Evaluation of breeding objectives, breeding practices and reproductive performance of indigenous dairy cows in selected districts of Kaffa Zone, South West Ethiopia

Abstract Background Breeding objectives are designed to achieve targeted dairy cow production goals, which can be affected by production type, farmer preferences, environmental factors and genetic factors individually or in combination. Breeding practices, such as both controlled and uncontrolled, and artificial insemination (AI) are the tools used to obtain the desired breeding objectives. The lower reproductive performance of indigenous dairy cows affects the total milk production and calf crops that are produced during their lifetime. Designing appropriate breeding objectives and breeding practices can improve the reproductive performance of dairy cows and their overall production performance. Materials and methods The current study was conducted with the objective of evaluating the breeding, practices and performance of indigenous dairy cattle in the south western part of Ethiopia. The districts of Gesha and Chena were purposefully chosen. The study design for the 384 household surveys was a cross‐sectional survey with a simple random sample approach. Data analysis was carried out by MS‐Excel (2010) and the general linear model procedure of SAS of 2008. Results The current study revealed that methods of breeding were predominantly natural‐controlled mating, followed by natural‐uncontrolled mating and AI in descending order. Breeding objectives were input function, output function, sociocultural and economic functions and assets and security functions in decreasing order of rank. Reproduction performance indexes of indigenous dairy cows age at first service (3.72 ± 0.05 years), age at first calving (AFC) (4.71 ± 0.07 years), calving interval (CI) (1.58 ± 0.03 years), days open (DO) (4.26 ± 0.11 months), services per conception in natural mating (1.4 ± 0.08) and AI (2.73 ± 0.14), age of bull at maturity (4.17 ± 0.74 years), interoestrus interval (23.18 ± 0.61 days), calves crop (7.53 ± 0.22) and the life span of indigenous dairy cow (11.94 ± 0.26 years) were significant (p < 0.01) between two districts, whereas the values of age of bull at maturity and number of services per conception in natural mating were significant (p < 0.05) between districts. Conclusions Using AI and major reproduction performances, such as AFC, CI and DO of indigenous dairy cows in the study area, were very low. Therefore, concerned bodies should intervene to improve reproduction performance through the utilization of AI techniques, with the integration of forage development activities and improvements in livestock health care.


INTRODUCTION
Cattle breeds fall into two main types, which are regarded as either two closely related species or two subspecies of one species.Bos indicus (or Bos taurus indicus) cattle, commonly called zebu, are adapted to hot climates and originated in tropical parts of the world, such as sub-Saharan Africa, India, China and Southeast Asia (Purdy et al., 2021).Bos taurus (Bos Taurus taurus), typically referred to as taurine cattle, are generally adapted to cooler climates and include almost all cattle breeds originating from Europe, the Mediterranean region and northern Asia (Marleen et al., 2014).Both species were likely present since ancient times in northern Africa and the Middle East, where both natural and human-caused hybridization likely occurred (Upadhyay et al., 2017).
In Ethiopia, there are 37 recognized indigenous cattle breeds (DAGRIS, 2017).They serve as a source of draught power for the rural farming population, supply farm families with milk, meat and manure, serve as a source of cash income and play a significant role in the social and cultural values of society.Cattle contribute nearly all the draught power to agricultural production at the smallholder level in Ethiopia (DAGRIS, 2017).The Central Statistical Agency (CSA) (2018) report revealed that the total cattle population of Ethiopia is 65.35 million.Out of these, female cattle constitute about 55.90% and 44.10% are male cattle.Out of these, 98.2% were unimproved indigenous breeds, 1.62% were crossbreeds and 0.18% were exotic pure cattle breeds (CSA, 2017a(CSA, , 2017b)).From these populations, dairy cows are estimated to be approximately 12.3 million heads, and milking cows are about 6.6 million heads (CSA, 2018).Even though the country has a higher number of cattle populations, their production and reproduction performance are very low due to technical, economic and institutional constraints.Total production of milk and meat reaches 5.6 billion litres and 1.1 million tonnes, respectively.Beyond providing foods and other goods and services to the population, the livestock sector is a major contributor to export earnings, mainly through the export of live cattle and small ruminants.The annual milk yield of the country was 3.1 billion litres with a 1.64 L daily milk yield and a 6-month average lactation length (CSA, 2018).Kaffa zone is located in the south western regional (SWRP) state.
According to the CSA (2018), the region has 5358,959 cattle population.Even though it was the home of a huge dairy cattle population, production and reproduction performance were below ideal levels.
Welfare, management practices and breeding techniques were tradi-tionally encircled with technical and non-technical constraints.Moreover, recent biotechnology-assisted dairy cow production, artificial insemination (AI) and standardized selection criteria were completely in their infant stages.Farmers were literally innocent and had no expectation for the mitigation of hazards, even if they occurred suddenly, and feeding was communal, private and on some occasions both on grazing land and from naturally occurring water sources.In the past, different researchers attempted to study dairy cattle management and its constraints in some parts of the country.Though the work on evaluating breeding objectives, breeding practices and performances of indigenous dairy cows have not been investigated in the south western part of Ethiopia, particularly in the Kaffa zone.Therefore, this study aimed at evaluating the breeding objectives, practices and reproductive performance of indigenous dairy cattle in selected districts of Kaffa zone.As a result, in the current study, the dry season was represented by April, whereas the rainy season was represented by June.The zone is known for a mixed crop-livestock production system, which is used to

