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Article

A Comparative Economic Analysis of Different Reproductive Management Strategies in Two Dairy Sheep Farms in Greece

by
Dimitra V. Liagka
1,2,3,*,
Antonis P. Politis
4,
Maria Spilioti
2,
Eleftherios Nellas
2,
Panagiotis Simitzis
3 and
Konstantinos Tsiboukas
2
1
Department of Animal Science, University of Thessaly, 41110 Larissa, Greece
2
Department of Agricultural Economics and Rural Development, Agricultural University of Athens, 11855 Athens, Greece
3
Department of Animal Science, Agricultural University of Athens, 11855 Athens, Greece
4
Veterinary Faculty, University of Thessaly, 43100 Karditsa, Greece
*
Author to whom correspondence should be addressed.
Agriculture 2025, 15(7), 719; https://doi.org/10.3390/agriculture15070719
Submission received: 12 February 2025 / Revised: 22 March 2025 / Accepted: 25 March 2025 / Published: 27 March 2025
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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Abstract

:
The aim of this study was the economic comparison of two equivalent sheep farms with different reproductive management systems. Financial data were selected from a farm that applied artificial insemination (AI) and from one that applied natural mating (NM). The main objective of the analysis was to estimate the cost of each farm’s products and then to calculate their economic indicators. The AI farm had higher production costs, as a result of higher labor and fixed capital costs. On the other hand, the invested capital for the equipment and buildings of the NM farm was lower. Furthermore, the invested livestock capital based on the genetic value of the animals was higher in the AI farm. The AI farm produced milk, replacement ewe lambs and replacement ram lambs as its primary products, whereas the NM farm produced only milk as its primary product. The production costs for milk were 0.08 EUR/kg lower in the AI farm compared with the NM farm. The AI farm had a higher gross revenue and net and gross profit, resulting from the higher genetic value of the AI farm’s livestock. As indicated, the breeding and sale of genetically improved animals can increase the financial results of a farm and offer alternative sources of income. In conclusion, AI results in more sustainable and economically efficient sheep farming. In this regard, training for farmers and governmental economic support could promote AI application. Finally, the fortification of farmer group initiatives that facilitate the trade of dairy sheep products can accelerate AI utilization in dairy sheep farms in Greece.

1. Introduction

Greece has number of sheep (7378.357 during 2022, [1]) which accounts for around 12.5% of the total animal population in Europe, occupying the 4th position amongst the European Union’s sheep flocks [2]. In contrast to northern Europe, sheep production in Greece is oriented in milk, being the only European country producing more ovine than bovine milk [3].
The intensification of sheep farming systems seems indispensable in order to increase productivity and thus improve the national economy and rural income [4,5,6]. During recent decades, new management techniques and approaches have developed in order to support the demand for high-quality and safe dairy products at a reasonable cost [7,8]. Reproductive management in sheep farming plays an important role in productivity and profitability by adjusting the lambing and milking period, increasing prolificacy, inducing early-onset reproductive maturity and implementing programs for genetic improvement [9]. It is widely known that the most effective tool for genetic improvement is the artificial insemination as it can boost production traits by the quick addition of important genes into a population [10]. Traits related to the milk yield, milk composition, udder morphology, somatic cell count and, at the same time, resistance to diseases like mastitis or scrapie can be ameliorated by AI insemination [8,10,11,12,13]. However various parameters associated with the management [14,15] of sperm and anatomical characteristics [16,17,18,19,20] can lead to a broad variance in AI success rates in sheep. This fact explains the low percentage of farms that apply this technique [21]. In a recent extensive countrywide investigation of reproductive management protocols in Greece, none of the farms reported the application of artificial insemination [22].
Advances in ram semen preservation and in management factors that affect female fertility can increase the success rate of AI [23,24]. However, farmers should be informed about the progress in this sector, in order to overcome their reluctance in applying AI. As farmers try to balance between the selection of profit and non-profit activities, in order to improve their economic sustainability [25], more studies regarding the financial effectiveness of different management practices should be carried out.
The aims of this study were, therefore, as follows: (a) the economic comparison of two dairy sheep farms with different reproductive management strategies in Greece and (b) to provide a step-by-step tool for the in-depth comparison of different strategies in farms, which has not been carried out so far, with the intention to fill the relevant gap in the existing literature.

