CN112213282A - Method for detecting content of crude fat in cyperus esculentus by applying near-infrared grain analyzer - Google Patents
Method for detecting content of crude fat in cyperus esculentus by applying near-infrared grain analyzer Download PDFInfo
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- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
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Abstract
The invention discloses a method for establishing a detection method of crude fat content in cyperus esculentus by using a near-infrared grain analyzer, wherein a plurality of cyperus esculentus samples are utilized, a cyperus esculentus crude fat model is firstly calibrated on the near-infrared grain analyzer, wherein the quality and the fat content of the standard sample directly influence the accuracy and the application range of marked lines, the standard sample adopted by the invention is a purified cyperus esculentus strain selected by a team, the coverage range of the crude fat content is 18.49-38.68%, and the requirement of measuring the crude fat content of the cyperus esculentus can be met. In addition, the invention has the advantages of high analysis speed, high analysis efficiency, no use of any chemical reagent, no damage to the sample, no pollution to the environment and the like. The method is used for detecting the crude fat content of a sample to be detected of the cyperus esculentus in an average time of only 1.5 minutes, the efficiency is far higher than that of a traditional method, and the rapid nondestructive analysis of the cyperus esculentus crude fat is realized.
Description
Technical Field
The invention relates to the technical field of detection and analysis, in particular to a detection method for establishing the content of crude fat in cyperus esculentus by applying a near-infrared grain analyzer.
Background
The cyperus esculentus is also called cyperus esculentus, underground Chinese chestnut, underground walnut, tiger nut and the like, belongs to perennial herbaceous plants in cyperus of cyperaceae, and is a novel plant integrating multiple purposes of oil collection, grain, grazing and feeding. When the cyperus esculentus is economically planted, the cyperus esculentus is planted as an annual crop, the plant on the ground is about 100 cm high, leaves are narrow, long and thin and leather, the root system of the underground part is developed, roots are fibrous roots, the root depth is about 15-25 cm, the tillering capability of the cyperus esculentus is strong, new plants can continuously grow from the plant base in the growth process, the underground fibrous roots can form a plurality of small spherical tubers, the tubers are spherical, elliptical and oblong after being mature, the diameter is 0.7-1.5 cm, the epidermis is tawny, the surface has nodes and scales, and the pulp is white or faint yellow. Cyperus esculentus is an underground tuber like tuber crops, can be directly eaten, and can also be used as a seed to be propagated.
The tuber and the stem of the cyperus esculentus can be utilized, the nutrient substances are rich, and the comprehensive value is high. The cyperus esculentus contains starch, fat, sugar, protein and dietary fiber, and is rich in vitamin C, vitamin E, potassium, phosphorus, sodium, calcium, magnesium and other minerals. The cyperus esculentus is the only crop accumulating grease in underground organs, namely rhizomes, in all the current crops, the content of crude fat is about 25 percent, and the oil yield of the cyperus esculentus per mu is over 120 kg. The tuber of the cyperus esculentus can be directly eaten, can be pulped to be made into soymilk, and can be ground into edible flour for oil pressing, sugar making and wine brewing; the stem and leaf of Cyperus esculentus can be used as green manure and feed, and can be used for making paper or weaving.
In recent years, along with the continuous development of the economy of China, the contradiction between the supply and the demand of edible oil is increasingly prominent, the country puts forward 'multi-oil co-operation' to increase new oil sources, the cyperus esculentus industry is gradually concerned, the planting area is steadily increased, related researches on the cyperus esculentus are also carried out successively, and the fat content of the cyperus esculentus is required to be clear in high-oil-quality seed cultivation and edible oil processing and utilization.
The conventional method for determining the fat content of the cyperus esculentus is mainly a laboratory Soxhlet extraction method, the method is long in detection time, complicated in process, large in workload, not beneficial to rapid detection of a large number of samples, and is not suitable for detection of important materials with small sample amount by destroying the samples.
