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

Página do item simplificado
dc.contributor.authorBorges, Maiara S. [UNESP]
dc.contributor.authorZanatta, Ana C. [UNESP]
dc.contributor.authorSouza, Otávio A. [UNESP]
dc.contributor.authorPelissari, João H. [UNESP]
dc.contributor.authorCamargo, Júlio G.S. [UNESP]
dc.contributor.authorCarneiro, Renato L.
dc.contributor.authorFunari, Cristiano S. [UNESP]
dc.contributor.authorBolzani, Vanderlan S. [UNESP]
dc.contributor.authorRinaldo, Daniel [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade Federal de São Carlos (UFSCar)
dc.date.accessioned2021-06-25T11:06:09Z
dc.date.available2021-06-25T11:06:09Z
dc.date.issued2021-07-01
dc.description.abstractIntroduction: 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.en
dc.description.affiliationInstitute of Chemistry UNESP – São Paulo State University
dc.description.affiliationSchool of Sciences UNESP – São Paulo State University
dc.description.affiliationDepartment of Chemistry UFSCar – Federal University of São Carlos
dc.description.affiliationSchool of Agricultural Sciences UNESP – São Paulo State University
dc.description.affiliationUnespInstitute of Chemistry UNESP – São Paulo State University
dc.description.affiliationUnespSchool of Sciences UNESP – São Paulo State University
dc.description.affiliationUnespSchool of Agricultural Sciences UNESP – São Paulo State University
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipIdFAPESP: 2014/50926-0
dc.description.sponsorshipIdFAPESP: 2016/08179-8
dc.description.sponsorshipIdFAPESP: 2017/06216-6
dc.description.sponsorshipIdCAPES: 88882.330061/2019-01
dc.description.sponsorshipIdCNPq: INCT-BioNat 465637/2014-0
dc.format.extent562-574
dc.identifierhttp://dx.doi.org/10.1002/pca.3006
dc.identifier.citationPhytochemical Analysis, v. 32, n. 4, p. 562-574, 2021.
dc.identifier.doi10.1002/pca.3006
dc.identifier.issn1099-1565
dc.identifier.issn0958-0344
dc.identifier.scopus2-s2.0-85094213676
dc.identifier.urihttp://hdl.handle.net/11449/208087
dc.language.isoeng
dc.relation.ispartofPhytochemical Analysis
dc.sourceScopus
dc.subjectbioeconomy
dc.subjectexperimental design
dc.subjectGlycine max
dc.subjectgreen chromatography
dc.subjectmetabolic fingerprinting
dc.titleA green and sustainable method for monitoring the chemical composition of soybean: an alternative for quality controlen
dc.typeArtigo
unesp.author.orcid0000-0002-6857-2190[6]
unesp.author.orcid0000-0003-0143-9448[7]
unesp.author.orcid0000-0003-0615-8776[8]
unesp.author.orcid0000-0001-5363-6481[9]

Arquivos

Coleções

Artigos - Química Orgânica - IQ