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The combined implementation of Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) has been identified as a suitable tool for the evaluation of the environmental and economic performance of multiple similar entities. In this study, a total of 82 rice paddy fields for spring and summer growing seasons in north of Iran were assessed using a combined LCA and DEA methodology to estimate the technical efficiency of each farmer. Furthermore, the environmental consequences of operational inefficiencies were quantified and target performance values benchmarked for inefficient units so that eco-efficiency criteria were verified. Results showed average reduction levels of up to 20% and 25% per material input for spring and summer systems, leading to impact reductions which ranged from 8% to 11% for spring farms and 19% to 25% for summer farms depending on the chosen impact category. Additionally, the potential economic savings from efficient farming operations were also determined. The economic results indicate that an added annual gross margin of 0.045 $ per 1 kg rice paddy could be achieved if inefficient units converted to an efficient operation. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this study was the application of non-parametric method of data envelopment analysis (DEA) to analyze the efficiency of farmers, discriminate efficient farmers from inefficient ones and to identify wasteful uses of energy for alfalfa production in Hamedan province, Iran. This method was used based on eight energy inputs including human labor, machinery, diesel fuel, fertilizers, farmyard manure, biocide, electricity and seed energy and single output of alfalfa yield. Technical, pure technical, scale and cross efficiencies were calculated using CCR and BCC models for farmers. From this study the following results were obtained: from the total of 80 farmers, considered for the analysis, 46% and 69% were found to be technically and pure technically efficient, respectively. The average values of technical, pure technical and scale efficiency scores of farmers were 0.84, 0.97 and 0.89, respectively. Also, energy saving target ratio for alfalfa production was calculated as 9.4%, indicating that by following the recommendations resulted from this study, about 75.90GJ ha−1 of total input energy could be saved while holding the constant level of alfalfa yield. Moreover the contribution of electricity input from total saving energy was 77.4% which was the highest share followed by chemical fertilizers (15%) and diesel fuel (4%) energy inputs. Optimization of energy use improved the energy use efficiency, energy productivity and net energy by 10.6%, 10.4% and 10.6%, respectively. [Copyright &y& Elsevier]

The main objectives of this study were to analyze the technical and scale efficiencies of farmers and to identify the wasteful uses of energy in different farm sizes of barberry production in Iran. For these purposes the data envelopment analysis approach was applied to the data of energy use for barberry production in individual farms. The results indicated that total energy input and yield value of small farms were higher than those of large farms. Also, energy resources are used more efficiently in small farms; technical efficiency of farmers in small and large farms was calculated as 0.66 and 0.50, respectively; also, scale efficiency was 0.82 and 0.62 for the respective farms. Total energy input in small and large farms could be reduced by 13.2% and 15.2%, respectively; accordingly, total energy requirement in target conditions was calculated as 20,702.4 and 13,761.2 MJ ha −1 . The highest potential improvement was derived from diesel fuel, followed by electricity and biocides. Improving energy use efficiency of water pumping systems, improving timing, amount and reliability of water application, employing the conservation tillage methods and applying integrated pest management technique are suggested for improving energy use efficiency and reducing the environmental footprints of barberry production. [ABSTRACT FROM AUTHOR]

Abstract: In this study, Data Envelopment Analysis approach was used to analyze the energy efficiency of farmers, to find efficient and inefficient ones and to identify the wasteful uses of energy in kiwifruit production. Moreover, the effect of optimization of energy on improvement of input costs and energy indices was investigated. The results revealed that based on variable returns to scale model, 62.79% of growers were efficient, though, based on constant returns to scale model it was just 23.26%. The technical, pure technical and scale efficiencies of farmers were calculated as 0.942, 0.993 and 0.948, respectively. Total optimum energy requirement was found to be 26,604.11 MJ ha−1; showing that 12.17% of input energy could be saved if the farmers follow the results recommended by this study. The contribution of chemical fertilizers input from total saving energy was about 78% which was the highest share. Optimization of energy use improved the energy use efficiency, specific energy and net energy by 13.86%, 12.17% and 22.56%, respectively. The results of economical analysis showed that optimization of energy decreases the total costs of production by 4.91%; and the benefit–cost ratio and productivity increased by 5.15% and 5.19%, respectively. [Copyright &y& Elsevier]

Abstract: The objective of this study was to determine energy use efficiency in greenhouse cucumber production using a non-parametric production function. The method used to quantify energy use efficiency or, more specifically, excess input energy used, is data envelopment analysis (DEA). DEA creates a ‘‘best practice’’ production frontier based on the growers that produce their level of cucumber yield with the least amount of input energy. These greenhouses then serve as benchmarks against which the energy use inefficiency of all other growers can be measured. The data used in this study was obtained through a face-to-face questionnaire method in the surveyed region – Yazd province of Iran. The total energy input and energy output were calculated to be 1168023 and 124663MJha−1, respectively. According to this information, the energy productivity was 0.14kgMJ−1, and net energy value was estimated to be –1043360MJha−1 indicating energy has been lost in greenhouse cucumber production. Basic DEA models (CCR and BCC) were used to measure the technical efficiency of the growers based on seven energy inputs human labor, diesel fuel, FYM, fertilizers, chemicals, water for irrigation and electricity, and a single output included yield of cucumber (kgha−1). The CCR and BCC models indicated 10 and 25growers were efficient, respectively. The average values of overall technical efficiency, pure technical efficiency and scale efficiency of growers were found to be 0.8235, 0.9273 and 0.8880, respectively. The results also revealed that about 21% of the total input resources could be saved if the growers follow the input package recommended by the DEA. The maximum contribution to the total energy savings is 53% from diesel fuel, followed by electricity (27%). [Copyright &y& Elsevier]

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: In this study a non-parametric method of Data Envelopment Analysis (DEA) is used to estimate the energy efficiencies of soybean producers based on eight energy inputs including human labor, diesel fuel, machinery, fertilizers, chemicals, water for irrigation, electricity and seed energy and single output of grain yield. The study also helps to rank efficient and inefficient farmers and to identify optimal energy requirement and wasteful uses of energy. Data were collected using face-to-face surveys from 94 farms in Golestan province which is the most important center of soybean production in Iran. Based on the results, average yield and energy consumption for soybean production were 3233.15kgha−1 and 35372.23MJha−1, respectively. Also, the results of DEA application showed that, the technical, pure technical and scale efficiencies of farmers were 0.853, 0.919 and 0.926, respectively. Moreover, energy saving target ratio for soybean production was calculated as 20.12%, indicating that by following the recommendations resulted from this study, about 7116.84MJha−1 of total input energy could be saved while holding the constant level of soybean yield. Also, electrical energy had the highest share (78.08%) from total saving energy, followed by fertilizers (10.46%) and diesel fuel (6.18%) energy inputs. [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]