Green vegetable intelligent identification and leaf color environment change prediction method

Abstract

The invention discloses a green vegetable intelligent identification and leaf color environment change prediction method, which belongs to the field of agricultural planting, and comprises the steps of pattern acquisition, intelligent identification, leaf color information extraction, meteorological data acquisition, day and time regression model establishment, model goodness of fit judgment and prediction accuracy analysis, model determination and the like. According to the invention, facility agriculture field monitoring equipment can automatically identify and cut green vegetable plant images in real time in an open and natural environment, extract related leaf color parameters, and establish a change prediction mode of image information and environmental meteorological factors. The technology has the advantages of intelligent identification, timing automatic focus tracking, rapid and accurate cutting, high-speed parameter extraction and analysis, and high prediction model accuracy,and is suitable for day and time prediction and analysis. The method provides a technical basis for dynamic monitoring and early warning services of facility agriculture.

Description

technical field [0001] The invention belongs to the technical field of agricultural planting, and in particular relates to a method for intelligent identification of green vegetables and prediction of leaf color environmental changes. Background technique [0002] In recent years, the scale of my country's facility agriculture has continued to expand, the facility planting area has gradually increased, and the level of industrialization has continued to improve. It has become a major industrial form of modern agriculture. The No. 1 Document of the Ministry of Agriculture in 2018 clearly stated the need to "improve the development level of facility agriculture". Facility agriculture is mainly oriented towards high-efficiency production of horticultural crops and off-season cultivation. The output value per unit area can generally reach 7 to 10 times that of field fields, or even higher. It has become the most profitable industry in agricultural planting. At the same time, fa...

AI Technical Summary

Problems solved by technology

However, the analysis and application of observation data, especially real-world observation data, is limited by technical means, and is still in the exploratory stage.

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