Standardization of milk infrared spectra for the retroactive application of calibration models

The objective of this study was to standardize the infrared spectra obtained over time and across 2 milk laboratories of Canada to create a uniform historical database and allow (1) the retroactive application of calibration models for prediction of fine milk composition; and (2) the direct use of spectral information for the development of indicators of animal health and efficiency. Spectral variation across laboratories and over time was inspected by principal components analysis (PCA). Shifts in the PCA scores were detected over time, leading to the definition of different subsets of spectra having homogeneous infrared signal. To evaluate the possibility of using common equations on spectra collected by the 2 instruments and over time, we developed a standardization (STD) method. For each subset of data having homogeneous infrared signal, a total of 99 spectra corresponding to the percentiles of the distribution of the absorbance at each wavenumber were created and used to build the STD matrices. Equations predicting contents of saturated fatty acids, short-chain fatty acids, and C18:0 were created and applied on different subsets of spectra, before and after STD. After STD, bias and root mean squared error of prediction decreased by 66% and 32%, respectively. When calibration equations were applied to the historical nonstandardized database of spectra, shifts in the predictions could be observed over time for all investigated traits. Shifts in the distribution of the predictions over time corresponded to the shifts identified by the inspection of the PCA scores. After STD, shifts in the predicted fatty acid contents were greatly reduced. Standardization reduced spectral variability between instruments and over time, allowing the merging of milk spectra data from different instruments into a common database, the retroactive use of calibrations equations, or the direct use of the spectral data without restrictions.