Mixed modeling for fiber yield genetic selection in sugarcane

Autores/as

  • João de Andrade Dutra Filho Federal University of Pernambuco. Vitoria Academic Center/ Biological Science Nucleus. Rua Alto do Reservatório. S/n Bela Vista. CEP: 55608-680. Vitória de Santo Antão. Pernambuco. Brazil. https://orcid.org/0000-0002-9515-7267
  • Lauter Silva Souto Federal University of Campina Grande. Agri-Food Science and Technology Center. Rua Jairo Vieira Feitosa. 1770. Pereiros. CEP: 58840-000. Pombal. Paraiba. Brazil.
  • Rômulo Gil de Luna Federal University of Campina Grande. Agri-Food Science and Technology Center. Rua Jairo Vieira Feitosa. 1770. Pereiros. CEP: 58840-000. Pombal. Paraiba. Brazil.
  • Anielson dos Santos Souza Federal University of Campina Grande. Agri-Food Science and Technology Center. Rua Jairo Vieira Feitosa. 1770. Pereiros. CEP: 58840-000. Pombal. Paraiba. Brazil. https://orcid.org/0000-0003-0145-0989
  • Frank Gomes Silva Federal Rural University of Pernambuco. Department of Statistics and Informatics. Rua Dom Manuel de Medeiros. s/n Dois Irmãos. CEP: 52171-900. Recife. Pernambuco. Brazil. https://orcid.org/0000-0002-3481-3099
  • Fabiana Aparecida Cavalcanti Silva Phytosanitary Diagnosis Laboratory. Northeast Strategic Technologies Center. Avenida Professor Luís Freire. Cidade Universitária. Recife 50740-545. Pernambuco. Brazil. https://orcid.org/0000-0002-4674-895X
  • Djalma Euzébio Simões Neto Federal Rural University of Pernambuco. Carpina Sugarcane Experimental Station, Rua Ângela Cristina Canto Pessoa de Luna. S/n. Centro. CEP: 55810-700. Carpina. Pernambuco. Brazil.
  • Tercilio Calsa Júnior Federal University of Pernambuco. Department of Genetics. Avenida Professor Moraes Rego. 1235. Cidade Universitária. CEP: 50670-901. Recife. Pernambuco. Brazil. https://orcid.org/0000-0002-8302-2031

DOI:

https://doi.org/10.48162/rev.39.034

Palabras clave:

biomassa, bioenergía, bioelectricidad, Saccharum spp., REML/BLUP

Resumen

The current demand for clean and renewable energy has provoked considerable changes in the production system of agroindustrial companies. The generation of bioelectricity through the burning of sugarcane bagasse has considerably risen in the recent years. This work aimed to focus on the sugarcane genotypes selection for fiber productivity. The experiment was outlined in randomized blocks with four repetitions, and sixteen genotypes were evaluated. The evaluated traits  were: cane tons per hectare, sucrose tons per hectare, fiber tons per hectare, fiber content and apparent sucrose content. To the selection, the mixed linear models methodology was used. The heritability coefficients suggest a significant genetic gain and the harmonic means of relative performances of predicted genotypic values allowed the identification of stable genotypes related to the traits evaluated in four harvest cycles. Considering the current average demand of sugarcane agroindustry for varieties with fiber content between 12% and 17% and sucrose content near 13%, for energy generation and sugar production, the genotypes EECAC 06, EECAC 03, EECAC 04 and EECAC 07 are presented as commercial cultivation options.

Highlights

- Mixed models constitute an efficient tool for sugarcane selection focused onto fiber and sucrose production.

- This methodology provides significant genetic gains based on predicted genetic values free from interaction with harvest cycles.

- The evaluated genotypes present high fiber and sucrose productivity, genotypic adaptability and stability throughout harvest cycles, indicating longevity in the sugarcane crop.

Descargas

Publicado

01-12-2021

Cómo citar

Dutra Filho, J. de A., Souto, L. S., de Luna, R. G., Souza, A. dos S., Silva, F. G., Silva, F. A. C. ., Simões Neto, D. E., & Calsa Júnior, T. (2021). Mixed modeling for fiber yield genetic selection in sugarcane. Revista De La Facultad De Ciencias Agrarias UNCuyo, 53(2), 11–19. https://doi.org/10.48162/rev.39.034

Número

Sección

Genética y mejoramiento vegetal

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