Method for near-infrared rapid detection of acid detergent fiber content of feeding ramie leaves

Abstract

The invention discloses a method for quickly detecting the content of acid detergent fibers in ramie leaves through near infrared. The method comprises the following steps: detecting the content of the acid detergent fibers in a ramie leaf powder sample by adopting a chemical measurement method; adopting a near-infrared agricultural product quality tester to scan absorption spectrum data of the ramie leaf powder sample; selecting a spectrum pretreatment method of acid detergent fibers; establishing a spectral analysis model by using the scanned absorption spectrum data and combining the detection value of the chemical measurement method and the data obtained by the spectrum pretreatment method; and selecting and verifying ramie leaf powder to correct the spectral analysis model.

Description

Technical Field

[0001] The invention belongs to the field of biotechnology, and particularly relates to a method for quickly detecting the acid detergent fiber content of ramie leaves for feeding by near infrared. Background Art

[0002] Domestic and foreign studies have found that ramie tender stems and leaves are rich in crude protein, crude fiber, trace elements, amino acids and other nutrients, and can be used as high-quality protein feed. At the same time, ramie is rich in acid detergent fiber, which is a feed additive that has been acid-treated with cellulose and belongs to the cellulose feed additive. It can significantly increase the cellulose content of the feed, and improve the structure and physical properties of cellulose, providing better feed nutrition for animals. Therefore, it is particularly important to screen out ramie leaf germplasm with low acid detergent fiber content and suitable for high-quality protein feed.

[0003] Traditionally, the acid detergent fiber content is usually determined by the 72% concentrated sulfuric acid method. The main disadvantages of this method are that it is complicated to operate, time-consuming, cannot be carried out in large quantities, and the chemical reagents cause pollution. Although the high-performance liquid chromatography method for determining acid detergent fiber is accurate, the equipment is expensive. Therefore, it is particularly important to find a method for determining the acid detergent fiber content quickly, accurately, efficiently, and at a low price.

[0004] Near-infrared spectroscopy analysis technology has the advantages of being fast, accurate, and pollution-free. Therefore, a near-infrared prediction model for detecting acid detergent fiber in ramie leaves is established to shorten time and reduce costs. It can not only provide a reference for the quality evaluation of ramie as feed, but also provide a rapid screening technology for feed-type ramie germplasm. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention aims to provide a method for rapid near-infrared detection of the acid detergent fiber content of ramie leaves, so as to achieve rapid and efficient detection of the acid detergent fiber content of ramie leaves, accurately evaluate the quality of ramie feed, and provide a rapid screening technology for feed-type ramie germplasm.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] The method for rapid near infrared detection of the acid detergent fiber content of ramie leaves comprises the following steps:

[0008] Step 1: using a chemical measurement method to detect the content of acid detergent fiber components in the sample ramie leaf powder;

[0009] Step 2: Scan the absorption spectrum data of the sample ramie leaf powder using a near-infrared agricultural product quality tester;

[0010] Step 3: Select the spectral pretreatment method for acid detergent fiber;

[0011] Step 4: Using the scanned absorption spectrum data, combined with the detection value of the chemical measurement method and the data obtained by the spectrum preprocessing method, a spectrum analysis model is established;

[0012] Step 5: Select and verify ramie leaf powder to calibrate the spectral analysis model;

[0013] Furthermore, the determination of the acid detergent fiber content in step 1 is repeated at least three times.

[0014] Furthermore, in step 2, an S400 near-infrared agricultural product quality measuring instrument is used to collect the absorption spectrum, and the scanning range is 1100nm to 2500nm (4000-9090.91 (1 / cm)).

[0015] Furthermore, in the step 2, the absorption spectrum of the ramie leaves is scanned multiple times; and in the step 4, an infrared spectrum analysis model is established using the average value of the absorption spectrum data of the multiple scans.

[0016] Furthermore, the step 3 of selecting the spectral preprocessing method for the acid detergent fiber is to select a spectral preprocessing method that maximizes the coefficient of determination and resolution of the spectral analysis model and minimizes the calibration standard deviation and relative standard deviation.

