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Registro Completo |
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Biblioteca(s): |
Embrapa Pesca e Aquicultura; Embrapa Unidades Centrais. |
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Data corrente: |
20/04/2011 |
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Data da última atualização: |
17/01/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
AVANZI, J. C.; NORTON, L. D.; SILVA, M. L. N.; CURI, N.; OLIVEIRA, A. H.; SILVA, M. A. da. |
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Afiliação: |
JUNIOR CESAR AVANZI, CNPASA; LLOYD DARRELL NORTON, USDA; MARX LEANDRO NAVES SILVA, UNIVERSIDADE FEDERAL DE LAVRAS; NILTON CURI, UNIVERSIDADE FEDERAL DE LAVRAS; ANNA HOFFMANN OLIVEIRA, UNIVERSIDADE FEDERAL DE LAVRAS; MAYESSE APARECIDA DA SILVA, UNIVERSIDADE FEDERAL DE LAVRAS. |
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Título: |
Aggregate stability in soils cultivated with eucalyptus. |
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Ano de publicação: |
2011 |
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Fonte/Imprenta: |
Pesquisa Agropecuária Brasileira, Brasília, DF, v. 46, n. 1, p. 89-96, jan. 2011. |
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Idioma: |
Inglês |
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Conteúdo: |
The objective of this work was to evaluate the aggregate stability of tropical soils under eucalyptus plantation and native vegetation, and assess the relationships between aggregate stability and some soil chemical and physical properties. Argisols, Cambisol, Latosols and Plinthosol within three eucalyptus-cultivated regions, in the states of Espírito Santo, Rio Grande do Sul and Minas Gerais, Brazil, were studied. For each region, soils under native vegetation were compared to those under minimum tillage with eucalyptus cultivation. The aggregate stability was measured using the high‑energy moisture characteristic (HEMC) technique, i.e., the moisture release curve at very low suctions. This method compares the resistance of aggregates to slaking on a relative scale from zero to one. Thus, the aggregate stability from different soils and management practices can be directly compared. The aggregate stability ratio was greater than 50% for all soils, which shows that the aggregate stability index is high, both in eucalyptus and native vegetation areas. This suggests that soil management adopted for eucalyptus cultivation does not substantially modify this property. In these soils, the aggregate stability ratio does not show a good relationship with clay or soil organic matter contents. However, soil organic matter shows a positive relationship with clay content and cation exchange capacity. |
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Palavras-Chave: |
Curva característica de umidade em alta energia; Eucalyptus sp; Forest systems; High-energy moisture characteristic curve; Sistema florestal; Sward structure. |
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Thesagro: |
Eucalipto; Floresta; Solo tropical; Umidade. |
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Thesaurus Nal: |
Eucalyptus; Forest soils; tropical soils. |
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Categoria do assunto: |
--
K Ciência Florestal e Produtos de Origem Vegetal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/43772/1/Avanzi2011.pdf
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/168472/1/Aggregate-stability-in-soils.pdf
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Marc: |
LEADER 02375naa a2200337 a 4500
001 1903131
005 2024-01-17
008 2011 bl uuuu u00u1 u #d
100 1 $aAVANZI, J. C.
245 $aAggregate stability in soils cultivated with eucalyptus.
260 $c2011
520 $aThe objective of this work was to evaluate the aggregate stability of tropical soils under eucalyptus plantation and native vegetation, and assess the relationships between aggregate stability and some soil chemical and physical properties. Argisols, Cambisol, Latosols and Plinthosol within three eucalyptus-cultivated regions, in the states of Espírito Santo, Rio Grande do Sul and Minas Gerais, Brazil, were studied. For each region, soils under native vegetation were compared to those under minimum tillage with eucalyptus cultivation. The aggregate stability was measured using the high‑energy moisture characteristic (HEMC) technique, i.e., the moisture release curve at very low suctions. This method compares the resistance of aggregates to slaking on a relative scale from zero to one. Thus, the aggregate stability from different soils and management practices can be directly compared. The aggregate stability ratio was greater than 50% for all soils, which shows that the aggregate stability index is high, both in eucalyptus and native vegetation areas. This suggests that soil management adopted for eucalyptus cultivation does not substantially modify this property. In these soils, the aggregate stability ratio does not show a good relationship with clay or soil organic matter contents. However, soil organic matter shows a positive relationship with clay content and cation exchange capacity.
650 $aEucalyptus
650 $aForest soils
650 $atropical soils
650 $aEucalipto
650 $aFloresta
650 $aSolo tropical
650 $aUmidade
653 $aCurva característica de umidade em alta energia
653 $aEucalyptus sp
653 $aForest systems
653 $aHigh-energy moisture characteristic curve
653 $aSistema florestal
653 $aSward structure
700 1 $aNORTON, L. D.
700 1 $aSILVA, M. L. N.
