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| Figure 1. Effect of insemination time after the onset of heat on overall conception rate |
| Livestock Research for Rural Development 28 (5) 2016 | Guide for preparation of papers | LRRD Newsletter | Citation of this paper |
To assess the reproductive performance of cows/ heifers in smallholder dairy farms, retrospective and longitudinal studies based on artificial insemination were conducted. The recommended basic AI procedures were kept and applied for study animals.
In the longitudinal study 86.4% of the dairy cattle inseminated were found to be pregnant which is by far greater than the retrospective result (<59%). The first service conception rate was 49.3% and the mean (±SE) number of insemination per conception was 1.95±0.41. The conception rate was significantly higher in cow/ heifers, which were inseminated between 10-20 hours after the detection of heat (92.3%) than those inseminated below 10 hours and greater than 20 hours, which were 72.7% and 64.3%, respectively. Similarly, among different body condition scorings (lean vs medium) and between parities (cow’s vs heifers) there was a significant difference (P<0.05) in conception rates, 40% and 94% for the former, and 91.6% and 75% for the later, respectively. There was a tendency for higher conception rate in the cross than local breeds. In addition, repeat breeding, poor husbandry and poor recording systems were observed. Further, poor body condition, parity and breed were also major factors that affected the efficiency of artificial insemination in the study area. However, it can be concluded, maintaining the proper time of insemination, which took the major share of the success in this study, can result in a comparatively higher first service conception rate. Hence, it is possible to improve reproductive performance of dairy cows using AI (obtaining an optimum result at farmer’s level), by simply adhering to the proper time of insemination.
Key words: conception rate, first service, repeat breeder, reproductive efficiency, service per conception
The size and diversity of Ethiopian major agro-ecological zones have made the country suitable to support a large number and classes of livestock. Among the different livestock classes, cattle constitute the largest number. Ethiopia is known to have a cattle population around 41.5 million, 99.4% of them are indigenous breeds with very few hybrids (0.5%) and exotics (0.1%). Cattle production together with the production of other livestock sectors, are known to be very important and essential components of agricultural sector contributing for meat, milk, cheese, butter, exporting commodities (live animals, hides, skins), draught power, manure, near-cash capital stock (Hunderra 2004).
In Ethiopia, in spite of the diverse breeds of cattle available, the production level is low when it is compared with other countries. The low productivity is due to a number of factors among which are quantitative and qualitative deficiency of feed recourses base, disease, poor animal management and insufficient knowledge on the dynamics of the different types of farming system existing in the country (Plazier 1993). As one option to improve the genetic potential of the indigenous breeds of cattle, a cross breeding program has been introduced to Ethiopia at wider scope in late 1960’s (Brannang et al 1980). Artificial insemination (AI) has been introduced to Ethiopia in the early 1930’s, but it was interrupted by World War II. In 1981 National Artificial Insemination Center (NAIC) has been established to coordinate the overall AI activities throughout the country (NAIC 1995). AI has become one of the most important and successful reproductive biotechnology ever devised for the genetic improvement of farm animals. It has been most widely used for breeding dairy cattle and has made bulls of high genetic merit available to all (Webb 1992; Mukasa-Mugerwa 1989).
There are different factors that can affect conception rate per AI service. Among them cow related factors including cow fertility, body condition, environmental stresses, bull fertility/ quality of semen, accuracy of heat detection, the timing of AI, efficiency of AI techniques, skills of the inseminators, care of the semen collected, processed and stored etc (Nichlson and Butherworth 1986 ; Ntombizakhe 2002; Rogers 2001). The risk of all these factors vary as the type of production system, level of the dairy business and even with agro ecology (Hafez 1993; Franclin 2003; Smith 1982). Among these factors accuracy of heat (estrus detection) is one of the major factors that determine AI program since ova remains viable for about 12-18 hours after ovulation (Bekana 1991; Rodriguez-Martinez 2000). Compared with natural mating AI has been used for genetic improvement by utilizing proven sires, decrease risk of venereal disease transmission, maintaining accurate breeding records necessary for good herd management, economic service, culling dangerous males on the farm, avoiding injury during mating, utilizing semen of incapacitated bulls (Hafez 1993; Roberts 1986; Rodring-Martinez 2000). Even though there are some disadvantages, they have been overweighed by the advantages (Roberts 1986).
