Assessment of subclinical mastitis in milch animals by different field diagnostic tests in Barishal district of Bangladesh

Autor: Jaisan Islam, Farzana Islam Rume, Isart Jahan Liza, Preeti Kumari Chaudhary, AKM Mostafa Anower
Rok vydání: 2019
Zdroj: Asian-Australasian Journal of Bioscience and Biotechnology. 4:24-33
ISSN: 2414-6293
2414-1283
Popis: This study was carried out to assess the prevalence of subclinical mastitis in milch animals by different field diagnostic tests. A total of 100 milk samples (40 cow, 40 buffalo and 20 goat) were culled to pursue this study which were subjected to physical assay and subsequently screened for subclinical mastitis by using 5 different field diagnostic tests viz. California Mastitis Test (CMT), White Side Test (WST), White Side + Dye Test (WSDT), Surf Test (ST) and Surf + Dye Test (SDT). Overall prevalence of subclinical mastitis (SCM) found in this study was 42.5%, 32.5% and 35% in cow, buffalo and goat respectively. Higher prevalence of SCM was detected in cow (47.06%) and buffalo (53.85%) aged between 3 to 5 years whereas in goat (57.15%), 2 to 3 years of age. In aspect of breed, crossbred cow (50%), Murrah buffalo (40%) and Jamunapari goat (50%) were found more affected with SCM. The prevalence of SCM was higher in cows of 3rd parity (41.18%), buffaloes of both 2nd and 3rd parity (30.77%) and goats of 2nd parity (42.86%). Animals being in mid lactation gave more positive cases (46.67% cow, 46.67% buffalo and 42.85% goat). SCM was found in higher prevalence in high yielding animals and in animals that were not being subjected to hygienic milking practice. Among the 5 diagnostic tests, SCM detection efficacy in comparison was higher by CMT. So as SCM has been found to be a major ascending risk in the area, the hygienic milk production activity in this area as a whole requires an intervention including further investigation on the etiological agents associated with prevalence of mastitis to undertake measurable control options of mastitis in the area. Asian Australas. J. Biosci. Biotechnol. 2019, 4 (1), 24-33
Databáze: OpenAIRE
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