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The Use of FTIR Spectroscopy Combined with Multivariate Analysis in Food Composition Analysis

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Spectroscopic Techniques & Artificial Intelligence for Food and Beverage Analysis

Abstract

Infrared spectroscopy, one of the vibrational spectroscopies, has emerged as rapid and powerful analytical technique for identification and quantitative analysis of food component. FTIR spectra is fingerprint analytical technique, therefore, by selecting the specific region, some analytical purposes can be achieved such as identification, confirmation and quantitative analysis of analyte(s) of interest in food samples. Equipped with some sampling technique such as attenuated total reflectance and combined with chemometrics software such as principal component analysis for classification and multivariate calibration for multicomponent analysis, FTIR spectroscopy has been successfully used for compositional analysis of food. The method is rapid with minimum or without sample preparation and is not involving the extensive solvents and reagents.

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Acknowledgements

The authors are thankful to Dr. Teo Wei Boon (PerkinElmer, Singapore) for preparing 2D-FT-IR of Curcuma longa during short visit at the Faculty of Pharmacy, Airlangga University, Surabaya (2016), Dr. Robert Packer (PerkinElmer, Shelton, CA, USA) and Dr. Tan Boon Chun (PerkinElmer Selangor, Malaysia) for permission to reproduce some figures, Ms. Febry Ardiana (PT Bernofarm, Sidoarjo, Surabaya) for reference (USP 42, General method <854>) [23].

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Authors and Affiliations

  1. Faculty of Pharmacy, Universitas Surabaya, Surabaya, East Java, Indonesia

    Gunawan Indrayanto

  2. Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia

    Abdul Rohman

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  1. Gunawan Indrayanto
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  2. Abdul Rohman
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Correspondence to Abdul Rohman .

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  1. Department of Physics, Ewing Christian College, Prayagraj, Uttar Pradesh, India

    Ashutosh Kumar Shukla

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Indrayanto, G., Rohman, A. (2020). The Use of FTIR Spectroscopy Combined with Multivariate Analysis in Food Composition Analysis. In: Shukla, A. (eds) Spectroscopic Techniques & Artificial Intelligence for Food and Beverage Analysis. Springer, Singapore. https://doi.org/10.1007/978-981-15-6495-6_2

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