Autor(es): Borges, Maiara S. [UNESP] ; Zanatta, Ana C. [UNESP] ; Souza, Otávio A. [UNESP] ; Pelissari, João H. [UNESP] ; Camargo, Júlio G.S. [UNESP] ; Carneiro, Renato L. ; Funari, Cristiano S. [UNESP] ; Bolzani, Vanderlan S. [UNESP] ; Rinaldo, Daniel [UNESP]
Data: 2021
Identificador Persistente: http://hdl.handle.net/11449/208087
Origem: Oasisbr
Assunto(s): bioeconomy; experimental design; Glycine max; green chromatography; metabolic fingerprinting
Made available in DSpace on 2021-06-25T11:06:09Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-07-01
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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°C, and flow rate of 1 mL/min, by employing a phenyl-hexyl column (150 mm × 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.
Institute of Chemistry UNESP – São Paulo State University
School of Sciences UNESP – São Paulo State University
Department of Chemistry UFSCar – Federal University of São Carlos
School of Agricultural Sciences UNESP – São Paulo State University
Institute of Chemistry UNESP – São Paulo State University
School of Sciences UNESP – São Paulo State University
School of Agricultural Sciences UNESP – São Paulo State University
FAPESP: 2014/50926-0
FAPESP: 2016/08179-8
FAPESP: 2017/06216-6
CAPES: 88882.330061/2019-01
CNPq: INCT-BioNat 465637/2014-0
