Genetic divergence and truncation and simultaneous selection in inbred families (S


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
01 Aug 2024
Historique:
received: 26 02 2024
accepted: 24 07 2024
medline: 2 8 2024
pubmed: 2 8 2024
entrez: 1 8 2024
Statut: epublish

Résumé

The State University of North Fluminense Darcy Ribeiro (UENF) has been developing for fifteen years a breeding program that aims at the development of new cultivars of elephant grass due to its high potential and the low availability of cultivars developed by genetic breeding programs that meet the needs of producers in the State of Rio de Janeiro. In this sense, inbred families were also obtained as a way of fixing potential alleles for traits related to production, as the inbreeding process apparently does not strongly affect elephant grass in aspects related to inbreeding depression. This study aimed to estimate genetic diversity, variance components and prediction of genotypic values in 11 (S

Identifiants

pubmed: 39090204
doi: 10.1038/s41598-024-68466-9
pii: 10.1038/s41598-024-68466-9
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

17850

Informations de copyright

© 2024. The Author(s).

Références

Paterlini, E. M. et al. Evaluation of elephant grass for energy use. J. Biotechnol. Biodivers. 4, 119–125 (2013).
da Alves, F. G. S., Silva, S. F., de Santos, F. N. S. & de Carneiro, M. S. S. Elephant grass: A bioenergetic resource. Nucl. Anim. 10, 117–130. https://doi.org/10.3738/21751463.3032 (2018).
doi: 10.3738/21751463.3032
Fontoura, C. F., Brandão, L. E. & Gomes, L. L. Elephant grass biorefineries: Towards a cleaner Brazilian energy matrix?. J. Clean. Prod. 96, 85–93. https://doi.org/10.1016/j.jclepro.2014.02.062 (2015).
doi: 10.1016/j.jclepro.2014.02.062
Ambrósio, M. et al. Adaptability and stability via mixed models in elephantgrass (Cenchrus purpureus (Schumach.) Morrone) varieties for energy purposes. Bragantia 82, e20230150 (2023).
doi: 10.1590/1678-4499.20230150
de Sant’Ana, J. A. A. et al. Nitrogen and phosphate fertilizers in elephant-grass for energy use. Afr. J. Agric. Res. 13, 806–813. https://doi.org/10.5897/ajar2016.11913 (2018).
doi: 10.5897/ajar2016.11913
Pereira, A. V., Ledo, F. J. S., Morenz, M. J. F., Leite, J. L. B., Santos, A. M. B., Martins, C. E. & Machado, J. C. BRS Capiaçu: cultivar de capim-elefante de alto rendimento para produção de silagem. Embrapa Gado de Leite-Comunicado Técnico (INFOTECA-E), (2016).
Pereira, A. V., Auad, A. M., Dos Santos, A. M. B., Mittelmann, A., Gomide, C. A. De M., Martins, C. E., Paciullo, D. S. C., Lédo, F. J. S. & Oliveira, J. S. BRS CAPIAÇU E BRS KURUMI: cultivo e uso. Brasília, DF:Embrapa, 116 p. (2021).
Woodard, K. R. & Sollenberger, L. E. Production of biofuel crops in Florida: Elephant grass SS-AGR-297, Agronomy Department, University of Florida UF)/Institute of Food and Agricultural Sciences (IFAS) Extension, Gainesville, Florida, USA (2015). Available at: https://edis.ifas.ufl.edu/ag302
Silva, V. B., Daher, R. F. & de Souza, Y. P. Assessment of energy production in full-sibling families of elephant grass by mixed models. Renew. Energy 146, 744–749. https://doi.org/10.1016/j.renene.2019.06.152 (2020).
doi: 10.1016/j.renene.2019.06.152
Gravina, L. M. et al. Multivariate analysis in the selection of elephant grass genotypes for biomass production. Renew. Energy 160, 1265–1268. https://doi.org/10.1016/j.renene.2020.06.094 (2020).
doi: 10.1016/j.renene.2020.06.094
Daher, R. F. et al. Use of elephant grass for energy production in Campos dos Goytacazes-RJ, Brazil. Genet. Mol. Res. 13, 10898–10908. https://doi.org/10.4238/2014 (2014).
doi: 10.4238/2014 pubmed: 25526210
Mapa-Ministério da Agricultura, Pecuária e Abastecimento. 2021. Disponível em: . Acesso em: 10 nov. 2022.
