Comparison and economic analysis of artificial insemination and natural service practices in Murrah buffalo: A comprehensive field study

1. Introduction

              The livestock sector contributes significantly to the Indian national economy, and its growth rate is expanding. This sector generated 5.21 % of the total Gross Value Added, which is around 28.36 % of the agriculture and allied sector GVA [1]. In the economics of rearing dairy animals, reproduction is a significant factor. Despite having 192.49 million cattle and 109.85 million buffaloes [2], average milk productivity is still very low. One of the primary issues is indigenous cattle’s low production potential, because the average milk production (per animal per day) of indigenous cattle is 3.34 kg/day, whereas the average yield of crossbred cattle is 7.22 kg/day [1]. Artificial insemination is a proven technology for improving milk production and productivity of bovines. Artificial insemination (AI) can be extremely beneficial in a country like India, where the availability of good males is few and has become a major impediment to the improvement of dairy cows. The function of AI is critical not just for bettering the livestock sector’s growth, but also for generating adequate seed stocks of enhanced germplasm to keep livestock production growing. AI coverage in the country is now restricted to 30% of breedable bovines, with 70% of breedable animals being naturally served mainly by scrub bulls of unknown genetic potential [1]. Compared to natural services, artificial insemination has many benefits, including the eradication of venereal diseases, more precise dry-off dates, decreased incidence of injury, and increased safety for farm workers, and a greater role in genetic improvement leading to daughters that are more productive and profitable. It is also the cheapest and most suitable method for improving genetics [3]. Most importantly, AI does away with the burden of raising bulls. The only issue with AI in buffaloes is that they frequently don’t show many overt signs of heat. Dairy farmers commonly believe that NS is less expensive because of its shorter service period or days open and simple solution to estrus detection issues. Several researchers have also concluded that NS has a benefit in terms of the length of the calving interval, confirming the common farmer perception [4–7]. Therefore, any additional “days-open or service period” costs must be included in the economic comparison of the breeding methods. There aren’t any studies available regarding economic comparisons between NS and AI systems in buffaloes. In order for these comparisons between AI and NS to be valid and acceptable to dairy farmers, they must take into account actual farm circumstances, procedures, and economics. This study’s objective was to evaluate the economic viability of both natural service and artificial insemination methods.

• Materials and methods

2.1. Selection of villages

A multistage sampling technique was used for the selection of zone, districts and respondents. The district of Muzaffarnagar in western Uttar Pradesh was purposely selected for this experiment. As the dairy farmers received semen delivery services from the ICAR-National Dairy Research Institute’s center. This zone is renowned as “The Sugar Bowl of India” since the region’s economy is mostly dependent on agriculture; sugarcane. Geographically, the district is located at 29⁰47’N latitude, 77⁰71’E longitude and 233m elevation. Four villages were chosen at random.

2.2. Data exploration and editing

Field visits were undertaken to gather data on 161 buffaloes from the farm households using well-structured, pre-tested survey schedules in the year 2021 (January to May). Primary data was collected from farming households about their socioeconomic background, farming practices, breeding system, cost of mating, productive parameters (milk yield, lactation length), reproductive parameters (calving interval, service period, service per conception), milk prices, feed intake, cost of feed and fodder, and the cost of rearing for buffalo bulls. Dairy farmers in the study area hardly ever kept any farming records, they used their recollections to answer our queries. To verify the information, they provided and in the event of any discrepancies, more questions were asked.  Additionally, complete data clean-up was carried out to eliminate blatantly incorrect replies. If any discrepancies were found, the responder was called to make an information correction. Some of the data were missing or not relevant, more specifically related to the cost of rearing buffalo bulls.

