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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sudeste. Para informações adicionais entre em contato com cppse.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Pecuária Sudeste. |
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Data corrente: |
29/06/2021 |
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Data da última atualização: |
01/07/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
AZEVEDO, B. T.; VERCESI FILHO, A. E.; GUTMANIS, G.; VERISSIMO, C. J.; KATIKI, L. M.; OKINO, C. H.; OLIVEIRA, M. C. de S.; GIGLIOTI, R. |
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Afiliação: |
BIANCA TAINA AZEVEDO, IZ; ANIBAL EUGENIO VERCESI FILHO, IZ; GUNTA GUTMANIS, IZ; CECÍLIA JOSE VERISSIMO, IZ; LUCIANA MORITA KATIKI, IZ; CINTIA HIROMI OKINO, CPPSE; MARCIA CRISTINA DE SENA OLIVEIRA, CPPSE; RODRIGO GIGLIOTI, IZ. |
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Título: |
New sensitive methods for fraud detection in buffalo dairy products. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
International Dairy Journal, v.117, 105013, jun. 2021. |
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Páginas: |
9 p. |
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DOI: |
https://doi.org/10.1016/j.idairyj.2021.105013 |
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Idioma: |
Inglês |
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Conteúdo: |
The rising consumption of buffalo milk derivatives in recent years has highlighted the search for buffaloes in Brazilian livestock farming. These products have greater added value compared with common dairy milk products. Consequently, addition of variable amounts of cows' milk during manufacture of buffalo dairy products may occur, which constitutes fraud by product adulteration. Thus, the present study developed and standardised a DNA extraction protocol for application on different dairy derivatives and two methods based on real-time PCR for fraud identification: high-resolution melting (HRM) and rhAmp® SNP system. The extraction method allowed to extraction of DNA from eleven different dairy products. The sensitivity of the rhAmp method (1%) was five times higher than HRM assay (5%) and may be considered a better choice for identification of product adulteration when high sensitivity levels are required. |
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Palavras-Chave: |
DNA extraction; High resolution melting; Real time PCR; RhAmpR SNP system. |
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Thesaurus Nal: |
Buffalo milk. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 01769naa a2200289 a 4500
001 2132629
005 2021-07-01
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.idairyj.2021.105013$2DOI
100 1 $aAZEVEDO, B. T.
245 $aNew sensitive methods for fraud detection in buffalo dairy products.$h[electronic resource]
260 $c2021
300 $a9 p.
520 $aThe rising consumption of buffalo milk derivatives in recent years has highlighted the search for buffaloes in Brazilian livestock farming. These products have greater added value compared with common dairy milk products. Consequently, addition of variable amounts of cows' milk during manufacture of buffalo dairy products may occur, which constitutes fraud by product adulteration. Thus, the present study developed and standardised a DNA extraction protocol for application on different dairy derivatives and two methods based on real-time PCR for fraud identification: high-resolution melting (HRM) and rhAmp® SNP system. The extraction method allowed to extraction of DNA from eleven different dairy products. The sensitivity of the rhAmp method (1%) was five times higher than HRM assay (5%) and may be considered a better choice for identification of product adulteration when high sensitivity levels are required.
650 $aBuffalo milk
653 $aDNA extraction
653 $aHigh resolution melting
653 $aReal time PCR
653 $aRhAmpR SNP system
700 1 $aVERCESI FILHO, A. E.
700 1 $aGUTMANIS, G.
700 1 $aVERISSIMO, C. J.
700 1 $aKATIKI, L. M.
700 1 $aOKINO, C. H.
700 1 $aOLIVEIRA, M. C. de S.
700 1 $aGIGLIOTI, R.
773 $tInternational Dairy Journal$gv.117, 105013, jun. 2021.
