Determination method, prediction method and prediction device for protein, starch, cellulose, hemicellulose, pectin and lignin in sample

Abstract

The invention belongs to the field of detection and analysis, and relates to a method for measuring protein, starch, cellulose, hemicellulose, pectin and lignin in a sample, which comprises the following steps: extracting the sample with an ethanol saturated salt solution to obtain a liquid phase substance; extracting the solid-phase substance with a dimethyl sulfoxide solution to obtain extract liquor and residues; measuring a liquid phase substance and the extract liquor by a coomassie brilliant blue method to obtain the protein content; carrying out acidolysis on the extract and dilute sulphuric acid, and measuring an acidolysis product by ion chromatography to obtain the content of starch; carrying out acidolysis on the residues and concentrated sulfuric acid, diluting, and continuously carrying out acidolysis to obtain liquid and solid products; measuring the liquid product by ion chromatography to obtain the contents of cellulose, hemicellulose and pectin; measuring the absorbance of a liquid product by using an ultraviolet spectrophotometer to obtain the content of the acid-soluble lignin; drying and roasting the solid product, and changing the mass before and after roasting to obtain the content of the acid-insoluble lignin; the sum of the acid-soluble lignin and the acid-insoluble lignin is the lignin content. The invention also relates to a method and a device for predicting the components in a sample. The method can quickly and accurately determine the contents of the components in the sample, and is high in precision.

Description

Technical Field

[0001] This invention belongs to the field of detection and analysis, specifically relating to a method for determining protein, starch, cellulose, hemicellulose, pectin and lignin in a sample, and also relating to a method and apparatus for predicting the content of protein, starch, cellulose, hemicellulose, pectin and lignin in a sample. Background Technology

[0002] Carbohydrates are the main products of photosynthesis in green plants, primarily including macromolecules such as starch, cellulose, lignin, and pectin. Starch is an important indicator of tobacco quality. Some related studies have shown that small molecule compounds produced by starch degradation break down during combustion to produce acidic substances. These acidic substances play an important role in neutralizing the alkaline gases produced during the combustion of nitrogen-containing compounds. To improve the quality of flue-cured tobacco, it is essential to balance the relationship between starch content and nicotine and nitrogen-containing compound content in the tobacco leaves. Appropriate starch content is a crucial indicator for improving the aroma and flavor of cigarettes. Cellulose, hemicellulose, and lignin are the main components of tobacco cell walls, accounting for approximately 20% of the total dry matter in flue-cured tobacco leaves and over 30% of the dry matter in tobacco stems. They determine the quality and processing resistance of tobacco leaves. Simultaneously, when these components decompose under heat, they release harmful components such as lower aldehydes, phenols, and benzo[a]pyrene, forming a woody aroma in the smoke, increasing the irritation of cigarettes, reducing their smoking quality, and thus affecting the sensory characteristics of cigarette smoke. Whether from the perspectives of tobacco leaf quality evaluation, processing and manufacturing, or cigarette smoke improvement, tar reduction and harm reduction, or even heated cigarette formulation design, accurately and rapidly determining the content of these key macromolecules in tobacco is of significant practical importance. Therefore, there is an urgent need for a method to determine or rapidly predict the content of key macromolecules in tobacco samples.

[0003] Near-infrared spectroscopy not only offers advantages such as fast analysis speed, simple instrument operation and maintenance, and low analysis cost, but also provides rich and stable spectral information, making it suitable for analyzing complex systems. Summary of the Invention

[0004] One objective of this invention is to provide a method for determining the content of protein, starch, cellulose, hemicellulose, pectin, and lignin in tobacco samples. This method can rapidly and accurately determine the content of the above-mentioned components in tobacco samples. Furthermore, another objective of this invention is to provide a method and apparatus for predicting the content of protein, starch, cellulose, hemicellulose, pectin, and lignin in tobacco samples. This method and apparatus can rapidly and accurately predict the content of protein, starch, cellulose, hemicellulose, pectin, and lignin in tobacco samples, and has good repeatability and high precision.

[0005] To achieve the above objectives, the first aspect of the present invention provides a method for determining protein, starch, cellulose, hemicellulose, pectin, and lignin in a sample, comprising the following steps:

[0006] The sample is extracted at least once (e.g., twice) using a saturated saline solution containing ethanol, and then separated into a liquid phase and a solid phase to obtain a liquid phase and a solid phase; wherein the sample is a tobacco sample; optionally, the solid phase is washed with a saturated saline solution containing ethanol, and the liquid after washing is incorporated into the liquid phase;

[0007] The solid phase was extracted at least once (e.g., three times) with a dimethyl sulfoxide solution to separate the extract and residue.

[0008] The protein content in the liquid phase and extract was determined by the Coomassie brilliant blue method, and the protein content in the sample was calculated based on the total protein content in the liquid phase and extract.

[0009] The extract is subjected to a first acid hydrolysis at 40°C-60°C (e.g., 50°C) with a sulfuric acid solution of 1%-4% by mass (e.g., 2% by mass) for 1-3 hours (e.g., 2 hours) to obtain the first acid hydrolysis product.

[0010] The first acid hydrolysis product or its dilution was detected by ion chromatography 1, and the starch content in the sample was calculated based on the glucose ion chromatography peak in the spectrum, wherein the starch content was expressed as glucose content.

[0011] The residue is optionally washed and then subjected to a second acid hydrolysis with a sulfuric acid solution of 70%-80% by mass (e.g., 72% by mass) at 20°C-40°C (preferably 27°C-35°C, e.g., 30°C) for 1-3 hours (preferably 1-2 hours, e.g., 1.8 hours, 2 hours) to obtain a second acid hydrolysis product.

[0012] The second acid hydrolysis product is diluted to a sulfuric acid concentration of 2%-6% by mass (e.g., 4% by mass), and then subjected to a third acid hydrolysis at 115℃-130℃ (preferably 120℃-125℃, e.g., 121℃) under sealed conditions for 40-70 minutes (preferably 50-70 minutes, e.g., 60 minutes). Solid-liquid separation is performed to obtain the acid hydrolysis liquid phase product and the acid hydrolysis solid phase product.

[0013] The acid hydrolysis liquid phase product or its dilution was detected by ion chromatography 1, and the cellulose and hemicellulose content in the sample was calculated based on the ion chromatographic peaks of arabinose, galactose, glucose, xylose and mannose in the spectrum.

[0014] The acid hydrolysis liquid phase product or its dilution was detected by ion chromatography 2. The pectin content of the sample was calculated based on the ion chromatography peak of galacturonic acid in the spectrum. The pectin content was calculated based on the galacturonic acid content.

[0015] The absorbance of the acid hydrolysis liquid phase product or its dilution at a wavelength of 210 nm was detected using a UV-Vis spectrophotometer, and the acid-soluble lignin content in the sample was calculated based on the absorbance value.

[0016] The acid-hydrolyzed solid product is dried at 90℃-110℃ (preferably 95℃-105℃, for example 100℃) and calcined at 530℃-560℃ (for example 540℃, 550℃) for 2-4 hours (preferably 2.5-3.5 hours, for example 3 hours, 3.5 hours). The acid-insoluble lignin content in the sample is calculated based on the mass change before and after calcination.

[0017] The sum of the acid-soluble lignin content and the acid-insoluble lignin content in the sample is taken as the lignin content in the sample.

[0018] In any embodiment of the first aspect, the operating conditions of ion chromatography 1 and ion chromatography 2 each independently include one or more of the following:

[0019] (A) The chromatographic column was a Carbo PAC PA 10;

[0020] (B) The detection mode is integral pulse amperometric detection;

[0021] (C) The working electrode is an Au electrode, and the reference electrode is an AgCl / Ag electrode;

[0022] (D) The flow rate of the mobile phase is 0.25 mL / min;

[0023] (E) The detection temperature is 20 ℃;

[0024] (F) The injection volume is 25 μL;

[0025] (G) The scan potential is the pulse point waveform shown in the table below; .

