Factors affecting conception rates when using sex sorted semen in Western

Australian dairy heifers Felicity Jane Marshall Searle BSc

This thesis is presented for the degree of Bachelor of Science Honours, School of

Veterinary and Life Sciences, of Murdoch University, 2019

i

I declare this thesis is my own account of my research and contains as its main

content, work which has not been previously submitted for a degree at any tertiary

education institution

Felicity Jane Marshall Searle

ii

Abstract

The purpose of this study was to evaluate the effect of oestrous detection within a

5-day timed artificial insemination program (TAI) on conception rates in dairy

heifers when using sex sorted semen. This was compared to a control group using

conventional semen.

.A total of 198 healthy dairy heifers were subjected to a 5 Day Co-synch protocol.

Animals were determined to be in oestrus based on the activation of a scratcher

detection patch and were assigned into two treatment groups: conventional semen

(n=77) and sex sorted semen (n=76). Semen type and heifer weight had statistically

significant and positive effects on conception rates (P<0.05, P0.01).

Insemination technician, body condition score, bull, heat and reproductive tract

score did not affect pregnancy per artificial insemination (P/AI). Further research

should be conducted on a larger sample size to explore the potential effects of

these factors.

Table of Contents

Acknowledgments ................................................................................................ 1

Introduction ......................................................................................................... 2

Literature Review ................................................................................................. 3

Welfare ............................................................................. Error! Bookmark not defined.

Male calves .................................................................................................................. 3

Sperm Sex sorting ......................................................................................................... 7

Flow Cytometry ............................................................................................................ 7

Limitations of Flow Cytometry ...................................................................................... 8

Practical application ................................................................................................... 10

Oestrus cycle .............................................................................................................. 12

Puberty ...................................................................................................................... 13

Nutrition .................................................................................................................... 14

Reproductive tract scoring .......................................................................................... 17

Reproduction hormones .................................................... Error! Bookmark not defined.

Economics .................................................................................................................. 19

Methods ..................................................................................................................... 25

Statistical Analysis ..................................................................................................................... 26

Results ....................................................................................................................... 27

Semen Type ............................................................................................................................... 27

Table 1 ........................................................................................................................................ 28

12

Weight ....................................................................................................................................... 28

Table 2 ........................................................................................................................................ 28

Farm Management .................................................................................................................... 29

Table 3 ........................................................................................................................................ 29

Technician .................................................................................................................................. 29

Table 4 ........................................................................................................................................ 30

Body Condition Score ................................................................................................................ 30

Table 5 ........................................................................................................................................ 31

Bull ............................................................................................................................................. 31

Table 6 ............................................................................................ Error! Bookmark not defined.

Heat ........................................................................................................................................... 32

Table 7 ........................................................................................................................................ 33

Table 8 ........................................................................................................................................ 33

Reproductive Tract Score .......................................................................................................... 33

Table 9 ........................................................................................................................................ 34

Discussion .................................................................................................................. 34

Significance ................................................................................................................................ 34

Limitations ................................................................................................................................. 40

Conclusions ................................................................................................................ 41

References ................................................................................................................. 42

Acknowledgments

I would like to acknowledge Dr Shane Ashworth for his initial help starting this

project. I would like to thank Western Dairy for the funding put towards this project

as well as help finding farms, in particular, Jessica Andony and Esther Jones.

I would also like to thank my supervisors, Dr Herb Rovay and Dr Joshua Aleri, for all

of their help and guidance throughout this project, as well as the early morning and

late emails.

I would like to thank Victoria Rawlings, Georgia Welsh, Teanna Cahill and Malavika

Nair for their assistance in data collection.

I would finally like to thank my family for their help and support through this

process as it has not been easy, and I could not have completed it without them.

2

Introduction

Interest in the use of sex sorted semen has always been high, due to the fact that it

can skew the sex ratio of offspring and experimentation has occurred for many

years to try and increase conception rates. In the current climate, the dairy industry

faces two major concerns. First, there are decreased profit margins due to the

mounting pressure on farmgate milk prices. In the last thirty years, the number of

dairy farms in Australia have dropped by almost three quarters (21,994 in 1980 to

5,699 in 2018) (Dairy Australia, 2018), due to issues related to debt and

profitability.

There has also been a rise in animal activism with increasing on farm

protests and media attention. The key issue which seems to be at the forefront is

bobby calves. The public as well as consumers are concerned with the fate of male

calves being born and their place within the supply chain. As males cannot produce

the saleable product of the industry, unless there is a need for seedstock

production, their fate is uncertain, and their welfare is arguably worse than their

female counterparts. In skewing the sex ratio to produce more females, the welfare

of the animals as well as the profitability of the enterprise can be improved.

The use of sex sorted semen can increase the income of a business

through the potentially higher number of heifers produced per season. If more

heifers are available, this can allow for harder selection at breeding to continue

herd improvement, as females could not be the limiting factor. If all females were

kept and bred from, this could allow for an increase in herd numbers while

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maintaining a closed herd. More animals allow for a higher milk production and a

larger amount of saleable product. This follows a trend that has been reported by

Dairy Australia, that the average herd size has increased from 93 cows in 1985 to

273 in recent times (Dairy Australia, 2018). If herd growth is not desirable within an

enterprise, surplus heifers can be sold to increase income. This is dependent on a

viable market, either within Australia or abroad. For example, in 2012/13 Western

Australia exported 12,188 dairy heifers where as in 2017/18, this number

decreased to 1,616 (Dairy Australia, 2018).

Literature Review

Male calves

Male dairy calves, also known as bobby calves, are considered a by-product of the

dairy industry. Males calves cannot be utilised on farm and have little to no value

(Cave et al, 2005). Currently, Australia does not have a well-established production

system for male dairy calves (Renaud et al, 2017), their welfare for the duration of

their short lives is becoming increasingly important.

The production of calves is fundamental to the dairy industry as it results in the

production of the main profit driver for the farm, milk. However, male and female

calves are treated differently due to the difference in economic value of each

animal to the farm. In North America bull calves were given colostrum on average

1.6 hours later than their female counter parts (Shivley et al, 2016) and 9% of farms

4

did not always feed the male calves colostrum (Renaud et al, 2017). The lack of

colostrum is significant due to the amount of prophylactic care given to the male

calves, with only 40% having navel dipping and less than 15% being vaccinated

(Renaud et al, 2017).

There are risks associated with a low immune system and emaciation of young

calves and this is seen in a mortality rate of 2.3% on farm (Shivley et al, 2016) as

well as at the abattoir. In 2005, in Victoria, roughly 600,000 very young bobby

calves were sold for slaughter alone. These calves had a mortality rate of 0.64%

pre-slaughter within one study (Cave et al, 2005). A similar study within New

Zealand showed similar results with 0.7% pre-slaughter mortality. 64% of these

deaths resulted from digestive tract disorders with 25% having no food remnants in

the abomasum at the time of necropsy and 10-15% dying of septicaemia or

peritonitis (Thomas and Jordaan, 2013).

.

