Supporting data and ARRIVE reporting materials for “Technical Performance of Wearable Sensors for Behavioural Signals of Heat Detection in Nigerian Commercial Dairy Cattle”

This repository contains the de-identified dataset and supporting reporting materials associated with the study “Technical Performance of Wearable Sensors for Behavioural Signals of Heat Detection in Nigerian Commercial Dairy Cattle.”The study evaluated the technical feasibility and behavioural performance of Bodit Farmer’s Hands wearable collar sensors during a 56-day observational field study involving 20 crossbred Friesian-Holstein × White Fulani dairy cows at the FanMilk Danone Model Cattle Farm in Ogun State, Nigeria.The dataset contains 1,116 cow-day observations retained after application of a minimum 90% daily data-completeness criterion. Recorded variables include sensor-derived measures of rumination, eating, resting, activity, mounting, sniffing and related behaviours, together with environmental and data-quality measures.Heat-positive cow-days were classified by the sensor algorithm and were not independently validated against progesterone measurements, artificial insemination records, conception outcomes or other reproductive ground-truth measures. The data should therefore be interpreted as supporting a technical and behavioural feasibility assessment rather than a biological validation study.Supporting files include the completed ARRIVE 2.0 checklist and the ARRIVE study flowchart.