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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
13/02/2019 |
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Data da última atualização: |
13/02/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
FARHATE, C. V. V.; SOUZA, Z. M. de; OLIVEIRA, S. R. de M.; CARVALHO, J. L. N.; LA SCALA JÚNIOR, N.; SANTOS, A. P. G. |
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Afiliação: |
CAMILA VIANA VIEIRA FARHATE, Feagri/Unicamp; ZIGOMAR MENEZES DE SOUZA, Feagri/Unicamp; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA, Feagri/Unicamp; JOÃO LUÍS NUNES CARVALHO, CNPEM; NEWTON LA SCALA JÚNIOR, Unesp; ANA PAULA GUIMARÃES SANTOS, Feagri/Unicamp. |
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Título: |
Classification of soil respiration in areas of sugarcane renewal using decision tree. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Scientia Agricola, v. 75, n. 3, p. 216-224, May/June 2018. |
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DOI: |
http://dx.doi.org/10.1590/1678-992X-2016-0473 |
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Idioma: |
Inglês |
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Conteúdo: |
ABSTRACT: The use of data mining is a promising alternative to predict soil respiration from correlated variables. Our objective was to build a model using variable selection and decision tree induction to predict different levels of soil respiration, taking into account physical, chemical and microbiological variables of soil as well as precipitation in renewal of sugarcane areas. The original dataset was composed of 19 variables (18 independent variables and one dependent (or response) variable). The variable-target refers to soil respiration as the target classification. Due to a large number of variables, a procedure for variable selection was conducted to remove those with low correlation with the variable-target. For that purpose, four approaches of variable selection were evaluated: no variable selection, correlation-based feature selection (CFS), chisquare method (χ2) and Wrapper. To classify soil respiration, we used the decision tree induction technique available in the Weka software package. Our results showed that data mining techniques allow the development of a model for soil respiration classification with accuracy of 81 %, resulting in a knowledge base composed of 27 rules for prediction of soil respiration. In particular, the wrapper method for variable selection identified a subset of only five variables out of 18 available in the original dataset, and they had the following order of influence in determining soil respiration: soil temperature > precipitation > macroporosity > soil moisture > potential acidity. MenosABSTRACT: The use of data mining is a promising alternative to predict soil respiration from correlated variables. Our objective was to build a model using variable selection and decision tree induction to predict different levels of soil respiration, taking into account physical, chemical and microbiological variables of soil as well as precipitation in renewal of sugarcane areas. The original dataset was composed of 19 variables (18 independent variables and one dependent (or response) variable). The variable-target refers to soil respiration as the target classification. Due to a large number of variables, a procedure for variable selection was conducted to remove those with low correlation with the variable-target. For that purpose, four approaches of variable selection were evaluated: no variable selection, correlation-based feature selection (CFS), chisquare method (χ2) and Wrapper. To classify soil respiration, we used the decision tree induction technique available in the Weka software package. Our results showed that data mining techniques allow the development of a model for soil respiration classification with accuracy of 81 %, resulting in a knowledge base composed of 27 rules for prediction of soil respiration. In particular, the wrapper method for variable selection identified a subset of only five variables out of 18 available in the original dataset, and they had the following order of influence in determining soil respiration: soil temperature > precipi... Mostrar Tudo |
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Palavras-Chave: |
Árvore de decisão; Data mining; Decision tree; Emissão de gás carbônico no solo; Matéria orgânica no solo; Mineração de dados; Seleção de variável; Temperatura no solo; Variable selection. |
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Thesagro: |
Respiração do Solo. |
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Thesaurus Nal: |
Carbon dioxide; Soil organic matter; Soil temperature. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/192660/1/AP-Classification-soil-Farhate.pdf
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Marc: |
LEADER 02675naa a2200349 a 4500
001 2105884
005 2019-02-13
008 2018 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.1590/1678-992X-2016-0473$2DOI
100 1 $aFARHATE, C. V. V.