2.3. Data management and analysis

During data analysis. the cell for missing data or information that is not relevant was left empty (i.e., not recorded as zero) in order to prevent errors in the statistical analysis from counting the cells. The collected data were scored, compiled, and tabulated using Microsoft Excel, 2019 and analyzed systematically commensurate with the objectives of the study using statistical software SPSS 22 (SPSS version 22, SPSS Inc. Chicago, Illinois). The t-test was used to evaluate continuous variables. Statistical significance was defined as a P-value of 0.05 or less. Frequency and percentage calculations were made for categorical data, whereas mean values were computed for continuous variables. The economic losses were analyzed descriptively.

2.3.1. Survival analysis: The calving-to-conception interval, also known as the days open or service period, is the response variable of interest. In lactating buffaloes, conception is often examined as a binary variable based on whether a buffalo becomes pregnant after insemination after calving. The continuity of the conception process and the precise timing of pregnancy or “failure” are ignored when conception is seen as a binary attribute, which sees pregnancy as having happened during a certain time period. For assessing days open as time intervals in buffaloes, an analytical tool such as survival analysis is available that offers various advantages over conventional regression procedures [8,9]. The key benefit of using survival analysis is that it can preserve data from buffaloes who were not pregnant when data were collected and make effective use of all the information at hand.

Using SPSS software, the Kaplan-Meier model of the survival analysis approach was used to calculate the median days open for buffaloes who did conceive.  Kaplan-Meier (KM) is a graphical representation method. In clinical studies or community trials, the intervention effect (here, AI or NS) is evaluated over time by counting the participants (here, buffaloes) who survived (here not conceived). To identify events (in this case, conception) and censoring (in this case, not conceived at the time of data collection), curves are utilized in the Kaplan-Meier estimate [10].

A statistical hypothesis test known as the log-rank test can be used to compare two survival curves [11]. The log-rank test was used to examine the breeding system that was thought to affect days open. The null hypothesis is that there is no difference between the two groups (here, AI and NS) in the likelihood of an event (here, conception) at any given time point [12]. When the likelihood of conception is consistently higher for one group than another, the log-rank test is most likely to identify a difference between the groups.

2.4. Calculation of natural service costs

Data on 11 Murrah buffalo bulls were collected. All buffalo bulls utilized for natural service were bred in the farmer’s herd. None of the bulls were given TB, JD, or Brucellosis screenings. marginal (≤ 3 animals) and small farmers (4-10 animals) did not raise bulls. Only medium-sized farmers (> 10 animals) retained bulls for natural service and used them for draught purposes in sugarcane fields. These bulls were also utilized to service the buffaloes owned by other dairy producers in the community. Overall, no bull produced more than 30 calves per year in any of the study villages, and this was thought to be the typical performance for NS buffalo bulls. Farmers’ complaints of low bull fertility, libido, and health issues (lameness) were extremely uncommon and weren’t taken into account in this study. All expenses incurred on rearing bulls such as feeding, labour, health, equipment and other miscellaneous costs were recorded at the farmer’s doorstep. All costs related to rearing buffalo bulls were projected for a year. All the costs were expressed in Indian rupees (INR)

• Fixed cost: This covers annual ownership cost and risk of bull loss. The average annual decrease in the bull’s value is represented by the annual ownership cost.

Annual ownership cost = Value of bull ………………………………….………….……. (1)

                                             Useful life

The risk of bull loss resulting from a bull being disabled owing to sickness, injury, infertility, etc. is calculated as follows:

Risk of bull loss = Value of bull × Probability of occurring such loss…………….….…. (2)

Housing costs were not taken into account in the study since all of the bulls were raised in an open field without a shed.

• Variable cost: These expenses include the cost of feed, labor, veterinary care, and other incidentals.

Feed cost: It refers to the amount spent on the green fodder, dried fodder, and concentrate used to feed the bulls. It was calculated by multiplying the amount of feed and fodder consumed by bulls with the relevant prevailing prices in the research region. Common feeds available in study area were wheat straw, sugarcane tops, berseem, oats, cottonseed cake, mustard cake, wheat bran, gram chunni, soybean meal etc.

Cost of labour: Family and paid labor were both involved in bull rearing. The inferred value for family labour was calculated using the average wage for casual labour in the studied area.

