Energy efficiency improvement for broiler production using non-parametric techniques

The goal of this study was to evaluate the sustainability and efficiency of broiler production with regard to energy consumption in Ardabil province, Iran. To reach the goal, linear programming model and Data Envelopment Analysis (DEA) were employed.  Data were collected from the farmers using a face–to–face questionnaire performed in September–December 2014 period.  The DEA application results showed that the average values of technical, pure technical and scale efficiency scores of producers were 0.949, 0.988 and 0.960, respectively.   Also, energy saving target ratio for broiler production was calculated as 8.33%, indicating that by following the recommendations resulted from this study, about 12316.85 MJ/(1000 bird) of total input energy could be saved while holding the constant level of broiler production.  The results of linear programming model revealed that by using of optimum energy, producers could increase average yield by 17.6%.   Also the results indicated that the existing productivity level could be achieved even by reducing the existing energy use level by 13.89%.  Diesel fuel, natural gas and electricity energy inputs had the highest potential for saving energy in two methods; so, if inefficient producers would pay more attention towards these sources, they would considerably improve their energy productivity

A two-stage DEA model to evaluate sustainability and energy efficiency of tomato production

The aims of this study were to evaluate the sustainability and efficiency of tomato production and to investigate the determinants of inefficiency of tomato farming in Marand region of East Azerbaijan province, Iran. For these purposes, a two-stage methodology was applied, in which for the first time a fractional regression model (FRM) was employed in the second stage of analysis, so that, in the first stage a nonparametric Data Envelopment Analysis (DEA) was used to analyze the efficiencies of tomato production and in the second stage, farm specific variables such as education level, farmersâ age, total land size and use of manure were used in a fractional regression model to explain how these factors influenced efficiency of tomato farming. The results of the first stage showed that there are considerable differences between efficient and inefficient farmers in the studied area, so that the main differences were in the use of chemical fertilizers, biocides and water for irrigation. Also, the results of second stage revealed that farmersâ age, education level and total land size positively affected efficiency in tomato production. So, better use of land, chemical fertilizers, water for irrigation and improving the farmersâ educational levels through literacy campaign and land consolidation would probably increase the efficiency in the long term. Keywords: Data envelopment analysis, Energy efficiency, Fractional regression model, Tomat