Renaka, Jalanidi Ilmi and Setyaningsih, Widiastuti and Palma, Miguel (2025) Fast and solvent-free determination of kappa and iota carrageenan in Kappaphycus alvarezii using ATR-FTIR spectroscopy and chemometrics. Food Chemistry, 495: 146371. pp. 1-12. ISSN 03088146
Full text not available from this repository. (Request a copy)Abstract
Determining kappa and iota carrageenan composition is essential for optimizing its functionality in food applications. Kappaphycus alvarezii is a major source of carrageenan, widely used as a gelling agent, thickener, and stabilizer. However, conventional carrageenan analysis requires time-consuming extraction and chemical treatments, limiting efficiency in quality control. This study proposes a rapid, solvent-free approach to quantify total carrageenan yield and its kappa and iota composition in different forms of raw macroalgae. Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy combined with Partial Least Squares (PLS) regression was employed to develop a predictive model for carrageenan determination. The model achieved high accuracy, with calibration, cross-validation, and prediction coefficients (R2) exceeding 0.9 within the 600–1100 cm−1 spectral range. Validation with real samples confirmed its reliability, making it a suitable tool for carrageenan quality assessment and industrial applications. © 2025 Elsevier Ltd
| Item Type: | Article |
|---|---|
| Additional Information: | Cited by: 1 |
| Uncontrolled Keywords: | Carrageenan; Chemometrics; Edible Seaweeds; Kappaphycus; Plant Extracts; Rhodophyta; Seaweed; Spectroscopy, Fourier Transform Infrared; Least squares approximations; Quality control; Spectrum analysis; Supersaturation; carrageenan; solvent; carrageenan; plant extract; Attenuated total reflectance Fourier transform infrared; Carrageenans; Chemometrices; Iota-carrageenan; Kappa carrageenan; Kappaphycus alvarezii; Partial least square regression; Quality assessment; Seaweed analyze; Solvent free; Article; attenuated total reflectance Fourier transform infrared spectroscopy; chemometrics; cluster analysis; geographic distribution; Kappaphycus alvarezii; nonhuman; partial least squares regression; predictive model; quality control; workflow; chemistry; edible seaweed; evaluation study; Fourier transform infrared spectroscopy; Kappaphycus; procedures; red alga; seaweed; Fourier transform infrared spectroscopy |
| Subjects: | S Agriculture > S Agriculture (General) |
| Divisions: | Faculty of Agricultural Technology > Food and Agricultural Product Technology |
| Depositing User: | Diah Ari Damayanti |
| Date Deposited: | 30 Dec 2025 06:53 |
| Last Modified: | 30 Dec 2025 06:53 |
| URI: | https://ir.lib.ugm.ac.id/id/eprint/24370 |