Veterinary cost: This includes the expense of vaccinations, medications, and other services rendered by veterinarians.

Miscellaneous costs: Repair expenses, utility costs, bucket and rope costs, etc.

• Total direct cost: By summing each component contained in fixed cost and variable costs, the total direct cost of NS was calculated.

2.5 Calculation of revenue generated when bulls used for draught purposes

Buffaloes can reportedly draw up to six times their body weight, but they typically only lift 1.5 to 2.0 tonnes (three to four times their weight). When estimating the economic gains of draught animal power, we contrasted it with the work done by a tractor. The majority of farmers in the research region didn’t own any tractors; instead, they rented them from others on a per-acre basis. Two buffalo bulls can complete an equivalent amount of labor i.e., plowing 1 acre in a single day. However, using bulls to plough is a labor-intensive activity, thus labor costs must be included in the calculation. So, the following formula was used to determine the economic gains of using draught buffalo bull:

VDAP = (TRAC – LC) × WD………………………………………………………….…. (3)

                             2

Where VDAP (INR/buffalo bull) is the value gained from draught animal power, TRAC is the cost of renting a tractor for plowing one acre of land, LC is the labour cost of a day and WD is the total number of working days in a year.

2.6 Calculation of direct artificial insemination costs

The cost of semen straw and the technician’s fee were added together and then multiplied by the service per conception of buffaloes bred with AI. The costs related to hormone treatments were excluded from this study since local dairy farmers seldom ever use them. The following equation was used for the calculation of the direct cost of AI:

DAI = (CSS + TF) × SPC_AI………….……..………………………………………….…. (4)

Where DAI is the direct cost of AI (INR/buffalo), CSS is the cost of semen straw, TF is the technician’s fee, and SPC_AI is service per conception in case of artificial insemination (AI).

2.7 Calculation of indirect AI cost (losses due to extended calving interval)

A straightforward and considerate methodology should be used to evaluate the financial impacts of extended days open in a dairy herd. Using the approach of  Cattaneo et al. (2015); Kim and Jeong (2019), with certain adjustments in the context of our study, the total cost of the prolonged calving interval caused by the delayed service period or days open in case of artificially inseminated buffaloes was determined [13,14]. In the approach being employed, the following factors are taken into account:  Loss of milk production owing to extended days open (VML); additional labor cost (ALC); additional feeding cost (AFC) and value of calf loss (VCL). The sum of all these four items represents the financial losses due to extended days open in artificially inseminated buffaloes, which is expressed in Indian rupees (INR) per buffalo.

2.7.1. Value of milk loss: While an increase in the days open lengthens the time during which milk is produced, however, the overall milk production decreases as a result of the delay in the start of the following lactation [15]. The cost of milk loss is influenced by mean milk yield, number of extended days open, and milk price. The milk price was determined in accordance with the farmers’ information on local per-litre milk prices. Following is a calculation of the value of milk loss as a result of extended days open in the case of artificially inseminated buffaloes.

VML = MMY x EDO x MP ………………………………………………………………. (5)

Where VML is the value of milk loss (INR/buffalo), MMY is mean milk yield (kg/buffalo/day), EDO is the extended number of days open and MP is the milk price

2.7.2. Added feeding cost: Feed cost is calculated for each feeding regime employed in the study area. Per day cost of feed was estimated by multiplying the consumption amount of each feed ingredient such as dry fodder, green fodder, and concentrate their individual costs in the research region and adding the results to get the total cost. The additional feed cost as a result of the delayed conception was calculated as follows:

AFC = PDFC × EDO …………………………………………………….…………….…. (6)

Where AFC is added feed Cost (INR/buffalo), PDFC is per day feed cost per buffalo and EDO is the extended number of days open.

