The use of energy in milk production; a case study from Konya
province of Turkey
Cennet Oguz
*, Aysun Yener (Ogur)
Department of Agricultural Economics, Faculty of Agriculture Selcuk University, 42130, Konya, Turkey
a r t i c l e i n f o
Article history:Received 29 January 2019 Received in revised form 19 June 2019
Accepted 21 June 2019 Available online 23 June 2019 Keywords: Energy Milk production Technical efficiency Konya
a b s t r a c t
The aim of this study is to examine the energy efficiencies of dairy products produced in dairy enter-prises in Konya region and to provide suggestions to increase energy efficiency. For this purpose, 125 dairy enterprises have been selected as samples by using stratified random sampling method to identify the enterprises to be examined. As a result, 8.05% of total energy input per cow was direct energy and 91.95% was indirect energy. 89.66% of total energy output is from milk production, 4.65% is from pro-ductive stock value (PSV) and 5.69% is cow manure. The energy use efficiency in the research area was found to be 1.07. Energy productivity in milk production has been calculated as 0.13 (kgMJ1) when milk production per unit animal was taken into consideration. The specific energy value per dairy cow has been calculated as 7.42 MJ/kg. A non-parametric production function of DEA (Data Envelopment Anal-ysis) has been applied to optimize energy use in dairy enterprises. The average technical efficiency (TE) in the research area has been calculated as 0.921. In this sense, the amount of input needs to be reduced by 7.9% in order to achieve the same level of production.
© 2019 Elsevier Ltd. All rights reserved.
1. Introduction
One of the conditions required for sustainable agricultural production is the efficient use of energy in agriculture. Agriculture itself plays an important role as an energy consumer as well as an energy supplier in the form of bio-energy [1]. Identifying animal production methods that maximize energy efficiency has a direct impact on the profitability and environmental sustainability of an enterprise. Efficient energy use saves fossil fuel resources and re-duces air pollution and also makes saving in terms of agricultural production andfinancing [2].
Energy analysis is performed, despite the fact that it requires a lot of economic and technical studies, mainly to examine whether a service or product that will be presented to the market is viable in terms of energy use efficiency. Comparing the total energy value of the inputs used in agricultural production processes with the en-ergy value of the obtained product is a more realistic approach to evaluate production efficiency. It is important to know the energy consumption of milk production in order to increase the cost competitiveness of dairy farmers, as the cost of electricity will
increase significantly in the future and energy consumption will become a major problem in milk production [3]. A number of different studies have discussed the need to measure basic data related to energy input in total milk production as a marker of the sustainability of milk production enterprises [4,5]. Dairy enter-prises are both energy consumers and energy producers. The use of different energy inputs will produce energy outputs (milk and fertilizer). The amount of energy used in dairy farming depends on the level of milk production, the consumption amount of food, diesel fuel, human labour, electricity consumption as well as the mechanization level of the enterprise. Only a handful of studies have focused on energy use in livestock enterprises [6]. In addition, these studies are all different from each other and the results are partially comparable [7]. Developing applicable methods for the calculation of energy inputs in livestock is highly important for determining achievable targets for efficient energy use. Konya province is in a pretty good condition in dairy farming and it con-stitutes 5% of the total animal presence and 6% of the total dairy production in Turkey [8]. Big changes began to take place in dairy farming in Konya province after 2002. Dairy farming enterprises began to follow the changes and developments in technology closely, such as in the form of cultured animals. Since 2009 in particular, the expansion of the international agriculture and rural development support program (IPARD) and the national agency
* Corresponding author.
E-mail address:coguz@selcuk.edu.tr(C. Oguz).
