%0 Journal Article
%T Seasonal assessment of mastitis using thermogram analysis in murrah buffaloes.
%A Gayathri SL
%A Bhakat M
%A Mohanty TK
%J J Therm Biol
%V 121
%N 0
%D 2024 Apr 3
%M 38608549
%F 3.189
%R 10.1016/j.jtherbio.2024.103842
%X Mastitis is a global threat that challenges dairy farmers' economies worldwide. Sub-clinical mastitis (SCM) beholds the lion's share in it, as its visible clinical signs are not evident and are challenging to diagnose. The treatment of intramammary infection (IMI) demands antimicrobial therapy and subsequent milk withdrawal for a week or two. This context requires a non-invasive diagnostic tool like infrared thermography (IRT) to identify mastitis. It can form the basis of precision dairy farming. Therefore, the present study focuses on thermal imaging of the udder and teat quarters of Murrah buffaloes during different seasons to identify SCM and clinical mastitis (CM) cases using the Darvi DTL007 camera. A total of 30-45 lactating Murrah buffalo cows were screened out using IRT regularly throughout the year 2021-22. The IMI was further screened using the California mastitis test. The thermogram analysis revealed a significant difference (p < 0.01) in the mean values of the udder and teat skin surface temperature of Murrah buffaloes between healthy, SCM, and CM during different seasons. The mean values of udder skin surface temperature (USST) during different seasons ranged between 30.28 and 36.81 °C, 32.54 to 38.61 °C, and 34.32 to 40.02 °C among healthy, SCM, and CM-affected quarters. Correspondingly, the mean values of teat skin surface temperature (TSST) were 30.52 to 35.96 °C, 32.92 to 37.55 °C, and 34.51 to 39.05 °C, respectively. Further results revealed an increase (p < 0.01) in the mean values of USST during winter, summer, rainy, and autumn as 2.26, 4.04; 2.19, 3.35; 1.80, 3.21; and 1.45, 2.64 °C and TSST as 2.40, 3.99; 2.28, 3.26; 1.59, 3.09; and 1.68, 2.92 °C of SCM, CM-affected quarters to healthy quarters, respectively. The highest incidence of SCM was observed during autumn and CM during winter. Henceforth, irrespective of the seasons studied in the present study, IRT is an efficient, supportive tool for the early identification of SCM.