Dystocia is a risk as it is 25% more likely with male calves (Mee, 2008). This

is due to a number of factors, including increased birth weight, it has been shown

that even at the same weight, females caused less dystocia (Seidel, 2003). Males

generally have a slightly longer gestation length (Healy et al, 2013) which allows a

longer period of time for the calf to grow. Male calves are 9% heavier than their

female counterparts and the dystocia risk increases by 13% per kilogram increase in

birthweight (Mee, 2008). The higher weight at birth increases risk to the mothers

themselves which presents an issue as the female cows are inherently more

valuable and needed for the continuation of the enterprise.

5

There are very strong economic drivers to reduce the number of male calves

produced in the dairy industry, including the higher value of female calves and the

reduced risk of dystocia. The use of sex sorted semen could potentially reduce

dystocia costs by 20% (Seidel, 2003). Another study by Norman et al showed that

dystocia risks were decreased in heifers by 28% and cows by 64% with sexed semen

use (Norman et al, 2010) through lower birth weights associated with heifer calves

which is on average 2kg less than bull calves (Seidel, 2013).

Welfare

Ethically sourced food is in the mind of consumers and the food producing industry

has to adapt this new concerns. Animal welfare is the second most important

consideration with consumers in Belgium (Barkema et al, 2015), and in the United

Kingdom, consumers are willing to pay a premium price for ethically produced dairy

products (Wolf et al, 2016). Several reasons have been identified as hindering the

acceptance of good welfare standards on the consumers side as well. Harper and

Henson (2001) narrowed this down to five major aspects, including the minimal

information provided to consumers, the lack of options given to them in terms of

products available, the costs associated, the disassociation of the source animal

from the product on the supermarket shelves and lack of belief in personal power.

Overall, consumers do not believe that they alone can make changes to industry

welfare standards and therefore will not put their own money at stake (Harper and

Henson, 2001). It is possible for consumers to choose the more “animal friendly”

option, as is seen by the rise of free-range eggs. In 1999, free-range eggs held 6% of

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the market share, with consumers still buying caged eggs and avoiding the $3

premium (Rolfe, 1999). However, in 2015 free-range eggs held the largest

percentage for retail turnover (49%), meaning an increase of 43% in market share

(Scott et al, 2017). Several reasons that could account for this other than welfare,

the most popular being the belief of better quality. Another theory is that free-

range eggs have been more widely accepted as the base price is minimal, making

the premium not as big of a concern. This alleviates monetary concern as a factor of

purchase.

Potentially the same thing could translate to milk, given that it is a relatively

inexpensive product for consumers and it is widely utilised across Australia. It is

important that with the current rise in availability of alternative milk products that

Australian milk continues to be the ‘preferred choice’. A recent analysis of the EU

market conditions during the recent milk price crisis provides and interesting

insight, while the price of conventional milk fell by 0.11 €/kg between 2014 and

2016, the price of organic milk stayed constant even with the significant price

premium (Markova-Nenova and Wätzold, 2018). This suggests that price is not the

sole important factor, but also the marketing and ethics behind a product also have

influence. A way of promoting milk in a new light would be to highlight better

animal welfare practices and providing consumers with more information about

practices, though this can be a double-edged sword.

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Sperm Sex sorting

There are many advantages in using sex sorted semen to skew the sex ratio of

offspring. It can make a system more efficient in terms of terminal cross-breeding

(Hohenboken, 1999), faster genetic gain (Rath and Johnson, 2008) as well as making

the number of animals born not the limiting factor to an enterprise (Healy et al,

2013). The benefits would be highest to early adopters as they can make the most

profit out of surplus heifers (Seidel, 2003) but this depends on the need. It is

thought that this will follow the trend of milk costs (Norman et al, 2010) due to the

law of supply and demand.

The male to female ratio is not 1:1 as was once thought as it can be changed

by many factors. One study showed that the normal sex ratio for artificial

insemination was 51% male and that older cows produce 53% male offspring

(Garner and Seidel, 2008). Due to this, accurate and effective reproductive

technology is highly beneficial. The first offspring from a sexed semen mating was

produced in 1988 (Rath et al, 2013).

Flow Cytometry

Flow cytometry allowed for the proper orientation of the flattened sperm head,

allowing proper analysis of the DNA content. This development is credited to Dr

Daniel Pinkel (Garner and Seidel, 2008) and is a repeatable and reliable method

(DeJarnette et al, 2008).

The amount of DNA content in bovine sperm with an x chromosome is 3.8%

more than that of bovine sperm with a y chromosome (Garner, 2006). In order for

this to be read accurately, the process has been refined to its current protocol.

8

After normal semen collection, sperm are stained for half an hour using Hoechst

33342 which is a membrane permeable bisbenzimidazole fluorescent dye. This was

introduced by Johnson et al as it allowed for the staining of sperm without

removing the sperm membrane (Garner and Seidel, 2008), greatly lessening the

damage done to the sperm during handling.

The sperm is then hydrodynamically pumped into the flow cytometer in

single file so that each sperm can be analysed separately. The sperm then pass

through two wavelengths of an argon laser, 351nm and 364nm, and the light

emittance is read by a photomultiplier tube. A computer then analyses the reading

and will assign the sperm a charge, identifying either an X or Y chromosome. A

crystal vibrator is then utilised to break the stream into droplets containing a single

sperm. Droplet formation can sit around 80,000 droplets per second but around

two thirds of droplets contain more than one sperm and cannot be sorted (Seidel,

2013). The results in between 5000-10,000 of the desired sperm being collected per

second. The drops fall past positive and negatively charged plates, being attracted

to the opposite charge, then separate into different streams based on this. A third

stream is created for the sperm that cannot been assigned a charge due to

improper readings, defects or other abnormalities and these are discarded. This

technology was invented by Dr Lawrence Johnson (Garner and Seidel, 2008).

Limitations of Flow Cytometry

There are limitations and damages sustained to sperm through the sorting process,

including shear force damage, the argon laser being mutagenic as well as repeated

9

electrical doping (Rath et al, 2013). The shear force damage has been lessened by

changing the pound-force per square inch from 50 to 40, resulting in a positive

effect on fertility (Rath et al, 2013). There has also been recent research into the

use of sodium fluoride as it can reversibly stop the movement of sperm if used at

low levels. This allows for more energy to be conserved by the sperm until

insemination (Rath et al, 2013), increasing chances of conception.

Time is also a major factor in sorting as the process is lengthy, with one

sorting of 12-20 million sperm taking an hour (Rath et al, 2008) or more recently 18-

36 million sperm per hour (Seidel, 2013). With an average ejaculation containing

4.8 billion sperm, sorting times are extensive (Hafs et al, 1959). Another limitation

associated with this technology is the amount of sperm in each dose, with the most

common dose being around 2 million sperm (DeJarnette et al, 2008) as opposed to

10 million sperm per straw which would be within a low normal range (Seidel,

2013). This is seen as the best balance between conception rates and the extra cost

of the semen per dose (Healy et al, 2013). When the sperm is sorted, only 33.3% of

it can be counted as 90% accurate, meaning there is less sperm actually available to

the consumer and a large amount of wastage (Garner, 2006). This was further built

upon by Seidel by the discovery of only 15% of sperm being collected for use

(Seidel, 2013), due to around 10% of sperm being discarded due to being dead or

dying.

