Assessment of milk conductivity and ph as early indicators of mastitis in lactating dairy cows

Mastitis, especially in its subclinical form, remains one of the most prevalent and economically detrimental diseases in dairy farming. It leads to a reduction in milk yield, alters milk composition, and generates considerable economic losses due to decreased quality and increased treatment costs. Early detection is therefore crucial to limit both health impacts on the animals and financial losses for producers. This study was conducted at the Jéthro center, a semi-intensive dairy farm located in Burkina Faso, with the objective of assessing the relevance of two key physicochemical parameters—electrical conductivity (EC) and pH—as potential early indicators of mastitis. Four cows at different stages of lactation were selected randomly from a herd of 15, and 56 residual milk samples were manually collected from individual udder quarters over four sampling campaigns. The electrical conductivity of milk samples was measured using a calibrated conductimeter, while pH values were obtained via a laboratory pH meter following standard calibration procedures. The findings show that 92.86% of the quarters presented EC values below 6 mS/cm, a level generally associated with healthy mammary quarters. However, one quarter (7.14%) displayed a conductivity between 6 and 7 mS/cm, suggesting potential subclinical mastitis. Across all samples, pH values remained relatively stable, within the normal range for bovine milk (6.6 to 6.8), with no strong anomalies observed. These results highlight milk electrical conductivity as a more sensitive and responsive indicator of udder health compared to pH. While pH remained largely unchanged even in potentially infected quarters, EC exhibited measurable variations correlated with udder condition. The study supports the integration of EC measurements into routine herd monitoring as a practical, cost-effective, and non-invasive tool for early detection of mastitis, particularly subclinical cases. Additionally, improvements in hygiene practices—such as teat disinfection, individual cleaning cloths, and regular milking equipment maintenance—are recommended to reduce infection risks. In conclusion, the evaluation of milk EC, supported by pH monitoring, can serve as a valuable diagnostic approach in dairy herd management. Further research involving a larger number of farms and incorporating microbiological analyses would strengthen these findings and contribute to better prevention strategies.