Monitoring activity patterns of animals offers the opportunity to assess individual health and welfare in support of precision livestock farming. The purpose of this study was to use a triaxial accelerometer sensor to determine the diel activity of sheep on pasture. Six Perendale ewe lambs, each fitted with a neck collar mounting a triaxial accelerometer, were filmed during targeted periods of sheep activities: grazing, lying, walking, and standing. The corresponding acceleration data were fitted using a Random Forest algorithm to classify activity (=classifier). This classifier was then applied to accelerometer data from an additional 10 ewe lambs to determine their activity budgets. Each of these was fitted with a neck collar mounting an accelerometer as well as two additional accelerometers placed on a head halter and a body harness over the shoulders of the animal. These were monitored continuously for three days. A classification accuracy of 89.6% was achieved for the grazing, walking and resting activities (i.e., a new class combining lying and standing activity). Triaxial accelerometer data showed that sheep spent 64% (95% CI 55% to 74%) of daylight time grazing, with grazing at night reduced to 14% (95% CI 8% to 20%). Similar activity budgets were achieved from the halter mounted sensors, but not those on a body harness. These results are consistent with previous studies directly observing daily activity of pasture-based sheep and can be applied in a variety of contexts to investigate animal health and welfare metrics e.g., to better understand the impact that young sheep can suffer when carrying even modest burdens of parasitic nematodes.

The objective of this study was to determine the relationships between ewe lamb live weight and body condition score immediately prior to breeding with fertility (ewes pregnant per 100 ewes bred) and reproductive rates (fetuses per 100 ewes bred). Over 2 years, ewe lambs on seven commercial sheep farms in the North Island of New Zealand were monitored during the breeding period until pregnancy diagnosis. Live weight and body condition score were recorded prior to breeding. Fertility rates increased with live weight up to 47.4 kg but did not increase above this ( P > 0.05). Reproductive rate peaked for ewes in the 47.5–52.4 kg breeding live weight category at 138% (133%–143%). Ewe fertility peaked at a body condition score (BCS) of 3.5 (90% [88%–91%]) while reproductive rates peaked at a BCS of 3.0 (130% [127%–133%]). The apparent plateauing of the relationship indicates there is a point at which no further benefits are gained from increasing live weight or BCS.

Knowledge of the use of farm management tools by New Zealand farmers is important to enable the identification of areas where better uptake of tools can result in improvements in farm profitability. In October 2012, a survey was sent to all New Zealand sheep farmers asking them to indicate which farm management tools they had used in the previous 3 years. A total of 962 usable survey responses were returned which represented 7.8% of sheep farmers. The results showed that a number of the management tools were used by a small percentage of farmers thus indicating that improvements in farm productivity could be achieved by increasing their use. In addition, use of these management tools was associated with a number of demographic factors including farm size, farmer age and highest education level. This new knowledge indicates that the delivery of technology transfer should be tailored to farmers based on at least these socioeconomic factors.