The Effect of Awareness of Renewable Energy Resources on Sustainable Production in Dairy Farming: The Case of Konya Province (Turkey)

Abstract

In this study, the effect of awareness of renewable energy sources on sustainable production in dairy farming was determined. One hundred thirty-six surveys were conducted in the research area. Multiple linear regression analysis was used to determine the effect of awareness of renewable energy resources of dairy cattle farms on sustainable production. According to the results of the analysis, the number of animals, land assets, and age of farmers were found to be statistically significant at a 5% significance level. Awareness of renewable energy sources, environmental factors, and economic factors were found to be significant at a 10% significance level. Therefore, biogas should be converted into electricity. In order to provide waste management, organization should be ensured, and animal waste collection centers should be established.

1. Introduction

Agriculture is the only sector that meets the food needs of people [1]. Sustainable development is needed for the continuity of agricultural production. The emergence of the concept of sustainable development represents the most serious social and political attempt to change how humanity views its relationship to the world of which it is a part [2]. Mill’s stage theory is quite influential in development studies. However, today, with the COVID-19 pandemic and economic crisis, new development problems have emerged. Therefore, we need to examine the fundamental questions and understandings of Adam Smith’s classical political economy in particular. We must also look at the traditions that led to Karl Marx’s critique of the political economy [3]. “Sustainable agriculture” is needed to meet current and future societal needs [4]. The idea of sustainable agriculture gained importance with the Brundtland Report in 1987. However, the concept of sustainable agriculture is very vague. This vague situation makes the use and application of the concept extremely difficult [5]. Sustainable agriculture is an integrated system of crop and animal production specific to a particular area and will provide some benefits in the long term. These benefits are (a) meeting the food needs of people; (b) improving the quality of the environment; (c) using non-renewable resources and on-farm resources efficiently and ensuring natural biological cycles; (d) ensuring the economic sustainability of farms; and (e) improving the quality of life of farmers and society [6]. Sustainable agriculture is an alternative to solve fundamental and practical problems related to food production in an ecological way [7]. It is an approach that aims to balance environmental, social, and economic dimensions in agricultural production. The two most important global concerns affecting sustainable development today are the energy crisis and environmental degradation [8]. Various stresses on our natural resources have contributed to the current energy crisis. The energy crisis summarizes global issues such as circular economy, sustainable development, and agricultural waste management [9]. The objectives of sustainable agriculture are to increase productivity in agriculture, reduce environmental damage, improve the self-confidence and capacity of farmers, reduce the use of non-renewable energy resources, keep the economy alive in the short and long term, eliminate marketing problems, provide reliable products to consumers, and increase the welfare level of those engaged in agriculture [10,11,12,13]. In this context, sustainable management of resources is important for economic, social, and environmental development. Sustainable agricultural systems are designed to maximize the benefits of existing soil nutrient and water cycles, energy flows, beneficial soil organisms, and natural pest controls [1]. Efficient energy use is crucial for sustainability in agriculture [14,15,16]. The balance between energy demand and the economy plays an important role in sustainable agriculture goals. Energy demand is also increasing rapidly due to population growth, economic and technological development, urbanization, and climate change. It is predicted that the world’s energy demand will increase by 50% by 2050 [17]. Energy is an indispensable part of our daily lives. According to global reports, not only is there an ever-increasing demand for energy around the world, but communities and households in underdeveloped and developing countries still lack access to basic energy services such as electricity, liquid fuels, and natural gas [18]. About 1.5 billion people in the world (more than 20% of the world’s population) do not have access to electricity, and about 3 billion people (about 45% of the world’s population) depend on solid fuels such as wood, coal, crop residues, and cattle manure [19]. Energy in agriculture is important for crop production, agricultural processing, and added value of products. In agriculture, human, animal, and mechanical energy are used intensively in crop production. Energy use and consumption in the agricultural sector is divided into direct and indirect energy consumption. Direct energy consumption is the use of various fossil fuels. For example, agricultural inputs include land preparation, irrigation, and harvesting. Indirect energy consumption refers to the energy consumed during the production and transportation of farm inputs and outputs. For example, energy is used in the manufacture, packaging, and transportation of fertilizers, pesticides, seeds, and agricultural machinery [1,20].