700 1 $aCURI, N.
700 1 $aOLIVEIRA, A. H.
700 1 $aSILVA, M. A. da
773 $tPesquisa Agropecuária Brasileira, Brasília, DF$gv. 46, n. 1, p. 89-96, jan. 2011.
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Registro original: |
Embrapa Pesca e Aquicultura (CNPASA) |
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Registro Completo
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Biblioteca(s): |
Embrapa Pesca e Aquicultura. |
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Data corrente: |
25/01/2024 |
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Data da última atualização: |
25/01/2024 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
GREENSTREET, L.; FAN, J.; PACHECO, F. S.; BAI, Y.; UMMUS, M. E.; DORIA, C.; BARROS, N. O.; FORSBERG, B. R.; XU, X.; FLECKER, A.; GOMES, C. |
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Afiliação: |
LAURA GREENSTREET, CORNELL UNIVERSITY; JOSHUA FAN, CORNELL UNIVERSITY; FELIPE SIQUEIRA PACHECO, CORNELL UNIVERSITY; YIWEI BAI, CORNELL UNIVERSITY; MARTA EICHEMBERGER UMMUS, CNPASA; CAROLINA DORIA, UNIVERSIDADE FEDERAL DE RONDÔNIA; NATHAN OLIVEIRA BARROS, UNIVERSIDADE FEDERAL DE JUIZ DE FORA; BRUCE R. FORSBERG, INPA; XIANGTAO XU, CORNELL UNIVERSITY; ALEXANDER FLECKER, CORNELL UNIVERSITY; CARLA GOMES, CORNELL UNIVERSITY. |
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Título: |
Detecting aquaculture with deep learning in a low-data setting. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
In: SIGKDD FRAGILE EARTH WORKSHOP, 2023, Long Beach. |
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Idioma: |
Inglês |
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Conteúdo: |
Aquaculture is growing rapidly in the Amazon basin and detailed spatial information is needed to understand the trade-offs between food production, economic development, and environmental impacts. Large open-source datasets of medium resolution satellite imagery offer the potential for mapping a variety of infrastructure, including aquaculture ponds. However, there are many challenges utilizing this data, including few labelled examples, class imbalance, and spatial bias. We find previous rule-based methods for mapping aquaculture perform poorly in the Amazon. By incorporating temporal information through percentile data, we show deep learning models can outperform previous methods by as much as 15% with as few as 300 labelled examples. Further, generalization to unseen regions can be improved by incorporating segmentation information through masked pooling and using contrastive pretraining to harness large quantities of unlabelled data. |
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Palavras-Chave: |
Attention; Contrastive learning; Convolutinal neural networks; Image classification; Image segmentation; Representation learning. |
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Thesagro: |
Aquicultura; Sensoriamento Remoto. |
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Thesaurus NAL: |
Aquaculture; Digital images; Neural networks; Remote sensing. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1161305/1/detecting-aquaculture-with-dee.pdf
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Marc: |
LEADER 01980nam a2200373 a 4500
001 2161305
005 2024-01-25
008 2023 bl uuuu u00u1 u #d
100 1 $aGREENSTREET, L.
245 $aDetecting aquaculture with deep learning in a low-data setting.$h[electronic resource]
260 $aIn: SIGKDD FRAGILE EARTH WORKSHOP, 2023, Long Beach.$c2023
520 $aAquaculture is growing rapidly in the Amazon basin and detailed spatial information is needed to understand the trade-offs between food production, economic development, and environmental impacts. Large open-source datasets of medium resolution satellite imagery offer the potential for mapping a variety of infrastructure, including aquaculture ponds. However, there are many challenges utilizing this data, including few labelled examples, class imbalance, and spatial bias. We find previous rule-based methods for mapping aquaculture perform poorly in the Amazon. By incorporating temporal information through percentile data, we show deep learning models can outperform previous methods by as much as 15% with as few as 300 labelled examples. Further, generalization to unseen regions can be improved by incorporating segmentation information through masked pooling and using contrastive pretraining to harness large quantities of unlabelled data.
650 $aAquaculture
650 $aDigital images
650 $aNeural networks
650 $aRemote sensing
650 $aAquicultura
650 $aSensoriamento Remoto
653 $aAttention
653 $aContrastive learning
653 $aConvolutinal neural networks
653 $aImage classification
653 $aImage segmentation
653 $aRepresentation learning
700 1 $aFAN, J.
700 1 $aPACHECO, F. S.
700 1 $aBAI, Y.
700 1 $aUMMUS, M. E.
700 1 $aDORIA, C.
700 1 $aBARROS, N. O.
700 1 $aFORSBERG, B. R.
700 1 $aXU, X.
700 1 $aFLECKER, A.
700 1 $aGOMES, C.
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Registro original: |
Embrapa Pesca e Aquicultura (CNPASA) |
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