[0026] In any embodiment of the first aspect, the mobile phase used in ion chromatography 1 comprises: mobile phase A being water, mobile phase B being an aqueous solution of 180-220 mmol / L NaOH (e.g., 200 mmol / L NaOH), mobile phase C being an aqueous solution containing 0.7-1.2 mol / L NaAc (e.g., 1.0 mol / L NaAc) and 70-120 mmol / L NaOH (e.g., 100 mmol / L NaOH), and mobile phase D being an aqueous solution of 8-12 mmol / L NaOH (e.g., 10 mmol / L NaOH); and the elution program of the mobile phase is shown in the table below: .

[0027] In any embodiment of the first aspect, the mobile phase used in ion chromatography 2 comprises: mobile phase A being water, mobile phase B being an aqueous solution of 180-220 mmol / L NaOH (e.g., 200 mmol / L NaOH), and mobile phase C being an aqueous solution containing 0.7-1.2 mol / L NaAc (e.g., 1.0 mol / L NaAc) and 70-120 mmol / L NaOH (e.g., 100 mmol / L NaOH); and the elution program of the mobile phase is shown in the table below: .

[0028] In any embodiment of the first aspect, the sample is crushed and sieved (e.g., through a 40-60 mesh sieve) before extraction.

[0029] In any embodiment of the first aspect, each extraction is performed at 20°C-30°C (e.g., 25°C) and under ultrasonic conditions for 0.5-2 hours (e.g., 1 hour, 1.5 hours).

[0030] In any embodiment of the first aspect, after extraction, solid-liquid separation is performed after standing for 10-60 minutes (e.g., 20 minutes, 30 minutes, 50 minutes).

[0031] In any embodiment of the first aspect, solid-liquid separation is performed by filtration through a sand core funnel.

[0032] In any embodiment of the first aspect, the ratio of the saturated saline solution containing ethanol to the sample used in each extraction is 120:1-160:1 mL / g (e.g., 140:1 mL / g).

[0033] In any embodiment of the first aspect, the concentration of the saturated saline aqueous solution containing ethanol is 65%-95% by mass (e.g., 70% or 80% by mass).

[0034] In any embodiment of the first aspect, the volume of the saturated saline solution containing ethanol used for washing does not exceed the volume of the saturated saline solution containing ethanol used in each extraction.

[0035] In any embodiment of the first aspect, each extraction is performed at 50°C-70°C (e.g., 60°C) and under ultrasonic conditions for 5 minutes to 5 hours (e.g., 5 minutes, 10 minutes, 1 hour, 2 hours, 3 hours).

[0036] In any embodiment of the first aspect, after extraction, the sample is allowed to stand for 10-60 minutes (e.g., 30 minutes) before separation.

[0037] In any embodiment of the first aspect, the ratio of dimethyl sulfoxide solution to sample used in each extraction is 80:1 to 180:1 mL / g (e.g., 80:1 mL / g, 100:1 mL / g, 140:1 mL / g, 150:1 mL / g, 160:1 mL / g).

[0038] In any embodiment of the first aspect, the concentration of the dimethyl sulfoxide solution is 75%-95% by mass (e.g., 80%, 85%, 90%).

[0039] In any embodiment of the first aspect, the residue is washed with pure water and ethanol.

[0040] In any embodiment of the first aspect, during the first acid hydrolysis, the volume ratio of the extract to the sulfuric acid solution is 1:5 to 1:15 (e.g., 1:7, 1:9, 1:10, 1:12).

[0041] In any embodiment of the first aspect, during the second acidolysis, the residue is immersed in the sulfuric acid solution; optionally, the ratio of the sample to a sulfuric acid solution with a concentration of 70%-80% by mass (e.g., 72% by mass, 75% by mass, 78% by mass) is 1:3-1:8 g / mL (e.g., 1:4 g / mL, 1:6 g / mL).

[0042] In any embodiment of the first aspect, the acid-hydrolyzed solid product is dried to constant weight at 90°C-110°C.

[0043] In any embodiment of the first aspect, the Coomassie Brilliant Blue method includes: mixing the liquid phase and the extract with Coomassie Brilliant Blue G-250 solution respectively, then using a UV-Vis spectrophotometer to detect the absorbance of the two mixtures at a wavelength of 595 nm, and calculating the protein content in the liquid phase and the extract based on the absorbance value using an external standard analysis method; optionally, the external standard used in the external standard analysis method is bovine serum albumin.

[0044] In any embodiment of the first aspect, in the step of calculating the starch content in the sample, the glucose content C in the first acid hydrolysis product or its dilution is calculated by external standard analysis based on the ion chromatographic peak of glucose in the spectrum. 葡萄糖 Then calculate the starch content in the sample using the following formula:

[0045] Starch content in the sample = C 葡萄糖 ×0.9×V×f / m

[0046] Where V represents the volume of the first acid hydrolysis product or its dilution; f represents the volume ratio of the total extract to the extract taken; and m represents the dried mass of the sample.

[0047] In any embodiment of the first aspect, in the step of calculating the cellulose and hemicellulose content in the sample, the contents of arabinose, galactose, glucose, xylose, and mannose in the acid hydrolysis liquid product or its dilution are calculated by external standard analysis based on the ion chromatographic peaks of arabinose, galactose, glucose, xylose, and mannose in the chromatogram, and then the contents of cellulose and hemicellulose in the sample are calculated according to the following formula:

[0048] Ci = Cms × Dilution factor / Ri

[0049] Cellulose content in the sample = C 葡萄糖 ×0.9×V / m,

[0050] Hemicellulose content in the sample = [(C 阿拉伯糖 +C 木糖 )×0.88+(C 半乳糖 +C 甘露糖 [0.90] × V / m

[0051] Where Ri represents the recovery rate of a single sugar; Cms represents the content of a single sugar in the diluted acid hydrolysis product, with the dilution factor being the dilution factor of the acid hydrolysis product, or Cms × dilution factor representing the content of a single sugar in the acid hydrolysis product; Ci represents the converted content of a single sugar in the acid hydrolysis product; C 葡萄糖 C represents the glucose content in the converted acid hydrolysis liquid phase product; 半乳糖 This represents the galactose content in the converted acid hydrolysis liquid phase product; C 甘露糖 This represents the mannose content in the converted acid hydrolysis liquid phase product; C 木糖 This represents the xylose content in the converted acid hydrolysis liquid phase product; C 阿拉伯糖 V represents the arabinose content in the converted acid hydrolysis liquid phase product; V represents the volume of the acid hydrolysis liquid phase product; m represents the dried mass of the sample.

[0052] In any embodiment of the first aspect, the recovery rate Ri of a single type of sugar is calculated by the following steps:

[0053] A mixture of various sugars is mixed with a sulfuric acid solution of 70%-80% by mass (e.g., 72% by mass) to obtain a solution of the mixed sugars before acid hydrolysis.

[0054] The solution of the mixed sugar before acid hydrolysis was reacted sequentially according to the second and third acid hydrolysis processes, and the collected acid hydrolysis liquid phase product was used as the mixed sugar acid hydrolysis solution.

[0055] The mixed sugar solution before acid hydrolysis and the mixed sugar solution after acid hydrolysis were tested by ion chromatography (under the same detection conditions as above), and the contents of various sugars in the mixed sugar solution before acid hydrolysis and the mixed sugar solution after acid hydrolysis were calculated according to the spectra.

[0056] The recovery rate Ri of a single sugar is obtained by dividing the content of a single sugar in the acid hydrolysis solution of the mixed sugar by the content of the corresponding sugar in the solution before acid hydrolysis of the mixed sugar.

[0057] In any embodiment of the first aspect, in the step of calculating the pectin content in the sample, the content of galacturonic acid in the acid hydrolysis liquid phase product or its dilution is calculated by external standard analysis based on the ion chromatographic peak of galacturonic acid in the spectrum, and then the pectin content in the sample is calculated.