Description of study area
produce dairy cows (KZANRDD, 2021).Therefore, two representative woredas, namely Gesha and Chena, were selected to evaluate breeding objectives, breeding practices and the reproduction performance of indigenous dairy cows (Figure 1).

Study design and data collection
A cross-sectional study design was employed to evaluate breeding, practices and performances of indigenous dairy cattle.

Sampling techniques
Aside from the districts that were specifically chosen, three kebeles from each district were picked using basic random selection approaches (six kebeles in total).Similarly, 64 farmers were chosen at random from each of the kebeles for the cross-sectional research (a total of 384).For the monitoring project, 32 lactating cows with varying parity numbers and lactation phases were purposefully selected from survey data.

Sample size determination
The sample size was calculated using the formula given by Thrusfield (2018).

Sources and methods of data collection
The types of data sources were both primary and secondary.Primary data were collected from all households, focus group discussions (FGDs) and key informants by a well-structured and pretested

Oestrus synchronization
The sources of information were secondary data obtained from

Data management and analysis
Collected data on objectives of animal breeding and breeding practices obtained from individual farmers were entered into an MS Excel spreadsheet (Excel, 2010) for data clearance, and indices were calculated to rank breeding objectives and breeding practices by the farmer according to the following formula: Index = The value of the index corresponds to the order of ranks (the highest index value, the most desired/favoured variable).Index is the sum of (n times number of response criteria ranked first + n times number of response ranked second. . .+ number of response ranked nth) given for particular qualitative variables divided by the sum of responses under each rank summation of (n − 1 times total response ranked first +n − 1 times total response ranked second. . .+ total response ranked nth) for all qualitative variables (criteria) considered (Musa et al., 2006): where n is the number of trait ranks in concern.
Oestrus synchronization response rate and conception rate (CR) of dairy cows were calculated by using percentage and the Chi-square test.Reproduction performance data were analysed using the general linear model (PROC GLM) procedure of SAS (2008).If there was a significant difference between means, the Tukey honestly significance test at α < 0.05 and α < 0.01 were considered significant and highly significant differences, respectively, to adjust the mean separation.The model for the analysis was Yijkl = μ + Ai + Sj + Pk + εijkl, where Yijklm is response variables, μ is the overall mean (intercept), Ai is the effect of district, Sj is the effect of parity, Pl is the effect of season and εijkl is random error.years, life expectancy and family size in the current study were significantly (p < 0.05) higher for Gesha district.The current study revealed that a higher percentage of illiteracy was recorded for Chena district compared to Gesha.

Breeding objectives
In this study, the fundamental objectives were classified into four basic categories (Table 3).Breeding objective variation rose from dairy production system distinction in the study area.

