The effects of the ratio of pellets of wheat and barley grains to ground corn grain in the diet on sorting and chewing activities of heat stressed dairy cows

Abstract

Background Normal feeding behaviours is one of the criteria of the health condition of dairy cows particularly in the condition of heat stress. Objective The study evaluated the effects of the ratio of pellets of wheat and barley grains to ground corn grain on sorting activity and chewing behaviour of lactating dairy cows managed under ambient conditions including natural heat stress events. Materials and Methods Nine multiparous cows (650 ± 56 kg Body Weight; mean ± SD) averaging 102 ± 13 days in milk and producing 54 ± 6 kg/d were randomly assigned to a triplicate 3 × 3 Latin square. During each 21‐d period, cows received one of three total mixed rations as dietary treatments. The dietary treatments were three ratio of pellets (containing 50% ground wheat and 50% ground barley): ground corn on a dry matter (DM) basis: 1) 33.3:66.6 (low); 2) 66.6:33.3 (medium); and 3) 100:0 (high). During the experiment, the ambient temperature‐humidity index was equal or more than 72, indicating that the cows were predisposed to heat stress condition. Results Increasing the proportion of wheat‐barley pellets in the diet had a minimal effect on sorting index of different particles during the first 6 h of the day. However, later in the day (6‐18h), sorting against long particles (particles >19 mm) and in favour of fine particles (particles <1.18 mm) linearly increased with increasing the proportion of pellet; as a result overall daily sorting against long particles was increased with increasing the proportion of pellets. Although the average of daily eating and rumination was not affected by the treatments in the day times with high ambient THI, time spent for eating and rumination was low and eating time had more fluctuation for diet contained a high level of pellets. Conclusion Increasing the proportion of pellets of barley and wheat grains in the diet under conditions of heat stress caused more fluctuation in daily eating behaviour and cows were predisposed to sort against long particles.

Development of a Low-Cost Livestock Sorting Information Management System Leveraging Deep Learning, AI, and IoT Technologies

“…The process of livestock sorting entails the systematic classification of animals according to several criteria, including weight, health condition, and productivity effectiveness. Accurate sorting techniques are of utmost importance to enhance agricultural operations, reduce labor expenses, and maintain the well-being of animals [4]. Precisely categorizing animals is crucial in effectively controlling and containing diseases and mitigating infection transmission throughout livestock populations.…”