Registro Completo
Biblioteca(s): |
Embrapa Milho e Sorgo. |
Data corrente: |
05/01/2022 |
Data da última atualização: |
05/01/2022 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 2 |
Autoria: |
MELO, M. L. A. de; CAMILO, J. A.; ANDRADE, C. de L. T. de; AMARAL, T. A.; SOUZA, I. R. P. de; SIMEÃO, R. M. |
Afiliação: |
MARINA LUCIANA ABREU DE MELO, Escola Superior de Agricultura “Luiz de Queiroz”; JENNIFER ALVES CAMILO, Universidade Federal de São João del-Rei; CAMILO DE LELIS TEIXEIRA DE ANDRADE, CNPMS; TALES ANTÔNIO AMARAL; ISABEL REGINA PRAZERES DE SOUZA, CNPMS; ROSANGELA MARIA SIMEAO, CNPGC. |
Título: |
Sowing period and estimated maize production for silage under tropical conditions. |
Ano de publicação: |
2021 |
Fonte/Imprenta: |
Revista Brasileira de Milho e Sorgo, v. 20, e1219, 2021. |
DOI: |
https://doi.org/10.18512/rbms2021v20e1219 |
Idioma: |
Inglês |
Conteúdo: |
In Brazil, livestock activity is affected by the seasonality of forage supply, which depends on the distribution of rainfall. The use of silage is one of the strategies to solve the problem during the annual dry season. The objective of this study was to use modeling to assess the productivity and quality of the maize silage in the state of Minas Gerais, Brazil. The CSM-CERES-Maize model was used to simulate maize silage production in 18 counties, at 52 sowing dates distributed throughout the year, with and without the use of irrigation. Absence of rainfall during the harvest period was also used as criterion to define the best sowing date in each county. In general, the best sowing dates were concentrated in October and February, respectively, for rainfed water supply and irrigated condition. The maize silage productivity under rainfed condition presented greater interannual variability and lower quality in comparison to that obtained under irrigated conditions. Under optimal soil-water conditions, climatic factors such as temperature and solar radiation are determinant to crop performance. |
Palavras-Chave: |
DSSAT; Modelagem; Modeling; Silage quality. |
Thesagro: |
Irrigação; Silagem; Zea Mays. |
Thesaurus NAL: |
Irrigation. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/229960/1/Sowing-period.pdf
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Marc: |
LEADER 01934naa a2200289 a 4500 001 2138745 005 2022-01-05 008 2021 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.18512/rbms2021v20e1219$2DOI 100 1 $aMELO, M. L. A. de 245 $aSowing period and estimated maize production for silage under tropical conditions.$h[electronic resource] 260 $c2021 520 $aIn Brazil, livestock activity is affected by the seasonality of forage supply, which depends on the distribution of rainfall. The use of silage is one of the strategies to solve the problem during the annual dry season. The objective of this study was to use modeling to assess the productivity and quality of the maize silage in the state of Minas Gerais, Brazil. The CSM-CERES-Maize model was used to simulate maize silage production in 18 counties, at 52 sowing dates distributed throughout the year, with and without the use of irrigation. Absence of rainfall during the harvest period was also used as criterion to define the best sowing date in each county. In general, the best sowing dates were concentrated in October and February, respectively, for rainfed water supply and irrigated condition. The maize silage productivity under rainfed condition presented greater interannual variability and lower quality in comparison to that obtained under irrigated conditions. Under optimal soil-water conditions, climatic factors such as temperature and solar radiation are determinant to crop performance. 650 $aIrrigation 650 $aIrrigação 650 $aSilagem 650 $aZea Mays 653 $aDSSAT 653 $aModelagem 653 $aModeling 653 $aSilage quality 700 1 $aCAMILO, J. A. 700 1 $aANDRADE, C. de L. T. de 700 1 $aAMARAL, T. A. 700 1 $aSOUZA, I. R. P. de 700 1 $aSIMEÃO, R. M. 773 $tRevista Brasileira de Milho e Sorgo$gv. 20, e1219, 2021.
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Registro original: |
Embrapa Milho e Sorgo (CNPMS) |
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