2. Materials and Methods

2.1. Farms

Two dairy sheep farms were included in this study and a comparison was carried out between them. Both farms were located in the same district, in the prefecture of Achaia in the region of Western Greece. Also, both farms applied the intensive management system [26]. Lambs were removed from their dams on their second day of life and then fed for 40 days with lamb feed device. The ewes were machine-milked for a period of up to 8–10 months. In both farms, sheep were of Lacaune breed (imported breed). Similar vaccination and antiparasitic programs were followed in both farms, which were under the care of the same veterinarian. Feeding was carried out by using commercially produced feed. The total amount of milk produced in each of the two farms was similar: 153,000 L. However, in AI farm, artificial insemination was applied and in NM farm, only natural mating was applied.

2.2. Economic Definitions

An economic analysis was carried out on the two farms, starting with calculation of the fix capital or total fixed assets (the agricultural land and farm buildings and forest capital + buildings + machinery and equipment + breeding livestock, intangible assets and other non-current assets). The fixed capital is associated with land rent, amortization expenses, remuneration of fixed capital, maintenance and insurance of fixed capital. The variable capital or current assets are the non-breeding livestock + circulating capital (stocks of agricultural products + other circulating capital) and they are consumed when used.
The average invested capital is the value in EUR of the various categories of capital, determined for each financial year, and which has been invested in the farms to achieve their objectives. It is calculated as the half-sum of the value of capital at the beginning and at the end of the financial year. The average invested capital is used for the calculation of the cost of production of the farms’ products.
For the calculation of the financial results of each farm, the annual production expenses should be firstly determined. The annual production expenses can be classified as variable (feed, fuel, electricity cost, etc.) and fixed (land’s rent, labor cost, etc.) expenses. At the same time, all the production expenses can be categorized as explicit (direct costs) or implicit (expenditure that is not actually paid, e.g., rent of a personal property).
The calculation of financial results is based on specific mathematical formulas for calculation which are similar to the corresponding calculations in FADN and as it is shown above:
  • Gross revenue is the gross production value (output) adding balance current subsidies (European direct payments).
  • Net profit (or loss) can be determined if the total annual production expenses are subtracted from the gross revenue. A positive net profit reflects the profitability of the farm and a negative net profit indicates a financial loss.
  • Gross profit is calculated when the variable expenses are subtracted from the gross revenue. It can be defined as the sum of net profit and the fixed capital expenses.
  • Family farm income (or Farm Net Income based on terminology in FADN) corresponds to remuneration of fixed factors of production of family (work, land and capital) and remuneration of the entrepreneur’s risks (loss/profit) in the accounting year. It is defined as the net profit and the sum of remuneration of family factors of production. It can be calculated as the deduction of direct cost from the gross revenue.
  • Net revenue (or Farm Net Value Added based on terminology in FADN) is the remuneration of the fixed factors of production (work, land and capital), whether they be external or family factors. It is calculated as the sum of net profit, interest and the land’s rent of family and third parties.
  • Net asset income is calculated by the remuneration of family land and family capital and the remuneration of the entrepreneur’s risks (loss/profit). It is defined as the sum of net profit, implicit rent and interest or as the deduction of payable rent and paid interest from the net revenue.
On each farm, products originating from production sector, simultaneously in the same production process (joint products), whose value participates by more than 10% in the output of the sector are defined as primary products and those that participate below 10% in the output were defined as secondary products or by-products.
Assuming that each by-product does not contribute to the profit (or loss) of the sector, i.e., the difference between the costs of the by-product and the output of the by-product is zero, then it follows that the costs of the by-product minus expenses are equal to the corresponding output. Thus, if the expenditure of each by-product (numerically equal to the corresponding output) is subtracted from the total expenses of the sector, the expenses corresponding to the main product(s) remain.
If there is more than one primary product, the total expenditure of the primary product(s) (calculated as above) will be allocated to them on the basis of their percentage contribution to the aggregate output of the primary product(s).
In this way, the parts of the costs corresponding to each primary product will be determined. For each primary product, if the corresponding costs are divided by the quantities produced, then the cost of production (or average cost of the main product), in EUR/kg, will be obtained.
Based on the above, the size of the production costs depends on three main factors: (a) the amount of total expenditures, (b) the number and achieved output of by-products, linked to production, and (c) the number and achieved output of the primary products, linked to production.
All calculations and results are presented in net values, without the taxes, to reflect the actual productivity.