Silva, V. B. et al. Selection among and within full-sib families of elephant grass for energy purposes. Crop Breed. Appl. Biotechnol. 18, 89–96. https://doi.org/10.1590/1984-70332018v18n1a12 (2018).
doi: 10.1590/1984-70332018v18n1a12
Vidal, A. K. F. et al. Simultaneous selection for yield, adaptability and stability and repeatability coefficient in full-sib families of elephant grass for energy purposes via mixed models. Euphytica https://doi.org/10.1007/s10681-022-03092-y (2022).
doi: 10.1007/s10681-022-03092-y
Vidal, A. K. F. et al. Estimation of repeatability and genotypic superiority of elephant grass half-sib families for energy purposes using mixed models. Sci. Agric. 80, 1–10. https://doi.org/10.1590/1678-992x-2022-0103 (2023).
doi: 10.1590/1678-992x-2022-0103
Rodrigues, E. V. et al. Selecting elephant grass families and progenies to produce bioenergy through mixed models (REML/BLUP). Gene. Mol.. Res. https://doi.org/10.4238/gmr16029301 (2017).
doi: 10.4238/gmr16029301
Ambrósio, M. et al. Genotypic superiority of Psidium guajava S
doi: 10.1590/1678-992X-2019-0179
Ambrósio, M., Pio Viana, A. & Pureza da Cruz, D. Categories of variables in analysis of genetic diversity in S1 progenies of Psidium guajava. Sci. Rep. 12, 1–13. https://doi.org/10.1038/s41598-022-26950-0 (2022).
doi: 10.1038/s41598-022-26950-0
Ambrósio, M. et al. Coefficient of repeatability, stability, and adaptability estimates for Psidium guajava S1 progenies via mixed models. Revista Brasileira de Fruticultura 45, 1–15. https://doi.org/10.1590/0100-29452023502 (2023).
doi: 10.1590/0100-29452023502
Resende, M. A. V., de Freitas, J. A., Lanza, M. A., de Resende, M. D. V. & Azevedo, C. F. Divergência genética e índice de seleção via BLUP em acessos de algodoeiro para características tecnológicas da fibra. Pesquisa Agropecuária Tropical 44, 334–340. https://doi.org/10.1590/S1983-40632014000300006 (2014).
doi: 10.1590/S1983-40632014000300006
Viana, A. P. & Resende, M. D. V. Genética quantitativa no melhoramento de fruteiras 1st edn, 296p (Interciencia, 2014).
Resende, M. D. & Alves, R. S. Linear, generalized, hierarchical, Bayesian and random regression mixed models in genetics/ genomics in plant breeding. Funct. Plant Breed. J. https://doi.org/10.35418/2526-4117/v2n2a1 (2020).
doi: 10.35418/2526-4117/v2n2a1
Gonçalves, G. M., Viana, A. P., Amaral Junior, A. T. D. & Resende, M. D. V. D. Breeding new sugarcane clones by mixed models under genotype by environmental interaction. Sci. Agric. 71, 66–71. https://doi.org/10.1590/S0103-90162014000100009 (2014).
doi: 10.1590/S0103-90162014000100009
Vivas, M. et al. Efficiency of circulant diallels via mixed models in the selection of papaya genotypes resistant to foliar fungal diseases. Genet. Mol. Res 13, 4797–4804. https://doi.org/10.4238/2014.July.2.9 (2014).
doi: 10.4238/2014.July.2.9 pubmed: 25062415
Ferreira, F. M. et al. Optimal harvest number and genotypic evaluation of total dry biomass, stability, and adaptability of elephant grass clones for bioenergy purposes. Biomass Bioenergy 149, 106104. https://doi.org/10.1016/j.biombioe.2021.106104 (2021).
doi: 10.1016/j.biombioe.2021.106104
Cruz, C. D., Carneiro, P. C. S., Regazzi, A. J. Modelos biométricos aplicados ao melhoramento genético. v.2, 3ª. ed. Viçosa: UFV, 2014. 668p
Dalbosco, E. Z. et al. Parametric and non-parametric indexes applied in the selection of sour passion fruit progenies. Revista Brasileira de Fruticultura 40, 282. https://doi.org/10.1590/0100-29452018282 (2018).
doi: 10.1590/0100-29452018282
Francis, G., Oliver, J. & Mulpuri, J. High yielding and trait specific genotypes and genetic associations among yield and yield contributing traits in Jatropha curcas L.. Agrofor. Syst. 92, 1417–1436. https://doi.org/10.1007/s10457-017-0089-2 (2017).
doi: 10.1007/s10457-017-0089-2