The near-infrared grain analyzer can realize the rapid measurement of the components of granular samples such as soybean, rapeseed, wheat, corn, peanut, barley, rice, sesame and the like, and judges and evaluates the structural composition of the sample by utilizing the change of the internal structure of the sample caused by the reaction to heat, sound, light, electricity, magnetism and the like on the premise of not damaging or damaging the detected object, thereby being suitable for the determination of large-batch materials and the screening of important breeding materials. However, no report of near infrared technology on analysis and test methods of the crude fat content of the cyperus esculentus or establishment of related models is found at home and abroad.
Disclosure of Invention
The invention aims to provide a method for establishing a detection method of the content of crude fat in cyperus esculentus by using a near-infrared grain analyzer.
In order to achieve the above purpose, the invention provides the following technical scheme:
a method for detecting the content of crude fat in cyperus esculentus by using a near-infrared grain analyzer comprises the following steps:
s1 Standard sample preparation the standard sample is a cyperus esculentus strain with crude fat content coverage of 18.49-38.68%, full and non-wormhole particles are selected, cleaned and dried for later use;
s2 near infrared scanning 20g of cyperus esculentus sample is placed in a rotating sample tray, a near infrared grain analyzer is adopted to scan the spectrum region 950 + 1650nm, the resolution is 5nm, the absorption spectrum of the sample is collected, all the spectrum information of the sample at the near infrared wavelength is obtained, the spectrum of a correction set sample is obtained, the sample is ensured to be in the same detection environment during spectrum collection, and the temperature, the humidity and the like of the detection environment are kept. (ii) a
S3 spectrum pretreatment, the obtained calibration set sample spectrum is pretreated by using TheUnscamblebler software;
s4 determination of chemical standard value according to NY/T4-1982 method for detecting the crude fat content of the cyperus esculentus sample as a chemical standard value;
s5 inputting chemical values and deriving a detection curve, inputting the measured chemical standard values of the samples into a near-infrared grain analyzer, and deriving a near-infrared spectrum curve endowed with the chemical standard values;
s6, establishing a calibration model by taking the chemical value of the cyperus esculentus sample as a standard value, establishing the calibration model by utilizing the relation between the near-infrared spectrum value of the sample and the corresponding chemical standard value and applying a partial least square method, and comparing and analyzing the chemical value and the near-infrared value, wherein the SEP value is less than 0.5%;
the S7 model importing setting item imports the calibration model of the crude fat into the setting item in the near-infrared grain analyzer, namely the setting is finished, and the calibration model can be used for detecting unknown samples;
s8 determination of crude fat of the cyperus esculentus sample with unknown content, the standard sample in the step S1 is replaced by the cyperus esculentus sample to be determined, the step S1 is repeated, and the set project program which is introduced into the calibration model is used for scanning the sample to be determined, so that the crude fat content of the cyperus esculentus sample to be determined can be obtained.
Further, the standard sample used was a purified strain of cyperus esculentus, and there was a difference in crude fat content among individuals of the strain.
Further, the standard sample is more than 100 parts of the cyperus esculentus strain.
Further, the near-infrared grain analyzer is a wave-pass DA7250 near-infrared grain analyzer.
Further, the scanning mode in step S2 is continuous wavelength near infrared scanning or discrete wavelength near infrared scanning.
Further, when the scanning mode is continuous wavelength near infrared scanning, the chemometrics multivariate correction algorithm is partial least squares or principal component regression.
Further, when the scanning mode is a discrete wavelength near infrared scanning, the chemometrics multivariate correction algorithm is a stepwise regression algorithm or a multivariate linear regression algorithm.
Further, the preprocessing method described in step S3 is at least one of a multivariate scatter correction method, a smoothing method, and a derivation method, and the derivation method is a first-order derivation or a second-order derivation method.