[0017] Furthermore, the process of establishing the spectral analysis model in step 4 is as follows: using CAUNIR near-infrared calibration software, the chemical measurement value of the acid detergent fiber content of the sample ramie leaf powder and the absorption spectrum data collected by three scans are averaged respectively, the chemical measurement value of the acid detergent fiber content of the sample ramie leaf powder and the data after absorption spectrum pretreatment are associated one by one, and the quantitative partial least squares (QPLS) method is used for modeling. The original spectral data preprocessing method that maximizes the determination coefficient and resolution of the spectral analysis model and minimizes the correction standard deviation and relative standard deviation is selected for data preprocessing and modeling.

[0018] Furthermore, in step 3, the acidic detergent fiber of the ramie leaf powder is spectrally preprocessed by an external detection method, and then spectrally preprocessed by second-order derivative+standard normal transformation+range normalization+centralization.

[0019] Furthermore, the correlation coefficients between the acid detergent fiber content in ramie leaves predicted by the spectral analysis model and the acid detergent fiber content in ramie leaves actually measured are respectively 0.9421.

[0020] Furthermore, in step 4, the content of acidic detergent fiber in the ramie leaves to be tested is predicted using a spectral analysis model, and the average value of the absorption spectrum data of the ramie leaf powder to be tested collected by the near-infrared agricultural product quality tester is input into the spectral analysis model. After spectral data preprocessing and model calculation and prediction, the predicted value of the component is obtained, and the content of acidic detergent fiber in the ramie leaves can be predicted.

[0021] The beneficial effect of the present invention is that the method for rapid near-infrared detection of the acid detergent fiber content of ramie leaves is to establish a spectral analysis model by utilizing the measured acid detergent fiber content of sample ramie leaves to achieve rapid, efficient and accurate detection of the acid detergent fiber content in ramie leaf powder, with low cost, and provide a rapid screening technology for feed-type ramie germplasm. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is the original spectrum of ramie leaf sample;

[0023] Figure 2 This is a correlation diagram between the measured and predicted values ​​of ramie acid detergent fiber. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] The present invention is a method for rapid near infrared detection of the acid detergent fiber content of ramie leaves, comprising the following steps:

[0026] Step 1: using a chemical measurement method to detect the content of acid detergent fiber components in the sample ramie leaf powder;

[0027] Step 2: Scan the absorption spectrum data of the sample ramie leaf powder using a near-infrared agricultural product quality tester;

[0028] Step 3: Select the spectral pretreatment method for acid detergent fiber;

[0029] Step 4: Using the scanned absorption spectrum data, combined with the detection value of the chemical measurement method and the data obtained by the spectrum preprocessing method, a spectrum analysis model is established;

[0030] Step 5: Select and verify ramie leaf powder to calibrate the spectral analysis model;

[0031] Furthermore, the determination of the acid detergent fiber content in step 1 is repeated at least three times.

[0032] Furthermore, in step 2, an S400 near-infrared agricultural product quality measuring instrument is used to collect the absorption spectrum, and the scanning range is 1100nm to 2500nm (4000-9090.91 (1 / cm)).

[0033] Furthermore, in the step 2, the absorption spectrum of the ramie leaves is scanned multiple times; and in the step 4, an infrared spectrum analysis model is established using the average value of the absorption spectrum data of the multiple scans.

[0034] Furthermore, the step 3 of selecting the spectral preprocessing method for the acid detergent fiber is to select a spectral preprocessing method that maximizes the coefficient of determination and resolution of the spectral analysis model and minimizes the calibration standard deviation and relative standard deviation.

[0035] Furthermore, the process of establishing the spectral analysis model in step 4 is as follows: using CAUNIR near-infrared calibration software, the chemical measurement value of the acid detergent fiber content of the sample ramie leaf powder and the absorption spectrum data collected by three scans are averaged respectively, the chemical measurement value of the acid detergent fiber content of the sample ramie leaf powder and the data after absorption spectrum pretreatment are associated one by one, and the quantitative partial least squares (QPLS) method is used for modeling. The original spectral data preprocessing method that maximizes the determination coefficient and resolution of the spectral analysis model and minimizes the correction standard deviation and relative standard deviation is selected for data preprocessing and modeling.

[0036] Furthermore, in step 3, the acidic detergent fiber of the ramie leaf powder is spectrally preprocessed by an external detection method, and then spectrally preprocessed by second-order derivative+standard normal transformation+range normalization+centralization.

[0037] Furthermore, the correlation coefficients between the acid detergent fiber content in ramie leaves predicted by the spectral analysis model and the acid detergent fiber content in ramie leaves actually measured are respectively 0.9421.

