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Registro Completo |
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
06/05/1999 |
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Data da última atualização: |
19/06/2010 |
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Autoria: |
BARROS, E. de V. |
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Título: |
Liderança rural. |
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Ano de publicação: |
1979 |
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Fonte/Imprenta: |
Vicosa: UFV, [197-]. |
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Páginas: |
25 p. |
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Idioma: |
Português |
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Notas: |
Publicação não convencional. |
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Palavras-Chave: |
Lideranca rural. |
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Thesaurus Nal: |
leadership. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00361nam a2200145 a 4500
001 1375751
005 2010-06-19
008 1979 bl uuuu u0uu1 u #d
100 1 $aBARROS, E. de V.
245 $aLiderança rural.
260 $aVicosa: UFV, [197-].$c1979
300 $a25 p.
500 $aPublicação não convencional.
650 $aleadership
653 $aLideranca rural
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Embrapa Amazônia Oriental (CPATU) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sudeste. Para informações adicionais entre em contato com cppse.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Instrumentação; Embrapa Pecuária Sudeste. |
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Data corrente: |
08/04/2024 |
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Data da última atualização: |
09/04/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
BABOS, D. V.; TADINI, A. M.; MORAIS, C. P. DE; BARRETO, B. B.; CARVALHO, M. A. R.; BERNARDI, A. C. de C.; OLIVEIRA, P. P. A.; PEZZOPANE, J. R. M.; MILORI, D. M. B. P.; MARTIN NETO, L. |
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Afiliação: |
DIEGO V. BABOS; AMANDA M. TADINI; CARLA P. DE MORAIS, Logiag Inc.; BIANCA B. BARRETO; MAYARA A. R. CARVALHO; ALBERTO CARLOS DE CAMPOS BERNARDI, CPPSE; PATRICIA PERONDI ANCHAO OLIVEIRA, CPPSE; JOSE RICARDO MACEDO PEZZOPANE, CPPSE; DEBORA MARCONDES BASTOS PEREIRA, CNPDIA; LADISLAU MARTIN NETO, CNPDIA. |
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Título: |
Laser-induced breakdown spectroscopy (LIBS) as an analytical tool in precision agriculture: evaluation of spatial variability of soil fertility in integrated agricultural production systems. |
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Ano de publicação: |
2024 |
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Fonte/Imprenta: |
Catena, v. 239, 107914, 2024. |
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Páginas: |
13 p. |
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DOI: |
10.1016/j.catena.2024.107914 |
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Idioma: |
Inglês |
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Conteúdo: |
The rapid determination of soil fertility assists in improving agricultural production and reducing environmental impacts. With a new concept of precision agriculture and digital agriculture, new demands have been generated using sensors, methods, and protocols to improve analysis time and agricultural production. In this context, multivariate calibration models (multiple linear regression) were calculated for the indirect prediction of eight parameters of soil fertility, pH (H2O and CaCl2 extractors), cation exchange capacity, sum of bases, base saturation, Ca-exchangeable, Mg-exchangeable, and labile P, using laser-induced breakdown spectroscopy (LIBS), and also, for some parameters laser-induced fluorescence spectroscopy. Soil samples from a native forest (NF) and different agricultural production systems, such as integrated crop-livestock-forest system (CLFS), integrated livestock-forest system (LFS), integrated crop-livestock system (CLS), extensive (EXT), and intensive (INT) pastures, were collected from 0 to 40 cm depth (195 samples). Calibration models with good performance (0.62 ≤ R2 values ≤ 0.87, and 1.61 ≤ residual prediction deviation values ≤ 2.86) and adequate root mean squared error of prediction (RMSEP) values were obtained for the seven fertility parameters (0.74 ≤ r values ≤ 0.97, for the validation set), except for labile P (r = 0.44 and RPD = 1.35). Through principal component analysis (PCA) it was verified the formation of two clusters, referring to samples of more fertile soils of the production systems (CLFS and LFS) and NF that present the tree variable, and the other group referring to samples of soils of low fertility (EXT, INT, and CLS). To evaluate and exemplify the use of LIBS for precision and digital agriculture, in-depth soil chemical attributes and spatial variability, maps were obtained for an analyzed area of the integrated CLFS. The
