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Registro Completo |
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Biblioteca(s): |
Biblioteca Rui Tendinha. |
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Data corrente: |
19/02/2024 |
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Data da última atualização: |
27/02/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
MAURI, L. V. R.; MENDONÇA, E. de Sá; BOLZAN, L. J.; ANGELETTI, M. da P. A. |
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Afiliação: |
Laura Vaillant Ribeiro Mauri, UFES; Eduardo de Sá Mendonça, UFES; Lenita Julia Bolzan, UFES; Maria da Penha Angeletti, Incaper. |
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Título: |
Olericulture No-Till System at Mountain Region: Physical and Biological Attributes of the Soil. |
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Ano de publicação: |
2024 |
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Fonte/Imprenta: |
Hindawi, v. 2024, p. 1-11, 2024. |
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Idioma: |
Inglês |
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Conteúdo: |
The production of vegetables and grains by the family farming in the mountains of the Atlantic Forest is characterized by intensive soil management with ploughing and harrowing practices. These practices are promoting hydric erosion and losses of soil quality in the region. In this context, the objective of this work was to evaluate soil physical and biological characteristics at two seasons of the year in agroecosystems producing vegetables and grains in the no-tillage system (NTS) for 3, 5, and 9 years compared to the conventional management system (CT) in the Atlantic Forest Biome, Brazil. Physical and organic matter attributes and carbon (C) and nitrogen (N) stock were evaluated. NTS showed, in general, greater total porosity than CT systems. The main differences between the systems were found in the organic attributes and C and N stocks. The content of microbial biomass C in NTS with 3, 5, and 9 years was 767.5, 326.5, and 210.0 mg·kg−1, while the areas with CT had 93.75, 78.25, and 45.75 mg·kg−1, respectively. The stock of C in winter at the 9NTS area was 33.0 and 41.5 Mg·ha−1, and the respective area in CT presented only 21.75 and 25.00 Mg·ha−1 in the depths of 0?10 and 10?20 cm, respectively. The metabolic quotient of the NTS areas did not differ from the reference ecosystems and is promoting lower C-CO2 emissions than the CT system. The adoption of NTS in vegetable production improves soil quality in family farm areas of mountains relief at the Atlantic Forest Biome. MenosThe production of vegetables and grains by the family farming in the mountains of the Atlantic Forest is characterized by intensive soil management with ploughing and harrowing practices. These practices are promoting hydric erosion and losses of soil quality in the region. In this context, the objective of this work was to evaluate soil physical and biological characteristics at two seasons of the year in agroecosystems producing vegetables and grains in the no-tillage system (NTS) for 3, 5, and 9 years compared to the conventional management system (CT) in the Atlantic Forest Biome, Brazil. Physical and organic matter attributes and carbon (C) and nitrogen (N) stock were evaluated. NTS showed, in general, greater total porosity than CT systems. The main differences between the systems were found in the organic attributes and C and N stocks. The content of microbial biomass C in NTS with 3, 5, and 9 years was 767.5, 326.5, and 210.0 mg·kg−1, while the areas with CT had 93.75, 78.25, and 45.75 mg·kg−1, respectively. The stock of C in winter at the 9NTS area was 33.0 and 41.5 Mg·ha−1, and the respective area in CT presented only 21.75 and 25.00 Mg·ha−1 in the depths of 0?10 and 10?20 cm, respectively. The metabolic quotient of the NTS areas did not differ from the reference ecosystems and is promoting lower C-CO2 emissions than the CT system. The adoption of NTS in vegetable prod... Mostrar Tudo |
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Palavras-Chave: |
Agricultura Convencional; Mata Atlântica. |
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Thesagro: |
Floresta Nativa; Plantio Direto. |
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Categoria do assunto: |
-- |
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URL: |
https://biblioteca.incaper.es.gov.br/digital/bitstream/item/4629/1/Applied-and-Environmental-Soil-Science.pdf
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Marc: |
LEADER 02260naa a2200205 a 4500
001 1025471
005 2024-02-27
008 2024 bl uuuu u00u1 u #d
100 1 $aMAURI, L. V. R.
