| Abstrak/Abstract |
Determining kappa and iota carrageenan composition is essential for optimizing its functionality in food ap
plications. 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 ach
ieved high accuracy, with calibration, cross-validation, and prediction coefficients (R
2
600–1100 cm
1
) exceeding 0.9 within the
spectral range. Validation with real samples confirmed its reliability, making it a suitable tool for
carrageenan quality assessment and industrial applications. |
