Method for predicting photosynthesis dry matter yield of greenhouse crops

Abstract

The invention discloses a method for predicting the photosynthesis dry matter yield of greenhouse crops. The method comprises the following steps: 1, greenhouse environment parameter acquisition and data processing; 2, crop model establishment: obtaining a crop leaf area index (LAI); obtaining a plant canopy extinction coefficient k; acquiring illumination intensity I above a crop canopy; obtaining the crop canopy light absorption amount Iabs; and obtaining the crop unit time photosynthesis dry matter synthesis amount P according to the absorbed illumination amount and the photosynthetic efficiency coefficient. The invention relates to the technical field of intelligent greenhouse crop production. According to the method for predicting the yield of the dry matter in the photosynthesis of the greenhouse crops, the problem that the environment control of an intelligent greenhouse at the present stage in China is mainly realized by setting corresponding parameters through a greenhouse environment control computer or following the rule by technicians according to experience so as to achieve preset temperature, illumination, CO2 and other environment elements to influence the crop yield and improve the environmental control cost.

Description

technical field [0001] The invention relates to the technical field of intelligent greenhouse crop production, in particular to a method for predicting photosynthetic dry matter output of greenhouse crops. Background technique [0002] Compared with traditional greenhouses, smart greenhouses can more effectively control the environment inside the greenhouse, improve labor efficiency, and increase crop yield per unit area. Western developed countries represented by the Netherlands have strong technical reserves and practical experience in the field of intelligent greenhouses. In recent years, with the development of China's economy, my country has introduced a large number of foreign advanced multi-span intelligent greenhouses since the 1990s. However, practice has proved that under the same hardware facilities, the production efficiency of China's smart greenhouses is much lower than that of foreign equivalent greenhouses. The lack of corresponding intelligent greenhouse ma...

AI Technical Summary

Problems solved by technology

This method is based on subjective judgment. The lack of quantitative indicators is not conducive to the expansion of applications. The interaction between various environmental elements is often ignored, and it is often difficult to achieve the best environmental indicators required by crops, resulting in low yields and increased environmental control costs.

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