Compared with the prior art, the invention has the beneficial effects that:
the invention relates to a method for establishing a detection method of the content of crude fat in cyperus esculentus by using a near-infrared grain analyzer, wherein a plurality of cyperus esculentus samples are utilized, a cyperus esculentus crude fat model is calibrated on the near-infrared grain analyzer for the first time, the quality and the fat content of the standard sample directly influence the accuracy and the application range of a marked line, and the coverage range of the detected standard sample of the content of crude fat is 18.49-38.68%, so that the detection of the content of the crude fat of the cyperus esculentus can be met. In addition, the invention has the advantages of high analysis speed, high analysis efficiency, no use of any chemical reagent, no damage to the sample, no pollution to the environment and the like. The method for detecting the crude fat content of the cyperus esculentus sample only needs 1.5 minutes on average, the efficiency is far higher than that of the traditional method, and the rapid nondestructive analysis of the cyperus esculentus crude fat content is realized.
Drawings
In order to more clearly illustrate the embodiments of the present application or technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings can be obtained by those skilled in the art according to the drawings.
FIG. 1 is a graph of spectra of 126 preprocessed cyperus esculentus samples according to an embodiment of the present invention.
Fig. 2 is a relational scattergram of chemical values and near-infrared detection values of 126 cyperus esculentus standard samples provided by the embodiment of the invention.
Fig. 3 is a spectrogram of 32 unknown samples provided by the embodiment of the present invention.
Fig. 4 is a graph showing a linear relationship between chemical values and near-infrared detection values of 32 unknown samples according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood by those skilled in the art, the present invention will be further described in detail with reference to the accompanying drawings and examples. The standard sample used in the method is a cyperus esculentus strain selected and purified by a cyperus esculentus team of the economic plant research institute of agricultural academy of sciences of Jilin province, the crude fat content of individual strains is different, the coverage range is 18.49% -38.68%, and the near-infrared grain analyzer is a wave-through DA7250 near-infrared grain analyzer.
The invention provides a method for detecting the content of crude fat in cyperus esculentus by applying a near-infrared grain analyzer, which comprises the following steps:
s1 Standard sample preparation
Taking 126 parts of standard sample, selecting full and non-wormhole granules, cleaning and drying for later use;
s2 near infrared scanning
Starting a near-infrared spectrometer at 25 ℃ for preheating for 30 minutes, and building a new project: the project name is analysis of the crude fat content of the cyperus esculentus, a sample disc is set to rotate as a small sample disc, the detection is repeated twice, the sample is in a granular form, and the ID format of the sample is a designated name. Parameter setting (virtual bit retention): custom parameters the parameters crude fat was entered, water based on dry basis, unit "%".
20g of cyperus esculentus sample is placed in a rotating sample tray, a near-infrared grain analyzer is adopted to scan the spectral region 950-1650nm, the resolution is 5nm, and the absorption spectrum of the sample is collected. In order to overcome the spectral differences caused by the particle size differences of the samples and reduce the errors, each sample was loaded 2 times.
And (3) respectively carrying out near infrared spectrum scanning on 126 standard samples by using a newly-established project program of 'crude fat content analysis', so as to obtain all spectrum information of the samples at near infrared wavelength, and obtain the spectrum of the sample in the correction set.
The scanning mode is continuous wavelength near infrared scanning or discrete wavelength near infrared scanning. Specifically, when the scanning mode is continuous wavelength near-infrared scanning, the chemometrics multivariate calibration algorithm is partial least squares or principal component regression. When the scanning mode is the discrete wavelength near infrared scanning, the chemometrics multivariate correction algorithm is a stepwise regression algorithm or a multivariate linear regression algorithm.
S3 Spectrum preprocessing
The calibration set sample spectra obtained above were pre-processed using the TheUnscamblebler software. The preprocessing method is at least one of a multivariate scattering correction method, a smoothing method and a derivation method, and the derivation method is a first-order derivation method or a second-order derivation method. The spectra of 126 standards were generated after pretreatment as shown in FIG. 1. The near infrared values of the crude fats of the 126 cyperus bean standards are shown in table 1.
