Behzad Elhami - Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran
Asadollah Akram - Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran
Majid Khanali - Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran
Seyed Hashem Mousavi-Avval - Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran

In the present study, the energetic and economic modeling of lentil and chickpea production in Esfahan province of Iran was conducted using adaptive neuro-fuzzy inference system (ANFIS) and linear regression. Data were taken by interviewing and visiting of 140 lentil farms and 110 chickpea farms during 2014-2015 production period. The results showed that the yield and total energy consumption were calculated 2,023 kgha-1 and 32,970.10 MJha-1, respectively for lentil; and 2,276 kg ha-1 and 33,211.18 MJ ha-1, respectively for chickpea. Energy use efficiency was found to be 0.9 for lentil and 1.02 for chickpea; while benefit-cost ratio (BCR) were obtained 1.60 for lentil and 1.74 for chickpea. Regression results demonstrated that the coefficient of determination (R2) were 0.92 for lentil and 0.89 for chickpea. In adittion, in regression estimated model in terms of BCR, R2 were obtained as 0.86 for lentil and 0.72 for chickpea. In modeling of yield using the best ANFIS model, R2 were calculated 0.99 and 0.98, respectively for lentil and chickpea. Finally, for evaluation of crops BCR by best ANFIS model, R2 were determinate as 0.94 and 0.91 for lentil and chickpea, respectively. It was concluded that ANFIS model could better predict the energy output and BCR than that of linear regression model.

Energy Use Efficiency, Linear Regression, Prediction, Cobb-Douglas Model