GREENHOUSE COST INDEX METHODOLOGY BASED ON THE DIVERSE REGIONS OF IRAQ

IF 1.6 Q3 PLANT SCIENCES Sabrao Journal of Breeding and Genetics Pub Date : 2023-08-31 DOI:10.54910/sabrao2023.55.4.20
H. H. AL-ASADI, N. Goga, M. Mandana, Prof. Naqib Ullah, Khan
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Abstract

Greenhouses have become widespread structures that create an ideal microclimate for growing crops worldwide. A greenhouse is a structure that allows people to regulate climatic conditions, such as, temperature and humidity. There are many different designs of greenhouses, but generally, these buildings include large areas of transparent material to capture the light and heat of the sun. They also offer protection from unfavorable weather conditions and pests, providing a popular solution for crop production worldwide, including Iraq, which uses alternative energy sources for climate control. Using machine learning models has helped design different greenhouse types; however, their ability to predict costs and designs based on features is yet to exist. Therefore, to address these issues, this study aimed to develop cost-effective and user-friendly greenhouse systems through two different approaches: Firstly, the use of random forests (RFs) model with the highest precision (0.99) formulated the cost of the greenhouse for new input data to calculate a greenhouse cost estimate based on the system's performance as a benchmark while selecting the greenhouse's features through training and testing, and secondly, the use of the farmer's desired price as a basis for developing a greenhouse design. This scientific approach will enable the farming community to manage the costs of various aspects, such as, building materials, energy sources, climate control devices, water and fertilizer delivery, growing substrates, internal logistics, and labor. The presented research will provide farmers with a practical basis that also considers the constraints, i.e., the economy, climate, law, market, and resource availability. It will empower the farmers to make the right decisions regarding greenhouse systems with their specific requirements and circumstances.
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基于伊拉克不同地区的温室气体成本指数方法
温室已经成为世界各地种植作物的理想小气候的广泛结构。温室是一种允许人们调节气候条件的结构,如温度和湿度。温室有许多不同的设计,但通常情况下,这些建筑包括大面积的透明材料,以捕捉太阳的光和热。它们还可以抵御不利的天气条件和害虫,为世界各地的作物生产提供了一种受欢迎的解决方案,包括使用替代能源控制气候的伊拉克。使用机器学习模型有助于设计不同类型的温室;然而,他们基于特征预测成本和设计的能力还不存在。因此,为了解决这些问题,本研究旨在通过两种不同的方法开发成本效益高、用户友好的温室系统:首先,使用精度最高(0.99)的随机森林(RFs)模型为新的输入数据制定了温室成本,以系统性能为基准计算温室成本估计,同时通过培训和测试选择温室的特征,其次,使用农民的期望价格作为制定温室设计的基础。这种科学的方法将使农业社区能够管理各个方面的成本,如建筑材料、能源、气候控制设备、水和肥料输送、种植基质、内部物流和劳动力。所提出的研究将为农民提供一个实用的基础,同时考虑经济、气候、法律、市场和资源可用性等制约因素。它将使农民能够根据他们的具体要求和情况,就温室系统做出正确的决定。
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来源期刊
Sabrao Journal of Breeding and Genetics
Sabrao Journal of Breeding and Genetics 农林科学-奶制品与动物科学
CiteScore
1.90
自引率
50.00%
发文量
63
期刊介绍: The SABRAO Journal of Breeding and Genetics is an international journal of plant breeding and genetics research and was first published in 1969. It is the official publication of the Society for the Advancement of Breeding Research in Asia and Oceania (SABRAO). Its objectives are to: promote the international exchange of research information on plant breeding and genetics, by describing new research findings, or ideas of a basic or practical nature; and be a medium for the exchange of ideas and news regarding members of the Society. The Journal gives priority to articles that are of direct relevance to plant breeders and with emphasis on the Asian region. Invited for publication are research articles, short communications, methods, reviews, commentaries, and opinion articles. Scientific contributions are refereed and edited to international standards. The journal publishes articles for SABRAO members mainly. The Journal preferred strongly that at least one author should be a current member of the Society. Non-members may also publish in the journal.
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