Breeding practices
The breeding practices of indigenous dairy cows are presented in Table 4.In this study area, natural-controlled mating was favoured, followed by natural-uncontrolled and AI, which ranked first, second and third, respectively.Sources of replacement for breeding bulls and heifers were from known pedigree (ancestry), and markets favoured them in decreasing rank order.Note: 'χ 2 ' stands for chi square.

Oestrus synchronization practices and its efficiency on dairy cow
efficiency rates among years of inseminations, between breeds and districts.The most probable factors for the variation in oestrus response rate could be hygiene and manipulation methods of semen while processing, management habits, AI technicians, insemination time and intimated factors.The study revealed that the overall CR and fruitfulness of massive synchronization were 9.85% in study area.

Effects of parity number of the dam and semen breed on OSMAI PR
As reported in Table 6, the results of the study revealed that parity of cows and breeds of semen did not affect CR (p > 0.05).According to the AI centre record and key informants, the major causes of failure to exhibit oestrus and conceive after oestrus synchronization and mass artificial insemination were AI technician incompatibilities with breeding technology.This was due to a lack of training and awareness, poor management of semen and ill-handling techniques and selection of inappropriate animals.Besides chronic diseases, gynaecological disorders and the provision of long-lasting semen were factors.Moreover, poor management, neglect and not availing cows when it revealed oestrus at the right time were listed.

Reproduction performances of indigenous dairy cow
The main indicators of reproductive performances were age at first service (AFS), age at first calving (AFC), calving interval (CI), days open (DO), number of services per conception (NSPC) in natural and AI, eligibility of bulls to serve, interservice or interoestrus intervals (IOIs), alive calf crop, voluntary waiting period (VWP), and average life span of dairy cows presented in Table 7.
AFS of dairy cows in the current study was 3.72 ± 0.05 years with statistically significant variation (p < 0.01) between districts.IOI was 23.18 ± 0.61 days with a highly significant difference (p < 0.01) between districts.Mating was accomplished at this moment artificially or naturally according to the preferences of farmers and the compatibility of dairy cows for service.NSPC of dairy cows in current study was 1.4 ± 0.08 for natural mating with significant difference (p < 0.05) between districts.NSPC in AI in current study was 2.73 ± 0.14 in study area without significant variation (p > 0.05) between districts.According to the key informants, survey and FGD, AI was not favoured.This was due to its limited CR, interruption of accessibility, technicians and infrastructural-based constraints.However, the AFC for indigenous dairy cows in the current study was 4.71 ± 0.07 years with highly significant variation (p < 0.01) between districts.Similarly, DO recorded for indigenous dairy cows in current was 26 ± 0.11-month highly significant difference (p < 0.01) between districts.VWP was unimaginative in the study area.
CI of dairy cows in the present study was 1.58 ± 0.03 years, with highly significant variation (p < 0.01) between districts.Current study found, the age at puberty of bulls to come up fully capacitated to inseminate was 4.17 ± 0.74 years with significant variation (p < 0.05) between districts.In study area, this age was believed that, after a bull attained the average puberty age (4.17 ± 0.74 years), it was allowed to serve (both mate females and responsible for traction).The results of current study revealed that calves harvested during the complete reproductive life span of cow from the onset of AFC to the beginning of menopause stage (manifested by the complete cessation of reproductive capacity) were 7.53 ± 0.22 with statistical difference (p < 0.01)

Effects of season of the year and parity number on reproductive performances
Elements of reproductive performance that are greatly prone to seasonal alteration within a year are IOI, NSPC, CI and DO.The results of this study revealed that the season of the year can affect IOI in the dry and wet seasons of the year, with highly significant variation (p < 0.01) between districts (Table 8).Moreover, NSPC both in natural mating and AI were affected (p < 0.01).The impact of season also can extend to the DO of dairy cows.According to the current study result publicized, there was a highly significant difference in DO between dry and wet seasons of the year (p < 0.01).Similarly, indigenous dairy cows in the study area had significantly (p < 0.01) higher CI for the dry season of the year.
Here it was revealed that first parity had the longest days to cycle oestrus than the second and third parties, with a highly significant difference (p < 0.01) by exposing parity determination on reproduction efficiency.Dissimilar to the parity linear increment, NSPC in natural and artificial mating increased abruptly in the sequence of second, third and first parities, with significant variation (p < 0.05) in both conditions and techniques of mating.DO was affected by parity number (p < 0.01) with the highest DO in the first parity than in the second and third parities in months.In a similar way, CI was prone to the impacts of parity number and found a highly significant effect (p < 0.01) between parity number and CI of indigenous dairy cows in the study area.