2.7.3. Added labour costs: It is common knowledge that dairy farming requires a lot of labour. The product of the daily labor cost per buffalo and the number of days delayed is the additional labour cost per cow per day. Man hour per buffalo per day is 30 minutes, and the cost of this amount of work is estimated using the monthly wages of casual workers.

ALC = PDLC × DD…………………………………………………..……………………. (7)

Where ALC is added labour cost (INR/buffalo), PDLC is per day labor cost per buffalo and EDO is the extended number of days open.

2.7.4. Value of Calf Loss:A calf is the most significant reward that dairy producers anticipate from animal husbandry. The market price of the calf (average market price of male and female calf) divided by desired calving interval is used to determine the cost associated with the decrease in the number of calves as a result of the longer calving interval caused by delayed successful conception. When conception is delayed, the value of calf loss is as follows:

VCL = MPC ×EDO…………………………………………………………………….…. (8)

             DCI

Where VCL is the value of calf loss (INR/buffalo), MPC is the market price of the calf, DCI is desired calving interval, and EDO is the extended number of days open.

2.7.5. Total loss due to extended days open in artificially inseminated buffaloes: The total loss (TL) is the total of the above-mentioned expenses as determined by:

TL = ML + AFC + ALC + VCL………………………………………………..………… (9)

2.8 Calculation of additional milk needed to be produced by AI daughters

For easy comprehension of dairy farmers, prospective additional expenses tied to AI were defined as the increased amount of milk that AI daughters must produce to compensate for the losses.  The calculation below was used to determine how much extra milk was needed from AI daughters:

Additional milk = (Net cost of NS per pregnancy – Total cost of AI)………………… (10)

                                            Milk price over feed cost

It was considered that a buffalo would produce 2.5 kg milk for every extra kg of concentrate.

2.7.2. Results

3.1 Reproductive Performance of buffaloes

The number of services per conception reflects the efficient use of time, quality semen, and the animal’s productive life. It is greatly influenced by the season in buffaloes [16]. There was a significant (P<0.01) increase in the average number of services per conception of artificially inseminated buffaloes as compared to the naturally bred buffaloes (Table 1).

According to the survival analysis, 34.8% of the buffaloes were censored since they did not conceive until the end of the study period. Compared to 164 days open for buffaloes exposed to the artificial insemination (AI) breeding system, the mean days open for natural service (NS) exposure was 140 days. Thus, the number of days open significantly (P<0.01) increased by 24 days (Table 1) when buffaloes were bred with artificial insemination. The survival function curve (Figure 1) shows the relationship between the breeding system and the number of days open. The plot demonstrates that the survival curve for buffaloes bred with natural service is higher than the survival curves for buffaloes bred with an artificial insemination breeding system. This indicates that buffaloes using a natural breeding system conceived earlier than buffaloes exposed to artificial insemination. The biggest disparities appeared only after 120 days.

Table 1:  Reproductive performance of Murrah buffaloes in different breeding systems.

Particular	Natural Service (Mean±SE)	Artificial insemination (Mean±SE)	p-value
Service per conception (number)	1.45±0.11	2.13±0.09	0.001
Days open (Days)	164.93±2.69	140.48±2.25	0.001

Figure 1. Survival curves for the days open in buffaloes that did or did not conceive during study period.

3.2 Calculation of costs and revenue generated by bull rearing in the NS breeding system

A partial budget analysis of rearing Murrah buffalo bull is given in table 2. In the calculation of annual ownership cost, the worth of the bull is estimated at 40 months of age at which buffalo bull becomes capable of labour, which is also the average age at which buffalo bulls are put to service [17]. The productive life of buffalo bull is thought to be 8 years in typical Indian farming conditions. The risk of bull loss is calculated at the 20% probability of the bull being incapacitated owing to sickness, injury, infertility or theft. The total fixed cost was estimated to be 18762 INR, which is around 21% of the total direct cost of rearing a Murrah buffalo bull for 1 year. An estimated 56575 INR, or around 65% of the total direct cost, is the cost of feeding a bull.