[0058] In any embodiment of the first aspect, in the step of calculating the acid-soluble lignin content in the sample, the acid-soluble lignin content in the acid hydrolysis liquid phase product or its dilution is calculated by external standard analysis based on the absorbance value, and then the acid-soluble lignin content in the sample is calculated; optionally, the external standard used in the external standard analysis is alkaline lignin.

[0059] A second aspect of the present invention provides a method for predicting the content of protein, starch, cellulose, hemicellulose, pectin, and lignin in a sample, comprising the following steps:

[0060] The sample was analyzed using a near-infrared spectrometer to obtain its near-infrared spectrum; wherein, the sample was a tobacco sample.

[0061] The near-infrared spectrum of the sample was preprocessed to obtain the preprocessed spectrum of the sample;

[0062] By substituting specific band spectra from the pre-processed spectrum of the sample into a pre-established prediction model, the predicted values ​​of protein, starch, cellulose, hemicellulose, pectin, and lignin content in the sample are obtained.

[0063] In any implementation of the second aspect, the prediction model is established through the following steps:

[0064] Near-infrared spectra of multiple samples were obtained by detecting them using a near-infrared spectrometer.

[0065] The near-infrared spectra of multiple samples were preprocessed to obtain the preprocessed spectra of multiple samples;

[0066] The contents of protein, starch, cellulose, hemicellulose, pectin and lignin in multiple samples were determined according to the method in the first aspect.

[0067] Specific bands in the preprocessed spectra of multiple samples were fitted with the contents of protein, starch, cellulose, hemicellulose, pectin, and lignin in the samples to obtain predictive models for the contents of protein, starch, cellulose, hemicellulose, pectin, and lignin in the samples.

[0068] In any implementation of the second aspect, the preprocessing method is selected from one or more of the following: multivariate scattering correction, standard normal variable transformation, first derivative, second derivative, SG smoothing, and Norris smoothing.

[0069] In any embodiment of the second aspect, when predicting the protein content in a sample and / or establishing a predictive model for protein content, the preprocessing methods are, in order, first derivative and Norris smoothing, using a specific wavelength range of 8341.12–3915.11 cm⁻¹. -1 .

[0070] In any embodiment of the second aspect, when predicting the starch content in a sample and / or establishing a predictive model for starch content, the preprocessing methods are, in order, first derivative and SG smoothing, using a specific wavelength range of 7846.67-3929.65 cm⁻¹. -1 .

[0071] In any embodiment of the second aspect, when predicting the cellulose content in a sample and / or establishing a predictive model for cellulose content, the preprocessing methods are, in sequence, multivariate scattering correction, first derivative, and Norris smoothing, using a specific wavelength range of 8222.05–3991.08 cm⁻¹. -1 .

[0072] In any embodiment of the second aspect, when predicting the hemicellulose content in a sample and / or establishing a predictive model for the hemicellulose content, the preprocessing methods are, in order, first derivative and SG smoothing, using a specific wavelength range of 8328.46–3901.08 cm⁻¹. -1 .

[0073] In any embodiment of the second aspect, when predicting the pectin content in a sample and / or establishing a predictive model for pectin content, the preprocessing methods are, in sequence, multivariate scattering correction, first derivative, and SG smoothing, using a specific wavelength band of 7866.05–4001.05 cm⁻¹. -1 .

[0074] In any embodiment of the second aspect, when predicting the lignin content in a sample and / or establishing a predictive model for lignin content, the preprocessing methods are, in sequence, multivariate scattering correction, first derivative, and Norris smoothing, using a specific wavelength range of 8062.85–3901.17 cm⁻¹. -1 .

[0075] In any implementation of the second aspect, the number of principal factors used in the step of establishing the prediction model is 7 to 11.

[0076] In any embodiment of the second aspect, the sample is dried, crushed, and sieved (e.g., powder with a particle size between 40 and 60 mesh) before detection using a near-infrared spectrometer.

[0077] In any embodiment of the second aspect, the operating conditions of the near-infrared spectrometer include one or more of the following:

[0078] (A) Scanning was performed using a diffuse reflectance spectral module;

[0079] (B) Scanning range is 10000-3900 cm -1 ;

[0080] (C) Scanning interval is 4 cm -1 ;

[0081] (D) The number of scans was 68;

[0082] (E) Resolution is 8 cm -1 ;

[0083] (F) Before testing, flatten the sample and make the sample thickness greater than 5 mm.

[0084] A third aspect of the present invention provides an apparatus for predicting the content of protein, starch, cellulose, hemicellulose, pectin, and lignin in a sample, comprising:

[0085] The detection module is used to detect the sample using a near-infrared spectrometer to obtain the near-infrared spectrum of the sample; wherein the sample is a tobacco sample;

[0086] The preprocessing module is used to preprocess the near-infrared spectrum of the sample to obtain the preprocessed spectrum of the sample.

[0087] The prediction module is used to substitute specific band spectra from the pre-processed spectrum of the sample into a pre-established prediction model to calculate the predicted values ​​of protein, starch, cellulose, hemicellulose, pectin and lignin content in the sample.

[0088] A fourth aspect of the present invention provides an apparatus for predicting the content of protein, starch, cellulose, hemicellulose, pectin, and lignin in a sample, wherein:

[0089] Memory, used to store instructions;

[0090] A processor coupled to the memory, the processor being configured to execute the method as described in the second aspect of the invention based on instructions stored in the memory.

[0091] A fifth aspect of the present invention provides a computer-readable storage medium, characterized in that the readable storage medium stores computer instructions, which, when executed by a processor, implement the method as described in the first or second aspect of the present invention.

[0092] The present invention has achieved at least one of the following beneficial effects:

[0093] 1. The determination method of the present invention can quickly and accurately determine the content of protein, starch, cellulose, hemicellulose, pectin and lignin in tobacco samples.

[0094] 2. The prediction method of the present invention can accurately predict the content of protein, starch, cellulose, hemicellulose, pectin and lignin in tobacco samples. It has good repeatability and high precision. Furthermore, the method of the present invention can obtain the predicted value by detecting the near-infrared spectrum of the sample, performing spectral preprocessing, and substituting specific bands into the prediction model for calculation. It has a short prediction time and high prediction efficiency.

[0095] 3. The prediction model of this invention adopts principal factor number optimization fitting to ensure the full extraction and stable expression of spectral information. Cross-validation and external validation results show that the correlation coefficient between the predicted value and the measured value exceeds 0.92, which significantly reduces the prediction error and improves the reliability and consistency of the prediction results.

[0096] 4. The prediction method of this invention is not only applicable to the quality evaluation of tobacco samples and the monitoring of the processing process, but also provides data support for the quality improvement, tar reduction and harm reduction of tobacco products and formula design. Attached Figure Description

[0097] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings, wherein...

[0098] Figure 1This is a schematic diagram of an embodiment of the method of the present invention for predicting the content of protein, starch, cellulose, hemicellulose, pectin and lignin in a sample;

[0099] Figure 2 This is a schematic diagram of an embodiment of the apparatus of the present invention for predicting the content of protein, starch, cellulose, hemicellulose, pectin and lignin in a sample;

[0100] Figure 3 This is a flowchart of the method for determining the protein, starch, cellulose, hemicellulose, pectin and lignin content of tobacco samples in Example 1 of the present invention.

[0101] Figure 4 This is a distribution chart of the measured and predicted values ​​of starch content in tobacco leaf samples from the verification set of Example 3 of the present invention; Figure 5 This is a distribution chart of the measured and predicted values ​​of cellulose content in tobacco leaf samples from the verification set of Example 3 of the present invention;

[0102] Figure 6 This is a distribution chart of the measured and predicted values ​​of hemicellulose content in tobacco leaf samples from the verification set of Example 3 of the present invention.

[0103] Figure 7 This is a distribution chart of the measured and predicted values ​​of lignin content in tobacco leaf samples from the verification set of Example 3 of the present invention;

[0104] Figure 8 This is a distribution chart of the measured and predicted values ​​of pectin content in tobacco leaf samples from the verification set of Example 3 of the present invention.

