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Energy audit of tobacco production agro-system based on different farm size levels in northern Iran

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Abstract

This study aimed to model the relationships between input and output energies of tobacco production in northern Iran, Guilan Province, and investigate how farm size would affect the energy use indices in the agro-system. A multilayer perceptron (MLP) neural network was designed to forecast the energy output in the tobacco agro-system. To analyze the effect of farm size, tobacco farms were divided into three groups of small-sized (˂0.5 ha), medium-sized (0.5–1 ha), and large-sized farms (˃1 ha). The findings highlighted that the total input energy and the energy use efficiency of tobacco production agro-system were 172,831.65 MJ ha−1 and 0.009, respectively. Natural gas used in the initial curing of green tobacco leaves accounted for around 60% of total input energy in the tobacco agro-system. Larger farms were significantly superior to the small-sized and medium-sized ones in energy use indicators (p ˂ 0.05). The most appropriate model to estimate the output energy of tobacco production was found to have a topology of 8-20-1. It can be concluded that the proposed MLP model is a robust tool to estimate the output energy of tobacco production in northern Iran.

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The financial support provided by the Islamic Azad University, Rasht, Iran, is duly acknowledged.

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Zare Derakhshan, J., Firouzi, S. & Kosari-Moghaddam, A. Energy audit of tobacco production agro-system based on different farm size levels in northern Iran. Environ Dev Sustain 24, 2715–2735 (2022). https://doi.org/10.1007/s10668-021-01552-4

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