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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
01/06/2018 |
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Data da última atualização: |
06/06/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
TAVARES, R. L. M.; OLIVEIRA, S. R. de M.; BARROS, F. M. M. de; FARHATE, C. V. V.; SOUZA, Z. M. de; LA SCALA JUNIOR, N. |
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Afiliação: |
ROSE LUIZA MORAES TAVARES, Rio Verde University; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; FLÁVIO MARGARITO MARTINS DE BARROS, Feagri/Unicamp; CAMILA VIANA VIEIRA FARHATE, Feagri/Unicamp; ZIGOMAR MENEZES DE SOUZA, Feagri/Unicamp; NEWTON LA SCALA JUNIOR, FCAV/Unesp. |
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Título: |
Prediction of soil CO2 flux in sugarcane management systems using the Random Forest approach. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Scientia Agricola, Piracicaba, v. 74, n. 4, p. 281-287, July/Aug. 2018. |
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DOI: |
http://dx.doi.org/10.1590/1678-992X-2017-0095 |
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Idioma: |
Inglês |
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Conteúdo: |
ABSTRACT: The Random Forest algorithm is a data mining technique used for classifying attributes in order of importance to explain the variation in an attribute-target, as soil CO2 flux. This study aimed to identify prediction of soil CO2 flux variables in management systems of sugarcane through the machine-learning algorithm called Random Forest. Two different management areas of sugarcane in the state of São Paulo, Brazil, were selected: burned and green. In each area, we assembled a sampling grid with 81 georeferenced points to assess soil CO2 flux through automated portable soil gas chamber with measuring spectroscopy in the infrared during the dry season of 2011 and the rainy season of 2012. In addition, we sampled the soil to evaluate physical, chemical, and microbiological attributes. For data interpretation, we used the Random Forest algorithm, based on the combination of predicted decision trees (machine learning algorithms) in which every tree depends on the values of a random vector sampled independently with the same distribution to all the trees of the forest. The results indicated that clay content in the soil was the most important attribute to explain the CO2 flux in the areas studied during the evaluated period. The use of the Random Forest algorithm originated a model with a good fit (R2 = 0.80) for predicted and observed values. |
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Palavras-Chave: |
Data mining; Green sugarcane; Mineração de dados; Random Forest algorithm. |
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Thesagro: |
Argila; Cana de Açúcar; Saccharum Officinarum. |
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Thesaurus Nal: |
Clay; Soil organic carbon; Soil respiration; Sugarcane. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://www.alice.cnptia.embrapa.br/alice/bitstream/doc/1092118/1/APPredictionTavaresetal.pdf
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Marc: |
LEADER 02375naa a2200325 a 4500
001 2092118
005 2018-06-06
008 2018 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.1590/1678-992X-2017-0095$2DOI
100 1 $aTAVARES, R. L. M.
245 $aPrediction of soil CO2 flux in sugarcane management systems using the Random Forest approach.$h[electronic resource]
260 $c2018
520 $aABSTRACT: The Random Forest algorithm is a data mining technique used for classifying attributes in order of importance to explain the variation in an attribute-target, as soil CO2 flux. This study aimed to identify prediction of soil CO2 flux variables in management systems of sugarcane through the machine-learning algorithm called Random Forest. Two different management areas of sugarcane in the state of São Paulo, Brazil, were selected: burned and green. In each area, we assembled a sampling grid with 81 georeferenced points to assess soil CO2 flux through automated portable soil gas chamber with measuring spectroscopy in the infrared during the dry season of 2011 and the rainy season of 2012. In addition, we sampled the soil to evaluate physical, chemical, and microbiological attributes. For data interpretation, we used the Random Forest algorithm, based on the combination of predicted decision trees (machine learning algorithms) in which every tree depends on the values of a random vector sampled independently with the same distribution to all the trees of the forest. The results indicated that clay content in the soil was the most important attribute to explain the CO2 flux in the areas studied during the evaluated period. The use of the Random Forest algorithm originated a model with a good fit (R2 = 0.80) for predicted and observed values.
650 $aClay
650 $aSoil organic carbon
650 $aSoil respiration
650 $aSugarcane
650 $aArgila
650 $aCana de Açúcar
650 $aSaccharum Officinarum
653 $aData mining
653 $aGreen sugarcane
653 $aMineração de dados
653 $aRandom Forest algorithm
700 1 $aOLIVEIRA, S. R. de M.
700 1 $aBARROS, F. M. M. de
700 1 $aFARHATE, C. V. V.
700 1 $aSOUZA, Z. M. de
700 1 $aLA SCALA JUNIOR, N.
773 $tScientia Agricola, Piracicaba$gv. 74, n. 4, p. 281-287, July/Aug. 2018.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Florestas. Para informações adicionais entre em contato com cnpf.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
02/10/2008 |
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Data da última atualização: |
02/10/2008 |
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Autoria: |
SANTOS, E. M. R.; FRANKLIN, E.; LUIZÃO, F. J. |
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Título: |
Litter manipulation and associated invertebrate fauna in secondary forest, central Amazonia, Brazil. |
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Ano de publicação: |
2008 |
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Fonte/Imprenta: |
In: INTERNATIONAL COLLOQUIUM ON SOIL ZOOLOGY, 15; INTERNATIONAL COLLOQUIUM ON APTERYGOTA, 12., 2008, Curitiba. Biodiversity, conservation and sustainabele management of soil animal: abstracts. Colombo: Embrapa Florestas. Editors: George Gardner Brown; Klaus Dieter Sautter; Renato Marques; Amarildo Pasini. 1 CD-ROM. |
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Idioma: |
Inglês |
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Conteúdo: |
Plant litter from selected tree species have been used for improving soil productivity in low-input
systems of secondary vegetation in central Amazon, leading to different conditions for the soil
organisms. Soil animal assemblages were monitored to test the effects of adding litter types of
contrasting nutritional quality, and periods of exposure on the development of the invertebrate
community. We established four second growth plots with 80 subplots of 3 m2 from which the
original litter was removed and replaced in 60 subplots. Twenty subplots received Hevea
brasiliensis leaves, 20 others Carapa guianensis leaves, and another 20 an equal mixture of H.
