CN106323796B - Method for determining content of chemical components of lignocellulose plant by using thermogravimetric analyzer - Google Patents
Method for determining content of chemical components of lignocellulose plant by using thermogravimetric analyzer Download PDFInfo
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Abstract
The invention relates to a method for rapidly determining the content of chemical components of a lignocellulose plant by using a thermogravimetric analyzer. The method comprises the steps of carrying out temperature programming treatment on a correction sample set by using a thermogravimetric analyzer to obtain a thermogravimetric curve of the correction sample set, measuring the target index content of the correction sample set by using a standard method to serve as a reference value, combining the thermogravimetric curve of the correction sample set and the reference value by using a partial least square method to establish a correction model, substituting the thermogravimetric curve of a sample to be detected into the correction model to calculate, and obtaining the target index content of the sample to be detected. Compared with the conventional wet chemical analysis, the method has the characteristics of short time, high speed, accurate analysis result, less sample demand and the like. The invention effectively solves the problems of complicated steps, long time, high cost and low efficiency of the traditional analysis method, and can carry out microanalysis and batch analysis.
Description
Technical Field
The invention relates to a method for rapidly obtaining the chemical component content of a sample to be tested by utilizing a chemometrics modeling to obtain a mathematical model related to the chemical component content of a plant and a thermogravimetric curve of the plant through chemometrics modeling in the process of analyzing the chemical components of the plant, which has the advantages of less required samples and rapid and accurate analysis and belongs to the field of analysis and test of the plant containing lignocellulose.
Background
The chemical component content determination of the lignocellulose plant is a necessary premise for reasonably utilizing plant resources, correctly evaluating the use value and the processing method of the plant resources and effectively applying the plant resources to degumming of textile hemp, pulping in papermaking and fermentation pretreatment of bioethanol.
The conventional method for testing the content of the phytochemicals generally adopts wet chemical analysis treatment, has the defects of complicated steps, more instruments and medicines, long analysis period, more sample quantity demand and the like, and is not beneficial to improving the working efficiency because the analysis steps are complicated, a large number of analysis testers need to be adhered to in the whole process in the analysis process. Therefore, the defects of the conventional analysis method are more obvious when the analysis is performed on a large batch of samples. For example, in the textile field, for example, when a sample is analyzed by using the national textile standard "GB 5889-86 ramie chemical component quantitative analysis method", 8 components, such as water content, lipid wax, pectin, hemicellulose, lignin, cellulose, ash content, and gel content, need to be tested and analyzed respectively. And some of the compositional tests, such as lignin, require several sub-experimental tests to obtain results. Normally a full chemical composition analysis of one sample takes a week to complete. In some cases where the need for analyzing samples is large, such as the evaluation of various plants cultivated in the germplasm research process and the composition analysis of various batches of hemp raw materials from different sources in degumming plants, tens to hundreds of samples need to be analyzed and tested every year. Only one analysis needs 1-2 analysis testers to complete the analysis all the year round, and due to the long analysis period, the production of a factory is often influenced due to the untimely analysis result. In addition, for the test analysis of a sample, about 20g of raw materials are consumed to obtain all chemical component data, so that the consumption of a large amount of samples increases the analysis cost and the burden of analysis testers; on the other hand, a small amount of sample cannot be analyzed.
Disclosure of Invention
The invention aims to provide a mathematical model for obtaining the contents of chemical components of plants and a thermogravimetric curve thereof by chemometric modeling, and a method for rapidly obtaining the contents of the chemical components by utilizing the model to analyze the thermogravimetric curve of a sample to be tested, wherein the analysis principle is as follows:
the plant mainly contains two major chemical components of polysaccharide (pectin, cellulose and hemicellulose) and lignin, and also has a small part of organic solvent extract, water extract and ash. The chemical components of plants have different thermal properties due to their different classes and structures. Specifically, the thermogravimetric analysis shows that chemical components of plants are thermally cracked in different temperature intervals, so that weight change is generated, a thermogravimetric curve is generated, the content of the chemical components of a sample is changed, and the generated thermogravimetric curves are different;
therefore, the thermogravimetric curve also carries a large amount of information of chemical component content besides reflecting the thermal performance information of the raw material. Chemometrics is the discipline that links the measurements of a chemical system to the state of the system through statistical and mathematical modeling.
