Milk and liquid-feed insufficiency during the vulnerable period of early calf development can result in inadequate energy and nutrient intake, impaired growth, increased susceptibility to disease, and potentially death. Orphaned calves are particularly vulnerable because they lack direct access to maternal milk and depend entirely on human-managed feeding. This paper proposes a precision-livestock framework for early detection of inadequate milk intake and emerging nutritional risk using a lightweight, multi-sensor collar combined with automated feeding records and machine-learning algorithms.

The proposed concept was motivated by the reported deaths in July 2026 of two orphaned calves, Maurya and Gauri, approximately 6 months and 2 months old, respectively, who were reported by the caregiver to have died following inadequate milk/nutritional intake. Their histories illustrate an important practical problem: a calf can deteriorate nutritionally before obvious clinical signs become apparent. Existing precision-dairy research demonstrates that automated milk feeders can record milk consumption, drinking speed, feeding visits and other feeding behaviours, and that these variables can contribute to early detection of disease and underperformance. Accelerometers and other wearable sensors can additionally monitor activity, lying behaviour and, with limitations, rumination[1-7].

We therefore hypothesize that a multimodal system integrating collar-derived activity, neck movement, temperature and feeding-related behaviour with direct milk-intake measurements, body-weight trajectories and environmental variables could generate an individualized nutritional-risk score before severe malnutrition develops. Importantly, the proposed collar would not directly diagnose lactose or sucrose deficiency. Instead, those conditions would require milk-composition measurement or laboratory analysis; the collar would detect physiological and behavioural consequences consistent with inadequate nutritional supply. A conceptual theorem and algorithm are proposed to formalize this early-warning framework.

 

Keywords: Dairy calf; Orphaned calf; Milk insufficiency; Malnutrition; Precision livestock farming; Smart collar; Wearable sensor; Automated milk feeder; Machine learning; Early warning system; Animal welfare; Nutritional surveillance.