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Determination of acrylamide in potato-based foods using headspace solid-phase microextraction based on nanostructured polypyrrole fiber coupled to ion mobility spectrometry: A heat treatment study

Abstract

In this work, headspace solid-phase microextraction (HS-SPME) coupled to ion mobility spectrometry (IMS) has been used as a simple and convenient method for acrylamide detection and quantification in heat treated food samples. IMS equipped with corona discharge (CD) ionization along with HS-SPME based on nanostructured polypyrrole (PPy) fiber has been successfully applied for quantitative analysis of acrylamide in potato-based foods. The effect of various analytical parameters on microextraction procedure like extraction temperature, extraction time, ionic strength and pH of the sample were also studied and optimized to obtain the best HS-SPME results. The HS-SPME–IMS method provided good repeatability (RSD ≤ 8%) and calibration graph was linear in the range of 10 – 100 ng g-1 (R2 > 0.99) with a detection limit of 4 ng g-1. The proposed method was applied for determination of acrylamide in potato-based foods, such as potato crisps and French fries samples. Validation of the analytical procedure was determined as percentage of recovery and was confirmed by the add-found method in the potato-based food samples. The results obtained by the proposed method are in satisfactory agreement with the amounts added (92%-96%). In conclusion, a direct relationship between temperature/time and acrylamide concentration in heat treated foods can be established.

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Publication details

The article was received on 19 Jun 2017, accepted on 01 Aug 2017 and first published on 01 Aug 2017


Article type: Paper
DOI: 10.1039/C7AY01506B
Citation: Anal. Methods, 2017, Accepted Manuscript
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    Determination of acrylamide in potato-based foods using headspace solid-phase microextraction based on nanostructured polypyrrole fiber coupled to ion mobility spectrometry: A heat treatment study

    N. Alizadeh, E. Pourmand and E. Ghaemi , Anal. Methods, 2017, Accepted Manuscript , DOI: 10.1039/C7AY01506B

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