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Method for judging storage period of tea by hyperspectral image technique

A technology of hyperspectral image and storage period, applied in the field of tea storage period discrimination, can solve the problems of expensive instruments, complicated operation methods, limited ability to evaluate tea quality, etc., and achieves no sample damage, high accuracy, and easy operation. Effect

Active Publication Date: 2018-08-24
ANHUI AGRICULTURAL UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] At present, the evaluation of tea quality is mainly based on the sensory evaluation of appearance and inner quality, and the evaluation results are easily affected by the subjective factors of tea judges
However, chemical analysis methods such as gas chromatography-mass spectrometry, electronic nose, and electronic tongue are expensive instruments and complicated operation methods, which cannot quickly and conveniently determine the storage period of tea.
Therefore, non-destructive testing methods such as spectral technology and image analysis technology have gradually attracted attention, but the ability of a single detection method to evaluate tea quality is very limited

Method used

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  • Method for judging storage period of tea by hyperspectral image technique
  • Method for judging storage period of tea by hyperspectral image technique

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Embodiment 1

[0029] This embodiment uses visible / near-infrared hyperspectral image analysis technology in combination with the qualitative analysis model established by the support vector machine algorithm to distinguish the storage period of tea leaves, including the following steps:

[0030] (1) Preparation of aged tea samples: After measuring the initial moisture content, the purchased Lu’an Guapian tea samples were divided into aluminum foil bags and sealed, and stored in two conditions; some tea samples were stored in cold storage as fresh-keeping The tea samples were aged for one year, and samples were taken at 0, 90, 180, 270, and 360 days respectively. A total of five groups of tea samples were taken, and 30 samples were taken for each group of tea samples, each sample was 30 g, and 150 The other part of the tea samples were stored at room temperature as stored tea samples. The aging time was set as one year, and samples were taken at 0, 90, 180, 270, and 360 days respectively. A to...

Embodiment 2

[0036] This embodiment uses visible / near-infrared hyperspectral image analysis technology in combination with the qualitative analysis model established by the support vector machine algorithm to distinguish the storage period of tea leaves, including the following steps:

[0037] (1) Preparation of aged tea samples: After measuring the initial moisture content, the purchased Huangshan Maofeng tea samples were divided into aluminum foil bags and sealed, and stored in two conditions; some tea samples were stored in cold storage as fresh-keeping The tea samples were aged for one year, and samples were taken at 0, 90, 180, 270, and 360 days respectively. A total of five groups of tea samples were taken, and 30 samples were taken for each group of tea samples, each sample was 30 g, and 150 The other part of the tea samples were stored at room temperature as stored tea samples. The aging time was set as one year, and samples were taken at 0, 90, 180, 270, and 360 days respectively. ...

Embodiment 3

[0043] This embodiment applies the qualitative analysis model established by the visible / near-infrared hyperspectral image analysis technology combined with the support vector machine algorithm to quickly determine the storage period of tea leaves, including the following steps:

[0044] (1) Pretreatment of unknown tea samples: take unknown tea samples, weigh 12±0.5g of tea leaves as a sample, and evenly spread the tea leaves in a petri dish with a specification of Ф9 cm;

[0045] (2) Acquisition of hyperspectral images: use the hyperspectral image system and supporting acquisition and analysis software based on visible / near-infrared spectrometers of Taiwan Isuzu Optical Co., Ltd. to collect hyperspectral images of unknown samples, visible / near-infrared cameras The scanning range is 370.38-1036.54 nm, the sampling interval is 0.55 nm, and each spectrum has 1232 variables; after setting the hyperspectral camera exposure time and delivery device, before the hyperspectral image da...

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Abstract

The invention discloses a method for judging storage period of tea by a hyperspectral image technique. The method comprises the following steps of establishing a qualitative analysis model by combining the hyperspectral image technique and a support vector machine algorithm, so as to quickly and accurately judge the storage period of the tea. The method has the characteristics that the analysis speed is quick, the efficiency is high, the cost is low, the testing reproductivity is good, the pretreatment of the sample is not needed, and the online non-destructive testing can be conveniently performed.

Description

technical field [0001] The invention relates to a method for judging the storage period of tea, in particular to a method for judging the storage period of tea using hyperspectral image technology. Background technique [0002] The planting area of ​​my country's tea gardens and the output of tea both rank first in the world, and tea is my country's traditional bulk export product. However, with the change of supply and demand in the international tea trade, the growth trend of my country's tea export volume and trade volume has declined. At the same time, the demand in the domestic market is also close to saturation. The total production of tea far exceeds the market demand, and tea is unsalable. Phenomenon. In the process of drinking tea, the quality of new tea is better than that of old tea, because with the increase of storage time, the appearance quality and taste substances of tea have undergone irreversible changes. The quality of new tea is good, but the price is hi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/25G01N21/3563G01N21/359
CPCG01N21/25G01N21/3563G01N21/359G01N2201/129
Inventor 张正竹李露青宁井铭
Owner ANHUI AGRICULTURAL UNIVERSITY
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