Reproductive performance of dairy cows under artificial insemination in south and northwest part of Ethiopia

T Ali, A Lemma and T Yilma

Addis Ababa University, College of Veterinary Medicine and Agriculture, P.O.Box 34, Debrezeit, Ethiopia
tesfaali@yahoo.com

Abstract

A cross sectional study and retrospective data analysis were conducted to examine and characterize the reproductive practices and outcomes by location (district) and to identify cow factors that influence reproductive efficiency of dairy cows under artificial insemination (AI). Data were collected on reproductive events from 428 dairy farms in four districts from two regional states of Ethiopia.

The overall mean age at first calving (AFC) was 34.8 (n=386) months, where it was significantly different across locations (districts). Mean days for calving to first service interval (CFSI) and calving to conception interval (CCI) were 222 (n=320) and 257(n=234), respectively. Even if breed and location differences had no effect on CFSI; CCI was significantly affected by location. Number of service per conception (NSC) for pregnant cows were 1.55 (n=234) and there was statistically significant difference (P<0.05) in the NSC between districts and between breeds. First service conception rate (FSCR) was 40.9% with significant difference ( P<0.05) between location (districts) and breeds. Days after last calving (DALC) were 260.8 (n=331) and had significant difference between breeds. All the traits studied did not differ significantly (P>0.05) between parities. In Ethiopia, location and breed differences are still the major determinants of reproductive performance of dairy cows.

Key words: breed, calving to conception interval, number of service per conception, parity, region

Introduction

Ethiopia has the highest livestock population in Africa. However, the dairy industry is not developed like other East African countries. The country has made great effort to improve the productivity of local breeds through AI program m to crossbreed locally adapted cattle breeds with improved exotic dairy breed ones. This program addresses major parts of the country including Amhara and SNNPR regions. However, the success of such programs is not satisfactory due to numerous factors, including substandard nutrition, poor husbandry practice and infrastructure status. Thus, dairy producers have challenging complaint about a poor reproductive performance in animals using AI (Lemma and Kebede 2011). To ensure the success of the AI programme, regular supervision should be taken by evaluating the reproductive performance of the dairy cow under the prevailing management and environmental conditions since dairy cattle are important sources of food and income for smallholders, especially in urban and peri-urban areas of Ethiopia.

Herd profitability is majorly determined by dairy cows reproductive performance (Esslemont and Kossaibati 2002, LeBlanc 2007) which is a major determinant for overall productivity of dairy production systems by affecting the efficiency of milk production, the number of calves produced per cow and lifetime milk production (de Varies 2006). Major reproductive performance factors encompass both herd-level management factors (such as methods of husbandry, feeding, estrus detection, semen handling and transition cow management) and cow-level factors (such as age, BCS, post parturient problem, disease events, milk yield, and genetics) (Lucy 2001, Hudson et al 2012). Studies in tropical countries showed that performance of smallholder dairy cattle affected by various factors such as genotype, location (geographical location), season of calving, suckling status, parity, and body condition score (Obese et al 1999, Msanga et al 2000, Masama et al 2003, Msanga and Bryant 2003, Msangi et al 2005, Lobago et al 2007).

Numerous measures of reproductive performance have been proposed, including calving to first service interval (CFSI), first service conception rate (FSCR), calving to conception interval (CCI), calving interval (CI), number of service per conception (NSC), and 21-days pregnancy rate (Pursley et al 1997). The most important parameters of fertility are FSCR, NSC and CCI (Cavestany and Galin 2001).

Retrospective research works have been done at institutional large dairy farms to evaluate reproductive performances of dairy cows (Gebyehu et al 2007, Amene et al 2010, Habtamu et al 2010, Tadesse et al 2010) and also cross-sectional studies were done to evaluate the performance of dairy cattle at a district level (one location) (Shiferaw et al 2003, Lobago et al 2006, Mureda and Mekuraw 2007, Solomon et al 2009, Yifat et al 2009, Mekonnen et al 2010). However, none of the studies were done to evaluate the reproductive performance of dairy cows for AI breeding solely. Furthermore, not any of the studies was done to evaluate the effect of locational differences on the efficiency of reproductive performance. Therefore, the specific objective of this study was to examine and characterize the reproductive practices and outcomes of the Ethiopian dairy cows by location and to identify the effect of location (district), breed and parity on dairy cows’ reproductive efficiency under AI breeding.

