[
AL-QAISSY, M. M. J. 2020. A study of some environmental and economic indicators of an automated greenhouse in comparison with the traditional ones when growing cucumbers (Cucumis sativus L.). Master thesis, Mosul University, Iraq.
]Search in Google Scholar
[
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. In Energy Conversion and Management, vol. 46, no. 4, pp. 655–666.
]Search in Google Scholar
[
CARTWRIGHT, H. – MARTON, M. 2015. Artificial Neural Networks. New York, USA : Springer New York, NY. ISBN 978-1-4939-2239-0.
]Search in Google Scholar
[
ÇEBI, Ü. K. – AYDIN, B. – Cakir, R. – Altintas, S. 2019. Energy use efficiency and economic analysis of greenhouse cucumber farming in Turkey: case of Thrace Region. In Custos e @gronegócio on line, vol. 15, no. 2, pp. 2–21.
]Search in Google Scholar
[
ESENGUN, K. – GUNDUZ, O. – ERDAL, G. 2007. Input-output energy analysis in dry apricot production of Turkey. In Energy Conversion and Management, vol. 48, no. 2, pp. 592–598.
]Search in Google Scholar
[
FIROOZI, S. – SHEIKHDAVOODI, M. J. – FARANI, S. M. 2014. Optimizing energy consumption efficiency for greenhouse cucumber production using the DEA (data envelopment analysis) approach in Markazi Province of Iran. In Journal of Agricultural Technology, vol. 10, no. 3, pp. 543–558.
]Search in Google Scholar
[
HILAL, Y. Y. – YAHYA, A. – ISMAIL, W. I. W. – ASHA’ARI, Z. H. 2021. Neural networks method in predicting oil palm FFB yields for the Peninsular States of Malaysia. In Journal of Oil Palm Research, vol. 33, no. 3, pp. 400–412. https://assets.publishing.service.gov.uk/media/5b3b63a3e5274a6ff466faa5/Environmental_risks_in_Iraq.pdf
]Search in Google Scholar
[
HUSSAIN, Z. – KHAN, M. A. – IRFAN, M. 2010. Water energy and economic analysis of wheat production under raised bed and conventional irrigation systems: A case study from a semi-arid area of Pakistan. In Soil and Tillage Research, vol. 109, no. 2, pp. 61–67.
]Search in Google Scholar
[
IRAQ MINISTRY OF AGRICULTURE (MoA). 2019. Strategic Plan for Agriculture 2015–2018. (in Arabic).
]Search in Google Scholar
[
JADHAV, H. T. – ROSENTRATER, K. A. 2017. Economic and environmental analysis of greenhouse crop production with special reference to low cost greenhouses: A review. In 2017 ASABE Annual International Meeting. St. Joseph, Michigan : ASABE, paper no. 1701178, pp. 1–6.10.13031/aim.201701178
]Search in Google Scholar
[
KARDONI, F. – PARANDE, S. – JASSEMI, K. – KARAMI, S. 2013. Energy input-output relationship and economical analysis of wheat product ion in Khuzestan province of Iran. In International Journal of Agronomy and Plant Production, vol. 4, no. 9, pp. 2187–2193.
]Search in Google Scholar
[
KITANI, O. – JUNGBLUTH, T. – PEART, R. M. – RAMDANI, A. 1999. CIGR Handbook of Agricultural Engineering – Volume V “Energy and Biomass Engineering”. USA : American Society of Agricultural Engineers, pp. 8–20. ISBN 0-929355-97-0.
]Search in Google Scholar
[
LIVINGSTONE, D. J. 2008. Artificial Neural Networks: Methods and Applications. Totowa, NJ, USA : Humana Press, pp. 185–202. ISBN 978-1-60327-101-1.
]Search in Google Scholar
[
MOHAMMADI, A. – TABATABAEEFAR, A. – SHAHIN, S. – RAFIEE, S. – KEYHANI, A. 2008. Energy use and economical analysis of potato production in Iran a case study: Ardabil province. In Energy Conversion and Management, vol. 49, no. 12, pp. 3566–3570.
]Search in Google Scholar
[
NASROLLAHI, H. – AHMADI, F. – EBADOLLAHI, M. – NOBAR, S. N. – AMIDPOUR, M. 2021. The greenhouse technology in different climate conditions: A comprehensive energy-saving analysis. In Sustainable Energy Technologies and Assessments, vol. 47, article no. 101455.
]Search in Google Scholar
[
NOURAEIN, M. – KOUCHAK-KHANI, H. – JANMOHAMMADI, M. – MOHAMADZADEH, M. – ION, V. 2020. The effects of tillage and fertilizers on growth characteristics of Kabuli chickpea under Mediterranean conditions. In Acta Technologica Agriculturae, vol. 23, no. 1, pp. 18–23.
]Search in Google Scholar
[
NOURANI, A. – BENCHEIKH, A. 2020. Energy requirement optimization of greenhouse vegetable production using data envelopment analysis (DEA) method in Algeria. In Acta Technologica Agriculturae, vol. 23, no. 2, pp. 60–66.
]Search in Google Scholar
[
OMID, M. – GHOJABEIGE, F. – DELSHAD, M. – AHMADI, H. 2011. Energy use pattern and benchmarking of selected greenhouses in Iran using data envelopment analysis. In Energy Conversion and Management, vol. 52, no. 1, pp. 153–162.
]Search in Google Scholar
[
PLASTINA, A. 2016. Estimated costs of crop production in Iowa – 2016. Iowa State University Extension and Outreach. Available at: https://www.extension.iastate.edu/agdm/crops/pdf/a1-20_2016.pdf
]Search in Google Scholar
[
PRICE, R. 2018. Environmental risks in Iraq. Helpdesk reports by the UK Department for International Development. Available at: SHETTY, S. A. – PADMASHREE, T. – SAGAR, B. M. – CAUVERY, N. K. 2021. Performance analysis on machine learning algorithms with deep learning model for crop yield prediction. In JEENA JAKOB, I. et al. (eds.) Data Intelligence and Cognitive Informatics, chapter 58, pp. 739–750. Singapore : Springer Nature Singapore Pte Ltd.10.1007/978-981-15-8530-2_58
]Search in Google Scholar
[
TAKI, M. – AJABSHIRCHI, Y. – MAHMOUDI, A. 2012. Prediction of output energy for wheat production using artificial neural networks in Esfahan province of Iran. In Journal of Agricultural Technology, vol. 8, no. 4, pp. 1229–1242.
]Search in Google Scholar
[
WORLD WEATHER ONLINE. 2022. Mosul Climate Weather Averages. Available at: https://www.worldweatheronline.com/mosul-weather-averages/ninawa/iq.aspx
]Search in Google Scholar
[
ZIAEI, S. M. – MAZLOUMZADEH, S. – JABBARY, M. 2015. A comparison of energy use and productivity of wheat and barley (case study). In Journal of the Saudi Society of Agricultural Sciences, vol. 14, no. 1, pp. 19–25.
]Search in Google Scholar
[
ZWEIFEL, P. – PRAKTIKNJO, A. – ERDMANN, G. 2017. Energy in science and engineering. In Energy Economics, pp. 15–35. Springer Texts in Business and Economics. Berlin, Heidelberg : Springer.10.1007/978-3-662-53022-1_2
]Search in Google Scholar