Emprego de estratégias quimiométricas para a diferenciação de alimentos de acordo com as formas de produção.
Ano de defesa: | 2006 |
---|---|
Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Tese |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de São Carlos
|
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Química - PPGQ
|
Departamento: |
Não Informado pela instituição
|
País: |
BR
|
Palavras-chave em Português: | |
Área do conhecimento CNPq: | |
Link de acesso: | https://repositorio.ufscar.br/handle/ufscar/6079 |
Resumo: | The application of pattern recognition techniques such as principal component analysis and cluster analysis was evaluated for classification of foods according to their production mode (industrial or homemade and organically or conventionally produced), refine mode or geographical source. The main variables were the mineral contents of samples of coffee (roasted and green), vegetables, legumes, sugar, milk, sugar-cane spirit, beans, and rice. The concentrations of metals were determined by ICP OES or by GF AAS after microwave-assisted digestion or dilution. Other variables, such as nitrate and crude protein contents, were determined in vegetables and legumes samples. Nuclear magnetic resonance of 1H was applied to green coffee and beans to attempt to correlate chemical classes with production mode. Separations were obtained for differentiation between organic and conventional green coffees, and between instant soluble and roasted coffees. Attempts to correlate metals contents with geographical sources for coffee and sugar samples, and metals contents and production mode for vegetables, legumes, milks, sugar cane spirits, and rices were not successful. However, differentiation was observed for lettuces and cachaças based on geographical source, and for sugar samples based on the refine mode. Additionally, differentiation was also observed for lettuce samples based on the production mode, and nitrate was the main variable for differentiation. It was observed a trend towards the classification of beans according to the production mode based on NMR data set, however it is necessary to identify the chemical compounds that led to differentiation. According to these results, pattern recognition analyses were able to differentiate some important features in different samples based on their metals contents. Additionally, taking into account metals contents there was no appreciable difference between organically and conventionally produced foods. |
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Fernandes, Andréa PiresNóbrega, Joaquim de Araújohttp://lattes.cnpq.br/8833989058164529http://lattes.cnpq.br/39643131813514112016-06-02T20:34:05Z2007-08-012016-06-02T20:34:05Z2006-11-14FERNANDES, Andréa Pires. Chemometrics strategies applied to the diferentiation of foods according to their production mode.. 2006. 228 f. Tese (Doutorado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2006.https://repositorio.ufscar.br/handle/ufscar/6079The application of pattern recognition techniques such as principal component analysis and cluster analysis was evaluated for classification of foods according to their production mode (industrial or homemade and organically or conventionally produced), refine mode or geographical source. The main variables were the mineral contents of samples of coffee (roasted and green), vegetables, legumes, sugar, milk, sugar-cane spirit, beans, and rice. The concentrations of metals were determined by ICP OES or by GF AAS after microwave-assisted digestion or dilution. Other variables, such as nitrate and crude protein contents, were determined in vegetables and legumes samples. Nuclear magnetic resonance of 1H was applied to green coffee and beans to attempt to correlate chemical classes with production mode. Separations were obtained for differentiation between organic and conventional green coffees, and between instant soluble and roasted coffees. Attempts to correlate metals contents with geographical sources for coffee and sugar samples, and metals contents and production mode for vegetables, legumes, milks, sugar cane spirits, and rices were not successful. However, differentiation was observed for lettuces and cachaças based on geographical source, and for sugar samples based on the refine mode. Additionally, differentiation was also observed for lettuce samples based on the production mode, and nitrate was the main variable for differentiation. It was observed a trend towards the classification of beans according to the production mode based on NMR data set, however it is necessary to identify