novel approaches to expression and detection of oestrus in dairy cows

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achieving 100% (At-Taras and Spahr, 2001). Error rate remains high however, ranging between 17 and 55% (Firk et al., 2002). Cow factors which can affect expression of oestrus by activity monitoring are reported in Chapter 2. Activity monitoring was used to confirm oestrus in Chapter 5 and correctly identified all cows showing oestrus according to visual observation. Milk progesterone measurements (Chapter 5) suggested that some oestruses were missed however, both with activity monitoring and visual observation. Changes in milk progesterone concentration suggested 2 potential incidences of silent oestrus where overt oestrus was not displayed. Progesterone monitoring gives an accurate assessment of the cows physiological status and eligibility for oestrus, but is weak at predicting the precise time of oestrus and timing of insemination relative to ovulation (Lovendahl and Friggens, 2008). Current methods of detection are not proven to significantly increase detection rates and so do not improve dairy cow fertility, when compared with the traditional technique of visual observation. In order to improve upon current methods of detection this thesis investigated possible ways to improve oestrous expression by genetic selection and alternative methods of oestrous detection to improve detection rates. Fertility traits are of low heritability, h 2
oestrus, h 2 =0.27 (Lovendahl et al., 2008). In addition, the heritability of oestrous behaviour verified by pedometer data has been reported: days to first activity increase, h 2 =0.18, duration of oestrus, h 2 =0.02 and strength of oestrus, h 2 =0.04 (Lovendahl and Chagunda, 2009). Heritability is low, however, compared to production traits and to enhance selection for dairy cow fertility genomic selection would be a suitable alternative to traditional selection methods. Genomic selection provides a rapid, permanent solution to declining oestrous expression which reaps cumulative gains (Hayes et al., 2009). Genomic selection has advantages over current genetic selection methods, especially for traits of low heritability because accuracy of SNP selection is high (Muir, 2007), so there is potential to improve fertility whilst milk yield is maintained (Veerkamp et al., 2000). Molecular markers for fertility have already been reported in the bovine genome (Hastings et al., 2006;Khatib et al., 2008a), yet in this study no true significant associations were found between SNPs and the increase in activity. There is potential to investigate further the association between SNPs and oestrous expression to provide an opportunity, with effective interpretation and integration, for incorporation of genomic breeding values for oestrous expression into breeding programs to allow selection of animals that show strong oestrous expression. Alternative methods of oestrous detection are required to improve detection rates. An accurate and effective method of detection is required to fulfil the criteria described by Senger (1994), where detection rate has the potential to be 100% using an effective system of continuous monitoring of all oestrous symptoms (Van Vliet and Van Eerdenburg, 1996). A commercial technique developed to improve oestrous detection rates is online monitoring of milk progesterone concentration. The HerdNavigator system has additional elements to detect health, fertility and metabolic status (Lovendahl and Friggens, 2008). Monitoring of hormones gives an accurate representation of the cow’s physiological status (Friggens and Chagunda, 2005) and oestrous detection rates using the progesterone model described by Friggens and Chagunda (2005) are comparable with other automated techniques; 99.2% and 93.7% detection rates (Friggens et al., 2008). However precise timing of oestrus is unknown, so monitoring of oestradiol would be advantageous (Lopez et al., 2002). Studies 155
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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
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CHAPTER 3 - Single Nucleotide Polym
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population owing to previous select
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Table 3.1 Cont. Follicle Stimulatin
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3.2.4 Sequencing of DNA in the Labo
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was achieved. PCR products were rem
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3.4 DISCUSSION The objectives of th
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fertility and oestrous expression.
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CHAPTER 4 - Development of a Novel
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In summary UWB seems a good option
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Initial tests were carried out to i
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Therefore this demonstrates that X
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which is most important for achievi
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Figure 4.9 Horizontal - Vertical Di
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that UWB is matching the ‘truth
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mounting cow. For example height ch
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Backpack 1 st put on in AI stalls E
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Cows’ behaviour was assessed at 5
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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 and 134: Table 5.1 Results from POC 2 showin
Page 135 and 136: Table 5.3 Efficiency and accuracy o
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: CHAPTER 6 - Overall Discussion & Co
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
Page 187 and 188: 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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