LIBS technique can determine and assist in evaluating the variability of soil fertility attributes with reliability, agility (without the need for extraction procedures since the soil is thoroughly analyzed in the form of pellets), and accuracy. MenosThe rapid determination of soil fertility assists in improving agricultural production and reducing environmental impacts. With a new concept of precision agriculture and digital agriculture, new demands have been generated using sensors, methods, and protocols to improve analysis time and agricultural production. In this context, multivariate calibration models (multiple linear regression) were calculated for the indirect prediction of eight parameters of soil fertility, pH (H2O and CaCl2 extractors), cation exchange capacity, sum of bases, base saturation, Ca-exchangeable, Mg-exchangeable, and labile P, using laser-induced breakdown spectroscopy (LIBS), and also, for some parameters laser-induced fluorescence spectroscopy. Soil samples from a native forest (NF) and different agricultural production systems, such as integrated crop-livestock-forest system (CLFS), integrated livestock-forest system (LFS), integrated crop-livestock system (CLS), extensive (EXT), and intensive (INT) pastures, were collected from 0 to 40 cm depth (195 samples). Calibration models with good performance (0.62 ≤ R2 values ≤ 0.87, and 1.61 ≤ residual prediction deviation values ≤ 2.86) and adequate root mean squared error of prediction (RMSEP) values were obtained for the seven fertility parameters (0.74 ≤ r values ≤ 0.97, for the validation set), except for labile P (r = 0.44 and RPD = 1.35). Through principal component analysis (PCA) it was verified the formation of two clusters, referring to sam... Mostrar Tudo |
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Palavras-Chave: |
Digital agriculture; Integrated production system; Soil sensing; Tropical soil. |
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Thesaurus NAL: |
Soil pH. |
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Categoria do assunto: |
--
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 03167naa a2200313 a 4500
001 2163391
005 2024-04-09
008 2024 bl uuuu u00u1 u #d
024 7 $a10.1016/j.catena.2024.107914$2DOI
100 1 $aBABOS, D. V.
245 $aLaser-induced breakdown spectroscopy (LIBS) as an analytical tool in precision agriculture$bevaluation of spatial variability of soil fertility in integrated agricultural production systems.$h[electronic resource]
260 $c2024
300 $a13 p.
520 $aThe rapid determination of soil fertility assists in improving agricultural production and reducing environmental impacts. With a new concept of precision agriculture and digital agriculture, new demands have been generated using sensors, methods, and protocols to improve analysis time and agricultural production. In this context, multivariate calibration models (multiple linear regression) were calculated for the indirect prediction of eight parameters of soil fertility, pH (H2O and CaCl2 extractors), cation exchange capacity, sum of bases, base saturation, Ca-exchangeable, Mg-exchangeable, and labile P, using laser-induced breakdown spectroscopy (LIBS), and also, for some parameters laser-induced fluorescence spectroscopy. Soil samples from a native forest (NF) and different agricultural production systems, such as integrated crop-livestock-forest system (CLFS), integrated livestock-forest system (LFS), integrated crop-livestock system (CLS), extensive (EXT), and intensive (INT) pastures, were collected from 0 to 40 cm depth (195 samples). Calibration models with good performance (0.62 ≤ R2 values ≤ 0.87, and 1.61 ≤ residual prediction deviation values ≤ 2.86) and adequate root mean squared error of prediction (RMSEP) values were obtained for the seven fertility parameters (0.74 ≤ r values ≤ 0.97, for the validation set), except for labile P (r = 0.44 and RPD = 1.35). Through principal component analysis (PCA) it was verified the formation of two clusters, referring to samples of more fertile soils of the production systems (CLFS and LFS) and NF that present the tree variable, and the other group referring to samples of soils of low fertility (EXT, INT, and CLS). To evaluate and exemplify the use of LIBS for precision and digital agriculture, in-depth soil chemical attributes and spatial variability, maps were obtained for an analyzed area of the integrated CLFS. The LIBS technique can determine and assist in evaluating the variability of soil fertility attributes with reliability, agility (without the need for extraction procedures since the soil is thoroughly analyzed in the form of pellets), and accuracy.
650 $aSoil pH
653 $aDigital agriculture
653 $aIntegrated production system
653 $aSoil sensing
653 $aTropical soil
700 1 $aTADINI, A. M.
700 1 $aMORAIS, C. P. DE
700 1 $aBARRETO, B. B.
700 1 $aCARVALHO, M. A. R.
700 1 $aBERNARDI, A. C. de C.
700 1 $aOLIVEIRA, P. P. A.
700 1 $aPEZZOPANE, J. R. M.
700 1 $aMILORI, D. M. B. P.
700 1 $aMARTIN NETO, L.
773 $tCatena$gv. 239, 107914, 2024.
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