Improved fish swarm algorithm-based tomato seedling stage photosynthesis optimization regulation and control model, establishment method and application

Abstract

The invention relates to an improved fish swarm algorithm-based tomato seedling photosynthesis optimization regulation and control model. According to the model, with temperature T adopted as an independent variable and photon flux density (PFD) corresponding to a light saturation point adopted as a dependent variable, a model formula is put forward. The invention also discloses an establishment method and application of the model. According to the establishment method of the model, multidimensional data are obtained through utilizing a photosynthetic rate double-factor nested test; a temperature and photon flux density coupled photosynthetic rate multivariate nonlinear regression model is constructed; an improved fish swarm algorithm-based photosynthetic rate model optimization method is designed, so that a light saturation point under different temperature conditions is obtained; and the tomato photosynthetic optimization regulation and control model with the light saturation point adopted as a target value is established. As indicated by the result of a model verification test, the light saturation point under different temperature conditions can be dynamically acquired; the determination coefficient of the actual measurement value and calculated value of the light saturation point is 0.967, and the maximum relative error of the actual measurement value and calculated value of the light saturation point is smaller than 2%, and the regulation and control model has high accuracy and has great significance for improving the regulation and control efficiency of light environment of facilities.

Description

technical field [0001] The invention belongs to the technical field of intelligent agriculture, and in particular relates to an improved fish swarm algorithm-based optimal control model for photosynthesis in tomato seedling stage and its establishment and application. Background technique [0002] Tomato is one of the main crops cultivated in greenhouses in the world, with a cultivation area of ​​4.5034 million hectares 2 , and the photosynthetic rate directly affects the yield and quality of tomato. Studies have shown that the photosynthetic rate is affected by environmental factors such as temperature, carbon dioxide concentration, and photon flux density. As a light-loving crop, the photosynthetic rate of tomato has received special attention. Studies by Hu Wenhai et al. have shown that the photosynthetic rate of tomato seedlings will decrease under low temperature and weak light; research results by Zhang Fucun et al. have shown that high temperature stress will also re...

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Problems solved by technology

The above research provides a theoretical basis for the dynamic optimization of the light saturation point, but there are still problems in the algorithm design, such as parameter types, optimization conditions, and different function types.

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