Abstract
A rapid method for the quantification of cholesterol in the standardized dairy powders was developed using Fourier transform near-infrared (FT-NIR) spectroscopy coupled with appropriate chemometric techniques. Different spectral preprocessing methods were investigated for the partial least-squares (PLS) regression model development. The results showed that the second derivative PLS model in the spectral region of 6101.9–5446.2 cm−1 was the most robust with the best performance indicators (r2 validation = 0.9998, RMSECV = 1.05 mg cholesterol/100 g, rank = 6 and RPD > 8). Functional band assignment of the major spectral peaks in the cholesterol spectrum was also possible. Statistical evaluation with the HPLC method proved that the developed NIR–chemometric method has good reproducibility and satisfactory accuracy profile. The comparable relative standard deviation (RSD) along with good precision accuracy (95.9–101%) of the proposed FT-NIR method, demonstrate its suitability for the rapid and routine analysis of cholesterol content in the dairy powders.
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