Assessment of agronomic performance and prediction of genetic gains through selection indices in silage corn
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.21475/ajcs.18.12.05.PNE1004 http://hdl.handle.net/11449/221081 |
Resumo: | During the dry season, the production of pastures is decreased, making farmers necessary to use corn silage as roughage source. Maize is increasingly recommended as the most important silage crop due to their qualitative and quantitative traits on top of the great acceptance for most animals. This work aimed to evaluate, through selection indices, the agronomic performance and prediction of genetic gains in corn hybrids for silage production. Eight topcross hybrids and seven controls were assessed in randomized blocks with six replications in two environments, in the municipalities of Campos dos Goytacazes and Itaocara - RJ, respectively, in the 2015/2016 agricultural year. The following agronomic traits were assessed: plant height (PH), height of first ear insertion (TH), stem diameter (CD), number of ears (NT), yield of ear with straw and ready for silage (TPS); yield of ear without straw and ready for silage (TPWS); yield of grain ready for silage (GY); ratio of grains in the fresh weight (GFM) and fresh weight vield (FMY). The selection indices of Smith & Hazel, Willians, Pesek & Baker and Mulamba & Mock were used for gain prediction. The results showed that Mulamba & Mock provided the highest predictive values in the estimation of gains for the selection of hybrids. The topcross hybrids UENF-2205, UENF-2208, UENF-2209 and UENF-2210 presented the best performance and indicated high potential of TPWS, GY and GFM for silage production in the Northern and Northwestern Rio de Janeiro state. |
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Assessment of agronomic performance and prediction of genetic gains through selection indices in silage cornHybridsProductionTesterTopcrossesZea mays L.During the dry season, the production of pastures is decreased, making farmers necessary to use corn silage as roughage source. Maize is increasingly recommended as the most important silage crop due to their qualitative and quantitative traits on top of the great acceptance for most animals. This work aimed to evaluate, through selection indices, the agronomic performance and prediction of genetic gains in corn hybrids for silage production. Eight topcross hybrids and seven controls were assessed in randomized blocks with six replications in two environments, in the municipalities of Campos dos Goytacazes and Itaocara - RJ, respectively, in the 2015/2016 agricultural year. The following agronomic traits were assessed: plant height (PH), height of first ear insertion (TH), stem diameter (CD), number of ears (NT), yield of ear with straw and ready for silage (TPS); yield of ear without straw and ready for silage (TPWS); yield of grain ready for silage (GY); ratio of grains in the fresh weight (GFM) and fresh weight vield (FMY). The selection indices of Smith & Hazel, Willians, Pesek & Baker and Mulamba & Mock were used for gain prediction. The results showed that Mulamba & Mock provided the highest predictive values in the estimation of gains for the selection of hybrids. The topcross hybrids UENF-2205, UENF-2208, UENF-2209 and UENF-2210 presented the best performance and indicated high potential of TPWS, GY and GFM for silage production in the Northern and Northwestern Rio de Janeiro state.Universidade Estadual do Norte Fluminense Darcy Ribeiro, Avenida Alberto Lamego 2000 Parque CalifórniaUniversidade Estadual Paulista Júlio de Mesquita Filho Faculdade de Ciências Agrárias e Veterinárias de Jaboticabal, Via de Acesso Prof. Paulo Donato Castellane s/nUniversidade Estadual Paulista Júlio de Mesquita Filho Faculdade de Ciências Agrárias e Veterinárias de Jaboticabal, Via de Acesso Prof. Paulo Donato Castellane s/nUniversidade Estadual do Norte Fluminense Darcy RibeiroUniversidade Estadual Paulista (UNESP)Crevelari, Jocarla AmbrosimDurães, Nayara Norrene LacerdaBendia, Laila Cecília Ramosda Silva, Alysson Jalles [UNESP]Azevedo, Flávio Henrique VidalAzeredo, Valdinei CruzPereira, Messias Gonzaga2022-04-28T19:08:56Z2022-04-28T19:08:56Z2018-05-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article800-807http://dx.doi.org/10.21475/ajcs.18.12.05.PNE1004Australian Journal of Crop Science, v. 12, n. 5, p. 800-807, 2018.1835-27071835-2693http://hdl.handle.net/11449/22108110.21475/ajcs.18.12.05.PNE10042-s2.0-85047376891Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAustralian Journal of Crop Scienceinfo:eu-repo/semantics/openAccess2022-04-28T19:08:56Zoai:repositorio.unesp.br:11449/221081Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:51:04.086528Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Assessment of agronomic performance and prediction of genetic gains through selection indices in silage corn |
