Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Subject: search.filters.subject.Honey adulteration

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  • Article
    Citation - WoS: 8
    Citation - Scopus: 10
    Use of Magic Sandwich Echo and Fast Field Cycling Nmr Relaxometry on Honey Adulteration With Corn Syrup
    (John Wiley and Sons Inc., 2021) Berk, Berkay; Çavdaroğlu, Çağrı; Grunin, Leonid; Ardelean, Ioan; Kruk, Danuta; Mazı, Bekir G.; Öztop, Halil Mecit
    conventional time domain nuclear magnetic resonance (TD-NMR) pulse sequence: magic sandwich echo (MSE) was used to detect the adulteration of honey by glucose syrup (GS) and high fructose corn syrup (HFCS) accompanied with T-1 and T-2 relaxation times. Also, fast field cycling NMR (FFC-NMR) relaxometry and multivariate analysis were performed to investigate the adulteration. RESULTS Higher maltose in GS and changing glucose to water ratio of HFCS gave high correlation with the crystal content values. In HFCS adulteration, two separate populations of protons having different T-2 values were detected and T-1 times were also used to determine GS adulteration. Addition of GS increased T-1 while addition of HFCS increased T-2, significantly. CONCLUSION The results showed that it is possible to differentiate the unadulterated and adulterated honey samples by using TD-NMR relaxation times and crystal content values obtained by the MSE sequence. By FFC-NMR relaxometry, not only GS addition but also the amount of GS was examined. The multivariate analysis technique of principal component analysis was able to distinguish the types of adulterants.
  • Article
    Citation - WoS: 43
    Citation - Scopus: 48
    Determination of Honey Adulteration With Beet Sugar and Corn Syrup Using Infrared Spectroscopy and Genetic-Algorithm Multivariate Calibration
    (Wiley, 2018) Başar, Başak; Özdemir, Durmuş
    BACKGROUND Fourier transform infrared spectroscopy (FTIR) equipped with attenuated total reflectance accessory was used to determine honey adulteration. Adulterated honey samples were prepared by adding corn syrup, beet sugar and water as adulterants to the pure honey samples in various amounts. The spectra of adulterated and pure honey samples (n = 209) were recorded between 4000 and 600 cm(-1) wavenumber range. RESULTS CONCLUSION Genetic-algorithm-based inverse least squares (GILS) and partial least squares (PLS) methods were used to determine honey content and amount of adulterants. Results indicated that the multivariate calibration generated with GILS could produce successful models with standard error of cross-validation in the range 0.97-2.52%, and standard error of prediction between 0.90 and 2.19% (% w/w) for all the components contained in the adulterated samples. Similar results were obtained with PLS, generating slightly larger standard error of cross-validation and standard error of prediction values. The fact that the models were generated with several honey samples coming from various different botanical and geographical origins, quite successful results were obtained for the detection of adulterated honey samples with a simple Fourier transform infrared spectroscopy technique. Having a genetic algorithm for variable selection helped to build somewhat better models with GILS compared with PLS. (c) 2018 Society of Chemical Industry