| |
|
|
| Registros recuperados : 263 | |
| 44. |  | FELBERG, I.; DELIZA, R.; SOUZA, A. M. de S.; FARAH, A.; DONANGELO, C. M. Aceitação de bebida gelada de soja e café solúvel. In: CONGRESSO BRASILEIRO DE CIÊNCIA E TECNOLOGIA DE ALIMENTOS, 21.; SEMINÁRIO LATINO AMERICANO E DO CARIBE DE CIÊNCIA E TECNOLOGIA DE ALIMENTOS, 15., 2008, Belo Horizonte. Anais... Belo Horizonte: SBCTA, 2008. 1 CD-ROM.| Biblioteca(s): Embrapa Agroindústria de Alimentos. |
|   |
| 49. | | KILCA, R. V.; LONGHI, S. J.; SCHWARTZ, G.; SOUZA, A. M.; WOJCIECHOVSKI, J. C. Application of fisher's discriminant analysis to classify forest communities in the pampa biome. Ciência Florestal, Santa Maria, v. 25, n. 4, p. 885-895, out./dez. 2015.| Biblioteca(s): Embrapa Amazônia Oriental; Embrapa Florestas. |
|  |
| Registros recuperados : 263 | |
|
|
|
 | Acesso ao texto completo restrito à biblioteca da Embrapa Solos. Para informações adicionais entre em contato com cnps.biblioteca@embrapa.br. |
Registro Completo
|
Biblioteca(s): |
Embrapa Solos. |
|
Data corrente: |
15/08/2019 |
|
Data da última atualização: |
08/11/2019 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Circulação/Nível: |
A - 1 |
|
Autoria: |
SANTANA, F. B. de; SOUZA, A. M. de; POPPI, R. J. |
|
Afiliação: |
FELIPE B. DE SANTANA, UNICAMP; ANDRE MARCELO DE SOUZA, CNPS; RONEI J. POPPI, UNICAMP. |
|
Título: |
Green methodology for soil organic matter analysis using a national near infrared spectral library in tandem with learning machine. |
|
Ano de publicação: |
2019 |
|
Fonte/Imprenta: |
Science of the Total Environment, v. 658, p. 895-900, Mar. 2019. |
|
DOI: |
10.1016/j.scitotenv.2018.12.27 |
|
Idioma: |
Inglês |
|
Conteúdo: |
Precision agriculture requires faster and automatic responses for fertility parameters, especially regarding soil organic matter (SOM). In Brazil, the standard methodology for SOMdetermination is awet procedure based on the oxidation of the sample by an excess of potassium dichromate based on Walkley-Black method. This methodology has serious drawbacks, since, at a national level, generates approximately 600,000 L/year of toxic acid waste containing Cr3+ and possibly Cr6+, besides time consuming and expensive. Herein, we present a faster green methodology that can eliminate the generation of these hazardous wastes and reduces the costs of analysis by approximately 80%, democratizing the soil fertility information and increasing the productivity. The methodology is based on the use of a national near infrared spectral library with approximately 43,000 samples and learning machine data analysis based on a randomforest algorithm. The methodology was validated by submitting the prediction results of 12 blind soil samples to a proficiency assay used for fertility soil laboratories qualification, receiving the maximum quality excellence index, indicating that it is suitable for use in routine analysis. |
|
Thesagro: |
Agricultura de Precisão; Espectrômetro; Floresta; Matéria Orgânica; Raio Infravermelho; Solo. |
|
Thesaurus NAL: |
Near-infrared spectroscopy; Soil. |
|
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
|
Marc: |
LEADER 02026naa a2200253 a 4500
001 2111368
005 2019-11-08
008 2019 bl uuuu u00u1 u #d
024 7 $a10.1016/j.scitotenv.2018.12.27$2DOI
100 1 $aSANTANA, F. B. de
245 $aGreen methodology for soil organic matter analysis using a national near infrared spectral library in tandem with learning machine.$h[electronic resource]
260 $c2019
520 $aPrecision agriculture requires faster and automatic responses for fertility parameters, especially regarding soil organic matter (SOM). In Brazil, the standard methodology for SOMdetermination is awet procedure based on the oxidation of the sample by an excess of potassium dichromate based on Walkley-Black method. This methodology has serious drawbacks, since, at a national level, generates approximately 600,000 L/year of toxic acid waste containing Cr3+ and possibly Cr6+, besides time consuming and expensive. Herein, we present a faster green methodology that can eliminate the generation of these hazardous wastes and reduces the costs of analysis by approximately 80%, democratizing the soil fertility information and increasing the productivity. The methodology is based on the use of a national near infrared spectral library with approximately 43,000 samples and learning machine data analysis based on a randomforest algorithm. The methodology was validated by submitting the prediction results of 12 blind soil samples to a proficiency assay used for fertility soil laboratories qualification, receiving the maximum quality excellence index, indicating that it is suitable for use in routine analysis.
650 $aNear-infrared spectroscopy
650 $aSoil
650 $aAgricultura de Precisão
650 $aEspectrômetro
650 $aFloresta
650 $aMatéria Orgânica
650 $aRaio Infravermelho
650 $aSolo
700 1 $aSOUZA, A. M. de
700 1 $aPOPPI, R. J.
773 $tScience of the Total Environment$gv. 658, p. 895-900, Mar. 2019.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Solos (CNPS) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
