Rapid quantification of cholesterol in dairy powders using Fourier transform near infrared spectroscopy and chemometrics

- FT-NIR spectroscopy used for cholesterol quantification from dairy powders using 80 samples.
- Major peaks of cholesterol successfully elucidated.
- Second derivative preprocessing gave the best predictive ability with highest r2 of 0.9998 and lowest RMSECV of 1.05.
- Comparison with HPLC method proved its accuracy and reproducibility.

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.