[0038] Furthermore, in step 4, the content of acidic detergent fiber in the ramie leaves to be tested is predicted using a spectral analysis model, and the average value of the absorption spectrum data of the ramie leaf powder to be tested collected by the near-infrared agricultural product quality tester is input into the spectral analysis model. After spectral data preprocessing and model calculation and prediction, the predicted value of the component is obtained, and the content of acidic detergent fiber in the ramie leaves can be predicted.

[0039] Example

[0040] The test materials are 195 samples of ramie leaf powder, each of which is divided into two groups, one for chemical composition determination and the other for near-infrared spectrum collection. The near-infrared spectrum sample set is divided into a calibration set and a test set. The calibration set is used to establish the model and the internal cross-validation of the model, and the test set is used for the external validation of the model. In this experiment, 173 samples were selected as the calibration set and 22 samples were selected as the test set.

[0041] Collection of near infrared scanning spectra:

[0042] Use a micro-plant crusher to crush, fully mix and sieve, dry at 105℃ for 24 hours, place the sample in a glass dryer, cool to room temperature, put it into a small round sample cup, scrape and compact the sample to ensure that the loaded sample is uniform, and the sample weight is about 3g. The S400 near-infrared agricultural product quality tester is used to collect the absorption spectrum, with a scanning range of 1100nm~2500nm (4000-9090.91(1 / cm)). In order to reduce the interference of instrument fluctuations and sample loading on spectral scanning, each sample is scanned 3 times, and the spectrum processing software is used to merge into an average spectrum for modeling and verification.

[0043] Determination of acid detergent fiber content

[0044] The statistical results of the calibration set and test set sample data of the near infrared model of ramie leaf acid detergent fiber components are shown in Table 1. The acid detergent fiber content in the ramie leaf calibration set ranges from 15.04% to 40.04%, with an average of 24.66%; the acid detergent fiber content in the validation set ranges from 19.21% to 37.80%, with an average of 26.87%. The distribution range of the chemical composition content of the samples is significantly different, and the samples are representative to a certain extent.

[0045] Table 1 Determination of the acidic detergent fiber content of ramie leaves

[0046]

[0047] Collection of original spectra

[0048] Figure 1 The figure shows the near-infrared diffuse reflectance spectrum of ramie leaf samples at 1100nm-2500nm (4000-9090.91 (1 / cm)). There are multiple absorption peaks in the full wavelength range. The absorption spectrum characteristics of different samples in the near-infrared spectrum region are basically the same, and the full spectrum shows a high-low and gentle trend, indicating that the main components of the samples are basically the same, but the relative content of each component is different. The near-infrared spectrum of the sample can be used to determine the lignocellulose content.

[0049] Original spectrum preprocessing and model building:

[0050] There are six methods for preprocessing the original spectrum: centering, range normalization, vector correction, scatter correction, first-order derivative, and second-order derivative. The recommended principal component number methods include external detection and internal crossover. The choice of the original spectrum preprocessing method directly affects the quality of the analysis model. The quantitative partial least squares (QPLS) method was used for modeling. The larger the determination coefficient (R2) and resolution (RPD) of the constructed near-infrared prediction model, the smaller the calibration standard deviation (SEC) and relative standard deviation (RSD), and the more accurate the prediction model. The above six preprocessing methods and the two recommended principal component number methods were compared and analyzed. The results are shown in Table 2. It was found that the second-order derivative + standard normal transformation + range normalization + centering was used for spectrum preprocessing to determine the acid detergent fiber content of ramie leaf powder.

[0051] Table 2 Results of ramie leaf acid detergent fiber spectral pretreatment

[0052]

[0053] Model building:

[0054] The CAUN IR software was used to construct the model, and the predicted value and the measured value after correction had a good linear relationship. The correlation coefficient of acid detergent fiber was 0.9421. This showed that the near infrared model of ramie leaf acid detergent fiber content had good prediction accuracy and could meet the accuracy requirements in material quality analysis.

[0055] Model Validation:

[0056] 22 ramie leaf samples that were not involved in the calibration were selected to verify the acid detergent fiber model. The verification results are shown in Table 3. The average values ​​of the measured and predicted values ​​of acid detergent fiber are close, which are 26.87% and 26.31% respectively, and the average difference is 0.56%. The maximum absolute error between the chemical value of acid detergent fiber and the predicted value is 3.64%, the minimum absolute error is 0.07%, and the average absolute error is 1.56%.

