Effects of Incorporating Dry Matter Intake and Residual Feed Intake into a Selection Index for Dairy Cattle Using Deterministic Modeling.

The inclusion of feed efficiency in the breeding goal for dairy cattle has been discussed for many years. The effects of incorporating feed efficiency into a selection index were assessed by indirect selection (dry matter intake) and direct selection (residual feed intake) using deterministic modeling. Both traits were investigated in three ways: (1) restricting the trait genetic gain to zero, (2) applying negative selection pressure, and (3) applying positive selection pressure. Changes in response to selection from economic and genetic gain perspectives were used to evaluate the impact of including feed efficiency with direct or indirect selection in an index. Improving feed efficiency through direct selection on residual feed intake was the best scenario analyzed, with the highest overall economic response including favorable responses to selection for production and feed efficiency. Over time, the response to selection is cumulative, with the potential for animals to reduce consumption by 0.16 kg to 2.7 kg of dry matter per day while maintaining production. As the selection pressure increased on residual feed intake, the response to selection for production, health, and fertility traits and body condition score became increasingly less favorable. This work provides insight into the potential long-term effects of selecting for feed efficiency as residual feed intake.

Opportunities and limitations of milk mid-infrared spectra-based estimation of acetone and ß-hydroxybutyrate for the prediction of metabolic stress and ketosis in dairy cows.

Subclinical (SCK) and clinical (CK) ketosis are metabolic disorders responsible for big losses in dairy production. Although Fourier-transform mid-infrared spectrometry (FTIR) to predict ketosis in cows exposed to great metabolic stress was studied extensively, little is known about its suitability in predicting hyperketonemia using individual samples, e.g. in small dairy herds or when only few animals are at risk of ketosis. The objective of the present research was to determine the applicability of milk metabolites predicted by FTIR spectrometry in the individual screening for ketosis. In experiment 1, blood and milk samples were taken every two weeks after calving from Holstein (n = 80), Brown Swiss (n = 72) and Swiss Fleckvieh (n = 58) cows. In experiment 2, cows diagnosed with CK (n = 474) and 420 samples with blood ß-hydroxybutyrate [BHB] <1.0 mmol/l were used to investigate if CK could be detected by FTIR-predicted BHB and acetone from a preceding milk control. In experiment 3, correlations between data from an in farm automatic milk analyser and FTIR-predicted BHB and acetone from the monthly milk controls were evaluated. Hyperketonemia occurred in majority during the first eight weeks of lactation. Correlations between blood BHB and FTIR-predicted BHB and acetone were low (r = 0.37 and 0.12, respectively, P < 0.0001), as well as the percentage of true positive values (11.9 and 16.6%, respectively). No association of FTIR predicted ketone bodies with the interval of milk sampling relative to CK diagnosis was found. Data obtained from the automatic milk analyser were moderately correlated with the same day FTIR-predicted BHB analysis (r = 0.61). In conclusion, the low correlations with blood BHB and the small number of true positive samples discourage the use of milk mid-infrared spectrometry analyses as the only method to predict hyperketonemia at the individual cow level.