S4 determination of chemical Standard value
The content of the crude fat of the cyperus esculentus sample is detected according to the NY/T4-1982 method to be used as a chemical standard value. The specific method comprises the following steps: analysis of fat content quantification was performed by extracting fat in a sample by purifying ether using a Soxhlet extraction apparatus. The fat that is melted and extracted in ether is not only fat and oil, but also contains a very small amount of organic acids, alcohols, low oils, pigments, fat-soluble vitamins, and the like, and thus the fat quantified by this method is called crude fat (crudefat) or ether extract. The 2-10g samples of cyperus esculentus flour were placed in cylindrical filter paper, the upper part of the samples were covered with absorbent cotton and placed in a container, and dried in a desiccator at 80 ℃ for 2-3 hours. The extract was cooled in a desiccator and then placed in an extraction tube of a Soxhlet extraction apparatus, and anhydrous diethyl ether of half the volume was placed in a receiving vessel (water apparatus) to conduct extraction for 8 hours. After the extraction was completed, the cooler was removed, the cylindrical filter paper in the extraction tube was taken out with tweezers, the cooler was connected to the extraction tube again, and after all the ether had been transferred to the extraction tube, the ether was separated and completely evaporated off using a thickener connected to a thermostatic water bath. Wiping the outside of the water purifier with gauze, drying in a drier at 98-100 deg.C for about 1 hr to constant weight, cooling in the drier, and quantifying the weight of the water purifier. The amount of crude fat is calculated by the following equation.
Crude fat (g) [ (W)1-W0)/S]×100
Wherein: w0To receive the weight (g) of the vessel (water container);
W1weight (g) of receiving vessel for extraction of dried crude fat;
s is the sample amount (g).
The results are shown in Table 1.
Chemical and near-infrared values of crude fats of Table 1126 Cyperus bean standards
S5 inputting chemical value and deriving detection curve
Inputting the 126 measured chemical standard values of the samples into a near-infrared grain analyzer, and exporting a near-infrared spectrum curve endowed with the chemical standard values in a 'analysis of crude fat content of cyperus esculentus'.
A scattergram of the relationship between the correction value (chemical value) and the detection value (near-infrared value) is shown in fig. 2. The abscissa in the figure represents the corrected value (chemical value), the ordinate represents the detected value (near-infrared value), the scatter in the figure represents the corresponding relationship between the corrected value and the verified value for each sample, blue is the calibration set, red is the verified set, a linear relationship exists between 126 points, a straight line Slope is 0.97, an R-Square (correlation) is 0.97, and a polar correlation represents a close proximity between the corrected value and the detected value for each sample.
S6 establishing calibration model
And establishing a calibration model by using the relation between the near-infrared spectrum value of the sample and the corresponding chemical standard value and applying a partial least square method by taking the chemical value of the cyperus esculentus sample as a standard value. The chemical values and near infrared values are detailed in table 1.
S7 model import setting item
And (4) guiding the calibration model of the crude fat into a set item in the near-infrared grain analyzer, namely completing the setting, and detecting an unknown sample.
S8 determination of crude fat of Cyperus esculentus sample with unknown content
Taking 32 chufa samples with unknown content, replacing the standard samples in the step S1 with chufa samples to be detected, repeating the step S1, scanning the samples to be detected by the set project program introduced into the calibration model, obtaining the crude fat content of the chufa samples to be detected, obtaining the spectrogram of the 32 unknown samples shown in figure 3, detecting the chemical standard value of the unknown samples according to a NY/T4-1982 method, comparing and analyzing the chemical value and the near infrared value, and obtaining the chemical value and the near infrared detection value shown in figure 2. The linear relationship between the chemical value and the near infrared detection value is shown in FIG. 4. The analysis results of the chemical value and the near infrared detection value of the unknown sample are shown in table 3, the correlation is 0.990, the SEP (prediction standard deviation) value is 0.245%, and the method proves that the model is successfully established and can completely meet the requirement of measuring the crude fat content of the cyperus esculentus.
