FT-IR spectroscopy with chemometrics for rapid detection of wheat flour adulteration with barley flour
| العنوان: | FT-IR spectroscopy with chemometrics for rapid detection of wheat flour adulteration with barley flour |
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| المؤلفون: | Birol Üner, Ibrahim Yilmaz, Gönül Akin, Fatma Nur Arslan, Hans-Gerd Janssen, Adnan Kenar, Şükriye Nihan Karuk Elmas |
| المساهمون: | Supramolecular Separations (HIMS, FNWI) |
| المصدر: | Journal of Consumer Protection and Food Safety, 15, 245-261 Journal of Consumer Protection and Food Safety 15 (2020) Journal für Verbraucherschutz und Lebensmittelsicherheit, 15(3). Birkhauser Verlag Basel |
| بيانات النشر: | Springer Science and Business Media LLC, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Flour, Wheat flour, 01 natural sciences, Rapid detection, Cross-validation, Chemometrics, 0404 agricultural biotechnology, Food Animals, Partial least squares regression, Cereal, Food science, Spectroscopy, Mathematics, Adulterant, Organic Chemistry, 010401 analytical chemistry, Barley flour, 04 agricultural and veterinary sciences, Organische Chemie, 040401 food science, 0104 chemical sciences, Adulteration, Ft ir spectroscopy, Agronomy and Crop Science, Food Science, Biotechnology |
| الوصف: | The quality of wheat flour (WF) is among the highest of cereal flours and therefore, it is one of the most expensive flours for manufacturing food products. In developing countries, adulteration of WF by mixing up with lower price cereal flours is often seen. Hence, the classification and determination of the adulteration quantity in WF is of great interest. The aim of this research was to evaluate the feasibility of FT-IR spectroscopy and multivariate data analysis methods for the detection of adulteration of WF with the most likely adulterant barley flour (BF). For this purpose, 20 pure cereal flours and 120 flour blends were analyzed using FT-IR spectroscopy with chemometrics. The spectra were collected in the region of 4000-450 cm-1 and up to 15 wavenumber regions corresponding to peaks of flour constituents were selected. The classification limit value of soft independent modeling of class analogies for detection of BF added to WF was better than 1 Additionally, 98.25% of the flours were correctly classified by linear discriminant analysis. Partial least squares regression was adopted to construct a model to quantify the adulteration level. The root mean square error of calibration for sample calibration associated forecast parameters was 0.34-1.34% and the root mean square error of cross validation was 0.36-1.50 Thus, the BF adulterant could be detected down to approximately 0.30%. |
| وصف الملف: | application/pdf |
| تدمد: | 1661-5867 1661-5751 |
| DOI: | 10.1007/s00003-019-01267-9 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d94c3f15633fbe8a6821dbd6ebc3e969 https://doi.org/10.1007/s00003-019-01267-9 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....d94c3f15633fbe8a6821dbd6ebc3e969 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 16615867 16615751 |
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| DOI: | 10.1007/s00003-019-01267-9 |