Maize canopy leaf color modeling system and method

Abstract

The invention relates to a maize canopy leaf color modeling system and method. The maize canopy leaf color modeling system comprises a support module arranged on a field preset place, an image acquisition module, an automatic meteorological and moisture state acquisition module, a data acquisition and transmission module, and a cloud storage and calculating module. The image acquisition module, the automatic meteorological and moisture state acquisition module, the data acquisition and transmission module, and the cloud storage and calculating module are arranged on the support module. The cloud storage and calculating module is used for carrying out maize canopy image sequence analysis in dependence on the maize canopy image, the meteorological data and soil information, and establishes a maize canopy leaf color changing model in order to carry out analysis and evaluation on the maize canopy leaf color and the growth vigor of the image acquired in real time in dependence on the maize canopy leaf color changing model. According to the invention, maize populations in the field can be continuously monitored in the whole growth period, influence of factors such as different meteorological conditions, different soil moisture states and the like on the maize leaf color is considered, the maize canopy leaf color changing model is established, and a feasible scheme is provided for chlorophyll content determination and maize growth vigor analysis which are based on the maize canopy leaf color.

Description

technical field [0001] The invention relates to the technical field of agricultural remote sensing, in particular to a corn canopy leaf color modeling system and method. Background technique [0002] Corn is a food and feed crop widely grown in my country, and it is also an important industrial raw material. Maize leaves are the main place for photosynthesis, and their color characteristics can reflect the physiological and biochemical attributes inside the leaves, and have a certain correlation with physiological traits such as chlorophyll content and photosynthetic rate. Chlorophyll content is an important physiological index of crops, and routine determination methods include spectrophotometer method and Amon method. However, these measurement methods usually cause damage to crops, and the workload is heavy, making it difficult to achieve continuous measurement of crops throughout their growth period. In addition, the traditional determination of maize leaf color mainly...

AI Technical Summary

Problems solved by technology

However, these measurement methods usually cause damage to crops, and the workload is heavy, making it difficult to achieve continuous measurement of crops throughout the growth period

In addition, the traditional determination of corn leaf color mainly relies on manual visual observation, which is highly subjective and lacks quantitative indicators for the determination of corn leaf color types.

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