novel approaches to expression and detection of oestrus in dairy cows

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Daily mounting activity determined by the optimised script is reported in Tables 5.5 and 5.6. These results showed that the automated script analysis declared mounting on all days of the trial where mounting only occurred on one day in POC 2 and over 2 days in POC 3. 97 out of 173 declared mounts were visually observed mounts during POC 2 on one day when cows were in oestrus and 62 out of 117 declared mounts were visually observed mounts during POC 3 spanning 2 days when cows exhibited oestrous behaviour. These results again suggested 50% error in the accuracy of the script. In Tables 5.5 and 5.6, however, an important pattern to note is that the level of error was increased on the days when cows were in oestrus compared to days of no oestrus activity. Furthermore the number of erroneously declared mounts by the script was substantially increased for cows in oestrus compared to those not in oestrus. Results of the automated analysis of UWB data are reported in Table 5.7 to detect cows that are in oestrus rather than individual events of mounting and standing to be mounted. Oestrous data was reported by cow number and in order of date and real-time of onset of mounting. Onset of standing to be mounted was also reported. The results show that 9 out of 10 cows were correctly identified in oestrus by the script; confirmed by visual observation, milk progesterone concentration of 10ng/ml (Figure 5.7 and 5.8), and no activity increase from baseline (Figure 5.10 and 5.11). Two cows that were synchronized to come into oestrus but did not show any overt signs of oestrus were also identified not in oestrus by UWB automated analysis. These cows had no increase in activity but progesterone concentration was low, which may indicate a silent oestrus. 118
Table 5.3 Efficiency and accuracy of the optimised script at identifying mounts from POC 2 on day of oestrus. Cow Number 539 320 323 611 48 516 292 620 Total Total number of 41 70 11 25 0 0 0 0 147 mounts a Total mounts 29 89 18 36 0 0 0 1 173 script b identified by the Identified mounts c 20 50 7 20 0 0 0 0 97 Not identified 3 6 0 2 0 0 0 0 11 mounts d Out of boundary e 6 11 0 2 0 0 0 0 19 UWB error f 12 3 4 1 0 0 0 0 20 Matching Rate*, % Script Accuracy*, % 69.0 74.6 100.0 83.3 - - - - 76.4 69.0 56.2 38.9 55.6 - - - - 56.1 Table 5.4 Efficiency and accuracy of the optimised script at identifying mounts from POC 3 on days of oestrus Cow Number 1 123 313 424 623 127 38 106 Total Total number of 24 51 6 7 27 0 2 0 117 mounts a Total mounts 24 37 14 14 26 0 5 1 121 script b declared by the Identified 15 27 4 1 13 0 2 0 62 mounts c Not identified 0 5 1 1 3 0 0 0 10 mounts d Out of boundary e 6 4 0 4 6 0 0 0 20 UWB error f 3 15 1 1 5 0 0 0 25 Matching Rate, 71.4 75.0 80.0 53.9 50.0 - 100.0 - 67.4 %* Script 62.5 73.0 28.6 14.3 59.1 - 40.0 - 51.2 Accuracy, %* a By visual observation, the actual number of mounts that occurred b Total number of mounts declared by the algorithm and script from the relative positioning of the cows, noting the increased number of false positives causing erroneous declaration of mounting c Mounts identified by the script that match with mounts identified by visual observations d Mounts observed but not identified by the script e Coordinates for the positions were outside of the boundaries set by the script, but these mounts were determinable from the raw data f Error resulting from the UWB system, resulting in mounts unable to be identified; either through missing data, units turned off or from poor signal quality *Measure of the efficiency and accuracy a) script matching rate is correctly identified mounts/ total number of visual observations minus UWB error (=c/(af)*100) b) script accuracy is calculated as a percentage of the total number of correctly identified mounts/ total number of mounts according to the script (including false positives) (=c/b*100) 119
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NOVEL APPROACHES TO EXPRESSION AND
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TABLE OF CONTENTS TABLE OF CONTENTS
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2.2.3 Statistical Analyses ........
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5.3 RESULTS .......................