TA B L E 9
Leading constraints of dairy production in study area.

General information of households
The higher male family head recorded for current study was friendly with Wondatir and Mekasha (2014), who reported 86.7% and 13.3% male-and female-headed households in the northern highland area.
However, current study result for a male-headed household was higher than Bekele et al. (2015) and Jobir and Yohannes (2021)  The family size of household was higher than the estimated national family size of 4.6 family members in Ethiopia and the world's average of 4.0 family size per household (WPDS, 2020).Friendly result was reported by Haile et al. (2012) and Misganu ( 2019), having 7.13 ± 0.24 and 7.34 family sizes, respectively.Abebe et al. ( 2021) also reported that 6.42 ± 2.28 and 6.18 ± 2.17 in urban and peri-urban dairy production systems, respectively, which was lower than current study result.
The life expectancy of indigenous dairy producers in study area was higher than national report of 65.5 years (The World Bank, 2018) and 67.07 years (ELE, 2021).Most probably, it was due to the less consumption of fabricated food which can predispose for obesity linked diseases and the presence of enough oxygen supply in rural areas enhancing erythropoiesis to maintain cells to live longer (Pyrkov et al., 2021 The households in the current study were proportionally educated than 73.6% and 64% illiterates in trans-human and sedentary production system in Enderta district (Tsadikan. 2012).In addition, it was better than illiterate 53.3%, primary school 36.7%,secondary school 6.7% and higher 3.3% in Yabello (Nurye Gebeyehu, 2017).Better educated households were reported by Belay and Janssens (2014), in Jimma urban dairy production system.Generally, dairy farmers need to get more education and extension service for efficient dairy cow production in the country as stated by Gwandu et al. (2018) in Tanzania.

Cattle population and land holding capacity
The current result recorded on cattle population was a little bit disagreed with the report of Fissha and Deng (2021) cows 4.75 ± 0.19, heifers 1.76 ± 0.13, bulls 1.68 ± 0.11 and calves 1.65 ± 0.07 and steers 1.07 ± 0.09 in lowland parts of Ethiopia.Abebe et al. (2021) also reported average dairy cow was 4.48 ± 1.85, heifers 1.89 ± 1.0 and 1.66 ± 0.47 bulls.The number dairy cow per household was higher than 1.04 ± 0.89 the value reported by Leyla (2016) at the Agarfa district.However, lower cattle population as calves 1.28 ± 0.04, heifer 1.39 ± 0.04, bull 1.35 ± 0.05 and lactating dairy cow 1.25 ± 0.04 were reported in Jimma zone dairy producers (Misganu, 2019).Dairy production system, the prevalence of epidemic and endemic diseases, accessibility of land, purpose of production and agro-ecological factors were responsible for livestock and dairy cow population variation (Fissha and Deng, 2021;Abebe et al., 2021).
The land holding capacity of households reported in current study was higher than previous South Nation Nationality and Peoples Region (SNNPR) (0.49 ha), Oromia region (1.15 ha) and 1.09 ha of Amhara region (DMoFA, 2020).It could be an element within the range of 1.5-4 ha in the Gambella region (Yaynshet et al., 2010).Gatwech (2012) reported 3.0 and 2.18 ha in urban and mixed crop-livestock production systems in the same region.Extremely low 0.0067 and 1.46 ha of land was reported in urban and peri-urban production systems, respectively (Misganaw et al., 2021).