[0105] Figure 9 This is a distribution chart of the measured and predicted values ​​of protein content in tobacco leaf samples from the verification set of Example 3 of the present invention. Detailed Implementation

[0106] The embodiments of the present invention will now be clearly and completely described in conjunction with examples. Obviously, the described embodiments are merely some, not all, of the embodiments of the present invention. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0107] Figure 1 This is a schematic diagram of an embodiment of the method of the present invention for predicting the content of protein, starch, cellulose, hemicellulose, pectin and lignin in a sample;

[0108] The method includes:

[0109] Step 101: Detect the sample using a near-infrared spectrometer to obtain the near-infrared spectrum of the sample; wherein, the sample is a tobacco sample;

[0110] Step 102: Preprocess the near-infrared spectrum of the sample to obtain the preprocessed spectrum of the sample;

[0111] Step 103: Substitute the specific band spectrum in the pre-processed spectrum of the sample into the pre-established prediction model to calculate the predicted values ​​of protein, starch, cellulose, hemicellulose, pectin and lignin content in the sample.

[0112] In some implementations, the prediction model is established through the following steps:

[0113] Near-infrared spectra of multiple samples were obtained by detecting them using a near-infrared spectrometer.

[0114] The near-infrared spectra of multiple samples were preprocessed to obtain the preprocessed spectra of multiple samples;

[0115] The contents of protein, starch, cellulose, hemicellulose, pectin and lignin in multiple samples were determined according to the method in the first aspect.

[0116] Specific bands in the preprocessed spectra of multiple samples were fitted with the contents of protein, starch, cellulose, hemicellulose, pectin, and lignin in the samples to obtain predictive models for the contents of protein, starch, cellulose, hemicellulose, pectin, and lignin in the samples.

[0117] In some implementations, the preprocessing method is selected from one or more of the following: multivariate scattering correction, standard normal variable transformation, first derivative, second derivative, SG smoothing, and Norris smoothing.

[0118] In some implementations, when predicting protein content in a sample and / or establishing a predictive model for protein content, the preprocessing methods are, in order, first derivative and Norris smoothing, using a specific wavelength range of 8341.12–3915.11 cm⁻¹. -1 .

[0119] In some implementations, when predicting the starch content in a sample and / or establishing a predictive model for starch content, the preprocessing methods are, in order, first derivative and SG smoothing, using a specific wavelength range of 7846.67–3929.65 cm⁻¹. -1 .

[0120] In some implementations, when predicting the cellulose content in a sample and / or establishing a predictive model for cellulose content, the preprocessing methods are, in sequence, multivariate scattering correction, first derivative, and Norris smoothing, using a specific wavelength range of 8222.05–3991.08 cm⁻¹. -1 .

[0121] In some implementations, when predicting the hemicellulose content in a sample and / or establishing a predictive model for hemicellulose content, the preprocessing methods are, in order, first derivative and SG smoothing, using a specific wavelength range of 8328.46–3901.08 cm⁻¹. -1 .

[0122] In some implementations, when predicting the pectin content in a sample and / or establishing a predictive model for pectin content, the preprocessing methods are, in sequence, multivariate scattering correction, first derivative, and SG smoothing, using a specific wavelength range of 7866.05–4001.05 cm⁻¹. -1 .

[0123] In some implementations, when predicting the lignin content in a sample and / or establishing a predictive model for lignin content, the preprocessing methods are, in sequence, multivariate scattering correction, first derivative, and Norris smoothing, using a specific wavelength range of 8062.85–3901.17 cm⁻¹. -1 .

[0124] In some implementations, the number of principal factors used in the step of building the prediction model is 7 to 11.

[0125] In some implementations, the sample is dried, crushed, and sieved (e.g., powder with a particle size between 40 and 60 mesh) before being detected by a near-infrared spectrometer.

[0126] In some implementations, the operating conditions of the near-infrared spectrometer include one or more of the following:

[0127] (A) Scanning was performed using a diffuse reflectance spectral module;

[0128] (B) Scanning range is 10000-3900 cm -1 ;

[0129] (C) Scanning interval is 4 cm -1 ;

[0130] (D) The number of scans was 68;

[0131] (E) Resolution is 8 cm -1 ;

[0132] (F) Before testing, flatten the sample and make the sample thickness greater than 5 mm.

[0133] Figure 2 This is a schematic diagram of an embodiment of the apparatus of the present invention for predicting the content of protein, starch, cellulose, hemicellulose, pectin and lignin in a sample; Figure 1 The method shown is through Figure 2 The device is implemented.

[0134] The device includes:

[0135] The detection module 11 is used to detect the sample using a near-infrared spectrometer to obtain the near-infrared spectrum of the sample; wherein the sample is a tobacco sample;

[0136] The preprocessing module 12 is used to preprocess the near-infrared spectrum of the sample to obtain the preprocessed spectrum of the sample.

[0137] The prediction module 13 is used to substitute specific band spectra from the pre-processed spectrum of the sample into a pre-established prediction model to calculate the predicted values ​​of protein, starch, cellulose, hemicellulose, pectin and lignin content in the sample.

[0138] The present invention also relates to another apparatus for predicting the content of protein, starch, cellulose, hemicellulose, pectin and lignin in a sample, wherein:

[0139] Memory, used to store instructions;

[0140] A processor, coupled to the memory, is configured to execute instructions stored in the memory, such as... Figure 1 The method shown.

[0141] The present invention also relates to a computer-readable storage medium, characterized in that the readable storage medium stores computer instructions, which, when executed by a processor, implement as follows: Figure 1 The method shown.

[0142] The memory may include high-speed RAM or non-volatile memory, such as at least one disk drive. The memory may also be a memory array. The memory may be divided into blocks, and these blocks may be combined into virtual volumes according to certain rules.

[0143] The processor may be a central processing unit (CPU), a GPU, an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention.

[0144] The apparatus described above can be implemented as a general-purpose processor, programmable logic controller (PLC), digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component or any suitable combination thereof for performing the functions described herein.

[0145] Coomassie Brilliant Blue G-250 solution: Weigh 0.01g of Coomassie Brilliant Blue G-250, dissolve it in 5mL of 95% ethanol aqueous solution, add 10mL of 85% phosphate aqueous solution, and finally dilute to 100mL with ultrapure water. Mix well and store in a brown bottle for later use.

[0146] Example 1: Method for determining the content of protein, starch, cellulose, hemicellulose, pectin, and lignin.

[0147] The method for determining the content of protein, starch, cellulose, hemicellulose, pectin, and lignin in tobacco samples in this embodiment is illustrated in the flowchart below. Figure 1 As shown.

[0148] (1) Sample pretreatment

[0149] Tobacco leaves were dried at 40℃ until they could be crushed, ground, and passed through a 40-60 mesh sieve. The sieved material was collected as the test sample. 0.25g of the test sample was accurately weighed and 35mL of a saturated saline solution containing 80% ethanol was added. The sample was extracted at 25℃ under ultrasonic conditions for 1 hour, allowed to stand for 0.5 hours, and filtered using a sintered glass funnel. The filtrate was collected. 35mL of a saturated saline solution containing 80% ethanol was added to the precipitate, and the above process was repeated. The filtrate was collected. The precipitate was then washed with 20mL of a saturated saline solution containing 80% ethanol, and the washing liquid was collected. The filtrate and washing liquid were combined as the test solution.

[0150] Add 40 mL of 90% dimethyl sulfoxide aqueous solution to the remaining precipitate from the above operation and extract for 3 hours at 60°C under ultrasonic conditions. Let stand for 0.5 hours and filter to obtain the extract and filter residue. Add 40 mL of 90% dimethyl sulfoxide aqueous solution to the filter residue and repeat the above operation to obtain the extract and filter residue. Then add 20 mL of 90% dimethyl sulfoxide aqueous solution to the filter residue and extract for 5-10 minutes at 60°C under ultrasonic conditions to obtain the extract and filter residue. Combine all the extracts.