Contents lists available atScienceDirect
Energy
j o u r n a l h o me p a g e : w w w . e l s e v i e r . c o m/ l o ca t e / e n e r g y
https://doi.org/10.1016/j.energy.2019.06.133
support programs in the region, research results of the universities, provincial practices of the Ministry of Food, Agriculture and Live-stock have improved the dairy farming investments in the region and increased total milk production. However, especially the in-crease of dairy farming in the region requires that the resources of the enterprises are used more effectively. One such requirement is energy efficiency. Productivity analyses have been a popular trend in recent years, implemented by different authors from different fields [9]. Energy output/input analysis is performed usually to measure the energy efficiency and the environmental dimension. There are many studies related to energy output/input analysis in plant production in Turkey and some of them are; carrot [10], sugar beet [11], greenhouse tomato [12], barley [13], lentil [14], chickpeas [15], tobacco [16]. Energy output/input analysis can determine how efficiently the energy is used. In this way, both the waste caused by excessive energy consumption will be avoided and the harm that the environment is exposed to because of excessive energy use (fertilizer, feed, fuel etc.) will be prevented. One of the most effective ways to reduce energy use in the agricultural sector is to increase energy efficiency. In Turkey, almost all of the studies done in this regard focus on input-output energy analysis in plant pro-duction. There is not a single study so far that has been conducted to increase energy efficiency in dairy farming enterprises.
In this study, the technical activities, pure technical efficiencies and scale efficiencies of the enterprises have been calculated by determining the efficient and inefficient enterprises as well as performing input output energy analysis. Data Envelopment Anal-ysis (DEA) was used for the analAnal-ysis of energy activities and the comparison of agricultural enterprises and the development of energy activities of dairy enterprises in recent years [17e19]. DEA approach has been used to compare units in consideration of all resources and outputs involved in dairy enterprises. In other words, it has been used to identify, in terms of energy-use efficiency, most productive diary enterprises (best practice units) and non-productive enterprises where productivity improvements are possible [20]. Hence, the amount of possible input energy savings in dairy enterprises to achieve energy efficiency have been revealed. 2. Materials and methods
This study has been conducted in Konya province of Turkey. Konya is located between 36410and 39160northern latitudes and 31140and 34260eastern longitudes. The main material of the study was the primary data obtained from the surveys con-ducted with the agricultural enterprises engaged in dairy farming in Konya province. Research area was in Konya, where 25% of the total population lives in rural areas and agricultural activities are their main source of income. The focal point of this study is the animal assets of dairy farm enterprises in Çumra, Karapinar and Eregli districts, which collectively constitute 15% of the total number of cattle in Konya. In this sense, 125 enterprises formed the sample size in accordance with stratified sampling method, one of the simple random sampling methods, for a 99% confidence inter-val and an error margin of 5% [21]. The required data was collected from 125 dairy farm producers by using face to face survey method.
n¼ ½ P ðNhShÞ2 N2D2þPhNhðShÞ2 i D¼dt n¼ Sampling size.
N¼ Number of total holdings in population.
d¼ Allowed error rate from the main mass average value. t¼ Standard normal distribution value.
Nh¼ h. Number of the population in h (small, medium or large)
S2h¼ is the variance of h.
D2 ¼ d2=z2, z is the reliability coefficient (1.96 which represents
95% confidence). Data from the 125 surveys conducted in the research area have been evaluated in accordance with the enter-prise sizes based on the suckled cow number; 0e50 heads (72 enterprises), 51e150 heads (38 enterprises) and 151 heads and more (15 enterprises).
The DEA method, which is a nonparametric method, was used in the study in order to determine the technical, pure technical and scale efficiencies of dairy enterprises producing milk. In DEA method it is recommended that practises include a decision unit number that is at least equal to the multiplication of input number and output number or three times the total of input and output numbers [22]. Thus, 125 enterprise is a sufficient number for the study.
The milk yield per milked cow, Productive Stock Value (PSV), fertilizer were evaluated together and included in the model as a single output variable. PSV¼ (year-end stock value þ value of the sold stockþ value of the stock slaughtered) - (value of the stock at the beginning of yearþ value of the stock bought) [23,24].
DEA method is one of the nonparametric models and measures the relative effectiveness of“n” decision making units (DMU). This model has been used in the study to assess the energy amount by ranking dairy cow enterprises on the basis of their performance and to determine the resource usage efficiency. The milk yield per milked cow, PSV and fertilizer have been assessed together and included in the model as a single output variable. There were 9 input energy consumption deemed as input variables: labour, ma-chine, diesel fuel, oil, electricity, labour, feeds (concentrate, maize silage, alfalfa, straw). This data was standardized by using daily values and quantities of output and inputs used per animal.
