Neural network model of CO۲ emissions for chickpea production under dryfarming system in Ravansar county of Iran

The aims of this research are to scrutinize carbon dioxide (CO۲) emissions chickpea production underdry farming system and its modeling by artificial neural network (ANN) in the Ravansar county of Iran.The results reveal that the total CO۲ emissions and chickpea yield are calculated about ۲۶۶.۱۶ kgCO۲eq. ha-۱ and ۴۸۹.۱۷ kg ha-۱, respectively. Highest share of CO۲ emissions is related to diesel fuel with۷۹% of total emissions. The results of ANN modeling indicated that the best topology is ۴-۴-۱ forprediction of chickpea yield based on emission inputs. Also, the R۲, RMSE and MAPE (%) of the beststructure are computed as ۰.۹۹۴, ۰.۱۲۲ and ۰.۴۱۴, respectively. Finally, it can be said the artificialmodeling can offer sufficient accuracy for modeling and help to save the environmental situation,significantly.