According to the principle, the chemical component content of the corrected sample set is correlated with the thermogravimetric curve by using a chemometric means, a prediction model is obtained by modeling, and the unknown sample is predicted by using the model.
The invention adopts the following technical scheme: a method for rapidly determining the content of chemical components of a lignocellulose plant by using a thermogravimetric analysis technology is characterized by comprising the following steps of:
the first step, the sample thermogravimetric analysis step:
(1) respectively taking more than 60 plant varieties in different producing areas and different growing periods as samples to be detected; the collected samples to be tested are divided into two groups: one set was used as the calibration sample set and the other set was used as the validation sample set; wherein the ratio of the number of samples in the correction sample set to the number of samples in the verification sample set is 4: 1;
(2) respectively drying each sample of the correction sample set and each sample of the verification sample set at 105 ℃ for more than 4 hours until the samples are completely dried; then, crushing the samples, and sieving the samples by a 40-mesh sieve to obtain powder of each sample;
respectively weighing 20mg of powder of each sample, putting the powder into a thermogravimetric analyzer for thermogravimetric analysis, starting from the room temperature of 20 ℃, heating to 900 ℃ at the speed of 5 ℃/min, stopping heating, and cooling by using liquid nitrogen to obtain powder thermogravimetric analysis curves of all samples of the correction sample set and the samples of the verification sample set one by one;
and step two, a sample wet chemical analysis step:
respectively measuring lignin and holocellulose of the samples of all the correction sample sets and the samples of the verification sample set; determining the hemicellulose of the sample after the holocellulose is determined to obtain reference values of the lignin, the hemicellulose and the cellulose content of the sample;
thirdly, establishing a model by combining the thermogravimetric curve with a sample reference value:
carrying out baseline deduction and first derivative pretreatment on the collected correction sample heat collection thermogravimetric curve by using thermogravimetric analysis software to obtain a pretreatment thermogravimetric curve containing characteristic information of chemical component content of the correction sample concentrated sample;
then, combining the measured lignin, hemicellulose and cellulose content data with the pretreatment thermogravimetric curve data in the correction sample set, and establishing a correction model by adopting a partial least square method;
fourthly, model verification:
and (3) after the obtained original thermogravimetric curve data of the verification sample set is subjected to the same pretreatment of the third step, inputting the pretreated thermogravimetric curve data into a correction model to obtain a predicted value of the verification sample set, comparing the predicted value with the content of the phytochemical components in the verification sample set measured by a wet chemical analysis method, verifying the correction model, and judging whether the verification sample set is an out-of-range point outside a correction range.
If the sample set is verified to contain no bounded outliers, the model is complete and does not need to be optimized; if the correction model contains bounded external points, adding the bounded external points to reestablish the correction model according to the correction model establishing step again, continuously improving the correction model, optimizing and checking the performance of the correction model, circularly optimizing each modeling parameter, and finally determining the optimal parameter to ensure that the predicted value of the model verification set sample is consistent with the chemical analysis value to obtain the optimal model;
step five, a sample prediction step:
crushing a plant sample to be detected, obtaining thermogravimetric curve data through thermogravimetric analysis, wherein the analysis condition and method are consistent with the condition and method for obtaining the thermogravimetric curve of the correction sample set, preprocessing the thermogravimetric curve data, and substituting the preprocessed thermogravimetric curve data into the correction model to obtain the chemical component content value of the sample, wherein the thermogravimetric curve preprocessing method is consistent with the thermogravimetric curve preprocessing of the correction sample set.
Preferably, the lignocellulosic plant is wood, hemp or straw.
Further preferably, the method for rapidly determining the chemical component content of the lignocellulose plant by using the thermogravimetric analysis technology adopts an analysis method of national laboratory of renewable energy resources of America to determine the lignin of the sample;
adopting the national paper making standard: GB 02677.10-1995-T determination of the content of holocellulose in a papermaking raw material, and determination of the holocellulose in a sample is carried out;
for the sample after the determination of holocellulose, the national textile standard is adopted: GB5889-86 ramie chemical composition quantitative analysis method, survey the hemicellulose of sample, obtain sample chemical composition content reference value.
The direct technical effect brought by the technical scheme is as follows: the method has the advantages of less sample requirement (20mg), short analysis time (the content data of lignin, hemicellulose and cellulose in the sample can be measured after 3 h), and low manpower requirement (manual operation is needed only at the beginning and the end of the experiment, and the time for directly operating 100 samples by manpower is less than 8 h); and the whole testing process does not need any chemical consumption, the analysis and testing cost is low, the safety is high, the operation is simple, the analysis flow is short, and the subsequent sample residue and chemical waste liquid treatment is not needed.