An achievement in increasing milk and meat production by improving the genetic merit of indigenous cattle has been one of the primary livestock development objectives of Ethiopia (Heinonen 1989). Improvement in livestock resources have been achieved through the implementation of an efficient and reliable AI service, in parallel with proper feeding, health care, and management of livestock (Meles and Heinonen 1991). In Ethiopia, though the establishment of AI program passed nearly half a century, very few studies in limited parts of the country have been conducted to evaluate the success rate of AI. Therefore, the objectives of this study were to evaluate the reproductive performance of cows delivered the AI service and to investigate factors influencing the efficiency of AI in the study area.
This study was conducted in smallholder dairy farms in Fitche area of Selale, North Shoa Zone of Oromia Region. Fitche is the central town of North Shoa Zone as well as Girar Jarso Wereda and it is located 112 km north of Addis Ababa. The area is at an altitude of 2800 m above sea level and 9000’ -100 44’ North latitude and 37057’ – 39 033’ East latitude (Abiot 2004). The total area of the Girar Jarso Wereda is 42400km2.
The climatic conditions of the area include highland, midland, and lowland 52%, 41%, and 7%, respectively (NSDAD 2005). The maximum and minimum temperature is 350C and 11.50C, respectively. It has bimodal rainfall with maximum and minimum of 1115 mm and 615 mm, respectively. A short rainy season occurs from March to May followed by along rainy season lasting from June to September. The long dry season is from October to February (NSDAD 2005). Different types of livestock populations found in the area. Estimated animal populations were cattle 49594, goats 9996, sheep 30236, donkey 9964, horse 2230, mule 225, poultry 36527, and beehives 2926 (EASE 2004/05V).
Crop agriculture with extensive livestock production system is the main livelihood of the population and the major plants grown on the area include eucalyptus, junipers, olive, acacia and bushes while teff, barely, wheat, bean, peas, lentils, and vetch are the main crop varieties, besides to this grasses from natural pasture and crop residues constitute a major component of feed resources used for livestock in rural areas where as stall-feeding using hay and concentrates (nouge-cake, oat grains etc.) who own crossbreed cattle in urban dwellers (NSDAD 2005).
The study was conducted on 140 dairy cows/ heifers. The age of animal varied from 2 to 9 years. All were inseminated during the whole course of the research period October to April/ 2006 according to the techniques described by Morrow and Roberts (1986). All inseminated cows were subjected to pregnancy diagnosis by rectal palpation (Roberts 1986).
Using a structured questionnaire format a longitudinal study was carried out. Data were collected and registered on the prepared format for each cow/heifer by interviewing the owners, concomitant to performing AI services. The information collected comprise animal identifications, breeding status, history of reproductive problems and health status, feeding and housing conditions, about knowledge and method of heat detection by the owner and the inseminator, etc. Accordingly, a total of 140 cows and heifers served by AI were visited to determine the pregnancy status and to assess housing condition, feeding and health status. Rectal palpation was performed to diagnose pregnancy following the usual routine procedure.
Ninety-six cows and forty-four heifers brought to the station for AI were served after confirming the heat symptoms. The heat was detected according to the procedures described previously (O’Connor 1993; Hafez 1993) by grouping the animals in to three based on the time of presentation: below 10 hrs, 10-20 hrs and above 20 hrs after heat detection based on the information given by the owners.
For the insemination of the animals in heat, similar materials and equipments were used with the previous description (Asefa 2004; Webb 1992). These include frozen semen under a straw at -1960c in liquid nitrogen, a thermos, towel, a thermometer, straw cutting scissor, an inseminating catheter gun made from thin metal tube, disposable plastic sheath and plastic long rectal glove. The semen used for this study was obtained from Kaliti Artificial Insemination Center where the center collects semen from exotic Holstein-Friesian and Jersey breeds and local Borana and Fogera types of bulls.
After hygienic practices carried out for reproductive organs, the thawed straw cut at the sealed end and inserted in to the gun by pulling the plunger backward and holding it is in upright position, allowing air bubbles to rise to the sealed end and then install the sheath over the gun (Asefa 2004). Then the semen deposited in to the body of the uterus recto-vaginally by holding the cervix to monitor the position of the head of the catheter gun. Finally, owners provided with AI certificate set and told to them to bring the cow/heifer after two months for pregnancy diagnosis (Ibrahim 1990).
