Fingerprint-based micro-loss method for identification of Pterocarpus species

A fingerprint and hedgehog technology, applied in the field of wood identification, can solve the problems of complicated process, large sampling volume, damage to the appearance and function of wood or furniture, and achieve the effect of easy repair and accurate identification results

Active Publication Date: 2017-07-28
中山市中广测协同创新中心
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, different varieties of mahogany are similar in appearance, but their functions and values ​​are very different. As a result, hedgehog rosewood products often appear in the market as shoddy and shoddy products. Therefore, it is necessary to identify the authenticity of hedgehog rosewood.
[0004] At present, the identification of hedgehog rosewood is based on the manual identification method of wood characteristics. The technical defects are: ① Professionals are required to take representative samples, the process is complicated and will seriously damage the appearance of furniture, making it difficult to restore the furniture to its original state
②Manual discrimination requires experts to identify wood species, but there are still subjective uncertainties, and misjudgment will inevitably occur
③The identification result only distinguishes the "category", and it is difficult to go deep into the level of "species" for identification
[0005] Although someone has developed a fingerprint method to identify mahogany furniture, but because it is a slice sampling, the sampling volume is large, which will destroy the appearance and function of wood or furniture.
In addition, it uses a simple gas chromatograph to measure the shape of the fingerprints. Those skilled in the art know that the gas chromatograph is only a "finger" spectrum, and the qualitative parameter is the retention time of the characteristic peak. There is only identification of "fingers", but no identification of "pattern". If there is a large difference in the content of a certain component, it will cause misjudgment, so the identification method is difficult to meet the requirements of consumers.

Method used

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  • Fingerprint-based micro-loss method for identification of Pterocarpus species
  • Fingerprint-based micro-loss method for identification of Pterocarpus species
  • Fingerprint-based micro-loss method for identification of Pterocarpus species

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] Embodiment 1: 1. Follow the steps (1.1) (1.2) in the pretreatment method of the above-mentioned standard sample to obtain the GC-MS 3D fingerprint of sample 1 (such as figure 2 ), and the matching table of the chemical substance information of the characteristic peaks of the spectrum and Table 1, as shown in Table 2 below.

[0054] Table 2

[0055]

[0056] 2. Identification

[0057] According to the chemical substance information table (Table 2) and Table 1 and figure 1 and figure 2 From the comparison, it can be seen that: ① The consistency of the retention time (D1) requires an allowable deviation of ±0.5min, which meets the requirements. ② The consistency of the mass spectrum (D2) is that the search matching rate is greater than 90%, among which there are 20 characteristic peaks whose mass spectrum matching rate is less than 90%, and the mass spectrum matching rate of five characteristic peaks are greater than 90%, which does not meet the requirements. ③ T...

Embodiment 2

[0059] 1. Follow the steps (1.1) (1.2) in the pretreatment method of the above-mentioned standard sample for the test sample 2 to obtain the GC-MS 3D fingerprint of the sample 2 (such as image 3 shown), and the matching table of the chemical substance information of the characteristic peaks of the spectrum compared with Table 1, as shown in Table 3 below.

[0060] table 3

[0061]

[0062] 2 identification

[0063] According to the chemical substance information table (Table 3) and Table 1 and figure 1 and image 3 From the comparison, it can be seen that: ① The consistency of the retention time (D1) requires an allowable deviation of ±0.5min, which meets the requirements. ② The consistency of the mass spectrum (D2) is that the search matching rate is greater than 90%, among which the mass spectrum matching rate of one characteristic peak is less than 90%, and the mass spectrum matching rate of 24 characteristic peaks is greater than 90%, which meets the requirements. ...

Embodiment 3

[0064] Example 3: 1. Follow the steps (1.1) (1.2) in the pretreatment method of the above-mentioned standard sample for the test sample 3 to obtain the GC-MS 3D fingerprint of the sample 3 (such as Figure 4 ), and the matching table of the chemical substance information of the characteristic peaks of the spectrum and Table 1, as shown in Table 4 below.

[0065] Table 4

[0066]

[0067] 2. Identification

[0068] According to the chemical substance information table (Table 4) and Table 1 and figure 1 and Figure 4 The comparison shows that: ① The consistency of the retention time (D1) requires a tolerance of ±0.2 min, and the retention time deviation of the characteristic peak 20 gestrinone is greater than 0.5 min, which is listed as a suspicious characteristic peak. ②The consistency of the mass spectrum (D2) is that the search matching rate is greater than 90%, among which the mass spectrum matching rate of 21 characteristic peaks is less than 90%, and the mass spectr...

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Abstract

The invention relates to a method for identifying pterocarpus erinaceus species in a microdamage mode based on a fingerprint spectrum. The method includes the steps that micropore sampling is conducted with a drill bit, a sample to be detected is added into solvent to be subjected to ultrasonic extraction, the retention time D1 of characteristic peaks, a mass spectrum D2 and the peak area D3 of a total ions chromatogram of an extraction solution serve as qualitative parameters to form the GC-MS 3D fingerprint spectrum, and then authenticity of the pterocarpus erinaceus species sample is judged by checking matching consistency or similarity between the characteristic peaks in the GC-MS 3D fingerprint spectrum of the sample to be detected and 3D data of characteristic peaks in a GC-MS 3D fingerprint spectrum of the standard pterocarpus erinaceus species. The unique mass spectrum D2 of organic matter is used as one of important qualitative parameters, the qualitative parameters D1 and D3 are added to form the 3D fingerprint spectrum, and multi-layer fingerprint confirmation ensures that an identification method is conducted on the pterocarpus erinaceus species to judge authenticity accurately. Authenticity of a pterocarpus erinaceus species product is judged through the method, and results are accurate and reliable; microdamage sampling is conducted, and the sampling amount is small, so that repair is easy, and the appearance of the product is not damaged.

Description

technical field [0001] The invention relates to the field of wood identification, in particular to a method for identifying the species of red sandalwood hedgehog based on fingerprints with minimal damage. Background technique [0002] Hedgehog rosewood (Latin: Pterocarpus erinaceus ), Papilionaceae Pterocarpus, wood characteristics: ① heartwood purple reddish brown or reddish brown, often with dark stripes, visible scratches. ②Diffuse-porous wood and semi-ring porous wood tend to be obvious, and the growth ring is slightly obvious or obvious. ③ After the sawdust sinks into water, the fluorescence phenomenon is not obvious. The pungent smell is weak, and sometimes there is a sour or sour smell. ④Under a magnifying glass, the pores are medium to fine, and the parenchyma is abundant. Banded, wavy. ⑤The wood grain texture is staggered, the tip is straight, the structure is thin and uniform, the freshly cut wood has a fragrance, which fades or disappears after a long time, ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N30/88G01N30/06
CPCG01N30/06G01N30/88G01N2030/062
Inventor 陈智勇黄明华罗晓妍仇镇武郭佳胡传宝刘孟琪许鼎均马新年
Owner 中山市中广测协同创新中心
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