For better understanding of the above technical effects, the detailed analysis and description are as follows:
in the technical scheme, at least 60 plant varieties with different producing areas and different growing periods are selected to ensure the robustness and universality of the final model; the model established by less than 60 samples has insufficient extraction of the characteristic information of the corresponding plant chemical components, the final model is not stable enough, and is easy to generate out-of-range points and cause larger prediction errors; the types of the samples in different regions and different growth periods are too single, and the prediction samples in different regions and different growth periods cannot be accurately predicted.
In the subsequent thermogravimetric analysis step, a plant thermogravimetric curve with the highest quality can be obtained in the shortest analysis time by using the temperature rise rate of 5 ℃/min, the total thermogravimetric analysis time is too long when the temperature rise rate is reduced, the temperature rise rate is increased, the temperature hysteresis measured by the test is more serious, the measured values of the initial weight loss temperature and the termination temperature become higher, the decomposition temperature range also becomes wider, and for chemical components which are not sensitive to decomposition weight loss, if the temperature rise rate is too fast, the temperature rise rate cannot respond sufficiently, and the weight loss step cannot be measured accurately or cannot be measured.
The chemical analysis method is one of the key points of the invention and has very critical effect on the quality of the final model.
This is because existing methods for the analysis of phytochemicals exist in different systems in different industries and in different fields and even in different countries. Due to the reasons of early establishment time, narrow application range and the like of a part of analysis systems, larger analysis errors can be generated for the chemical component analysis of conventional plant varieties; inaccurate chemical component reference values directly affect the stability and accuracy of the final model.
The analysis method adopted by the invention is generally accepted and adopted by a large number of scholars in recent years, can be generally suitable for the analysis method of lignin, hemicellulose and cellulose of various plants, and not only ensures the accuracy of the analysis result, but also has the analysis universality.
The method is characterized in that the thermogravimetric curve is combined with the plant chemical composition data, and the chemometrics means is used for correlation modeling, which is a technical key point of the method and is also the 'invention point' of the method.
To properly understand this, the following detailed explanation and description are provided:
as is well known to those skilled in the art, thermogravimetric analysis is a conventional quantitative analysis of the chemical composition of a multi-component mixture. The principle is that a mixture is heated in a program under a certain environment (oxygen, air or nitrogen), corresponding substances are decomposed or vaporized in different temperature intervals due to the difference of thermal properties of all chemical components of the mixture, so that the absolute mass of the mixture is changed, the change is reflected on a thermogravimetric curve, the thermogravimetric analysis calculates the absolute mass of the corresponding chemical substances at the corresponding temperature according to the change of the thermogravimetric curve, and the content of the compound in the mixture is obtained compared with the initial mass of the mixture.
However, lignocellulosic plants contain extremely complex chemical components, usually containing three major components, cellulose, hemicellulose, and lignin. That is, lignocellulosic plants are distinguished from other organic materials.
The chemical components (except cellulose) of the lignocellulose plant are general names of a mixture of similar chemical substances, the hemicellulose is a heteromultimer formed by several different types of monosaccharides, the lignin is an amorphous aromatic high polymer which is widely existed in a plant body and contains structural units of oxyphenbutamol or derivatives thereof in a molecular structure, the cellulose is a macromolecular polysaccharide formed by glucose, and the chemical components also have different polymerization degrees in the same plant; and the chemical components of different plants also have differences in structure and specific composition; the properties of the plant chemical components are reflected on thermogravimetric analysis, and the direct influence is that the thermal degradation of each chemical component has a certain temperature interval, and the degradation temperature intervals of different chemical components are overlapped, so that the direct quantification difficulty of the conventional thermogravimetric analysis is caused;
in addition, due to different types, sources and growth conditions, the thermal decomposition temperature intervals and the degradation speeds of the same chemical components of different samples are different, and the difficulty of direct quantification of thermogravimetric analysis is further increased.
Therefore, conventional thermogravimetric analysis cannot directly quantify the chemical composition of lignocellulosic plants. For the above reasons, wet chemical analysis methods are still commonly used for the analysis of lignocellulosic phytochemical components. However, as is well known, the conventional analysis method has the disadvantages of complicated steps, more instruments and medicines, long analysis period, more sample quantity requirements and the like.