By ensuring sustainability in animal production, environmental, economic, and social sustainability will also be improved [21,22]. The dairy industry is a vital component of the food and agriculture sector, as it ensures the consumption of milk and dairy products by the population, which occupies an important place in their daily dietary intake [23]. Dairy farms cause significant increases in total GHG emissions throughout the life cycle of milk and other dairy products [24,25]. In particular, this is due to direct methane gas (CH4) produced by dairy cattle during digestion and manure management, as well as indirect GHG emissions related to energy consumption [26]. In an assessment of GHG emissions from the liquid milk supply chain, it was found that 72% of the emissions originate from the milk farm [27]. Digested manure emits less CH4 during storage than undigested manure because it contains less carbon and volatile solids [28]. The lack of manure management in dairy farming and intensive fossil-based energy consumption in the sector is one of the main contributors to climate change [29]. Renewable energy production from manure is crucial for dairy farm sustainability [30,31]. Energy consumption in the dairy sector is driven by the direct consumption of various fossil fuels, electricity, and wood [20]. Energy security and the depletion of fossil fuel resources have supported the advancement of sustainable and renewable technologies using cheap or zero-cost biomass. Renewable energy sources are technologies that consume primary energy resources that are not subject to depletion. Examples of renewable technologies include solar energy, wind energy, geothermal energy, and biomass. Given this definition and the fact that water resources are replenished in the annual hydrological cycle, hydropower is considered part of the mix of renewable technologies [32]. With renewable energy, liquid or gaseous biofuels are produced, greenhouse gas emissions are reduced, and energy security is ensured [33]. Renewable energy sources contribute to the sustainability of dairy farms while also providing significant monetary advantages [34]. Investing in renewable energy technologies can increase farmers’ financial returns while accelerating the transition to sustainable development [35]. In this study, the effect of awareness of renewable energy resources on sustainable production in dairy farming was determined for Konya province, which accounts for 6.17% of Turkey’s milk production and ranks first in milk production.

2. Materials and Methods

The study was conducted in Konya province, which has the highest milk production in Turkey. In the study, Konya Province Ministry of Agriculture and Forestry records were used to determine the population. The districts to be surveyed in the research region were selected as Ereğli, Karapınar, and Meram districts, which constitute 36.87% in terms of number of animals and 35.36% in terms of milk production [36]. The main framework of the research consists of 8738 dairy farms in these three districts. Since the distribution of the number of animals in the districts is heterogeneous, the sample volume was selected according to the Neyman Method from the Stratified Random Sampling Method. Neyman’s “Stratified Random Sampling Method” was used to calculate the sample volume. Stratified sampling means dividing the population into strata and selecting samples within these groups using a simple random sampling method [37]. There are three main stages used in stratified sampling. The population is divided into homogeneous but heterogeneous strata. An independent sample is selected from each stratum. An estimate is obtained for the population parameter [38].

$$n={\displaystyle \frac{{\left[\sum (N_n\times S_h)\right]}^2}{N^2\times D^2+\sum \left[(N_h\times {\left(S_h\right)}^2\right]}}$$

$D$ ² = d/z

In the formula,

• n: number of samples,
• N: Number of establishments in the main population,
• Nh: Number of establishments in the hth stratum (frequency),
• Sh: Standard deviation of the hth stratum,
• d: Allowable margin of error from the main population mean,
• z: Refers to the z value in the standard normal distribution chart according to the error rates. If the number of units is over 30, the z value is used in the t distribution [39].

The sample size was determined as 136 with a 95% confidence interval and 5% margin of error. The distribution of the samples to the strata was performed using the following formula [38,39].

$$n_i={\displaystyle \frac{\left(N_h\times S_h\right)\times n}{\sum N_h\times S_h}}$$

As a result, the number of sample enterprises according to the enterprise size groups (number of animals) of the enterprises in the research region is given in

Table 1. Method used in sampling of dairy cattle farms.

Enterprise Groups (Number of Cattle (Head))	Number of Units in Strata (Nh)	Standard Deviation (Sh)	Nh ∗ Sh	Nh ∗ (Sh)2	Sample Volume (n)	Number of Surveys (Number)
6–20	3675	4.31	15,838.29	68,259	17.07	17
21–50	2867	8.38	24,028.99	201,393	25.90	26
51–150	1751	25.51	44,673.93	1,139,783	48.15	48
151–+	445	94.11	41,878.77	3,941,194	45.13	45
Total	8738	132.31	126,419.97	5,350,628	136.25	136

.

