Livestock Research for Rural Development 23 (3) 2011 Notes to Authors LRRD Newsletter

Citation of this paper

Factors that limit first service pregnancy rate in cows at char management of Bangladesh

A K Paul, M G S Alam and M Shamsuddin

Department of Surgery and Obstetrics, Faculty of Veterinary Science, Bangladesh Agricultural University,
Mymensingh, Bangladesh


This study was conducted from February 2009 to February 2010 at the selected char areas of river Jamuna of Kazipur Upazila (sub district) at Sirajgonj district of Bangladesh to determine the factors that limit the pregnancy rate to first artificial insemination (PR/FAI) in cows. A number of 852 cows were selected considering potential factors of body weight, breed, age, parity, season, breed of bull semen and artificial insemination (AI) technician. Among 852 cows, overall pregnancy rate was 57.3% (n=488) and first AI pregnancy rate 42.7% (n=364). Overall 1.7 AI was required for each pregnancy. Multiple logistic regression analysis was done to measure the association between first AI pregnancy rate and potential risk factors.

A significantly (p<0.01) (OR=0.591, 95% CI 0.413, 0.846) low PR/FAI (34.9%) was in L HF cows. The first parity cows was significantly (P< 0.01) considered (OR=0.573, 95% CI 0.404, 0.813) as a risk factor for low (37.3%) PR/FAI. A significantly (P<0.05) (OR=1.73, 95%CI 1.113, 2.706) higher (45.5%) PR/FAI was in spring (March - April) compared to summer (43.1%) (May - July). A chance of pregnancy to first AI in spring (March - April) was comparatively more (1.7 times) than summer (May - July). The less skilled/experienced AI technician had significant (P<0.05) (OR=0.662, 95%CI 0.466, 0.940) poor performance (38.6%) compared to skilled and well experienced AI technician, and it was considered as one of the risk factors (P<0.05) for PR/FAI. It is suggested that training on dairying with community veterinary care improves the livelihood of poorest people living in the island chars in Bangladesh.

Key words: risk factors, desi, odd ratio, tropics


Development of dairy cattle is an important tool for self employment opportunity and poverty alleviation (Kurwijila et al 1995). For this purpose development partners had introduced cows to the poor people as an asset more than a decade. Dairy cattle rearing and management in the main land is convenience and easy due to available facilities such as feeds, drugs, veterinary support as well as milk and meat price. But in char areas, farmers face more troubles for rearing of cattle due to some constraints such as lack of knowledge about cattle rearing, unavailable of drugs, feeds, veterinary supports, low milk price etc which results unhealthy and infertility of cows. Most of the cows are Zebu type producing -1 litres of milk per day. As a result, development of cattle population in the char area and improvement of livelihoods is hampered. For increasing cattle population and milk yield per cow, crossbreeding with superior bull’s semen using Artificial Insemination (AI) technique as well as increasing pregnancy rate of cows is essential in char area.

One of the major constrains of profitable dairy farming is low pregnancy rate in cows (Alam et al 1994, Shamsuddin et al 2001). The productivity of cattle is low because of poor genetics (Alam and Ghosh 1994; Rahman et al 1995; Alam et al 2001), poor nutrition (Ghosh et al 1993; Alam et al 2006), weak herd health veterinary services and marketing access (Alam 2005, Shamsuddin et al 2007). Economy of dairy farming largely depends on a good pregnancy rate after artificial insemination (AI). The twelve-month calving interval is advantageous for maximal milk yield per cow per year with good economic return (Opsomer et al 1996). It was observed that the loss in gross margin (milk sell over feed cost) is increased when calving interval exceeded twelve month (Opsomer et al 1996, Shamsuddin et al 2006).

AI is widely used as a breeding tool. It is used for spreading superior germ plasm of proven sires. Government has spent a lot of money for AI coverage since 1950 (Ahmed and Islam 1987). The efficiency of the AI technique and the fertility of cow depend on several factors. Any deficiency reduces fertility resulting in economic losses. Cow’s fertility is commonly measured by calculating the percentage of cows that one pregnant after a single service, also known as the pregnancy per artificial insemination (PR/ FAI), Quintela et al 2004). There is minimal work done on improving fertility of cows in the char areas. It is not possible to develop dairying without improving fertility of cows.

