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Open AccessFeature PaperArticle

Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting

1
Department of Chemistry, M.V.Lomonosov Moscow State University, GSP-1, Leninskie Gory, 1–3, 119991 Moscow, Russia
2
Laboratory of Multivariate Analysis and Global Modeling, Samara State Technical University, 244 Molodogvardeyskaya str., 443100 Samara, Russia
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(18), 5351; https://doi.org/10.3390/s20185351
Received: 20 July 2020 / Revised: 8 September 2020 / Accepted: 15 September 2020 / Published: 18 September 2020
(This article belongs to the Special Issue Multisensor Systems and Signal Processing in Analytical Chemistry)
In this study we develop a variant of fluorescent sensor array technique based on addition of fluorophores to samples. A correct choice of fluorophores is critical for the successful application of the technique, which calls for the necessity of comparing different discrimination protocols. We used 36 honey samples from different sources to which various fluorophores were added (tris-(2,2′-bipyridyl) dichlororuthenium(II) (Ru(bpy)32+), zinc(II) 8-hydroxyquinoline-5-sulfonate (8-Ox-Zn), and thiazole orange in the presence of two types of deoxyribonucleic acid). The fluorescence spectra were obtained within 400–600 nm and treated by principal component analysis (PCA). No fluorophore allowed for the discrimination of all samples. To evaluate the discrimination performance of fluorophores, we introduced crossing number (CrN) calculated as the number of mutual intersections of confidence ellipses in the PCA scores plots, and relative position (RP) characterized by the pairwise mutual location of group centers and their most distant points. CrN and RP parameters correlated with each other, with total sensitivity (TS) calculated by Mahalanobis distances, and with the overall rating based on all metrics, with coefficients of correlation over 0.7. Most of the considered parameters gave the first place in the discrimination performance to Ru(bpy)32+ fluorophore. View Full-Text
Keywords: fluorescent fingerprinting; fluorophores; honey; discrimination; chemometrics; principal component analysis; tris(2,2′-bipyridyl)dichlororuthenium(II) fluorescent fingerprinting; fluorophores; honey; discrimination; chemometrics; principal component analysis; tris(2,2′-bipyridyl)dichlororuthenium(II)
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MDPI and ACS Style

Rukosueva, E.A.; Belikova, V.A.; Krylov, I.N.; Orekhov, V.S.; Skorobogatov, E.V.; Garmash, A.V.; Beklemishev, M.K. Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting. Sensors 2020, 20, 5351. https://doi.org/10.3390/s20185351

AMA Style

Rukosueva EA, Belikova VA, Krylov IN, Orekhov VS, Skorobogatov EV, Garmash AV, Beklemishev MK. Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting. Sensors. 2020; 20(18):5351. https://doi.org/10.3390/s20185351

Chicago/Turabian Style

Rukosueva, Elizaveta A.; Belikova, Valeria A.; Krylov, Ivan N.; Orekhov, Vladislav S.; Skorobogatov, Evgenii V.; Garmash, Andrei V.; Beklemishev, Mikhail K. 2020. "Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting" Sensors 20, no. 18: 5351. https://doi.org/10.3390/s20185351

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