Enterprise sizes were examined by organizing them in various strata, and it was deemed appropriate to form 4 strata by taking frequency distributions into consideration. The boundaries of these strata were determined as enterprises with 6–20 heads, 21–50 heads, 51–150, and 151 heads or more of cattle.

The socio-demographic characteristics of dairy cattle farms in the research region were determined. Gross production value, changing costs, and gross profit analysis were calculated as an economic analysis of dairy cattle farms. The gross production value was determined separately for crop and animal production. In crop and animal production, the value of production sold and consumed was calculated [40,41].

Changing costs were calculated separately for both crop production and animal production. Changing costs for crop production include seed, seedling, fertilizer, medicine, fuel oil, oil, repair and maintenance, temporary workers, machine rent, water fees, crop insurance, marketing, etc. For animal production, costs such as animal purchase and sale costs, concentrate and roughage costs, non-permanent shepherd costs, medicine costs, artificial insemination and vaccination costs, animal insurance costs, marketing costs, etc., were taken as variable cost elements [40]. Gross profit is calculated by subtracting the variable costs calculated for these production activities from the sum of crop and animal GDP [41].

Renewable energy sources used in dairy farms will be determined with a 5-point Likert scale. In dairy farming enterprises, solar, wind, biomass energy, geothermal, hydroelectric, and waste management will be discussed as renewable energy sources. The Likert scale was developed by Rensis Likert (1932) to measure the attitudes, tendencies, and opinions of individuals and groups. Likert-type questions contain options that examine the attitudes and behaviors of individuals or groups on the subject under investigation and indicate the level of participation [42]. The 5-point Likert scale used in determining the factors affecting the sustainability of milk production and the level of knowledge of farmers about renewable energy was created as 1: Strongly disagree, 2: Disagree, 3: Undecided, 4: Agree, and 5: Strongly agree. The 5-point Likert scale used in the implementation situation of farmers was created as 1: Never heard of it, 2: I don’t know, 3: I know, 4: I sometimes implement, and 5: I definitely implement.

Multiple linear regression analysis was used to determine the effect of awareness of renewable energy resources on the sustainable production of dairy cattle farmers. In the analysis, regression models based on the Least Squares (LS) method, which minimizes the sum of error squares, were used. Stepwise selection analysis was used, which adds the independent variables to the model one by one and selects the most compatible model that performs addition and elimination processes by taking into account the partial correlations between both independent variables and the dependent variable [43,44,45]. Multiple linear regression analysis is a statistical analysis that shows the relationship between a criterion variable and one or more predictor variables [46]. The simple linear regression equation for mass is where Y is the dependent variable, X1 is the independent variable, β1 is the unknown parameter of this variable, and εi is the unobserved error term.

Y = β + β Xi + ε, i = 1, 2, …, n is written in the form.

Milk production sustainability was taken as the dependent variable in the regression analysis. The Likert scale was used to calculate milk production sustainability. An index was created for Likert scale questions asked to farmers about milk production sustainability.

$${index}_{\mathrm{s}\mathrm{u}\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{i}\mathrm{n}\mathrm{a}\mathrm{b}\mathrm{i}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}}={\displaystyle \frac{\sum _{k=1}^n\left(\right(MPS)\ast ISF)}{\sum _{k=1}^n\left(\right({MPS}_k)\ast MaxP)}}\ast 100$$

• ${index}_{\mathrm{s}\mathrm{u}\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{i}\mathrm{n}\mathrm{a}\mathrm{b}\mathrm{i}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}}$: Milk Production Sustainability Index;
• (MPS_k): n Sustainable Production questions (1, 2, 3, …, n number of indicators);
• ISF: Implementation Status of Farmers (1: Never heard of it, 2: I don’t know, 3: I know, 4: I sometimes implement, 5: I definitely implement);
• MaxP: The maximum score (5) that can be obtained in the current implementation situation [47].

Independent variables were land holding (da), livestock holding (cow-head), age, renewable energy awareness, and economic, social, and environmental dimensions of sustainability.

Factor analysis was performed on 11 Likert scale questions to measure renewable energy awareness. In the study, “Confirmatory Factor Analysis (CFA)” was conducted on 11 Likert scale questions. Confirmatory Factor Analysis measures whether a previously used scale fits the original factor structure when used in the current research, and if so, to what extent [48]. Factor analysis divides a large number of variables into groups, maximizing the relationship between variables within each group and minimizing the relationship between groups. The Bartlett’s test and Kaiser–Meyer–Olkin (KMO) test were performed in the study. Bartlett’s test requires that the data come from a multiple normal distribution, while the KMO test measures sample adequacy and tests sample size [49]. As a result of factor analysis, 2 factors were obtained. These factors were named as awareness of renewable energy resources and the need for incentives and support for renewable energy resources. Multiple linear regression analysis and factor analysis were conducted in SPSS-15. Additionally, in the research, 1 dollar was taken as 30.72 TL.