The price of sexed semen is significantly higher than that of conventional to

account for the loss. Being able to produce faster genetic gain has several

conditions on it. Theoretically, breeding younger animals will increase the rate of

genetic gain but there is also a need for bulls of high genetic merit. This is not

10

generally the case, due to the amount of semen wasted in sorting, it would be too

expensive to go through the process with the top bulls. This affects the rate at

which genetic gain is then attained (Ettema et al, 2017) so the 15% annual genetic

gain that was suggested by multiple sources is generous at best.

Location of flow cytometer is also a significant factor in viability of the

product. Sorting facilities often need to be close to where the bulls are housed due

to time constraints of sex sorting. Although it is possible to delay sorting after

semen collection, there is a gap of roughly 15 hours before sperm degradation is

too high (Seidel, 2013). There are often too many risks associated with

transportation for this to be done on a regular basis. There is also the option of

sexing semen after freezing but this is most commonly used in only in vitro

fertilization, as semen must be used within hours after sorting (Seidel, 2013).

Practical application

In an average dose of conventional semen, there can be up to 10 times the amount

of sperm than in a dose of sex sorted semen. Consequently, the timing of

insemination must be precise and use on the animals most appropriate for the

extra expenditure. Studies show that sex sorted semen will most commonly result

in conceptions rates from between 70-80% of results seen with conventional semen

(Garner 2006, DeJarnette et al, 2008).

Heifers are the ideal candidate for this reproductive technology as they have the

highest conception potential (DeJarnette et al, 2008). Lactating dairy cows have

other stresses which diminish the energy set aside for reproduction, with a study

11

showing that they need almost double the services (2.6 in heifers vs 4.0 in cows) for

pregnancy to be achieved (Norman et al, 2010) and so are not ideal for this

reproductive technology. Given this, it is a recommendation to breed animals 6

hours later than is usual with conventional semen (Seidel, 2013), with best results if

insemination occurs around 18 hours post standing estrus.

Sex sorted semen can be used for commercial dairy herd expansion by

producing more heifers each season if an enterprise were to try and increase

production. This would also pose fewer risks in terms of farm security by not

bringing in new livestock, for example the increased risk of Johne’s disease being

introduced (Seidel, 2013). It also allows for consolidation on successful breeding

programs already occurring on farm with their own genetics.

Though it has been suggested that the annual genetic gain can be increased

by 9-15% through the use of sexed semen (Hohenboken, 1999), this is under the

condition that the bulls were also of the highest genetic merit. Due to the price of

sexing and the amount of semen wasted in the process, it is unlikely that the top

bulls genetic merit bulls semen to be commercially available in sex sorted. Thus

resultsing in lower genetic gain than originally outlined by Hohenboken (1999).

It is not economical for a system to inseminate all heifers with sex sorted

semen, resulting in several potential breeding strategies for the rest of the herd.

These strategies should be optimized to the overall farm objectives, including to

inseminate animals not receiving sexed semen to an inexpensive dairy bull. This

would select further for genetic traits desirable within the dairy industry such as

milk production. Another option suggested by Hohenboken (1999) would be to

breed the remaining animals to a beef sire. The resulting progeny could then be

12

sold into the meat production chain, having traits more desirable to that industry.

These include heavier muscling and higher levels of intramuscular fat. Although

there has been the recommendation to breed these animals with sex sorted semen

to produce beef bull calves, the difference in value at weaning is only around $100

(Seidel, 2013). It has been outlined by Seidel that for the extra expenditure for

sexed semen to be justified, the offspring of the desired sex must be between

$200-300 more valuable (Seidel, 2013).

In summary, It is recommended that sexed sorted semen be used in a

proportion of breedings to manipulate and balance selection intensity, generation

interval as the loss of production, and higher expenditure for use on a whole herd

would not be economically viable (Hohenboken, 1999).

Oestrous cycle

Cows are spontaneous ovulators, making it difficult to predict the specific time of

ovulation. The process is initiated by an increase in oestradiol and a concurrent

absence of progesterone which will induce a GnRH surge. This then produces a

surge of lutenizing hormone. This is then followed by ovulation approximately 28

hours later. A cow’s oestrous cycle begins with the follicular wave emergence,

which is where there is a growth of small follicles which lasts for about 2-3 days.

After this point, a dominant follicle emerges, this will then suppress all of the other

follicles that had been growing up to this point through the use of hormonal signals.

There are two different types of follicular wave patterns, a two-wave cycle and a

three-wave cycle.

13

The two-wave cycle was a concept first mentioned by Rajakoski and lasts for

19-20 days. As it sounds, a cow’s cycle will include two follicular waves, meaning

two chances for a cow to fall pregnant. The start of both cycles is at ovulation. The

second wave commences at either day 9 or 10 and the corpus luteum will regress at

day 16. This theory was further built upon over the next 30 years by the

introduction of a three-wave cycle (Adams et al, 2008). The second wave

commences at either day 8 or 9, a day earlier than the two-wave cycle. The third

wave commences at day 15 or 16 and the corpus luteum regresses at day 19.

Although it was earlier thought that breed had no influence on wave cycle in Bos

taurus (Adams et al, 2008), it is now believed that the two-wave cycle is more

common within dairy breeds, Friesians and Jerseys for example (Forde et al, 2011).

Within the three-wave cycle, the first wave is 3 days shorter, as this manipulation

allows for more opportunities for conception. By the use of a shorter

synchronization cycle, a three-wave cycle is encouraged, giving the producer more

opportunities to get things right.

Puberty

The time that a cow begins to cycle for the first time not only affects that pregnancy

but also subsequent pregnancies (McDougall and Compton 2006, Schillo et al,

1992). It is most economical if an animal conceives at 14 to 16 months of age,

therefore they calve at 24 months of age, though in studies it has been shown that

up to 35% of animals do not achieve this (Kasimanickam et al, 2016). An animal

reaches the point at which it starts to cycle once it has enough energy to fulfil its

14

maintenance requirements as well as enough extra energy to devote to

reproduction.

An animal reaching sexual maturity is inversely related to their plane of

nutrition, not necessarily dependant on how much they are fed past a critical

weight point, previously noted as 295kg (Schillo et al, 1992, Ellis, 1974).It is seen as

most desirable if animals reach 85% of their mature weight before this occurs as

being nutritionally stressed affects the subsequent matings. It is acknowledged that

the corpus luteum in a nutritionally stressed animal is of a lighter weight than that

of an unstressed animal (Lee, 1993).

Given that there are already stress factors associated with sex sorted

semen, it is imperative that all female factors of a mating are optimum. Not only is

the ova itself important but also the time of mating comes into play, especially in a

dairy enterprise in order to time split-calvings. A synchronization program is the use

of hormonal manipulation to control the reproductive cycle of an animal and can

allow for more closely grouped calvings. Given this, an understanding of the

hormones involved is vital in order to allow the most benefit to the farming system.

