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dc.contributor.authorSOARES, A. C.
dc.contributor.authorSOARES, J. C.
dc.contributor.authorSANTOS, D. M. dos
dc.contributor.authorMIGLIORINI, F. L.
dc.contributor.authorPOPOLIN-NETO, M.
dc.contributor.authorPINTO, D. dos S. C.eng
dc.contributor.authorCARVALHO, W. A.eng
dc.contributor.authorBRANDAO, H. de M.eng
dc.contributor.authorPAULOVICH, F. V.eng
dc.contributor.authorCORREA, D. S.eng
dc.contributor.authorOLIVEIRA JUNIOR, O. N.eng
dc.contributor.authorMATTOSO, L. H. C.eng
dc.date.accessioned2023-06-06T16:47:30Z-
dc.date.available2023-06-06T16:47:30Z-
dc.date.created2023-06-06
dc.date.issued2023
dc.identifier.citationACS Omega, v. 8, n. 15, p. 13721-13732, 2023.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1154290-
dc.descriptionWe report a nanoarchitectonic electronic tongue made with flexible electrodes coated with curcumin carbon dots and zein electrospun nanofibers, which could detect Staphylococcus aureus(S. aureus) in milk using electrical impedance spectroscopy. Electronic tongues are based on the global selectivity concept in which the electrical responses of distinct sensing units are combined to provide a unique pattern, which in this case allowed the detection of S. aureus through non-specific interactions. The electronic tongue used here comprised 3 sensors with electrodes coated with zein nanofibers, carbon dots, and carbon dots with zein nanofibers. The capacitance data obtained with the three sensors were processed with a multidimensional projection technique referred to as interactive document mapping (IDMAP) and analyzed using the machine learning-based concept of multidimensional calibration space (MCS). The concentration of S. aureus could be determined with the sensing units, especially with the one containing zein as the limit of detection was 0.83 CFU/mL (CFU stands for colony-forming unit). This high sensitivity is attributed to molecular-level interactions between the protein zein and C?H groups in S. aureus according to polarization-modulated infrared reflection-absorption spectroscopy (PM-IRRAS) data. Using machine learning and IDMAP, we demonstrated the selectivity of the electronic tongue in distinguishing milk samples from mastitis-infected cows from milk collected from healthy cows, and from milk spiked with possible interferents. Calibration of the electronic tongue can also be reached with the MCS concept employing decision tree algorithms, with an 80.1% accuracy in the diagnosis of mastitis. The low-cost electronic tongue presented here may be exploited in diagnosing mastitis at early stages, with tests performed in the farms without requiring specialized laboratories or personnel.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectNanofibraeng
dc.subjectProduto lácteoeng
dc.subjectCalibraçãoeng
dc.subjectPropriedade elétricaeng
dc.subjectDoença infecciosaeng
dc.titleNanoarchitectonic E-tongue of electrospun zein/curcumin carbon dots for detecting Staphylococcus aureus in milk.
dc.typeArtigo de periódico
dc.subject.thesagroLeite
dc.subject.thesagroBactéria
dc.subject.thesagroZeínaeng
dc.subject.thesagroProduto Derivado do Leiteeng
dc.subject.nalthesaurusBeverageseng
dc.subject.nalthesaurusCalibrationeng
dc.subject.nalthesaurusDairy productseng
dc.subject.nalthesaurusElectrical propertieseng
dc.subject.nalthesaurusInfectious diseaseseng
riaa.ainfo.id1154290
riaa.ainfo.lastupdate2023-06-06
dc.identifier.doihttps://doi.org/10.1021/acsomega.2c07944?urlappend=%3Fref%3DPDF&jav=VoR&rel=cite-as
dc.contributor.institutionANDREY COATRINI SOARES
dc.contributor.institutionJULIANA COATRINI SOARES, Universidade de São Pauloeng
dc.contributor.institutionDANILO MARTINS DOS SANTOSeng
dc.contributor.institutionFERNANDA L. MIGLIORINIeng
dc.contributor.institutionMARIO POPOLIN-NETO, Instituto Federal de Educação, Ciência e Tecnologia de São Pauloeng
dc.contributor.institutionDANIELLE DOS SANTOS CINELLI PINTOeng
dc.contributor.institutionWANESSA ARAUJO CARVALHO, CNPGLeng
dc.contributor.institutionHUMBERTO DE MELLO BRANDAO, CNPGLeng
dc.contributor.institutionFERNANDO VIEIRA PAULOVICH, Eindhoven University of Technologyeng
dc.contributor.institutionDANIEL SOUZA CORREA, CNPDIAeng
dc.contributor.institutionOSVALDO N. OLIVEIRA JUNIOR, Universidade de São Pauloeng
dc.contributor.institutionLUIZ HENRIQUE CAPPARELLI MATTOSO, CNPDIA.eng
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