3. Results

The relationship between renewable energy sources and farmers’ land use has been examined in many studies [50,51,52,53]. Gross production value, variable costs, and gross profits of dairy cattle enterprises are given in

Table 2. Farmers’ GDP, Changing Expenses, and Gross Profit Value (USD).

	1. Group	2. Group	3. Group	4. Group	Enterprises Average
Animal Production Value (USD)	28,561.27	82,467.52	224,188.99	624,439.35	305,077.49
Crop Production Value (USD)	30,423.31	50,913.07	42,324.13	115,171.52	66,582.44
Total GDP (USD)	58,984.58	133,380.59	266,513.11	739,610.87	371,659.94
Animal Production Changing Costs (USD)	29,899.53	84,005.81	169,085.64	475,925.63	236,950.05
Crop Production Changing Costs (USD)	11,144.28	23,510.27	31,376.43	57,406.14	35,956.36
Total Changing Costs (USD)	41,043.81	107,516.08	200,462.07	533,331.77	272,906.41
Gross Profit (USD)	17,940.77	25,864.51	66,051.04	206,279.10	98,753.53

. According to Table 2, the average number of cows of farmers is 109.82 heads. It is 10.41 heads in the 1st group enterprise, 44.66 heads in the 2nd group enterprise, 80.77 heads in the 3rd group enterprise, and 224.67 heads in the 4th group enterprise. The average animal production value of farmers in the research area is USD 305,077.49. Feed costs constitute the highest item among the variable costs of animal production. This cost is followed by veterinary and medicine-vaccine costs, water-salt-vitamin costs, electricity-heating costs, animal insurance costs, fuel costs, tax costs and other expense items. In the research area, corn is produced by 33.26% of the farmers, sunflowers by 19.34%, beets by 14.86%, wheat by 13.55%, alfalfa by 12.86%, barley by 4.07%, and vetch by 2.05%. In the research area, farmers obtain the highest crop production value from maize plants. Maize is followed by sunflowers, alfalfa, and beets. Of the variable costs, 26.57% were labor costs, 22.72% were water costs, 14.86% were fuel costs, 12.11% were fertilizer costs, 8.52% were seed costs, 7.68% were pesticide costs, 1.98% were electricity costs, and 5.55% were other costs.

According to Table 2, the average gross profit value of farmers is USD 98,753.53. In order for farmers to adapt to innovations, their agricultural production capacity and agricultural income are very important [54]. Innovations in agriculture have played crucial roles in economic development worldwide [55].

In recent years, the world’s population has increased with rapid industrialization, leading to various serious concerns about the environmental crisis [33,56]. These concerns include pollution and global warming, as well as sustainable food and energy supplies [57,58]. As the world population, urbanization, and climate change impacts are increasing daily, demands on the global food and energy sector have increased. This has led to radical changes in meeting these demands [59]. Food production and supply accounts for 15%-20% of total energy consumption [60]. Fossil fuel resources, including crude oil and its derivatives, coal and natural gas, represent the world’s major energy sources. Energy use in agriculture has been a priority for many years. Studies on the efficient use of energy started with the oil crisis in 1970. Subsequently, studies have increased day by day due to the increase in energy prices [29]. Figure 1 shows the status of farmers’ knowledge, use, and support of renewable energy in agricultural production.

According to the table, 69.85% have information about renewable energy sources. As for the use of renewable energy in agricultural production, 19.85% of them use it. When the status of receiving support from the government on renewable energy is analyzed, none of the farmers received support. The use of renewable energy in the research region is low. Therefore, the renewable energy supply situation in the region is low. To address energy demand challenges, two main solutions were proposed in similar studies. The first recommendation is the use of more efficient energy and technologies [61]. The second is to utilize various renewable energies [62,63]. In other words, reducing dependence on fossil fuels means using renewable energy sources instead of fossil fuels. For example, increasing the share of alternative energy sources such as solar, wind, or bio-energy [64,65,66].

Table 3. Renewable energy types in the research region and their usage status according to the purposes of the farmers in the region.