Material and methods

The study was carried on dairy farms kept in Amhara and South Nation and Nationality People Region (SNNPR) regions of Ethiopia which are located in Northwestern and Southern part of Ethiopia, respectively. Two districts from each region were selected that were believed to have better application of AI technology, wide range of agro-ecology constitution and availability of institutions that exercise in livestock sector. The districts were Fogera and Guangua from Amhara region and Aletawendo and Dale districts from SNNPR region. One hundred and seven farms using exclusively AI were selected from each district and only cows beyond 60 days since their last calving were used in this study. Of the total 565 dairy cows were selected as studied animals; 386, 320, 234 and 331 animals were used for computing AFC, CFSI, CCI and DALC were, respectively

All selected farms were visited and data on the farm characteristics of interest and reproductive histories of individual cows since their last calving were collected by examining records, survey questionnaire for farm owners and/or attendants and examinations of individual animals including rectal palpation. Herd size and composition, feeding and reproductive management information was also collected. Cow data recorded were: age, age at first calving (AFC), parity, last calving date and calving type, date of first postpartum heat, date of first service in this lactation, number and date of last service for this lactation, BCS and rectal examination. BCS were done using a five-point scale based on Mathewman (1993). Cows non-returned to estrus for two or more months since last AI were examined per rectum for confirmation of pregnancy. The data obtained from the reproductive, breeding, and management histories were used to evaluate the reproductive performance of the dairy cows. Days after last calving (DALC), which refers to the number of days from last calving to the day of examination were used to assess the reproductive performance of non-pregnant cows. AFC, CFSI, CCI, DALC, NSC and FSCR were used as reproductive indices to determine reproductive performance. Individual cow data were entered to Microsoft Excel 2007(Microsoft Corporation, Richmond, WA). Data editing and statistical analyses were performed using SPSS for Windows (SPSS 2006). The effect of breed, location and parity on AFC, CFSI, CCI, CI and NSC were analyzed using Generalized Linear Model since these dependent variables had a non-normal distribution and to know the linear effect location, parity and breed on the above variables. Conception rates and FSCR were analyzed using the chi-square procedures.

Results

The effect of location (district) on reproductive performance of dairy cows is shown in Table 1. The lowest AFC was recorded in Fogera and the highest observed in Aletawendo district and also the crossbred cows were younger at AFC than Zebu cows as shown in Table 2.

The effect of parity on CFSI, CCI, NSC and DALC is illustrated in Table 3. District, parity and breed differences had no significant effect on CFSI. CCI was statistically insignificant among parity groups and breeds. However, locational difference had an effect on CCI, in which cows in Fogera district had longer CCI than Dale district.

Average NSC was 1.55±0.05 and there were significant differences in NSC between districts and breeds as shown in Table 1.

The overall average DALC was 261±7.6days. Breed and parity had no affect on DALC; however, DALC was affected by location where the smallest DALC wwas observed in Guangua (238days).

The overall service per conception rate and FSCR was 72.0% and 41.8%, respectively where FSCR were affected by location. FSCR of 27.2, 43.3, 43.8, and 51.1% were observed in Fogera, Guangua, Aletawendo and Dale districts, respectively. The conception rate for crossbred and zebu cattle were 73.0% and 62.5%, respectively while the FSCR were 41.0% and 50.0% for crossbred and Zebu cattle, respectively. Bothe conception rate and FSCR were not affected due to breed differences.

Discussion

The mean AFC of the dairy cows under AI breeders were 34.8 months (34.5 for cross breed and 41.3 for zebu cows). The mean AFC of crossbred cows of the present study agrees with that of Mureda and Mekuraiw (2007), Ibrahim et al (2011), and Lemma and Kebede (2011) and Dinka (2012) who reported 36.2, 34.7, 33.2 and 34.8 months, respectively, for crossbred cows in different areas of Ethiopia. But it varies from the means (32.4, 39.2 and 40.6 months) reported by Tadesse et al (2010), Moges (2012) and Shiferaw et al (2003), respectively. The present AFC finding for Zebu cows is similar to the findings of Hailemariam and Kassamersha (1994) and Habib et al (2010). In this study, the crossbred cows were younger at AFC compared to Zebu cows and AFC also varies between locations. The variation in AFC between breeds and locations is probably due to the difference in management and feeding systems. The average AFC for cattle on recommended level of nutrition is approximately two years (Ibrahim and Zemmelink 2000, Ball and Peter 2004). According to the results of the present study, AFC values for both breeds of cattle were far below the standard values reported in temperate countries. In addition to genetic variation, the lower AFC of Zebu cows may be attributed to the reduced growth rate and delayed puberty as the result of low level of nutrient intake by heifers which have given low attention than the crossbreds. Almost all farmers in the study area keep their Zebu cows to graze in natural pasture with some supplementation. Management factors especially nutritional status determines pre-pubertal growth rates and reproductive development (Masama et al 2003), high plan of nutrition could hasten puberty by increasing the growth rate of heifers (Hafez and Hafez 2000).