The present invention addresses the above-mentioned problems of thermogravimetric analysis from another perspective. As described above, the thermogravimetric curve of a lignocellulosic plant is a comprehensive result of the degradation of one or more chemical components in a certain temperature interval, and therefore, it cannot be directly analyzed for further quantitative analysis.
From another perspective, however, the thermogravimetric curve data of the temperature interval includes partial information of one or more chemical components, so that the thermal degradation information of any one chemical component is the comprehensive reflection of the information of several temperature intervals on the thermogravimetric curve.
Therefore, theoretically, the content information of a certain chemical component of the sample can be comprehensively reflected through the information of several intervals of the thermogravimetric curve, namely, the content of the certain chemical component and the data of several temperature intervals on the thermogravimetric curve have a certain mathematical relationship, the relationship can be extracted and correlated through a chemometric means, and is gradually corrected and optimized through a large amount of corrected sample set data, and finally, a correlation model of the content of the certain chemical component and the thermogravimetric curve is established.
The technical scheme achieves the goal of quantifying the phytochemical components by using thermogravimetric analysis through a technical means combining statistical and chemometric means. The problems of data analysis difficulty caused by thermogravimetric curve deviation of the same chemical composition and thermogravimetric curve overlapping of different chemical compositions due to different types, different sources and different growth conditions in the prior art are solved.
More importantly, in the technical scheme, in the process of modeling the plant chemical components by adopting the chemometrics, the standard content data of the correction sample set is generally associated with two or more main factors in the thermogravimetric curve data, namely the content data of one chemical component can correspond to several characteristic data of the thermogravimetric curve, and the characteristic data is common characteristic information of the chemical components of all samples in the correction sample set.
It should be added that the near infrared spectroscopy is similar to the present invention, but the difference between the two is obvious. The concrete description is as follows:
although near infrared spectroscopy is consistent with the present invention in part, they differ significantly: in analytical principle, near infrared spectroscopy is a combined modeling of hydrogen bond information in plants with chemical composition.
The modeling is carried out by using the principle that the plant chemical components have the difference of thermal degradation performance; in the near-infrared spectroscopy, although the hydrogen bond information can also cover the content information of the chemical components of the plant, the hydrogen bond information contains too much information, and besides the information, the hydrogen bond information also contains other chemical, physical and even partial structure information of the plant, so that the near-infrared spectroscopy is difficult to extract the characteristic information of specific data, the modeling workload is large, and if the spectral information corresponding to the content of the chemical components cannot be accurately extracted, the robustness and the accuracy of a final model are not high;
the thermogravimetric analysis curve only expresses the thermal degradation information of the plant chemical components, so that the characteristic information is easy to extract, and an optimal prediction model is easy to obtain;
in sample preparation, the near infrared spectroscopy needs more than 5g of samples to carry out spectrum collection, and the thermogravimetric analysis method adopted by the invention can generally carry out analysis on 20mg of samples, so that the sample demand is small, and the method has unique advantages on trace sample analysis; in experimental operation, the near infrared spectroscopy requires manual spectral scanning of samples in sequence, and automation is not realized;
the thermogravimetric analysis rule adopted by the invention is provided with a batch sample automatic analysis system, and a large number of samples can be automatically analyzed after test parameters are set. Thus, the labor cost is saved.
In summary, compared with the prior art, the method for determining the content of the chemical components of the lignocellulose plant by the thermogravimetric analyzer provided by the invention analyzes the content of the chemical components of the plant by obtaining the thermogravimetric curve of the plant, and has the following technical effects:
(1) the sample amount is less, the method is suitable for analyzing trace samples, more than 10g of samples are needed for obtaining all chemical component contents by a common wet chemical method, and the sample used in thermogravimetric analysis of the application is only about 20 mg;
(2) the test is rapid, the common wet chemical method needs 3 days or more to obtain the content of all chemical components, and the time for thermogravimetric analysis of one sample is only about 3 hours;
(3) the thermogravimetric analyzer is less in labor consumption, high in working efficiency, capable of performing batch analysis, capable of only sequentially analyzing samples in wet chemical analysis, complex in analysis steps and operation and capable of requiring workers to supervise in the whole process, provided with an automatic sample feeding system, and capable of automatically performing test analysis without the need of the workers to supervise after early-stage setting.
