Evaluation of the Brix refractometer as an on-farm tool for the detection of passive transfer of immunity in dairy calves.

OBJECTIVES: To investigate the accuracy of both the optical and digital Brix refractometers compared with radial immunodiffusion (RID) for determining the immunoglobulin G (IgG) concentrations in dairy calf serum. DESIGN: The experiment design was a cross-sectional survey of four dairy farms. Serum was sampled from 12 calves from each farm at approximately 48 hours of age. METHODS: Serum IgG concentrations of 48 calves were measured using RID and both types of Brix refractometer. RESULTS: IgG concentrations measured by Brix refractometer scores correlated with RID results: 0.74 and 0.71 for the digital and optical devices, respectively. The minimum Brix score that identified calf serum with success of passive immunity (>1000 mg/dL RID IgG) with 100% accuracy was 10% for both devices. The optical and digital devices performed similarly at identifying IgG concentrations in calf serum, with a concordance of 87%. CONCLUSION: Brix refractometer score ≥10% can be used to classify calves with successful transfer of passive immunity and the devices are sufficiently accurate for use as a simple, inexpensive on-farm tool for the monitoring of neonatal dairy calf immunity levels.

Short communication: Validation of genomic breeding value predictions for feed intake and feed efficiency traits.

Validating genomic prediction equations in independent populations is an important part of evaluating genomic selection. Published genomic predictions from 2 studies on (1) residual feed intake and (2) dry matter intake (DMI) were validated in a cohort of 78 multiparous Holsteins from Australia. The mean realized accuracy of genomic prediction for residual feed intake was 0.27 when the reference population included phenotypes from 939 New Zealand and 843 Australian growing heifers (aged 5-8 mo) genotyped on high density (770k) single nucleotide polymorphism chips. The 90% bootstrapped confidence interval of this estimate was between 0.16 and 0.36. The mean realized accuracy was slightly lower (0.25) when the reference population comprised only Australian growing heifers. Higher realized accuracies were achieved for DMI in the same validation population and using a multicountry model that included 958 lactating cows from the Netherlands and United Kingdom in addition to 843 growing heifers from Australia. The multicountry analysis for DMI generated 3 sets of genomic predictions for validation animals, one on each country scale. The highest mean accuracy (0.72) was obtained when the genomic breeding values were expressed on the Dutch scale. Although the validation population used in this study was small (n=78), the results illustrate that genomic selection for DMI and residual feed intake is feasible. Multicountry collaboration in the area of dairy cow feed efficiency is the evident pathway to achieving reasonable genomic prediction accuracies for these valuable traits.