Rather than outputs, producers will need to check the efficiency of inputs that are used extensively and Farrell’s [25] input efficiency measurements have been used for the research. In this study, en-ergy values of the input variables of each enterprise engaged in dairy cattle including labour force (MJ Cow1), fuel (MJ L1), oil (MJ L1), electricity (MJ kWh 1), concentrated feed (MJ Kg1), straw (MJ kg1), alfalfa (MJ kg1) and maize silage (MJ kg1) were given per number of dairy cows. Output (Yi) is the energy value for annual milk production per animal, annual fertilizer yield per animal, and PSV (Table 1). In other words, an efficient model with 9 inputs and 1 output was created. 2 models of DEA method have been used in the study for calculating energy efficiency. These are; DEA, i.e., fixed
Table 1
Characteristics of the dairy cattle farms and cows of the studied area.
Races HolsteineFriesian
Average number of dairy cow (Head/Per Farm) 58.90 Avg. body weight of adult dairy cow (kg) 550
Lactation period (days) 300
Dry period (days) 65
Average milk yield (kg day1Cow1) 22.02 Average milk yield (kg year1Cow1) 6607.20 No. of lactations (times per day) 2
Barn Semi open
Feeding Total mixed ration
Concentrates (Dry matter) 88%
Maize silage (Dry Matter) 30%
Alfalfa (Dry matter) 85%
Straw (Dry Matter) 85%
PSV (kg year1Cow1) Meat (Life weight Cow)
Calving interval 1 calf cow-1year-1
New born female: male ratio 50%
Milk cooling system Direct cooling
Manure Disposal (DM) 60e70%
Location Konya
earning on the basis of CCR (Charnes-Cooper-Rhodes) scale [27] and increasing earning on the basis of BCC (Banker-Charnes-Cooper) scale [26]. Ineffective units in DEA can symmetrically be activated by performing both the same output level (for input) with minimum input and maximizing the output levels (for output) provided that inputs are kept constant. Milk production is carried out with inadequate and scarce resources. Thus, it is more appro-priate to reduce the inputs used in the production process in implementing the DEA method for input. Energy inputs (MJ/Cow) and yield of milk (Kg/Cow) were used to calculate technical, pure technical and scale efficiencies of enterprises in order to identify the efficient and inefficient ones. Technical Efficiency (TE) can be defined as the ability of the decision-making unit to produce maximum output from existing technology and a given input set. In the presence of multiple input and output factors, the TE score (ø) is as follows[28,29and30]. TEj¼ U1Yj1 þ U2Y2jþ ………… þ UnYnj V1Xj1jıþ V2X2jþ ………… þ VnXnj ¼ Pn r1þ UrYrj Pm s1þ VsXsj (1)
Ur; weight given to output“n”, “Vs”; weight given to input “n”,
Xs; amount of input“n”, “r”; number of outputs (r ¼ 1, 2, …., n), “s”;
number of inputs (s¼ 1, 2, …, m), “j” represents jth of DMUs. Following linear programming, Eq. can be solved as follows.
Maximize TE¼ a0þ Xn r1 UrYrj (2) Xn r1 UrYrj Xm s1 VsXsj 0 (3) Xm s1 VsXsj¼ 1; Ur 0; Vs 0 ve ð}i} ve }j} ¼ 1; 2; 3; ……kÞ (4)
CCR model calculates TE only, while BBC model calculates TE, SE and PTE. Therefore, BBC model has also been used in this model. This model assumes varying earning to a scale that represents changes in different ratios that correspond to a change per unit in inputs. Scale efficiency (SE) is associated to the most effective scales of enterprises that act upon the principle of maximizing average productivity. It can be calculated as follows.
Maximize Z¼ uyi ui
Subjected tovxi¼ 1
vX þ uY u0e 0
v 0; u 0
(5)
“Z” and “u0”; scalar and free in sign, “u” and “v”; output and
input weight matrixes, respectively, and “Y” and “X”; the corre-sponding output and input matrixes, respectively. The“xi” and “yi”
refer to the inputs and output of its DMU, respectively. In addition, in the efficiency analysis, enterprises with a TE coefficient between 0.95 and 1 were classified as efficient, those between 0.90 and 0.95 as less efficient and those below 0.90 as inefficient [26].