the chemical compounds that led to differentiation. According to these results, pattern recognition analyses were able to differentiate some important features in different samples based on their metals contents. Additionally, taking into account metals contents there was no appreciable difference between organically and conventionally produced foods.O presente trabalho avalia o emprego de métodos de reconhecimento de padrões não supervisionados, tais como análise de componentes principais e análise hierárquica de agrupamentos, para a classificação de alimentos de acordo com modo de produção, refino, processo de industrialização ou procedência. As principais variáveis empregadas foram os teores de constituintes minerais em amostras de café, verduras, legumes, açúcar, leite, cachaça, feijão e arroz. A concentração dos constituintes minerais nos diferentes grupos de amostra foi determinada por espectrometria de emissão óptica com plasma acoplado indutivamente ou por espectrometria de absorção atômica por forno de grafite após digestão assistida por radiação microondas ou diluição. Outras variáveis como concentração de nitrato e percentual de proteína bruta, foram determinadas para as amostras de verduras e legumes. Para as amostras de café verde e feijão foram utilizados espectros de RMN de 1H na tentativa de classificação por modo de produção. Constatou-se diferenciação entre os modos de produção para as amostras de café verde e torrado e entre cafés solúveis e torrados. Tentativas de correlacionar a concentração de metais com a origem geográfica dos cafés torrados e modo de produção (orgânica ou convencional) de açúcar, verduras e legumes, leite, cachaça e arroz não foram bem sucedidas. Obtiveram-se diferenciações por refino para as amostras de açúcar e por origem geográfica para as amostras de alface e cachaça. No caso das amostras de alface há uma tendência de diferenciação por modo de produção, sendo a variável teor de nitrato a maior responsável. Há uma tendência de diferenciação também para as amostras de feijão, considerando os dados obtidos por RMN, contudo é necessário identificar quais compostos são responsáveis pela diferenciação. De acordo com os resultados, a análise por reconhecimento de padrões foi capaz de diferenciar importantes características nas diferentes amostras com base nos teores de constituintes inorgânicos. Constatou-se que, em geral, alimentos produzidos organicamente não apresentaram diferenças apreciáveis quando comparados à produção convencional.application/pdfporUniversidade Federal de São CarlosPrograma de Pós-Graduação em Química - PPGQUFSCarBRPreparação de amostra (Química analítica)QuimiometriaICP OESMicroondasAlimentosCIENCIAS EXATAS E DA TERRA::QUIMICA::QUIMICA ANALITICAEmprego de estratégias quimiométricas para a diferenciação de alimentos de acordo com as formas de produção.Chemometrics strategies applied to the diferentiation of foods according to their production mode.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFSCARinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCARORIGINALTeseAPF.pdfapplication/pdf1919945https://{{ getenv "DSPACE_HOST" "repositorio.ufscar.br" }}/bitstream/ufscar/6079/1/TeseAPF.pdfc7be1a284fe2f15f46c8b687e1eb6a57MD51THUMBNAILTeseAPF.pdf.jpgTeseAPF.pdf.jpgIM Thumbnailimage/jpeg9168https://{{ getenv "DSPACE_HOST" "repositorio.ufscar.br" }}/bitstream/ufscar/6079/2/TeseAPF.pdf.jpg7e2bd63ac3a7c4cf995ee8d46fd48da4MD52ufscar/60792019-09-11 02:56:42.829oai:repositorio.ufscar.br:ufscar/6079Repositório InstitucionalPUBhttps://repositorio.ufscar.br/oai/requestopendoar:43222023-05-25T12:50:48.412788Repositório Institucional da UFSCAR - Universidade Federal de São Carlos (UFSCAR)false |
dc.title.por.fl_str_mv |
Emprego de estratégias quimiométricas para a diferenciação de alimentos de acordo com as formas de produção. |
dc.title.alternative.eng.fl_str_mv |
Chemometrics strategies applied to the diferentiation of foods according to their production mode. |
title |
Emprego de estratégias quimiométricas para a diferenciação de alimentos de acordo com as formas de produção. |
spellingShingle |
Emprego de estratégias quimiométricas para a diferenciação de alimentos de acordo com as formas de produção. Fernandes, Andréa Pires Preparação de amostra (Química analítica) Quimiometria ICP OES Microondas Alimentos CIENCIAS EXATAS E DA TERRA::QUIMICA::QUIMICA ANALITICA |
title_short |
Emprego de estratégias quimiométricas para a diferenciação de alimentos de acordo com as formas de produção. |
title_full |
Emprego de estratégias quimiométricas para a diferenciação de alimentos de acordo com as formas de produção. |
