|
|
Registro Completo |
Biblioteca(s): |
Embrapa Amazônia Oriental. |
Data corrente: |
27/10/2020 |
Data da última atualização: |
17/11/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
COSTA, S. D. A. da; BRASIL, E. C.; SILVA JÚNIOR, M. L. da. |
Afiliação: |
SIDNEY DANIEL ARAÚJO DA COSTA, UFRA; EDILSON CARVALHO BRASIL, CPATU; MÁRIO LOPES DA SILVA JÚNIOR, UFRA. |
Título: |
Influence of limestone and gypsum application on chemical attributes of dystrophic yellow latosol soil and corn yield in Eastern Amazon. |
Ano de publicação: |
2020 |
Fonte/Imprenta: |
Journal of Agricultural Studies, v. 8, n. 3, p. 363-383, 2020. |
DOI: |
10.5296/jas.v8i3.16744 |
Idioma: |
Inglês |
Conteúdo: |
The objectiveof this study was to evaluate changes in the chemical attributes of the soil caused by the use of limestone associated or not to with gypsum in no-tillage system. The experiment was conducted on a dystrophic Yellow Latosol in Pará state,Brazil. The experimental design was in randomized blocks in split plots with three replications. The treatments consisted of five doses of limestone (0, 1, 2, 3 and 4 t ha-1), with and without gypsum (0, 0.5 and 1 t ha-1). Soil samples were collected at depths of 0-20 and 20-40 cm. There was a significant effect on the analyzed variables at both depths. The doses of 3.64 and 2.19 t ha-1of limestone associated with 0.5 t ha-1of gypsum, were responsible for the largest increase in soil calcium content in the 0-20 and 20-40 cm layers, respectively. The highest increase in Ca + Mg content was found at 3.63 t ha-1limestone combined with 0.5 t ha-1gypsum. It was observed that 3.13 t ha-1of limestone combined with 0.5 t of gypsum increased soil CEC. The 2.89 t ha-1dose of limestone combined with 0.5 t of gypsum contributed to the increase in base saturation (V%). The use of limestone and gypsum promotes soil chemical conditions, as reflected by increased corn yield when compared with control (no treatment) plots. |
Thesagro: |
Calcário; Gesso; Latossolo Amarelo; Milho; Química do Solo; Zea Mays. |
Thesaurus Nal: |
Amazonia; Limestone; Plaster; Soil chemistry. |
Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/217113/1/Influence-of-Limestone-and-Gypsum-Application-on-Chemical-Attributes-of-Dystrophic-Yellow-Latosol-Soil-and-Corn-Yield-in-Eastern-Amazon.pdf
|
Marc: |
LEADER 02104naa a2200277 a 4500 001 2125939 005 2020-11-17 008 2020 bl uuuu u00u1 u #d 024 7 $a10.5296/jas.v8i3.16744$2DOI 100 1 $aCOSTA, S. D. A. da 245 $aInfluence of limestone and gypsum application on chemical attributes of dystrophic yellow latosol soil and corn yield in Eastern Amazon.$h[electronic resource] 260 $c2020 520 $aThe objectiveof this study was to evaluate changes in the chemical attributes of the soil caused by the use of limestone associated or not to with gypsum in no-tillage system. The experiment was conducted on a dystrophic Yellow Latosol in Pará state,Brazil. The experimental design was in randomized blocks in split plots with three replications. The treatments consisted of five doses of limestone (0, 1, 2, 3 and 4 t ha-1), with and without gypsum (0, 0.5 and 1 t ha-1). Soil samples were collected at depths of 0-20 and 20-40 cm. There was a significant effect on the analyzed variables at both depths. The doses of 3.64 and 2.19 t ha-1of limestone associated with 0.5 t ha-1of gypsum, were responsible for the largest increase in soil calcium content in the 0-20 and 20-40 cm layers, respectively. The highest increase in Ca + Mg content was found at 3.63 t ha-1limestone combined with 0.5 t ha-1gypsum. It was observed that 3.13 t ha-1of limestone combined with 0.5 t of gypsum increased soil CEC. The 2.89 t ha-1dose of limestone combined with 0.5 t of gypsum contributed to the increase in base saturation (V%). The use of limestone and gypsum promotes soil chemical conditions, as reflected by increased corn yield when compared with control (no treatment) plots. 650 $aAmazonia 650 $aLimestone 650 $aPlaster 650 $aSoil chemistry 650 $aCalcário 650 $aGesso 650 $aLatossolo Amarelo 650 $aMilho 650 $aQuímica do Solo 650 $aZea Mays 700 1 $aBRASIL, E. C. 700 1 $aSILVA JÚNIOR, M. L. da 773 $tJournal of Agricultural Studies$gv. 8, n. 3, p. 363-383, 2020.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Amazônia Oriental (CPATU) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
Registro Completo
Biblioteca(s): |
Embrapa Florestas. |
Data corrente: |
02/12/2019 |
Data da última atualização: |
