Application of nonparametric method to improve energy productivity and CO2 emission for barley production in Iran

The nonparametric method of data envelopment analysis (DEA) was used to investigate the energy efficiency and CO2 emission of barley farm in Hamedan province of Iran.  The 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 barley yield and technical, pure technical, scale and cross efficiencies were calculated using CCR and BCC models.  The results showed that the average values of technical, pure technical and scale efficiency scores of farmers were 0.788, 0.941 and 0.833, respectively.  Also, energy saving target ratio for barley production was calculated as 11.45%, indicating that by following the recommendations of this study, about 2,865 MJ ha–1 of total input energy could be saved with the same constant level of barley yield.  Moreover the contribution of chemical fertilizer input from total saving energy was 34.88% which was the highest share followed by diesel fuel (25.88%) and electricity (20.89%) energy inputs.  On one hand, optimization of energy use improved the energy use efficiency, energy productivity and net energy by 12.94%, 15.55% and 6.16%, respectively.  On the other hand, total greenhouse gases (GHG) emission was 885.56 kg CO2eq ha–1, which indicated that, the total CO2 emissions can be reduced by 11.06%.    Keywords: data envelopment analysis, energy saving, barley, chemical fertilizer

Proposing an Appropriate Soil Water Content Estimation Technique for Iran

Limitation of water resources is one of the major factors in the agricultural development of Iran. In recent years. Iran suffers from increases water consumption and drought conditions, This is why efficient water management in agriculture production becomes an inevitable requirement. One of the main aspects of water management in agriculture production is operating any type of irrigation system efficiently. A good on-farm irrigation water management requires a routine monitoring of soil water content (SWC). Recently a substantial number of different experimental methods in categories of direct, indirect, ground based and remote sensing have been developed to determine the SWC, and a large body of knowledge is now available on theory and applications. The need for indirect ground-based automatic methods for obtaining water content or indices of water content is evident when the time and labor involved in direct sampling is considered. In view of Iran conditions, selecting the best soil water measurement technology for the optimal management of irrigation system is a challenge for managers and the decision makers. This research aims to (i) compile the available ground based SWC measurement methods and discuses along with their advantages and their limitations, (ii) propose a technique that will be most useful for Iran condition. Considering regional parameters of Iran, these researchers found tensiometers as a proper technique for good water management. This technique with lower price in addition with other advantages could be more effective in development of Iran Agricultural Mechanization