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    Energy and Profitability Analysis of Dried Apricot Production in Terms of Sustainability: A Case Study for Turkey
    (Springer, 2023) Ucar, Kubilay; Engindeniz, Sait; Oruk, Gorkem
    The aim of this study was to analyze the energy and profitability of dried apricot production in terms of sustainability. The study was carried out in the Malatya province of Turkey. The samples of the study were 65 apricot farmers that were determined by the proportional sampling technique. The data collected belonged to the production period of 2019-2020. In the study, socio-economic characteristics of farmers were put forward, energy input-output analysis and economic analysis of dried apricot production were performed. According to the results for dried apricot production, total energy input, energy output, energy output/input ratio, energy productivity, specific energy, energy intensiveness, and net energy were determined to be 14,928.12 MJ, 28,794.44 MJ, 1.93, 0.14 kg MJ(-1), 6.90 MJ kg(-1), 7.65 MJ $(-1) and 13,866.32 MJ, respectively. Net profit obtained for apricots was calculated to be 2604.41 $ ha(-1). The most important criterion for the growing decision of apricot farmers was apricot yield.
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    Öğe
    Forecasting Pistachio Production in Turkey: A Comparison of ARIMA, Grey, and Exponential Smoothing Models
    (Univ Philippines Los Banos, 2022) Oruk, Gorkem
    This research aims to forecast pistachio production in Turkey using the Auto-Regressive Integrated Moving Average (ARIMA), the grey model (G.M. (1,1)), and Exponential Smoothing (Holt's and Brown's) models. The Food and Agriculture Organization provided the annual statistics on pistachio production in Turkey from 1961 to 2019, which was used in this study. Pistachio production is expected to increase between 2020 and 2030. The mean absolute error (MAE), root mean square error (RMSE), and the mean absolute percentage error (MAPE) statistics were used to assess the performance of the models. The G.M. (1,1) model was found to be significantly better than other models, and it was used to make future predictions. Results showed that the forecasted production value for 2020 was 157.80 thousand tons, rising to 302.86 thousand tons in 2030. Pistachio production is expected to increase during the next ten years.
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    Measurement of Input Usage Efficiency in Cotton Production in Diyarbakir Province, Turkey
    (Univ Fed Rural Pernambuco, Dept Administracao, 2020) Oruk, Gorkem
    This study aimed to measure the technical efficiency for cotton farms in Diyarbakir province in Turkey. Technical efficiency scores of cotton farms were calculated with Data Envelopment Analysis (DEA), which is a linear programming method of non-parametric. The sample for this study was 134 cotton farms in Diyarbakir province of Turkey selected using the proportional sampling method. Data collection was carried out following 2017-2018 growing seasons. Data were collected through a survey using questionnaire. The data were analysed by using basic descriptive statistics, Kolmogorov Smirnov test, Pearson correlation analysis, independent t-test, Mann Whitney U test, Correlation analysis, Tobit regression, and data envelopment analysis models. In the DEA analysis, size of cotton production area (ha), machine and human labour (h), N-P-K fertilizer (kg), pesticides (litres), fuel (litres), seeds (kg) and number of irrigations are used as input parameters whereas cotton yield (kg) is used as output parameter. The study results revealed that the scale efficiency score of cotton farms in Diyarbakir was 0.89 on average and ranged from 0.53 to 1.00. Additionally, cotton farms in the studied area could reduce their inputs by 3% and still produce the same level of cotton output. The Tobit analysis results showed that factors such cotton yield, N and K fertilizers have a positive effect on efficiency, whereas land size, P fertilizers, pesticides, machine, fuel, labour and seed have a negative effect on efficiency. The results imply that by improving knowledge of farmers about input usage and modern techniques of cotton production may increase technical efficiency. Also, policy makers should focus on technical training programs about input usage and improving production management.
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    Measurement of technical efficiency in cotton production in Batman Province, Turkey: a comparison of DEA and SFA
    (Univ Fed Rural Pernambuco, Dept Administracao, 2022) Oruk, Gorkem; Baran, Mehmet Firat
    This paper uses data envelopment analysis and stochastic frontier analysis to estimate technical efficiency of cotton production in Batman, Turkey. Full counting method was used for sampling. Data were collected on a sample of 64 cotton farmers in the production period of 2019/2020. Data on inputs such as land (ha), seeds (kg), N-P fertilizer (kg), machine and human labour (h), pesticides (litres), fuel (litres) and output such as yield (kg) were collected. According to the DEA results, the overall technical, pure technical, and scale efficiency were calculated as 0.90,0.98, and 0.91, respectively. The mean technical efficiency score obtained from SFA was calculated as 0.843. The mean technical efficiency obtained from the DEA was better than the result obtained from SFA. The empirical results indicated that technically inefficient farms had higher usage of land and P fertilizers. Therefore, cotton productivity can be increased with the proper use of inputs.