Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/31255
Title: Chemical profiling of floral and chestnut honey using high-performance liquid chromatography-ultraviolet detection
Authors: Aloğlu, Ahmet Kemal
Harrington, Peter de B
Uludağ Üniversitesi/Fen-Edebiyat Fakültesi/Kimya Bölümü.
Uludağ Üniversitesi/Mesleki Teknik Bilimler Yüksekokulu.
0000-0003-1508-0181
0000-0002-9381-0410
0000-0002-9347-8307
Şahin, Saliha
Demir, Cevdet
Güneş, Mesut Ertan
AAH-2892-2021
AFR-1890-2022
ABA-2005-2020
AAK-4470-2021
15027401600
7003565902
35388276000
Keywords: Chemistry
Food science & technology
Chemometrics
Chestnut honey
Classification
Floral honey
Food analysis
Food composition
FuRES
HPLC-DAD
Phenolic compounds
SVMTreeG
Partial least-squares
Building expert-systems
Antioxidant capacities
Physicochemical properties
Discriminant-analysis
Italian honeys
Classification
Spectrometry
Hplc
Authentication
Issue Date: 2-Jun-2017
Publisher: Elsevier
Citation: Aloğlu, A. K. vd. (2017). ''Chemical profiling of floral and chestnut honey using high-performance liquid chromatography-ultraviolet detection''. Journal of Food Composition and Analysis, 62, 205-210.
Abstract: Using the two-way images of phenolic compounds from high-performance liquid chromatography-ultraviolet diode array detection (HPLC-DAD), floral and chestnut honey from Turkey were successfully differentiated. A fuzzy rule-building expert system (FuRES), support vector machine classification tree (SVMTreeG), and super partial least-square discriminant analysis (sPLS-DA) were used to develop classification models. Normalization, retention time alignment, square root transform, and dissimilarity kernel were evaluated as data preprocessing methods. The bootstrapped Latin partition was used with 100 bootstraps and 4 partitions. Classification rates of FuRES and SVMTreeG with a square root transform were 97.6 +/- 0.4% and 97.6 +/- 0.4% for classifying the type of honey, respectively. The measures of precision are 95% confidence intervals. HPLC-DAD was demonstrated as a reliable analytical method for authentication of honey.
URI: https://doi.org/10.1016/j.jfca.2017.06.002
https://www.sciencedirect.com/science/article/pii/S0889157517301400
http://hdl.handle.net/11452/31255
ISSN: 0889-1575
1096-0481
Appears in Collections:Scopus
Web of Science

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