(4) The method has the advantages that no chemical reagent is consumed, a large amount of chemical reagent is consumed for ordinary wet chemical analysis to obtain data, and the needed data can be obtained by thermogravimetric analysis without any chemical reagent consumption.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a graph comparing the predicted lignin content and the measured chemical analysis of example 1;
FIG. 3 is a graph comparing the predicted result of cellulose content of example 1 with the result of chemical analysis;
FIG. 4 is a graph comparing the predicted hemicellulose content and the measured chemical analysis results of example 1.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and examples.
Example 1
Taking wood raw materials as an example
Selecting 60 parts of wood raw materials, wherein: 25 parts of the medicinal composition are derived from Shandong Linyi, 15 parts of the medicinal composition is derived from Guizhou Guiyang, and 20 parts of the medicinal composition is derived from Changsha in Hunan; samples were prepared, each weighing 50 g.
All samples were dried at 105 ℃ and crushed, sieved through a 40 mesh sieve to obtain sample powders, about 30g of each sample, and then divided into two portions, one (20mg) for thermogravimetric analysis and the other (30g) for wet chemical analysis;
as shown in fig. 1, thermogravimetric curve collection of the calibration sample set and the sample to be measured: weighing about 20mg of the sample, putting the sample into a thermogravimetric analyzer for thermogravimetric analysis, collecting a thermogravimetric curve, and setting a temperature rise program as follows: heating the sample at the temperature of 20 ℃ from room temperature by 5 ℃/min, stopping heating when the temperature is increased to 900 ℃, cooling by using liquid nitrogen, and finishing analysis;
determination of the reference values of the calibration sample set: measuring Lignin of a sample by referring to a national laboratory analysis method of renewable energy resources, namely Determination of Lignin of the sample and Determination of content of holocellulose of papermaking raw materials by referring to the national papermaking standard GB 02677.10-1995-T, and measuring hemicellulose of the sample by referring to the national textile standard GB5889-86 ramie chemical component quantitative analysis method;
establishing a correction model: selecting 48 samples to establish a correction model, carrying out baseline deduction and first derivative pretreatment on the collected thermogravimetric curves of the correction sample set by using thermogravimetric analysis software to obtain characteristic information of chemical component content of the samples in the correction sample set, combining the measured content data with the characteristic information in the correction sample set, and establishing the correction model by adopting a partial least square method;
and (3) verification of the correction model: and verifying the established correction model by using the other 12 samples, preprocessing the obtained original thermogravimetric curve data of the verification sample set, inputting the preprocessed data into the correction model to obtain a predicted value of the verification sample set, and verifying the correction model by comparing the predicted value with the content of the phytochemical components in the verification sample set determined by a wet chemical analysis method.
The verification results are as follows:
table 1: verifying the comparison result between the chemical test value of the chemical components of the wood in the sample set and the predicted value obtained by the method
TABLE 2 comparison of chemical analysis with the method of the invention
| Method of producing a composite material | Analysis of errors | Amount of sample | When single sample is used | When it is used in general | Sample consumption | Continuous batch testing |
| Chemical analysis method | ≤0.5％ | 12 | 3d | 36d | 20g | Whether or not |
| The invention | <0.4％ | 12 | 3h | 1.5d | 20mg | Can be used for |
As can be seen from the data in Table 1 above and FIGS. 2-4, the method of the present invention can be used to accurately predict lignin, cellulose and hemicellulose of wood, and the coefficient R is determined by the prediction result and the test value2The values are all higher than 0.95, namely the values of the correlation coefficients R are all higher than 0.97;
the mean square deviations of the predicted value and the test value are less than 0.4%, and the prediction error is small, so that the method provided by the invention can be used for accurately testing the chemical components of the sample.
Table 2 shows that on the basis of successfully establishing a prediction model, the method provided by the invention is used for testing a subsequent unknown sample, the number of the used samples is only 20mg, and the time for testing lignin, hemicellulose and cellulose is 3 h; the conventional method requires a sample amount of 20g and a time for testing lipid wax, lignin, hemicellulose and cellulose is 3 days.
Therefore, the invention greatly reduces the sample amount and the test time of the test.
In addition, the thermogravimetric analyzer has a batch analysis and test function, and can continuously test 50 samples under the unattended condition, so that the analysis and test time and the labor consumption are further saved.
