Changes in eating time, chewing activity and dust concentration in horses fed either alfalfa cubes or long‐stem hay

Abstract

Background:Chewing is an essential physiological process in horses; yet, the physical form of feeds may affect their chewing and feeding behaviour with consequences for equine digestion and health. Objectives and methods:The present study evaluated the potential of a commercial forage cubes made from alfalfa and mixed meadow grasses to maintain chewing activity when compared with a traditional long and fibre-rich hay. An additional aim was to measure the dust formation during feeding. The experiment was a crossover design with six horses (11 ± 4 years old, mean ± SD), fed with 5 kg (as-fed basis) of their feed (long hay or alfalfa cubes) overnight. Eating and chewing activity was measured using the EquiWatch system with a sensor-based halter.Results: Data showed that by feeding the same amount of feed overnight, cube feeding led to 24% shorter eating time (on average 67 min less) and 26% fewer total chews compared to the long hay. On an hourly basis, horses also spent more time eating and chewing the long hay compared to the cubes. The cube feeding led to a higher dust concentration of the inhalable fraction (<100 µm), but not of the thoracic (<10 µm) fraction. Nevertheless, average dust concentrations were generally low for both cubes and hay, whereby both were of sound hygienic status. Conclusion and recommendation:Our data suggest that feeding alfalfa-based cubes overnight generated shorter eating time and less chews than the long hay without major differences in the thoracic dust. Therefore, because of the decreased eating time and chews, alfalfa-based cubes should not be fed a sole forage source, especially when it is to be fed without restriction.

Socio-Technical Analysis of the Benefits and Barriers to Using a Digital Representation of the Global Horse Population in Equine Veterinary Medicine

“…Examples include implanted transponder (RFID) chips for unique animal identification [12], and devices that monitor vital health parameters, like heart-rate and regularity, respiratory rate, and body temperature, offering basic insights into the animal's well-being [13][14][15][16][17]. Additionally, there are systems for recording body movement patterns, crucial for the early detection of serious illnesses, such as infections or colic [18], as well as tools for intelligent stall interaction and (partially) automated animal husbandry, along with monitoring of feed and liquid intake [19][20][21].…”