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    Determination of quality characteristics of some Monofloral, Polyfloral and Honeydew honeys in terms of physical properties and Proline content
    (2024) Özbay, Merve; Arslan, Fatma Nur; Görür, Gazi
    This study aims to investigate some physical properties and proline content of 95 different honey samples to reveal their characteristic features and evaluate their quality according to the Turkish Food Codex. The moisture content, which is highly important parameter in determining the shelf life of honeys, determined between 14.60% and 21.20% and these values were determined to be within the limits (<20%) except for four honey samples. The brix values of honey samples were examined between 77.23% and 83.60%, and they were found to be within the acceptable range. The other physical parameter, namely the electrical conductivity values of samples determined between 0.11 and 1.20 mS/cm. Proline, which is an important value in determining the type and maturity of honey and is the amino acid found in the highest amount in honey, should be above 300 mg/kg in honey, according to the communique. The proline amount of the honey samples examined varied between 281.61 and 2259.43 mg/kg. It was determined that the proline amount of two honey samples were below the limit. It was concluded that most of the tested samples were in compliance with the food codex in terms of quality standards.
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    Qualitative and Quantitative Detection of Monofloral, Polyfloral, and Honeydew Honeys Adulteration by Employing Mid-Infrared Spectroscopy and Chemometrics
    (Springer, 2022) Ozbay, Merve; Arslan, Fatma Nur; Gorur, Gazi
    In this study, the potential of mid-infrared (MIR) spectroscopy complemented with chemometrics for the qualitative and quantitative detection of monofloral, polyfloral, and honeydew honeys adulteration (acacia, black cumin, carob, citrus, chestnut, lavender, linden, milk vetch, rhododendron, sunflower, thistle, thyme, honeydew, oak, and polyfloral honeys) was reported. A total of 311 honey samples (adulterated honeys with sugar syrups (2% to 50%) and pure honeys) were analyzed the spectral range of 4000-650 cm(-1). MIR data were analyzed by application of supervised and unsupervised multivariate data analyses including principle component analysis (PCA), hierarchical cluster analysis (HCA), soft independent modeling of class analogies (SIMCA), and partial least square-regression (PLS-R) analyses, by using full and characteristic wavenumber regions. The SIMCA models prescribed an excellent classification for pure honey samples of different botanical origins, and the classification limits for detecting sugar syrups added to honey samples were better than 2%. The PLS-R plots exhibited excellent predictions (R-2 > 0.9993), and the forecast calibration and validation parameters (RMSEC and RMSECV) were found as 0.4413-3.3104% and 0.6487-4.0374%, respectively. Thus, the MIR methods in conjunction with chemometrics developed here could be employed to estimate the amount of sugar syrup adulterant present at levels < 0.44% in unknown honey samples.