245 $aClassification of soil respiration in areas of sugarcane renewal using decision tree.$h[electronic resource]
260 $c2018
520 $aABSTRACT: The use of data mining is a promising alternative to predict soil respiration from correlated variables. Our objective was to build a model using variable selection and decision tree induction to predict different levels of soil respiration, taking into account physical, chemical and microbiological variables of soil as well as precipitation in renewal of sugarcane areas. The original dataset was composed of 19 variables (18 independent variables and one dependent (or response) variable). The variable-target refers to soil respiration as the target classification. Due to a large number of variables, a procedure for variable selection was conducted to remove those with low correlation with the variable-target. For that purpose, four approaches of variable selection were evaluated: no variable selection, correlation-based feature selection (CFS), chisquare method (χ2) and Wrapper. To classify soil respiration, we used the decision tree induction technique available in the Weka software package. Our results showed that data mining techniques allow the development of a model for soil respiration classification with accuracy of 81 %, resulting in a knowledge base composed of 27 rules for prediction of soil respiration. In particular, the wrapper method for variable selection identified a subset of only five variables out of 18 available in the original dataset, and they had the following order of influence in determining soil respiration: soil temperature > precipitation > macroporosity > soil moisture > potential acidity.
650 $aCarbon dioxide
650 $aSoil organic matter
650 $aSoil temperature
650 $aRespiração do Solo
653 $aÁrvore de decisão
653 $aData mining
653 $aDecision tree
653 $aEmissão de gás carbônico no solo
653 $aMatéria orgânica no solo
653 $aMineração de dados
653 $aSeleção de variável
653 $aTemperatura no solo
653 $aVariable selection
700 1 $aSOUZA, Z. M. de
700 1 $aOLIVEIRA, S. R. de M.
700 1 $aCARVALHO, J. L. N.
700 1 $aLA SCALA JÚNIOR, N.
700 1 $aSANTOS, A. P. G.
773 $tScientia Agricola$gv. 75, n. 3, p. 216-224, May/June 2018.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agrobiologia. Para informações adicionais entre em contato com cnpab.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agrobiologia. |
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Data corrente: |
09/11/2021 |
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Data da última atualização: |
09/11/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
SOARES, I. C.; PACHECO, R. S.; SILVA, C. G. N. da; SANTOS, R. S.; BALDANI, J. I.; URQUIAGA, S.; VIDAL, M. S.; ARAUJO, J. L. S. de. |
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Afiliação: |
ISIS CAPELLA SOARES, UFRRJ; RAFAEL SANCHES PACHECO, UFRRJ; CLEUDISON GABRIEL NASCIMENTO DA SILVA, UFLA; RAFAEL SALAZAR SANTOS, UFRRJ; JOSE IVO BALDANI, CNPAB; SEGUNDO SACRAMENTO U CABALLERO, CNPAB; MARCIA SOARES VIDAL, CNPAB; JEAN LUIZ SIMOES DE ARAUJO, CNPAB. |
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Título: |
Real-time PCR method to quantify Sp245 strain of Azospirillum baldaniorum on Brachiaria grasses under field conditions. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Plant and Soil, 06 September 2021 |
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ISSN: |
0032-079X |
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DOI: |
https://doi.org/10.1007/s11104-021-05137-y |
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Idioma: |
Inglês |
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Conteúdo: |
Bacterial quantification by qPCR is considered the gold standard for microbial molecular diagnosis. However, a fundamental pre-requisite in this methodology is the designing of specific primers for the bacterium of interest. With the increase in bacterial genome sequencing data in the recent years, it has become possible to design specific primers that can be used to quantify different strains of the same bacterial species. Methods: To develop a real-time PCR (qPCR) protocol for the specific quantification of Azospirillum baldaniorum Sp245 strain (old Azospirillum brasilense), the Sp245 genome sequence was fragmented into small contigs with 500 base pairs each, and analyzed for similarity against the NCBI non-redundant database. A. baldaniorum-specific contigs were used to design the primers. The best pair of primers was used to quantify these bacteria after inoculation in different cultivars of Brachiaria, grown under field conditions. Results: Our results showed