		1. Group	2. Group	3. Group	4. Group	Enterprises Average	%
Solar energy	I use it in electricity generation.	0.00	0.08	0.00	0.11	0.05	0.00
	I use it for storage.	0.00	0.04	0.02	0.00	0.01	0.00
	I use it in natural lighting.	0.06	0.04	0.00	0.00	0.01	5.88
	I use it for preheating and heating.	0.06	0.04	0.06	0.00	0.04	5.88
	I use it for water works.	0.00	0.04	0.08	0.07	0.06	0.00
Geothermal energy	I use it for greenhouse heating.	0.00	0.00	0.00	0.00	0.00	0.00
	I use it in my animal shelter.	0.00	0.00	0.00	0.00	0.00	0.00
	I use it for soil heating.	0.00	0.00	0.00	0.00	0.00	0.00
	I use it to dry my products.	0.00	0.00	0.00	0.00	0.00	0.00
	I use it for soil reclamation.	0.00	0.00	0.00	0.00	0.00	0.00
	I use it in agricultural production.	0.00	0.00	0.00	0.00	0.00	0.00
Biomass Energy	I use it in electricity generation.	0.00	0.00	0.02	0.00	0.01	0.00
	I use it for space heating and cooling.	0.00	0.00	0.00	0.00	0.00	0.00
	I use it for water heating and water cooling.	0.00	0.00	0.00	0.00	0.00	0.00
	I also use biodiesel fuel.	0.00	0.00	0.00	0.00	0.00	0.00
Wind power	I use it in electricity generation.	0.00	0.00	0.00	0.00	0.00	0.00
	I use it for mechanical strength.	0.00	0.00	0.00	0.00	0.00	0.00
	I use it for irrigation.	0.00	0.00	0.00	0.00	0.00	0.00
Hydroelectric Energy	I use it in electricity generation.	0.00	0.04	0.00	0.00	0.01	0.00
	I use it for irrigation.	0.00	0.04	0.00	0.00	0.01	0.00
Waste Management	I use it in animal manure.	0.24	0.23	0.27	0.69	0.40	23.53
	I contribute to the conversion of agricultural waste into biochar.	0.00	0.00	0.00	0.00	0.00	0.00

shows the utilization status of farmers according to renewable energy types and purposes.

According to the table, among alternative energy sources, waste management is the most used renewable energy source in the research area. Farmers in the research area use animal manure (23.53%) as waste management. Waste management is followed by solar energy. Solar energy is used for natural lighting (5.88%) and preheating and/or heating (5.88%).

According to

Table 4. Economic, social, and environmental factors affecting sustainability.

		1. Group	2. Group	3. Group	4. Group	Enterprises Average
Economic	If milk production is supported by plant production, income will increase further.	4.47	4.42	4.56	4.67	4.56
	Using the obtained farm manure in crop production will create an alternative source to chemical fertilizers and increase the income level.	4.53	4.5	4.48	4.6	4.53
	The use of renewable energy sources in milk production increases the income level	4.35	4.58	4.31	4.33	4.38
	Adoption of dairy production renewable energy source is very costly	3.88	4.31	4.19	4.36	4.23
	Dairy production waste management costs are high	4.12	3.96	4.06	4.36	4.15
	Milk production is more income-generating than alternative production	3.65	3.62	3.67	3.87	3.72
	The economic income of milk production is high	3.82	3.35	3.58	3.69	3.60
	I have the potential to establish a renewable energy source	1.94	2.77	3.25	3.6	3.11
	Milk production supports are sufficient	2.65	2.27	2.52	2.62	2.52
Social	Thanks to the use of renewable energy in milk production, income will increase and people will go beyond their needs for food and shelter.	4.18	4.42	4.44	4.64	4.47
	Thanks to waste management in milk production, people’s social areas will be cleaner.	4.12	4.54	4.42	4.69	4.49
	Renewable energy in milk production will facilitate the living spaces of farms	4.41	4.31	4.42	4.53	4.43
	The welfare level will increase when biomass obtained from dairy cattle is used as fuel.	4.24	4.38	4.27	4.38	4.32
	I encourage people around me to use renewable energy.	4	4.38	4.33	4.29	4.29
	Social facilities in the region are sufficient for the use of renewable energy	3.12	3.42	2.88	2.51	2.89
Environmental	Waste management in milk production makes a positive contribution to the environment	4.35	4.35	4.35	4.53	4.41
	Using renewable energy sources in milk production is environmentally friendly	4.24	4.46	4.38	4.33	4.36
	Using the obtained farm manure in plant production will provide an alternative source to chemical fertilizers and protect the environment from chemical contamination.	3.94	4.35	4.31	4.4	4.3
	Renewable energy source compared to fossil sources	4.29	4.15	4.25	4.44	4.3
	Appropriate storage method should be used to reduce methane gas emissions of the obtained farm manure.	3.94	4.27	4.1	4.27	4.17
	Milk production causes methane gas emissions.	3.47	3.62	3.42	3.78	3.58
	Environmental conditions in the region are sufficient for renewable energy installation.	2.59	3.15	3.13	4.56	3.54