Scale efficiency (SE) is associated with the most efficient scales of enterprises acting with the sensitivity of maximizing average productivity. It can be calculated as follows.
SE¼ TE =STE; (6)
The SE provides information about the quantity of the scale characteristics. It refers to the potential efficiency achieved by a decision unit achieving the optimum scale. However, scale in-efficiency is due to either the presence of increased return to the scale (IRS) or the decreased return to the scale (DRS). It can be
determined by comparing the efficiency scores obtained by IRS, DRS and BCC models. Thus, if the two efficiency scores are equal, then the DRS is applied. Otherwise, the IRS is superior [31]. Being the period for which energy consumption is estimated for, a lactation period of a cow is approximately 300 days and cows are dry in about 65 days. Therefore, input consumptions are considered to be a production year. More specific characteristics of the target farms and cows are given inTable 1.
2.1. Calculation of energy inputs
Data on energy consumption pattern for milk production came from the 2015e2016 production year. Secondary data and energy equivalents for energy input and energy output levels were ob-tained from previous studies and related literature. The inputs used for the milk production were direct energy (diesel fuel, lubricant, electricity, human labour), indirect energy (machinery, concen-trates, maize silage, alfalfa, straw); while output was milk yield and manure, calculated per cow. The energy associated with all inputs was estimated directly by multiplying the corresponding activity by the appropriate energy equivalent (Table 2). All of the feeds were calculated on dry matter.
2.1.1. Human labour energy (HE)
In the research area, human labour energy includes labour necessary for milking, feed distribution and animal care. HE for farm labour was calculated as below:
HE¼ðHours of WorkÞPer Cow xEE (7)
EE is the energy equivalent of human labour (MJ Cow1). The EE results are shown inTable 2.
2.1.2. Machine energy input (MJ Cow1)
The machine energy input is related to tractors and other ma-chines used in dairy farming and is calculated according to the formula
ME¼ ðGxEExtÞ=T (8)
Where ME is the machinery energy per cow (MJ/Cow), G is the material mass used for manufacturing (kg), EE is the energy equivalent of the machines (MJ/kg), t is the time a machine is used per cow (h), and T is the economic life of machine (h).
2.1.3. Fuel and lubricant energy inputs (MJCow1)
Fuel and lubricant are consumed during farm activities (manure removal, feed transportation and feed distribution). Water is also provided for cows and generally farmers are using pumping system and water energy consumption is measured by the fossil fuel and electricity use of pumping system
FE¼ QfxEE (9)
where FE is the fuel energy per cow (MJ/Cow), Qf is the fuel con-sumption (L/Cow), and EE is the energy equivalent of the fuel (MJ/ L). LE is lubricant energy per cow(MJ/Cow).
2.1.4. Electricity energy input (MJCow1)
Farmers were generally using pumping systems for water pro-vided for cows.
EE¼ QEXEE (10)
where EE is electricity energy per cow (kWh/Cow) QEelectricity 144
consumption is consumed during the farm activities (milking, cooling, pumping system e.t), EE is the electric energy equivalent.
2.1.5. Feed energy input (MJCow1)
The feed used in dairy farming production enterprises included concentrates, maize silage, Alfalfa, and straw. Feed energy (EF) was calculated using equivalences and the data fromTable 1separately for each feed type;
EF¼ QfeedXEE (11)
where EF is the feed energy (MJ/Cow), Qfeed is the feed con-sumption (kg/Cow), and EE is the energy equivalent for each feed type (MJ/kg).
3. Results and discussion
3.1. Estimation of energy use efficiency in investigated dairy enterprises
The energy output obtained per unit cow was calculated by the following formulas, based on the energy equivalent computation results, various energy indices including Energy Use Efficiency (EUE) or Energy Ratio (ER), Energy Productivity (EP), Specific En-ergy (SE) and Net EnEn-ergy Gain (NEG) were estimated as follows (Eq.
(12)e(17)): Energy use efficiency, energy productivity, specific en-ergy, energy intensity, energy intensiveness and net energy gain. It has been based on the calculations of Pishgar et al. [1].