Nutrition

Heifer nutrition plays a vital role in lifetime productivity in terms of calving

and milk production. Raising dairy heifers can be responsible for roughly 25% of a

farm’s total production cost if done responsibly and half of that is due to feed

(Atkins, 2016). In order to have heifers calve between 22-24 months of age,

nutritional set up is important. For example, if a heifer were to not calve until 30

15

months of age, it would equate to an extra $266 per heifer due to increased time

on feed. Heifers should be at 55% of Mature Body Weight (MBW) by time of joining

and 85% of MBW at the time of calving in order to have the best conception

(Atkins, 2016). Earlier it was thought that the minimum weight requirement would

be 270kg, as this was the weight at which 80% of heifers would be expected to

calve in 1974 (Ellis, 1974). There was a 7% increase in conception rate for each 10kg

increase in weight between 175-265kg, but no significant difference in conception

above the weight of 295kg (Ellis, 1974).

More recently, it is expected that with breed average of MBW of a Holstein

heifer at 682kg, recommended joining weight is 375kg at a minimum, 55% of MBW

(Atkins, 2016). This is a 105kg difference from prior recommendations. A MBW

calculation takes into account the dam’s post calving weight, multiplied by a factor

dependant on lactation number to equal the fourth lactation (Atkins, 2016). A

general recommendation based on this is a weight gain of 0.8kg/day in order to

reach calving by 24 months of age. The check points and composition of this weight

gain is also important.

From birth to weaning, it is expected that a calf should double its body

weight. The composition of that weight gain should be through muscle deposition

and skeletal growth rather than fat deposition (Atkins, 2016). This can be controlled

by what is fed and what concentration it is fed at. For example if milk with a 20%

protein content is given more frequently or in a higher volume, this results in higher

fat gain as the protein content is not high enough for other development (Atkins,

2016). In order to combat this, there are different feeding strategies such as

intensive feeding in order to allow acceptable growth rates. An intensive feed

16

program offers feed at 16-20% of body weight at a higher protein percentage. This

has been shown to increase the mammary fat pad mass which in turn has an effect

on mammary development, both through the paracrine and endocrine systems

(Atkins, 2016).

Future rumen activity is highly dependent on early acquisition of rumen

papillae. This development is initiated by the feed available from a young age.

Animals need access to solid feed with high levels of highly fermentable

carbohydrates, as the rumen microbes can transform this into volatile fatty acids,

absorbed by rumen papillae (Atkins, 2016). Although forages are needed in order

for muscular development of the stomach, the bulk of this feed source creates

competition for rumen space with the arguable more important concentrated feed

(Atkins, 2016). This then allows farmers to feed a lower cost feed such as pasture

later in life due to the prior papillae development (Atkins, 2016).

Mammary development is faster from 3-9 months of age than any other

organ and this is highly affected by nutrition. During this age, it is vital not to over

feed and over condition heifers. If they are fed excess energy, additional adipose

tissue is laid down within the mammary gland and this results in lower milk

production later in life (Atkins, 2016). For example, there was a difference if 8% in

milk production between heifers with 0.7kg daily gain and 1kg daily gain in favour

of the former (Lammers et al, 1999).

A potential strategy for feed intake during heifer development is call stair-

stepping. This is a method in which heifers are fed restricted strategically during

hormonally sensitive development stages, resulting in a compensatory growth

response (Ford and Park, 2001). This includes alternately feeding an energy

17

restricted diet of 17% crude protein and 2.35 mcal/kg and a diet for realimentation

of 12% crude protein and 3.05mcal/kg. This process begins in a prepubertal period

of energy restriction for three months followed by two months of realimentation.

At the time of puberty and breeding there is energy restriction for four months and

three months of realimentation. At the time of gestation, energy restriction diet

should be fed for four months followed by two months of realimentation. Although

animals are eating less quantities in the restriction period, with the higher crude

protein content comes increased cost, meaning a significant investment must be

made for this program. According to Ford and Park, the stairstepped heifers gained

more body weight than the control heifers (0.95 kg/d vs 0.8 kg/d) while consuming

less feed (8.8 kg/d vs 11.3 kg/d) (Ford and Park, 2001). This also affected

subsequent lactations with the first lactation resulting in 21% increase in milk

production and 15% increase in production in the following lactation. This shows

that in order to receive increased production through the life of a heifer, significant

investments must be made in heifer nutrition.

Reproductive tract scoring

The readiness of a heifer to start cycling is determined by the time they reach the

appropriate maturity which is not always measured by age or body condition

scoring. Reproductive tract scoring is a tool that can be used to assess if an animal

has already begun to cycle and their subsequent readiness for mating. This is done

by transrectal ultrasound or in some cases, transrectal palpation. If these animals

can be identified, it will give the producer a better understanding of which animals

are going to be more likely to fall pregnant, thus making them the most cost-

18

effective animals on which to utilise the sex sorted semen technology (Rosenkrans

and Hardin, 2003).

A reproductive tract score of 5 indicates that the heifer has a corpus luteum

present and that it is cycling whereas a reproductive tract score of 4 indicates that

the animal has a follicle over 10mm in size as well as tone to the animal’s uterus. A

tract score of 3 reflects slight tone to the animal’s uterus and follicle size between

8-10 mm. A reproductive tract score of 2 indicates that the animal has no uterine

tone and that the follicles that are present are less than 8mm in size. An animal

with a tract score of 1 has no palpable ovaries and has not started cycling, known as

pre-pubescent. It has been shown that heifers who are bred on their third oestrus

cycle have a higher conception rate than those bred on their first cycle (Rosenkrans

and Hardin, 2003). This suggests that animals with a reproductive tract score of 4-5

would be the most likely to conceive given their physiological readiness.

Heifers have shown a correlation between tract score and expression of

oestrus, within a study by LeFever and Odde, with almost all (>90%) of animals with

a score of 4 or 5 showing signs of oestrus. It has been shown in beef cattle that

animals that show oestrus behaviour are over 3 times more likely to conceive than

those who did not (Kasimanickam et al, 2016), though there are a number of

animals that show silent heat. Although animals with a score of 5 show the most

advanced stage in the oestrus cycle, this does not correlate to the highest rate of

conception. Once an animal has a corpus luteum, ovulation has already occurred,

and it is generally too late to inseminate that animal. This makes the highest

pregnancies per artificial insemination RTS of 4, seen in a study by Kasimanickam

with scores 4 and 5 showing 61.2% and 54.9% respectively. Although scoring is

19

subjective, it has been shown that it is repeatable between scorers (Rosenkrans and

Hardin, 2003).

Economics

It is not only important to use the appropriate protocol for each individual farm; the

timing of synchronisation also has an economic effect. The reproductive

management tool must also consider the lifestyle of farmers as this is an important

part of the balance in commercial systems. The implementation of a structured

breeding program can allow for different lifestyle choices of the farmer, both

socially through labour reductions and economically. The longer the wait until

conception, the higher the cost of the pregnancy given each day of feeding a heifer

is an additional 12-14kg dry matter (Silva et al, 2015).