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Furthermore, automated software was
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LIST OF FIGURES Figure 1.1 Hormonal
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LIST OF TABLES Table 1.1 Trends in
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LIST OF ABBREVIATIONS ˚ ˚C μM 2D
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CHAPTER 1 - Introduction & Literatu
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the past 50 years and duration of o
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Oestrus growing follicle (Staigmill
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ecomes the main inhibitor of FSH an
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calf at 40-50 days post partum; inv
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al., 2006). However, aged sperm hav
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can occur within 2-3 days, but if t
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educes the incidence of problem cow
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oestradiol, the LH surge and ovulat
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The secondary signs of oestrus can
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There are also changes in normal be
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engage in more natural behaviours i
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1983). Exact explanations and mecha
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2006) and disruption of LH secretio
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1.4.3.2 Milk Yield and Nutrition Di
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influence the ability of the ovary
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cyclicity can be delayed if dietary
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indication for the optimal time to
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calving), 3) pre-breeding heat date
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1.5.2 Physiological Changes Physiol
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1.5.2.3 Body and Milk Temperature T
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physical activity and stage of the
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caused by the general environment t
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may be gained. This is because data
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In summary the objective was to for
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diet, with concentrates at milking.
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oestrus was defined as 3 consecutiv
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The interaction between parity and
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individual oestrus was not signific
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Table 2.4 The effects of the intera
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(361 vs. 578 points, respectively,
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oestrous expression with increasing
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the blood (Sangsritavong et al., 20
Page 83 and 84: CHAPTER 3 - Single Nucleotide Polym
Page 85 and 86: population owing to previous select
Page 87 and 88: Table 3.1 Cont. Follicle Stimulatin
Page 89 and 90: 3.2.4 Sequencing of DNA in the Labo
Page 91 and 92: was achieved. PCR products were rem
Page 93 and 94: 3.4 DISCUSSION The objectives of th
Page 95 and 96: fertility and oestrous expression.
Page 97 and 98: CHAPTER 4 - Development of a Novel
Page 99 and 100: In summary UWB seems a good option
Page 101 and 102: Initial tests were carried out to i
Page 103 and 104: Therefore this demonstrates that X
Page 105 and 106: which is most important for achievi
Page 107 and 108: Figure 4.9 Horizontal - Vertical Di
Page 109 and 110: that UWB is matching the ‘truth
Page 111 and 112: mounting cow. For example height ch
Page 113 and 114: Backpack 1 st put on in AI stalls E
Page 115 and 116: Cows’ behaviour was assessed at 5
Page 117 and 118: or that the cows were in an area of
Page 119 and 120: plane, but mostly in achieving high
Page 121 and 122: Develop techniques for analysis of
Page 123 and 124: in elastic silicone moulded over a
Page 125 and 126: and time of mount, duration of moun
Page 127 and 128: observed matched with increases in
Page 129 and 130: 5.3 RESULTS Results demonstrate pos
Page 131 and 132: Figure 5.2 Graph showing mounting b
Page 133: Table 5.1 Results from POC 2 showin
Page 137 and 138: oestrus and oestrus it is clear to
Page 139 and 140: P4 Concentration, ng/ml P4 Concentr
Page 147 and 148: Activity Activity Activity Activity
Page 153 and 154: 5.4 DISCUSSION The aim of this work
Page 155 and 156: averaged 70% which was lower than t
Page 157 and 158: when the cows lie down, especially
Page 159 and 160: the level of oestrous activity was
Page 161 and 162: technology larger herds must be mon
Page 163 and 164: monitoring could also monitor non-l
Page 165 and 166: antennae which could affect accurac
Page 167 and 168: predispose cows to illness e.g. met
Page 169 and 170: CHAPTER 6 - Overall Discussion & Co
Page 171 and 172: oestrus, h 2 =0.27 (Lovendahl et al
Page 173 and 174: The final section of this thesis de
Page 175 and 176: ate. By using UWB in a commercial s
Page 177 and 178: provides an insight the potential o
Page 179 and 180: BLOWEY, R. (2005) Factors associate
Page 181 and 182: ovine gonadotrophin releasing hormo
Page 183 and 184: GINTHER, O. J., KOT, K., KULICK, L.
Page 185 and 186:
associated with embryonic survival
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ody condition at parturition on end
Page 189 and 190:
Signs in a 24-h Tie-Stalled Dairy H
Page 191 and 192:
SHERMAN, E. L., NKRUMAH, J. D., MUR
Page 193 and 194:
Influence of negative energy balanc
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