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Determination of honey adulteration with beet sugar and corn syrup using infrared spectroscopy and genetic‐algorithm‐based multivariate calibration

Başar, Başak, Özdemir, Durmuş
Journal of the science of food and agriculture 2018 v.98 no.15 pp. 5616-5624
Fourier transform infrared spectroscopy, adulterants, adulterated products, algorithms, beet sugar, corn syrup, honey, least squares, models, prediction, provenance, reflectance
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: 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. CONCLUSION: 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. © 2018 Society of Chemical Industry