Considering the above facts and circumstances, this study was designed to determine the first AI pregnancy rate in cows and find out the risk factors responsible for low pregnancy rate at first AI.

Materials and methods

Study area

The study was conducted from February 2009 to February 2010 at the char area of river Jamuna at Sirajgonj district of Bangladesh covering three unions of Nischantapur, Tekani and Natuarpara of Kazipur Upazila (Sub district). 

Preparation of a format for data entry

For collection of information, a format was used for keeping the recorded data. The format contained date, name of farmers and their address, location mark, age, breed, parity, breed of bull semen, season, date of oestrus, name of AI technicians, time and date of AI.   

Animal selection and management

Eight hundredth and fifty-two cows were selected and grouped according to breed (Local, LHF, LSL), age (2-3, 3-4 and 4-6 years), body weight (up to 150, 150-200 and >200 kg) parity (Heifer, 1st and 2nd), bull semen (sahiwal, HF and sindhi), season { Summer (May to July), Rainy (August to October), Winter (November to February) and Spring (March to April)}and skillness of artificial insemination (AI) technician (Mr. Technician 1, Mr. Technician 2 and Mr. Technician 3 who were 7, 5 and 1 year experienced to AI, respectively). The farmers cows were vaccinated against foot and mouth disease, black quarter, haemorrhagic septicemia and anthrax and dewormed at three month interval. All animals were dewormed orally using bolus containing tetramisole hydrochloride (2.0g) and oxyclozanide (1.2g) per 100-150 kg body weight (Levanid, The ACME Laboratories Ltd., Dhaka, Bangladesh). Animals were grazing from early morning up to noon (mid day) and fed 4-5 kg green grasses mixed with 2-3 kg straw daily as evening meal. Few farmers were able to supply 150 gm mixed concentrate (rice police, wheat bran, broken rice and oil cake) per animal. 

Artificial insemination and pregnancy diagnosis

All animals were inseminated with proven frozen bull semen and pregnancy was diagnosed by per rectum examination after 60-80 days post AI. The result of pregnancy diagnosis was recorded. 

Reproductive indices

i  Overall pregnancy rate = (No. of cows pregnant)/Total no. of cows receiving AI)*100

ii  Pregnancy rate to first AI (PR/FAI) = (No. of cows pregnant to first AI)/Total no. of cows receiving AI)*100

iii  AI per pregnancy = (Total number of AI)/Total cows pregnant 

Statistical analysis

The raw data were decoded, entered and sorted accordingly using the MS Excel. The data were then transferred to analytical software SPSS (version 11.5) for multiple logistic regression, which was done to measure the association and strength of association between the potential influencing factors (Anon 1996).

Results and discussion 

The overall pregnancy rate in cows artificially inseminated was 57.3%, which partially agrees with Khan et al (2008). The PR/FAI in cows was 42.7% which was supported by the report (41.9%) of Estrada and Perez (2001). This rate was, however, higher than that reported (49.8%) by Quintela et al (2004) and lower (34.5%) than that recorded by Mekonnen et al (2010). Local breed of cattle showed higher PR/FAI than LHF and LSL breed (Table 1).  The association between breeds of cows and PR/FAI was highly significant (Chi-square value: 22.6, P<0.001). In Table 2, the multiple logistic results shows that the LHF cross breed was significantly (P < 0.01) associated with low PR/FAI compared to Local breed. LHF breeds had less chances (0.6 times) to get PR/FAI than local breed. This is supported by Rao et al (1992) who reported higher conception rate of indigenous cows than for all other breed types (P<0.01). The PR/FAI of SL bull semen was higher than HF and Sindhi (Table 1 ). The correspondence between breed of bull semen and PR/FAI was non significant (P>0.05).

Table 1. Frequency distribution for the qualitative variables selected for the PR/FAI in cows.