[0151] The filter residue was rinsed multiple times with pure water to remove residual dimethyl sulfoxide solution, and then rinsed twice with a small amount of anhydrous ethanol. The filter residue was then dried for later use.

[0152] (2) Determination of protein content

[0153] (2.1) Plotting the standard curve:

[0154] A stock solution with a concentration of 10 mg / mL was prepared using bovine serum albumin standard (purity >99%, Beijing Bailingwei Technology Co., Ltd.). Volumes of 0, 2, 4, 8, 12, 16, and 20 μL of the stock solution were taken and diluted to 200 μL with water. 5 mL of Coomassie Brilliant Blue G-250 solution was added to each solution and mixed thoroughly to obtain a series of standard solutions of different concentrations. After standing for 5 min, the absorbance of each standard solution at 595 nm was measured using a UV-Vis spectrophotometer. A standard curve was plotted with the concentration of the standard solution on the x-axis and the absorbance on the y-axis, yielding the curve y = 6.035x + 0.13.

[0155] (2.2) Determination of protein content:

[0156] Accurately transfer 1.0 mL of the test solution and 1.0 mL of the extract, add 5 mL of Coomassie Brilliant Blue G-250 solution to each, mix well and let stand for 5 min, and then use a UV-Vis spectrophotometer to measure the absorbance of the two liquids at 595 nm.

[0157] Substitute the absorbance of the two liquids into the standard curve to calculate the protein concentrations C1 and C2 (in g / mL) in the test solution and extract, respectively. Calculate the protein content X (in g / 100g) in the tobacco sample according to the following formula.

[0158] X=(C1V1+C2V2) / m

[0159] Where V1 and V2 are the volumes of the test solution and the extract, respectively, in milliliters (mL); m is the dry mass of the tobacco sample, in grams.

[0160] (3) Determination of starch

[0161] (3.1) Plotting the standard curve:

[0162] A stock solution of glucose standard was prepared with water to a concentration of 0.28 mg / mL. This stock solution was then serially diluted with 0.004% sulfuric acid solution to obtain standard solutions with concentrations of 0.14 μg / mL, 0.28 μg / mL, 0.56 μg / mL, 1.12 μg / mL, and 2.8 μg / mL. Ion chromatography was used to determine the concentrations of each standard solution [the operating conditions for ion chromatography were the same as in step (3.2)]. A standard curve was plotted with the concentration of the standard solution on the x-axis and the glucose peak area on the y-axis to obtain the curve y = 10.058x + 0.971.

[0163] (3.2) Determination of starch content:

[0164] Transfer 2 mL of the extract to a 100 mL Erlenmeyer flask, add 18 mL of 2% sulfuric acid solution, and acidify in a 50°C water bath for 2 hours. Cool the acidification product to room temperature, add water to a final volume of 100 mL, and take a small amount of the diluted acidification product for ion chromatography detection. The ion chromatography operating conditions include:

[0165] Chromatographic column: Carbo PAC PA 10 (2.0 mm × 250 mm, with a PA 10 guard column of 2 mm × 50 mm); Detection mode: Integrating pulse amperometric detection; Working electrode: Au electrode; Reference electrode: AgCl / Ag electrode; Scan potential is the pulse point waveform shown in Table 1; Mobile phase: Mobile phase A is water, mobile phase B is 200 mmol / L NaOH aqueous solution, mobile phase C is an aqueous solution containing 1.0 mol / L NaAc and 100 mmol / L NaOH, and mobile phase D is 10 mmol / L NaOH aqueous solution; Mobile phase flow rate: 0.25 mL / min; Detection temperature: 20 ℃; Injection volume: 25 μL; Elution program of mobile phase is shown in Table 2.

[0166] Table 1. Scanning potentials in ion chromatography

[0167] Table 2 Elution program of mobile phase (volume percentage)

[0168] *: A negative retention time indicates the time required to rinse the ion chromatography column before injection.

[0169] Calculation process: Substitute the glucose peak area of ​​the acid hydrolysis product after volume adjustment into the standard curve to calculate the starch concentration C in the acid hydrolysis product after volume adjustment. 葡萄糖 (Calculated as glucose, in g / mL), and then calculate the starch content in the tobacco sample (calculated as glucose, in mass%) according to the following formula.

[0170] Starch content in tobacco leaf samples = C 葡萄糖 ×0.9×V×f / m,

[0171] Where V represents the volume of the acid hydrolysis product after volume adjustment (in mL); f represents the volume ratio of the total extract to the extract taken; and m represents the dried mass of the tobacco sample (in g).

[0172] (4) Determination of cellulose and hemicellulose

[0173] (4.1) Plotting the standard curve:

[0174] A mixed standard consisting of 0.008 g arabinose, 0.012 g galactose, 0.07 g glucose, 0.007 g xylose, and 0.003 g mannose was prepared by adding water to a mixed standard stock solution. The concentrations of arabinose, galactose, glucose, xylose, and mannose in the mixed standard stock solution were 0.032 mg / mL, 0.048 mg / mL, 0.28 mg / mL, 0.028 mg / mL, and 0.012 mg / mL, respectively. The mixed standard stock solution was transferred and diluted with 0.004% sulfuric acid solution by 2000 times, 1000 times, 500 times, 250 times, and 100 times, respectively, to obtain a series of mixed standard solutions with different concentrations. The concentrations of the mixed standard solutions were determined by ion chromatography [the operating conditions for ion chromatography are the same as in step (3.2)]. The standard curves for each sugar were plotted with the concentration of each sugar in the mixed standard solution as the abscissa and the peak area of ​​each sugar response as the ordinate, as shown in Table 3.

[0175] Table 3. Linearity, correlation coefficient, and limit of detection of monosaccharide standards

[0176] (4.2) Determination of cellulose and hemicellulose content:

[0177] The filter residue obtained in step (1) was transferred into a high-pressure flask, and 1.5 mL of 72% sulfuric acid aqueous solution was added. The mixture was stirred until the filter residue was completely submerged in the sulfuric acid aqueous solution. The first acid hydrolysis was carried out in a 30°C water bath for 2 hours. After the first hydrolysis, 42 mL of ultrapure water was added to the high-pressure flask for dilution to bring the sulfuric acid concentration in the diluted solution to 4% by mass.

[0178] Prepare a mixed standard (composed of 0.008 g arabinose, 0.012 g galactose, 0.07 g glucose, 0.007 g xylose, 0.003 g mannose and 0.04 g galacturonic acid). Transfer the mixed standard to another high-pressure flask, add 1.5 mL of 72% sulfuric acid aqueous solution, stir well to obtain the solution of the mixed standard before acid hydrolysis, and then repeat the above operation for acid hydrolysis and dilution.

[0179] The diluted two pressure-resistant bottles were placed in an autoclave and subjected to a second acid hydrolysis at 121 °C for 60 minutes. After cooling, the acid hydrolysis products were vacuum filtered using dried and weighed ashless filter paper, and the filtrate and residue were collected. The filtrates were the acid hydrolysis residue and the acid hydrolysis solution of the mixed standard, respectively. The acid hydrolysis residue was diluted to 250 mL with ultrapure water to obtain a diluted solution of the acid hydrolysis residue. Then, the diluted solution of the acid hydrolysis residue and the acid hydrolysis solution of the mixed standard were detected by ion chromatography. The operating conditions of ion chromatography were the same as in step (3.2).

[0180] The ion chromatographic peak areas of various sugars in the diluted filtrate of the filter residue acid hydrolysis and the acid hydrolysis solution of the mixed standard were substituted into the standard curve to calculate the content of various sugars in the diluted filtrate of the filter residue acid hydrolysis and the acid hydrolysis solution of the mixed standard. Then, the cellulose and hemicellulose content in the tobacco sample were calculated according to the following formula: Recovery rate Ri = Content of a single sugar in the acid hydrolysis solution of the mixed standard / Content of a single sugar in the solution before acid hydrolysis of the mixed standard.

