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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

A green and sustainable method for monitoring the chemical composition of soybean: an alternative for quality control

Texto completo
Autor(es):
Borges, Maiara S. [1] ; Zanatta, Ana C. [1] ; Souza, Otavio A. [1] ; Pelissari, Joao H. [1] ; Camargo, Julio G. S. [2] ; Carneiro, Renato L. [3] ; Funari, Cristiano S. [4] ; Bolzani, Vanderlan S. [1] ; Rinaldo, Daniel [1, 2]
Número total de Autores: 9
Afiliação do(s) autor(es):
[1] UNESP Sao Paulo State Univ, Inst Chem, Araraquara, SP - Brazil
[2] UNESP Sao Paulo State Univ, Sch Sci, Bauru, SP - Brazil
[3] UFSCar Fed Univ Sao Carlos, Dept Chem, Sao Carlos, SP - Brazil
[4] UNESP Sao Paulo State Univ, Sch Agr Sci, Botucatu, SP - Brazil
Número total de Afiliações: 4
Tipo de documento: Artigo Científico
Fonte: Phytochemical Analysis; v. 32, n. 4, p. 562-574, JUL 2021.
Citações Web of Science: 2
Resumo

Introduction Soybean is one of the most important crops in the world, an important source of isoflavones, and used to treat various chronic diseases. High-performance liquid chromatography (HPLC), associated with multivariate experiments and green solvents, is increasingly used to develop comprehensive elution methods for quality control of plants and derivatives. Objective The work aims to establish a HPLC fingerprinting method for soybean seeds employing Green Chemistry Principles, a sustainable solvent with low toxicity, and a comprehensive experimental design that reduces the number of experiments. Materials and Methods The fingerprinting method was optimised through Design of Experiments by evaluating seven chromatographic variables: initial percentage of ethanol (X1), final percentage of ethanol (X2), temperature (X3), percentage of acetic acid in water (X4), flow rate (X5), run time (X6), and stationary phase (X7). The dependent variable was the number of peaks (n). Results An initial factorial design for screening purposes indicated that the most significant quantitative parameters to separate soybean metabolites were X1 and X3. The conditions were optimised by a Doehlert design, to obtain a HPLC-PAD (photodiode array detector) fingerprinting of the polar extract of soybean seeds with the markers identified by liquid chromatography electrospray ionisation tandem mass spectrometry (LC-ESI-MS/MS). The optimum fingerprinting method was determined as 5-55% of ethanol in 30 min, at 35 degrees C, and flow rate of 1 mL/min, by employing a phenyl-hexyl column (150 mm x 4.6 mm). Conclusion The developed green method enabled markers of soybean to be separated and identified and could be an eco-friendlier alternative for soybean quality control that covered seven Green Analytical Chemistry Principles. (AU)

Processo FAPESP: 14/50926-0 - INCT 2014: biodiversidade e produtos naturais
Beneficiário:Vanderlan da Silva Bolzani
Modalidade de apoio: Auxílio à Pesquisa - Programa BIOTA - Temático
Processo FAPESP: 17/06216-6 - Desenvolvimento de metodologias analíticas verdes na busca por compostos orgânicos de alto valor agregado em resíduos agrícolas
Beneficiário:Cristiano Soleo de Funari
Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores
Processo FAPESP: 16/08179-8 - Desenvolvimento de alternativas verdes por CLAE para análise de plantas medicinais de interesse do Ministério da Saúde do Brasil
Beneficiário:Daniel Rinaldo
Modalidade de apoio: Auxílio à Pesquisa - Regular