Pregnancy rate at first AI (%)

Breed of cows










Breed of semen










Body weight of cows

Up to150 kg



>150-<200 kg



>200 kg



AI technicians

Mr. Technician 1 7 year experience



Mr. Technician 2 1 year experience



Mr. Technician 2 5 years experience




Summer (May - July)



Rainy (August -October)



Winter (November - February)



Spring (March – April)



Parity of cows










Age of cows

>2 – <3 years



>3 – <4 years



>4 years



The pregnancy rate at different body weights <150 kg, >150 kg to <200 kg and >200 kg were 36.5, 47.5 and 44.9%, respectively (Table 1). The PR/FAI in cows of body weight between 150kg and 200 kg was higher (47.5%) than body weight less than 150 kg (36.5%) and more than 200 kg (44.9%). The association between body weight and PR/FAI was highly significant (Chi-square value: 11.82, P<0.01). But logistic regression showed the effect of different body weights of cows on PR/FAI and it was not significant (P>0.05). Saacke et al (1991) reported that the performance of heavier cows more than lighter counterparts.

The performance on AI technicians Mr. Technician 1, Mr. Technician 2 and Mr. Technician 3 on pregnancy rate to first AI was 45.6, 38.7 and 43.6%, respectively (Table 1). The PR/FAI by Mr. Technician 1 was higher (45.6%) than Mr. Technician 2 (38.6%) and Mr. Technician 3 (43.6%). The association between AI technicians and PR/FAI was significant (chi-square value: 5.27 with 2df, P<0.05). Mr. Technician 1 was significantly (P<0.05) responsible for lower PR/FAI (OR=0.662, 95%CI 0.466, 0.940) compared to Mr. Technician 2. Thus, the cows those were inseminated by AI technician-2 had less chances (0.7 times) to PR/FAI than those by AI technician-1 (Mr. Technician 1). This finding is agreement with the report of Hassan (2003) and Shamsuddin et al. (2001).

Table 2. Final Logistic regression analysis to estimate adjusted odd ratio for the PR/FAI in cows



P value


95% CI of the OR

Lower Limit

Upper Limit

Breed of cows**
















Breed of semen
















Body weight of cows

Up to150 kg





>150-<200 kg





>200 kg







Mr. Technician 1





Mr. Technician 2





Mr. Technician 2






Summer (May - July)





Rainy (August –October)





Winter (November – February)





Spring (March - April)





Parity of cows**
















Age of cows

2-3 years










>4 years





1 Indicates base category, with which we have to compare the odds ratios of other categories. ** chi-square Value P<0.01 and * chi-square Value P<0.05

The PR/FAI of summer (May - July), rainy (August - October), winter (November - February) and spring (March - April) seasons were 43.1, 34.4, 47.1 and 45.6%, respectively (Table 1). The PR/FAI in winter (November - February) season was higher (47.1%) than summer (May - July) (43.1%), rainy (August - October) (34.4%) and spring (March - April) season (45.6%). The association between seasons of AI and PR/FAI was highly significant (chi-square value: 33.34 with 3df, P<0.01). The AI done in spring (March - April) season had significant (P<0.01) impact on PR/FAI compared with AI in summer (May - July) season. Thus, the AI done in spring (March - April) was 1.7 times more chances PR/FAI than AI in summer (May - July). In char areas, the green grass is available in winter (November - February) spring (March - April) and more scarcity of grass is in the rainy (August - October) due to flash flood. In the summer season, heat stress (290C) of dairy cattle is markedly affecting the pregnancy rate (25.4%) of dairy cattle (Ricardo et al 2004). The season of insemination might be the important factors to get maximum conception rate in cows (Miah et al 2004). This finding is agreed with Quintela et al. (2004) who stated calving season was a significant factor for low PR/FAI. It is reported that small ovarian follicles are susceptible to heat stress (Badinga et al 1993; Wolfenson et al 1995). Delayed effects of heat stress on follicular steroidogenic capacity (Roth et al 2001) and follicular dynamics (Roth et al 2000), as well as on oocyte quality and embryo development (Roth et al 1999) could be responsible for the lower fertility of cows in the autumn. Ahmed et al. (1992) studied the seasonal effect on conception rate of cows in Bangladesh and recorded the highest conception rate (62.1%) in spring followed by summer (51.6%), winter (47.8%) and rainy (41.5%). The author suggested that the spring (February to march) may be the best season for good fertility of cows and heifers in Bangladesh.

