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The effects of temporal and environmental factors on the urination behaviour of dairy cows using tracking and sensor technologies

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Abstract

New Zealand dairy farmers are facing increasing pressure to reduce nutrient losses from grazing ruminants to the environment. Research suggests that the major source of nutrient loss is animal excreta which, for nitrogen (N), relates to cattle urine in particular. Most models used to describe N cycling and predict loss assume homogeneous distribution of urine patches across grazing areas. This study aims to provide baseline knowledge of the temporal and spatial distribution of N by monitoring the urination behaviour of individual dairy cows on a commercial farm using remote precision tools. The study took place on No 4 Dairy Farm, Massey University, Palmerston North, New Zealand during early autumn in March 2009. Thirty cows in late lactation, balanced for milking order and age, from a herd of 180 milking cows, were fitted with global positioning system collars and urine sensors for seven consecutive days. The herd was milked twice a day and rotationally grazed, without supplementation. Cows were rotated through 12 paddocks, each ~1.1 ha. The majority of urine (85 % of total) was deposited on pasture, while 10 % of total urine deposits were captured in the holding yard and milking shed. Kernel density estimates indicated that urine patch distribution was not homogeneous, thus there was aggregation of urine patches within particular areas of the paddocks. Moderate correlations between the time spent in a location and urine patch density provided evidence that the time spent in a particular location was a factor affecting the density of urine patches. Substantial variation in results between paddocks suggested that paddock characteristics did not play a major role in determining urine distribution patterns in this study.

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Draganova, I., Yule, I., Stevenson, M. et al. The effects of temporal and environmental factors on the urination behaviour of dairy cows using tracking and sensor technologies. Precision Agric 17, 407–420 (2016). https://doi.org/10.1007/s11119-015-9427-4

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  • DOI: https://doi.org/10.1007/s11119-015-9427-4

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