Improving energy productivity of sunflower production using data envelopment analysis (DEA) approach

Abstract

Efficient use of energy in agriculture is one of the conditions for sustainable agricultural production. This study applies the data envelopment analysis (DEA) approach to the data of 95 randomly selected farms to investigate the technical and scale efficiencies of farmers with respect to energy use for sunflower production in Golestan province, Iran. The study also helps to identify the wasteful usage and the optimum level of energy from different inputs. According to the results of DEA models, about 36% of farmers were found to be technically efficient and the mean efficiency of sunflower producers was found to be 0.87 and 0.96 under the constant and variable returns to scale assumptions respectively. The optimum energy requirement was calculated as 8448.3 MJ ha⁻¹; accordingly, a potential reduction of 10.8% (1020.3 MJ ha⁻¹) in total energy input could be achieved by raising the performance of farmers to the highest level. Applying a better machinery management technique and conservation tillage methods, application of fertilisers by performance monitoring and utilisation of alternative sources of energy such as compost and chopped residues may be the pathways for improving energy productivity and reducing the environmental footprint.