Summary
Investigating the effect of homogenisation on the prediction performance of protein content by using near‐infrared (NIR) spectroscopy is helpful to improve protein determination precision. For this purpose, the influence of homogenisation on milk fat globules and NIR spectra was analysed firstly. Then, NIR spectra of eighty‐seven cow milk samples before and after homogenisation were obtained. Multiplicative scatter correction was used to do spectral pretreatment. Uninformative variable elimination based on partial least squares (UVE‐PLS) and successive projection algorithm was used to extract characteristic variables. Partial least squares regression (PLSR) and least squares support vector machine models were established. The results showed that homogenisation made milk fat globules be distributed evenly, decreased the size of fat globules and improved NIR spectral repeatability and prediction precision on protein content. The best model was PLSR‐UVE‐PLS, having good and excellent protein prediction ability for un‐homogenised milk (RMSEP = 0.06 g/100 g, RPD = 2.69) and homogenised milk (RMSEP = 0.04 g/100 g, RPD = 3.59), respectively.
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