EUE ¼ Energy OutputMJ Cow1. Energy InputMJCow1
(12)
EP¼ Milk yieldkg Cow1.Energy InputMJ Cow1 (13)
SE¼ Energy inputMJ Cow1.Milk Yieldkg Cow1 (14)
Energy Intensity¼ Milk InputMJCow1. Energy OutputMJCow1
(15)
Energy Intensiveness¼ Energy InputMJCow1.
Cost of Production$Cow1 (16)
NEG¼ Energy outputMJ Cow1 Energy inputMJ Cow1
(17)
Total Outputs¼ Dairy cow produce milk þ produvtive stock valueþ manure. PSV ¼ (Year-end stock value (LU)þvalue of the sold (LU)þ value of the stock slaughtered (LU))- (value of the stock at the beginning of year (LU)þ value of the bought (LU))X 550 kg X9.22
(MJ Cow1)). (18)
(Whole LU¼ livestock units, where 1 LU is equivalent to 1 adult dairy cow Body weight) [18,23,24].
Input energy is divided into 4 parts, as direct, indirect, renew-able and non-renewrenew-able energy. Direct energy includes diesel, lubricant, electricity and labour used in milk production, while indirect energy includes machinery, concentrated feed, silage, al-falfa and straw used in milk production. Non-renewable energy includes diesel, lubricant, electricity and feed while renewable energy includes workforce (Table 2). In the research area, it is calculated that the highest share in production inputs is indirect energy consumption by 91.95% and 8.05% is used for direct energy consumption. The total energy output is 52,617.13 (MJ/Cow1). Used for calculating the output energy, the energy obtained from milk, PSV and manure is shown inTable 3.
89.66% of total energy output is from milk production, 4.65% is from PSV and 5.69% is cow manure. The total energy output in Iran dairy enterprises is 23,642 (MJ Cow1), of which 91.36% is milk, 5.62% is meat and 3.02% is cow manure [43].
The EUE in the research area was found to be 1.07. This shows that energy is used effectively and that the production systems of the enterprises are good (Table 4). In a similar study in Tehran, Iran, the energy use rate was found to be 0.26 [44]. EP, on the other hand, shows how much energy input should be consumed for unit energy output. It was calculated as a proportion of total milk yield per cow to total energy input (Eq-2). The high energy efficiency means that the energy efficiency in production is high. EP of milk production in the research area was calculated as 0.13 kgMJ1, when only he milk production per unit animal was taken into consideration. That is,
Table 2
Energy equivalent coefficient of inputs and outputs used.
Inputs/Outputs Data Units Energy Equivalent MJ/Unit References
A. Inputs/Outputsa
1. Direct Energy
Diesel Amount of Diesel L 40.68 [32e34]
Lubricantsb Amount of Diesel L 3.6 [33]
Electricity Amount of Electricity kWh 11.93 [12,34]
Human Labour Energy equivalent H 1.96 [12,35]
2. Indirect Energy
Machines Energy equivalent kg 71.38 [32,35,36]
Concentrates Amount of purchased concentrates (DM) kg 6.3 [4,37]
Maize Silage Amount of purchased forage (DM) kg 2.2 [32,37]
Alfalfa Amount of purchased forage (DM) kg 1.5 [36e38]
Hay (Straw) Amount of purchased forage (DM) kg 12.5 [5,39]
B. Outputs
1. Milk Amount of milk kg 7.14 [40]
2. Productive Stock Value Live weight of cow kg 9.22 [41]
2. Cow Manure Dry Matter kg 0.30 [42]
aAll data required for calculations were found in the cited references.
b The energy input from lubricants for production offield machinery are related to the amount of diesel used during farm operations.
under Konya conditions, 0.13 kg of milk is produced with 1 MJ en-ergy consumption in milk production. In a study in Iran, it was calculated that 0.16 kg of milk was produced with 1 MJ energy consumption [19]. The ratio of the total amount of energy used in production processes to the total amount of product obtained is defined as SE. The SE value refers to the amount of energy consumed (MJ) to produce the unit quantity (kg) of the product. The low SE value means that the energy efficiency in production is high. This value was calculated as 7.42 MJ/kg1in the research area. That means 7.42 MJ of energy is consumed for 1 kg of milk pro-duction. That’s about $ 2.04. The price of 1 kg of milk is 0.42 dollars. A study in dairy enterprises in Estonia estimated that a total of 5.35 MJ energy input was consumed for 1 kg milk production [45]. In a study conducted in New Zealand, the SE value was calculated as 1.84 (MJkg1) [7].
