Abordagem verde e multivariada no desenvolvimento de um método sustentável para monitoramento da composição química da soja e determinação quantitativa dos parâmetros de combustão do extrato e de sua biomassa residual por TG/ DTG-DSC.
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Data
2021-04-22
Autores
Caires, Maiara Stefanini Borges
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Editor
Universidade Estadual Paulista (Unesp)
Resumo
A soja, Glycine max (L.) Merr. (Fabaceae), é uma das culturas mais importantes do mundo, por ser responsável pela produção de biodiesel, leite, tofu e etanol, fonte de óleo, proteína e principalmente de metabólitos secundários como as isoflavonas, que desempenham um papel importante na prevenção de doenças crônicas. A análise quimiométrica de dados multivariados associados à cromatografia líquida de alta eficiência é cada vez mais usado para desenvolver métodos de eluição abrangentes para o controle de qualidade de plantas como a soja. Este trabalho visou estabelecer um método de análise não poluente, seguro e sustentável para análise de sementes de soja. Um planejamento fatorial fracionário foi desenvolvido para o extrato hidroetanólico 70% de G. max para o desenvolvimento de um método cromatográfico verde, sendo que as variáveis determinadas como mais significativas foram % inicial de etanol na fase móvel e temperatura da análise em °C. Para as variáveis mais significativas, foi utilizado o modelo robusto chamado Doehlert para a otimização dos níveis e resposta do método cromatográfico. Sendo facilmente aplicado para otimizar variáveis exigindo menos experimentos, além desta metodologia ser mais ecologicamente correta devido à menor geração de resíduos químicos. Fornecendo uma condição ótima para se obter o fingerprinting das sementes de soja. As condições cromatográficas do método otimizado foram: coluna C18 XSelect (150 x 4.6 mm d.i.; 5 μm), com pré-coluna (4 x 3 mm, 5 μm), equipamento HPLC (Jasco®), Fase móvel: H2O + 0,5% de ácido acético (A) e EtOH (B) no seguinte gradiente: 5- 55% de B em 30 min. Vazão: 1 mL min−1. Temperatura de análise: 35 °C; volume de injeção: 20 μL, comprimento de onda 260 nm. O impacto ambiental do método desenvolvido para análise de isoflavonas de soja em comparação a métodos de referência foi avaliado pelas métricas HPLC-Environmental Assessment Tool e AGREE- Analytical GREenEss Calculator demonstrando que a metodologia desenvolvida é mais ambientalmente amigável e está de acordo com os princípios de química verde. A boa seletividade do método permitiu identificar por cromatografia líquida de alta eficiência e espectrometria de massas, as principais isoflavonas presentes e provou ser aplicável no controle de qualidade desses metabólitos interessantes, sendo uma alternativa viável na autenticação de seis amostras comerciais de soja de diferentes localidades. Não gerando resíduos tóxicos e sendo seguro para o analista, além de ser um método de custo reduzido. Outro viés pouco explorado é o comportamento térmico de extratos vegetais e biomassa residual de plantas medicinais e aromáticas. A Análise térmica permitiu determinar quantitativamente as características da decomposição térmica e termooxidativa e além de determinar os parâmetros de combustão para soja, extrato e sua biomassa residual. O efeito da extração sobre os parâmetros de combustão da biomassa residual e a estabilidade térmica dessa amostra foram afetados pela extração. Portanto esse trabalho mostra a aplicabilidade na utilização da cromatografia líquida de alta eficiência associada a abordagem multivariada, na obtenção de um método robusto, eficiente, de acordo com os princípios de química verde e ambientalmente amigável na análise de soja. Como também nessa perspectiva explorou a utilização da biomassa residual e sua aplicabilidade no setor de bioenergia.
