Feeding high-quality colostrum is essential for calf health and future productivity. Therefore, accurate assessment of colostrum quality is a key component of dairy farm management plans. Direct and indirect methods are available for assessment of colostrum quality; however, the indirect methods are rapid, inexpensive, and can be performed under field settings. A hierarchical latent class model fit within a Bayesian framework was used to estimate the sensitivity (Se) and specificity (Sp) of the radial immunodiffusion (RID) assay, transmission infrared (TIR) spectroscopy, and digital Brix refractometer for the assessment of low-quality bovine colostrum in Atlantic Canada dairy herds. The secondary objective of the study was to describe the distribution of herd prevalence of low-quality colostrum. Colostrum quality of 591 samples from 42 commercial Holstein dairy herds in 4 Atlantic Canada provinces was assessed using RID, TIR spectroscopy, and digital Brix refractometer. The accuracy of all tests at different Brix value thresholds was estimated using Bayesian latent class models to obtain posterior estimates [medians and 95% Bayesian credibility intervals (95% BCI)] for each parameter. Using a threshold of
