scholarly journals Consumption of Low Larkspur (Delphinium nuttallianum) by Grazing Sheep

2010 ◽  
Vol 63 (2) ◽  
pp. 263-266 ◽  
Author(s):  
J.A. Pfister ◽  
D.R. Gardner ◽  
K.E. Panter
1979 ◽  
Vol 20 (4) ◽  
pp. 601-603
Author(s):  
Torleiv Løken ◽  
Martha J. Ulvund ◽  
Torgeir Våg
Keyword(s):  

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 303
Author(s):  
Eloise S. Fogarty ◽  
David L. Swain ◽  
Greg M. Cronin ◽  
Luis E. Moraes ◽  
Derek W. Bailey ◽  
...  

In the current study, a simulated online parturition detection model is developed and reported. Using a machine learning (ML)-based approach, the model incorporates data from Global Navigation Satellite System (GNSS) tracking collars, accelerometer ear tags and local weather data, with the aim of detecting parturition events in pasture-based sheep. The specific objectives were two-fold: (i) determine which sensor systems and features provide the most useful information for lambing detection; (ii) evaluate how these data might be integrated using ML classification to alert to a parturition event as it occurs. Two independent field trials were conducted during the 2017 and 2018 lambing seasons in New Zealand, with the data from each used for ML training and independent validation, respectively. Based on objective (i), four features were identified as exerting the greatest importance for lambing detection: mean distance to peers (MDP), MDP compared to the flock mean (MDP.Mean), closest peer (CP) and posture change (PC). Using these four features, the final ML was able to detect 27% and 55% of lambing events within ±3 h of birth with no prior false positives. If the model sensitivity was manipulated such that earlier false positives were permissible, this detection increased to 91% and 82% depending on the requirement for a single alert, or two consecutive alerts occurring. To identify the potential causes of model failure, the data of three animals were investigated further. Lambing detection appeared to rely on increased social isolation behaviour in addition to increased PC behaviour. The results of the study support the use of integrated sensor data for ML-based detection of parturition events in grazing sheep. This is the first known application of ML classification for the detection of lambing in pasture-based sheep. Application of this knowledge could have significant impacts on the ability to remotely monitor animals in commercial situations, with a logical extension of the information for remote monitoring of animal welfare.


2014 ◽  
Vol 190 ◽  
pp. 112-119 ◽  
Author(s):  
Jean Victor Savian ◽  
Armindo Barth Neto ◽  
Diego Bitencourt de David ◽  
Carolina Bremm ◽  
Radael Marinho Três Schons ◽  
...  

1974 ◽  
Vol 60 (6) ◽  
pp. 989 ◽  
Author(s):  
K. C. Kates ◽  
M. L. Colglazier ◽  
F. D. Enzie ◽  
I. L. Lindahl ◽  
G. Samuelson

1998 ◽  
Vol 1998 ◽  
pp. 51-51
Author(s):  
S.M. Rutter ◽  
R.J. Orr ◽  
P.D. Penning ◽  
N.H. Yarrow ◽  
R.A. Champion ◽  
...  

The development of grazing management strategies to optimise nutrient intake from grazed herbage requires an understanding of the factors influencing the dietary preference of grazing domestic ruminants. Although there has been considerable progress in understanding the factors influencing the dietary preference of grazing sheep, there has been comparatively little research with lactating dairy cows (Rutter et al., 1997). The aim of the experiment reported here was to study the dietary preference of lactating dairy cows grazing grass and clover.


1984 ◽  
Vol 15 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Daniel Wallach ◽  
Jean Michel Elsen ◽  
Jean Louis Charpenteau

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