Chemical values and near infrared detection values of 232 unknown samples
TABLE 3 analysis results of unknown sample chemical values and near-infrared detection values
In addition, the method has the advantages of high analysis speed, high analysis efficiency, no use of any chemical reagent, no damage to the sample, no pollution to the environment and the like. The method for detecting the crude fat content of a cyperus esculentus sample to be detected only needs 1.5 minutes on average, and the efficiency is far higher than that of the traditional method.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: it is to be understood that modifications may be made to the technical solutions described in the foregoing embodiments, or equivalents may be substituted for some of the technical features thereof, but such modifications or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. The method for detecting the content of the crude fat in the cyperus esculentus by using the near-infrared grain analyzer is characterized by comprising the following steps of:
s1 Standard sample preparation the standard sample is a cyperus esculentus strain with crude fat content coverage of 18.49-38.68%, full and non-wormhole particles are selected, cleaned and dried for later use;
s2 near-infrared scanning, namely, putting 20g of cyperus esculentus samples into a rotating sample tray, scanning a spectrum region 950-1650nm by using a near-infrared grain analyzer, wherein the resolution is 5nm, collecting absorption spectra of the samples, obtaining all spectral information of the samples at near-infrared wavelength, and obtaining a calibration set sample spectrum;
s3 spectrum pretreatment, The obtained calibration set sample spectrum is pretreated by The Unscrambler software;
s4 determination of chemical standard value according to NY/T4-1982 method for detecting the crude fat content of the cyperus esculentus sample as a chemical standard value;
s5 inputting chemical values and deriving a detection curve, inputting the measured chemical standard values of the samples into a near-infrared grain analyzer, and deriving a near-infrared spectrum curve endowed with the chemical standard values;
s6, establishing a calibration model by taking the chemical value of the cyperus esculentus sample as a standard value, establishing the calibration model by utilizing the relation between the near-infrared spectrum value of the sample and the corresponding chemical standard value and applying a partial least square method, and comparing and analyzing the chemical value and the near-infrared value, wherein the SEP value is less than 0.5%;
the S7 model importing setting item imports the calibration model of the crude fat into the setting item in the near-infrared grain analyzer, namely the setting is finished, and the calibration model can be used for detecting unknown samples;
s8 determination of crude fat of the cyperus esculentus sample with unknown content, the standard sample in the step S1 is replaced by the cyperus esculentus sample to be determined, the step S1 is repeated, and the set project program which is introduced into the calibration model is used for scanning the sample to be determined, so that the crude fat content of the cyperus esculentus sample to be determined can be obtained.
2. The assay of claim 1, wherein the standard sample used is a purified strain of cyperus esculentus.
3. The detection method according to claim 1, wherein the standard sample used is 100 parts or more of a strain of Cyperus esculentus.
4. The detection method according to claim 1, wherein the near-infrared grain analyzer is a wave-pass DA7250 near-infrared grain analyzer.
5. The detection method according to claim 1, wherein the scanning mode in step S2 is continuous wavelength near infrared scanning or discrete wavelength near infrared scanning.
6. The detection method according to claim 5, wherein when the scanning mode is continuous wavelength near infrared scanning, the chemometric multivariate calibration algorithm is partial least squares or principal component regression.
7. The detection method according to claim 5, wherein when the scanning mode is a discrete wavelength near infrared scanning, the chemometric multivariate calibration algorithm is a stepwise regression algorithm or a multivariate linear regression algorithm.
8. The detection method according to claim 1, wherein the preprocessing method in step S3 is at least one of a multivariate scatter correction method, a smoothing method and a derivation method, and the derivation method is a first-order derivation or a second-order derivation method.
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