Alves, R. S. et al. Multiple-trait BLUP in longitudinal data analysis on Jatropha curcas breeding for bioenergy. Ind. Crops Prod. 130, 558–561. https://doi.org/10.1016/j.indcrop.2018.12.019 (2019).
doi: 10.1016/j.indcrop.2018.12.019
Ayizannon, R. G., Ahoton, L. E., Ezin, V., Quenum, F. & Mergeai, G. Improvement of physic nut (Jatropha Curcas L.) by intraspecific hybridization between ecotypes of Africa and Americana. J. Plant Breed. Crop Sci. 9, 54–62. https://doi.org/10.5897/JPBCS2016.0620 (2017).
doi: 10.5897/JPBCS2016.0620
Santos, H. G., Jacomine, P. K. T., Anjos, L. H. C., Oliveira, V. Á., Lumbreras, J. F., Coelho, M. R., Almeida, J. Á., Cunha, T. J. F., Oliveira, J. B., Brasília, D. F. (2013) (Eds.), Brazilian System of Soil Classification, vol. 3, p. 353.
Silva, V. Q. R. R. F., de Damer, G., da Amaral Gravina, F. J., Silva Ledo, F. D. & Tardin, M. C. Souza combining ability of elephant grass based on morphological characteristics Bol. Ind. Anim. 71, 63–70. https://doi.org/10.17523/bia.v71n1p63 (2011).
doi: 10.17523/bia.v71n1p63
Passos, L. P., Machado, M. A. & Vidigal, M. C. Campos molecular characterization of elephant-grass accessions through RAPD markers Cienc. E Agrotecnol. 29, 568–574. https://doi.org/10.1590/S1413-70542005000300009 (2005).
doi: 10.1590/S1413-70542005000300009
Freire, L. R., Balieiro, F. D. C., Zonta, E., Anjos, L. D., Pereira, M. G., Lima, E. & Polidoro J. C. Manual of liming and fertilization of the state of Rio de Janeiro. o. Embrapa; Seropédica Editora: Universidade Rural. 430p (2017).
Menezes, B. R. F. et al. Selection of elephant grass genotypes (Pennisetum purpureum) using the REML/BLUP methodology. Rev. Ciencias Agrar. 39, 360–365. https://doi.org/10.19084/RCA15073 (2016).
doi: 10.19084/RCA15073
Resende, M. D. V. Genética Biométrica e Estatística no Melhoramento de Plantas Perenes. Embrapa. p. 975 (2009).
R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
Mojena, R. Hierárquical grouping method and stopping rules: An evaluation. Comput. J. 110(20), 359–363 (1977).
doi: 10.1093/comjnl/20.4.359
Borém, A., Miranda, G. V., Fritsche-Neto, R. Plant breeding: Melhoramento de Plantas. 7 ed. UFV, Viçosa, MG, Brazil (2017).
Carvalho, L. P. F., Farias, J. C., Morello, C. L. & Teodoro, P. E. Uso da metodologia REML/BLUP para seleção de genótipos de algodoeiro com maior adaptabilidade e estabilidade produtiva. Bragantia 75, 314–321. https://doi.org/10.1590/1678-4499.275 (2016).
doi: 10.1590/1678-4499.275
Falconer, D. S. & Mackay, T. F. C. Introduction to quantitative genetics. 4 ed. Longman Group Limited, Edinburgh, 464p (1996).
Resende, M. D. V. Genética biométrica e estatística no melhoramento de plantas perenes. Embrapa Informação Tecnológica, Brasília, p. 975 (2002).
Morais, R. F. et al. Contribuition of biological nitrogen fixation to Elephant grass (Pennisetum purpureum Schum.). Plant Soil 356, 23–24. https://doi.org/10.1007/s11104-011-0944-2 (2012).
doi: 10.1007/s11104-011-0944-2
Pimentel, A. J. B. et al. Estimação de parâmetros genéticos e predição de valor genético aditivo de trigo utilizando modelos mistos. Pesquisa Agropecuária Brasileira 49, 882–890. https://doi.org/10.1590/S0100-204X2014001100007 (2014).
doi: 10.1590/S0100-204X2014001100007
Torres Filho, J. et al. Genotype by environment interaction in green cowpea analyzed via mixed models. Revista Caatinga 30, 687–697. https://doi.org/10.1590/1983-21252017v30n317rc (2017).
doi: 10.1590/1983-21252017v30n317rc
da Baldissera, J. N. C. et al. Uso do melhor preditor linear não viesado (BLUP) na predição de híbridos em feijão. Biosci. J. 28, 395–403 (2012).
Silva, F. H. L. et al. Prediction of genetic gains by selection indexes and REML/BLUP methodology in a population of sour passion fruit under recurrent selection. Acta Scientiarum 39, 183–190. https://doi.org/10.4025/actasciagron.v39i2.32554 (2017).
doi: 10.4025/actasciagron.v39i2.32554
