Detecção de pesticidas em cascas de alimentos por espectroscopia Raman amplificada por superfície e quimiometria
| Ano de defesa: | 2024 |
|---|---|
| Autor(a) principal: | |
| Orientador(a): | |
| Banca de defesa: | |
| Tipo de documento: | Dissertação |
| Tipo de acesso: | Acesso aberto |
| dARK ID: | ark:/80033/0013000001z93 |
| Idioma: | por |
| Instituição de defesa: |
Universidade Federal do Paraná
|
| Programa de Pós-Graduação: |
Programa de Pós Graduação em Química
|
| Departamento: |
Universidade Federal do Paraná
|
| País: |
Brasil
|
| Palavras-chave em Português: | |
| Área do conhecimento CNPq: | |
| Link de acesso: | https://deposita.ibict.br/handle/deposita/757 |
Resumo: | The development of efficient methodologies for detection, elimination, and control of health risks caused by harmful substances, such as pesticides, is a topic of great relevance for scientific research. In this context, this work aims to optmize the synthesis of thin film of reduced graphene oxide with silver nanoparticles (rGO/AgNPs) through the liquid-liquid interfacial route (LLIR). The optimization seeks to intensity the SERS (Surface-enhanced Raman Scattering) signal for the detection of 4-aminothiophenol (4-ATP) and, subsequently, the pesticide ametryn (AMT). 4 ATP was employed as a probe to identify and evaluate the parameters influencing the variation of the SERS signal. Thus, a fractional factorial design and, subsequently a Box-Behnken design were used to investigate the following factors: concentration and masses of reagents, reaction times, and rotation speed. The values obtained for the optimal condition were: 7.0 mg of silver nitrate, 1000 RPM, 60 minutes of dispersion time, 150 mg of sodium borohydride, 0.01 mg mL-1 of graphene oxide, and 45 minutes of reduction time. Based on the results, an empirical response surface model was constructed to determine the ideal conditions for the material synthesis. The model showed a good data fit, but the regression was not considered significant. There was an increase in the Raman scattering approximately 21,500 times greater compared of the pure 4-ATP solution. The material was characterized by scanning electron microscopy (SEM), and UV-Vis and Raman spectroscopies. The characterization techniques indicated the growth and agglomeration of AgNPs on graphene sheets, which contributes to the increase SERS intensity. After that, the SERS substrate was used to detect the herbicide directly deposited on food peels, such as apple and potato. Thus, to ensure the reproducibility of signal acquisition, hyperspectral imaging measurements of potato and apple peels with different concentrations of ametryn were performed. From the hyperspectral images, it was possible to detect ametryn at low concentrations (1.0x10-7 mol L-1) with minimal sample preparation |
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Soares, Frederico Luis Felipehttp://lattes.cnpq.br/1064620847107189Zarbin, Aldo José Gorgattihttp://lattes.cnpq.br/4008495434236758http://lattes.cnpq.br/4602597827266974Silva, Anderson Victor2025-05-09T17:28:18Z2024https://deposita.ibict.br/handle/deposita/757ark:/80033/0013000001z93The development of efficient methodologies for detection, elimination, and control of health risks caused by harmful substances, such as pesticides, is a topic of great relevance for scientific research. In this context, this work aims to optmize the synthesis of thin film of reduced graphene oxide with silver nanoparticles (rGO/AgNPs) through the liquid-liquid interfacial route (LLIR). The optimization seeks to intensity the SERS (Surface-enhanced Raman Scattering) signal for the detection of 4-aminothiophenol (4-ATP) and, subsequently, the pesticide ametryn (AMT). 4 ATP was employed as a probe to identify and evaluate the parameters influencing the variation of the SERS signal. Thus, a fractional factorial design and, subsequently a Box-Behnken design were used to investigate the following factors: concentration and masses of reagents, reaction times, and rotation speed. The values obtained for the optimal condition were: 7.0 mg of silver nitrate, 1000 RPM, 60 minutes of dispersion time, 150 mg of sodium borohydride, 0.01 mg mL-1 of graphene oxide, and 45 minutes of reduction time. Based on the results, an empirical response surface model was constructed to determine the ideal conditions for the material synthesis. The model showed a good data fit, but the regression was not considered significant. There was an increase in the Raman scattering approximately 21,500 times greater compared of the pure 4-ATP solution. The material was characterized by scanning electron microscopy (SEM), and UV-Vis and Raman spectroscopies. The characterization techniques indicated the growth and agglomeration