2.3. Economic Data and Management Practices

Economic data and management practices of the two farms were obtained. The flock size (Table 1), the facilities and the equipment (Table 2 and Table 3) for each farm were recorded. All the parameters for calculating the milk and meat production, the amount and price of sold replacement animals and the doses with the price of sold semen are presented in Table 4. Data related to economic results in the farms were obtained directly from the accountants of each of the farms; in compliance with GDPR rules, only abridged figures are presented herein. Data related to management applied in farms were obtained by means of an interview with the respective farmers.
For the calculation of the annual production expenses of each farm, data about rent and value of the land, farmers’ and employers’ labor remuneration and the interest that accompanies them were used. The expenses for feeding, reproduction strategies and flock health program belong to the variable capital. The expenses of feed, which is the main element of variable expenses, were 104.550 EUR for AI farm and 101.660 EUR for NM farm. The expenses for the estrus synchronization were 5 EUR/ewe and 6 EUR/ewe for the artificial insemination.
The fixed expenses include depreciation, interest, maintenance and insurance of constant and semi-constant capital. Subsequently, for the calculation of fixed expenses, the average invested capital for building, equipment and livestock was determined. Both farms had privately owned buildings and land and purchased all feed used.
European fundings (Basic Payment, Green Payment and Compensatory Allowance) as income support, motivation for environmentally friendly farming and support for maintaining agricultural activity in rural areas were 6500 EUR for AI farm and 9500 EUR for NM farm.

2.4. Βreakeven Analysis of Milk Production

A breakeven analysis was used to show the level of production at which farms start to generate profit. Milk is the most important or the only primary product in those farms, so the breakeven point of milk production in kg/ewe was calculated. The number of ewes (A), the yield per ewe (B), the expenses (C) and the output (D) corresponding to milk production per farm were used for the calculation of breakeven point of milk production. The process that followed included the calculations of profit from milk production per farm (EUR/farm) (E = D-C), the calculation of profit from milk production per ewe (EUR/ewe) (F = E/A) and the determination of the milk quantity in kg per ewe whose value is equal to the calculated milk production profit per ewe (kg/ewe) (G = F/1.55 EUR/kg of milk). The breakeven of milk production in kg/ewe was calculated after the deduction of G from B.

3. Results

3.1. Production Cost

The observation of the financial results and the production cost for each of the farms contribute to comparing them and reaching conclusions about their profitability. In this study, the AI farm has higher annual production expenses (218,874.72 EUR vs. 181,322.57 EUR in the NM farm). The annual production expenses summarize the expenses for land and labor and expenses for variable and fixed capital (Table 5). The expenses for labor, variable capital and fixed capital are higher in the AI farm (32,134.02 EUR, 137,288.58 EUR and 48,452.13 EUR in the AI farm vs. 26,045.82 EUR, 124,408.82 EUR and 27,867.92 EUR in the NM farm, respectively). The biggest difference between the farms is fixed capital expenditure that results from the higher value of fixed capital available to the AI compared to the NM farm. Specifically, the average invested capital for buildings and equipment is 137,250 EUR for the AI farm and 85,150 EUR for the NM farm. Also, the higher genetic value of the AI farm animals is represented by the higher average invested capital for the animals in the AI farm (111,000 EUR compared to 89,000 EUR in the NM farm). A detailed description of the expenses of the variable and fixed capital is presented in Table 6 and Table 7.
The variation between the examined farms regarding the formation of the total output from the products linked to production (primary and secondary) is shown in Table 6. Milk was defined as the primary product in both farms. It accounted for 69.36% of the total output (75% of the output of primary products) in the AI farm and 90.71% of the total output (100% of the output of primary products) in the NM farm. In the AI farm, two more primary products were calculated: the output of replacement ewe lambs and ram lambs (10.82% and 12.72% of the total output, respectively) (Table 8). The total output in the AI farm is 341.900 EUR and 261.450 in the NM farm. The expenses of the by-products are equal to the corresponding output; for the lamb meat sector, they are 4000.00 EUR, for ewe meat sector, they are 2250.00 EUR and for the semen doses sector, they are 18,000.00 EUR. The total expenditures (total production expenses) for the AI farm are 218,874.72 EUR and for the NM farm, 181,322.57 EUR. In order to calculate the expenses of each primary products’ sector, the expenses of the secondary products (by-products) are subtracted from the total expenditure and then this is multiplied by the percentage of output for each primary product (Table 8 and Table 9).
The milk production cost was 0.95 EUR/kg for the AI farm and 1.03 EUR/kg for the NM farm. Only the AI farm sold replacement animals. The production cost for replacement ewe lambs was 122.54 EUR/animal and 183.81 EUR/animal for replacement ram lambs. The milk profit was 0.6 EUR/kg for the AI farm and 0.52 EUR/kg for the NM farm. The AI farm also had profit from the sale of replacement animals (77.46 EUR/ewe lamb and 116.19 EUR/ram lambs). The profit for each primary product was calculated with the deduction of the production costs from the selling price. The profit for each product sector is calculated with the deduction of expenses for the primary products’ sector from the revenue of the corresponding sector.