The average total energy input was found as 3.9 MJkg1 by Ref. [45], the SE value was calculated as 3.3 by Ref. [6], 3.5 by Ref. [46], 6.4 by Ref. [47]. The difference between the total amount of energy gained at the end of production and the total amount of energy used in production processes is defined as NEG (MJ Cow1).
In the study, NEG was calculated as 3587.71 (MJ Cow1) and in a similar study NEG was calculated as 5480.22 (MJ Cow1) [19].
The share of direct input energy was 8.05% in the total energy compared to 91.95% for the indirect energy (Table 5). The results revealed that the non-renewable form of energy input was 98.59% on average, compared to 1.41% for renewable energy. Renewable energy sources are non-destructive energy sources that are constantly present. 98.59% of energy sources used for milk pro-duction is non-renewable energy.
Non-renewable energy sources are limited and many of these energy sources are environmentally damaging. Direct and indirect energies were calculated as 11,973 (8.11%) and 135,686 (91.89%) (MJ
Cow1) for dairy farms, respectively. Cost/benefit analysis was performed by taking variable and fixed cost components into consideration, including production costs and gross value for dairy enterprises separately(Table 6). Total production cost of investi-gated enterprises were 2457.24 $Cow-1 while gross production value (GPV) were 3302.08 $Cow1. The total production costs consisted of 72.02% variable costs and 27.98%fixed costs. Benefit/ cost ratio was 1.34. Net return were calculated as 884.84 $Cow1in the dairy enterprises.
3.2. Energy efficiency analysis in milk production
The limited resources in production should be used efficiently to ensure continuity of enterprises. The performance of production units is assessed by the efficiency or productivity of these units. The concepts of efficiency and productivity are interrelated, but they are quite different indicators.“Productivity” in production is the ratio of production quantity to input quantity.“Efficiency” is the differ-ence between optimum input-output quantities. Efficiency is an indication of the success of achieving the goal. The level of ef fi-ciency or inefficiency is measured by the difference between tar-geted and actual performance. Data envelopment analysis has been used for energy efficiency analysis. This method is commonly used in the literature and the efficiencies of the enterprises having more than one input and output can be calculated by this method. In this study, the energy efficiency of a number of enterprises has been analysed in terms of milk production. Efficiency measurements were made through DEA with a constant return to scale (CRS). Ef-ficiency values are divided into PTE (variable return to the
Table 3
Energy inputs and output equivalents for studied dairy cattle farms. Inputs/Outputs Energy Values (MJ Cow1) % A. Inputs 1. Direct Energy Diesel 860.15 1.75 Lubricants 76.12 0.16 Electricity 2319.43 4.73 Human Labour 690.05 1.41
Total Direct Energy 3945.75 8.05
2. Indirect Energy Machines 280.57 0.57 Concentrates 26,201.92 53.44 Maize Silage 3249.11 6.63 Alfalfa 1116.43 2.28 Hay (Straw) 14,235.63 29.03
Total Indirect En. 45,083.66 91.95
Total Energy Input 49,029.42 100.00
B. Outputs 1. Milk 47,175.41 89.66 2. PSV 2445.80 4.65 3. Cow manure 2995.92 5.69 Total Outputs 52,617.13 100.00 Table 4
Analysis of energy indices in milk production.
Indices Energy Values (MjCow1)
EUE 1.07 EP (kg MJ1) 0.13 SE (MJkg1) 7.42 Energy Intensity 0.93 Energy Intensiveness (MJ$1) 19.95 NEG (MJ Cow1) 3587.71 Table 5
Total energy input for milk production (MJ/Cow1).
Direct energya 3945.75 8.05
Indirect energyb 45,083.67 91.95
Renewable energyc 690.05 1.41
Non-renewable energyd 48,339.36 98.59
Total energy input 49,029.42 100.00
aIncludes human labour, diesel, lubricant, electric.
b Includes machinery, concentrates, maize silage, alfalfa, hay(straw). c Includes human labour.
d Includes diesel, lubricant, electric, machinery, concentrates, maize silage, alfalfa,
hay (straw).
