CN114295580B - Method for rapidly judging quality of peppers based on near infrared spectrum - Google Patents
Method for rapidly judging quality of peppers based on near infrared spectrum Download PDFInfo
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Abstract
The invention relates to a near infrared spectrum analysis technology, discloses a method for rapidly judging quality of peppers based on near infrared spectrum, and solves the problems that the existing technology for detecting and classifying peppers is complex in operation, damages a sample and cannot be rapidly measured. The method comprises the following steps: s1, collecting spectrum data of a pepper sample and performing second-order derivation; s2, calculating the contribution weight coefficient of each wavelength point in the pepper spectrum data according to the second-order derivative spectrogram of the pepper sample; s3, calculating a spectrum mean value according to the contribution weight coefficient and the light intensity value of each wavelength point in the spectrum data of the pepper sample; s4, calculating the reflectivity of the sample according to the corresponding relation between the spectrum average value of the pricklyash peel sample and the reflectivity of the pricklyash peel sample; s5, judging the quality of the pepper sample according to the reflectivity of the pepper sample.
Description
Technical Field
The invention relates to a near infrared spectrum analysis technology, in particular to a method for rapidly judging quality of peppers based on near infrared spectrum.
Background
Zanthoxylum bungeanum is one of important cash crops in China, and the total area and the total yield of the Zanthoxylum bungeanum all occupy the first part of the world. Modern natural product chemistry and pharmacology research show that the bioactive components in the pricklyash peel have the functions of resisting oxidation, resisting tumors, diminishing inflammation, inhibiting bacteria and preserving. Due to different geographic environments, climate differences, soil, varieties and the like, the quality of the peppers is different.
At present, for quality detection and classification of the peppers, a gas-mass spectrometry method, a high performance liquid chromatography method, a mid-infrared spectrometry method and the like are mainly adopted, but the methods are mainly applied in laboratories, the detection cost of the gas-mass spectrometry method and the detection cost of the high performance liquid chromatography method are relatively expensive, the sample treatment is complicated, the requirement on experimental operation is very high, the rapid measurement cannot be carried out, and great difficulty is brought to detection and classification of the peppers.
Therefore, the simple, quick and lossless method for distinguishing the quality of the peppers is realized, and the method has important practical significance.
Compared with other chemical analysis technologies, the portable near infrared spectrum technology has the characteristics of rapidness, accuracy, no need of sample pretreatment, no damage to samples, no pollution and the like, is a very suitable quality detection technology for the peppers, and meanwhile, the portable near infrared spectrometer is low in cost, simple to operate and convenient to carry, and can be purchased in a large amount to meet the detection requirements of various peppers.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: the method for rapidly judging the quality of the peppers based on the near infrared spectrum is provided, and the problems that the operation is complex, a sample is damaged and rapid measurement cannot be performed in the existing peppers inspection and classification technology are solved.
The technical scheme adopted for solving the technical problems is as follows:
a method for rapidly judging quality of pepper based on near infrared spectrum comprises the following steps:
s1, collecting spectrum data of a pepper sample and performing second-order derivation;
s2, calculating the contribution weight coefficient of each wavelength point in the pepper spectrum data according to the second-order derivative spectrogram of the pepper sample;
s3, calculating a spectrum mean value according to the contribution weight coefficient and the light intensity value of each wavelength point in the spectrum data of the pepper sample;
s4, calculating the reflectivity of the sample according to the corresponding relation between the spectrum average value of the pricklyash peel sample and the reflectivity of the pricklyash peel sample;
s5, judging the quality of the pepper sample according to the reflectivity of the pepper sample.
In step S1, the spectrum data of the pepper samples are collected by using a wavelength-division portable near infrared spectrometer, the wavelength range is 1350 nm-1850 nm, the resolution is 10nm, the spectrum data comprises 51 wavelength points, and the actual spectrum data of each pepper sample is represented as a matrix set of light intensity values at 51 wavelength points.
As a further optimization, in step S1, the manner of performing the second order derivative on the spectral data of the pricklyash peel sample is as follows: and adopting Savitzky-Golay derivation, setting the half window width to be 5, setting the highest order of the polynomial to be 5, and setting the derivation order to be 2.
As a further optimization, in step S2, the calculating the weight coefficient of each wavelength point in the pepper spectrum data according to the second-order derivative spectrum of the pepper sample specifically includes:
and selecting a difference value between the maximum value and the minimum value of the second derivative as a reference value through the second derivative spectrum diagram, and carrying out ratio operation on the second derivative value of each wavelength point, wherein the ratio is a contribution weight coefficient of each wavelength point.