245 $aOlericulture No-Till System at Mountain Region$bPhysical and Biological Attributes of the Soil.$h[electronic resource]
260 $c2024
520 $aThe production of vegetables and grains by the family farming in the mountains of the Atlantic Forest is characterized by intensive soil management with ploughing and harrowing practices. These practices are promoting hydric erosion and losses of soil quality in the region. In this context, the objective of this work was to evaluate soil physical and biological characteristics at two seasons of the year in agroecosystems producing vegetables and grains in the no-tillage system (NTS) for 3, 5, and 9 years compared to the conventional management system (CT) in the Atlantic Forest Biome, Brazil. Physical and organic matter attributes and carbon (C) and nitrogen (N) stock were evaluated. NTS showed, in general, greater total porosity than CT systems. The main differences between the systems were found in the organic attributes and C and N stocks. The content of microbial biomass C in NTS with 3, 5, and 9 years was 767.5, 326.5, and 210.0 mg·kg−1, while the areas with CT had 93.75, 78.25, and 45.75 mg·kg−1, respectively. The stock of C in winter at the 9NTS area was 33.0 and 41.5 Mg·ha−1, and the respective area in CT presented only 21.75 and 25.00 Mg·ha−1 in the depths of 0?10 and 10?20 cm, respectively. The metabolic quotient of the NTS areas did not differ from the reference ecosystems and is promoting lower C-CO2 emissions than the CT system. The adoption of NTS in vegetable production improves soil quality in family farm areas of mountains relief at the Atlantic Forest Biome.
650 $aFloresta Nativa
650 $aPlantio Direto
653 $aAgricultura Convencional
653 $aMata Atlântica
700 1 $aMENDONÇA, E. de Sá
700 1 $aBOLZAN, L. J.
700 1 $aANGELETTI, M. da P. A.
773 $tHindawi$gv. 2024, p. 1-11, 2024.
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Registro original: |
Biblioteca Rui Tendinha (BRT) |
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Biblioteca |
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Origem |
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Classificação |
Cutter |
Registro |
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Fechar
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Registro Completo |
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Biblioteca(s): |
Biblioteca Rui Tendinha. |
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Data corrente: |
06/08/2019 |
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Data da última atualização: |
06/08/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
- - - |
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Autoria: |
ESGARIO, J. G. M.; KROHLING, R. A.; VENTURA, J. A. |
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Afiliação: |
José G. M. Esgario, UFES; Renato A. Krohling, UFES; Jose Aires Ventura, Incaper. |
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Título: |
Deep learning for classification and severity estimation of Coffee leaf biotic stress. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
arXiv:1907.11561, p. 1-11, 26 jul 2019. |
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Idioma: |
Inglês |
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Conteúdo: |
Biotic stress consists of damage to plants through other living organisms. Efficient control of biotic agents such as pests and pathogens (viruses, fungi, bacteria, etc.) is closely related to the concept of agricultural sustainability. Agricultural sustainability promotes the development of new technologies that allow the reduction of environmental impacts, greater accessibility to farmers and, consequently, increase on productivity. The use of computer vision with deep learning methods allows the early and correct identification of the stress-causing agent. So, corrective measures can be applied as soon as possible to mitigate the problem. The objective of this work is to design an effective and practical system capable of identifying and estimating the stress severity caused by biotic agents on coffee leaves. The proposed approach consists of a multi-task system based on convolutional neural networks. In addition, we have explored the use of data augmentation techniques to make the system more robust and accurate. The experimental results obtained for classification as well as for severity estimation indicate that the proposed system might be a suitable tool to assist both experts and farmers in the identification and quantification of biotic
stresses in coffee plantations. |
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Thesaurus NAL: |
Agricultural sustainability; Biotic agents; Biotic stress; Coffee; Pathogens. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://biblioteca.incaper.es.gov.br/digital/bitstream/123456789/3652/1/deep-learning-classification-severty-coffee-ventura.pdf
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Marc: |
LEADER 01889naa a2200205 a 4500
001 1021504
005 2019-08-06
008 2019 bl uuuu u00u1 u #d
100 1 $aESGARIO, J. G. M.
245 $aDeep learning for classification and severity estimation of Coffee leaf biotic stress.$h[electronic resource]
260 $c2019
520 $aBiotic stress consists of damage to plants through other living organisms. Efficient control of biotic agents such as pests and pathogens (viruses, fungi, bacteria, etc.) is closely related to the concept of agricultural sustainability. Agricultural sustainability promotes the development of new technologies that allow the reduction of environmental impacts, greater accessibility to farmers and, consequently, increase on productivity. The use of computer vision with deep learning methods allows the early and correct identification of the stress-causing agent. So, corrective measures can be applied as soon as possible to mitigate the problem. The objective of this work is to design an effective and practical system capable of identifying and estimating the stress severity caused by biotic agents on coffee leaves. The proposed approach consists of a multi-task system based on convolutional neural networks. In addition, we have explored the use of data augmentation techniques to make the system more robust and accurate. The experimental results obtained for classification as well as for severity estimation indicate that the proposed system might be a suitable tool to assist both experts and farmers in the identification and quantification of biotic stresses in coffee plantations.
650 $aAgricultural sustainability
650 $aBiotic agents
650 $aBiotic stress
650 $aCoffee
650 $aPathogens
700 1 $aKROHLING, R. A.
700 1 $aVENTURA, J. A.
773 $tarXiv:1907.11561, p. 1-11, 26 jul 2019.
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Biblioteca Rui Tendinha (BRT) |
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