Abstract

Soybean (Glycine max L.) is grown in cropping systems of Gorgan (northeast of Iran) as an oil crop. Energy flow and greenhouse gas (GHG) emissions of soybean production were analyzed based on four major production scenarios in this region. The study aimed to evaluate fuel and energy consumption and GHG emissions in order to identify and introduce the most efficient and environmentally friendly scenarios in the region. Four scenarios were included: Scenarios I, II, III and IV. The first two scenarios are known as mechanized scenarios and constitute the production systems adopted by the practices of local farmers in recent years. Scenario I included modern equipment, e.g. no-till, gun-sprinklers system, and high amount of chemical use. Scenario II, encompassed combination machine, center pivot-sprinklers system, and high consumption of fertilizers and chemicals applied by most of the farmers. Scenarios III and IV are known as conventional scenarios: where all operations (i.e. tillage, sowing and spraying) were done with less powerful tractors (60–75 hp) with manually performed fertilizer treatments. These scenarios were different only in terms of tillage operation. In this research, data were collected from 26 farmers using a face-to-face questionnaire-based survey, in 2015. Results revealed that the highest (3.18) energy use efficiency was obtained in Scenario IV (conventional scenario). Water consumption in Scenario II was less than other scenarios. Also, the lowest amount of GHG emissions was 1265.1 kg eq-CO2 ha−1 in Scenario IV and the highest amount belonged to Scenario II (2969.2 kg eq-CO2 ha−1). These results demonstrate that electricity accounted for the highest energy use in Scenarios I (78%) and II (48%), while fuel was the predominant energy consumed in Scenarios III (44%) and IV (37%). In general, conventional scenarios were found to be more environmentally friendly in Gorgan. These results revealed that there is a huge potential for improving energy efficiency in studied scenarios, especially in mechanized scenarios.

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