Silva et al (2015) hypothesised that using a 5 day TAI at the heifer’s first

insemination would result in similar P/AI to heifers that were inseminated using

oestrus detection. Although there is a higher outlay of costs with a timed artificial

insemination, it allows for more regular cycling and inseminations than waiting for

the young heifers to come into heat naturally. It was hypothesised that if the

control group could produce conception rates higher than 80%, there would be no

economic benefit of a TAI. The study found that none of the farms could produce

higher than 70% conception which equated to an economic benefit of $17.00 in

favour of the TAI compared to the control group (Silva et al, 2015). It was even

shown that the use of sexed semen within the timed artificial insemination protocol

would cost less than the control group overall. The study showed limited

differences in labour costs, but feed costs had a significant effect. With the

20

changing weather patterns and Australia’s current issues with drought, the cost of

feed will increasingly become a significant factor in farm budgeting. Due to this,

using protocols and practices with economic benefit are even more important.

The selection of appropriate animals on which to use more advanced technology is

crucial to economic viability. If a farmer is wanting to improve the genetics within

their herd, instead of trying to bring the bottom 10% of their herd up to par, it

would be more beneficial to put the bulls with the highest genetic merit over the

heifers with the highest genetic merit and cull the bottom 10% of their herd. If the

number of cows is the limiting factor within the system, the female animals with

the least genetic merit could be used as recipients of embryo transfer from the top

producing females. This would result in more animals without diluting the merit

and standard of the herd.

The same theory can be applied to the use of sex sorted semen, given the

higher cost per dose as well as the lower conception rates associated with dose

size, it necessitates the use of animals with higher fertility to negate this. In this

case, that would be heifers (McCullock et al, 2013). If the 5 day Cosynch program is

utilised on heifers, this becomes the most cost effective way to produce more cows

within the dairy industry. This can also be strengthened if sex sorted semen is

utilised, making the practice more welfare friendly in terms of bobby calves as well

as dystocia risks.

Synchronization and Fixed Time Artificial Insemination

21

Synchronization for the purpose of reproduction is done primarily by manipulating

two hormones, gonadotrophin releasing hormone (GnRH) and oestradiol. By this

manipulation, times are restricted in which oestrus detection needs to be done or

negates the need entirely.

Colazo and Mapletoft detailed an oestradiol based protocol in a 2014

review, starting with a progestin releasing device on Day 0 which will synchronize

the follicle wave emergence. This device is removed 7 or 8 days later and a

prostaglandin injection is given at the same time to ensure luteolysis. 24 hours later

a low dose of oestradiol induces and synchronised an LH surge approximately 16-18

hours after treatment and ovulation follows 24-32 hours later. Insemination will be

performed typically 30-34 hours post second estradiol treatment. Alternatively, a

small dose of estradiol cyionate can be administered at progestin device removal

and insemination scheduled 48-56 hours later. This would be ideal if handling time

needs to be minimised (Colazo and Mapletoft, 2014).

GnRH based protocols are used in both beef and dairy cattle across the USA

and Canada. The first treatment with GnRH results in LH release and ovulation,

causing the emergence of the new follicular wave approximately. 6-7 days later a

prostaglandin injection should be given, followed by a second GnRH injection 36-48

hours later. This will result in the ovulation of the new dominant follicle.

Insemination is then recommended 16-20 hours later. This strict timeline is referred

to as a timed artificial insemination (TAI). This describes a program in which an

animal is inseminated whether it is showing oestrus behaviour like standing to be

mounted or showing no oestrus behaviour. This protocol is called Ovsynch, termed

by Wiltbank and Pursley in 1995. A Cosynch protocol is a modified Osynch protocol

22

where the second GnRH is given at the same time as insemination. This protocol is

utilised particularly within the beef industry as it only requires three handlings.

GnRH based protocols in lactating dairy cattle have been comparable to AI

after oestrus detection in lactating dairy cattle in regard to pregnancy rate.

Conception rate is often lower with Ovsynch protocols because approximately a

third of animals are not adequately synchronized (Colazo and Mapletoft, 2014). This

is due partially to the point of the animal’s cycle at which the program is initiated.

Best results are achieved if animals are between day 5 and day 12 of their cycle.

Pregnancy rates can be increased between 9-12% during this period.

Due to the varied response with an Ovsynch protocol, further advances have

been made to improve herd synchronization. A Presynch protocol with

prostaglandin was developed in order to have animals within day 5 and day 12 of

their cycle before the first treatment with GnRH. This consists of 2 doses of

prostaglandin given 14 days apart. 12 days after the second prostaglandin should

be the approximate time that an LH responsive follicle arises and that is when the

first GnRH should be given. Another system that has proved beneficial is a double

Ovsynch protocol. This consists of two rounds of the Ovsynch protocol with a third

injection of GnRH 7 days after the conclusion of the program. This program has

shown higher pregnancy rates within heifers specifically when compared to a

Presynch protocol (Colazo and Mapletoft, 2014).

Alternatively, a Presynch protocol can be done with progesterone instead of

prostaglandin. The hormone progesterone blocks the release of LH, which in turn

supresses oestrus and prevents ovulation. If progesterone in given for longer than

14 days, the lifespan of a corpus luteum, this will result in oestrus when the

23

progesterone is removed. The protocol with a progestin device (PD) runs for usually

7 or 15 days. The benefits of this program is strongly influenced by parity, with a

14% increase in pregnancy rates in heifers but no affect in cows (Colazo and

Mapletoft, 2014). This is due to inducing cyclicity through increasing LH surges as

well as stopping early ovulations.

In an experiment by Colazo and Mapletoft, the conventional 7 day Cosynch

with the use of a PD and insemination 60h later was compared to a 5 day Cosynch

with a PD and insemination 72h later. It is suggested that this provides a longer

period of proestrus and it was expected that due to the shorted period of time

between the first GnRH and the induction of luteolysis that two treatments of

prostaglandin would be needed to cause complete regression of the corpus luteum

(Mellieon et al, 2012). This was later negated when tests with one vs two

treatments with prostaglandin attained similar pregnancy results in heifers (53% vs

59%) (Colazo and Mapletoft, 2014).

It has been shown that P/AI did not differ between a 5 day Cosynch and a 7

day Cosynch in heifers (59% vs 58%) (Colazo and Mapletoft, 2014). This was using a

Cosynch protocol with a PD and a single dose of prostaglandin at the device

removal. This would suggest that management would be a major consideration

when it comes to choosing the appropriate protocol. When comparing these

protocols to the simpler use of a Presynch and oestrus detection for insemination,

it was found that the latter resulted in higher fertility but also resulted in higher

labour costs (MacMillan et al, 2017), as well as a further time commitment within

the breeding season.

24

Timing of insemination has an effect on conception rates across the board.

