Evaluating the Energy Balance and Environmental Effects of Almond Production Using Artificial Neural Networks (Case Study: Lenjan County, Isfahan Province)

Abstract

This research was conducted to investigate the energy balance and global warming potential of almond production through by traditional and mechanized cultivation in Lenjan county, Isfahan province. Information related to the consumption of inputs and outputs was collected using 175 and 177 questionnaires in traditional and mechanized cultivation, respectively. Equivalent energy of inputs and outputs, as well as global warming potential, were calculated using coefficients of equivalent inputs. The results showed that the total energy consumption in traditional and mechanized cultivation is 14108.53 and 13767.39 MJ ha -1, energy efficiency is 0.19 and 0.24, and energy efficiency is 0.10 and 0.12 kg/MJ, respectively. Statistically, a significant difference was observed between the energy intensity index and energy consumption in both methods (P≤ 0.05). However no significant difference was observed between the energy intensity index in these two methods. Based on the economic analysis, the profit-to-cost ratio in traditional and mechanized cultivation was 3.27 and 4.2, respectively. The global warming potential from traditional and mechanized cultivation was 533.23 and 672.3 kg equivalent of carbon dioxide per hectare. The highest levels of environmental pollution in traditional and mechanized farming were associated with diesel fuel, accounting for 64.46% and 83.83%, respectively.

Keywords

• crop yield
• net income
• global warming
• artificial neural network
• almonds