03/12/2019 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
CHIARELLO, F.; STEINER, M. T. A.; OLIVEIRA, E. B. de; ARCE, J. E.; FERREIRA, J. C. |
Afiliação: |
Flávio Chiarello, PUC-PR; Maria Teresinha Arns Steiner, PUC-PR; EDILSON BATISTA DE OLIVEIRA, CNPF; Júlio Eduardo Arce, UFPR; Júlio César Ferreira, PUC-PR. |
Título: |
Artificial neural networks applied in forest biometrics and modeling: state of the art (January/2007 to July/2018). |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
Cerne, v. 25 n. 2, p. 140-155, Apr./June 2019. |
DOI: |
10.1590/01047760201925022626 |
Idioma: |
Inglês |
Conteúdo: |
Artificial Intelligence has been an important support tool in different spheres of activity, enabling knowledge aggregation, process optimization and the application of methodologies capable of solving complex real problems. Despite focusing on a wide range of successful metrics, the Artificial Neural Network (ANN) approach, a technique similar to the central nervous system, has gained notoriety and relevance with regard to the classification of standards, intrinsic parameter estimates, remote sense, data mining and other possibilities. This article aims to conduct a systematic review, involving some bibliometric aspects, to detect the application of ANNs in the field of Forest Engineering, particularly in the prognosis of the essential parameters for forest inventory, analyzing the construction of the scopes, implementation of networks (type ? classification), the software used and complementary techniques. Of the 1,140 articles collected from three research databases (Science Direct, Scopus and Web of Science), 43 articles underwent these analyses. The results show that the number of works within this scope has increased continuously, with 32% of the analyzed articles predicting the final total marketable volume, 78% making use of Multilayer Perceptron Networks (MLP, Multilayer Perceptron) and 63% from Brazilian researchers. |
Palavras-Chave: |
Bibliometric Review; Forest Engineering Problems; Inteligência artificial; Multilayer Perceptron; Revisão Bibliométrica; Revisão sistemática. |
Thesaurus NAL: |
Artificial intelligence; Systematic review. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/205952/1/2019-Edilson-Cerne-Artificial.pdf
|
Marc: |
LEADER 02246naa a2200277 a 4500 001 2115699 005 2019-12-03 008 2019 bl uuuu u00u1 u #d 024 7 $a10.1590/01047760201925022626$2DOI 100 1 $aCHIARELLO, F. 245 $aArtificial neural networks applied in forest biometrics and modeling$bstate of the art (January/2007 to July/2018).$h[electronic resource] 260 $c2019 520 $aArtificial Intelligence has been an important support tool in different spheres of activity, enabling knowledge aggregation, process optimization and the application of methodologies capable of solving complex real problems. Despite focusing on a wide range of successful metrics, the Artificial Neural Network (ANN) approach, a technique similar to the central nervous system, has gained notoriety and relevance with regard to the classification of standards, intrinsic parameter estimates, remote sense, data mining and other possibilities. This article aims to conduct a systematic review, involving some bibliometric aspects, to detect the application of ANNs in the field of Forest Engineering, particularly in the prognosis of the essential parameters for forest inventory, analyzing the construction of the scopes, implementation of networks (type ? classification), the software used and complementary techniques. Of the 1,140 articles collected from three research databases (Science Direct, Scopus and Web of Science), 43 articles underwent these analyses. The results show that the number of works within this scope has increased continuously, with 32% of the analyzed articles predicting the final total marketable volume, 78% making use of Multilayer Perceptron Networks (MLP, Multilayer Perceptron) and 63% from Brazilian researchers. 650 $aArtificial intelligence 650 $aSystematic review 653 $aBibliometric Review 653 $aForest Engineering Problems 653 $aInteligência artificial 653 $aMultilayer Perceptron 653 $aRevisão Bibliométrica 653 $aRevisão sistemática 700 1 $aSTEINER, M. T. A. 700 1 $aOLIVEIRA, E. B. de 700 1 $aARCE, J. E. 700 1 $aFERREIRA, J. C. 773 $tCerne$gv. 25 n. 2, p. 140-155, Apr./June 2019.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Florestas (CNPF) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
Expressão de busca inválida. Verifique!!! |
|
|