Neiva, R. Nova cultivar de capim-elefante apresenta produtividade 30% maior. Embrapa, (2016). Disponível em: < https://www.embrapa.br/busca-de-noticias/-/noticia/17002039/nova-cultivar-de-capim-elefante-apresenta-produtividade-30-maior >. Acesso, (2021).
Quesada, D. M. et al. Parâmetros Qualitativos de Genótipos de Capim-elefante (Pennisetum purpureum Schum.) estudados para a produção de energia através da Biomassa. Seropédica: Embrapa Agrobiologia. 2004. 4p. (Embrapa Agrobiologia. Circular Técnica 8).
Cunha, M. V. et al. Association between the morphological and productive characteristics in the selection of elephant Grass genotype. Revista Brasileira de Zootecnia 40, 482–488 (2011).
doi: 10.1590/S1516-35982011000300004
Hodgson, J. Grazing Management: Science into Practice 203–208 (Longman Scientific and Technical, Essex, 1990).
Oliveira, A. V. et al. Avaliação do desenvolvimento de 73 genótipos de capim-elefante em campos dos goytacazes–RJ. Boletim de Indústria Animal 70, 119–131. https://doi.org/10.17523/bia.v70n2p119 (2013).
doi: 10.17523/bia.v70n2p119
Mello, A. C. L., Lira, M. A., Dubeux Júnior, J. C. B., Santos, M. V. F. & Freitas, E. V. Caracterização e seleção de clones de capim elefante (Pennisetum purpureum Schum.) na Zona da Mata de Pernambuco. Revista Brasileira de Zootecnia 31, 30–42. https://doi.org/10.1590/S1516-35982002000100004 (2002).
doi: 10.1590/S1516-35982002000100004
Zhang, L., Xu, C. & Champagne, P. Overview of recente advances in thermo-chemical conversion of biomass. Energy Convers. Manag. 51, 969–982. https://doi.org/10.1016/j.enconman.2009.11.038 (2010).
doi: 10.1016/j.enconman.2009.11.038
Meehan, P., Mc Donnell, K., Grant, J. & Finnan, J. The effect of harvest time and pre harvest treatment on the moisture content of Miscanthus × giganteus. Eur. J. Agron. 56, 37–44. https://doi.org/10.1016/j.eja.2014.03.003 (2014).
doi: 10.1016/j.eja.2014.03.003
Mckendry, P. Energy production from biomass (Part 1): Overview of biomass. Bioresour. Technol. 83, 37–46 (2002).
doi: 10.1016/S0960-8524(01)00118-3 pubmed: 12058829
Lédo, F. J. S. & Machado, J. C. Construindo um ideótipo de gramínea para produção de energia. In Construção de ideótipos de gramíneas para usos diversos (eds Souza, F. H. D. et al.) 227–236 (Embrapa, 2013).
Santos, M. E. R., Fonseca, D. M. & Gomes, V. M. Estádio de desenvolvimento e características morfológicas de lâminas foliares e de perfilhos de capim-braquiária sob lotação contínua. Boletim de Indústria Animal 66, 95–105 (2009).
Silva, V. et al. Capacidade combinatória de capim elefante com base em caracteres morfoagronômicos. Boletim de Indústria Animal 71, 63–70. https://doi.org/10.17523/bia.v71n1p63 (2014).
doi: 10.17523/bia.v71n1p63
Simeão, R. M., Assis, G. M. L., Montagner, D. B. & Ferreira, R. C. U. Forage peanut (Arachis spp.) genetic evaluation and selection. Grass Forage Sci. 72, 322–332. https://doi.org/10.1111/gfs.12242 (2017).
doi: 10.1111/gfs.12242
Shimoya, A., Cruz, C. D., Ferreira, R. P., Pereira, V. A. & Carneiro, P. C. S. Divergência genética entre acessos de um banco de germoplasma de capim-elefante. Pesquisa Agropecuária Brasileira 37, 971–980 (2002).
doi: 10.1590/S0100-204X2002000700011
da Negreiros, J. R. S., Alexandre, R. S., de Álvares, V. S., Bruckner, C. H. & Cruz, C. D. Divergência genética entre progênies de maracujazeiro-amarelo com base em características das plântulas. Revista Brasileira de Fruticultura 30, 197–201 (2008).
doi: 10.1590/S0100-29452008000100036
Oliveira, V. D., Rabbani, A. R. C., Silva, A. V. C. D. & Lédo, A. D. S. Genetic variability in physic nuts cultivated in Northeastern Brazil. Ciência Rural 43, 978–984. https://doi.org/10.1590/S0103-84782013005000060 (2014).
doi: 10.1590/S0103-84782013005000060
Carvalho, F. I. F., Lorencetti, C. & Benin, G. in Estimativas e implicações da correlação no melhoramento vegetal, 142 (UFPel, Pelotas, 2004)

