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    An analysis of technical performance in Turkish beekeeping farms using Translog Production Function
    (UNIV FED RURAL PERNAMBUCO, DEPT ADMINISTRACAOAV D MANOEL MEDEIROS S-N, BAIRRO DE DOIS IRMAOS, RECIFE PE CEP50670-901, BRAZIL, 2021) Uysal, O; Karlidag, S; Gunduz, O
    This paper investigates technical efficiencies of beekeeping farms and their determinants, using stochastic production frontier function in Malatya Province of Turkey. Data used in the study were collected from randomly selected 58 beekeepers. For the estimation of farm level technical efficiency coefficients, Stochastic Frontier Analysis method was performed. Translog production function was used in the analysis. Research results showed that the technical efficiency scores of beekeeping farms in Malatya varied from 0.261 to 0.998 with mean of 0.728. It revealed that beekeeping farms would have produced same output with the decreased of inputs by 27.2%. Results of the Stochastic Frontier Analysis model showed that inefficiencies of beekeeping farms were mostly due to non-random factors such as age, education, experience and migratory beekeeping condition. In order to achieve the rationale input use, training and extension studies consistent with the good farm management and adaptation of new production methods should be applied.
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    Economic and productivity analysis of cherry production in Turkey: case of the Cukurova Region
    (UNIV FED RURAL PERNAMBUCO, DEPT ADMINISTRACAOAV D MANOEL MEDEIROS S-N, BAIRRO DE DOIS IRMAOS, RECIFE PE CEP50670-901, BRAZIL, 2021) Subai, OS; Namdar, SC; Yılmaz, H; Sağlam, C; Uysal, O; Aydın, B
    This study was carried out in cherry enterprises in the Adana and Mersin provinces of the Cukurova Region in Turkey. The study aimed to put forward the socio-economic structures of the cherry enterprises and the profitability of cherry production. The data used in the study were obtained from a total of 90 cherry producers in the 2018-2019 production period. The average age and the family size of the producers were determined as 57.8 years and 3.4 persons, respectively. The average land size of the enterprises was found as 9.07 da, and the average cherry yield was found as 13880.00 kg ha(-1). The total production costs, gross output value, gross profit, and net profit of cherry production were found as 8121.04 $ ha-1, 9022.00 $ ha-1, 3374.68 $ ha(-1), and 900.96 $ ha(-1), respectively. Besides, the cost of producing 1 kg of cherry was calculated as 0.58 $ ha(-1). In cherry production, gross labor productivity and net labor productivity values were found as 2.56 $ and 0.26 $, whereas gross and net capital productivity values were determined as 0.44 $ and 0.04 $, respectively. Gross factor productivity of cherry production was found as 1.11, whereas net factor productivity was 0.11. These values indicated that the return ratio of the costs was 11%. According to the results, it was concluded that the cherry production in Cukurova Region was profitable.
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    Identification of the factors affecting the honey production in beekeeping farms of Mersin Province in Turkey
    (UNIV FED RURAL PERNAMBUCO, DEPT ADMINISTRACAOAV D MANOEL MEDEIROS S-N, BAIRRO DE DOIS IRMAOS, RECIFE PE CEP50670-901, BRAZIL, 2021) Uysal, O
    This study aims to evaluate the beekeeping farms in Mersin province economically and to reveal the factors affecting honey production. The questionnaires were carried out in October-November 2020, and the data were collected from 81 beekeepers through face-to-face interviews. The stratified method of sampling was used the number of hives owned to beekeeping farms. Variable, fixed, and total costs of beekeepers in honey production were calculated in the research area. As a result of the determination of honey production cost, it was revealed that 27.38% of the variable cost ratio among the total costs and the variable cost and fixed cost ratio was 72.62%. According to the results, it was seen that the production value was inversely proportional to the increase in size in beekeeping enterprises. It was concluded that the main reason for this difference was that small-scale enterprises used the marketing channel more effectively. The relative profit was calculated as 1.67 $ on average. This result showed that 67% profit could be obtained from spending 1 US$ on honey production in farms. In the study, 14 variables were subjected to factor analysis to determine the factors affecting honey production. As a result of the factor analysis, three groups were defined as production factors, demographic factors, external factors, and the effects of these factor groups on honey production were determined.