Method for identification and systematic classification of citrus variety based on 21 characteristic component content

A technology for systematic classification and content, applied in the field of analytical chemistry, which can solve problems such as quantitative analysis, accurate judgment of difficult kinship relationships, etc.

Active Publication Date: 2018-04-17
INST OF AGRI ENG TECH FUJIAN ACAD OF AGRI SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, at present, the analysis of the results of multiple experiments by most researchers is only on the intuitive description of the results of molecular markers such as AFLP and ISSR, without in-depth quantitative analysis. more accurate judgment
For each variety, there is no rapid and efficient measure for variety identification using phenolic substance content and organic acid ratio as markers combined with cluster analysis and principal component analysis methods.

Method used

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  • Method for identification and systematic classification of citrus variety based on 21 characteristic component content
  • Method for identification and systematic classification of citrus variety based on 21 characteristic component content
  • Method for identification and systematic classification of citrus variety based on 21 characteristic component content

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0030] Example 1 Results of cluster analysis and principal component analysis of 33 citrus peels

[0031] (1) Sampling: Weigh 10 fruits, separate the citrus peel and pulp, freeze-dry the peel samples for 72 hours, crush them through 60 meshes, use 50wt.% methanol and DMSO-methanol solutions for ultrasonic extraction for 20 minutes, add water to volume to 50mL, centrifuged at 8000rpm / min, the supernatant was filtered through a 0.22μm organic filter membrane, and set aside;

[0032] (2) Preparation of the test solution: take by weighing citric acid, tartaric acid, malic acid, and quinic acid reagents with HPLC chromatographic purity above 99%, and then prepare the four kinds of organic acids with different concentration gradients of 0.01 with the mobile phase water phase. ~1mg / mL standard sample solution; 17 characteristic components are gallic acid, chlorogenic acid, protocatechuic acid, caffeic acid, p-coumaric acid, menticoside, ferulic acid, sinapic acid, rutin, benzene For...

Embodiment 2

[0054] Example 2 Cluster analysis and principal component analysis results of 19 citrus pulps

[0055] (1) Sampling: Weigh 10 fruits, separate the citrus peel and pulp, freeze-dry the pulp samples for 72 hours, crush them through 60 meshes, use 50wt.% methanol and DMSO-methanol solutions for ultrasonic extraction for 20 minutes, add water to volume to 50mL, centrifuged at 8000rpm / min, the supernatant was filtered through a 0.22μm organic filter membrane, and set aside;

[0056] (2) Preparation of the test solution: after weighing citric acid, tartaric acid, malic acid and quinic acid reagents with HPLC chromatographic purity above 99%, prepare the four kinds of organic acids with different concentration gradients of 0.01~ 1mg / mL standard sample solution; 17 characteristic components are gallic acid, chlorogenic acid, protocatechuic acid, caffeic acid, p-coumaric acid, menticoside, ferulic acid, sinapic acid, rutin, benzoic acid , naringin, hesperidin, diosmin, quercetin, kaem...

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Abstract

The invention belongs to the filed of analytical chemistry, particularly relates to a method for the identification and systematic classification of citrus variety based on 21 characteristic componentcontent. The method comprises the following steps: selecting citrus standard samples, measuring the contents of 17 characteristic components in the standard samples and the percent ratio of the content of 4 organic acids to the content of the total acid, utilizing the content and percent ratio as indexes to build a sample matrix, applying a principal component analysis method and a clustering methodology method, selecting the chemical component with largest weight in principal component as a distinguishing factor, utilizing the distinguishing factor as an independent variable, calculating thesquared euclidean distance among the citrus standard samples with the same variety, obtaining the squared euclidean distance range of the standard samples, measuring the characteristic component content of the distinguishing factor of samples to be measured, respectively calculating the squared euclidean distance range of the characteristic component content of the distinguishing factor of samples to be measured and the citrus standard samples and judging the variety of samples to be measured. The method can realize the effective distinguishing among different citrus variety, especially amongpomelo, citrus reticulate and orange and the like, and is an objective and reliable method for citrus classification.

Description

technical field [0001] The invention belongs to the field of analytical chemistry, specifically a method for identifying and systematically classifying citrus varieties based on the contents of 21 characteristic components. Background technique [0002] Citrus is the largest fruit in the world and one of the main fruits grown in China. In 2015, my country's citrus cultivation area ranked first in the world, and its output ranked third. In 2015, the national citrus area was 2,513,000 hectares, and the output was 36,600,800 tons, which occupies a very important position in the rural economy in southern my country. Because citrus is a perennial woody plant, it is easy to hybridize between species and genus, has a high budding frequency and a long history of cultivation, making citrus germplasm resources very rich and complex, and many closely related varieties have little difference in agronomic traits, or even only a single species. Insignificant variation in traits. Variety...

Claims

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Application Information

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IPC IPC(8): G01N30/88
CPCG01N30/88
Inventor 陈源余文权杨道富
Owner INST OF AGRI ENG TECH FUJIAN ACAD OF AGRI SCI
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