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Registros recuperados : 2 | |
1. | | BECKER, W. R.; RICHETTI, J.; MERCANTE, E.; ESQUERDO, J. C. D. M.; SILVA JUNIOR, C. A. da; PALUDO, A.; JOHANN, J. A. Agricultural soybean and corn calendar based on moderate resolution satellite images for southern Brazil. Semina: Ciências Agrárias, v. 41, n. 5, p. 2419-2428, 2020. Suplemento 1. Biblioteca(s): Embrapa Agricultura Digital. |
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2. | | CAON, I. L.; BECKER, W. R.; GANASCINI, D.; CATTANI, C. E. V.; MENDES, I. de S.; PRUDENTE, V. H. R.; OLDONI, L. V.; ANTUNES, J. F. G.; MERCANTE, E. Comparativo entre os classificadores RF e MAXVER, para classificação de uso e cobertura da terra, em diferentes densidades temporais. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 19., 2019, Santos. Anais... São José dos Campos: INPE, 2019. 4 p. Editores: Douglas Francisco Marcolino Gherardi, Ieda Del?Arco Sanches, Luiz Eduardo Oliveira e Cruz de Aragão. SBSR 2019. Biblioteca(s): Embrapa Agricultura Digital. |
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Registros recuperados : 2 | |
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Registro Completo
Biblioteca(s): |
Embrapa Agricultura Digital. |
Data corrente: |
23/11/2020 |
Data da última atualização: |
23/11/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 1 |
Autoria: |
BECKER, W. R.; RICHETTI, J.; MERCANTE, E.; ESQUERDO, J. C. D. M.; SILVA JUNIOR, C. A. da; PALUDO, A.; JOHANN, J. A. |
Afiliação: |
WILLYAN RONALDO BECKER, Unioeste; JONATHAN RICHETTI, Unioeste; ERIVELTO MERCANTE, Unioeste; JULIO CESAR DALLA MORA ESQUERDO, CNPTIA; CARLOS ANTONIO DA SILVA JUNIOR, Unemat; ALEX PALUDO, Unioeste; JERRY ADRIANI JOHANN, Unioeste. |
Título: |
Agricultural soybean and corn calendar based on moderate resolution satellite images for southern Brazil. |
Ano de publicação: |
2020 |
Fonte/Imprenta: |
Semina: Ciências Agrárias, v. 41, n. 5, p. 2419-2428, 2020. |
DOI: |
10.5433/1679-0359.2020v41n5Supl1p2419 |
Idioma: |
Inglês |
Notas: |
Suplemento 1. |
Conteúdo: |
Abstract. Knowledge of the agricultural calendar of crops is essential to better estimate and forecast the cultivation of large-scale crops. The aim of this study was to estimate sowing date (SD), date of maximum vegetative development (DMVD), and harvest date (HD) of soybean and corn in the state of Paraná, Brazil. Dates from 120 farms and the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2011 to 2014 were used into a seasonal trend analysis to obtain soybean and corn seasonal patterns. The results indicate that the majority soybean is sown during October and the DMVD occurs between the second ten-day period of December and the first ten-day period of January. Owing to the spatial variability of the SD, the difference in the maturation cycles of the cultivars, and regional climatic variation, the HD of soybean varied greatly during the studied crop years, ranging from mid-February to late March. The SD of corn is before that of soybean, and mainly occurs in late September to mid-October. The DMVD mainly occurs during December, and the HD is distributed throughout January to March in Paraná. When comparing the estimated dates with observed dates the mean error (ME) varied from 0.2 days earlier to 3.3 days after the observed date for soybean with root mean square error (RMSE) from 1.93 to 14.73 days. For corn, the ME varied from 10.3 days to 18.5 days after the observed date with RMSE from 18.02 to 27.82 days. |
Palavras-Chave: |
Data de Colheita; Data de Semeadura; Enhanced Vegetation Index; Índice de Vegetação Aprimorado; Índice de vegetação melhorado; Timesat. |
Thesagro: |
Milho; Soja. |
Thesaurus NAL: |
Corn; Harvest date; Sowing date; Soybeans; Vegetation index. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/218126/1/AP-Agricultural-soybean-Semina-2020.pdf
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Marc: |
LEADER 02593naa a2200373 a 4500 001 2126956 005 2020-11-23 008 2020 bl uuuu u00u1 u #d 024 7 $a10.5433/1679-0359.2020v41n5Supl1p2419$2DOI 100 1 $aBECKER, W. R. 245 $aAgricultural soybean and corn calendar based on moderate resolution satellite images for southern Brazil.$h[electronic resource] 260 $c2020 500 $aSuplemento 1. 520 $aAbstract. Knowledge of the agricultural calendar of crops is essential to better estimate and forecast the cultivation of large-scale crops. The aim of this study was to estimate sowing date (SD), date of maximum vegetative development (DMVD), and harvest date (HD) of soybean and corn in the state of Paraná, Brazil. Dates from 120 farms and the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2011 to 2014 were used into a seasonal trend analysis to obtain soybean and corn seasonal patterns. The results indicate that the majority soybean is sown during October and the DMVD occurs between the second ten-day period of December and the first ten-day period of January. Owing to the spatial variability of the SD, the difference in the maturation cycles of the cultivars, and regional climatic variation, the HD of soybean varied greatly during the studied crop years, ranging from mid-February to late March. The SD of corn is before that of soybean, and mainly occurs in late September to mid-October. The DMVD mainly occurs during December, and the HD is distributed throughout January to March in Paraná. When comparing the estimated dates with observed dates the mean error (ME) varied from 0.2 days earlier to 3.3 days after the observed date for soybean with root mean square error (RMSE) from 1.93 to 14.73 days. For corn, the ME varied from 10.3 days to 18.5 days after the observed date with RMSE from 18.02 to 27.82 days. 650 $aCorn 650 $aHarvest date 650 $aSowing date 650 $aSoybeans 650 $aVegetation index 650 $aMilho 650 $aSoja 653 $aData de Colheita 653 $aData de Semeadura 653 $aEnhanced Vegetation Index 653 $aÍndice de Vegetação Aprimorado 653 $aÍndice de vegetação melhorado 653 $aTimesat 700 1 $aRICHETTI, J. 700 1 $aMERCANTE, E. 700 1 $aESQUERDO, J. C. D. M. 700 1 $aSILVA JUNIOR, C. A. da 700 1 $aPALUDO, A. 700 1 $aJOHANN, J. A. 773 $tSemina: Ciências Agrárias$gv. 41, n. 5, p. 2419-2428, 2020.
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Embrapa Agricultura Digital (CNPTIA) |
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