Breeding objectives
The breeding objectives of dairy producers in the study area agree with the report of Fissha and Deng (2021), who ranked milk first, meat second, asset third and dowry fourth in a mixed dairy production system.Fantahun and Admasu (2017) revealed food security, living assets, nutrition, economic sources, sociocultural merit and employment as friendly results for the current study.Kefena et al. (2011) reported that milk production, the sustainability of the herd and draft purposes were high rented objectives.Production performances, income generation, savings accounts, aesthetics, and dowry were appealing objectives as friendly report for the current study result (Hirwa et al., 2017).Traction power, food sources, economy source, employment and sociocultural functions were reported by disagreement with the current study result (Ledetu, 2019).

Breeding practices
In order to boost the production of milk and milk products and to meet the growing demand for these goods, it is essential that breeding practices be acceptable.This will ensure the long-term viability of the dairy industry (Kemer et al., 2021).The breeding practices of farmers in the study area were agreeable with the report of Gondadaw et al. (2015) who conducted study on indigenous dairy cattle in Northern Amhara.
Similarly, Gebremichael (2015) and Gebeyew et al. (2016) reported natural mating followed by AI in the Tigray region and Dawa Chefa district, respectively.Asrat et al. (2015) reported agreeable result in the Wolaita Sodo zone.Disobediently, Abebe et al. (2021) and Demissu et al. (2014) reported that natural mating was less preferred than AI.As it was reported by Kiros (2019), dairy farmers in the study area have remained loyal to natural mating because breeding bulls are accessible and adopted problem, semen is limited, conception failures and higher NSPC in AI due to incorrect heat detection, too early or too late insemination, dystocia, foetal oversize and technician incompatibility with reproductive technology.

Oestrus synchronization practices and its efficiency on dairy cow
The result reported on the efficiency of oestrus synchronization in the current study is similar to that reported by Bainesagn (2015) who reported 72.3% of the oestrus rate in the West Shoa Zone, Oromia Region.Disobediently, Debir (2016) in Sidama and Samuel et al. (2015) in West Gojjam reported 90% and 88.9% oestrus, respectively.Studies in Awassa Dale milk shed by Girmay et al. (2015) and around Wukrokilte Awulaelo district indicated that the rate of oestrus response in a single injection of prostaglandin protocol at the farmer level was 91.3%.Wubneh et al. (2021) reported 91.2% for OSMAI in Ari district.CR and the fruitfulness of massive synchronization in the study area are comparable with Wubneh et al. (2021) for indigenous breeds in the Ari district with 11.02% CR.On the other hand, Fantahun and Admasu (2017) observed 24.69% pregnancy rate in the Mizan Aman area of South West Ethiopia.Similarly, Azage et al. (2015) reported an average CR of 27.1% at the national and 33.3% at regional level (SNNPR).Similarly, findings of Samuel et al. (2015) reported 70.4%, 78.2% and 71.5% of CR for hormone-treated Holstein-Friesian, Jersey crosses and local cows/heifers in the Amhara region.Linearly, Detalem (2015) reported CRs of Holstein-Friesian, Begait local and non-descript local cows/heifers in the Tigray region were 38.4%, 39.7% and 37.7%, respectively.According to Wubneh et al. (2021), the main reasons for failure and a low pregnancy rate include improper timing of insemination, a failure to identify oestrus in time, poor feeding management, the skill of the producers and the inseminator, quality semen and improper handling.

