Rural Development
Mahdi Babaeian; Abolfazl Tavassoli; Mahdi Javaheri; Mostafa Jafarian
Abstract
Investigating of energy flow and greenhouse gas emissions is one of the methods to compare energy efficiency, production efficiency and environmental hazards of agroecosystems. This study investigates the patterns of energy consumption, greenhouse gas emissions and global warming potential of dryland ...
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Investigating of energy flow and greenhouse gas emissions is one of the methods to compare energy efficiency, production efficiency and environmental hazards of agroecosystems. This study investigates the patterns of energy consumption, greenhouse gas emissions and global warming potential of dryland chickpea production in rural areas of Qoshkhaneh region of Shirvan city. Data for this experiment were collected through a face-to-face questionnaire. Farms were selected by random sampling. In this study, energy inputs included: labor, machinery, diesel, chemical fertilizers, chemical pesticides and seeds, and the study output was grain yield and shoot yield (straw). The results showed that the average labor used per hectare of dryland chickpea farms in rural areas of North Khorasan was 21 people, nitrogen fertilizer 50 and phosphorus and potassium fertilizers 70 kg/ha, as well as diesel fuel consumption of 35 liters and the use of machinery 8 h/ha. Evaluation of energy consumption showed that among the inputs, nitrogen fertilizer with 3307 MJ/ha accounted for 40.06% of the total energy input and diesel fuel with 1970.85 MJ/ha, Consumed 23.23% of the total input energy. labor and seeds also had the lowest share of energy inputs with 0.49 and 1.87 percent, respectively. Total energy consumption efficiency (chickpea + straw) was 1.91, energy productivity was 0.08 kg/MJ and specific energy was 12.32 MJ/kg. In terms of greenhouse gas emissions was 399.20 kg/ha, the share of CO2 was 398.60, the share of N2O and CH4 was 0.02 and 0.57 kg/ha respectively. Global warming production potential per hectare of dryland chickpeas in North Khorasan Province was 419.13 kg CO2 equivalence. In general, the results showed that dryland chickpea fields have low energy consumption due to dependence on rainwater and lack of electricity consumption, as well as low consumption of chemical fertilizers. The most important strategies to reduce energy consumption in the production of dryland chickpeas is the use of appropriate crop rotation to reduce the use of herbicides and chemical fertilizers and also to observe the rules of farm traffic to reduce the movement of agricultural implements on farms.
Rural Development
Mahdi Babaeian; Abolfazl Tavassoli; Mohamad hosein salehi
Abstract
This research examines the energy use patterns and greenhouse gas emission of sugar beet farms in Hossein abad village of Shirvan city, in 2017-18. Data were collected by using a face-to-face questionnaire. Farms were selected with a random sampling method. In this study, the inputs in the calculation ...
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This research examines the energy use patterns and greenhouse gas emission of sugar beet farms in Hossein abad village of Shirvan city, in 2017-18. Data were collected by using a face-to-face questionnaire. Farms were selected with a random sampling method. In this study, the inputs in the calculation of energy use include: human labor, machinery, diesel fuel, chemical fertilizers, farmyard manure, biocides, electricity, water and the output in the calculation of total output energy include plant yield. The results indicated that total energy inputs were 66879.92 MJ ha-1and outputs 1310572.50 MJ ha-1. Of the total energy consumption in sugar beet production, 38.39% is related to the use of chemical fertilizers, 25.95% is related to diesel and 12.69% is related to electricity. Energy use efficiency of 19.59 and energy productivity of 0.72 kg MJ ha-1 were recorded. Chemicals, fuel and electricity played the largest role among energy inputs in beet farms. CO2, N2O and CH4 emissions were 2463.26, 21.02 and 3.26 kg ha-1, respectively. And the amount of global warming potential of these gases was calculated as 9048.85 CO2eq ha-1, of which 0.76% was related to CH4, 27.22% was related to CO2 and 72.02% was related to N2O.