Table 6
Economic analysis of milk production.
Cost items Unit Value
Variable costs $/Cow 1769.70
Fixed costs $/Cow 687.54
Total production costs $/Cow 2457.24
Milk Selling price $/kg 0.42
Milk yield kg/Cow 6607.20
Gross production Valuea $/Cow 3302.08
Gross profitb $/Cow 1532.38
Productivityc kg/$ 2.69
Net returnd $/Cow 884.84
Benefit/cost ratioe
e 1.34
In this study, 1 US$¼ 2.84 Turkish Liras calculated (approximately, in August 2015).
aGross production value¼ Milk yield (kg Cow1) x milk price ($kg1)þ
PSVþ Farm Manure.
b Gross profit ¼ Total Gross production value ($Cow1) e Total Variable costs
($Cow1).
c Productivity¼ milk yield (kg Cow1)/Total production costs ($ Cow1). d Net return¼ Total Gross production value ($ Cow1)e Total production costs ($
Cow1).
e Benefit/cost ratio ¼ Total Gross production value ($ Cow-1)/Total production
costs ($ Cow1). 146
scale¼ VRS) and SE in order to obtain more information from the measures. In the study, milk yield per total cow yield, PSV, fertilizer have been evaluated together and included as a single energy output variant. There were 9 different types of input energy con-sumption in the form input variables: labour, machine, diesel, lubricant, electricity, labour, feeds (concentrate, maize silage, al-falfa, straw). This data has been standardized by using daily values and quantities of output and inputs used per animal. The fact that the TE is equal to 1 indicates that the enterprise is on the border or that the operator has TE according to it [25]. In inefficient enter-prises, TE will be less than 1. In addition, in the efficiency analysis, enterprises with a TE coefficient between 0.95 and 1 were classified as efficient, those between 0.90 and 0.95 as less efficient and those below 0.90 as inefficient [26]. TE that shows whether enterprises operate effectively or not is divided into two subgroups as PTE and SE [48]. PTE indicates the effective use of inputs according to the variable return scale. For a specific production unit, TE values for constant return to the scale and variable return to the scale indicate that the production unit has scale inefficiency. TE (CRS) ¼ PTE (VRS) x SE [18,49].
According toTable 7, energy efficiencies are given in terms of total energy inputs and total output per dairy cow in the study area. The TE average of the enterprises has been calculated as 0,921. Accordingly, the amount of input needs to be reduced by 7.9% in order to achieve the same level of production. 56% of dairy farms are efficient in energy use per animal, 24.80% are less efficient and 19,20% are inefficient. In a similar study in Iran, the average TE, PTE and SE of farmers were calculated as 0.9, 0.94 and 0.953, respec-tively [43].
4. Conclusion
The purpose of this study was to calculate the energy usage per dairy cow in dairy farming enterprises in Konya province. This study is one of the rare studies that analyses EP in dairy product enterprises. Therefore, there are only a few comparable studies available in the literature. EUE has been calculated as 1.07 in this study, while Uzal [5] has calculated the same coefficient as 0.16 for different shelters related to dairy cattle, Frorip et al. [40]. reported it as 0.12, Unakıtan and Kumbar [50] reported it as 0.23 and Sefeed-pari [44] reported it as 0.26. EUE is higher in the study area when compared to other areas. However, one of the reasons for this higher value is the fact that output calculations have included PSV and animal manure rather than taking cow milk on its own.
The average milk yield was 6607.20 kg/Cow and the average energy input consumption per animal has been calculated. The average energy input was calculated as 49,029.42 (MJCow1) per cow and the energy output was calculated as 52,617.13 (MJCow1). The NEG has been calculated as 3587.71 (MJCow1) in this study and Sefeedpari et al. [44]. reported net energy productivity as 5480.22 (MJCow1).
