Crocus sativus identification method based on cloud-interconnection portable near-infrared technology and adulterated product quantitative prediction method thereof

A saffron, portable technology, applied in the field of geological exploration, can solve the problems such as reports on the identification of linear pulp that have not yet been seen, and achieve the effects of simple operation, good accuracy and reliability

Pending Publication Date: 2022-02-22
成都市食品药品检验研究院
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] There are few reports on the identification of saffron and its counterfeit and adulterated products by using near-infrared spectroscopy technology. At present, there are only reports by Eman Shawky et al. who use a desktop near-infrared instrument to establish qualitative and

Method used

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  • Crocus sativus identification method based on cloud-interconnection portable near-infrared technology and adulterated product quantitative prediction method thereof
  • Crocus sativus identification method based on cloud-interconnection portable near-infrared technology and adulterated product quantitative prediction method thereof
  • Crocus sativus identification method based on cloud-interconnection portable near-infrared technology and adulterated product quantitative prediction method thereof

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0037] Example 1 Judgment of Western Red Flowers and Its Pseudo Parts

[0038] First, establish the identification model of Western Red Flowers and their fake goods

[0039] (1) Take known Western Red Flowers, safflower, corn, lotus, chrysanthemum, and pulp samples, PV500R-I portable near-infrared gauges for mobile phones, collect near-infrared spectroscopy data, total Acquisition 6 times;

[0040] (2) For each sample spectrum data for step (1), the average spectrum is used to divide each sample into training samples and predictive samples with the Kennard-Stone algorithm;

[0041] (3) Establish a western red flower hoes differential model based on partial least squares discriminant analysis (PLS-DA) by training sample;

[0042] (4) Take the predictive sample verification model;

[0043] Second, identify the sample to be tested

[0044] (5) Retrieving the sample, PV500R-I portable near-infrared gauges controlled by mobile mobile phone, collecting near-infrared spectroscopy data of...

Example Embodiment

[0047] Example 2 Discount of Western Red Flower and Its Pseudo Products

[0048] First, establish the identification model of Western Red Flowers and their pseudops

[0049] (1) Take a known Western Red Flower, Western Red Flower, Western Red Flower Polymer, Western Red Flower Bullet, Western Red Flower Chrysanthemum and Western Red Flower Due Sample, with Mobile Phone Control PV500R-I portable near-infrared gauges collects near infrared spectroscopy data of 1350-1850 nm, total collection of 6 times;

[0050] (2) For each sample spectrum data for step (1), the average spectrum is used to divide each sample into training samples and predictive samples with the Kennard-Stone algorithm;

[0051] (3) Western safflower, Western red flowers, western red flowers, Western red flowers, Western red flowers, and Western red flowers, training samples, based on partial minimum The western red flower of the secondary discriminant analysis (PLS-DA), then uses the western red flowers, the Western ...

Example Embodiment

[0057] Example 3 The discrimination of Western Red Flowers and their fakes and pseudoques

[0058] First, establish the identification model of Western Red Flowers and their fakes and pseudo products

[0059] (1) Take known Western safflower, safflower, corn, lotus, chrysanthemum, pulp, Western safflower, western red flowers, western red flowers, western red flowers And Western Red Flower Divers Samples, PV500R-I Portable Near Infrared Meter-controlled PV500R-I Portable Near Infrared Meter, Total 6 times;

[0060] (2) For each sample spectrum data for step (1), the average spectrum is used to divide each sample into training samples and predictive samples with the Kennard-Stone algorithm;

[0061] (3) Establish the authenticity differentition model of western red flowers and fake goods:

[0062] Establishing a western red flower hioretial differential model based on partial least squares discriminant analysis (PLS-DA) based on Western Red Flower, Red Flower, Maize, Lotus, Chrysant...

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Abstract

The invention discloses a crocus sativus authenticity identification model based on a cloud-interconnection portable near-infrared technology, which is constructed by adopting the following steps: (1) taking known crocus sativus and counterfeit and/or adulterated samples thereof, collecting near-infrared spectral data, and preprocessing the spectral data; (2) dividing samples into training samples and prediction samples by using a Kennard-Stone algorithm according to the preprocessed data obtained in the step (1); (3) establishing a crocus sativus authenticity identification model based on partial least squares discriminant analysis (PLS-DA) by using the training sample; and (4) verifying the crocus sativus authenticity identification model by using the prediction sample. The crocus sativus authenticity identification model and the adulterated product adulteration amount detection model have good accuracy and reliability, can be used for on-site rapid detection of crocus sativus, and provide method reference for rapid detection of other rare traditional Chinese medicinal materials.

Description

technical field [0001] The invention relates to the field of geological exploration, in particular to a method for identifying saffron based on cloud-interconnected portable near-infrared technology and a method for quantitatively predicting adulterated products. Background technique [0002] Saffron is the dry stigma of Crocus sativus L., a plant of the Iridaceae family. It has the effects of promoting blood circulation and removing blood stasis, cooling blood and detoxifying, relieving stagnation and calming the nerves. Modern pharmacological research shows that saffron has various pharmacological effects such as treating cardiovascular and cerebrovascular diseases, mental diseases, diabetes, and anti-tumor. The yield of saffron is extremely low. It is reported that only 100,000 saffron plants can harvest 1 kg of saffron. [3] , expensive, also known as "plant gold". It is not uncommon for saffron to be adulterated in the market. The common counterfeit saffron products in...

Claims

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Application Information

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IPC IPC(8): G01N21/359G01N21/3563
CPCG01N21/359G01N21/3563G01N2201/1293
Inventor 李庆文永盛闫晓剑罗霄彭善贵许丽赵小琴严铸云
Owner 成都市食品药品检验研究院
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