A field high-throughput crop phenotype monitoring system and method

Abstract

The invention relates to a field high-throughput crop phenotype monitoring system and method. The system comprises a platform which is used for carrying a sensor and related equipment, a control mechanism which is arranged on the platform and is used for controlling the entire monitoring system, a positioning mechanism which is arranged on the platform and is used for positioning the movement track of the platform, and an imaging mechanism which is arranged on the positioning mechanism and is used for scanning and photographing an crop image. According to the invention, the crop collecting and monitoring system integrates crop position information, spectral band information and crop phenotype information into a whole body; non-destructive and high-throughput acquisition of crop growth information is realized; and crop phenotype information can be more accurately and effectively estimated.

Description

technical field [0001] The invention relates to an intelligent agricultural machinery equipment, in particular to a high-throughput crop phenotype monitoring system and method based on a field platform. Background technique [0002] Crop phenotype is the external expression of the interaction between crop genes and the environment, including the physiological and ecological traits and dynamic characteristics of crop growth and development, such as plant height, density, leaf length, leaf width, leaf inclination angle, and leaf area index. During the crop growth period, continuous, timely and accurate monitoring of multiple crop phenotypic traits (ie, high-throughput phenotypes) is an important basis for realizing intelligent diagnosis and management of crops. Among them, the green part of the crop canopy is the main organ for photosynthesis, mainly including the green part of leaves, stems, etc. Therefore, high-throughput phenotypic leaf area index and leaf inclination angle...

AI Technical Summary

Problems solved by technology

However, under field conditions, the UAV-based monitoring system is easily affected by environmental conditions. At the same time, due to the limitation of the time spent in the air, the accuracy of the image information acquired by the UAV often cannot meet the precise crop phenotype characteristics. extraction request

Although the field robot-based monitoring system can overcome the shortcomings of the UAV system, it is expensive and has very strict requirements on field layout, so it is not applicable except for breeding experiments on thousands of fields. in most agricultural experiments

[0004] In addition, most of the existing methods are limited to the application of a single camera or a single device. Due to the complexity of the distribution of stems and leaves in the canopy, photos taken from a single angle or images collected by a single device reflect a single canopy structure information. And the accuracy is not always guaranteed

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