As a further optimization, in step S3, the calculating a spectrum mean value according to the contribution weight coefficient and the light intensity value of each wavelength point in the spectrum data of the pricklyash peel sample specifically includes:
and carrying out product operation on the light intensity value of each wavelength point of the spectrum data of the pepper sample and the corresponding contribution weight coefficient to obtain the specific contribution value of each wavelength point, and carrying out average calculation on all the contribution values to obtain the spectrum average value.
As a further optimization, in step S4, the corresponding relationship between the spectral average value of the pricklyash peel sample and the reflectivity thereof is: the spectrum average value of the pricklyash peel sample is in linear positive correlation with the reflectivity thereof; and the corresponding relation between the spectral mean value of the pricklyash peel sample and the reflectivity of the pricklyash peel sample can be calculated by combining the illumination intensity of the near infrared illumination, the attenuation rate of the optical cavity and the illumination value received by the spectral sensor.
As a further optimization, in step S5, the quality of the pepper sample is determined by the reflectivity of the pepper sample, which specifically includes:
and setting reflectivity thresholds corresponding to different quality grades of the pricklyash peel samples, and comparing the reflectivity of the pricklyash peel samples with the reflectivity thresholds corresponding to different qualities, so as to determine the quality grade of the pricklyash peel samples.
The beneficial effects of the invention are as follows:
according to the method, the reflectivity of different pepper samples is calculated through near infrared spectrum data, so that the quality of the pepper samples is rapidly judged, and the problems that the operation is complex, the samples are damaged and rapid measurement cannot be performed in the existing pepper inspection and classification technology are solved.
Drawings
FIG. 1 is a flowchart of a method for rapidly discriminating quality of pricklyash peel based on near infrared spectrum in an embodiment of the present invention;
fig. 2 is a graph of second order derivative spectrum data of pricklyash peel samples.
Detailed Description
The invention aims to provide a method for rapidly judging quality of peppers based on near infrared spectrum, which solves the problems of complex operation, sample damage and incapability of rapid measurement existing in the prior peppers inspection and classification technology. According to the method, firstly, spectrum data of a pricklyash peel sample are collected, second-order derivative is conducted on the spectrum data of the pricklyash peel sample, then, the weight coefficient of each wavelength point on the spectrum data of the pricklyash peel sample is calculated according to a second-order derivative spectrum chart of the pricklyash peel sample, the spectrum average value is calculated according to the weight coefficient and the light intensity value of each wavelength point of the spectrum data of the pricklyash peel sample, the corresponding relation between the spectrum average value of the pricklyash peel sample and the reflectivity is calculated, finally, the reflectivity of the sample is calculated according to the spectrum average values of different pricklyash peel samples, and the quality difference of the pricklyash peel samples is further judged.
Examples:
as shown in fig. 1, the method for rapidly determining quality of peppers based on near infrared spectrum in this embodiment includes the following implementation steps:
s1, collecting spectrum data of a pepper sample and performing second-order derivation;
in the step, the spectrum data of the pricklyash peel samples are collected by adopting a wavelength average portable near infrared spectrometer, the spectrum data of the samples can be collected to the greatest degree of uniformity, according to the actual pricklyash peel samples to be detected, the portable near infrared spectrometer with the wavelength range of 1350-1850 nm and the resolution of 10nm is selected for data collection, the light intensity points contained in each spectrum data are N=1+ (1850-1350)/10=51, the wavelength ranges corresponding to the 1-51 wavelength points are (1350 nm,1360nm and … … 1850 nm), and the spectrum data of each pricklyash peel sample are actually expressed as a collection matrix of the light intensity values on the 51 wavelength points.
And carrying out second-order derivation on the spectrum data of the pricklyash peel sample, wherein the derivation mode is Savitzky-Golay derivation, the half window width is set to be 5, the highest order of the polynomials is set to be 5, and the derivation order is set to be 2.
S2, calculating the contribution weight coefficient of each wavelength point in the pepper spectrum data according to the second-order derivative spectrogram of the pepper sample;
in the pepper spectrum data, the contribution degree of the light intensity value on each wavelength point to the sample characteristic is different, namely the contribution weight is different, the difference value between the maximum value of the second derivative and the minimum value of the second derivative is selected as a reference value through the second derivative spectrum chart, and the second derivative value of each wavelength point is subjected to ratio operation, wherein the ratio is the contribution weight coefficient of each wavelength point.