[0181] Ci = Cms × Dilution factor / Ri

[0182] Cellulose content = 100% × (C glucose × V × 0.9) / M0

[0183] Hemicellulose content = 100% × [(C galactose + C mannose) × 0.9 + (C xylose + C arabinose) × 0.88] × V / M0

[0184] in:

[0185] Ri represents the recovery rate of a single type of sugar;

[0186] Cms represents the content (mg / L) of a single type of sugar in the diluted solution of the acid hydrolysis filtrate of the filter residue.

[0187] Ci represents the content (mg / L) of a single type of sugar in the converted acid hydrolysis filtrate of the filter residue.

[0188] C glucose is the glucose content (mg / L) in the acid hydrolysis filtrate of the filter residue after conversion.

[0189] C-galactose refers to the galactose content (mg / L) in the acid hydrolysis filtrate of the filter residue after conversion.

[0190] C_mannose is the mannose content (mg / L) in the acid hydrolysis filtrate of the filter residue after conversion.

[0191] C xylose is the xylose content (mg / L) in the acid hydrolysis filtrate of the filter residue after conversion.

[0192] C arabinose is the arabinose content (mg / L) in the acid hydrolysis filtrate of the filter residue after conversion.

[0193] V is the volume (L) of the filtrate from the acid hydrolysis of the filter residue;

[0194] M0 represents the mass (g) of the tobacco leaf sample.

[0195] In the above formula, "0.9" is the dehydration correction factor for dextran, galactan, or mannan; "0.88" is the dehydration correction factor for xylan or arabinogalactan.

[0196] (5) Determination of pectin

[0197] (5.1) Plotting the standard curve:

[0198] Accurately weigh 50 mg of galacturonic acid standard (accurate to 0.1 mg), dissolve it in 0.1 mol / L sulfuric acid solution, and then transfer it to a 50 mL volumetric flask and dilute to volume to prepare a 1000 mg / L standard stock solution. Pipette 10 mL of the standard stock solution into 100 mL volumetric flasks, dilute to volume with 0.1 mol / L sulfuric acid solution to prepare 100 mg / L standard solutions, and continue to dilute stepwise to obtain standard solutions with concentrations of 0.4, 1.2, 2.0, 2.5, and 5.0 mg / L. Ion chromatography was used to determine the concentration of each standard solution [the operating conditions for ion chromatography are the same as in step (5.2)]; a standard curve was plotted with the concentration of the galacturonic acid standard solution as the x-axis and the peak area of ​​galacturonic acid as the y-axis to obtain the standard curve (Table 4).

[0199] Table 4. Linearity, correlation coefficient, and detection limit of galacturonic acid

[0200] (5.2) Determination of pectin content:

[0201] The diluted solution of the acid hydrolysis filtrate obtained in step (4.2) was analyzed by ion chromatography. The mobile phases were: mobile phase A was water, mobile phase B was 200 mmol / L NaOH aqueous solution, and mobile phase C was an aqueous solution containing 1.0 mol / L NaAc and 100 mmol / L NaOH. The elution program of the mobile phases is shown in Table 5. Other operating conditions of ion chromatography were the same as in step (3.2).

[0202] Table 5 Elution program of mobile phase (volume percentage)

[0203] Calculation process: Substitute the peak area of ​​galacturonic acid measured in the diluted solution of the acid hydrolysis filtrate of the filter residue into the standard curve in Table 4 to calculate the galacturonic acid concentration C (in g / mL) in the diluted solution of the acid hydrolysis filtrate of the filter residue. Calculate the pectin content in the tobacco sample according to the following formula, expressed as galacturonic acid content.

[0204] Pectin content in tobacco leaf samples = 100% × C × V / m

[0205] Where V represents the volume of the diluted filtrate from the acid hydrolysis of the filter residue (in mL); m represents the dried mass of the tobacco sample (in g).

[0206] (6) Determination of lignin content

[0207] (6.1) Plotting the standard curve:

[0208] A series of standard solutions with concentrations of 1.0, 2.0, 4.0, 6.0, 8.0, 10.0, and 12.0 mg / L were prepared by adding water to alkaline lignin (standard, CNW GmbH, Germany). The absorbance of each standard solution at a wavelength of 210 nm was measured using a UV-Vis spectrophotometer. Regression analysis was performed on the absorbance (Y) of the standard solution and its corresponding concentration (X) to obtain the standard curve y = 0.0723x - 0.0003, with a detection limit of 0.8 mg / L.

[0209] (6.2) Determination of acid-soluble lignin content:

[0210] Take the diluted solution of the acid hydrolysis filtrate of the filter residue obtained in step (4.2), and measure its absorbance at a wavelength of 210 nm using a UV-Vis spectrophotometer. Substitute the absorbance value into the standard curve to calculate the acid-soluble lignin content C (in g / mL) in the diluted solution of the acid hydrolysis filtrate of the filter residue. Calculate the acid-soluble lignin content (in mass%) in the tobacco leaf sample according to the following formula.

[0211] Acid-soluble lignin content =

[0212] Where V represents the volume of the diluted filtrate from the acid hydrolysis of the filter residue (in mL); m represents the dried mass of the tobacco sample (in g).

[0213] (6.3) Determination of acid-insoluble lignin content:

[0214] The filter paper with acid hydrolysis residue obtained in step (4.2) (the mass of the dried and weighed ashless filter paper is recorded as m1) is placed in a ceramic crucible (the ceramic crucible needs to be calcined at 550 ℃ for 3 hours to constant weight), dried in an oven at 100 ℃ for 3-4 hours to constant weight, and naturally cooled to room temperature. The mass is accurately weighed and recorded as m2. Then, it is transferred to a muffle furnace and calcined at 550 ℃ for 3 hours. It is naturally cooled to room temperature and the mass is accurately weighed and recorded as m3. The acid-insoluble lignin content in the tobacco sample is calculated according to the following formula (in mass %).

[0215] Acid-insoluble lignin content = 100% × (m2 - m1 - m3) / m, where m represents the dry mass of the tobacco sample (in g).

[0216] (6.4) Add the acid-soluble lignin content and the acid-insoluble lignin content of the tobacco leaf sample to obtain the lignin content of the tobacco leaf sample.

[0217] Example 2: Establishment and Cross-Validation of the Prediction Model

[0218] 183 types of Class I or Class II tobacco leaves of different varieties and parts produced in Fujian and Yunnan.

[0219] The contents of protein, starch, cellulose, hemicellulose, pectin and lignin in each tobacco leaf were determined according to the method in Example 1.

[0220] Each tobacco leaf sample was dried at 40℃ for 4 hours, then cooled to room temperature in a desiccator. It was then ground into powder using a grinder, passed through a 40-mesh sieve, and then through a 60-mesh sieve, leaving a 40-60 mesh tobacco dust sample. This sample was sealed and stored in a desiccator with a moisture content controlled between 5% and 9%. An appropriate amount of tobacco dust sample was placed in a quartz cup, and the sample was pressed flat using a sample press, ensuring the tobacco dust thickness was greater than 5 mm. The tobacco dust sample was then analyzed using a near-infrared spectrometer. The operating conditions for the near-infrared spectrometer were: scanning using the diffuse reflectance module, with a spectral range of 10000-3900 cm⁻¹. -1 The scanning interval is 4 cm. -1 The number of scans was 68, and the resolution was 8 cm. -1 Each tobacco leaf was tested three times, and the average spectrum was taken as the spectrum of the tobacco leaf.

[0221] The spectra of each tobacco leaf are preprocessed. The preprocessing method can be one or more of the following: multivariate scattering correction (MSC), standard normal variable transformation (SNV), first derivative, second derivative, SG smoothing, and Norris smoothing.

[0222] By selecting a specific spectral range and using the partial least squares regression (PLS) algorithm, the preprocessed spectra of each tobacco leaf were fitted with the contents of protein, starch, cellulose, hemicellulose, pectin and lignin in the tobacco leaf, respectively, to obtain the prediction model of each component in the tobacco leaf. The model was then cross-validated, and the specific results are shown in Table 6.