title |
Assessment of agronomic performance and prediction of genetic gains through selection indices in silage corn |
spellingShingle |
Assessment of agronomic performance and prediction of genetic gains through selection indices in silage corn Crevelari, Jocarla Ambrosim Hybrids Production Tester Topcrosses Zea mays L. |
title_short |
Assessment of agronomic performance and prediction of genetic gains through selection indices in silage corn |
title_full |
Assessment of agronomic performance and prediction of genetic gains through selection indices in silage corn |
title_fullStr |
Assessment of agronomic performance and prediction of genetic gains through selection indices in silage corn |
title_full_unstemmed |
Assessment of agronomic performance and prediction of genetic gains through selection indices in silage corn |
title_sort |
Assessment of agronomic performance and prediction of genetic gains through selection indices in silage corn |
author |
Crevelari, Jocarla Ambrosim |
author_facet |
Crevelari, Jocarla Ambrosim Durães, Nayara Norrene Lacerda Bendia, Laila Cecília Ramos da Silva, Alysson Jalles [UNESP] Azevedo, Flávio Henrique Vidal Azeredo, Valdinei Cruz Pereira, Messias Gonzaga |
author_role |
author |
author2 |
Durães, Nayara Norrene Lacerda Bendia, Laila Cecília Ramos da Silva, Alysson Jalles [UNESP] Azevedo, Flávio Henrique Vidal Azeredo, Valdinei Cruz Pereira, Messias Gonzaga |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual do Norte Fluminense Darcy Ribeiro Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Crevelari, Jocarla Ambrosim Durães, Nayara Norrene Lacerda Bendia, Laila Cecília Ramos da Silva, Alysson Jalles [UNESP] Azevedo, Flávio Henrique Vidal Azeredo, Valdinei Cruz Pereira, Messias Gonzaga |
dc.subject.por.fl_str_mv |
Hybrids Production Tester Topcrosses Zea mays L. |
topic |
Hybrids Production Tester Topcrosses Zea mays L. |
description |
During the dry season, the production of pastures is decreased, making farmers necessary to use corn silage as roughage source. Maize is increasingly recommended as the most important silage crop due to their qualitative and quantitative traits on top of the great acceptance for most animals. This work aimed to evaluate, through selection indices, the agronomic performance and prediction of genetic gains in corn hybrids for silage production. Eight topcross hybrids and seven controls were assessed in randomized blocks with six replications in two environments, in the municipalities of Campos dos Goytacazes and Itaocara - RJ, respectively, in the 2015/2016 agricultural year. The following agronomic traits were assessed: plant height (PH), height of first ear insertion (TH), stem diameter (CD), number of ears (NT), yield of ear with straw and ready for silage (TPS); yield of ear without straw and ready for silage (TPWS); yield of grain ready for silage (GY); ratio of grains in the fresh weight (GFM) and fresh weight vield (FMY). The selection indices of Smith & Hazel, Willians, Pesek & Baker and Mulamba & Mock were used for gain prediction. The results showed that Mulamba & Mock provided the highest predictive values in the estimation of gains for the selection of hybrids. The topcross hybrids UENF-2205, UENF-2208, UENF-2209 and UENF-2210 presented the best performance and indicated high potential of TPWS, GY and GFM for silage production in the Northern and Northwestern Rio de Janeiro state. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-05-01 2022-04-28T19:08:56Z 2022-04-28T19:08:56Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.21475/ajcs.18.12.05.PNE1004 Australian Journal of Crop Science, v. 12, n. 5, p. 800-807, 2018. 1835-2707 1835-2693 http://hdl.handle.net/11449/221081 10.21475/ajcs.18.12.05.PNE1004 2-s2.0-85047376891 |
url |
http://dx.doi.org/10.21475/ajcs.18.12.05.PNE1004 http://hdl.handle.net/11449/221081 |
identifier_str_mv |
Australian Journal of Crop Science, v. 12, n. 5, p. 800-807, 2018. 1835-2707 1835-2693 10.21475/ajcs.18.12.05.PNE1004 2-s2.0-85047376891 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Australian Journal of Crop Science |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
800-807 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129558663135232 |