Document Type: Original Article

Authors

1 Department of Mechanics of Biosystem Engineering, Shahrekord University, Iran

2 Department of Agricultural Mechanization Engineering, Guilan University, Iran

Abstract

The present study attempts to investigate the potential relationship between input energies, performance production of greenhouse basil, and greenhouse gases emitted from this product. The data were collected from 24 greenhouses using a questionnaire and verbal interaction with farmers. Results of the study showed that the total input energy and total output energy for basil production were 119,852.9 MJ/ha and 61,040 MJ/ha, respectively. The highest rate of energy consumption was related to electricity (52,200 MJ/ha), followed by plastic (23,220 MJ/ha) and chemical fertilizers (13,894 MJ/ha). The energy and productivity indices were estimated at 0.45 and 0.21, respectively, which indicated that the efficiency of energy in the agricultural sector was low. In addition, it was found that the pure energy index and total greenhouse gases emitted from basil production were equal to -722,706.9 and 9,595.6 kg (CO2), respectively. The highest emission of greenhouse gases was attributed to electricity (2,216 kg/CO2). Results of modeling proved that artificial neural networks can predict basil performance and CO2 emissions with a high degree of accuracy (R2=0.99 and MSE= 0.00023).

Graphical Abstract

Highlights

The total input energy and total output energy for basil production were 119,852.9 MJ/ha and 61,040 MJ/ha.

The highest emission of greenhouse gases was attributed to electricity (2,216 kg/CO2).

Results of modeling proved that artificial neural networks can predict basil performance and CO2 emissions with a high degree of accuracy.

 

Keywords

Main Subjects

Al-Ghandoor, A., Jaber, J., Al-Hinti, I., & Mansour, I. (2009). Residential past and future energy consumption: Potential savings and environmental impact. Renewable and Sustainable Energy Reviews, 13(6), 1262-1274.

Alam, M.S., Alam, M.R., & Islam, K. (2005). Energy flow in agriculture: Bangladesh. American Journal of Environmental Sciences, 1(3), 213-220.

Alluvione, F., Moretti, B., Sacco, D., & Grignani, C. (2011). EUE (energy use efficiency) of cropping systems for a sustainable agriculture. Energy, 36(7), 4468-4481.

Barut, Z. B., Ertekin, C., & Karaagac, H. A. (2011). Tillage effects on energy use for corn silage in Mediterranean Coastal of Turkey. Energy, 36(9), 5466-5475.

Canakci, M., Topakci, M., Akinci, I., & Ozmerzi, A. (2005). Energy use pattern of some field crops and vegetable production: Case study for Antalya Region, Turkey. Energy Conversion and Management, 46(4), 655-666.

Chauhan, N. S., Mohapatra, P. K., & Pandey, K.P. (2006). Improving energy productivity in paddy production through benchmarking An application of data envelopment analysis. Energy Conversion and Management47(9), 1063-1085.

Coxworth, E., Leduc, P., & Hultgreen, G. (1995). Analysis of crop production systems for reducing carbon emissions, stashing carbon in soils and providing raw materials for bioenergy production. Agriculture Canada.

Dalgaard, T. (2000). Farm types-How can they be used to structure, model and generalize farm    data? In Agricultural data for life cycle assessments. Agricultural Economics Research Institute (LEI).

Dyer, J. A., & Desjardins, R. L. (2006). Carbon dioxide emissions associated with the manufacturing of tractors and farm machinery in Canada. Biosystems Engineering93(1), 107-118.

Erdal, G., Esengün, K., Erdal, H., & Gündüz, O. (2007). Energy use and economical analysis of sugar beet production in Tokat Province of Turkey. Energy, 32(1), 35-41.

Hatirli, S. A., Ozkan, B., & Fert, C. (2005). An econometric analysis of energy input–output in Turkish agriculture. Renewable and Sustainable Energy Reviews, 9(6), 608-623.

Khan, S., Khan, M., Hanjra, M., & Mu, J. (2009). Pathways to reduce the environmental footprints of water and energy inputs in food production. Food Policy, 34(2), 141-149.

Khodi, M., & Mousavi, S. (2009). Life cycle assessment of power generation technology using GHG emissions reduction approach. In 7th National Energy Congres,(pp. 22-23).

Khoshnevisan, B., Rafiee, S., Omid, M., Mousazadeh, H., & Clark, S. (2014a). Environmental impact assessment of tomato and cucumber cultivation in greenhouses using life cycle assessment and adaptive neuro-fuzzy inference system. Journal of Cleaner Production, 73, 183-192.

Khoshnevisan, B., Shariati, H. M., Rafiee, S., & Mousazadeh, H. (2014b). Comparison of energy consumption and GHG emissions of open field and greenhouse strawberry production. Renewable and Sustainable Energy Reviews, 29, 316-324.

Lal, R. (2004). Carbon emission from farm operations. Environment International,30, 981-990.

Mahdavian, A., Banakar, A., Mohammadi, A., Beigi, M., & Hosseinzadeh, B. (2012). Modelling of Shearing Energy of Canola Stem in Quasi-Static Compres-sive Loading Using Artificial Neural Network (ANN). Middle-East Journal of Scientific Research, 11(3), 374-381.

Mohammadshirazi, A., Akram, A., Rafiee, S., Avval, S.H.M.,& Kalhor, E.B.( 2012). An analysis of energy use and relation between energy inputs and yield in tangerine production. Renewable and Sustainable Energy Reviews,16, 4515-4521.                                                     

Mousavi-Avval, S. H., Rafiee, S., Jafari, A., & Mohammadi, A. (2011). Improving energy use efficiency of canola production using data envelopment analysis (DEA) approach. Energy, 36(5), 2765-2772.

Ozkan, B., Akcaoz, H., & Karadeniz, F. (2004). Energy requirement and economic analysis of citrus production in Turkey. Energy Conversion and Management, 45(11), 1821-1830.

Pahlavan, R., Omid, M., & Akram, A. (2012). The relationship between energy inputs and crop yield in greenhouse basil production. Journal of Agricultural Science and Technology, 14(6), 1243-1253.

Pishgar-Komleh, S., Ghahderijani, M., & Sefeedpari, P. (2012). Energy consumption and CO 2 emissions analysis of potato production based on different farm size levels in Iran. Journal of Cleaner Production, 33, 183-191.

Rahman, M., & Bala, B. (2010). Modelling of jute production using artificial neural networks. Biosystems Engineering, 105(3), 350-356.

Royan, M., Khojastehpour, M., Emadi, B., & Mobtaker, H. G. (2012). Investigation of energy inputs for peach production using sensitivity analysis in Iran. Energy Conversion and Management, 64, 441-446.

Safa, M., & Samarasinghe, S. (2011). Determination and modelling of energy consumption in wheat production using neural networks:A case study in Canterbury province, New Zealand. Energy, 36(8), 5140-5147.

Soltani, A., Rajabi, M., Zeinali, E., & Soltani, E. (2013). Energy inputs and greenhouse gases emissions in wheat production in Gorgan, Iran. Energy, 50, 54-61.

Tabatabaeefar, A., Emamzadeh, H., Varnamkhasti, M. G., Rahimizadeh, R., & Karimi, M. (2009). Comparison of energy of tillage systems in wheat production. Energy, 34(1), 41-45.

Unakitan, G., Hurma, H., & Yilmaz, F. (2010). An analysis of energy use efficiency of canola production in Turkey. Energy, 35(9), 3623-3627.

Zangeneh, M., Omid, M., & Akram, A. (2010). A comparative study on energy use and cost analysis of potato production under different farming technologies in Hamadan Province of Iran. Energy, 35(7), 2927-2933.