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Near infrared spectrum variable selection method based on LASSO

A technology of near-infrared spectroscopy and variable selection, applied in the field of non-destructive analysis and analytical chemistry, it can solve the problems of time-consuming data volume and unstable calculation results, and achieve the effect of fast running speed and good prediction results.

Inactive Publication Date: 2015-12-30
TIANJIN POLYTECHNIC UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, due to the random selection of each modeling sample, the calculation results of these two methods are somewhat unstable, and it is time-consuming when the amount of data is large.

Method used

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  • Near infrared spectrum variable selection method based on LASSO
  • Near infrared spectrum variable selection method based on LASSO
  • Near infrared spectrum variable selection method based on LASSO

Examples

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Embodiment 1

[0042] This embodiment is applied to near-infrared spectroscopic analysis to determine the content of reducing sugar in tobacco samples. The specific steps are as follows:

[0043] (1) The near-infrared spectrum data of tobacco leaf samples were collected, and 269 tobacco leaf thin slice samples from different tobacco leaf production areas were tested using a BrukerVector22 / N near-infrared spectrometer (Bruker Optical Instrument Company, Germany). NIR spectral wavenumber range is 4000~9000cm -1 , the sampling interval is 4 wavenumbers, a total of 1296 wavelength points, the near-infrared spectrum of the sample is as follows figure 1 shown. The content of reducing sugar (ReducingSugar) in the tobacco samples was measured using a type AAIII continuous flow analyzer (BranLuebbe, Germany) according to standard methods. Before modeling, the tobacco leaf samples were randomly divided into two parts, including the training set and the prediction set samples. The training set sampl...

Embodiment 2

[0054] This embodiment is applied to near-infrared spectrum analysis, and the near-infrared spectrum data of the ternary blending of sesame oil, soybean oil, and rice oil are measured. The specific steps are as follows:

[0055] (1) Collect the NIR spectral data of the ternary blending samples of sesame oil, soybean oil, and rice oil, and use a near-infrared spectrophotometer (TJ270-60, Tianjin Tuopu Instrument Co., Ltd.) to measure the near-infrared spectral data. The wavelength range is 800~2500nm, the sampling interval is 1nm, a total of 1701 wavelength points. The near-infrared spectrum of the sample is shown in Figure 5 shown. Samples are configured according to a certain ratio (soybean oil quality 0.05-2.5, interval 0.05; rice oil concentration 0.05-2.5, interval 0.05). Before modeling, the samples are randomly divided into two parts, including training set and prediction set samples, where the training set samples are used to build the model, and the prediction set ...

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Abstract

The invention provides a near infrared spectrum variable selection method based on LASSO. The method comprises the following concrete processes of collecting a near infrared spectrum of a sample, and using a conventional method for measuring a concentration vector of a tested ingredient; dividing a data set into a training set and a prediction set by adopting a certain grouping mode; determining the constraint value t of an LASSO method through crossed verification; using a minimum angle regression algorithm for calculating the regression coefficient beta; remaining the position of a wavelength point of the beta being not zero; building a partial least squares regression model between a training set spectrum and the concentration vector by utilizing the training set spectrum corresponding to the remained wavelength, and predicting the concentration of a tested ingredient of a prediction set sample. The method has the advantages that an effective wavelength can be extracted; a quantitative analysis model is simplified; the prediction precision of the model is improved. Compared with an existing variable selection method, the method has the advantages that the speed is high; the repeating performance can be realized; the higher prediction precision can be reached by using fewer variables. The near infrared spectrum variable selection method is applicable to the variable selection of complicated sample near infrared spectrums.

Description

technical field [0001] The invention of the method belongs to the technical field of non-destructive analysis in the field of analytical chemistry, and specifically relates to a method for selecting variables of near-infrared spectrum based on LASSO. Background technique [0002] Near-infrared spectroscopy is a rapidly developing technology in the field of analytical chemistry. It has the advantages of high analysis efficiency, fast detection speed, and no need for sample pretreatment. It has been widely used in food, petroleum and other industries. Establishing a model between the near-infrared spectrum and the content or category of the measured substance can realize direct qualitative and quantitative analysis of complex substances. A very important problem in NIR spectral modeling is the existence of redundant wavelengths in the spectrum. General near-infrared spectroscopy (NIR) contains hundreds of wavelength variable points, and some of these wavelengths are irrelevan...

Claims

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Application Information

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IPC IPC(8): G01N21/359
Inventor 卞希慧颜鼎荷李淑娟谭小耀李翔
Owner TIANJIN POLYTECHNIC UNIV
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