(5: Strongly agree, 4: Agree, 3: Undecided, 2: Disagree, 1: Strongly disagree).

, economic, social, and environmental factors affecting sustainability are analyzed. There are many views on the conceptualization of sustainable agriculture in the literature. However, it is generally emphasized that the concept of sustainability has multidimensional characteristics that cover economic, environmental, and social aspects [67,68,69,70,71,72,73,74,75,76,77,78]. According to Table 4, it was determined that they agreed with the factors of economic factors, such as if milk production is supported by plant production, income will increase even more, and the use of the obtained farm manure in plant production will create an alternative source to chemical fertilizers and increase the income level. When social factors were examined, it was determined that they agreed with five factors. When environmental factors were examined, it was determined that they participated in all factors.

Table 5. Factor analysis of producers’ renewable energy knowledge levels.

Factors	Scale Items	Factor Loadings	Ort. Mean	Standard Deviation	Variance Ratios	Cronbach Alpha Coefficients
The need for encouragement and support about renewable energy sources	Tax exemption is required due to the high maintenance cost of the renewable energy system.	0.764	4.5588	0.80521	37.856	0.882
	Renewable energy sources contribute to the improvement of the economy.	0.734	4.6838	0.65209
	Subsidies are required for the purchase of a renewable energy system.	0.722	4.4265	0.75653
	Tax exemption is required due to the high installation costs of renewable energy systems.	0.704	4.4926	0.77933
	Renewable energy sources are more profitable than other energy systems.	0.650	4.6103	0.67957
	Renewable energy sources are important for agricultural production.	0.640	4.6912	0.60264
	It should support pilot demonstration projects for all types of renewable energy technologies.	0.628	4.5147	0.73015
	Subsidies are required for renewable energy system maintenance.	0.610	4.4044	0.80165
	Information about renewable energy should be included in secondary and post-secondary education curricula.	0.584	4.3824	0.95109
Awareness of renewable energy sources	The need for encouragement and support about renewable energy sources	0.884	4.7353	0.65812	22,064	0.827
	Awareness of renewable energy sources	0.866	4.7132	0.66564
Cumulative Value						59.920
	Kaiser–Meyer–Olkin Bartlett’s Test of Sphericity					0.854
	Chi-square Value					762.590
	df					55
	p					0.000

shows the renewable energy knowledge levels of agricultural production enterprises. Factor analysis was performed on 11 variables representing renewable energy knowledge levels. As a result of the factor analysis, two groups were identified. These groups were named “The Need for Encouragement and Support about Renewable Energy Sources” and “Awareness of Renewable Energy Sources”.

One of the key food sectors that is highly vulnerable to the challenges of increasing demand and the impact of climate change is the dairy sector [79]. The impact of climate change on the dairy sector is predominantly threefold. First, although the effects of global warming are not negative everywhere, drought events are expected to increase worldwide, affecting crop yields and consequently reducing production [80].

Secondly, increasing temperatures can cause heat stress in cows, which can lead to reduced milk production and increased risk of mortality [81]. Finally, food safety concerns will arise as a result of foodborne pathogens adapting to global warming, where heat resistance and survival and/or reproduction rates may change [59].

Therefore, factors affecting milk production sustainability were identified in the field of research.

Table 6. Descriptive statistics of factors affecting milk production sustainability.