[0057] Table 3 Near infrared model verification results

[0058]

[0059] The prediction model is built using the predicted values ​​of optical data and the values ​​measured by chemical methods. The chemical method for detecting these indicators is done in accordance with national standards, which is time-consuming and laborious. The preliminary modeling requires obtaining a certain amount of chemical values ​​of ramie. After the model is built, it needs to be opened in the near-infrared analysis software. The x value is the predicted value of the absorption spectrum data scanned by the near-infrared agricultural product quality tester, and y is the predicted chemical value. The prediction model is established using the real measured value to ensure the reliability of the predicted value. In actual applications, it is only necessary to use a near-infrared instrument to scan the ramie leaf powder to obtain optical data, and directly use the model to measure the acid detergent fiber content in the leaves without the need for chemical methods. It is simple, fast, efficient, and saves money and effort.

[0060] For those skilled in the art, various corresponding changes and modifications can be made according to the above technical solutions and concepts, and all of these changes and modifications should be included in the protection scope of the claims of the present invention.

Claims

1. A method for rapid near-infrared detection of ramie leaf acid detergent fiber content, characterized in that: The steps include: Step 1: using chemical measurement method to detect the acid detergent fiber content in the sample ramie leaf powder; Step 2: Scan the absorption spectrum data of the sample ramie leaf powder using a near-infrared agricultural product quality tester; Step 3: Select the spectral pretreatment method for acid detergent fiber; Step 4: Using the scanned absorption spectrum data, combined with the detection value of the chemical measurement method and the data obtained by the spectrum preprocessing method, a spectrum analysis model is established; Step 5: Select ramie leaf powder for verification to calibrate the spectral analysis model.

2. The method for rapid near-infrared detection of ramie leaf acid detergent fiber content according to claim 1, characterized in that: In step 1, the determination of the acid detergent fiber content is repeated at least three times.

3. The method for rapid near-infrared detection of ramie leaf acid detergent fiber content according to claim 1, characterized in that: In the step 2, the absorption spectrum of the ramie leaves is scanned multiple times, and the scanning range is 1100nm to 2500nm.

4. The method for rapid near-infrared detection of ramie leaf acid detergent fiber content according to claim 1, characterized in that: When selecting the spectral preprocessing method for acid detergent fiber, the original spectral processing method with the smallest post-modeling correction standard deviation (SEC) and relative standard deviation (RSD) is selected. The second-order derivative + standard normal transformation + range normalization + centralization method is selected to preprocess the spectral data of acid detergent fiber.

5. The method for rapid near-infrared detection of ramie leaf acid detergent fiber content according to claim 1, characterized in that: In the step 4, the chemical measurement value of the acid detergent fiber content of the sample ramie leaf powder and the absorption spectrum data collected by three scans are averaged respectively by using CAUNIR near-infrared calibration software, the chemical measurement value of the acid detergent fiber content of the sample ramie leaf powder and the absorption spectrum preprocessed data are correlated one by one, and the quantitative partial least squares (QPLS) method is used for modeling; The original spectral data preprocessing method that maximizes the coefficient of determination and resolution of the spectral analysis model and minimizes the correction standard deviation and relative standard deviation is selected for data preprocessing and modeling.

6. The method for rapid near-infrared detection of ramie leaf acid detergent fiber content according to claim 1, characterized in that: In step 5, the spectral analysis model is verified, and the method with the smallest standard deviation of the predicted chemical value distribution of the calibration set is the optimal model.

7. The method for rapid near-infrared detection of acid detergent fiber content in ramie leaves according to claim 6, characterized in that: The correlation coefficient between the acid detergent fiber content in ramie leaves predicted by the spectral analysis model and the acid detergent fiber content in ramie leaves actually measured is 0.9421.

8. The method for rapid near-infrared detection of ramie leaf acid detergent fiber content according to claim 1, characterized in that: The step 4 uses a spectral analysis model to predict the content of acid detergent fiber in the ramie leaves to be tested, and the average value of the absorption spectrum data of the ramie leaf powder to be tested collected by the near-infrared agricultural product quality tester is input into the spectral analysis model. After spectral data preprocessing and model calculation and prediction, the contents of cellulose, hemicellulose, lignin and lignocellulose in the ramie leaves can be predicted.

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