Auteurs

Moisés Ambrósio (M)

Center for Agricultural Sciences and Technologies, State University of North Fluminense Darcy Ribeiro, Avenida Alberto Lamego, 2000, Parque Califórnia, Campos dos Goytacazes, RJ, 28013-602, Brazil. ambrosio_20007@hotmail.com.

Rogério Figueiredo Daher (RF)

Center for Agricultural Sciences and Technologies, State University of North Fluminense Darcy Ribeiro, Avenida Alberto Lamego, 2000, Parque Califórnia, Campos dos Goytacazes, RJ, 28013-602, Brazil.

Josefa Grasiela Silva Santana (JG)

Center for Agricultural Sciences and Technologies, State University of North Fluminense Darcy Ribeiro, Avenida Alberto Lamego, 2000, Parque Califórnia, Campos dos Goytacazes, RJ, 28013-602, Brazil.

Cleudiane Lopes Leite (CL)

Center for Agricultural Sciences and Technologies, State University of North Fluminense Darcy Ribeiro, Avenida Alberto Lamego, 2000, Parque Califórnia, Campos dos Goytacazes, RJ, 28013-602, Brazil.

Joao Victor Bousquet Duarte (JVB)

Center for Agricultural Sciences and Technologies, State University of North Fluminense Darcy Ribeiro, Avenida Alberto Lamego, 2000, Parque Califórnia, Campos dos Goytacazes, RJ, 28013-602, Brazil.

Ana Kesia Faria Vidal (AKF)

Center for Agricultural Sciences and Technologies, State University of North Fluminense Darcy Ribeiro, Avenida Alberto Lamego, 2000, Parque Califórnia, Campos dos Goytacazes, RJ, 28013-602, Brazil.

Maxwel Rodrigues Nascimento (MR)

Center for Agricultural Sciences and Technologies, State University of North Fluminense Darcy Ribeiro, Avenida Alberto Lamego, 2000, Parque Califórnia, Campos dos Goytacazes, RJ, 28013-602, Brazil.

Alexandre Gomes de Souza (AG)

Center for Agricultural Sciences and Technologies, State University of North Fluminense Darcy Ribeiro, Avenida Alberto Lamego, 2000, Parque Califórnia, Campos dos Goytacazes, RJ, 28013-602, Brazil.

Rafael Souza Freitas (RS)

Center for Agricultural Sciences and Technologies, State University of North Fluminense Darcy Ribeiro, Avenida Alberto Lamego, 2000, Parque Califórnia, Campos dos Goytacazes, RJ, 28013-602, Brazil.

Wanessa Francesconi Stida (WF)

Center for Agricultural Sciences and Technologies, State University of North Fluminense Darcy Ribeiro, Avenida Alberto Lamego, 2000, Parque Califórnia, Campos dos Goytacazes, RJ, 28013-602, Brazil.

João Esdras Calaça Farias (JEC)

Center for Agricultural Sciences and Technologies, State University of North Fluminense Darcy Ribeiro, Avenida Alberto Lamego, 2000, Parque Califórnia, Campos dos Goytacazes, RJ, 28013-602, Brazil.

Raiane Mariani Santos (RM)

Center for Agricultural Sciences and Technologies, State University of North Fluminense Darcy Ribeiro, Avenida Alberto Lamego, 2000, Parque Califórnia, Campos dos Goytacazes, RJ, 28013-602, Brazil.

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