Abstract: [Objective] To meet the demand for rapid and accurate quantitative determination of lactoferrin content in a large number of samples during dairy processing a detection and correction model for lactoferrin content in milk was established by combining mid-infrared spectroscopy with chemometric. [Method] Taking 108 milk samples as the research objects,the lactoferrin content was measured by high performance liquid chromatography,and the spectral data of the milk samples were collected. To investigate the effects of preprocessing methods such as normalization first derivative second derivative standard normal variable transformation multiple scattering correction and wavelet transform on the prediction accuracy of partial least squares PLS quantitative model lactoferrin. [Result] The first derivative and the standard normal variable transformation were the optimal preprocessing methods for spectral data. The determination coefficient of the model correction set was 0.941 7, and the root mean square error of the correction was 1.142. The root mean square error of prediction was 1.187 which had good prediction ability. [Conclusion] The results of this study are of great significance for quality control and production efficiency optimization in dairy production proces.

Key words: lactoferrin, mid-infrared spectroscopy, PLS prediction model, quantitative analysis, quality monitoring