Effects of parity number of the dam and semen breed on OSMAI PR
The effect of parity number and artificially inseminated cows of the current study was contrary to reports of Samuel et al. (2015) who revealed an increasing trend of pregnancy rate as the parity of cows increased.However, it was in line with the findings by Bainesagn (2015) and Debir (2016).The findings of Yeshimebet et al. (2017) in the North Shoa Zone showed that high pregnancy rates were obtained in the double injection of PGF2α treatment (63.1%) than in animals treated with one shot protocol 55.8% (p < 0.05).Analogously, reasons for the failure of the OSMAI campaign in Oromia, Amhara, Tigray and SNNP regions were technician inefficiency, poor quality of semen, feed problems, an inappropriate season of AI and low awareness of farmers (Tegegne et al., 2016).However, an agreeable result was reported by Misganaw (2019), from the Jimma zone with current study.
Contrarily, the current study result was shorter than 3.933 years of Fogera breed (Damitie et al., 2015).Similarly, 4.21 years of indigenous breed around lowland of Ethiopia (Fissha and Deng, 2021), Ogaden breed having 4.07 years (Kassahun et al., 2015) and 3.445 ± 1.020 years for local breed in Siltie zone (Bayesa & Eyob, 2021) and 53 months (Guta, 2021).The heifer's reproductive and productive activities begin with the AFS signals, which also have an impact on the female's reproductive and productive life span through their impact on her lifetime calf crop.Due to the cow's extended, non-lactating, unproductive phase over several months, a significant delay in reaching sexual maturity may result in a significant economic loss (Tiruneh & Taddie, 2016).
IOI was equivalent to the result of 23 days reported by Blavy et al. (2018).Remnant et al. (2018) reported 28 days, which is more longer time, and Greenham et al. (2019) revealed IOI can be prolonged from 11 to 31 days within its range of the current findings.The result of NSPC of dairy cows in current study was larger than Barka breed, Holstein Friesian and their ¾ cross with Fogera breed cow with 1.11, 1.4 and 1.3, respectively, in the central highland of Ethiopia (Adisu & Zewdu, 2021).Contrarily, Ayeneshet et al. (2018) stated 1.68 ± 0.60 NSPC.In its analogous result, numbers of services per conception vary with the breed and 1.3-1.5 in exotic breeds and 1.4-2.8 in indigenous dairy cow was reported (Guta, 2021).
AFC for indigenous dairy cow of the present study was longer than national indigenous cow AFC of 4.417 years (Galmessa & Fita, 2019).Zelalem et al. (2011) reported B. indicus heifers reach puberty at older ages than B. taurus heifers HF and Borana crossbred was obtained at 34.6,33.7, 33.3 and 33.96 months in 50% (F1), 75% (F2), 87.5% (F3)and ≥93.75% (F4) blood levels, respectively.The findings were shorter than Kassahun et al. (2015) who reported 4.99 years of AFC for the Ogaden breed.The difference in the nutritional condition and management practices for dairy cows may account for the AFC variation (Kemer et al., 2021).According to studies of Gebreyohannes et al. (2019), extended AFC leads in high milk yields during the first lactation but lower lifetime output due to fewer calves being born.
DO recorded for indigenous dairy cow was comparatively longer than 2.53 months for Pure HF and pure Boran (Zelalem et al., 2011).
However, the result was shorter than 4.53 months of cross 7/8 Friesian and 1/8 Boran, 4.3 months for cross of ¾ Friesian and ¼Boran (Mengistu et al., 2016).Contrarily, Ayeneshet et al. (2018) reported 9.72 ± 0.40 months.VWP was unimaginative for cows not only in the study area but also in 37 identified breeds throughout the country (DAGRIS, 2017).DOs have an impact on lifetime productivity, generation times and annual genetic gain (Tadesse, 2006).CI of dairy cow in the present study was similar to the value of 1.50 year reported by Shiferaw (2006) for the Kereyu breed.But the findings were longer than 1.219 year of the Arsi breed (Kgaudi et al., 2018), and 1.15 year of the Friesian breed (Mengistu et al., 2016).Disobediently, the result of this study was better than extreme edges 4.51 years Begait breed (Mezgebe et al., 2017), 2.16 years of the Horro breed (Kassahun et al., 2015) and 2.08 years of average indigenous Cattle breed at national level (Ulfina & Lemma, 2019) and 18.38 ± 1.05 months for local cow in Wollo (Demeke, 2020).Guta (2021) reported CIs of zebu breeds usually vary from 12.2 to 26.6 months within the range of the result of current study result lays.The extended CI may be caused by the dam's age, genetics, the availability of food and the calving season (Ayalew and Asefa, 2013).The result of age at puberty of bull present study was higher than the value of 27.3 months for crossbreed reported and 42.2 months for local breed bull to attain full maturity.
Another factor that hinders the development of favourable conditions for puberty is disease (Hassan et al., 2020) (2012) 6.46 ± 0.13 for Horro breed, Chali (2014) 7.0 ± 0.2 for Arsi breed.Similarly, current study showed a higher calf yield than three to four calves of average indigenous cow at national level (Galmessa & Fita, 2019).Contrarily, Demeke (2020) reported 9.59 ± 0.49 calves of the local breed of dairy cow in Wollo which was far away from the result of current study.
The total life span (the longevity of life to stay alive on this planet of the earth) reported in present study was found in the range of 11-13 years at national level reported by Galmessa and Fita (2019).Comparably, Solomon et al. (2011) reported 12.7 for Boran breed dairy cows.
Higher age was declared by Agere et al. (2012) reported for Horro 13.67 ± 0.31 years, Demeke (2020) 16.21 ± 0.27 and 14.07 ± 0.23 years for indigenous cow and with their crosses, respectively.Contrarily, Damitie et al. (2015) reported 4.94 ± 0.17 for Fogera breed, and Teweldemedhn (2016) reported 11.0 ± 0.8 for Begait breed dairy cow lower than current study result.Age at puberty, first calving age, and CI all affect a cow's lifetime production, as do the cow's genetic make-up, health state and management and feeding practices (Legesse, 2016).