3.2. Financial Results

The financial results of the farms were calculated and are presented in Figure 1, where the differences between the two farms can be observed. The calculations were all based in the economic definitions given in Section 2.2. The gross revenue for both of the farms was calculated as the sum of the total output with current subsidies (341,900.00 EUR and 6000.00 EUR for the AI farm and 261,450.00 EUR and 9500.00 EUR for the NM farm). For the calculation of the net profit, 218,874.72 EUR was deducted from 347,900.00 EUR for the AI farm and 181,322.57 EUR was deducted from 270,950.00 EUR for the NM farm. The gross profit for the AI farm came from the deduction of 132,288.58 EUR from 347,900.00 EUR and for the NM farm, the deduction of 124,408.82 EUR from 270,950.00 EUR. The farm family income was calculated as the deduction of the direct cost from the gross revenue. The explicit production expenses (direct cost) for the AI farm were 185,909.51 EUR and for NM farm were 143,375.42 EUR. The determination of the net revenue comes from the sum of the net profit, interest and implicit rent of the land. The total interest was 29,181.86 EUR for the AI farm and 21,880.83 EUR for the NM farm. The land’s implicit rent was 1000 EUR for the AI farm and 3000 EUR for the NM farm. The net asset income and net revenue have the same number for both of the farms as the interest and rent for the land is only implicit (159,207.14 EUR for the AI and 114,509.09 EUR for the NM farm).
The values of the financial results were higher in the AI farm compared to those of the NM farm.
In order to draw safe conclusions about the financial results of the two farms, the comparison between them needs to be made on an equivalent basis. They were calculated by assuming that the two farms have equipment and buildings with common years of function and then the numbers of the gross revenue, net profit, gross profit, farm family income, net revenue and net asset income were calculated for 100 productive animals. The financial results that occurred after this modification are shown in Figure 2.

3.3. Breakeven Analysis of Milk Production

In order to define the level of production that farms start to generate profit, the breakeven of milk production in kg/ewe was calculated, since milk is the most important or even the only primary product in the farms under consideration. The expenses related to milk production for each of the farms and all the necessary calculations for the breakeven point of milk production in kg/ewe are shown in Table 10. For the AI farm, the breakeven point of milk production is 312.48 kg/ewe, while for the NM farm, it is slightly lower, at 297.96 kg/ewe (Figure 3). Those values represent the point from which milk production starts to become profitable, as the selling price of milk remains 1.55 EUR/kg. In conclusion, in both farms, the breakeven point of milk production is quite high, in terms of the milk yield of ewes, and it is even a little higher in the AI farm which has relatively higher fixed costs (a higher value of animals and more recent buildings and equipment) and higher variable costs due to higher feeding costs, since the ewes have a greater milk yield compared to the NM farm.