of AgNPs on graphene sheets, which contributes to the increase SERS intensity. After that, the SERS substrate was used to detect the herbicide directly deposited on food peels, such as apple and potato. Thus, to ensure the reproducibility of signal acquisition, hyperspectral imaging measurements of potato and apple peels with different concentrations of ametryn were performed. From the hyperspectral images, it was possible to detect ametryn at low concentrations (1.0x10-7 mol L-1) with minimal sample preparationO desenvolvimento de metodologias eficientes para detecção, eliminação e controle de riscos à saúde causados por substâncias nocivas, como pesticidas, é um tema de grande relevância para a pesquisa científica. Neste contexto, este trabalho visa otimizar a síntese de um filme fino de óxido de grafeno reduzido com nanopartículas de prata (rGO/AgNPs) por meio da rota interfacial líquido-líquido (LLIR). A otimização busca intensificar o sinal SERS (Surface-enhanced Raman Scattering) para a detecção de 4-aminotiofenol (4-ATP) e, posteriormente, do pesticida ametrina (AMT). O 4-ATP foi empregado como sonda para identificar e avaliar os parâmetros que influenciam a variação do sinal SERS. Dessa forma, foi utilizado um planejamento fatorial fracionário e posteriormente, um planejamento Box-Behnken para investigar os seguintes fatores: concentração e massas dos reagentes, tempos de reação e velocidade de rotação. Os valores obtidos para a condição ótima foram: 7,0 mg de nitrato de prata, 1000 RPM, 60 minutos de tempo de dispersão, 150 mg de borohidreto de sódio, 0,01 mg mL-1 de óxido de grafeno e 45 minutos de tempo de redução. Com base nos resultados, foi construído um modelo de superfície de respostas empírica para determinar as condições ideais de síntese do material. O modelo apresentou um bom ajuste de dados, mas a regressão não foi considerada significativa. Houve um aumento na dispersão Raman cerca de 21500 vezes maior em relação à solução pura de 4-ATP. O material foi caracterizado por microscopia eletrônica de varredura (MEV), e espectroscopias UV-Vis e Raman. As técnicas de caracterização indicaram o crescimento e aglomeração das AgNPs sobre as folhas de grafeno, o que contribui para o aumento da intensidade SERS. Após isso, o substrato SERS foi utilizado para fazer a detecção do herbicida diretamente depositado em cascas de alimentos, sendo estes maçã e batata. Dessa forma, para garantir a reprodutibilidade da aquisição do sinal, foram realizadas medidas de imageamento hiperespectral das cascas de batata e maçã com diferentes níveis de concentração de ametrina e, a partir das imagens hiperespectrais, foi possível detectar a ametrina em concentrações baixas (1,0x10-7 mol L-1) com o mínimo de preparo de amostrasCNPqSul-1application/pdfporUniversidade Federal do ParanáPrograma de Pós Graduação em QuímicaBrasilUniversidade Federal do ParanáSERS, RAMAN, ANALISE DE ALIMENTOSSERSRamanGrafenoQuimiometriaQuímica AnalíticaDetecção de pesticidas em cascas de alimentos por espectroscopia Raman amplificada por superfície e quimiometriainfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Comum do Brasil - Depositainstname:Instituto Brasileiro de Informação em Ciência e Tecnologia (Ibict)instacron:IBICTTEXTR - D - ANDERSON VICTOR DA SILVA.pdf.txtWritten by FormatFilter org.dspace.app.mediafilter.TikaTextExtractionFilter on 2025-06-06T20:16:18Z (GMT).Extracted texttext/plain102683https://deposita.ibict.br/bitstreams/05899bff-44a2-46c8-83ff-7a468581e069/downloadd202d63701361fe6b2b5776000f2f327MD53falseAnonymousREADTHUMBNAILR - D - ANDERSON VICTOR DA SILVA.pdf.jpgWritten by FormatFilter org.dspace.app.mediafilter.PDFBoxThumbnail on 2025-06-06T20:16:18Z (GMT).Generated Thumbnailimage/jpeg3551https://deposita.ibict.br/bitstreams/275622cb-4a24-451c-960d-ecc99a5cbf0b/download7df976219c5337abde2f69832a20ede7MD54falseAnonymousREADLICENSElicense.txtWritten by org.dspace.content.LicenseUtilstext/plain; charset=utf-81867https://deposita.ibict.br/bitstreams/103dc2da-8a6d-4eae-961c-353cb22cd8a4/downloada7c148eec59885ba1ba6d14692be8465MD51falseAnonymousREADORIGINALR - D - ANDERSON VICTOR DA SILVA.pdf/dspace/deposita/upload/R - D - ANDERSON VICTOR DA SILVA.pdfDissertação completaapplication/pdf7133558https://deposita.ibict.br/bitstreams/3ee75b1f-f80f-4b20-9ead-d7c8ea5c326d/download15487a385b22e5b8e52afbfaa44bb3e2MD52trueAnonymousREADdeposita/7572025-06-06T20:16:18.884Zopen.accessoai:deposita.ibict.br:deposita/757https://deposita.ibict.brRepositório ComumPUBhttp://deposita.ibict.br/oai/requestdeposita@ibict.bropendoar:46582025-06-06T20:16:18Repositório Comum do Brasil - Deposita - Instituto Brasileiro de Informação em Ciência e Tecnologia (Ibict)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 |
| dc.title.por.fl_str_mv |