that the primer pair Sp245p10 was highly specific for the Sp245 strain in the Brachiaria root and shoot field under different conditions. The qPCR assay using these primers showed differences among cultivars in the number of bacteria detected in plants after inoculation. Additionally, the number of bacteria observed in the roots was higher than that in the shoots. Conclusion: The qPCR methodology using a Sp245 strain-specific primer may be used to monitor A. baldaniorum inoculated into other plants and may find potential application in field experiments. MenosBacterial quantification by qPCR is considered the gold standard for microbial molecular diagnosis. However, a fundamental pre-requisite in this methodology is the designing of specific primers for the bacterium of interest. With the increase in bacterial genome sequencing data in the recent years, it has become possible to design specific primers that can be used to quantify different strains of the same bacterial species. Methods: To develop a real-time PCR (qPCR) protocol for the specific quantification of Azospirillum baldaniorum Sp245 strain (old Azospirillum brasilense), the Sp245 genome sequence was fragmented into small contigs with 500 base pairs each, and analyzed for similarity against the NCBI non-redundant database. A. baldaniorum-specific contigs were used to design the primers. The best pair of primers was used to quantify these bacteria after inoculation in different cultivars of Brachiaria, grown under field conditions. Results: Our results showed that the primer pair Sp245p10 was highly specific for the Sp245 strain in the Brachiaria root and shoot field under different conditions. The qPCR assay using these primers showed differences among cultivars in the number of bacteria detected in plants after inoculation. Additionally, the number of bacteria observed in the roots was higher than that in the shoots. Conclusion: The qPCR methodology using a Sp245 strain-specific primer may be used to monitor A. baldaniorum inoculated into other plants and may find pot... Mostrar Tudo |
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Palavras-Chave: |
Azospirillum baldanioru; Plant growth promoting bacteria; Quantification; Signal grass. |
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Categoria do assunto: |
S Ciências Biológicas |
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Marc: |
LEADER 02397naa a2200277 a 4500
001 2135952
005 2021-11-09
008 2021 bl uuuu u00u1 u #d
022 $a0032-079X
024 7 $ahttps://doi.org/10.1007/s11104-021-05137-y$2DOI
100 1 $aSOARES, I. C.
245 $aReal-time PCR method to quantify Sp245 strain of Azospirillum baldaniorum on Brachiaria grasses under field conditions.$h[electronic resource]
260 $c2021
520 $aBacterial quantification by qPCR is considered the gold standard for microbial molecular diagnosis. However, a fundamental pre-requisite in this methodology is the designing of specific primers for the bacterium of interest. With the increase in bacterial genome sequencing data in the recent years, it has become possible to design specific primers that can be used to quantify different strains of the same bacterial species. Methods: To develop a real-time PCR (qPCR) protocol for the specific quantification of Azospirillum baldaniorum Sp245 strain (old Azospirillum brasilense), the Sp245 genome sequence was fragmented into small contigs with 500 base pairs each, and analyzed for similarity against the NCBI non-redundant database. A. baldaniorum-specific contigs were used to design the primers. The best pair of primers was used to quantify these bacteria after inoculation in different cultivars of Brachiaria, grown under field conditions. Results: Our results showed that the primer pair Sp245p10 was highly specific for the Sp245 strain in the Brachiaria root and shoot field under different conditions. The qPCR assay using these primers showed differences among cultivars in the number of bacteria detected in plants after inoculation. Additionally, the number of bacteria observed in the roots was higher than that in the shoots. Conclusion: The qPCR methodology using a Sp245 strain-specific primer may be used to monitor A. baldaniorum inoculated into other plants and may find potential application in field experiments.
653 $aAzospirillum baldanioru
653 $aPlant growth promoting bacteria
653 $aQuantification
653 $aSignal grass
700 1 $aPACHECO, R. S.
700 1 $aSILVA, C. G. N. da
700 1 $aSANTOS, R. S.
700 1 $aBALDANI, J. I.
700 1 $aURQUIAGA, S.
700 1 $aVIDAL, M. S.
700 1 $aARAUJO, J. L. S. de
773 $tPlant and Soil, 06 September 2021
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