A method for constructing a rapid quantitative detection model of heavy metal element copper in mulberry leaves

A quantitative detection and construction method technology, which is applied in the direction of measuring devices, character and pattern recognition, instruments, etc., can solve the problems of information variable abandonment, affecting the calculation accuracy and calculation time of multivariate detection models, and failing to make full use of them.

Active Publication Date: 2021-05-04
ZHEJIANG UNIV
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  • Claims
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Problems solved by technology

However, when LIBS technology is used to detect the heavy metal copper in mulberry leaves, the following problems are encountered. First, the LIBS spectrum has a high data dimension (usually containing tens of thousands of variables), which seriously affects the multivariate detection model. Calculation accuracy and calculation time; second, many important information variables in LIBS data were abandoned during the modeling process and were not fully utilized, making the established mulberry leaf heavy metal copper detection model less stable

Method used

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  • A method for constructing a rapid quantitative detection model of heavy metal element copper in mulberry leaves
  • A method for constructing a rapid quantitative detection model of heavy metal element copper in mulberry leaves

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Embodiment 1

[0065] (1) Select 100 samples of fresh mulberry tea leaves with uniform size, no pests and diseases, and no mechanical damage, and use analytical pure CuSO 4 Prepared 0, 500, 1000, 2000 and 4000mg / L 5 groups of Cu 2+ Solution, the selected 100 pieces of mulberry tea fresh leaf samples were divided into 5 parts, each corresponding to a group of Cu 2+ Solution, the immersion time of each group is 48h;

[0066] Take out the fully soaked mulberry leaves, rinse the surface of the soaked fresh mulberry tea leaves with dewatered water, and remove the residual Cu on the leaf surface. 2+ solution; put the rinsed mulberry leaf sample into an oven for drying until the sample has a constant weight, weigh the dried mulberry leaf sample, grind it, pass through a 100-mesh sieve, and press into tablets to finally obtain a weight of about 100 uniform square samples of 0.25g in thickness, 2mm in length and 10mm in length and width;

[0067] (2) Collect the laser-induced breakdown spectrum da...

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Abstract

The invention provides a method for constructing a rapid quantitative detection model of copper, a heavy metal element in mulberry leaves, and belongs to the technical field of quality and safety detection. The invention first constructs a quantitative detection model of heavy metal copper, and then performs quantitative detection of heavy metal copper in blind mulberry leaf samples according to the quantitative detection model. When constructing the quantitative detection model, the present invention performs non-supervised clustering of the self-organizing neural network on the laser-induced breakdown spectrum data, and then uses the non-information variable elimination method to select the clustered variables, thereby avoiding information redundancy , to obtain the most relevant model variable information, and then establish a partial least squares regression model, select a partial least squares regression sub-model with high accuracy and stability, and fuse the partial least squares regression sub-model through a consensus fusion algorithm, A quantitative detection model for heavy metal copper was obtained.

Description

technical field [0001] The invention relates to the technical field of quality and safety detection, in particular to a method for constructing a rapid quantitative detection model of heavy metal element copper in mulberry leaves. Background technique [0002] Mulberry leaf tea is rich in a variety of biologically active substances and nutrients (such as multivitamins, minerals, polyphenols, flavonoids and 1-deoxynojirimycin), regular drinking can achieve intestinal detoxification, lower blood pressure and blood lipids, and resist oxidation and aging and treatment of diabetes. However, with the rapid development of industry and the improvement of people's living standards in recent years, a large amount of waste from industrial production, automobile traffic, and daily production has been discharged into rivers, soil, and the atmosphere, causing heavy metal pollution. As a woody plant with strong stress resistance, mulberry will not show obvious symptoms when it is stressed...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N21/71G06K9/62
CPCG01N21/718G01N2201/1296G06F18/23
Inventor 黄凌霞孟留伟杨良
Owner ZHEJIANG UNIV
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