Although highest conception rates are still found when insemination occurs after

display of oestrus (Colazo and Mapletoft, 2014), fixed time artificial insemination

(FTAI) is becoming more widely accepted with synchronization protocols. Original

experiments by Wiltbank and Pursley tested the conception rates between

insemination at 0 hours post final GnRH treatment, 16 hours post and 32 hours

post. Animals that were inseminated at 16 hours had the greatest number of P/AI,

with reduced fertility in the other two groups. This is likely due to reduced sperm

viability in the 0 hour group, given the time before ovulation, and reduced oocyte

viability in the 32 hour group. The timings have changed as the Ovsynch and

Cosynch protocols have been further developed.

There are two time ranges post synchronization that are commonly utilised,

between 55-56 hours and 68-72 hours. A study by Schenk et al. showed the longer

of the two to be more beneficial (34% vs 49%) in terms of pregnancy rates in

heifers. . This is echoed in results post oestrus behaviour, with a 24-hour window

yielding 55% conception and the shorter 12 hour period resulting in only 25%

conception (Schenk et al, 2009). This means that the sperm energy is not being

wasted for a longer period of time while waiting for ovulation. This is then

contradicted in a later study by Colazo and Mapletoft where heifers inseminated at

56h post protocol had a 10% higher pregnancy rate than those inseminated at 72h

post protocol. This was only testing when giving a second GnRH treatment at the

time of insemination. More data is needed in regard to a fixed time artificial

insemination time frame for a clearer picture of the process.

25

The combination of a TAI with heat detection when using sex sorted semen

could produce more favourable results, if farmers were to use semen selectively at

insemination. This study is to directly compare the difference between expression

of heat and non-expression when using sexed semen.

Methods

200 animals were included in this study, ranging from between 12-19 months of

age. The heifers came from 2 different commercial farms in the south west of

Western Australia in 2018. Neither of these farms provided supplemental feeding

prior or during the program, providing only available pasture.

A 5 day Cosynch protocol with the use of a Controlled Internal Drug Release device

(CIDR, Zoetis, Perth, Australia) was used in this study as the timed artificial

insemination program. This protocol creates a longer proestrus period with

favourable results in other studies (Mellieon et al, 2012). On Day 0 of the protocol,

individual animal information was collected and recorded. This included animal

identifiers, breed, age, weight, body condition score (BCS) and reproduction tract

score. A CIDR was then placed inside the heifer’s vagina using a CIDR inserter. On

Day 5, the CIDR was removed from the heifer, while also being checked for signs of

vaginitis or other abnormalities. The heifer was then injected intramuscularly with

2mls of Estromil (PGF) (Ilium, Perth, Australia), a synthetic prostaglandin which

initiates the regression of the corpus luteum. An adhesive detection aid (Estrotect,

Perth, Western Australia) was placed between the hips and tail head. If the aid had

26

over a 50% colour change at the time of insemination, this was classed as in

oestrus.

Insemination commenced on Day 8, after which the heifer was injected with 1ml of

GONAbreed (GnRH) (Parnell, Perth, Western Australia) which stimulates the

pituitary gland to release LH and FSH which initiates ovulation.

At the time of inseminatio with 3 different inseminators, heifers were classified as

either having displayed oestrus or not (heat or no heat) and assigned to a group

accordingly for a 2 x 2 factorial arrangement of treatments. Of the heifers that

displayed heat, half were inseminated with conventional semen and half with sex

sorted semen . Of the heifers that do not display heat, half were inseminated with

conventional semen and half with sex sorted semen. All sexed semen bulls within

the program have previously been proven as sex sorted breeders within the

industry.

Due to management factors on farm, pregnancy was diagnosed at 70 days post

insemination by trans-rectal ultrasound. Ideally, there would be two ultrasounds at

60 days and 90 days post insemination to account for embryonic loss. Pregnancy

per artificial insemination (P/AI) will be calculated by dividing the number of heifers

diagnosed pregnant after AI by the number of heifers having been inseminated.

Statistical Analysis

Prior to data analysis, data was checked and cleaned to maintain confidentiality of

the participants. Data was analysed using SPSS Statistics software version 22.0,

2013 (SPSS Inc., Chicago 111) in 3 stages. Descriptive statistics (proportions and

27

percentages) were generated for all variables in order to determine the effect of

semen type, weight, body condition score, heat, farm, AI technician and

reproduction tract score on conception rates.

Separate chi-square tests were used as screening tests. Similarly, multivariable

analysis under the linear mixed model framework were used to test these

associations. The final models used logistic regression analysis to determine the

associations between the various variables that were fitted as outcomes variables

and the predictor variables at significance level P≤0.05 and also the measures of

effects (odds ratios) were determined in order to establish a causal-effect

relationship. Results from the separate chi-squares tests were reported for

variables that were insignificant at P≤0.05.

Results

The sample size for this study was only 153 animals, as 45 animals were removed

from the study due to lack of random selection at time of insemination due to

farmer request.

Semen Type

There was a statistically significant effect (P<0.05) of semen type on conception

rates. Conventional semen achieved 63.64% conception whereas sexed semen

achieved only 36.84%. (Table 1.)

28

Table 1 The effect of semen type (conventional versus sexed semen) on conception

rates in Australian dairy heifers within a timed artificial insemination program

Weight

Weight has a significant effect of pregnancy per artificial insemination (P<0.05)

(Table 2). Animals with higher weight achieved a higher P/AI compared to animals

with lower weights. Of the animals that were above 350kg, 73.91% achieved

conception, where animals below 350kg achieved 46.15% conception. The lightest

heifer within the study was 248kg and the heaviest was 405kg, resulting in a 157kg

range. The median weight was 314kg, which sits below the recommended weight

cut off.

Table 2 The effect of weight on conception rates of Australian dairy heifers in a

timed artificial insemination program

Semen Type N Percentage Significance

Conventional 77 63.64 <0.05

Sexed 76 36.84

29

Farm Management

Farm was not a significant predictor of pregnancy outcome within this study

(P=0.14) and the sample size was too small to analyse. 93 heifers were included

from Farm 1 and had achieved 46.23% overall conception, whereas 60 heifers were

included from Farm 2 with a slightly higher conception rate of 56.67% (Table 3).

Table 3 The effect of farm on conception rates of Australian heifers in a timed

artificial insemination program

Farm N Percentage Significance

1 93 46.23 0.14

2 60 56.67

Technician

Inseminator is not a significant predictor of conception within this study (P = 0.36)

(Table 4.) There were three technicians used within this study. Technician 1

inseminated 19 heifers and achieved 57.89% conception. 9 heifers were

inseminated with conventional semen and 10 were inseminated with sexed semen.

13 animals were classified as in heat and 6 animals did not show signs of heat.

Technician 2 inseminated 133 heifers and achieved 49.62% conception. 66 heifers

Weight N Percentage Significance

<350kg 130 46.15 0.01

>350kg 23 73.91

30

were inseminated with conventional semen and 67 animals were inseminated with

sexed semen. 100 animals were classified as in heat at the time of insemination and

33 animals showed no sign on heat. Technician 3 inseminated 1 heifer who was on

heat with conventional semen and did not achieve a pregnancy.