brasiliensis, C. guianensis and Vismia guianensis. Twenty subplots were left with the original
litter. Litter and mineral soil (5 cm deep) sub-horizons were collected after 45, 100, 160, 240
and 300 days of exposure. The invertebrates were extracted using Kempson apparatus. At the
day 210th, the litter was replenished to match the surrounding litter. Regression analyses showed
no significant effect of litter type, but the period of exposure did affect the community in both subhorizons.
Only after the litter replacement, the type of litter and periods of exposure affected the
community in the litter sub-horizon. Because we tried to isolate the effects of litter composition
from other large-scale phenomena, several factors interfered in the experiment and potential
problems were identified to optimize the investigation. The results suggest that the sampling
design must be improved by using a larger number of subsamples for each kind of litter within
each plot. As the scale of the experiments was too small, future manipulations should be done
on much larger scale so that their effects on ecosystem processes can be evaluated, and the
replicates need to be spread over larger areas to capture the natural variations within ecosystems.
Financial support: SHIFT/ENV 052, CNPq/PNOPG: 55 04 09/01-7, CAPES. MenosPlant litter from selected tree species have been used for improving soil productivity in low-input
systems of secondary vegetation in central Amazon, leading to different conditions for the soil
organisms. Soil animal assemblages were monitored to test the effects of adding litter types of
contrasting nutritional quality, and periods of exposure on the development of the invertebrate
community. We established four second growth plots with 80 subplots of 3 m2 from which the
original litter was removed and replaced in 60 subplots. Twenty subplots received Hevea
brasiliensis leaves, 20 others Carapa guianensis leaves, and another 20 an equal mixture of H.
brasiliensis, C. guianensis and Vismia guianensis. Twenty subplots were left with the original
litter. Litter and mineral soil (5 cm deep) sub-horizons were collected after 45, 100, 160, 240
and 300 days of exposure. The invertebrates were extracted using Kempson apparatus. At the
day 210th, the litter was replenished to match the surrounding litter. Regression analyses showed
no significant effect of litter type, but the period of exposure did affect the community in both subhorizons.
Only after the litter replacement, the type of litter and periods of exposure affected the
community in the litter sub-horizon. Because we tried to isolate the effects of litter composition
from other large-scale phenomena, several factors interfered in the experiment and potential
problems were identified to optimize the investigation. The res... Mostrar Tudo |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02680naa a2200145 a 4500
001 1315004
005 2008-10-02
008 2008 bl uuuu u00u1 u #d
100 1 $aSANTOS, E. M. R.
245 $aLitter manipulation and associated invertebrate fauna in secondary forest, central Amazonia, Brazil.
260 $c2008
520 $aPlant litter from selected tree species have been used for improving soil productivity in low-input systems of secondary vegetation in central Amazon, leading to different conditions for the soil organisms. Soil animal assemblages were monitored to test the effects of adding litter types of contrasting nutritional quality, and periods of exposure on the development of the invertebrate community. We established four second growth plots with 80 subplots of 3 m2 from which the original litter was removed and replaced in 60 subplots. Twenty subplots received Hevea brasiliensis leaves, 20 others Carapa guianensis leaves, and another 20 an equal mixture of H. brasiliensis, C. guianensis and Vismia guianensis. Twenty subplots were left with the original litter. Litter and mineral soil (5 cm deep) sub-horizons were collected after 45, 100, 160, 240 and 300 days of exposure. The invertebrates were extracted using Kempson apparatus. At the day 210th, the litter was replenished to match the surrounding litter. Regression analyses showed no significant effect of litter type, but the period of exposure did affect the community in both subhorizons. Only after the litter replacement, the type of litter and periods of exposure affected the community in the litter sub-horizon. Because we tried to isolate the effects of litter composition from other large-scale phenomena, several factors interfered in the experiment and potential problems were identified to optimize the investigation. The results suggest that the sampling design must be improved by using a larger number of subsamples for each kind of litter within each plot. As the scale of the experiments was too small, future manipulations should be done on much larger scale so that their effects on ecosystem processes can be evaluated, and the replicates need to be spread over larger areas to capture the natural variations within ecosystems. Financial support: SHIFT/ENV 052, CNPq/PNOPG: 55 04 09/01-7, CAPES.
700 1 $aFRANKLIN, E.
700 1 $aLUIZÃO, F. J.
773 $tIn: INTERNATIONAL COLLOQUIUM ON SOIL ZOOLOGY, 15; INTERNATIONAL COLLOQUIUM ON APTERYGOTA, 12., 2008, Curitiba. Biodiversity, conservation and sustainabele management of soil animal: abstracts. Colombo: Embrapa Florestas. Editors: George Gardner Brown; Klaus Dieter Sautter; Renato Marques; Amarildo Pasini. 1 CD-ROM.
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