The 222days CFSI of this study is much higher than 115, 141, 162 and 165 days values reported by Tadesse et al (2010), Shiferaw et al (2003), Mureda and Mekuriaw (2007) and Ibrahim (2011) respectively. While the CFSI of zebu cows (246 days) coincides with the finding of Mekonnen et al (2010) who reported 241days. Location, parity and breed differences had no effect on CFSI. Zebu cows had higher CFSI than the crossbred ones.

CCI of 257days coincides with that of Lobago et al (2007) who reported 253 days in a longitudinal study in central highlands of Ethiopia. However, it is higher than that of Cavestany and Galina (2001), Lobago et al (2006), Mureda and Mekuraiw (2007) and Lemma and Kebede (2011) who reported 132, 201, 219 and 176 days, respectively and lower than 285days reported by Amene et al (2011). Cows in Fogera district had longer CCI when compared to Dale district. The higher value of CCI at the present study may be attributed to managemental problem like nutrition and breeding practices. The difference of CCI across locations in is associated to the efficiency of AI, since Fogera district have the highest NSC (table 1) and lowest FSCR.

The overall NSC mean found in this study was 1.55 whereas Fogera, Guangua, Dale and Aletawendo districts reported values of 1.96, 1.41, 1.35 and 1.40, respectively. The NSC revealed in the present study is related to 1.52 of Dinka (2012), and 1.54 of Habib et al (2010). Although, the current value lower than 1.8 and 2.1 values reported by Tadesse et al (2010) and Lemma and Kebede (2011), it is much higher than the report of Moges (2012), Sutradhar et al (2010) and Ibrahim et al (2011) who reported 1.29, 1.36 and 1.4 respectively. The insignificance difference of parity on NSC coincides with the report of Assegd and Brahanu (2004). The local breed (1.20) had lower NSC rate than the crossbred (1.58). These results agree with those of Rahman et al ( 1998) who reported 1.30 and 1.70 NSC for local and crossbred cows respectively. Similarly Miazi et al (2007) reported that local breeds (1.3) have lower NSC than Holstein-Frisian cross (1.5). The reasons for the high numbers of services per conception as the results of problems associated with poor semen quality, poor semen handling practices and poor insemination practices.

Two hundred sixty (260) days of DALC of the current study is much higher than148, 178 and 201days reported by Kassa et al (1998), Lemma and Kebede (2011) and Lobago et al (2006) for crossbred cows studied in Ethiopia. Even if breed and Parity did not affect DALC, regional difference had significant effect. In addition to the delayed postpartum anestrous other factors possibly silent estrus, poor estrus detection, or other factors, such as farmer decision’s or ignorance, plays a role in the extended DALC.

The overall mean FSCR (41.8%) obtained in this study, is lower than the recommended 45-60% (Gaines 1989), indicating the inefficiency of AI service in the study area which could be associated to several factors. Successful service or insemination depends on many factors such as quality of semen, skill of the inseminator, proper time of insemination and cows’ related factors. The noticeable difference of FSCR and NSC found between location (districts) suggested that breeders’ techniques in AI differs greatly between districts. The current figure is also lower than previously reported values of 45.5 (Lemma and Kebede, 2011), 45.9 (Mureda and Mekuriaw 2007), 44-45% (Shiferaw et al 2003) and higher than 34.5% (Mekonnen et al 2010). This difference is attributed due to the lowest FCR of Fogera district (27.2%) since other location (districts) had values that are comparable to the above reports. In addition, this value is similar to that of Cavestany and Galina (2001) and Ansari-Lari et al (2010) who reported 40.5 and 41.6% respectively.

Conclusion

• The AFC was greater than 32 months. The extended value of CFSI, CCI and DALC in the study area shows the inefficiency of the reproductive performance of dairy cows. The cow factors such as parity and breed did not affect many of the reproductive indices; CCI, NSC and FCR variations recorded between locations (districts) shows the wide difference in reproductive management specially the efficiency of the AI technicians. Thus, rather than the cow factors, in Ethiopia management differences are still the major determinants of reproductive performance of dairy cows. The higher value of CCI and DALC from the previous studies shows that the declining of reproductive efficiency of dairy cows, by which the dairy industry is non-promising to meet the ever growing milk demand of the country. Thus, a sustainable extension service should be established in order to improve the management and efficiency of AI service to bridge the existing gaps and to improve the reproductive performance of dairy cows.

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Received 31 July 2013; Accepted 4 October 2013; Published 1 November 2013

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