2.1 Bovine Artificial Insemination
Artificial insemination (AI) was arguably the first great
biotechnology innovation dealing with animal reproduction and animal breeding.
The first scientific research on the use of AI in domestic animals
dates back to 1780 by the Italian scientist Lazanno Spalbanzani (Salisbury et
al., 1978; Parish, 2016). The development of AI raised knowledge level of the animal
reproduction industry over the subsequent centuries (Foote, 2002; Verma et al., 2012).
In the 1940s, there was a
significant increase in the market of genetically sound animals in US, which
led to a phenomenal growth of the AI technology. One of the procedures
developed in US is bovine AI, and has been adopted worldwide (Salisbury et al., 1978; Foote, 2002; Dalton, 2011). AI in cattle (or Bovine AI) is a process by which sperm is placed
into a female cattle’s uterus or cervix at proper time using artificial means and with the intention of
impregnating the female cattle with good genetics from the bull (Foote, 1992; Morrell, 2011). The application of bovine AI has brought enormous economic
benefits because it contributes to the reduction of sexual transmissible diseases,
improvement in milk production and reduction of lethal genes (Noguera et al., 2013).
The benefits of AI can be
understood with a One Health perspective – “One Health is the integrative
effort of multiple disciplines working locally, nationally, and globally to
attain optimal health for people, animals, and the environment”(Musoke,et al., 2016). AI helps reducing the cost of maintenance of breeding bulls,
preventing the spread of infectious diseases like contagious abortion,
vibriosis that can be transmitted from cattle to fish and to human, and minimizing
sterility due to genital diseases; it is also environmental friendly because it
reduces the amount of grasses and forage to feed the bulls (CAB, 1999; Rensis
et al., 2003; Hansen, 2013).
Moreover, AI can also enable
the early detection of inferior or sterile males, thus, allow better breeding
efficiency through regular quality checking after collection (Stevenson, 1997 ; Rodriguez, 2012) .
2.2. Success of Artificial
In the early nineties
approximately 60% of dairy cows in the U.S. were artificially inseminated, with
a 84% success rate, and similarly, 90% were artificially inseminated in
European countries such as Denmark, Holland and England, with a success rate of
92% (Magyar, 1991 ).
A study conducted over a period of two years in
Bangladesh showed that AI was an important technique for economic growth of
famers in both dairy and beef production industries (Shamsuddin et al.,
1998; Uddin et al., 2014). However, only 40% of cows were artificially
inseminated in Bangladesh and the success rate was only 53% (Shamsuddin et al.,1998; Gofur & Bhuyan,
2015). Studies suggested that constraints limiting the
success of AI in Bangladesh were prolonged postpartum interval between calving,
nutritional condition of the cow at calving and thereafter, weaning age of
calves, frequency of suckling, cattle rearing system, accuracy of heat
detection, interval between estrus, the estrus signs detection and semen
quality (Shamsuddin et al.,1998; Uddin et al., 2010).
AI was first introduced to Ethiopia in 1938 as a tool
for genetic improvement; the application of AI to cattle was interrupted due to
Second World War (Yemane et al.,
1993; Zewdie et al.,2006; Jemal, 2012).
Despite the challenges in AI application, a 10-year retrospective
study in Ethiopia showed the average AI success rate was about 56% (Ashebir, 2016), and the government of Ethiopia demonstrated improvement
in dairy production and livestock management (Moard, 2007; Jemal , 2015). The two main constraints faced by farmers in Ethiopia
are the lack of laboratories to handle semen and failure to watch heat period
on cows (Samre, et al., 2015).
2.3 Artificial Insemination in Rwanda
In Rwanda, AI started in the 1990s
(NISR, 2013). The service was interrupted during the 1994 Genocide against the Tutsi and the
provision resumed in 2001 when the country renovated its agriculture framework
(MINAGRI, 2004; Chatikobo, 2009). At that time, 65% of bovines in
Rwanda were of local race, and their milk production and nutritive value were
2006, the president of Rwanda initiated the Girinka program to give one dairy
cow to a poor family. The main objective of Girinka is to fight against
malnutrition and it is an income generating
opportunity (Mudingu, 2017). Any Rwandan family which is among the first category of Ubudehe as
per Rwanda’s economic classification and possesses a piece of land that can be
used to cultivate grass is eligible to the program (Kayisanabo, 2014). So far, the Girinka has reached over 259,087 families while the
target is 350,000 families by 2017 (Mudingu, 2017).
Through the bovine AI program,
semen was imported from Holstein and Jersey varieties, with the goal of genetic
improvement (MINAGRI, 2015 ; Argent et al., 2014). As farmers realized the improved
breeds could bring in more revenue, the demand for AI increased (RAB, 2012). In 2007, a semen collection
center (Masaka Bull Station) was set up in Rwanda to collect, store and
distribute semen (MINAGRI, 2013). The AI industry in Rwanda is not
market competitive, as the government is providing mandatory training on the
use of AI Kits to AI providers with no cost. Once these providers complete
training, Rwanda Agriculture Board (RAB) integrates them
into district or sector offices, making them government employees (RAB, 2012).
