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Feed accounts for the greatest proportion of egg production costs and there is substantial variation in feed to egg conversion ratio (FCR) efficiency between individual hens. Despite this understanding, there is a paucity of information regarding layer hen feeding behaviour, diet selection and its impact on feed efficiency. It was hypothesised that variation in feed to egg conversion efficiency between hens may be influenced by feeding behaviour. For this experiment, two 35-bird groups of ISA Brown layers were selected from 450 individually caged hens at 25-30 weeks of age for either low FCR < 1.8 ± 0.02 (high feed efficiency (HFE) or high FCR > 2.1 ± 0.02 (low feed efficiency (LFE)). For each of these 70 hens, intake of an ad-libitum mash diet at 2-minute time intervals, 24 h a day, for 7 days was determined alongside behavioural assessment and estimation of the selection of components of the mash. The group selected for HFE had a lower feed intake, similar egg mass and associated lower FCR when compared with the LFE group. Whilst feed intake patterns were similar between HFE and LFE hens, there was a distinct intake pattern for all layer hens with intake rate increasing from 0300 to 1700 h with a sharp decline to 2200 h. High feed efficiency hens selected a diet with 25% more ash and 4% less gross energy than LFE hens. The LFE hens also spent more time eating with more walking events, but less time spent resting, drinking, preening and cage pecking events as compared with HFE hens. In summary, there was no contrasting diurnal pattern of feed consumption behaviour between the groups ranked on feed efficiency, however high feed efficiency hens consumed less feed and selected a diet with greater ash content and lower gross energy as compared with LFE hens. Our work is now focused on individual hen diet selection from mash diets with an aim of formulating precision, targeted diets for greater feed efficiency.

Cattle liveweight (LW) monitoring is essential for the effective management of animal productivity and welfare, particularly in decision-making on farms. Traditional static weigh (SW) systems require animals to be moved to fixed scales, posing challenges in extensive beef systems due to labour demands, costs, stress, and weight loss during muster. This study evaluated the relationship between LW measured by a SW system and a mobile in-field weighing system, Optiweigh (OW), in 65 weaners (Angus, Shorthorn, and Angus-Shorthorn cross) grazing on forage oats at a commercial beef property in north-west NSW, Australia. Over 22 weeks, cattle were weighed fortnightly using SW scales in the cattle yards while OW continuously monitored LW in the paddock. Lin's concordance correlation coefficient showed a strong association between OW and SW liveweight (CCC = 0.97; P < 0.001), with no influence from breed or sex. However, OW slightly over-predicted LW for lighter cattle (≤ 382 kg) and under-predicted for heavier cattle (> 382 kg), prompting the development of a correction. Further research is needed to understand the reasons for these discrepancies, potentially related to diet. Additionally, cattle attendance at OW was affected by size, season, and individual variation (P < 0.001). Overall, the OW system simply and accurately monitored the temporal changes in cattle LW through voluntary animal attendance in remote systems.

Heat stress causes significant economic losses by reducing the productivity and welfare of cattle whilst requiring a significant investment in resource for amelioration. Panting score (PS) is considered a robust indicator of cattle heat stress; however, individualised visual monitoring is impractical. Thermal index-based monitoring and mitigation decisions are applied at the herd level, but they have limited application for the individual animal. As such, an automated system to monitor the real-time animal response to heat stress is required for strategic mitigation. Our objectives were to validate an accelerometer-based ear tag sensor to monitor cattle panting and to determine individual variability in heat stress responses with reference to thermal indices. Two experiments were conducted: Experiment 1 validated the sensors, and Experiment 2 determined individual variability comparing sensor data against thermal indices. Ear tag sensors were fitted at feedlot entry to continuously monitor the behaviour of 100 steers of mixed breed in Experiment 1 and 200 steers and heifers of mixed breed in Experiment 2. Sensor-derived ‘heavy breathing’ was validated against visually observed PS. Sensor-derived behaviour bouts were analysed as ‘raw’, and single behaviour states were also converted to the preceding bout of ≥2 min, which was referred to as ‘fill’ data for the validation study. Our results demonstrate the sensors’ ability to accurately monitor panting in feedlot cattle. Sensor-recorded ‘heavy breathing’ duration per animal was highly correlated to observed panting duration for both raw (r = 0.89) and fill (r = 0.90) data; however, the concordance correlation co-efficient was lower for raw (0.45) as compared with fill (0.76). Predicted agreement for raw data were 75%, 45%, and 68% and predicted agreement for fill data were 65%, 54%, and 83% for PS0, PS1, and PS2, respectively. Sensitivity for raw data were 39%, 37%, and 45% and for fill data, they were 59%, 54% and 82% for all PS data, PS1 and PS2, respectively. Specificity and positive predictive values for both raw (77% and 79%, respectively) and fill (65% and 77%, respectively) data show the probability of reporting false positives by sensors to be low. Experiment 2 revealed that the duration of panting increased from 0800 to 1700 h alongside changes in thermal indices with significant differences between and within breed and coat colour categories of cattle, suggesting that grouping and allocating heat amelioration measures by breed and coat colour can be effective in commercial feedlots. However, there was high variability (CV > 80%) in the duration of panting between individuals within the same breed and same coat colour, revealing the potential for strategic management at an individual level, and with the same data, genetic selection for heat resilience.

Modern livestock selection is rapidly condensing the indigenous cattle gene pool. This trend limits the options for future genetic selection to benefit both animal well-being and farmer challenges. Here we reveal the potential of Red Chittagong cattle (RCC), a native genotype of Bangladesh, for tackling these current and pending challenges. Red Chittagong cattle are reddish in color and small in size with mature bulls and cows weighing 342 and 180 kg from birth weights of 16 and 14 kg, respectively. Whilst low mean levels of milk production of 618 L across a 228-day lactation are recorded so are high levels of milk protein (3.8%) and fat (4.8%) with offered feed types typically low in nutritive value, particularly crude protein. However, one in five cows under farm condition yield >1,000 L/lactation. Alongside high levels of milk protein and fat, other key features of this breed include resistance to common diseases and parasites with a high level of adaptation to agro-ecological conditions. As opposed to other indigenous breeds, there is currently high genetic variation in the RCC population, and associated variation in productive and reproductive traits highlighting the opportunity for development through long-term breeding programs alongside improved management conditions. Such efforts would enable this breed to become a global resource for tackling the challenges of modern animal production systems. In addition, further work is required to reveal the demographic distribution of the breed, potential production levels through the provision of improved diets and the mechanisms enabling disease resistance and digestibility of feeds.