Detecção de pesticidas em cascas de alimentos por espectroscopia Raman amplificada por superfície e quimiometria |
| title |
Detecção de pesticidas em cascas de alimentos por espectroscopia Raman amplificada por superfície e quimiometria |
| spellingShingle |
Detecção de pesticidas em cascas de alimentos por espectroscopia Raman amplificada por superfície e quimiometria Silva, Anderson Victor SERS Raman Grafeno Quimiometria Química Analítica |
| title_short |
Detecção de pesticidas em cascas de alimentos por espectroscopia Raman amplificada por superfície e quimiometria |
| title_full |
Detecção de pesticidas em cascas de alimentos por espectroscopia Raman amplificada por superfície e quimiometria |
| title_fullStr |
Detecção de pesticidas em cascas de alimentos por espectroscopia Raman amplificada por superfície e quimiometria |
| title_full_unstemmed |
Detecção de pesticidas em cascas de alimentos por espectroscopia Raman amplificada por superfície e quimiometria |
| title_sort |
Detecção de pesticidas em cascas de alimentos por espectroscopia Raman amplificada por superfície e quimiometria |
| author |
Silva, Anderson Victor |
| author_facet |
Silva, Anderson Victor |
| author_role |
author |
| dc.contributor.advisor1.fl_str_mv |
Soares, Frederico Luis Felipe |
| dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/1064620847107189 |
| dc.contributor.advisor-co1.fl_str_mv |
Zarbin, Aldo José Gorgatti |
| dc.contributor.advisor-co1Lattes.fl_str_mv |
http://lattes.cnpq.br/4008495434236758 |
| dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/4602597827266974 |
| dc.contributor.author.fl_str_mv |
Silva, Anderson Victor |
| contributor_str_mv |
Soares, Frederico Luis Felipe Zarbin, Aldo José Gorgatti |
| dc.subject.por.fl_str_mv |
SERS Raman Grafeno Quimiometria |
| topic |
SERS Raman Grafeno Quimiometria Química Analítica |
| dc.subject.cnpq.fl_str_mv |
Química Analítica |
| description |
The development of efficient methodologies for detection, elimination, and control of health risks caused by harmful substances, such as pesticides, is a topic of great relevance for scientific research. In this context, this work aims to optmize the synthesis of thin film of reduced graphene oxide with silver nanoparticles (rGO/AgNPs) through the liquid-liquid interfacial route (LLIR). The optimization seeks to intensity the SERS (Surface-enhanced Raman Scattering) signal for the detection of 4-aminothiophenol (4-ATP) and, subsequently, the pesticide ametryn (AMT). 4 ATP was employed as a probe to identify and evaluate the parameters influencing the variation of the SERS signal. Thus, a fractional factorial design and, subsequently a Box-Behnken design were used to investigate the following factors: concentration and masses of reagents, reaction times, and rotation speed. The values obtained for the optimal condition were: 7.0 mg of silver nitrate, 1000 RPM, 60 minutes of dispersion time, 150 mg of sodium borohydride, 0.01 mg mL-1 of graphene oxide, and 45 minutes of reduction time. Based on the results, an empirical response surface model was constructed to determine the ideal conditions for the material synthesis. The model showed a good data fit, but the regression was not considered significant. There was an increase in the Raman scattering approximately 21,500 times greater compared of the pure 4-ATP solution. The material was characterized by scanning electron microscopy (SEM), and UV-Vis and Raman spectroscopies. The characterization techniques indicated the growth and agglomeration of AgNPs on graphene sheets, which contributes to the increase SERS intensity. After that, the SERS substrate was used to detect the herbicide directly deposited on food peels, such as apple and potato. Thus, to ensure the reproducibility of signal acquisition, hyperspectral imaging measurements of potato and apple peels with different concentrations of ametryn were performed. From the hyperspectral images, it was possible to detect ametryn at low concentrations (1.0x10-7 mol L-1) with minimal sample preparation |
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2024 |
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2024 |
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2025-05-09T17:28:18Z |
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por |
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SERS, RAMAN, ANALISE DE ALIMENTOS |
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Universidade Federal do Paraná |
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Brasil |
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Universidade Federal do Paraná |
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Universidade Federal do Paraná |
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