4. Discussion

In this study, after the economic analysis that was carried out for the two farms, it was concluded that the farm which applies artificial insemination had improved financial results compared to the farm that applies natural mating. It was also found that the AI farm had higher milk profit which contributes to its greater profitability than the NM farm. The production cost (EUR/kg) is compared with the selling price of the product (in EUR/kg) to determine the level of profitability of the production of the product in market terms. The two farms had the same selling price for milk, but different cost production, leading to an increased profit for the AI farm. Taking into account the genetic progress of milking productivity (1% of the mean phenotypic milk production) because of the genetic improvement, this profit can be increased in future years [12]. It is notable that the AI farm has a higher breakeven point and this outlines the significance of a certain scale of production.
The leading cause for the different impact in the financial results and profitability was the ability of the AI farm to sell animals with a high genetic value. It is considered that multiple primary products can enhance the sustainability of a farm, as it can provide alternative income sources. In the AI farm, this can also be accomplished if the number of semen doses increases to over 10% of the value of the products sold. The price of milk during the study period was one of the highest in recent years according to the Agricultural Economics Research Institute of ELGO Demeter. It is characteristic that since 2022, the significant increase in the price of animal feed, caused as a result of the large increase in energy and fertilizer prices, has automatically caused the price of sheep’s milk to increase by approximately 50% (currently over EUR1.5/liter) [27]. The prices are mainly determined by dairy companies and the consumers’ preferences while the production cost depends mainly on feed expenses. Hence, the difference in the price of milk over the years reflects the need to maintain the level of the profitability of production at satisfactory levels and not to affect the supply of cheese dairies, given that sheep’s milk is the raw material to produce Feta cheese, which currently maintains strong demand in international markets [3]. If the farmers act collectively and negotiate prices through a cooperative, they might ensure better milk sale prices [28]. Therefore, the farm that performs artificial insemination and aims to develop high-genetic-value livestock brings the producer higher profits. It can be predicted that in the long term, as production improves and the capital invested is depreciated, profitability can increase.
The application of artificial insemination on a farm requires proper planning and methodology, observing all the appropriate conditions and requirements [29], the most important being the use of animals of a high genetic value. Improving livestock must be a priority as it has been shown that this can increase the farm’s economic results [12]. Reproductive technologies, together with targeted nutritional and health management, can contribute to fast genetic improvement [30,31,32] by increasing milking periods and fertility rates and reducing reproductive cycles [7,33]. Artificial insemination in Mediterranean countries, where dairy sheep farming is dominant, is a tool for applying breed selection schemes to improve specific productive traits [12,34]. In a recent study where the reproductive management of sheep flocks in Greece was recorded, none of the 325 farms had applied artificial insemination [22]. It is recorded that annually, approximately 300.000 ewes in France and 60.000 ewes in Spain are inseminated [21,32].
Despite the rapid genetic progress that can be achieved, the fluctuating outcome of artificial insemination leads to the limited application of this reproductive technique and hesitation of the farmers to adopt it [35]. The main reason is a low fertility rate due to the anatomical complexity of the ewe cervix and difficulty for a deep deposit of the sperm [18,29]. The highest fertility rate is 60–70% in healthy animals with the correct hormonal preparation of the female and proper use and preservation of the sperm [32], whereas, commonly, a rate of around 50% is encountered [11]. In sheep farming, artificial insemination is mainly performed with fresh semen, which is challenging to preserve and omissions during the processing of semen can decrease the number of motile spermatozoa and the fertility rate [14,36]. Frozen semen can also be used with a success rate of 70–80%, but with the indicated method of the laparoscopic or transcervical intrauterine insemination which cannot be applied in the field [11,37]. The correct time of insemination is 55 h (for single) and 50–60 h (for double) after a gonadotropin injection and vaginal progestogen sponges’ removal, which is another challenging point of the procedure [37]. It is, thus, crucial for artificial insemination to be carried out by highly qualified scientific staff [15,29] in order to achieve the highest fertility rates. Another reason for farmers’ hesitation may be the need for the estrus sychronization of the animals which can be challenging, especially in small-scale farms with limited staff and spaces. It is noteworthy that in recent field studies in Greece, it was found that only 30% of the farmers applied reproductive control [22,38].
Effective communication regarding positive effects on profitability by applying artificial insemination is essential. The AKIS agricultural advisory system, through the 10th objective of the current Common Agricultural Policy 2023–2027, in the framework of strengthening the resilience of the European Union’s agricultural systems, can contribute to the dissemination of the benefits and the correct implementation of artificial insemination [39]. The agricultural advisory services could help livestock farmers overcome technical challenges since specialized advisors–scientists will support them [40]. The European Union’s Horizon Project may complement the above by further promoting research and innovation in such areas [41]. When the results of artificial insemination start to be clear, fewer natural service rams will be kept on farms, reducing the feeding cost and increasing farm profitability [42]. Increased milk production, which can be achieved through the genetic improvement of animals, together with the higher selling prices for superior breeding animals, will also improve the profitability of the farms [12]. The genetic selection can develop resistance in significant diseases such as mastitis, foot rot and scrapie, reducing the financial loses from insufficient disease control, eliminating the antibiotic use [43,44]. By decreasing antimicrobial resistance, the approach of “One Health” is efficiently fulfilled [45]. The comprehension of those benefits from the farmers plays the most important role in applying breeding programs. Their reluctancy can be overcome when they are organized in clusters that emphasize creating high-efficiency farms through the training and education of farmers by scientific staff [46].