The draught animal power that bulls offer was often used by farmers as justification for bull rearing. Therefore, we took into account the revenue that bulls made through working in sugarcane or paddy fields.Cropping season in the study area typically lasts 60 days every year i.e., around 30 days during Kharif and 30 days during Rabi. Buffalo bulls were only utilized for cultivation throughout during 60-day period for six hours each day. We assumed there are a total of 100 working days in a year for all purposes (cultivation and transportation). So, the revenue generated from working buffalo bull was calculated for the 100 days in a calendar year. On average, hiring a tractor to plow one acre of land for once costs roughly around 800 INR in the study area. So, the revenue generated was about 26700 INR. As a result, the total cost of rearing a bull for a year came to 59173 INR.

Table 2: Partial budget analysis of rearing a Murrah buffalo bull for a year.

	Type of cost	Amount (INR)
A	Fixed cost:
i	Annual ownership cost [62543 INR / 10 years]	6254
ii	Risk of bull loss [62543 INR × 0.2]	12508
B	Variable cost:
iv	Cost of green fodder [20Kg/buffalo bull/day × 365 days @2 INR/Kg]	14600
v	Cost of dry fodder [5Kg/buffalo bull/day × 365 days @5 INR/Kg]	9125
vi	Cost of concentrate [3Kg/buffalo bull/day × 365 days @30 INR/Kg]	32850
vii	Labour cost (Hired and family labour)	8000
viii	Veterinary care	2000
ix	Miscellaneous	500
	Total direct cost	85837
C	Revenue:
x	Value of draught animal power [(800 INR-266 INR) / 2]× 100 days	26700
D	Net cost (Total direct cost – Revenue)	59137
E	Net cost per pragnency [59137 INR / 30]	1971

3.3 Calculation of direct and indirect cost of AI

The total cost of AI is depicted in Table 3. It costs 20 INR to purchase the frozen semen straw of the Murrah buffalo bull from the ICAR-NDRI centre in the study area. The AI technician charges an additional fee of about 150 INR. So, the total direct cost of AI was estimated to be 362 INR. The average milk production of buffaloes was revealed to be 7.2 kg, and milk loss was the main contributor to losses brought on by extended days open. The average per-day feeding cost in the study area was estimated to be 195 INR.  The optimal calving interval, which was taken into account when determining the value of calf loss, was 420 days [18]. Consequently, the total indirect cost of AI due to 24 days extension in days open was around 14124 INR or a loss of 588 INR per day.

Table 3. Total cost of AI due to direct and indirect cost

	Types of costs	Value (INR)
A	Direct cost of AI [(20 INR + 150 INR)× 2.13]	362
B	Indirect cost of AI (losses due to extended days open):
I	Value of milk loss (VML) [7.2kg × 24 × 50 INR]	8640
II	Added feeding cost (AFC) [195 INR × 24]	4680
III	Added labour cost (ALC) [22 INR × 24]	528
IV	Value of Calf loss (VCL) [(4835 INR / 420) × 24]	276
	Total cost of AI	14486

3.4 Amount of additional milk needed to offset the extra cost of AI

According to the data above, farmers lose around 12515 INR extra, when artificial insemination is used to breed buffaloes as opposed to natural service. To make up for this significant loss, AI daughters must perform better than NS daughters. In order to offset the higher expenses associated with utilizing AI, 338 kg more milk was required per lactation.

For the purpose of calculating the performance of NS and AI daughters born from the high genetic merit buffalo bull whose semen is supplied in the research region. We collected data from 16 AI and 16 NS daughters who were either in their first or second lactation. Farmers provided information on their peak milk yield, which was then multiplied by 200 to get their 305-day lactation yield [19]. It was revealed that when compared to NS daughters, the first lactation milk yield was improved by 525 kg, and the second lactation milk yield was better by 750 kg. While just 338 kg additional milk was required to compensate the losses due delayed successful conception. The rest of the milk assisted to the farmer’s economic profitability.