The prices farmers pay for AI
services depend on the quality of the semen and the AI provider (Ilse et al., 2006;
al.,2013). Semen can be divided
into three general categories: ordinary, super and extra-super. Ordinary is the
cheapest semen from local breeds. The semen is unproven and is not distributed
in Rwanda. Super is genetically tested and proven semen; it is higher in
quality and is being used in Rwanda. Extra-super is the sexed semen which gives
95% accuracy that the calf will be a female; the semen are imported from other countries
to be distributed in Rwanda (Parker et al., 1999;Hirwa et al., 2017).
2.4 Factors affecting the success of Artificial Insemination in Rwanda
The profitability of AI is
dependent on the success rate of AI. There are many factors affecting the
success of AI. The RAB and the Rwanda college of
Agriculture in 2015 have identified the main factors associated with the low
success rate of artificial insemination and were categorized into farmers
associated factors and inseminator associated factors (RAB, 2015, Nishimwe et al.,
I. Farmers associated
The farmers’ ability to detect heat is crucial to the success
of AI. Heat detection is the most limiting factor in an AI program (NISHIMWE et al., 2015). Heat is the period when cows can conceive and thus is the
best time for successful AI (Amann et al., 2000; Nebel, 2014). Farmers who fail to detect the heat will
significantly reduce the success rate of AI. A study in Rwanda showed heat
detection is the primary factor affecting the success rate of AI; accurate
detection of heat can increase AI success rate by 38% (Chatikobo et al., 2009). A similar study conducted in Tunisia showed by improving
farmer’s knowledge on heat detection, the success rate of AI increased by 15%;
and in turn contributed to significant increase in revenue due to calves and
milk production (Salem & Khemiri, 2008; Nebel, 2014).
Due to such importance, farmers
are advised to observe cows for heat signs at least three times a day (in the
morning, afternoon and late evening) for a total of 20 minutes a day (Amann et
al., 2000; Nilsson, 2010).
In order to help manage heat/reproduction and reduce the economic loss
due to missed heat, farmers are advised to learn to observe and record the pre-heat,
standing heat and post-heat signs (Hansen, 2013; Hansen & Aréchiga, 1999; Noguera et al., 2013).
Pre-heat signs are when the cow
presented restlessness, separation from herd, ear movements, attempts to mount
others, clear mucus, reduced milk production, bellowing. Standing heat signs
included the cow stand still when mounted, clear and copious mucus, vulva
enlarged, rests head on back of other cows, tail head roughened. The post-heat signs
happen usually 2-3 days after the start of heat and include cows move away when
mounted, tired and lying while others graze, clear or bloody mucus on tail or
legs (Hansen, 2013; Hansen & Aréchiga, 1999; Noguera et al., 2013). Farmers who can successfully
detect these heat signs can enhance the timing, and success, of AI.
II. Inseminator associated factors
Other than farmers’
ability to detect heat, there are factors related to inseminators that affect
the success of AI.
a. Semen source, Semen Handling and Insemination techniques
Proper handling of high-quality semen is another factor to promote successful
AI (Gebre et al., 2007). The quality of semen can be compromised during collection,
handling, freezing, storing, thawing or insemination (Lamb, 2007;Murage & Ilatsia, 2011). Certified Semen Services (CSS) labs have strict quality-control
standards for semen processing and monitoring, therefore are usually more
reliable source of semen (Salamon and Maxwell, 1995b; Joost et.al, 2010). Studies have shown semen quality could be four times better when
shipped from CSS companies compared to from other sources (Amann et al., 2000;
Parker et al., 1999; Van & Webb, 2013).
b. Skills of the Inseminator
and technique of inseminators play a role in the success of AI. Professional technicians
are more successful at insemination than inexperienced owners or managers
(Dejarnette, 2016; RAB, 2012). Although the insemination process is simple to
understand, it does require considerable manipulative skills, and less
experienced inseminators generally have lower conception rates (FAO, 2005).
During insemination, a portion of semen is retrieved from a tank, and the
remaining semen in the tank can easily be damaged if not handled properly.
Similarly, thawing the semen, loading the AI gun, and manipulating the gun
through the cervix to deposit semen in the uterine body could all be potential
steps for inexperienced inseminators to cause damage to the semen (Cohlen &
c. Availability of Inseminator
Heat detection is
important in AI as putting semen in a cow that is in heat with proper timing is
critical (Boujenane & Boussaq, 2014). Frozen-thawed sperm can survive approximately 20 to 24 hours in
the female reproductive tract, thus it is important to make sure AI was
conducted at the right time to ensure the fertile life of sperm and egg overlap
(Ilatsia, 2011). As the heat only lasts
for 48 hours, the availability of inseminator is critical to ensure proper timing
of AI (Foote, 2001;Vickers, 2014)
figure shows the ideal timing of insemination during the heat (Foote, 2001).
Even if the farmer can correctly identify heat, if inseminator is not available
during the best time to inseminate, the success rate may be reduced (Ombelet & Robays, 2015).
Figure 1: Schematic timeline of best time to
inseminate (Huyin, 2008)
In summary, bovine AI plays an important role in improving
cattle breeds genetically, reducing sexually transmissible diseases, and enhancing
cost effectiveness – the cost of raising a bull can be reduced by up to 60% if using
AI (Eklundh, 2013).
In Rwanda’s Huye district, the average success
rate of AI is 44%, lower than the FAO recommended 75% (Chandel & Pushpa, 2014). Very few studies were conducted in Rwanda to investigate the
farmer’s knowledge of heat detection. Accordingly this project proposes to
study if providing training to cattle farmers in Rwanda on heat detection can increase
the AI success rate.