High-precision vegetable quality intelligent detection system based on phenotype group

Abstract

The invention discloses a high-precision intelligent vegetable quality detection system based on a phenotype group, and belongs to the technical field of food detection equipment.The high-precision intelligent vegetable quality detection system based on the phenotype group comprises cloud data, a spectrograph, a processing module, a controller and a reminding mechanism, the spectrograph is electrically connected with the processing module, and the controller is electrically connected with the processing module; the processing module is in data connection with the cloud, the processing module is electrically connected with the controller, after vegetables are detected, data can be automatically compared with cloud data, the freshness degree of the vegetables can be rapidly judged, accordingly, reminding of corresponding light colors is triggered, the detection efficiency is effectively improved, meanwhile, food colorant water is injected for marking, and the detection accuracy is improved. In addition, through the light source reminding assembly, when the detection light cylinder is kept perpendicular to the platform, the reminding function can be achieved, the user is informed that detection can be conducted at present, and the detection accuracy of the detector is improved to a certain degree.

Description

technical field [0001] The invention relates to the technical field of food detection equipment, and more particularly, to a high-precision vegetable quality intelligent detection system based on phenotype groups. Background technique [0002] The handheld spectrometer is a spectrum analysis instrument based on XRF spectrum analysis technology. It is mainly composed of X-ray tube, detector, CPU and memory. , consumer goods and other fields have important applications. [0003] The existing hand-held spectrometer can be used to analyze the internal components of vegetables, and can detect the internal moisture content, chlorophyll, lycopene, anthocyanin and other quality pigments and other quality indicators, so as to judge the freshness of the detected vegetables. degree. [0004] However, the existing detection methods are inefficient, can only detect the components of vegetables, need to manually judge the freshness of the vegetables, and do not have the corresponding re...

AI Technical Summary

Problems solved by technology

[0004] However, the existing detection method is inefficient and can only detect the ingredients of vegetables, which requires artificial judgment of the freshness of the vegetables, and does not have the corresponding reminder and marking functions. Vegetable quality intelligent detection system

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