Rapid detection method for sorghum halepense and similar species

A detection method, the technology of false sorghum, applied in measuring devices, material analysis through optical means, instruments, etc., can solve the problems of complicated operation process and long time consumption, and achieve the effect of high recognition accuracy and accurate identification

Inactive Publication Date: 2014-04-23
YANCHENG INST OF TECH
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  • Abstract
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Problems solved by technology

The existing identification and classification methods for Sorghum plants are based on cytological methods and DNA detection. These methods are time-consuming and complicated.

Method used

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  • Rapid detection method for sorghum halepense and similar species
  • Rapid detection method for sorghum halepense and similar species

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0032] The objects of collection are the seeds of three kinds of Sorghum genus Sorghum, Sorghum pseudosorghum and Sudangrass. This detection method is also applicable to other seeds of the Sorghum genus.

[0033] The spectral data is collected in the range of 325-1075nm, the spectral sampling interval is 1.5nm, the number of scans is 30 times, and the field of view of the probe is 20 degrees. The light source is a 14.5V halogen lamp matched with the spectrometer.

[0034] A total of 120 samples (40 for each variety) were collected from three species of Sorghum. Various samples are all packed in petri dishes with a diameter of 40-50mm and a height of 8-10mm. In order to reduce the experimental error and ensure that the measured object is equidistant from the instrument, each petri dish is filled as an experimental sample. 40 samples were made for each variety, a total of 120 samples. All experimental samples were randomly divided into a modeling set and a prediction set. Th...

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Abstract

The invention discloses a rapid detection method for sorghum halepense and similar species based on a near infrared spectrum. The method comprises the following steps: adopting the near infrared spectrum to obtain spectral reflectance characteristic curves of three kinds of sorghum seeds of sorghum, sorghum halepense and sorghum sudanense between 325-1075 nm, adopting a partial least squares method for pattern character analysis, and adopting a cross validation method for judgment to determine that the optimal number of principal components is 9; after character extraction is completed, using the 9 kinds of principal components as the input variable of neural network, establishing three layers of BP (Back Propagation) neural networks, and calculating the category of each seed. The method combines the near infrared spectrum analysis with a chemical measurement method to rapidly and accurately judge the category of the three kinds of sorghum seeds, the detection time is greatly shortened, the detection efficiency is improved, and the detection cost is reduced.

Description

technical field [0001] The invention relates to the field of entry-exit inspection and quarantine, in particular to a rapid detection method for false sorghum and its similar species. Background technique [0002] Sorghum (Sorghum) has a variety of plants that are widely grown in various arid regions of the world as food, feed and industrial raw materials. However, a considerable part of the Sorghum genus belongs to invasive plants or invasive species, the most representative of which is S. halepense (L. Pers) . False sorghum is one of the top ten vicious weeds in the world. It can reproduce together with rhizomes and seeds, and has a strong ability to destroy the diversity of vegetation in my country. It is harmful, reproduces quickly, and is difficult to control. It is a quarantine pest for imported plants in my country. . False sorghum was originally introduced and distributed only in Fujian, Guangdong, and Taiwan. However, with the increasing quantity of grain imports, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/359
Inventor 林萍陈永明胡国文
Owner YANCHENG INST OF TECH
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