Online Prediction Control Model of CO&lt;sub&gt;2&lt;/sub&gt; Concentration for &lt;i&gt;Pleurotus eryngii&lt;/i&gt; in the Sporocarp Period Based on Matlab and LabVIEW

Tian, Xiao Qing; Zhang, Kang; Bai, Nan; Zhu, X. J.

doi:10.4028/www.scientific.net/amm.868.45

Cited by 1 publication

(1 citation statement)

References 7 publications

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“…Kim et al [31] conducted a similar investigation on king oyster mushrooms to collect practical data of CO 2 concentrations, and characterized the impact of CO 2 on mushroom yields and quality. Later, Tian et al [32,33] developed a CO 2 concentration prediction model using initial CO 2 concentration and the relative growth time as the inputs. The model was built based on priorly recorded environmental data using Back Propagation (BP) Neural Network.…”

Section: Smart Controlmentioning

confidence: 99%

Research progress on indoor environment of mushroom factory

Chen¹,

Liu²,

Xiao³

et al. 2022

International Journal of Agricultural and Biological Engineering

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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 CO 2 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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Section: Smart Controlmentioning

confidence: 99%