésio, E. C. A. D., Bonfim-silva, E. D. N. A., Silva, T. J. A. D., & Pacheco, A. B. (2018). Nitrogênio e potássio em cártamo: índice de clorofila, características biométricas e uso da água. Revista Caatinga, 31(2), 424-433.

Arantes, E. M., Cremon, C., & Luiz, M. A. C. (2012). Alterações dos atributos químicos do solo cultivado no sistema orgânico com plantio direto sob diferentes coberturas vegetais. Agrarian, 5(15), 47-54.

Bagheri, H., & Sam-Daliri, M. (2011). Effect of water stress on agronomic traits of spring safflower cultivars (Carthamus tinctorius L.). Australian Journal of Basic and Applied Sciences, 5(12), 2621-2624.

Cruz, C. D. (2016). Programa Genes: aplicativo computacional em genética e estatística: versão windows. Viçosa: UFV.

Dallacort, R., da Silva Neves, S. M. A., & Nunes, M. C. M. (2014). Variabilidade da temperatura e das chuvas de Cáceres/Pantanal Mato-Grossense-Brasil. Geografia (Londrina), 23(1), 21-33.

Debbi, A., Boureghda, H., Monte, E., & Hermosa, R. (2018). Distribution and genetic variability of Fusarium oxysporum associated with tomato diseases in Algeria and a biocontrol strategy with indigenous Trichoderma spp. Frontiers in microbiology, 9, 282.

Gower, J. C. A general coeficiente of similarity and some of its properties. Biometrics, p. 857-871, 1971.

IBPGR [International Board for Plant Genetic Resources]. (1983). Safflower descriptors. Plant Genetic Resources Newsletter (IBPGR/FAO).

Machado, C. D. F., Jesus, F. N. D., & Ledo, C. A. D. S. (2015). Divergência genética de acessos de maracujá utilizando descritores quantitativos e qualitativos. Revista Brasileira de Fruticultura, 37, 442-449.

MAPA-Ministério da Agricultura, Pecuária e Abastecimento. (2013). Instruções para execução dos ensaios de distinguibilidade, homogeneidade e estabilidade de cultivares de cártamo (Carthamus tinctorius L.). http://www.agricultura.gov.br/assuntos/insumos-agropecuarios/insumos agricolas/protecao-de-cultivar/arquivos agricolas/formulario_cartamo_jan13p.doc.

Moura, M. D. C. C., Gonçalves, L. S., Sudré, C. P., Rodrigues, R., do Amaral Júnior, A. T., & Pereira, T. N. (2010). Algoritmo de Gower na estimativa da divergência genética em germoplasma de pimenta. Horticultura Brasileira, 28, 155-161.

Nahak, S. C., Nandi, A., Sahu, G. S., Tripathy, P., Dash, S. K., Patnaik, A., & Pradhan, S. R.(2018). Studies on variability, heritability and genetic advance for yield and yield contributing characters in chilli (Capsicum annuum L.). J. Pharma. Phytochem, 7(1), 2506–2510.

Oliveira, C. V. K. D. (2016). Análise do cártamo como cultura enérgica.

Pandey, M. K., Pandey, A. K., Kumar, R., Nwosu, C. V., Guo, B., Wright, G. C., Bhat, R. S., Chen, X., Bera, S. K., & Yuan, M.(2020). Translational genomics for achieving higher genetic gains in groundnut. Theoretical and Applied Genetics, 133(5), 1679–1702.

Perini, L. J., Zeffa, D. M., Freiria, G. H., Novais, P. S., & Prete, C. E. C. (2018). Diversidade genética entre acessos de soja tipo alimento com base no algoritmo de Gower. In Colloquium Agrariae. ISSN: 1809-8215 (Vol. 14, No. 4, pp. 47-57).

Queiroga, V. P., Girão, E. G., Albuquerque, E. M. B. (2020) Cártamo (Carthamus tinctorius L.) tecnologias de plantio e utilização. Ed. A Barriguda.

Queiroz, D. C. (2016). Avaliação de progênies de meio-irmãos e identificação de clones promissores de pinhão-manso por meio de caracteres morfoagronômicos e moleculares.

Quintal, S. S. R., Viana, A. P., Gonçalves, L. S. A., Pereira, M. G., & do Amaral Júnior, A. T. (2012). Divergência genética entre acessos de mamoeiro por meio de variáveis morfoagronômicas. Semina: Ciências Agrárias, 33(1), 131-142.

RAO, C. R. Advanced statistical methods in biometric research. New York: John Wiley & Sons; 1952. 390p.

Santos, D. B. D. (2013). Procedimentos multivariados no agrupamento de genótipos de maracujazeiro com base em matriz de distância conjunta e em separado para características quantitativas e categóricas.

Sehgal, D., & Raina, S. N. (2005). Genotyping safflower (Carthamus tinctorius L.) cultivars by DNA fingerprints. Euphytica, 146(1), 67-76.

Vaz Patto, M. C., Satovic, Z., Pêgo, S., & Fevereiro, P. (2004). Assessing the genetic diversity of Portuguese maize germplasm using microsatellite markers. Euphytica, 137(1), 63-72.

Vilela, F. O., Amaral Júnior, A. T. D., Pereira, M. G., Scapim, C. A., Viana, A. P., & Freitas Júnior, S. D. P. (2008). Effect of recurrent selection on the genetic variability of the UNB-2U popcorn population using RAPD markers. Acta Scientiarum. Agronomy, 30, 25-30.

Downloads

Published

08/06/2022

How to Cite

LIRA, J. P. E.; SANTOS, A. A. C. dos; OLIVEIRA, A. J. de; OLIVEIRA, E. P. de; GALBIATI, C.; POLETINE, J. P.; NEVES, L. G.; BARELLI, M. A. A. . Use of the Gower algorithm in determining genetic divergence among genotypes of Carthamus tinctorius L. Research, Society and Development, [S. l.], v. 11, n. 8, p. e6011830044, 2022. DOI: 10.33448/rsd-v11i8.30044. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/30044. Acesso em: 20 apr. 2024.

Issue

Vol. 11 No. 8

Section

Agrarian and Biological Sciences

License

Copyright (c) 2022 João Paulo Egues Lira; Andressa Alves Cabreira dos Santos; Altacis Junior de Oliveira; Emerson Palermo de Oliveira; Carla Galbiati; Juliana Parisotto Poletine; Leonarda Grilo Neves; Marco Antonio Aparecido Barelli

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with this journal agree to the following terms:

1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

2) Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

3) Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.