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Abstract: In this study a non-parametric method of data envelopment analysis (DEA) was applied to analyze the efficiency of farmers, discriminate efficient farmers from inefficient ones and to identify wasteful uses of energy in order to optimize the energy inputs for apple production in Tehran province, Iran. From this study the following results were obtained: from the total of 56 farmers, considered for the analysis, 34% and 54% were found to be technically and pure technically efficient, respectively. The technical, pure technical and scale efficiency scores of farmers were 0.7857, 0.8982 and 0.8666, respectively. Optimum energy requirement was found to be 37993.15MJha−1; indicating that 11.29% of total energy input could be saved if the recommendations of this study are followed. From total energy saving, the contribution of electrical energy was the highest; it followed by chemicals energy inputs; implying that there was a great scope for saving energy inputs by improving the use pattern of these inputs. The results of economical analysis showed that the total costs of production could decreased from 8227.70 to 7570.01 $ha−1; also the benefit to cost ratio and productivity improved from 1.24 to 1.34 and 2.52 to 2.74, respectively. [Copyright &y& Elsevier]

Abstract: This study was conducted to determine the energy balance between the energy inputs and yield for apple production in Tehran, Iran. For this purpose the data were collected from 56 apple orchards. The following results were obtained from this study: The total energy input of 42819.25MJha−1 was required for apple production. The share of diesel fuel by 21.88% of the total energy inputs was the highest energy input. This was followed by farmyard manure (17.66%) and electricity (13.09%), respectively. The energy use efficiency, energy productivity, Specific energy, and net energy were found as 1.16, 0.49kgMJ−1, 2.06MJkg−1 and 7038.18MJha−1, respectively. According to the research results, the contribution of direct energy was higher than that of indirect energy; also the share of non-renewable energy was more than that of renewable energy. The results of econometric model estimation revealed that the impact of farmyard manure, water for irrigation, electricity, chemical fertilizer and human labour energy inputs were significantly positive on yield. The results of sensitivity analysis of the energy inputs showed that the MPP value of water for irrigation was the highest, followed by human labour and chemicals energy inputs, respectively. [Copyright &y& Elsevier]

Abstract: In this study energy use pattern for canola production in Golestan province of Iran was studied and the degrees of technical and scale efficiency of producers were analyzed using a non-parametric data envelopment analysis technique. The study also helped to identify the wasteful uses of energy by inefficient farmers and to suggest reasonable savings in energy uses from different inputs. Further, the effect of optimization of energy on energy ratio and energy productivity was investigated. Data used in this study were obtained from 130 randomly selected canola farms from Golestan, the most important center of canola production in Iran. The inputs were human labor, diesel, machinery, fertilizers, chemicals, water for irrigation, seeds and electrical energies; while the yield value of canola was considered as output. The results revealed that, the total energy of 17,786MJha−1 was consumed for canola production; about 15% of farmers were found to be technically efficient and the mean efficiency of farmers was found to be 0.74 and 0.88 under constant and variable returns to scale assumptions, respectively. The results also suggested that, on average, a potential 9.5% (1696MJha−1) reduction in total energy input could be achieved provided that all farmers operated efficiently. [Copyright &y& Elsevier]