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Registro original: |
Embrapa Pecuária Sudeste (CPPSE) |
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Voltar
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Registro Completo
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
28/08/2012 |
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Data da última atualização: |
05/03/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
MENDONÇA-SANTOS, M. de L.; SANTOS, H. G. dos; COELHO, M. R. |
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Afiliação: |
MARIA DE LOURDES M SANTOS BREFIN, CNPS; HUMBERTO GONCALVES DOS SANTOS, CNPS; MAURICIO RIZZATO COELHO, CNPS. |
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Título: |
Modelling and digital soil mapping of the organic carbon stock in the topsoil (0-10 cm) of Rio de Janeiro State, Brazil. |
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Ano de publicação: |
2008 |
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Fonte/Imprenta: |
In: GLOBAL WORKSHOP ON DIGITAL SOIL MAPPING, 3., 2008, Logan, Utah. Bridging research, production, and environmental applications: papers. Logan, UT: University of Utah, 2008. 1 CD-ROM. |
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Idioma: |
Inglês |
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Conteúdo: |
A soil database with 431 soil profiles of Rio de Janeiro State was used in the scope of a research project entitled "Quantifying the magnitude, spatial distribution and organic carbon in soils of Rio de Janeiro State, using quantitative modeling, GIS and database technologies" (Projeto Carbono_RJ, funded by FAPERJ - Carlos Chagas Filho Foundation for Research Support in Rio de Janeiro State). Considering that these soil data were collected to other purpose, there was only a few sparse data to soil bulk density, which is essential to estimate of soil organic carbon (SOC) stock. To face this problem, pedotransfer functions (PTFs) were estimated to be used in the modeling of organic soil carbon of topsoil (0-10 cm), using s.c.o.r.p.a.n model. The following environmental correlates were used as predictor variables: satellite data, lithology and soil maps, DEM (Digital Elevation Model) and its derivatives as source of information for these variables. This dataset, that represents the best organized soil dataset in Brazil, is working as a trial for learning/teaching of Digital Soil Mapping (DSM) using a variety of methods for predicting soil classes and their properties. The "f" of the equation was modeled by means of multilinear analysis and regression-kriging. Seven different models were built and compared through statistical methods. In a general way, all models performed well to predict the SOC stock. Nevertheless, model 6 (M6) was an exceptional model, presenting the smallest AIC e RMSE, due to the use of existing soil information (polygon soil map) as predictor variable, in addition to the variables used in the other models. The result obtained in M6 was used for mapping topsoil carbon stock at spatial resolution of 90 m. MenosA soil database with 431 soil profiles of Rio de Janeiro State was used in the scope of a research project entitled "Quantifying the magnitude, spatial distribution and organic carbon in soils of Rio de Janeiro State, using quantitative modeling, GIS and database technologies" (Projeto Carbono_RJ, funded by FAPERJ - Carlos Chagas Filho Foundation for Research Support in Rio de Janeiro State). Considering that these soil data were collected to other purpose, there was only a few sparse data to soil bulk density, which is essential to estimate of soil organic carbon (SOC) stock. To face this problem, pedotransfer functions (PTFs) were estimated to be used in the modeling of organic soil carbon of topsoil (0-10 cm), using s.c.o.r.p.a.n model. The following environmental correlates were used as predictor variables: satellite data, lithology and soil maps, DEM (Digital Elevation Model) and its derivatives as source of information for these variables. This dataset, that represents the best organized soil dataset in Brazil, is working as a trial for learning/teaching of Digital Soil Mapping (DSM) using a variety of methods for predicting soil classes and their properties. The "f" of the equation was modeled by means of multilinear analysis and regression-kriging. Seven different models were built and compared through statistical methods. In a general way, all models performed well to predict the SOC stock. Nevertheless, model 6 (M6) was an exceptional model, presenting the smallest... Mostrar Tudo |
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Thesagro: |
Carbono; Estoque. |
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Thesaurus NAL: |
Soil organic carbon. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/65152/1/Mendonca-Santos-Session-6.pdf
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Marc: |
LEADER 02449nam a2200169 a 4500
001 1932483
005 2020-03-05
008 2008 bl uuuu u00u1 u #d
100 1 $aMENDONÇA-SANTOS, M. de L.
245 $aModelling and digital soil mapping of the organic carbon stock in the topsoil (0-10 cm) of Rio de Janeiro State, Brazil.$h[electronic resource]
260 $aIn: GLOBAL WORKSHOP ON DIGITAL SOIL MAPPING, 3., 2008, Logan, Utah. Bridging research, production, and environmental applications: papers. Logan, UT: University of Utah, 2008. 1 CD-ROM.$c2008
520 $aA soil database with 431 soil profiles of Rio de Janeiro State was used in the scope of a research project entitled "Quantifying the magnitude, spatial distribution and organic carbon in soils of Rio de Janeiro State, using quantitative modeling, GIS and database technologies" (Projeto Carbono_RJ, funded by FAPERJ - Carlos Chagas Filho Foundation for Research Support in Rio de Janeiro State). Considering that these soil data were collected to other purpose, there was only a few sparse data to soil bulk density, which is essential to estimate of soil organic carbon (SOC) stock. To face this problem, pedotransfer functions (PTFs) were estimated to be used in the modeling of organic soil carbon of topsoil (0-10 cm), using s.c.o.r.p.a.n model. The following environmental correlates were used as predictor variables: satellite data, lithology and soil maps, DEM (Digital Elevation Model) and its derivatives as source of information for these variables. This dataset, that represents the best organized soil dataset in Brazil, is working as a trial for learning/teaching of Digital Soil Mapping (DSM) using a variety of methods for predicting soil classes and their properties. The "f" of the equation was modeled by means of multilinear analysis and regression-kriging. Seven different models were built and compared through statistical methods. In a general way, all models performed well to predict the SOC stock. Nevertheless, model 6 (M6) was an exceptional model, presenting the smallest AIC e RMSE, due to the use of existing soil information (polygon soil map) as predictor variable, in addition to the variables used in the other models. The result obtained in M6 was used for mapping topsoil carbon stock at spatial resolution of 90 m.
650 $aSoil organic carbon
650 $aCarbono
650 $aEstoque
700 1 $aSANTOS, H. G. dos
700 1 $aCOELHO, M. R.
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