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

• Autor(a) principal: Borges, Maiara S. [UNESP]
• Data de Publicação: 2021
• Outros Autores: 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]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1002/pca.3006; http://hdl.handle.net/11449/208087
• topic: bioeconomy; experimental design; Glycine max; green chromatography; metabolic fingerprinting

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.