Example 2
Taking kenaf plants as an example, selecting 80 parts of kenaf raw materials, wherein the production place is 40 parts of Hunan, 20 parts of Shandong and 20 parts of Xinjiang; samples were prepared, each weighing 50 g.
All samples were dried at 105 ℃ and crushed, sieved through a 40 mesh sieve to obtain sample powders, about 30g of each sample, and then divided into two portions, one (20mg) for thermogravimetric analysis and the other (30g) for wet chemical analysis;
as shown in fig. 1, thermogravimetric curve collection of the calibration sample set and the sample to be measured: weighing about 20mg of the sample, putting the sample into a thermogravimetric analyzer for thermogravimetric analysis, collecting a thermogravimetric curve, and setting a temperature rise program as follows: heating the sample at the temperature of 20 ℃ from room temperature by 5 ℃/min, stopping heating when the temperature is increased to 900 ℃, cooling by using liquid nitrogen, and finishing analysis;
determination of the reference values of the calibration sample set: measuring Lignin of a sample by referring to a national laboratory analysis method of renewable energy resources, namely Determination of Lignin of the sample and Determination of content of holocellulose of papermaking raw materials by referring to the national papermaking standard GB 02677.10-1995-T, and measuring hemicellulose of the sample by referring to the national textile standard GB5889-86 ramie chemical component quantitative analysis method;
establishing a correction model: selecting 60 samples to establish a correction model, carrying out baseline deduction and first derivative pretreatment on the collected thermogravimetric curves of the correction sample set by using thermogravimetric analysis software to obtain characteristic information of chemical component content of the samples in the correction sample set, combining the measured content data with the characteristic information in the correction sample set, and establishing the correction model by adopting a partial least square method;
and (3) verification of the correction model: and verifying the established correction model by using the other 20 samples, preprocessing the obtained original thermogravimetric curve data of the verification sample set, inputting the preprocessed data into the correction model to obtain a predicted value of the verification sample set, and verifying the correction model by comparing the predicted value with the content of the phytochemical components in the verification sample set determined by a wet chemical analysis method.
The results show that the relationship between the predicted results of the method for predicting the lignin, cellulose and hemicellulose of the kenaf wood and the chemical test values is as follows: 0.98,0.97, 0.93; the predicted mean square deviations are respectively: 0.21%, 0.37%, 0.29%.
Example 3
Taking corn plants as an example, selecting 120 parts of cornstalk raw materials, wherein the production place is 40 parts of Shandong Gaomia, 40 parts of Shandong chatting and 40 parts of Shandong Dezhou; samples were prepared, each weighing 50 g.
All samples were dried at 105 ℃ and crushed, sieved through a 40 mesh sieve to obtain sample powders, about 30g of each sample, and then divided into two portions, one (20mg) for thermogravimetric analysis and the other (30g) for wet chemical analysis;
as shown in fig. 1, thermogravimetric curve collection of the calibration sample set and the sample to be measured: weighing about 20mg of the sample, putting the sample into a thermogravimetric analyzer for thermogravimetric analysis, collecting a thermogravimetric curve, and setting a temperature rise program as follows: heating the sample at the temperature of 20 ℃ from room temperature by 5 ℃/min, stopping heating when the temperature is increased to 900 ℃, cooling by using liquid nitrogen, and finishing analysis;
determination of the reference values of the calibration sample set: measuring Lignin of a sample by referring to a national laboratory analysis method of renewable energy resources, namely Determination of Lignin of the sample and Determination of content of holocellulose of papermaking raw materials by referring to the national papermaking standard GB 02677.10-1995-T, and measuring hemicellulose of the sample by referring to the national textile standard GB5889-86 ramie chemical component quantitative analysis method;
establishing a correction model: selecting 90 samples to establish a correction model, carrying out baseline deduction and first derivative pretreatment on the collected thermogravimetric curves of the correction sample set by using thermogravimetric analysis software to obtain characteristic information of chemical component content of the samples in the correction sample set, combining the measured content data with the characteristic information in the correction sample set, and establishing the correction model by adopting a partial least square method;
and (3) verification of the correction model: and verifying the established correction model by using the other 30 samples, preprocessing the obtained original thermogravimetric curve data of the verification sample set, inputting the preprocessed data into the correction model to obtain a predicted value of the verification sample set, and verifying the correction model by comparing the predicted value with the content of the phytochemical components in the verification sample set determined by a wet chemical analysis method.
