Identifying the licking behaviour in beef cattle may provide a means to measure time spent licking for estimating individual block supplement intake. This study aimed to determine the effectiveness of tri-axial accelerometers deployed in a neck-collar and an ear-tag, to characterise the licking behaviour of beef cattle in individual pens. Four, 2-year-old Angus steers weighing 368 ± 9.3 kg (mean ± SD) were used in a 14-day study. Four machine learning (ML) algorithms (decision trees [DT], random forest [RF], support vector machine [SVM] and k-nearest neighbour [kNN]) were employed to develop behaviour classification models using three different ethograms: (1) licking vs. eating vs. standing vs. lying; (2) licking vs. eating vs. inactive; and (3) licking vs. non-licking. Activities were video-recorded from 1000 to 1600 h daily when access to supplement was provided. The RF algorithm exhibited a superior performance in all ethograms across the two deployment modes with an overall accuracy ranging from 88% to 98%. The neck-collar accelerometers had a better performance than the ear-tag accelerometers across all ethograms with sensitivity and positive predictive value (PPV) ranging from 95% to 99% and 91% to 96%, respectively. Overall, the tri-axial accelerometer was capable of identifying licking behaviour of beef cattle in a controlled environment. Further research is required to test the model under actual grazing conditions.

No abstract

Objective: To examine the effects of the salinity level of drinking water on the egg production and quality of Alabio ducks. Materials and Methods: A total of 60 female Alabio ducks, aged 6 months, were subjected to this study. All ducks were kept in stage-type cages (1 m length × 1 m width × 0.5 m height), where each cage was inhabited by 4 ducks for 56 days of experimentation. All ducks were offered a mixed ration ad libitum for laying ducks, according to the nutritional requirements for egg-type ducks. The treatment in this study was drinking water with five stratified salinity levels, namely P0 = freshwater (0% salinity); P1 = water with a salinity of 0.75 practical salinity unit (PSU) (equal to 0.75 g NaCl/l); P2 = water with a salinity of 1.5 PSU (1.5 gm/l); P3 = water with a salinity of 2.5 PSU (2.5 gm/l); and P4 = water with a salinity of 3 PSU (3.0 gm/l). Observations were made on water intake, feed intake, egg production, and egg quality (egg weight, egg shape index density, shell proportion, shell thickness, yolk index, albumen index, and Haugh unit). Results: The results showed that the difference in salinity levels in drinking water from 0.75 PSU to 3 PSU did not affect water intake, feed intake, egg production, or egg quality of Alabio ducks for the first 56 days of the laying period (p > 0.05). Conclusions: It was concluded that Alabio ducks have a good tolerance for drinking water salinity of up to 3 PSU, or equal to 3 gm/l NaCl.

Automated weighing systems to monitor BW and supplement intake (SI) of individual grazing cattle are being developed to better understand the seasonal nutrition and performance of grazing livestock. This study established (1) the accuracy and repeatability of a commercial walk-over weighing (WoW) system for estimating BW and (2) the accuracy of an automatic supplement weighing (ASW) unit for estimating SI based on measuring time spent at the unit. The WoW and ASW units monitored BW and SI of 112 cattle consisting of 55 cows and 57 calves grazed on a 32.5 ha paddock for 41 days, with an average of 258 BW records collected per day. Static BWs were recorded at each mustering event (n = 7) and were compared to repeated measurements collected by the WoW on the day of each mustering event. Body weight was overestimated by the WoW, with the predicted BW of calves and cows averaging 10 and 21 kg heavier, respectively, than actual, and root MS prediction errors (RMSPE) of 5.1% and 5.5% of the static BW, respectively. For both calves and cows, 38% of the MS prediction errors (MSPE) was mean bias (MB) error and 9% of MSPE was slope bias error. The concordance correlation coefficient (CCC; 0.90 v. 0.80) and modelling efficiency (MEF; 0.78 v. 0.62) of WoW BW for calves were higher than for cows, indicating that the predicted values were deviating from a 1 : 1 relationship and in particular as weight increases. A rolling average across five or more consecutive BW measures improved the accuracy of the WoW BW estimates. Regarding estimates of SI, the aggregated time the herd spent at the ASW unit was strongly associated with total SI (R2 = 0.92; P < 0.001). Further, positive linear relationships (P < 0.001) existed between cumulative weighted time spent at the ASW unit (min) and concentration of fenbendazole (FBZ) used as an intake marker and its derivatives (oxfendazole and oxfendazole sulfone) in the plasma of individual cows, with R2 of 0.54, 0.73 and 0.75, respectively. Although the WoW overestimated static BW, the low bias in the slope indicated that a linear regression model could be developed to adjust the WoW BW to reduce the MB and improve the estimate of WoW BW. The significant positive relationship between time spent at the ASW unit and individual blood FBZ concentration identified the suitability of the ASW unit for estimating SI by grazing cattle.

No abstract