The preliminary semen motility test was done before commencing the procedures. The semen of each batch was assessed for post-thaw motility by using light microscope at 40x as recommended by Hafez (1993) and Rodriguez-Martinez (2000). It was done by warming the stage of the microscope and the glass slide, then putting a drop of semen from the thawed straw on the glass slide and covering with the cover slip.
Retrospective information generated from the records from 2000/01 to 2003/04 in Girar Jarso District AI station recording book was evaluated for some aspects of the reproductive indices (Gaines 1989). All the data were entered in to Microsoft excel sheet. Data was summarized using descriptive statistics (means, standard errors, proportions, minimum and maximum values). Proportions were compared using Chi-square test. The relationships between variables breed, parity, BCS and postpartum reproductive disorders were computed using Pearson correlation. The level of significance was held at p<0.05 to show statistically significant differences among variables.
irs service conception rate- the number of successful first services (pregnancies) divided by the total number of first service and expressed as percentages; Mean number of services per conception- the total number of service divided by the number of successful services (pregnancies) and Conception rate- the percentage of cows/heifers diagnosed to be pregnant up to three services divided by all cows/heifers inseminated during the study period.
Due to the limitation of recording system, only the conception rate was analyzed to assess the quantitative status of AI efficiency in the study area for the previous four consecutive years. The total number of animals inseminated from 2000/01 to 2003/04 was 1902, but those checked through rectal palpation for pregnancy were 1167 (Table 1).
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Table 1. Animals inseminated and conception rate during the year 2000 to 2004 in Selale, Fitche AI station |
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Year |
No of animals inseminated |
Conception |
||
|
Total |
Cross |
Local |
||
|
2000/01 |
193 |
130 |
63 |
52 |
|
2001/02 |
214 |
163 |
51 |
56 |
|
2002/03 |
350 |
254 |
91 |
53 |
|
2003/04 |
420 |
308 |
112 |
58 |
During house-to-house visits, farm husbandry including feeding, housing and hygiene status was generally evaluated as poor. Especially the floor, ventilation and drainage systems of the houses were poor. Greater conception rate was found in cross than local breeds with no significant difference statistically, whereas parity number had significant effect (P<0.05) on conception rate (Table 2).
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Table 2. Effect of parity number and breed on conception rate |
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Factor |
Total no Inseminated |
Pregnancy rate |
x 2 |
p |
|
|
No |
% |
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|
Parity
|
|
|
|
|
|
|
Breed
|
|
|
|
|
|
Of the 140 cows inseminated during the study period, the highest pregnancy rate, 74.3% (n=104) was found in cows/heifers inseminated between 10-20 hrs after the observation of estrus. As can be seen from Figure 1, the lowest pregnancy rate was found in those cows inseminated after 20 hours (10%, n=14) post estrus and in animals that inseminated before 10 hrs (15.7%, n=22) post estrus (Figure 1).
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| Figure 1. Effect of insemination time after the onset of heat on overall conception rate |
The conception rate was found to be significantly affected by condition scorings in that animals with lean body condition score had lower conception rate (40%, n=20) than animals with medium body condition score (94.2%, n=113).
The mean (SE) number of services per conception was 1.95 ±0.41 and when only those cows/heifers that have got pregnancy were considered, the mean number of services per conception was 1.47 ±0.053.
The first service conception rate was 49.3% (n=140). The overall pregnancy rate was 86.4% (n=140).
From the total cows/heifers inseminated, thirty-six were with the history of miscellaneous reproductive problems, of which 69.4% of them were pregnant and this was significantly different from those cows/heifers inseminated with no history of abnormalities having the conception rate of 92.3% (n=107).
Those animals getting inseminations ≥3 were examined and the percentage of repeat breeders found to be 13.5% (n=19) where 11 of them were heifers and eight were cows.
The overall pregnancy rate observed in this study was 86.4%. This value lies within the level reported by Falvey and Chantalakhana (1999)>80% as optimum overall conception rate in smallholder dairy farms where as higher than the findings reported by Shiferaw (2000) and Arthur (1990) 84.66% and 63%-71%, respectively. Sovani and Franceschini (1998) from Debre Zeit ILCA station reported conception rate of 65.8% while Kaziboni et al (2004) reported lower conception rate of 59% on zebu breeds. Compared to the retrospective findings, the current study was by far greater with regard to conception rate. This could be attributed to inadequate recording system used, and lack of regular monitory system. Moreover, the owners usually bring back their cows/heifers after insemination only if they have hesitation of pregnancy otherwise they are not volunteer to bring back their animals.
