Development of methods for quantification and classification of gelatin in capsule shell using chemometric analysis of FTIR spectroscopic data
DOI:
https://doi.org/10.3329/bjsir.v57i2.60405Keywords:
Fourier-transform infrared spectroscopy (FTIR); Partial least-square regression (PLSR); Soft independent Modeling by Class Analogy (SIMCA)Abstract
Capsule shell from animal source (bovine or porcine gelatin) is a problem for the follower of different religions and vegetarian. In that case, vegetable capsule shell could be a solution. In this research, we proposed a simple and cost-effective technique for detection of gelatin in vegetable capsule shell and for classification of capsule shell by source, based on Chemometric techniques with FTIR spectroscopic data. Partial Least-Square Regression (PLSR) models were developed and their efficiencies were assessed with spectroscopic data of range of 4000-700 cm-1. PLSR shows very good prediction efficiency (R2= 98%) for both vegetable capsule shell and gelatin. In addition, Soft Independent Modeling by Class Analogy (SIMCA) classification method were developed and assessed with spectral data of capsule shells from vegetable and animal sources. Results prove that FTIR spectroscopy in combination with chemometric method can be used for the classification of capsule shell by source and quantification of gelatin in vegetable capsule shell to ensure their authenticity.
Bangladesh J. Sci. Ind. Res. 57(2), 91-98, 2022
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