Table 4 The effect of artificial insemination technician on conception rates of

Australian dairy heifers in a timed artificial insemination program

Body Condition Score

Body condition score did not have a significant effect on pregnancy (P = 0.36) Of the

animals below a body condition score of 2.5 (n=64), 48.44% managed to attain

pregnancy. Of the animals that attained a body condition score over 2.5, 51.69%

were positive at the pregnancy check. 16 animals were of a score <2 and achieved

50% pregnancy, 97 animals were between 2.25 and 2.5 and achieved 48.45%

pregnancy, 41 animals were between 2.75 and 3.25 and achieved 53.66%

pregnancy.

Artificial

Insemination

Technician

N Percentage Significance

1 19 57.89 0.36

2 133 49.62

3 1 0.00

31

Table 5 The effect of body condition score on conception rates of Australian dairy

heifers in a timed artificial insemination program

BSC N Percentage Significance

<2.5 64 48.44 0.41

>2.5 89 51.69

Bull

Of the five bulls that were utilised in the study, none significantly outperformed

another and therefore had no statistical significance (P= 0.41). All bulls had a

different number of females assigned and varying percentages of conception. The

highest performing bull was 5, having 38 animals within the group and achieving a

conception rate of 60.53%. This bull was had a mixture of both conventional and

sexed semen being used (n=20, n=18). Bull 2 had one fewer heifer and achieved

54.05% conception with conventional semen. Bulls 1 and 4 both had 50%

conception with 10 and 22 animals respectively. Bull 1 was conventional semen

only but Bull 4 was a mix of both conventional and sexed semen (n=11, n=11). The

bull with the lowest production was Bull 3 but there was almost the highest

number of heifers in that group (n=46) and only sexed semen was used.

32

Table 6 The effect of a bull on conception rates in Australian dairy heifers in a timed

artificial insemination program

Heat

Heat was not a predictor of conception within this study ( P = 0.48) (Table 7). 114

animals expressed signs of heat at time of AI, and 39 animals did not. Of the

animals that expressed heat, there was a conception rate of 50.88% with 58

animals treated with conventional semen and 56 animals treated with sexed

semen. Of the animals that did not express heat, there was a conception rate of

48.72% with 19 animals treated with conventional semen and 20 animals treated

with sexed semen.

Bull N Percentage Significance

1 10 50.00 0.41

2 37 54.05

3 46 39.13

4 22 50.00

5 38 60.53

33

Table 7 The effect of heat on conception rates in Australian dairy heifers in a timed

artificial insemination program

Table 8 The effect of semen type and expression of heat on conception rates in

Australian dairy heifers in a timed artificial insemination program

Heat Expression and Semen Type Pregnant Non Pregnant Pregnancy %

Heat and Sexed 33 23 58.9

Heat and Conventional 43 15 74.1

Non Heat and Sexed 11 9 55

Non Heat and Conventional 16 3 84.2

Reproductive Tract Score

Reproductive tract score was not a predictor of conception for this study (P = 0.56)

(Table 9.). All animals within this study had reached puberty at the time of

breeding, with no scores of 1 being recorded. Six animals recorded a score of 2 and

there was a 50.00% conception rate. 28 animals recorded a score of 3 and this

resulted in 46.43% conception. 54 animals recorded a score of 4 and there was an

Heat N Percentage Significance

Heat 114 50.88 0.48

No Heat 39 48.72

34

overall pregnancy rate of 50.00% within this group. Of the animals that scored 5

(n=66), there was a conception rate of 54.69%, the highest proportion of

pregnancies.

Table 9 The effect of reproductive tract score on conception rates in Australian

dairy heifers in a timed artificial insemination program

The overall P/AI of the project was 50.3% (76/153), with the P/AI of conventional

semen being 60.6% (49/77) and sexed resulting in a P/AI of 36.9% (28/76).

Discussion

Significance

Semen type and weight were the main factors within this study that affected

pregnancy outcomes. It is documented that there is a statistically significant

difference between P/AI between the two semen types (Colazo and Mapletoft,

2017). In a 1999 study by Seidel et al, P/AI varied from 40-68% with sex sorted

semen and 67-82% with conventional semen (Seidel et al, 1999). Colazo and

Reproductive

Tract Score

N Percentage Significance

1-3 34 50.00 0.56

4-5 119 50.42

35

Mapletoft found 39.3% conception with sexed semen (n = 2319) and 59.8%

conception with conventional semen (n = 2292) when used after TAI (Colazo and

Mapletoft, 2017). Other studies have shown that sexed semen achieves 70-80% of

conception achieved with conventional semen (D. L. Garner, 2006, DeJarnette et al,

2008), or even up to 90% in ideal scenarios (Seidel, 2013).

During the sorting process factors including the shear force of

centrifugation, electrical doping and extended period before freezing (Rath and

Johnson, 2008) result in a significant amount of damage to the sperm. Schenk et al

in 2009 decreased the sorting psi from 50 to 30 and examined conception rates.

Conception rates post sorting at 30 psi was 82% (55/67) and 50 psi (12/67) showing

considerable effect (P <0.01) (Schenk et al, 2009).

The lower fertility may have been partly due to the number of sperm within

each dose for insemination, which is greatly reduced in comparison to conventional

semen (Seidel, 2013), sometimes to 1/5 of conventional dose. Within this study,

that was confirmed with a P-value of >0.05. Sexed semen achieved 57.14% of the

conception rates achieved by conventional semen.

There was statistical significance (P-value = 0.01) that pregnancy was affected by

weight at the commencement of the 5 Day Co-synch which disputes the findings of

Ellis who hypothesised that there was no significant conception rate difference

above the weight of 295kg (Ellis, 1974). Instead, it fits in more closely with the

finding of Atkins in which a recommendation of 375kg at a minimum for joining or

at 55% of MBW (Atkins, 2016). Very few animals reached the required weight which

highlights optimum nutrition as a necessity for breeding programs. If appropriate

36

nutrition cannot be obtained from pasture, supplementary feeding is

recommended or if possible, delay the start of breeding until animals have put on

more condition. Without significant investment in heifer nutrition and

development, the extra expenditure on sex sorted semen is unlikely to be beneficial

economically to the enterprise.

Farm did not have a significant effect (P-value: 0.14) on pregnancies and the sample

size was too small to analyse but it is well known that management factors will

affect reproductive performance. It is suggested that both farms seemed to have

similar management strategies given there was no statistical significance.

AI technician was not a significant factor in this study with a P-value of 0.36, though

there were only 3 inseminators and as such the sample size was too small. Although

there is variation between inseminators, all inseminators did not have the same

number of heifers or the same number of animals treated with each semen type.

This makes it difficult to compare them directly. There have been varying reports on

the effect of AI technician throughout many different studies. Technician had a

significant effect (P-value <0.001) on conception rates in a 2013 Australian study

though 9 different inseminators did have varying numbers of inseminations (Healy

et al, 2013). Another study found that inseminator did not have an effect on

pregnancy within a herd, testing 51 herds and 9,172 inseminations (DeJardette et

al, 2011). Technicians were not compared directly as there were varying numbers

of inseminations per technician.

