novel approaches to expression and detection of oestrus in dairy cows
novel approaches to expression and detection of oestrus in dairy cows novel approaches to expression and detection of oestrus in dairy cows
5.2.6.2 Activity Data Analysis Activity data collected over the trial period was analysed by plotting activity against date and time. This resulted in 12 activity readings daily of the mean activity for 2 hourly periods with peaks denoting oestrus. Date and time of activity increase, peaks on the graph, were used to confirm oestrus detected by UWB and to compare methods of detection. 5.2.6.3 Analysis of CCTV and Visual Records After POC 1 CCTV video footage recorded during the trial was analysed in order to record the mounting behaviour of each cow in oestrus. The quality of data from POC 1 was poor due to lack of continuity of data collection, but selected oestrus data could be determined from the UWB raw data by comparing the time of oestrus events with the CCTV recording. The visual records of oestrus from POC 2 and POC 3 were compared with UWB data to determine if the specific positions associated with oestrous behaviour were recorded by UWB. The visual records were then compared to UWB data which had been analysed automatically by script algorithms to determine the accuracy of the script at predicting individual episodes of mounting and standing to be mounted. CCTV footage from POC 3 was also used to confirm or deny any mounts declared by automated script analysis that did not correspond to visual records. These were either due to the UWB system or human error. 5.2.6.4 UWB Analysis UWB data were analysed to determine if mounting had been recorded by increases in the Z positioning coordinates. The UWB data were then analysed by an automated script (MatLab R2009b, The MathWorks, Inc., US) to determine episodes of oestrous behaviour by the cows relative position in relation to each other. Finally, automated script software was developed to detect cows in oestrus. 5.2.6.4.1 UWB Data UWB raw data were analysed against the times of mounting events recorded by visual observation to determine whether the elevation in height that occurred during mounting had been recorded by UWB. Mounts were recorded as ‘identified mounts’ if the events that were visually 110
observed matched with increases in height coordinates present in the UWB data, or not identified mounts if the visual observations did not match with increases in height coordinates in the UWB data. The UWB observations were expressed as a percentage of the total number of mounts visually observed and recorded (minus UWB error; where data was missing because coordinates were not recorded by UWB, signal quality was poor therefore accuracy had deteriorated or when the unit had turned off) to determine the percentage accuracy of UWB. 5.2.6.4.2 Script Analysis It was clear from analysis of UWB data that cow positions and elevations in height during oestrus were recorded which prompted development of a script to automatically analyse UWB data and declare mounting and standing events occurring by individual cows. Script 1 was developed to take into account the average dimensions of a Holstein Friesian dairy cow and thus the relative position between 2 cows whilst one stood to be mounted by another. Firstly data were filtered to remove any outlying values above and below the set height limits for a mount (minimum; 1.3m and maximum; 2.6m) and to remove data of poor quality (
- Page 75 and 76: Table 2.4 The effects of the intera
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5.2.6.2 Activity Data Analysis<br />
Activity data collected over the trial period was analysed by plott<strong>in</strong>g activity<br />
aga<strong>in</strong>st date <strong>and</strong> time. This resulted <strong>in</strong> 12 activity read<strong>in</strong>gs daily <strong>of</strong> the<br />
mean activity for 2 hourly periods with peaks denot<strong>in</strong>g <strong>oestrus</strong>. Date <strong>and</strong><br />
time <strong>of</strong> activity <strong>in</strong>crease, peaks on the graph, were used <strong>to</strong> confirm <strong>oestrus</strong><br />
detected by UWB <strong>and</strong> <strong>to</strong> compare methods <strong>of</strong> <strong>detection</strong>.<br />
5.2.6.3 Analysis <strong>of</strong> CCTV <strong>and</strong> Visual Records<br />
After POC 1 CCTV video footage recorded dur<strong>in</strong>g the trial was analysed <strong>in</strong><br />
order <strong>to</strong> record the mount<strong>in</strong>g behaviour <strong>of</strong> each cow <strong>in</strong> <strong>oestrus</strong>. The quality<br />
<strong>of</strong> data from POC 1 was poor due <strong>to</strong> lack <strong>of</strong> cont<strong>in</strong>uity <strong>of</strong> data collection,<br />
but selected <strong>oestrus</strong> data could be determ<strong>in</strong>ed from the UWB raw data by<br />
compar<strong>in</strong>g the time <strong>of</strong> <strong>oestrus</strong> events with the CCTV record<strong>in</strong>g.<br />
The visual records <strong>of</strong> <strong>oestrus</strong> from POC 2 <strong>and</strong> POC 3 were compared with<br />
UWB data <strong>to</strong> determ<strong>in</strong>e if the specific positions associated with oestrous<br />
behaviour were recorded by UWB. The visual records were then compared<br />
<strong>to</strong> UWB data which had been analysed au<strong>to</strong>matically by script algorithms <strong>to</strong><br />
determ<strong>in</strong>e the accuracy <strong>of</strong> the script at predict<strong>in</strong>g <strong>in</strong>dividual episodes <strong>of</strong><br />
mount<strong>in</strong>g <strong>and</strong> st<strong>and</strong><strong>in</strong>g <strong>to</strong> be mounted.<br />
CCTV footage from POC 3 was also used <strong>to</strong> confirm or deny any mounts<br />
declared by au<strong>to</strong>mated script analysis that did not correspond <strong>to</strong> visual<br />
records. These were either due <strong>to</strong> the UWB system or human error.<br />
5.2.6.4 UWB Analysis<br />
UWB data were analysed <strong>to</strong> determ<strong>in</strong>e if mount<strong>in</strong>g had been recorded by<br />
<strong>in</strong>creases <strong>in</strong> the Z position<strong>in</strong>g coord<strong>in</strong>ates. The UWB data were then<br />
analysed by an au<strong>to</strong>mated script (MatLab R2009b, The MathWorks, Inc.,<br />
US) <strong>to</strong> determ<strong>in</strong>e episodes <strong>of</strong> oestrous behaviour by the <strong>cows</strong> relative<br />
position <strong>in</strong> relation <strong>to</strong> each other. F<strong>in</strong>ally, au<strong>to</strong>mated script s<strong>of</strong>tware was<br />
developed <strong>to</strong> detect <strong>cows</strong> <strong>in</strong> <strong>oestrus</strong>.<br />
5.2.6.4.1 UWB Data<br />
UWB raw data were analysed aga<strong>in</strong>st the times <strong>of</strong> mount<strong>in</strong>g events<br />
recorded by visual observation <strong>to</strong> determ<strong>in</strong>e whether the elevation <strong>in</strong><br />
height that occurred dur<strong>in</strong>g mount<strong>in</strong>g had been recorded by UWB. Mounts<br />
were recorded as ‘identified mounts’ if the events that were visually<br />
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