[0223] Table 6. Selected conditions and fitting parameters for the prediction model of each component.

[0224] As shown in Table 6, the correlation coefficients of each component prediction model are all above 0.9. Furthermore, the RMSEC and RMSEP of the calibration model are both within a reasonable range, less than 5%-10% of the upper limit of the predicted content range. This indicates that the prediction effect of each prediction model is good.

[0225] Example 3: Accuracy Verification of the Prediction Model

[0226] Thirty tobacco leaf samples were used as the validation set.

[0227] The measured values ​​of cellulose and lignin content in each tobacco leaf sample of the validation set were determined according to the method in Example 1 and used as standard values.

[0228] The near-infrared spectra of each tobacco leaf sample in the validation set were measured according to the method in Example 2 and the spectra were preprocessed. The specific spectral ranges shown in Table 6 were selected and substituted into the prediction model established in Example 2 to calculate the predicted values ​​of cellulose and lignin content of each tobacco leaf sample.

[0229] The results are shown in Table 7.

[0230] Table 7. Predicted and Standard Values ​​of Cellulose and Lignin Content in Validation Tobacco Leaf Samples

[0231] As shown in Table 7, the average relative deviation between the predicted value and the standard value of the lignin content of the verification tobacco leaf samples was 3.15%, and the average relative deviation between the predicted value and the standard value of the cellulose content of the verification tobacco leaf samples was 1.62%, indicating that the prediction model of the present invention has high accuracy.

[0232] Based on the above experimental results, the number of tobacco leaf samples in the validation set was expanded to 130 to further verify the relationship between the measured (standard) values ​​and predicted values ​​of starch, cellulose, hemicellulose, lignin, pectin, and protein. Figures 4 to 9 As can be seen, the measured values ​​are quite close to the predicted values, and the slope of the fitted curve is close to 1, which further demonstrates the high accuracy of the model's prediction.

[0233] Example 4: Precision Validation of the Prediction Model

[0234] A tobacco leaf sample was selected, and its near-infrared spectrum was measured five times in accordance with the method in Example 2. The spectrum was preprocessed. For each near-infrared spectrum, the specific spectral range shown in Table 6 was selected and substituted into the prediction model established in Example 2 to calculate the predicted values ​​of protein, starch, cellulose, hemicellulose, pectin and lignin content of the tobacco leaf sample. The results are shown in Table 8.

[0235] Table 8. Predicted values ​​of protein, starch, cellulose, hemicellulose, pectin, and lignin content in tobacco leaf samples.

[0236] As shown in Table 8, the relative deviations of the predicted values ​​of each component content in the tobacco leaf samples are all within 1.55%, indicating that the prediction model of this invention has high precision.

[0237] It should be noted that this application is not limited to the above-described embodiments. The above embodiments are merely examples, and any embodiments with the same structure and effect as the technical concept within the scope of this application are included in the technical scope of this application. Furthermore, various modifications that can be conceived by those skilled in the art to the embodiments, and other ways of constructing by combining some of the constituent elements of the embodiments, without departing from the spirit of this application, are also included in the scope of this application.

Claims

1. A method for determining protein, starch, cellulose, hemicellulose, pectin, and lignin in a sample, comprising the following steps: The sample was extracted at least once using a saturated saline solution containing ethanol, followed by solid-liquid separation to obtain a liquid phase and a solid phase; wherein, The sample is a tobacco sample; optionally, the solid phase is washed with a saturated saline solution containing ethanol, and the washed liquid is incorporated into the liquid phase. The solid phase was extracted at least once with dimethyl sulfoxide solution to separate the extract and residue. The protein content in the liquid phase and extract was determined by the Coomassie brilliant blue method, and the protein content in the sample was calculated based on the total protein content in the liquid phase and extract. The extract was subjected to a first acid hydrolysis at 40°C-60°C with a sulfuric acid solution of 1%-4% by mass for 1-3 hours to obtain the first acid hydrolysis product. The first acid hydrolysis product or its dilution was detected by ion chromatography 1, and the starch content in the sample was calculated based on the glucose ion chromatography peak in the spectrum, wherein the starch content was expressed as glucose content. The residue is optionally washed and then subjected to a second acid hydrolysis at 20 °C-40 °C with a sulfuric acid solution of 70%-80% by mass for 1-3 hours to obtain a second acid hydrolysis product. The second acid hydrolysis product was diluted to a sulfuric acid concentration of 2%-6% by mass, and then subjected to a third acid hydrolysis at 115℃-130℃ under sealed conditions for 40-70 minutes. Solid-liquid separation was performed to obtain the acid hydrolysis liquid phase product and the acid hydrolysis solid phase product. The acid hydrolysis liquid phase product or its dilution was detected by ion chromatography 1, and the cellulose and hemicellulose content in the sample was calculated based on the ion chromatographic peaks of arabinose, galactose, glucose, xylose and mannose in the spectrum. The acid hydrolysis liquid phase product or its dilution was detected by ion chromatography 2. The pectin content of the sample was calculated based on the ion chromatography peak of galacturonic acid in the spectrum. The pectin content was calculated based on the galacturonic acid content. The absorbance of the acid hydrolysis liquid phase product or its dilution at a wavelength of 210 nm was detected using a UV-Vis spectrophotometer, and the acid-soluble lignin content in the sample was calculated based on the absorbance value. The acid hydrolysis solid product was dried at 90℃-110℃ and calcined at 530℃-560℃ for 2-4 hours. The acid-insoluble lignin content in the sample was calculated based on the mass change before and after calcination. The sum of the acid-soluble lignin content and the acid-insoluble lignin content in the sample is taken as the lignin content in the sample.