5. Conclusions

Artificial insemination brings economic changes to a sheep farm and can be advantageous when applied under the right conditions. The success of this technique depends on the specialization of the practitioner and on compliance with the necessary standards for the suitability of the semen used. Maintaining high-genetic-value livestock gives the opportunity for a high level of dairy production by keeping a smaller number of ewes and, at the same time, extending the commercial activity of the farm through the sale of replacement animals. The breeding and sale of genetically improved animals can increase the financial results of a farm, in particular, the gross revenue and net and gross profit.
However, improvements still have to be made to aspects that can make this activity profitable and attractive to the general public, to raise awareness among the farmers of the positive results of the application of artificial insemination in order to realize that sheep farming in Greece can be more sustainable and economically efficient. Key initiatives regarding the training of the farmers, partial governmental economic support and some European policies could benefit the success of such actions. Therefore, targeted interventions, such as awareness campaigns and educational programs, should be organized to promote AI application in dairy sheep farming. At the same time, the minimization of the distance from AI centers and reliable AI services can mitigate the risk of missed heat cycles. Legislating a cost-sharing strategy or subsidies can enhance affordability, especially for financially constrained farmers. Moreover, support for the cooperation and fortification of farmer group initiatives that facilitate the trade of dairy sheep products while ensuring strengthened extension services can accelerate the faster application of AI in sheep farms.

Author Contributions

Conceptualization, K.T. and D.V.L.; methodology, K.T. and D.V.L.; investigation, D.V.L. and A.P.P.; writing—original draft preparation, D.V.L.; writing—review and editing, A.P.P., M.S., E.N., P.S. and K.T.; visualization, D.V.L. and M.S.; supervision, K.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Most data have been presented in the manuscript. The remaining data are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AI farmFarm that applied artificial insemination,
NM farmFarm that applied natural mating.