Soybean, Glycine max (L.) Merr. (Fabaceae), is one of the most important crops in the world, as it is responsible for the production of biodiesel, milk, tofu and ethanol, a source of oil, protein and mainly of secondary metabolites such as isoflavones, which play an important role in the prevention of diseases chronic. The chemometric analysis of multivariate data associated with high-performance liquid chromatography is increasingly used to develop comprehensive elution methods for the quality control of plants such as soybeans. This work aimed to establish a non-polluting, safe and sustainable analysis method for analyzing soybean seeds. A fractional factorial design was developed for the hydroethanolic extract 70% of G. max for the development of a green chromatographic method, and the variables determined as the most significant were the initial % of ethanol in the mobile phase and the temperature of the analysis in ° C. For the most significant variables, the robust model called Doehlert was used to optimize the levels and response of the chromatographic method. Being easily applied to optimize variables requiring less experiments, in addition to this methodology being more environmentally friendly due to the lower generation of chemical residues. Providing an optimal condition for obtaining the fingerprinting of soybean seeds. The chromatographic conditions of the optimized method were: C18 XSelect column (150 x 4.6 mm di; 5 μm), with pre-column (4 x 3 mm, 5μm), HPLC equipment (Jasco®), Mobile phase: H2O + 0.5 % acetic acid (A) and EtOH (B) in the following gradient: 5-55% B in 30 min. Flow rate: 1 mL min− 1. Analysis temperature: 35 °C; injection volume: 20 μL, wavelength 260 nm. The environmental impact of the method developed for the analysis of soy isoflavones in comparison to reference methods was evaluated by the metrics HPLC-Environmental Assessment Tool and AGREEAnalytical GREenEss Calculator demonstrating that the methodology developed is more environmentally friendly and is in accordance with the principles of green chemistry. The good selectivity of the method allowed to identify by HPLC and mass spectrometry, the main isoflavones present and proved to be applicable in the quality control of these interesting metabolites, being a viable alternative in the authentication of six commercial samples of soy from different locations. It does not generate toxic waste and is safe for the analyst, in addition to being a low cost method. Another little explored bias is the thermal behavior of plant extracts and residual biomass of medicinal and aromatic plants. The thermal analysis allowed to determine quantitatively the characteristics of the thermal and thermo-oxidative decomposition and in addition to determining the combustion parameters for soybean, extract and its residual biomass. The effect of the extraction on the combustion parameters of the residual biomass and the thermal stability of this sample were affected by the extraction. Therefore, this work shows the applicability in the use of high performance liquid chromatography associated with the multivariate approach, in obtaining a robust, efficient method, according to the principles of green and environmentally friendly chemistry in soybean analysis. In this perspective, he also explored the use of residual biomass and its applicability in the bioenergy sector.
Soybean, Glycine max (L.) Merr. (Fabaceae), is one of the most important crops in the world, as it is responsible for the production of biodiesel, milk, tofu and ethanol, a source of oil, protein and mainly of secondary metabolites such as isoflavones, which play an important role in the prevention of diseases chronic. The chemometric analysis of multivariate data associated with high-performance liquid chromatography is increasingly used to develop comprehensive elution methods for the quality control of plants such as soybeans. This work aimed to establish a non-polluting, safe and sustainable analysis method for analyzing soybean seeds. A fractional factorial design was developed for the hydroethanolic extract 70% of G. max for the development of a green chromatographic method, and the variables determined as the most significant were the initial % of ethanol in the mobile phase and the temperature of the analysis in ° C. For the most significant variables, the robust model called Doehlert was used to optimize the levels and response of the chromatographic method. Being easily applied to optimize variables requiring less experiments, in addition to this methodology being more environmentally friendly due to the lower generation of chemical residues. Providing an optimal condition for obtaining the fingerprinting of soybean seeds. The chromatographic conditions of the optimized method were: C18 XSelect column (150 x 4.6 mm di; 5 μm), with pre-column (4 x 3 mm, 5μm), HPLC equipment (Jasco®), Mobile phase: H2O + 0.5 % acetic acid (A) and EtOH (B) in the following gradient: 5-55% B in 30 min. Flow rate: 1 mL min− 1. Analysis temperature: 35 °C; injection volume: 20 μL, wavelength 260 nm. The environmental impact of the method developed for the analysis of soy isoflavones in comparison to reference methods was evaluated by the metrics HPLC-Environmental Assessment Tool and AGREEAnalytical GREenEss Calculator demonstrating that the methodology developed is more environmentally friendly and is in accordance with the principles of green chemistry. The good selectivity of the method allowed to identify by HPLC and mass spectrometry, the main isoflavones present and proved to be applicable in the quality control of these interesting metabolites, being a viable alternative in the authentication of six commercial samples of soy from different locations. It does not generate toxic waste and is safe for the analyst, in addition to being a low cost method. Another little explored bias is the thermal behavior of plant extracts and residual biomass of medicinal and aromatic plants. The thermal analysis allowed to determine quantitatively the characteristics of the thermal and thermo-oxidative decomposition and in addition to determining the combustion parameters for soybean, extract and its residual biomass. The effect of the extraction on the combustion parameters of the residual biomass and the thermal stability of this sample were affected by the extraction. Therefore, this work shows the applicability in the use of high performance liquid chromatography associated with the multivariate approach, in obtaining a robust, efficient method, according to the principles of green and environmentally friendly chemistry in soybean analysis. In this perspective, he also explored the use of residual biomass and its applicability in the bioenergy sector.
Descrição
Palavras-chave
Plantas medicinais, Planejamento experimental, Química verde, Sustentabilidade, Análise térmica, Medicinal plants, Experimental planning, Green chemistry, Sustainability, Thermal analysis