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Accuracy of direct and indirect methods for assessing bovine colostrum quality using a latent class model fit within a Bayesian framework.
Elsohaby, I; Arango-Sabogal, J C; McClure, J T; Dufour, S; Buczinski, S; Keefe, G P.
Afiliación
  • Elsohaby I; Department of Animal Medicine, Faculty of Veterinary Medicine, Zagazig University, Zagazig City 44511, Sharkia Province, Egypt; Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, PEI, Canada C1A 4P3. Electronic address: ielsohaby@upei.ca.
  • Arango-Sabogal JC; One Health and Veterinary Innovative Research and Development Group, School of Veterinary Medicine, University of Antioquia, Medellin, Colombia 050034.
  • McClure JT; Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, PEI, Canada C1A 4P3.
  • Dufour S; Department of Pathology and Microbiology, Faculty of Veterinary Medicine, University of Montreal, Saint-Hyacinthe, QC, Canada J2S 2M2.
  • Buczinski S; Département des Sciences Cliniques, Faculty of Veterinary Medicine, University of Montreal, Saint-Hyacinthe, QC, Canada J2S 2M2.
  • Keefe GP; Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, PEI, Canada C1A 4P3.
J Dairy Sci ; 104(4): 4703-4714, 2021 Apr.
Article en En | MEDLINE | ID: mdl-33612236
ABSTRACT
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 <23% for digital Brix refractometer and <50 g/L for RID and TIR spectroscopy, median (95% BCI) Se estimates were 73.2 (68.4-77.7), 86.2 (80.6-91.0), and 91.9% (89.0-94.2), respectively. Median (95% BCI) Sp estimates were 85.2% (81.0-88.9) for digital Brix refractometer, 99.4% (97.0-100) for RID, and 90.7% (87.8-93.2) for TIR spectroscopy. Median (95% BCI) within-herd low-quality colostrum prevalence was estimated at 32.5% (27.9-37.4). In conclusion, using digital Brix refractometer at a Brix threshold of <23% could reduce feeding of low-quality colostrum to calves and improve colostrum and calf management practices in Atlantic Canada dairy herds. The TIR spectroscopy showed high Se in detection of low-quality colostrum. However, the RID assay, which is used as the reference test in several studies, showed limited Se for detection of low-quality colostrum.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Inmunoglobulina G / Calostro Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals / Pregnancy País/Región como asunto: America do norte Idioma: En Revista: J Dairy Sci Año: 2021 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Inmunoglobulina G / Calostro Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals / Pregnancy País/Región como asunto: America do norte Idioma: En Revista: J Dairy Sci Año: 2021 Tipo del documento: Article