On the other hand, in the present study the first service conception rate was 49.3%, which is within the range of Arthur et al (1986) who reported as 40-60%. Sovani and Franceschini (1998) reported a higher figure 65.8% from Debire Zeit ILCA and Shiferaw et al (2003) has 51.68% in Holetta research center. Gaines (1989) found conception rate of 45-60% while 48% recorded at Gobe ranch by Mukasa-Mugerwa (1989). The differences among the different reports could be attributed to a multitude of factors such as the skill of AI technician, service time after heat onset, semen quality and breed of animals.
The mean number of services per conception obtained in the longitudinal study was 1.95±0.41 which is a bit higher than that of 1.74-1.8 by Tegene et al (1981) and 1.75 by Shiferaw (2002) while slightly lower than that of 2.0 ±0.1 by Nugussie et al (1998). In the same study area (Selale Fitche) a report released by NAIC (1995) indicated that the average service per conception was found to be 1.8 which is close to the current study. When considering only those pregnant, the value obtained 1.47 ± 0.053 closer to the result 1.4±0.6 found by Sovani and Franceschini (1998) in cross breeds. The variation probably due to the difference of breeding system used (Mukasa-Mugerwa 1989) and other related factors as mentioned above. Conception rate in crosses was better than the local breeds even though there was no significant difference (p>0.05) among breeds in this study. This could be due to the shortness of estrus period in local breeds (Anderson 1993; Mukasa-Mugerwa 1989) and the management difference where more of the cross breeds reared in town dwellers and fed them outdoor. Galina and Arthur (1990), Tegegne et al (1989) and Mukasa-Mugerwa et al (1991) also reason out local zebus doesn’t exhibit overt estrus signs as like cross breeds which may lead to incorrect timing of insemination. An important finding to note was the difference in response by parity with an improvement of conception in cows than heifers. This is consistent with reports in the literature where by heifers are normally recognized to be immature and may not exhibit a fertile first estrus (Kaziboni et al 2002) which is correspond with the presents result. Also similar results reported on the effect of parity on conception rate by Mukasa-Mugerwa et al (1991). Time for insemination reported by Falvey and Chantalkhana (1999) in the later part of the heat period around 12-18 hours while Roberts (1986) and Galina et al (1982) indicated that 8-24 hours. But for the present study the time range used was the optimum time discussed by Cartmill et al (2001), Roelofs et al (2005) and Smith (1982) who concluded that for maximum conception rates, cows should be inseminated at 10-20 hrs after the beginning of standing heat and result was higher and significantly different (p<0.05) from those inseminated below 10 hrs and beyond 20 hrs.
Good body condition scoring during the mating period has a positive impact on conception rate (Mukasa-Mugerwa 1989; Kaziboni et al 2002). Our result in this study also fully agreed with this assumption and there was a tendency for conception rate to increase with increasing in body condition score (Shiferaw et al 2003). The observed differences to be significant may be attributed to the finding that the variations in condition of animals were maximal. Those cows/heifers without previous history of reproductive disorders including uterine prolapse, retained fetal membrane, dystocia and ovarian cyst have significant difference in conception rates between cows without previous history of postpartum problems as has been reported earlier (Roberts 1986; Bekana et al 1997).
Rate of repeat breeders were high in this study. This is supported by Hafez (1993) and Bekana et al (1994) indicated that the rate of repeat breeders higher in dairy herds using artificial insemination. Arthur (1990) associated this case with early embryonic mortality, poor semen quality, poor insemination techniques, subclinical uterine infection and environmental temperature. Also Shiferaw et al (2002) detected high proportion of reproductive abnormalities as having important contribution for reproductive inefficiency. The incidence of repeat breeders has been reported by Roberts (1986) 10.2 to 13.7, which comprises the present result in this range.
The authors are grateful to Fitche veterinary clinic staffs for their facilitation and support during the data collection.
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Received 27 December 2015; Accepted 1 April 2016; Published 1 May 2016