37

The effect of BCS on conception rates was not evident within this study (P-value:

0.41). BCS can be a measure of readiness to cycle but is not the sole indicator or a

predictor of conception. One study found no association between body condition

score and conception at first service (Donovan et al, 2003). Instead, it was

suggested that pelvic size, and in turn skeletal size, had a better association when

bred in summer. A similar correlation was not found when bred in winter. It has

been suggested that extreme BCSs result in lower conception rates, either too

heavily conditioned or too lean (Leaver, 1977). Following on from this, it is thought

that if a heifer is gaining less than 750g per day prior to insemination, an increase in

feed post insemination may improve conception rates (Leaver, 1977).

In this study the AI sire did not have a significant effect on conception in terms of

statistics. The highest performing bull had a mix of sex sorted and conventional

semen within the program while the lowest performing bull only had sex sorted

semen utilised. It would be expected that sex sorted semen would produce a lower

conception rate in general, but the difference was not big enough to have a

statistical effect. It has been seen within other studies that the sire is a predictor of

conception for both semen types (Healy et al, 2013). The variation difference was

stated to be equal to 25.5%, with different fertility of each bull and then the added

pressure of sorting.

Evaluating the effect of sire on conception rates is complicated by the use of

sexed semen, given the lower volume of each dose. DeJarnette et al tested the

effect of a higher sperm dose from the same sire to evaluate the effect in heifers.

38

With one sire, doses of 5 x 106 achieved 13.1% higher conception than doses of 2.1

x 106. Within the same study, it was determined dosage did not have an effect on

conception across sires (DeJarnette et al, 2008).

Expression of heat has been shown in multiple studies to have an effect on

conception rates throughout the years. There are limitations associated with the

form of measurement used within this study. Animals can have false negatives and

false positives with this type of recording, with some showing silent heat. If funds

were not a limiting factor within this study, blood testing would be a more accurate

way of recording the progesterone spike associated with heat. Often, the

recommendation is to wait until the expression of heat until insemination (Melleion

et al, 2012), which result in higher labour costs (Macmillan et al, 2017). Colazo and

Mapletoft found that overall pregnancy rate is higher when inseminating after

oestrus detection as opposed to TAI, with 70% conception and 63% conception

respectively. This was also found by MacMillan et al where heifers inseminated post

oestrus detection had a P/AI of 61.9% versus TAI P/AI of 58.2%. This study had 370

heifers in total and had a total of 527 inseminations (MacMillan et al, 2017). In a

study by Silva et al, heifers were inseminated with sex sorted semen either after

expression of heat or in a TAI trial. Insemination after expression of heat achieved

31.6% pregnancy (18/57), whereas insemination after TAI achieved 54.8% (40/73).

This could be due to not having the recommended delayed insemination when

using sexed semen.

Within this study, the expression of heat is not statistically significant with a

P-value of 0.48. Similarly, in a study by Silva et al, although expression of heat had a

39

numerically different effect of conception rates compared to no expression of heat,

it was not statistically significant (67.8% vs 58.1%) (Silva et al, 2015).

In a study conducted by Colazo and Mapletoft in 2017, heat had an effect on

P/AI on both semen types. Of 41 animals that expressed heat and were treated

with conventional semen, 28 heifers became pregnant (68.3%). When heifers did

not show heat, only 50% became pregnant with conventional semen (7/14). Of 46

heifers that expressed heat and were treated with sexed semen, 32 animals

became pregnant (69.6%). When heifers did not show heat, only 36.4% became

pregnant with sexed semen (4/11), which makes expression of heat important to

conception rates (Colazo and Mapletoft, 2017).

It has been shown that there is a strong correlation between a high (4-5) RTS and

the incidence of oestrus, attaining greater than 90% whereas heifers with RTS of 3

or lower achieved an incidence of oestrus lower than 80% (LeFever and Odde,

1986). It was expected that animals with an RTS of 4 would have the highest

pregnancy rate, shown in a study by Kasimanickam et al, with 232 heifers out of 379

were diagnosed pregnant (61.2%). Heifers with a reproductive tract score of 5

attained 54.9% conception rate (605/1103) and heifers with a score of 2 and 3 both

attained less than 54% pregnancy (53.4% and 53.8%). From Kasimanickam’s study,

RTS did not change the expression of oestrus with a P-value of >0.1.

This is also shown in a 2014 study where heifers with a higher RTS became

pregnant earlier in the season than those with a lower RTS. Within this study,

heifers were either artificially inseminated as well as receiving a natural service or

were only naturally served. RTS affected both whether heifers became pregnant

40

and at which point in the breeding season they became pregnant (Gutierrez et al,

2014).

There is also evidence that RTS was not a predictor for conception. This is

supported by a paper published in the Journal of Dairy Science, in which

reproductive tract score did not affect P/AI and it is suggested that this technique is

utilised to tell an animal’s puberty status rather than likelihood of conception

(Stevenson et al, 2008).

The P/AI overall was lowered than expected (50.3%). It was thought that a P/AI of

55% or higher would be achieved within the study but this was not the case.

Although the pregnancy rate was above 55% with conventional alone (60.6%), it

would be expected to be higher (Colazo & Mapletoft, 2017). In a study by Colazo

and Mapletoft, the overall P/AI which included conventional and sexed semen was

66.51%.

Limitations

The sample size for this study was only 153 animals, as 45 animals were removed

from the study due to lack of random selection. For this study to have acceptable

power, a minimum of 2000 animals would be required. This sample size could not

be achieved given the time in which the project was undertaken.

Ideally, this project would have been carried out with a number of rounds on each

farm instead of a single round of insemination. This would replicate a protocol

more likely to be seen within most Australian dairy herds. A second round was

41

completed on one of the farms within the study but could not be included due to

not repeating the program on the second farm. Having multiple rounds could help

to increase pregnancy rates given fertility is greater in subsequent reproductive

cycles in animals that have not yet begun to cycle (Colazo & Mapletoft, 2014).

A way in which to improve this study would be to monitor the amount of nutrition

being given to the animals not only at the time of conception, but also in the

months prior as a rising plane of nutrition has shown better conception results

(Schillo et al, 1992). Measuring the feed on offer (FOO) on both farms that the

heifers had access to would have been greatly beneficial to this study to determine

how much supplementation would have been necessary.

On farms utilised within this study, there was a lack of previous pregnancy testing.

This does not allow for a comparison between fertility in this study to the normal

fertility seen within the herd. Though comparison between conventional and sexed

semen conceptions allowed for a control, for a proper evaluation of the TAI

program, previous pregnancy results are needed.

Conclusions

There are a reasonable number of limitations when using sex sorted semen. These

include the damage done to sperm resulting in lower fertility. If it is to be used,

certain factors need to be taken into consideration, such as weights. Animals are

more likely to conceive if between 350kg and 375kg at a minimum before

insemination to create a better chance for conception as this is supported by other

research. A larger sample size and further testing would be ideal in testing the

42

correlation between weight at insemination and pregnancy. Expression of heat

should also be a significant consideration at the time of insemination, given there

was a difference of 18% in conception rate when sexed semen was used in heifers

on heat and heifer not on heat, though it was not statistically significant within this

study.

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