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Agriculture 15 00719 g001
Figure 1. The financial results for AI farm and NM farm, farms that apply different reproductive management. In AI farm, artificial insemination was applied, while in NM farm, only natural mating was applied.
Figure 1. The financial results for AI farm and NM farm, farms that apply different reproductive management. In AI farm, artificial insemination was applied, while in NM farm, only natural mating was applied.
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Agriculture 15 00719 g002
Figure 2. The financial results for AI farm and NM farm, farms that apply different reproductive management after modification for common years of function in equipment/buildings and number of productive animals. In AI farm, artificial insemination was applied, while in NM farm, only natural mating was applied.
Figure 2. The financial results for AI farm and NM farm, farms that apply different reproductive management after modification for common years of function in equipment/buildings and number of productive animals. In AI farm, artificial insemination was applied, while in NM farm, only natural mating was applied.
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Agriculture 15 00719 g003
Figure 3. Breakeven points of milk production for AI and NM farms. The values represent the point from which farms’ milk production starts to become profitable, at a selling price of 1.55/kg. In AI farm, artificial insemination was applied, while in NM farm, only natural mating was applied.
Figure 3. Breakeven points of milk production for AI and NM farms. The values represent the point from which farms’ milk production starts to become profitable, at a selling price of 1.55/kg. In AI farm, artificial insemination was applied, while in NM farm, only natural mating was applied.
Agriculture 15 00719 g003
Table 1. The number and the value of the animals for AI farm and NM farm.
Table 1. The number and the value of the animals for AI farm and NM farm.
AI Farm *NM Farm *
Number of AnimalsAverage ValueTotal ValueNumber of AnimalsAverage ValueTotal Value
nEUR/AnimalEURnEUR/AnimalEUR
Ewes30028084,00034022074,800
Replacement lamb ewes5030015,00010012012,000
Rams12100012,000102202200
* In AI farm, artificial insemination was applied, while in NM farm, only natural mating was applied.
Table 2. Parameters used for calculation of depreciation of the buildings and equipment for NM farm.
Table 2. Parameters used for calculation of depreciation of the buildings and equipment for NM farm.
NM Farm *
Reconstruction Cost—ValueUseful Life (Years)Years of FunctionDepreciation
Stable80,000.00 EUR25103200.00 EUR
Feed store35,000.00 EUR25101400.00 EUR
Milking parlor (facility)15,000.00 EUR2510600.00 EUR
Farm equipment (mill, mixer, troughs and waterers)20,000.00 EUR12101666.67 EUR
Milking machine30,000.00 EUR12102500.00 EUR
Lamb feeding device8000.00 EUR841000.00 EUR
* In NM farm, only natural mating was applied.
Table 3. Parameters used for calculation of depreciation of the buildings and equipment for AI farm.
Table 3. Parameters used for calculation of depreciation of the buildings and equipment for AI farm.
AI Farm *
Reconstruction Cost—ValueUseful Life (Years)Years of FunctionDepreciation
Stable75,000.00 EUR2543000.00 EUR
Feed store35,000.00 EUR2541400.00 EUR
Milking parlor (facility)15,000.00 EUR254600.00 EUR
Farm equipment (mill, mixer, troughs and waterers)20,000.00 EUR1241666.67 EUR
Milking machine30,000.00 EUR1242500.00 EUR
Lamb feeding device8000.00 EUR841000.00 EUR
* In AI farm, artificial insemination was applied.
Table 4. Parameters used for calculation of production for AI farm and NM farm.
Table 4. Parameters used for calculation of production for AI farm and NM farm.
AI Farm *NM Farm *
Milk
     Yield per ewe510 L450 L
     Annual yield153,000 L153,000 L
     Price1.55 EUR/L1.55 EUR/L
Lamb
     Culled100380
     Price (Culled)5 EUR/kg5 EUR/kg
     Sold as replacement animals330-
     Price200 EUR/female lambs
300 EUR/yearling rams		-
Culled Sheep2580
Price (Culled sheep)3 EUR/kg3 EUR/kg
Semen doses3000-
Price per dose (semen) 6 EUR/dose-
* In AI farm, artificial insemination was applied, while in NM farm, only natural mating was applied.
Table 5. Annual production expenses for AI farm and NM farm.
Table 5. Annual production expenses for AI farm and NM farm.
AI Farm *NM Farm *
Land1000.00 EUR3000.00 EUR
Labor32,134.02 EUR26,045.82 EUR
Expenses of variable capital132,288.58 EUR124,408.82 EUR
Expenses of fix capital48,452.13 EUR27,867.92 EUR
Total production expenses218,874.72 EUR181,322.57 EUR
* In AI farm, artificial insemination was applied, while in NM farm, only natural mating was applied.
Table 6. Detailed expenses of fixed capital for AI and NM farms.
Table 6. Detailed expenses of fixed capital for AI and NM farms.
Εxpenses of Fixed CapitalAI Farm *NM Farm *
Depreciation22,766.67 EUR10,366.67 EUR
Interest22,478.78 EUR15,748.01 EUR
Maintenance for constant and semi-constant2067.50 EUR1046.50 EUR
Insurance for constant and semi-constant1139.18 EUR706.75 EUR
Total48,452.13 EUR27,867.92 EUR
* In AI farm, artificial insemination was applied, while in NM farm, only natural mating was applied.
Table 7. Detailed expenses of variable capital for AI and NM farms.
Table 7. Detailed expenses of variable capital for AI and NM farms.
Expenses of Variable CapitalAI Farm *NM Farm *
Feed expenses104,550.00 EUR101,660.00 EUR
Insurance for livestock (ELGA)545.52 EUR677.00 EUR
Services (i.e., electricity, health control, reproductive control, application artificial insemination in AI farm)26,800.00 EUR17,000.00 EUR
Interest of variable capital5393.06 EUR5071.82 EUR
Total137,289.58 EUR124,408.82 EUR
* In AI farm, artificial insemination was applied, while in NM farm, only natural mating was applied.
Table 8. Parameters used for the determination of cost and profit for each of the revenue-generating products for the AI farm.
Table 8. Parameters used for the determination of cost and profit for each of the revenue-generating products for the AI farm.
ProductsPriceRevenueOutput of Production Output of Primary ProductsExpenses for Primary Products’ SectorCostProfit of Each Product Sector
%Classification as a primary or secondary product% participation in output of the primary products(Annual production expenses minus cost of production of secondary products) × % of output of each primary productEUR/kg or EUR/animal
Milk1.55 EUR/kg237,150.00 EUR69.36%Primary75%145,302.23 EUR0.95 EUR/kg91,847.77 EUR
Lamb meat5.00 EUR/kg4000.00 EUR1.17%Secondary----
Ewe meat3.00 EUR/kg2250.00 EUR0.66%Secondary----
Replacement ewe lambs200.00 EUR/animal37,000.00 EUR10.82%Primary12%22,669.97 EUR122.54 EUR/animal13,330.03 EUR
Replacement ram lambs300.00 EUR/animal43,500.00 EUR12.72%Primary14%26,652.53 EUR183.81 EUR/animal16,847.47 EUR
Semen doses6.00 EUR/dose18,000.00 EUR5.26%Secondary----
Total 341,900.00 EUR ----
Price, revenue and output of production and of primary products are presented. For the calculation of the expenses for primary products’ sector, the cost production of secondary products was subtracted from the annual production expenses and then multiplied by the participation percentage in primary products output. Expenses for each primary product divided by the quantities produced lead to cost of production in EUR/kg or EUR/animal. Profit derived from each product sector is calculated with the deduction of expenses from revenue. In AI farm, artificial insemination was applied.
Table 9. Parameters used for the determination of cost and profit for each of the revenue-generating products for the NM farm.
Table 9. Parameters used for the determination of cost and profit for each of the revenue-generating products for the NM farm.
ProductPriceRevenueOutput of Production Output of Primary ProductsExpenses for Primary Products’ SectorCostProfit of Each Product Sector
%Classification as a primary or secondary product% participation in output of the primary products(Annual production expenses minus cost production of secondary products) × % of output of each primary productEUR/kg
Milk1.55 EUR/kg237,150.0090.71%Primary100%157,022.571.03 EUR/kg80,127.5
Lamb meat5.00 EUR/kg17,100.006.54%Secondary
Ewe meat3.00 EUR/kg7200.002.75%Secondary
Replacement ewe lambs--------
Replacement ram lambs--------
Semen doses--------
Total 261,450.00
Price, revenue and output of production and of primary products are presented. For the calculation of the expenses for primary products’ sector, the cost production of secondary products was subtracted from the annual production expenses and then multiplied by the participation percentage in primary products output. Expenses for each primary product divided by the quantities produced lead to cost of production in EUR/kg or EUR/animal. Profit derived from each product sector is calculated with the deduction of expenses from revenue. In NM farm, only natural mating was applied.
Table 10. Step-by-step breakeven analysis of milk production in kg/ewe for AI and NM farm.
Table 10. Step-by-step breakeven analysis of milk production in kg/ewe for AI and NM farm.
Number of Ewes
(A)		Yield per Ewe (kg)
(B)		Expenses Corresponding to Milk Production/Farm (EUR/Farm)
(C)		Output of Milk Production/Farm (EUR/Farm)
(D = A×B*1.55 EUR/kg of Milk)		Profit of Milk Production/Farm (EUR/Farm)
(E = D-C)		Profit of Milk Production/Ewe (EUR/Ewe)
(F = E/A)		Quantity of Milk in kg per Ewe Whose Value Is Equal to the Calculated Milk Production Profit per Ewe (kg/Ewe)
(G = F/1.55 EUR/kg of Milk)		Breakeven of Milk Production in kg/Ewe (kg/Ewe)
(H = B-G)
AI farm *300510145,302.23237,150.0091,847.77306.16197.52312.48
NM farm *340450157,022.57237,150.0080,127.43235.67152.04297.96
* In AI farm, artificial insemination was applied, while in NM farm, only natural mating was applied.
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MDPI and ACS Style

