Evaluation of an early warning system for elevated ß-hydroxy­butyrate and non-esterified fatty acid values based on Fourier transform infrared spectra from routine milk samples

Abstract

The objective of our study was to evaluate an early warning system for the detection of elevated ß-hydroxybutyrate (BHB) and non-esterified fatty acid (NEFA) levels in Fourier transform infrared (FTIR) spectroscopy data from routine milk samples. Starting from the monthly milk performance test of the German Dairy Herd Improvement Associations (DHIAs), we evaluated the benefit of more frequent milk sampling in early lactation to detect cows at risk for hyperketonemia and exaggerated fat mobilization. For the validation of the early warning system, milk and blood samples as reference data were obtained from Holstein-Friesian (HF) and German Simmental (GS) dairy cows in a one-year field trial. To establish an early warning system that utilizes a prediction model for FTIR data, the preferable day in milk (DIM) and a suitable sampling interval were investigated. For elevated NEFA values, a DIM of 6 – 13 was identified as the period for preferable sampling. A weekly testing frequency was used for nearly all of the cows in early lactation, and the number of identified cows with elevated NEFA or BHB values was three times higher than the actual situation of milk testing. Prediction models based on the regression tree full model selection (rtFMS) method, as presented by previous work, were validated to detect elevated BHB and NEFA values in FTIR data from routine milk samples. Different model options were compared in the regression tree regarding their significant impact on the prediction performance, measured in balanced accuracy. The chosen prediction model for each metabolite was validated on the reference data set as the gold standard. The evaluated early warning system might be implemented as an additional flexible milk sampling in the routine processes of the milk performance test of the DHIAs.