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Research progress on indoor environment of mushroom factory

文献类型： 外文期刊

作者： Chen, Long 1 ; Qian, Lei 1 ; Zhang, Xiao 1 ; Li, Jiazheng 1 ; Zhang, Zhijun 1 ; Chen, Xiaoming 1 ;

作者机构： 1.Tianjin Acad Agr Sci, Tianjin 300192, Peoples R China

2.Minist Agr & Rural Affairs, Natl Engn & Technol Res Ctr Preservat Agr Prod, Key Lab Storage Agr Prod, Tianjin Key Lab Postharvest Physiol & Storage Agr, Tianjin 300384, Peoples R China

关键词： modern farming; mushroom factory; indoor environment control; computational fluid dynamics; remote sensing

期刊名称：INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING （ 影响因子：1.885； 五年影响因子：2.232 ）

ISSN： 1934-6344

年卷期： 2022 年 15 卷 1 期

页码：

收录情况： SCI

摘要： Mushroom factory is an emerging production mode that is relied on facility and equipment by creating a suitable, steady, and uniform growing environment to accommodate the demand of edible fungus at each stage of growth. Therefore, an optimal range of key environmental factors (temperature, humidity, light, and CO2 concentrations) in mushroom facilities is crucial to achieving satisfactory production rates. This research aimed to provide an overview of recent progress on indoor environmental studies of mushroom cultivation facilities from three perspectives, 1) the development of environmental monitoring and controlling systems; 2) the application of computer modelling in addressing indoor environmental issues; 3) the refinement of mushroom facility design, including structure and ventilation scheme. With the aid of cutting-edge technologies, accomplishments have been made in developing smart farming systems that facilitate real-time recording of environmental parameters and automatic regulation of equipment, which helps the establishment of growth models for specific mushroom species. Computational Fluid Dynamics (CFD) modelling has been adopted by researchers to investigate indoor airflow patterns and assess the distribution of critical environmental parameters. Studies have been conducted to modify the design of mushroom facilities to improve the performance in structural stability, ventilation efficiency, and internal environmental condition. However, some existing problems still need further investigations, such as the lack of design guidelines, energy-saving strategies, and Artificial Intelligent (AI) quality control. Therefore, this overview was expected to provide constructive insights for future studies in addition to references of previous studies.

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