2. The method according to claim 1, wherein, The operating conditions for ion chromatography 1 and ion chromatography 2 each independently include one or more of the following: (A) The chromatographic column was a Carbo PAC PA 10; (B) The detection mode is integral pulse amperometric detection; (C) The working electrode is an Au electrode, and the reference electrode is an AgCl / Ag electrode; (D) The flow rate of the mobile phase is 0.25 mL / min; (E) The detection temperature is 20 ℃; (F) The injection volume is 25 μL; (G) The scan potential is the pulse point waveform shown in the table below; 。 3. The method according to claim 1 or 2, wherein, The mobile phases used in ion chromatography 1 included: mobile phase A was water, mobile phase B was an aqueous solution of 180-220 mmol / L NaOH, mobile phase C was an aqueous solution containing 0.7-1.2 mol / L NaAc and 70-120 mmol / L NaOH, and mobile phase D was an aqueous solution of 8-12 mmol / L NaOH; and the elution programs for the mobile phases were shown in the table below: 。 4. The method according to any one of claims 1 to 3, wherein, The mobile phases used in ion chromatography 2 included: mobile phase A was water, mobile phase B was an aqueous solution of 180-220 mmol / L NaOH, and mobile phase C was an aqueous solution containing 0.7-1.2 mol / L NaAc and 70-120 mmol / L NaOH; and the elution program of the mobile phases was shown in the table below: 。 5. The method according to any one of claims 1 to 4, characterized in that... One or more of the following: Before extraction, the sample is crushed and sieved; Each extraction was performed at 20℃-30℃ under ultrasonic conditions for 0.5-2 hours. After extraction, allow the mixture to stand for 10-60 minutes before performing solid-liquid separation; The ratio of saturated saline solution containing ethanol to the sample used in each extraction was 120:1-160:1 mL / g; The concentration of a saturated saline solution containing ethanol is 65%-95% by mass. The volume of the saturated saline solution containing ethanol used for washing shall not exceed the volume of the saturated saline solution containing ethanol used in each extraction. Each extraction is performed at 50℃-70℃ under ultrasonic conditions for 5 minutes to 5 hours; After extraction, allow to stand for 10-60 minutes before separation; The ratio of dimethyl sulfoxide solution to sample used in each extraction was 80:1-180:1 mL / g; The concentration of the dimethyl sulfoxide solution is 75%-95% by mass; The residue was washed with pure water and ethanol; During the first acid hydrolysis, the volume ratio of the extract to the sulfuric acid solution is 1:5 to 1:15; During the second acidolysis, the residue is immersed in the sulfuric acid solution; optionally, the ratio of the sample to the sulfuric acid solution with a concentration of 70%-80% by mass is 1:3-1:8 g / mL. The acid hydrolysis solid product was dried at 90℃-110℃ to constant weight; The Coomassie Brilliant Blue method includes: mixing the liquid phase and the extract with Coomassie Brilliant Blue G-250 solution respectively, then using a UV-Vis spectrophotometer to detect the absorbance of the two mixtures at a wavelength of 595 nm, and calculating the protein content in the liquid phase and the extract based on the absorbance values ​​using external standard analysis; optionally, the external standard used in the external standard analysis is bovine serum albumin. In the step of calculating the starch content in the sample, the glucose content C in the first acid hydrolysis product or its dilution is calculated by external standard analysis based on the ion chromatographic peak of glucose in the spectrum. 葡萄糖 Then calculate the starch content in the sample using the following formula: Starch content in the sample = C 葡萄糖 ×0.9×V×f / m Where V represents the volume of the first acid hydrolysis product or its dilution; f represents the volume ratio of the total extract to the extract taken; and m represents the dried mass of the sample. In the step of calculating the cellulose and hemicellulose content in the sample, the contents of arabinose, galactose, glucose, xylose, and mannose in the acid hydrolysis liquid product or its dilution are calculated by external standard analysis based on the ion chromatographic peaks of arabinose, galactose, glucose, xylose, and mannose in the chromatogram. Then, the cellulose and hemicellulose content in the sample is calculated according to the following formula: Ci = Cms × Dilution factor / Ri Cellulose content in the sample = C 葡萄糖 ×0.9×V / m, Hemicellulose content in the sample = [(C 阿拉伯糖 +C 木糖 )×0.88+(C 半乳糖 +C 甘露糖 [0.90] × V / m Where Ri represents the recovery rate of a single sugar; Cms represents the content of a single sugar in the diluted acid hydrolysis product, with the dilution factor being the dilution factor of the acid hydrolysis product, or Cms × dilution factor representing the content of a single sugar in the acid hydrolysis product; Ci represents the converted content of a single sugar in the acid hydrolysis product; C 葡萄糖 C represents the glucose content in the converted acid hydrolysis liquid phase product; 半乳糖 This represents the galactose content in the converted acid hydrolysis liquid phase product; C 甘露糖 This represents the mannose content in the converted acid hydrolysis liquid phase product; C 木糖 This represents the xylose content in the converted acid hydrolysis liquid phase product; C 阿拉伯糖 V represents the arabinose content in the converted acid hydrolysis liquid phase product; V represents the volume of the acid hydrolysis liquid phase product; m represents the dried mass of the sample. In the step of calculating the pectin content in the sample, the content of galacturonic acid in the acid hydrolysis liquid phase product or its dilution is calculated by external standard analysis based on the ion chromatographic peak of galacturonic acid in the spectrum, and then the pectin content in the sample is calculated. In the step of calculating the acid-soluble lignin content in the sample, the acid-soluble lignin content in the acid hydrolysis liquid phase product or its dilution is calculated based on the absorbance value using the external standard analysis method, and then the acid-soluble lignin content in the sample is calculated; optionally, the external standard used in the external standard analysis method is alkaline lignin.

6. A method for predicting the content of protein, starch, cellulose, hemicellulose, pectin, and lignin in a sample, comprising the following steps: The sample was analyzed using a near-infrared spectrometer to obtain its near-infrared spectrum; among which, The sample was a tobacco sample; The near-infrared spectrum of the sample was preprocessed to obtain the preprocessed spectrum of the sample; By substituting specific band spectra from the pre-processed spectrum of the sample into a pre-established prediction model, the predicted values ​​of protein, starch, cellulose, hemicellulose, pectin, and lignin content in the sample are obtained.

7. The method according to claim 6, wherein, The prediction model is established through the following steps: Near-infrared spectra of multiple samples were obtained by detecting them using a near-infrared spectrometer. The near-infrared spectra of multiple samples were preprocessed to obtain the preprocessed spectra of multiple samples; The contents of protein, starch, cellulose, hemicellulose, pectin and lignin in multiple samples were determined according to the method of any one of claims 1 to 5. Specific bands in the preprocessed spectra of multiple samples were fitted with the contents of protein, starch, cellulose, hemicellulose, pectin, and lignin in the samples to obtain predictive models for the contents of protein, starch, cellulose, hemicellulose, pectin, and lignin in the samples.

8. The method according to claim 6 or 7, characterized in that... One or more of the following: (1) The preprocessing method is selected from one or more of the following: multivariate scattering correction, standard normal variable transformation, first derivative, second derivative, SG smoothing and Norris smoothing; (2) When predicting the protein content in a sample and / or establishing a predictive model for protein content, the preprocessing methods are first derivative and Norris smoothing, respectively, using a specific wavelength range of 8341.12-3915.11 cm. -1 ; (3) When predicting the starch content in the sample and / or establishing a predictive model for starch content, the preprocessing methods are first derivative and SG smoothing, respectively, using a specific wavelength range of 7846.67-3929.65 cm. -1 ; (4) When predicting the cellulose content in the sample and / or establishing a predictive model for cellulose content, the preprocessing methods are, in order, multivariate scattering correction, first derivative, and Norris smoothing, with the specific wavelength range being 8222.05-3991.08 cm⁻¹. -1 ; (5) When predicting the hemicellulose content in the sample and / or establishing a predictive model for the hemicellulose content, the preprocessing methods are first derivative and SG smoothing, respectively, using a specific wavelength range of 8328.46-3901.08 cm⁻¹. -1 ; (6) When predicting the pectin content in a sample and / or establishing a predictive model for pectin content, the preprocessing methods are, in order, multivariate scattering correction, first derivative, and SG smoothing, with the specific wavelength range being 7866.05-4001.05 cm. -1 ; (7) When predicting the lignin content in the sample and / or establishing a predictive model for lignin content, the preprocessing methods are, in order, multivariate scattering correction, first derivative, and Norris smoothing, with the specific wavelength range being 8062.85-3901.17 cm⁻¹. -1 ; (8) In the steps of establishing the prediction model, the number of principal factors used is 7 to 11; (9) Before using a near-infrared spectrometer for detection, dry, crush, and sieve the sample (e.g., take powder with a particle size between 40-60 mesh).

9. The method according to any one of claims 7 to 8, wherein, The operating conditions for a near-infrared spectrometer include one or more of the following: (A) Scanning was performed using a diffuse reflectance spectral module; (B) Scanning range is 10000-3900 cm -1 ; (C) Scanning interval is 4 cm -1 ; (D) The number of scans was 68; (E) Resolution is 8 cm -1 ; (F) Before testing, flatten the sample and make the sample thickness greater than 5 mm.

10. An apparatus for predicting the content of protein, starch, cellulose, hemicellulose, pectin, and lignin in a sample, comprising: The detection module is used to detect the sample using a near-infrared spectrometer to obtain the near-infrared spectrum of the sample; wherein the sample is a tobacco sample; The preprocessing module is used to preprocess the near-infrared spectrum of the sample to obtain the preprocessed spectrum of the sample. The prediction module is used to substitute specific band spectra from the pre-processed spectrum of the sample into a pre-established prediction model to calculate the predicted values ​​of protein, starch, cellulose, hemicellulose, pectin and lignin content in the sample.

11. An apparatus for predicting the content of protein, starch, cellulose, hemicellulose, pectin, and lignin in a sample, wherein: Memory, used to store instructions; A processor coupled to the memory, the processor being configured to execute the method as described in any one of claims 6 to 9 based on instructions stored in the memory.

12. A computer-readable storage medium, characterized in that, The readable storage medium stores computer instructions that, when executed by a processor, implement the method as described in any one of claims 1 to 9.

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