An optimized approach to hourly temperature and humidity setpoint generation for reducing tomato disease and saving power cost in greenhouses

文献类型： 外文期刊

第一作者： Wang, Hui

作者： Wang, Hui;Laktionov, Ivan;Diaz, Francisco Rodriguez;Sanchez-Molina, Jorge Antonio;Li, Ming

作者机构：

关键词： Multi-objective optimization; Evolutive algorithm; Grey leaf spot; Leaf area index; Climate control

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：8.9； 五年影响因子：9.3 ）

ISSN： 0168-1699

年卷期： 2024 年 226 卷

页码：

收录情况： SCI

摘要： Context: Grey leaf spot is a main leaf disease of tomato in Mediterranean greenhouses, characterized by warm temperatures and high humidity during the spring and winter seasons, hence suitable for pathogen infection and spore spread. Consequently, the utilization of automatic control and optimization algorithms has emerged as effective means to prevent chemical-oriented disease control and enhancing the overall quality and safety of food and crops. Objective: The aim of this work is to search an optimal strategy for precision management on greenhouse tomato growth environment. So, multi-objective optimization rises to an alternative to achieve this goal. While there were lots of research on determining trajectories to control a desired crop growth, and lacking works that optimize climate conditions for restraining the damage of disease on crop. Methods: Based on the multi-objective genetic algorithm optimization method (MOGA), the solution balances the conflict of two objectives: minimum power cost caused by climate control and maximum health leaves with few effects of grey leaf spot. This study also highlights disease and high temperature impact on tomato growth, which are as inequality constraints of the optimization problems. Results and conclusions: The results showed MOGA strategy performers good, the minimum power cost is only need 0.084*day(-1) in warm weather condition, as well as 3.74 *day(-1) in cold weather condition, the uninfected LAI (m(2)[Leaves](m(-2)[soils]*day(-1))) is the range of [0.14 0.20]. The yearly power cost at least [308 1365].These are able to embed within a control scheme for achieving optimization purpose. Significance: The farmer receives the data necessary for decision-making to establish the setpoints during the crop cycle, modifying the control decisions, lowering production costs, reducing the use of pesticides and increasing the system efficiency to optimize crop growth.

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