title_fullStr |
Emprego de estratégias quimiométricas para a diferenciação de alimentos de acordo com as formas de produção. |
title_full_unstemmed |
Emprego de estratégias quimiométricas para a diferenciação de alimentos de acordo com as formas de produção. |
title_sort |
Emprego de estratégias quimiométricas para a diferenciação de alimentos de acordo com as formas de produção. |
author |
Fernandes, Andréa Pires |
author_facet |
Fernandes, Andréa Pires |
author_role |
author |
dc.contributor.authorlattes.por.fl_str_mv |
http://lattes.cnpq.br/3964313181351411 |
dc.contributor.author.fl_str_mv |
Fernandes, Andréa Pires |
dc.contributor.advisor1.fl_str_mv |
Nóbrega, Joaquim de Araújo |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/8833989058164529 |
contributor_str_mv |
Nóbrega, Joaquim de Araújo |
dc.subject.por.fl_str_mv |
Preparação de amostra (Química analítica) Quimiometria ICP OES Microondas Alimentos |
topic |
Preparação de amostra (Química analítica) Quimiometria ICP OES Microondas Alimentos CIENCIAS EXATAS E DA TERRA::QUIMICA::QUIMICA ANALITICA |
dc.subject.cnpq.fl_str_mv |
CIENCIAS EXATAS E DA TERRA::QUIMICA::QUIMICA ANALITICA |
description |
The application of pattern recognition techniques such as principal component analysis and cluster analysis was evaluated for classification of foods according to their production mode (industrial or homemade and organically or conventionally produced), refine mode or geographical source. The main variables were the mineral contents of samples of coffee (roasted and green), vegetables, legumes, sugar, milk, sugar-cane spirit, beans, and rice. The concentrations of metals were determined by ICP OES or by GF AAS after microwave-assisted digestion or dilution. Other variables, such as nitrate and crude protein contents, were determined in vegetables and legumes samples. Nuclear magnetic resonance of 1H was applied to green coffee and beans to attempt to correlate chemical classes with production mode. Separations were obtained for differentiation between organic and conventional green coffees, and between instant soluble and roasted coffees. Attempts to correlate metals contents with geographical sources for coffee and sugar samples, and metals contents and production mode for vegetables, legumes, milks, sugar cane spirits, and rices were not successful. However, differentiation was observed for lettuces and cachaças based on geographical source, and for sugar samples based on the refine mode. Additionally, differentiation was also observed for lettuce samples based on the production mode, and nitrate was the main variable for differentiation. It was observed a trend towards the classification of beans according to the production mode based on NMR data set, however it is necessary to identify the chemical compounds that led to differentiation. According to these results, pattern recognition analyses were able to differentiate some important features in different samples based on their metals contents. Additionally, taking into account metals contents there was no appreciable difference between organically and conventionally produced foods. |
publishDate |
2006 |
dc.date.issued.fl_str_mv |
2006-11-14 |
dc.date.available.fl_str_mv |
2007-08-01 2016-06-02T20:34:05Z |
dc.date.accessioned.fl_str_mv |
2016-06-02T20:34:05Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
FERNANDES, Andréa Pires. Chemometrics strategies applied to the diferentiation of foods according to their production mode.. 2006. 228 f. Tese (Doutorado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2006. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufscar.br/handle/ufscar/6079 |
identifier_str_mv |
FERNANDES, Andréa Pires. Chemometrics strategies applied to the diferentiation of foods according to their production mode.. 2006. 228 f. Tese (Doutorado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2006. |
url |
https://repositorio.ufscar.br/handle/ufscar/6079 |
dc.language.iso.fl_str_mv |
por |
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por |
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openAccess |
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application/pdf |
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Universidade Federal de São Carlos |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Química - PPGQ |
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UFSCar |
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BR |
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Universidade Federal de São Carlos |
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