	Range	Minimum	Maximum	Mean	Std. Deviation	Variance
Milk Production Sustainability Index	0.80	0.20	1.00	0.8141	0.19773	0.039
Land Asset (Decar)	3010.00	0.00	3010.00	216.7463	371.70849	138,167.204
Animal Asset (Head)	595.00	5.00	600.00	109.8235	94.74894	8977.361
Age	57.00	18.00	75.00	47.5735	12.47910	155.728
Economic	2.67	2.33	5.00	3.8663	0.65565	0.430
Social	2.67	2.33	5.00	4.1496	0.65012	0.423
Environmental	2.57	2.43	5.00	4.0943	0.58780	0.346
The need for encouragement and support about renewable energy sources	8.46843	−5.09871	3.36973	0.0000000	1.00000000	1.000
Awareness of renewable energy sources	8.17149	−6.23434	1.93715	0.0000000	1.00000000	1.000

shows the descriptive statistics of the factors affecting milk production sustainability.

Table 7. Factors affecting milk production sustainability.

	Unstandardized Coefficients		Standardized Coefficients	t	Sig.	VIF
	B	Std. Error	Beta
(Constant)	0.119	0.151		0.789	0.432
Land Asset (Decar)	0.000	0.000	−0.222	−2.588	0.011 *	1.341
Animal Asset (Head)	0.000	0.000	0.227	2.593	0.011 *	1.394
Age	0.003	0.001	0.173	2.258	0.026 *	1.068
Economic	0.051	0.030	0.168	1.704	0.091 *	1.781
Social	0.023	0.030	0.077	0.786	0.433	1.746
Environmental	0.060	0.031	0.178	1.948	0.054 *	1.524
The need for encouragement and support about renewable energy sources	0.021	0.016	0.105	1.341	0.182	1.122
Awareness of renewable energy sources	0.030	0.016	0.154	1.963	0.052 *	1.121

R Square: 0.304. P: 0.000. F: 6920. Durbin Watson: 1.676. * p < 0.05.

shows the analysis of factors affecting milk production sustainability. The ratio of independent variables explaining the dependent variable is 30.40%. In the linear regression analysis, the dependent variable was the “Milk Production Sustainability Index”. The independent variables were land assets, animal assets, age, economic factors, social factors, environmental factors, the need for encouragement and support about renewable energy sources, and awareness of renewable energy sources.

According to the results of the analysis, the number of animals, land assets, and age of farmers were found to be statistically significant at a 5% significance level for milk production sustainability (Table 7). As the land and animal stock of dairy farms in the research region increases, milk production sustainability will increase. At the same time, milk production sustainability will increase as the age of farmers increases. Awareness of renewable energy sources, environmental factors, and economic factors were found to be significant at a 10% significance level. As the land and animal stock of dairy cattle farms in the research region increases, milk production sustainability will increase. At the same time, milk production sustainability will increase as the age of farmers increases. As the awareness of renewable energy sources of dairy farms in the research region increases, milk production sustainability will increase. Again, according to the analysis results, milk production sustainability will increase as awareness of environmental and economic factors increases.

4. Discussion and Conclusions

To ensure the sustainability of milk production, farmers’ age, animal wealth, land wealth, awareness of renewable energy sources and sensitivity to environmental and economic factors affecting the sustainability of milk production were investigated. The use of renewable energy sources by farmers in the research area is low. When the status of receiving support from the government on renewable energy is analyzed, none of the farmers received support. For the research area, Konya province, state support for renewable energy use is very important. Renewable energy policies should be encouraged for Konya province, which accounts for 6.19% of Turkey’s total milk production and ranks first in milk production. Awareness and use of renewable energy sources are extremely important in ensuring sustainability in milk production for the research area. However, solar energy and waste management are relatively high. In order to prevent greenhouse gas emissions from dairy farming, fossil fuels should be replaced by biogas conversion to electricity [82]. Another way to reduce the use of fossil fuels and greenhouse gas emissions is the use of photovoltaic system (PV) technology that converts solar energy into electricity. Milking, pumping, and cooling milk are daily activities that require electrical appliances and consumption. In the study, when the changing costs of animal production are analyzed, it is seen that 21.98% of them are electricity costs. PV technology generates electricity directly from solar energy, does not contain fossil fuels, and saves energy consumption and greenhouse gas emissions during operation [83,84]. The PV system represents a promising source of electricity generation in dairy farms. Thus, the dairy farm becomes a producer of electricity instead of a consumer of electricity and will reduce CO₂ emissions with less damage to the environment [84,85]. In recent years, the worldwide movement towards renewable energy sources has led the dairy industry to move away from dependence on fossil fuels and to adopt environmentally friendly policies [29]. In order to ensure waste management, organization should be ensured, and animal waste collection centers should be established.