The results show that the relationship between the predicted results of the method for predicting the lignin, cellulose and hemicellulose of the kenaf wood and the chemical test values is as follows: 0.94,0.99, 0.97; the predicted mean square deviations are respectively: 0.13%, 0.34%, 0.32%.
Claims (3)
1. A method for rapidly determining the content of chemical components of a lignocellulose plant by using a thermogravimetric analysis technology is characterized by comprising the following steps of:
the first step, the sample thermogravimetric analysis step:
(1) respectively taking more than 60 plant varieties in different producing areas and different growing periods as samples to be detected; the collected samples to be tested are divided into two groups: one set was used as the calibration sample set and the other set was used as the validation sample set; wherein the ratio of the number of samples in the correction sample set to the number of samples in the verification sample set is 4: 1;
(2) respectively drying each sample of the correction sample set and each sample of the verification sample set at 105 ℃ for more than 4 hours until the samples are completely dried; then, crushing the samples, and sieving the samples by a 40-mesh sieve to obtain powder of each sample;
respectively weighing 20mg of powder of each sample, putting the powder into a thermogravimetric analyzer for thermogravimetric analysis, starting from the room temperature of 20 ℃, heating to 900 ℃ at the speed of 5 ℃/min, stopping heating, and cooling by using liquid nitrogen to obtain powder thermogravimetric analysis curves of all samples of the correction sample set and the samples of the verification sample set one by one;
and step two, a sample wet chemical analysis step:
respectively measuring lignin and holocellulose of the samples of all the correction sample sets and the samples of the verification sample set; determining the hemicellulose of the sample after the holocellulose is determined to obtain reference values of the lignin, the hemicellulose and the cellulose content of the sample;
thirdly, establishing a model by combining the thermogravimetric curve with a sample reference value:
carrying out baseline deduction and first derivative pretreatment on the collected correction sample heat collection thermogravimetric curve by using thermogravimetric analysis software to obtain a pretreatment thermogravimetric curve containing characteristic information of chemical component content of the correction sample concentrated sample;
then, combining the measured lignin, hemicellulose and cellulose content data with the pretreatment thermogravimetric curve data in the correction sample set, and establishing a correction model by adopting a partial least square method;
fourthly, model verification:
after the same pretreatment of the third step is carried out on the obtained original thermogravimetric curve data of the verification sample set, inputting the pretreated thermogravimetric curve data into a correction model to obtain a predicted value of the verification sample set, comparing the predicted value with the content of the phytochemical components in the verification sample set measured by a wet chemical analysis method, verifying the correction model, and judging whether the verification sample set is an outlier outside a correction range;
if the sample set is verified to contain no bounded outliers, the model is complete and does not need to be optimized; if the correction model contains bounded external points, adding the bounded external points to reestablish the correction model according to the correction model establishing step again, continuously improving the correction model, optimizing and checking the performance of the correction model, circularly optimizing each modeling parameter, and finally determining the optimal parameter to ensure that the predicted value of the model verification set sample is consistent with the chemical analysis value to obtain the optimal model;
step five, a sample prediction step:
crushing a plant sample to be detected, obtaining thermogravimetric curve data through thermogravimetric analysis, wherein the analysis condition and method are consistent with the condition and method for obtaining the thermogravimetric curve of the correction sample set, preprocessing the thermogravimetric curve data, and substituting the preprocessed thermogravimetric curve data into the correction model to obtain the chemical component content value of the sample, wherein the thermogravimetric curve preprocessing method is consistent with the thermogravimetric curve preprocessing of the correction sample set.
2. The method of claim 1, wherein the lignocellulosic plant is wood, hemp, or straw.
3. The method for rapidly determining the chemical component content of the lignocellulose plant by using the thermogravimetric analysis technology according to claim 1 or 2, characterized in that the lignin of the sample is determined by using the analytical method of the national laboratory of renewable energy sources of the United states;
adopting the national paper making standard: GB 02677.10-1995-T determination of the content of holocellulose in a papermaking raw material, and determination of the holocellulose in a sample is carried out;
for the sample after the determination of holocellulose, the national textile standard is adopted: GB5889-86 ramie chemical composition quantitative analysis method, survey the hemicellulose of sample, obtain sample chemical composition content reference value.
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