Liagka, D.V.; Politis, A.P.; Spilioti, M.; Nellas, E.; Simitzis, P.; Tsiboukas, K. A Comparative Economic Analysis of Different Reproductive Management Strategies in Two Dairy Sheep Farms in Greece. Agriculture 2025, 15, 719. https://doi.org/10.3390/agriculture15070719

AMA Style

Liagka DV, Politis AP, Spilioti M, Nellas E, Simitzis P, Tsiboukas K. A Comparative Economic Analysis of Different Reproductive Management Strategies in Two Dairy Sheep Farms in Greece. Agriculture. 2025; 15(7):719. https://doi.org/10.3390/agriculture15070719

Chicago/Turabian Style

Liagka, Dimitra V., Antonis P. Politis, Maria Spilioti, Eleftherios Nellas, Panagiotis Simitzis, and Konstantinos Tsiboukas. 2025. "A Comparative Economic Analysis of Different Reproductive Management Strategies in Two Dairy Sheep Farms in Greece" Agriculture 15, no. 7: 719. https://doi.org/10.3390/agriculture15070719

APA Style

Liagka, D. V., Politis, A. P., Spilioti, M., Nellas, E., Simitzis, P., & Tsiboukas, K. (2025). A Comparative Economic Analysis of Different Reproductive Management Strategies in Two Dairy Sheep Farms in Greece. Agriculture, 15(7), 719. https://doi.org/10.3390/agriculture15070719

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