The pregnancy rates of Parity-0, Parity-1 and Parity-2 were 44.8, 37.3 and 42.2%, respectively (Table 1). The PR/FAI of parity-0 was higher (44.8%) than parity-1 (37.3%) and parity-2 (42.2%). The PR/FAI of parity-2 was higher (42.2%) than parity-1 (37.3%). The association between parity and PR/FAI was highly significant (chi-square value: 12.89, p<0.01). The first parity cows were significantly (P<0.01) associated with low PR/FAI compared to parity-0 (Table 2). Thus, first parity cows had less chances (0.6 times) to get PR/FAI than non parity. This finding was in agreement with Quintela et al (2004) and Khan et al (2008) showed slightly decreased PR/FAI as parity increased. Sarder (2001) observed the effects of parities on parturition to first oestrus interval longest in first parity cows (150.214.7 days).

The pregnancy rate in cows 2-3, 3-4, and >4 years of age of cattle was 41.8, 43.5 and 38.7%, respectively (Table-1). The PR/FAI at 3-4 years of old was higher (43.5%) than 2-3 (41.8%) and >4 years (38.8%) old of cows. It is supported by Spalding et al (1974) who reported that a slightly increase in the fertility of cows up to 3 to 4 years of age and decline after 4 years of age and marked decline in fertility in the cow over 7 years of age. Bakhinov and Sabostin (1995) reported that conception rate to first insemination was 39.1, 38.0 and 34.8% for heifers and in younger and older cows respectively. The association between age and PR/FAI was non significant (chi-square value: 4.01, P>0.05). Table 2 shows that the effect of age on PR/FAI was not significant (P>0.05). 

The overall (One & Two) AI per pregnancy was 1.7 which indicates good fertility of cows. It is supported by Abeygunawardena et al (2001) who found an overall AI per pregnancy of 2.0 in small holdings and 1.9 in large farms in Srilanka. Jabbar and Ali (1988) studied the productive performance of Indigenous and crossbred cows in Bangladesh and demonstrated the overall AI per pregnancy was 1.7. AI per pregnancy of Local, LHF and LSL was 1.6, 2.2 and 1.6, respectively. It is supported by Sarder et al (1997) and Shamsuddin et al (2001) who are reported that the local cows required fewer services per conception (1.4) than the crossbred animals (1.8). AI per pregnancy of SL, HF and Sindhi bull semen was 1.6, 1.9 and 1.7, respectively. AI per pregnancy of body weight up to 150 kg, >150 to <200 kg and >200 kg was 2.0, 1.6 and 1.7, respectively. AI per pregnancy of Mr. Technician 1, Mr. Technician 2 and Mr. Technician 2 was 1.6, 1.9 and 1.6, respectively. AI per pregnancy of summer (April-June), Rainy (July- September), winter (October-January) and spring (February –March) was 1.7, 2.3, 1.8 and 1.4, respectively. AI per pregnancy of Parity-o, Parity-1 and Parity-2 was 1.6, 2.1 and 1.7, respectively. AI per pregnancy at 2, 3 and 4 years of age was 1.7, 1.7 and 2.0, respectively. This result is supported by the observation of Sultana (1995) who demonstrated AI per Pregnancy of 540 cows from Indigenous, Sahiwal, Sahiwal Friesian (F1), Jersey, Indigenous Jersey (F1), and Indigenous Friesian were 1.8, 1.1, 2.1, 2.0, 1.4 and 1.7, respectively. Mondal (1998) found that the AI per pregnancy was 1.6, 1.7, 1.5, 1.7 and 1.9 for Jersey cross, Sahiwal cross, Sindhi cross, Holstein cross and Red Chittagong cows, respectively.

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Received 22 August 2010; Accepted 14 January 2011; Published 6 March 2011

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