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Method for rapidly detecting heavy metal pollution to shellfish

A detection method and technology for heavy metals, applied in the field of heavy metal detection, can solve the problems of complex operation, environmental pollution, destructiveness, etc., and achieve the effects of high classification accuracy, simple and fast operation, and good test reproducibility.

Inactive Publication Date: 2019-04-23
LINGNAN NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] Most of the existing detection methods are traditional heavy metal pollution detection methods, which require analysis and sampling of samples or complex processing. The detection is destructive, the operation is complicated, and chemical reagents are needed during the analysis process, which is polluting to the environment.

Method used

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  • Method for rapidly detecting heavy metal pollution to shellfish
  • Method for rapidly detecting heavy metal pollution to shellfish
  • Method for rapidly detecting heavy metal pollution to shellfish

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Embodiment 1

[0053] The present invention takes three kinds of common cultured shellfish Philippine clam, near river oyster and emerald mussel as the research objects, and four typical heavy metal ions of copper, zinc, cadmium and lead as the analysis indicators, aiming at single heavy metal pollution and composite Two cases of heavy metal pollution, using hyperspectral image technology to carry out rapid non-destructive detection of heavy metal pollution in shellfish and determination of heavy metal ion content.

[0054] Such as figure 1 Shown, a kind of shellfish heavy metal pollution rapid detection method comprises the following steps;

[0055] S1: Prepare samples in the laboratory, including non-polluted samples, single-polluted samples, and compound-polluted samples;

[0056] S2: Collect and correct the hyperspectral image of the sample, and then extract and preprocess the spectral data;

[0057] S3: Perform band selection based on neighborhood evidence decision-making on the prepr...

Embodiment 2

[0091] In conjunction with the best characteristic band subset obtained in the above-mentioned embodiment 1, a portable shellfish heavy metal detection instrument based on ARM9 is designed, and a structured design method is adopted. The hardware main body of the device is composed of several substructures with independent functions. Including spectrum acquisition module, control module, display module, power supply module and some auxiliary circuits, etc. The device is low in price, easy to carry, and has relatively high detection accuracy, and can realize fast and convenient detection of heavy metals in shellfish.

[0092] The development process of the portable shellfish heavy metal pollution rapid detector based on hyperspectral image technology includes:

[0093] (1) Demand analysis, including the characteristic analysis of the test object and the research and development feasibility analysis;

[0094] (2) Pre-experiment and overall plan determination;

[0095] (3) The c...

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Abstract

The invention relates to the technical field of heavy metal detection, in particular to a method for rapidly detecting heavy metal pollution to shellfish. The method comprises the following steps: firstly, preparing samples; secondly, carrying out hyperspectral image collection, correction, data extraction and preprocessing on the samples; thirdly, carrying out neighbourhood evidence decision making-based wave band selection on data, and extracting a subset of a characteristic waveband; fourthly, establishing a classification detection model, wherein the classification detection model comprises a quantum neural network classifier and an integrated learning classifier, the quantum neural network classifier is used for carrying out pollution and non-pollution detection classification on theshellfish by utilizing the subset of the selected waveband, and the integrated learning classifier is used for identifying and classifying different kinds of heavy metal pollution to the shellfish byutilizing the subset of the selected waveband; finally, obtaining a detection result of the samples. According to the method disclosed by the invention, data collection of the samples is carried out by utilizing a hyperspectral detection technology, waveband selection is carried out through the neighbourhood evidence decision making theory, classification detection is carried out by applying the quantum neural network classifier and the integrated learning classifier, the operation is simple and fast, better testing reproducibility is obtained, no any chemical reagent is required for assistingduring an analysis process, and pollution to environment is not generated.

Description

technical field [0001] The invention relates to the technical field of heavy metal detection, in particular to a rapid detection method for shellfish heavy metal pollution. Background technique [0002] Shellfish (such as mussels, scallops, clams, oysters, cockles, razor clams, etc.) grow in the seabed sediments, and their location is small. Once they encounter water quality and sediment pollution, it is difficult to avoid, and they will also move the water body during feeding. And the heavy metal pollutants in the sediment accumulate in the body, and the heavy metal content in the body is several orders of magnitude higher than that in the surrounding environment, which seriously affects the edible value. If it is eaten for a long time, it will cause harm to human health. Therefore, improving the heavy metal pollution detection ability of shellfish and ensuring the quality and edible safety of shellfish has become one of the basic problems that need to be solved urgently in...

Claims

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Application Information

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IPC IPC(8): G01N21/25G06K9/62
CPCG01N21/25G06F18/254
Inventor 刘瑶孟祥丽李明王润涛王树文
Owner LINGNAN NORMAL UNIV
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