Physiological and production profiling with TOPSIS multi-criteria ranking for identification of heat-tolerant White Fulani cows under tropical farm conditions

Heat stress negatively affects dairy productivity in the humid tropics. To quantify individual variation in tolerance, a longitudinal study was conducted on 45 multiparous White Fulani cows monitored for 180 days (mean Temperature–Humidity Index (THI) = 81.00 ± 3.00; peaks = 88.00). Physiological traits (rectal temperature, RT; respiratory rate, RR; heart rate, HR) and milk yield (MY) were recorded twice daily. Linear mixed-effects models, with cow random intercepts, were used to estimate adjusted least-squares means for each trait and to quantify responses to THI. The RT rose by 0.11 °C per unit THI (p < 0.001), while RR and HR increased by 3.4 breaths min⁻¹ and 1.9 beats min⁻¹ per unit THI, respectively. MY declined by 0.26 kg d⁻¹ per 10-unit THI rise (p = 0.032). The adjusted cow-level means were subsequently integrated into a multi-criteria decision-making framework using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with CRITIC-derived weights. MY received the highest weight (0.34), followed by RT (0.27), RR (0.22) and HR (0.17). Closeness coefficients ranged from 0.19 to 0.84, and five cows consistently ranked highest across weighting scenarios (ρ = 0.89 between CRITIC- and equal-weight rankings). Principal component analysis and Ward’s clustering separated cows into tolerant, intermediate, and susceptible groups, with strong agreement to the TOPSIS classification (Adjusted Rand Index = 0.82). The findings demonstrate that combining mixed-effects modelling with CRITIC-weighted TOPSIS provides a robust, field-ready pipeline for ranking heat tolerance in White Fulani cows. Approximately 22% of the herd were identified as highly tolerant, maintaining lower RT and higher MY under severe THI. This approach offers a practical tool for genetic selection and management of thermotolerant cows in tropical dairy systems.