4.8
Effects of season of the year and parity number on reproductive performances Similar results were reported by Guta (2021) on the effect of the season of the year and parity number for NSPC, CI and DO and in all conditions, the variation was highly significant.Similarly, Anwar et al. (2017) reported that the season of calving has significant impact on reproduction performances of dairy cows.This was due to any environmental hardship and inaccessibility of feeds and health cares for dairy cow depressing performance capacities.Similarly, Kiros (2019) reported a significant effect of parity on NSPC and other reproduction performances.Furthermore, Ayalew and Asefa (2013) reported that factors associated with negative energy balance caused from malnutrition and feed scarcity have been considered causes of reproductive failure, lower CRs, longer CIs and an increased incidence of silent heat.
NSC might be lower or greater depending on the need for accurate and prompt heat detection and insemination (Gebreyohannes et al., 2019).

Constraints of dairy production in study area
The major constraints of dairy production in the study area agreeably with the report of Fissha and Deng (2021) who reported major constraints, such as poor genetics, diseases, feed and water shortage, scarcity of services and clinics were hindering factors for pastoral and mixed crop dairy production system.Constraints can vary based on agro-ecology, management factors and production system.Shortage of feed (43%), health problem (37%) and water security (20%) were major challenges affecting dairy cattle production and productivity in Abaya Woreda (Jobir & Yohannes, 2021).Similarly, the shortage of land, high feed price, feed shortage, disease problems and market fluctuations were the main constraints found at 84.8%, 81.8%, 75.75%, 69.69%, and 62.12%, respectively, in north western Ethiopia (Abebe et al., 2021).Haile et al. (2012) reported prioritized constraints were shortage of feed, limited space for proper housing and waste disposal and disease incidence in Hawasa.Odero-Waitituh (2017) for Kenya and Gillah et al. (2012) for tropical dairy production reported that the shortage of feed was the leading constraint.To enhance the dairy sector in study area, constraints must be mitigated (Lokuruka, 2016) and appropriate interventions must be sought by government, non-government and any concerned actors (Baliyan & Gosalamang, 2016).As friendly result, Hirwa et al. (2017) reported poor health, old age, infertility, high calf mortality, slow growth, small offspring, to avoid inbreeding, bad conformation, unfavourable colour and bad body condition.Similarly, disease, low milk yield, ageing, injury and infertility were leading factors for culling (Idesa & Aman, 2021).

