Determining efficiency of energy input for silage corn production: An econometric approach

• Combination of Cobb–Douglass econometric modelling and MPP (Marginal Physical Productivity) analysis are employed.
• Suitable energy input scenarios for silage corn production are improved using the above techniques.
• Three scenarios are proposed that cover all the situations with regard to energy availability.
• Silage corn production is most sensitive to the chemical pesticides, water and machinery energy inputs.

This study was undertaken to analyze the energy consumption patterns of silage corn production, the corresponding GHG emissions, the relationships between energy inputs and outputs, and the sensitivity of yield-to-energy inputs, using the Cobb–Douglass econometric model and MPP (Marginal Physical Productivity) in the Fars province of southwest Iran. Although the average amount of inputs and outputs were analyzed, 20% of the maximum and minimum values were also reported as cluster 1 (C1) and cluster 2 (C2) farmers. The results showed that around 45–68 GJ/ha energy was needed to produce 67–85 ton ha−1 of silage corn. According to the MPP, the most effective inputs on the yield were human power, chemicals and seed energy inputs, since the yield had the highest sensitivity to these three inputs. Three energy input scenarios were proposed based on the average, minimum and maximum energy consumptions; i.e. LEI (Low Energy Input), MEI (Medium Energy Input) and HEI (High Energy Input) scenarios. The lowest energy and yield were consumed and produced in the LEI, respectively. The output–input energy ratio, energy productivity and kg yield per kg CO2, were highest in the LEI, although higher energy and yield were used and produced in the MEI and HEI, respectively.