When milk production is taken into consideration on its own, EP (kg MJ1) score has been calculated as 0.13 KgMJ1, Uzal [5] has
reported it as 0,05 and Sefeedpari et al. [44] as 0.12. SE indicates the energy consumption amount per product unit. In this study, SE (MJKg1) value has been calculated as 7.42 MJ and 7.42 MJ energy is required to produce 1 Kg of milk. According to Unakıtan and Kumbar [50] the requirement is 13.65 while Uzal [5] reported it as 3, Frorip et al. [41]. as 5.35, Wells [33] as 1.84 and Hartman and Sims [45] as 3.9. These values indicate that energy is used efficiently in the area and the enterprises have sound production systems and their technology usage levels are high. The innovation index of dairy enterprises in Konya region is 57.50% [17,18]. The energy ef-ficiency of the diary enterprises in the region is good enough, however, it would still be beneficial to improve their resource usage efficiencies to make it even better and to create awareness. Furthermore, new agricultural policies need to be developed to encourage efficiency in input usage in livestock enterprises.
The highest energy consumption was indirect energy 91.95% and direct energy consumption level was 8.05%. Renewable energy was 1.41% while non-renewable energy consumption was 98.59%. 92.68% of non-renewable energy consumption was concentrated feed, maize silage, alfalfa and straw. Non-renewable energy re-sources are not only limited but most of them are also harmful for the environment.
There is no other reference in the literature on measuring en-ergy usage efficiency of milk production by DEA method. In this aspect, this study is also measuring the difference between opti-mum input-output amounts, in addition to energy efficiency, by using the energy equivalents of all input and outputs. This study has concluded that having a TE equal to 1 in DEA analysis indicates that the enterprise is above the limit. And according to Farrell (1957) [25], this indicates that the enterprise has technical efficiency (TE). Hence, the regional technical efficiency (TE) average of the enter-prises has been calculated as 0.921. In accordance, the input amount has to be reduced by 7.9% to achieve the same level of production. The meaning of this is that an enterprise could have a low energy efficiency despite having technical efficiency and vice versa. It will be contributing to the literature in both cases. In the study area, 56% of the dairy enterprises were effective in energy usage per cow, 24.80% were less-effective and 19.20% were non-effective. Bandbafha et al. [43] have calculated it respectively as 0.9, 0.94 and 0.953. The important thing at this point is the fact that new policies need to be developed to help farm owners to have more effective use of energy and also to manage the process better. Furthermore, if the non-effective and less-effective enterprises adopt the administrative practises of productive and effective en-terprises, there is a possibility of making an energy saving of around 1475.02 MJCow1without making any changes in the output level. The highest level of energy saving in milk production can be ach-ieved from coarse feed and concentrate feed consumption. There-fore, it can be sad that DEA approach is possibly a beneficial tool to enlighten the non-productive enterprises and to help themfind the reasons behind the inefficiency. Furthermore, increasing energy savings and productivity in dairy enterprises can be achieved only by adopting new technologies and implementing them in
Table 7
Average technical, pure and scale efficiency of dairy farms. Farm Size Groups (Head) Nu. of Businesses Technical
Efficiency Total Technical Effi. Pure Technical Effi. Scale Effi.
Effici ent Less Effici ent Inefficient Total
0e50 72 0.894 0.894 1 0.894 32 16 24 72 51e150 38 0.952 0.952 1 0.952 24 14 e 38 151-þ 15 0.974 0.974 1 0.974 14 1 e 15 Avg. 125 0.921 0.921 1 0.921 70 31 24 125 Oran (%) 56.00 24.80 19.20 100.00 147
workplace. In this sense, the inefficient enterprises need to be trained and the successful ones need to be acknowledge to encourage them even more.
It is also useful to implement a good management strategy in enterprises for economic, environmental and energy analysis of a production system. Energy management in enterprises should be considered as an important area in terms of efficient, sustainable and economical energy use. The use of energy in milk production is not very efficient, usually due to animal feeding, lubricant, diesel and electricity input. All these measurements will be useful not only to ensure sustainability and reduce production costs, but also to ensure higher energy use efficiency.
Therefore, it is necessary to promote the development of new technologies and encourage the use of alternative energy sources in livestock enterprises.
Acknowledgement
This study has been supported by Selcuk University, Scientific Research Fund (BAP) Project No: 15401020. We would like to thank Selcuk University Scientific Research and Projects Coordination Unit for thefinancial support they granted to this project. References
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