CONCLUSIONS
The current study revealed that household family size was above the national and international estimated averages.The breeding practices were predominantly natural-controlled mating, followed by natural- records of AI centres and veterinary clinics for 5 consecutive years from 2017 to 2021.After rectal examination, a single shot of 5 mL of PGF2α was administered intramuscularly to those cows possessing corpus luteum and not pregnant cows.A treated cow expresses oestrus symptoms for 3-5 days.Dairy cows or heifers used for hormonal synchronization are classically selected based on their pedigree anamnesis, body conditions and body size (CWLFRDO, 2021; GWL-FRDO, 2021 . B. indicus (indigenous cattle) in the tropics and subtropics are thought to reach puberty between the ages of 16 and 40 months (Tiruneh & Taddie, 2016).Calves harvested during the complete reproductive life span of cow from the onset of AFC to the beginning of menopause stage (manifested by complete cease of reproductive capacity) were comparable with Solomon et al. (2011) reported 7.3 for Boran breed and Teweldemedhn (2016) reported 7 ± 1 for Begait breed indigenous dairy cows.Disobediently, Guta (2021) reported three to four live calf crops, Damitie et al. (2015) reported 4.94 ± 0.17 for Fogera, Agere et al.
uncontrolled, and AI in descending order.Breeding objectives were for input function, output function, sociocultural and economic function and for assets and security function in descending order.The study revealed that overall reproduction performances of indigenous dairy cows are very low due to technical and non-technical constraints.Even though indigenous dairy cows were the powerhouse of opportunities, welfare abandonment and poor management besides constraints made them deprived of production and reproduction aptitudes under ideal standards.AUTHOR CONTRIBUTIONSYakob Asfaw contributed to designing the study, performing the study, analysing and interpreting the data and writing the manuscript.Regasa Begna Roba contributed to designing the study, supervising the study and writing the manuscript.Worku Masho Bedane contributed to designing the study, supervising the study and writing the manuscript.
General household characteristics of study area.

Table 5
Objectives of dairy cow breeding.Effects of parity number of the dam and semen breed on oestrus synchronization and mass artificial insemination pregnancy rate (OSMAI PR).
(Sharifuzzaman et al., 2015) of oestrus synchronization in indigenous dairy cows in the study area.The results revealed that overall oestrus response rate to a single injection of PGF2α (synchromate) was 70.5%.However, there were variations in oestrus responseTA B L E 3Note: Asset, acts as a kind of savings account and durable form of storing wealth; Buffer, for astonishing jeopardies to generate immediate income restoration.TA B L E 4Breeding practices of indigenous dairy cow in study area.Gesha (N = 192)Chena (N = 192)Note: CR = conceived/inseminated(Sharifuzzaman et al., 2015); where CR stands for conception rate.Abbreviation: ERR, oestrus response rate.TA B L E 6

TA B L E 7
Effects of district on reproductive performances of dairy cow.Season and parity effects on reproductive performances of indigenous dairy cow in study area.
Abbreviations: AI, artificial insemination; CI, calving interval; DO, days open; IOI, interoestrus interval; NM, natural mating; NSPC, number of services per conception; SE, standard error.*p < 0.05.**p < 0.01.between districts.The total life span (the longevity of life to stay as alive on this planet) reported in present study was 11.94 ± 0.26 years, with highly significant variation (p < 0.01) between districts.

Table 9
discusses the major constraints on dairy cattle production in the study area.For the keenest clarity, constraints are categorized into two categories: technical and non-technical challenges.Top prioritized constraints in study area were poor genetic makeup, prevalence of diseases, feed scarcity and water scarcity from the technical side.Moreover, the lack of infrastructure (roads, electricity, pure water, clinics and services), the lack of access and the high cost of improved dairy heifers/cows and the lack of research and information exchange between the government and NGOs were predominating non-technical delayers.According to FGD, key informants and survey results, reasons for culling dairy cows from herds in study area were low reproduction capacities and production performances, non-infectious diseases like fractures, disabilities and genetic defects like poor pedigree inheritance, sterility, the lack of sexual libido, anoestrus, anatomical defects of the reproduction tract causing excessive dystocia and pendulous udder due to loose median suspensory ligament.
and Agere et al. (2012) reported 42 ± 6, 43.32 ± 0.96 and 46.56 ± 0.06 months for Begait, Mursi and Horro breed bulls, respectively, to attain age at maturity.Similarly, ages at puberty of bulls were 36.7 and 29.3 months for local and crossbred, respectively, reported by indicating types of breed and agro-ecology significantly affect age at bull maturity