| |
|
|
|
Registro Completo |
|
Biblioteca(s): |
Embrapa Agricultura Digital. |
|
Data corrente: |
14/09/2021 |
|
Data da última atualização: |
14/09/2021 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Autoria: |
MARÇAL, M. F. M.; SOUZA, Z. M. de; TAVARES, R. L. M.; FARHATE, C. V. V.; OLIVEIRA, S. R. de M.; GALINDO, F. S. |
|
Afiliação: |
MARIA FERNANDA MAGIONI MARÇAL, FEAGRI/UNICAMP; ZIGOMAR MENEZES DE SOUZA, FEAGRI/UNICAMP; ROSE LUIZA MORAES TAVARES, UNIVERSITY OF RIO VERDE; CAMILA VIANA VIEIRA FARHATE, FEAGRI/UNICAMP, UNESP; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; FERNANDO SHINTATE GALINDO, FEAGRI/UNICAMP, UNESP. |
|
Título: |
Predictive models to estimate carbon stocks in agroforestry systems. |
|
Ano de publicação: |
2021 |
|
Fonte/Imprenta: |
Forests, v. 12, n. 9, p. 1-15, Sept. 2021. |
|
DOI: |
https://doi.org/10.3390/f12091240 |
|
Idioma: |
Inglês |
|
Notas: |
Article 1240. Na publicação: Stanley Robson Medeiros Oliveira. |
|
Conteúdo: |
Abstract: This study aims to assess the carbon stock in a pasture area and fragment of forest in natural regeneration, given the importance of agroforestry systems in mitigating gas emissions which contribute to the greenhouse effect, as well as promoting the maintenance of agricultural productivity. Our other goal was to predict the carbon stock, according to different land use systems, from physical and chemical soil variables using the Random Forest algorithm. We carried out our study at an Entisols Quartzipsamments area with a completely randomized experimental design: four treatments and six replites. The treatments consisted of the following: (i) an agroforestry system developed for livestock, (ii) an agroforestry system developed for fruit culture, (iii) a conventional pasture, and (iv) a forest fragment. Deformed and undeformed soil samples were collected in order to analyze their physical and chemical properties across two consecutive agricultural years. The response variable, carbon stock, was subjected to a boxplot analysis and all the databases were used for a predictive modeling which in turn used the Random Forest algorithm. Results led to the conclusion that the agroforestry systems developed both for fruit culture and livestock, are more efficient at stocking carbon in the soil than the pasture area and forest fragment undergoing natural regeneration. Nitrogen stock and land use systems are the most important variables to estimate carbon stock from the physical and chemical variables of soil using the Random Forest algorithm. The predictive models generated from the physical and chemical variables of soil, as well as the Random Forest algorithm, presented a high potential for predicting soil carbon stock and are sensitive to different land use systems. MenosAbstract: This study aims to assess the carbon stock in a pasture area and fragment of forest in natural regeneration, given the importance of agroforestry systems in mitigating gas emissions which contribute to the greenhouse effect, as well as promoting the maintenance of agricultural productivity. Our other goal was to predict the carbon stock, according to different land use systems, from physical and chemical soil variables using the Random Forest algorithm. We carried out our study at an Entisols Quartzipsamments area with a completely randomized experimental design: four treatments and six replites. The treatments consisted of the following: (i) an agroforestry system developed for livestock, (ii) an agroforestry system developed for fruit culture, (iii) a conventional pasture, and (iv) a forest fragment. Deformed and undeformed soil samples were collected in order to analyze their physical and chemical properties across two consecutive agricultural years. The response variable, carbon stock, was subjected to a boxplot analysis and all the databases were used for a predictive modeling which in turn used the Random Forest algorithm. Results led to the conclusion that the agroforestry systems developed both for fruit culture and livestock, are more efficient at stocking carbon in the soil than the pasture area and forest fragment undergoing natural regeneration. Nitrogen stock and land use systems are the most important variables to estimate carbon stock from the physic... Mostrar Tudo |
|
Palavras-Chave: |
Agroforestry systems; Data mining technique; Floresta aleatória; Land use systems; Mineração de dados; Modelo preditivo; Predictive models; Random forest; Sequestro de carbono; Sistemas agroflorestais; Sistemas de uso da terra. |
|
Thesagro: |
Matéria Orgânica; Uso da Terra. |
|
Thesaurus Nal: |
Agroforestry; Carbon sequestration; Land use; Organic matter. |
|
Categoria do assunto: |
-- |
|
URL: |
https://www.alice.cnptia.embrapa.br/alice/bitstream/doc/1134318/1/AP-Predictive-models-Forests-2021.pdf
|
|
Marc: |
null
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
|
Registro Completo
|
Biblioteca(s): |
Embrapa Pecuária Sul. |
|
Data corrente: |
11/08/2017 |
|
Data da última atualização: |
15/08/2017 |
|
Tipo da produção científica: |
Resumo em Anais de Congresso |
|
Autoria: |
FARO, A. M. C. da F.; MONTEIRO, A. L. G.; HENTZ, F.; SILVA, C. J. A. da; SCUCATO, T.; GENRO, T. C. M.; PRADO, O. R.; RIBEIRO FILHO, H. M. N. |
|
Afiliação: |
AMANDA MOSER COELHO DA FONSECA FARO, IFC; ALDA LÚCIA GOMES MONTEIRO, UFPR; FERNANDO HENTZ, UFPR; CLAUDIO JOSÉ ARAÚJO DA SILVA, UFPR; THAILINE SCUCATO, UFPR; TERESA CRISTINA MORAES GENRO, CPPSUL; ODILEI ROGÉRIO PRADO, UTPR; HENRIQUE M.N. RIBEIRO FILHO, UDESC. |
|
Título: |
Herbage intake and productivity in lamb production systems on pastures of Southern Brazil. |
|
Ano de publicação: |
2017 |
|
Fonte/Imprenta: |
In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 54., 2017, Foz do Iguaçu. A new view of animal science: challenges and perspectives: proceedings. Foz do Iguaçu: Sociedade Brasileira de Zootecnia, 2017. |
|
Páginas: |
p. 1074. |
|
Idioma: |
Inglês |
|
Thesagro: |
Ovino; Pastagem. |
|
Categoria do assunto: |
-- |
|
URL: |
https://www.alice.cnptia.embrapa.br/alice/bitstream/doc/1073948/1/Faroetalsbz2017.pdf
|
|
Marc: |
null
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Pecuária Sul (CPPSUL) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