Figure 2. Lactation yield of AI vs. NS daughters

• DISCUSSION

When adopting artificial insemination (AI) or natural service (NS), dairy producers’ primary concerns revolve around the herd’s reproductive efficiency, which is crucial for their economic benefits. Higher services per conception are typically a sign of issues with poor fertility or problems in the breeding system employed, which have a detrimental effect on farm economics [20,21]. Artificially inseminated buffaloes have higher services per conception, which results in longer days open and fewer potential lactations over the buffalo’s lifespan and a reduction in the overall profitability of dairy farmers.

The efficacy of heat detection is the key environmental component that influences the average number of services per conception. Compared to cattle, buffaloes’ estrus signs are significantly less apparent. For instance, only around one-third of buffaloes in estrus may be identified by their homosexual behavior. Swollen vulva, mucous discharge, and increased frequency of urination are not considered to be reliable signs of estrus [22]. The peak of sexual activity in buffaloes is during the night hours after estrus begins in the late evening. The prevalence of silent estrus is greater in herds utilizing artificial insemination (AI) than those using natural services, which suggests that the concern might lie with heat detection rather than the animal itself [23]. That is the reason why dairy farmers in the study area used natural services only in the case of buffaloes, not for cows. The efficacy of insemination can be increased if heat detection is executed properly and the insemination procedure is carried out with successful tactics [24]. In the present study, The sub-optimal service per conception in artificially inseminated buffaloes may be attributed to poor heat detection, substandard inseminator skills, inappropriate straw handling, contamination of the reproductive tract, and other factors that contributed to the disparity in service per conception, indicating poor quality of AI services in the study area. The results of the present study conformed with the findings of Yadav and Chandel (2014), who reported that AI/conception in buffaloes was ranging from 3-4 AI/conception [25]. The buffalo owners should thus frequently monitor the buffaloes and be trained to recognize buffalo in estrus. Additionally, AI technicians should be properly trained to provide efficient AI services in order to enhance the conception rate and reduce economic loss.

            Buffaloes need to conceive between 120–140 days after calving to maintain a calving interval of 14–15 months and produce two calves every three years. The days open in naturally served buffaloes were about optimum whereas days open got extended by 24 days in the case of artificially inseminated buffaloes, which theoretically will lead to an increased calving interval. While, according to the reports of Tadesse et al. (2022), the mean calving to days open is extended by 45.04 days in cows that did not conceive at their first artificial insemination (AI) but did so at their second and third attempts [26]. This increase in calving interval due to delayed conception by AI is validated by many large-scale studies that reveal calving intervals of 13.6 vs. 14.1 months [5], 13.8 vs. 14.1 [4] and 13.0 vs. 13.7 [27] for NS and AI. The majority of the time, this gap due to late successful conception was less than one month. However, other researchers have found that AI performs as well as or better than NS [6,28], suggesting that the calving interval is primarily a management issue rather than a breeding system-related one.

Farmers frequently criticize the rising cost of production. But the majority of them undervalue or otherwise neglect the price of maintaining NS bulls on their farms.  After taking into account the revenue generated by the labor of buffalo bulls, the calculated annual net cost of rearing a bull came to be 59137 INR. The principal cost of bull rearing was attributed to feeding cost, which is in line with the reports of Valergakis (2000), according to whom Feed and depreciation account for 75% of the overall costs associated with maintaining NS bulls [27]. The results of the simulation study of Valergakis et al. (2007) on Greek dairy farms, revealed that NS bull maintenance expenses ranged from $1,820 (147601 INR)  to $2,111 (171201 INR) [7]. Our study used a bull-to-buffalo ratio of 1:30 since that represented the typical performance of an NS bull in the study region. In the same manner, Valergakis et al. (2007) reported that for farms with more than 30 cows, direct AI expenses were more than NS costs, and Extended calving interval due to the late successful conception of AI-bred cows added a significant undue burden [7]. 

