Analysis and modeling of energy and the amount of greenhouse gas production in apple production using machines laerning in Nazarabad city

Authors

1 Department of Agricultural Machinery Engineering, University of Tehran, Karaj, Iran

2 Department of Mechanical Engineering of Agricultural Machinery, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

3 A student at Payam Noor University in Karaj, Alborz province

10.22034/jam.2024.58882.1259

Abstract

Today, providing food security for the world's growing population by preserving the earth's resources and minimal environmental effects has become one of the basic and important challenges in sustainable agriculture, and the optimal use of resources is one of the main requirements of sustainable agriculture. In this study, the pattern of energy consumption during apple production, analysis and modeling of energy and greenhouse gas emissions in Nazarabad city was investigated. The results showed that the total energy consumption was equal to 35934.46 megajoules per hectare and the emissions were equal to 1220031 grams of carbon dioxide equivalent per hectare. Nitrogen fertilizer was the most consumed input with a share of 32.43% of the total input energy The indices of energy.efficiency, energy productivity, energy intensity and net energy were obtained as 1.43, (kg/Mj) 0.59, (Mj/Kg) 1.67 and (Mj) 15541.18. Modeling was done with three methods GBR, DTR and RFR and RRMSE was calculated as 0.02, 0.07 and 0.08 and R as 0.99, 0.96 and 0.94 respectively. The results showed that the GBR method is able to is to accurately predict the values of energy efficiency indices of apple production. The results showed that energy consumption and emissions can be predicted by machine learning method with high accuracy through the inputs of irrigation water, electricity, chemical and animal fertilizers, labor force, chemical poisons, diesel fuel and machines. Sensitivity analysis was performed with SHAP and the most influential input on energy prediction was nitrogen fertilizer.

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Main Subjects

Agricultural Mechanization
Volume 8, Issue 4
January 2024

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History

  • Receive Date: 21 October 2023
  • Revise Date: 22 January 2024
  • Accept Date: 22 January 2024

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