One of the main arguments for using NS is the higher perceived AI costs compared with those of keeping herd bulls and additional costs resulting from extended days open because of poor heat detection and conception rates in buffaloes when using AI. Days open have frequently been utilized as a metric for a successful breeding system. Previous research has shown that extended days open have a significant negative effect on revenue. This is simply due to the increased maintenance costs of the animal and the sharp drop in pregnancy income as a partial revenue source [29]. Additionally, any pregnancy delay has a negative impact on milk production. Due to the prolonged time spent in late lactation and the higher milk SCC that is connected to this stage of lactation, cows with an extended calving interval suffer from greater milk losses [30,31].  In this study, only 18% of the net cost per pregnancy of NS was incurred directly by AI. The majority of the costs associated with AI came from the cost of extended days open, which was also driven by milk losses. Similarly, Diro et al. (2021) reported that milk loss accounts for more than 55% of the cost of extended days open as a result of the local zebu cows’ poor reproductive performance in Ethiopia [32].

In this study, the farmer loses an amount of 588 INR per buffalo for every extended day open. Similarly, Tadesse et al. (2022) reported that the dairy farmer in Ethiopia loses an average of 473.7 ETB (731 INR) per cow per day in additional expenses for cows that failed to conceive at their first AI but conceived by second and third service [26]. One US dollar (81 INR) is lost as a consequence of a longer calving interval for each additional day after the ideal calving interval in Nili-Ravi buffaloes in Pakistan [33]. According to research by Kim and Jeong (2019), the failure of the first service conception in Korea resulted in a total economic loss of $622.40 (50476 INR) per animal [14]. In another research, the profit was reduced by more than $205 (16625 INR) per cow in a year in Spanish dairy cattle that required three or more inseminations to conceive [34]. In his research on high-yielding cows, Esslemont et al. (2001) found that, when conception is delayed from 85 to 115 days post-calving, the net cost of one day of delay in conception is estimated to be £2.48(243 INR) [35]. Similarly, Kafi and Zibaei (2007) estimated that in Iranian dairy farms, the cost of extended days open tends to increase to 6.68$ (541.94) per day when conception is delayed from 85 to 100 days post-calving [15]. In another study on 1000 Holstein cows in California (USA), Comparing AI with NS, AI is around $10 (810 INR) cheaper per cow. Additionally, stochastic simulation revealed that 60% of the time, AI is less expensive than employing NS sires [28]. The effect of delayed conception on the animal’s calving interval was studied by Khan et al. (2008). According to the study, dairy buffaloes that conceived later in lactation saw a drop in financial returns of 24% to 27% compared to those who conceive earlier [36].

If the genetic gap between an AI bull and an NS bull is modest and the latter produces better herd genetics, it is unquestionably a worthwhile decision to keep NS bulls in villages. But that is not the case, ICAR-NDRI ensures that the semen given in the research region emanates from genetically superior sires as compared to bulls maintained for NS in field conditions. This is evident from the superior performance of AI daughters, which not only recovers the losses but also contributes significantly to the income of dairy farmers.

• Conclusion

An economic comparison of breeding systems (AI or NS) is influenced by a variety of factors. This study provides pieces of evidence of the monetary benefit of artificial insemination using semen of genetically superior bulls. Even under less-than-average management conditions, AI was more profitable than the best NS scenario. The field-level empirical analysis used in this work is essential for the comprehension of the farmers about the economic implications of artificial insemination.

Funding

This research was funded by ICAR – National Dairy Research Institute, Karnal, India.

Credit authorship contribution statement

Divyanshu Singh Tomar: Writing – original draft, Formal analysis, investigation & Visualization. S.S. Lathwal: Conceptualization, Resources, Supervision, Writing – review & editing. Pawan Singh: Methodology, Validation, Supervision, Writing – review & editing. Indu Devi: Writing – review & editing.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

            We gratefully acknowledge the ICAR-National Dairy Research Institute, Karnal, for its financial support and facilities in carrying out this research.

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