In this embodiment, as shown in fig. 2, the maximum value of the second derivative is at point a of the second spectrum, the corresponding band range is 1380nm, the corresponding second derivative value is 20759, the minimum value of the second derivative is at point C of the second spectrum, the corresponding band range is 1630nm, the corresponding second derivative value is-7543, and the weight reference value X can be further calculated as:
X＝20759-(-7543)＝28302
the second derivative value of each wavelength point is subjected to ratio operation, and the ratio is the contribution weight coefficient of each wavelength point, such as C point with the wave band range of 1420nm, and the corresponding contribution weight coefficient T c The method comprises the following steps:
T c ＝12250/X＝12250/28302＝0.4328
namely, the contribution weight coefficient of the light intensity value point with the wave band range of 1420nm to the spectrum data of the pricklyash peel sample is 43.28%.
The contribution weight coefficient (alpha) of the light intensity value points in each wavelength range to the spectral data of the pricklyash peel sample can be further calculated by the same method 1 ，α 2 ……，α 51 ) The contribution weight coefficient of the light intensity value point with the wave band range of 1350nm is alpha 1 The contribution weight coefficient of the light intensity value point with the wavelength range of 1360nm is alpha 2 。
S3, calculating a spectrum mean value according to the contribution weight coefficient and the light intensity value of each wavelength point in the spectrum data of the pepper sample;
in the step, the specific contribution value of each wavelength point can be obtained by carrying out product operation on the light intensity value of each wavelength point of the spectrum data of the pepper sample and the corresponding contribution weight coefficient, and the spectrum average value can be obtained by carrying out average calculation on all the contribution values.
In this embodiment, the spectral data of the pricklyash peel sample is set to (P 1 ，P 2 ……，P 51 ) I.e. the light intensity corresponding to a band of 1350nm is P 1 The light intensity value corresponding to the wavelength range 1360nm is P 2 The specific contribution value of each wavelength point is (alpha) obtained by combining the weight coefficient of each wavelength point of the spectrum data of the pricklyash peel sample 1 *P 1 ，α 2 *P 2 ……，α 2 *P 51 ) Further, the spectrum mean value P can be obtained ave The method comprises the following steps:
P ave ＝(α 1 *P 1 +α 2 *P 2 ……+α 2 *P 51 )/51
s4, calculating the reflectivity of the sample according to the corresponding relation between the spectrum average value of the pricklyash peel sample and the reflectivity of the pricklyash peel sample;
the portable near infrared light source emits near infrared light to reach the surface of the object to be detected after being attenuated by the near infrared light cavity, the near infrared light is converged into sampling light spots, the sampling light spots are subjected to light reflection by the object to be detected, the sampling light spots reach the spectrum sensor after being attenuated by the light cavity, and the spectrum sensor receives the reflected light intensity information to generate corresponding spectrum data values. And by combining the illumination intensity of the near infrared illumination and the attenuation rate of the optical cavity, the corresponding relation between the spectral average value of the pricklyash peel sample and the reflectivity of the pricklyash peel sample can be calculated by the illumination intensity value received by the spectral sensor.
In this embodiment, the reflectance of the pepper sample is set to be β, the attenuation rate of the optical cavity of the portable near infrared spectrometer is γ, the illuminance value of the illumination emitted by the portable near infrared light source is K, and the following is known according to the working principle of the portable near infrared spectrometer:
the relation between the illumination intensity K of the portable near infrared spectrum and the receiving illumination intensity Z of the sensor is as follows:
Z＝K*(1-γ)*β*(1-γ)
the light cavity attenuation rate of the same portable near infrared spectrometer is a fixed value, the illumination intensity is also a fixed value, the illumination intensity value received by the sensor is only related to the reflectivity of an object to be detected and is linearly and positively related, meanwhile, the illumination intensity value received by the sensor is converted into spectrum data through analog-digital conversion according to the working principle of the portable near infrared spectrometer, namely, the illumination intensity value received by the sensor and the spectrum mean value are linearly and positively related, and accordingly, the spectrum mean value of a pricklyash peel sample and the reflectivity of the pricklyash peel sample are linearly and positively related.
S5, judging the quality of the pepper sample according to the reflectivity of the pepper sample;
as the absorption degrees of the pepper samples with different qualities to the near infrared light are different, the better the quality of the pepper samples, the stronger the absorption to the near infrared light, namely the smaller the spectrum average value of the pepper samples collected by the same portable near infrared spectrometer, the smaller the reflectivity of the pepper samples, namely the stronger the absorption to the near infrared light, the better the quality of the pepper samples is further judged.
Therefore, the reflectivity threshold corresponding to different quality grades of the pricklyash peel sample can be set, and the reflectivity of the pricklyash peel sample is compared with the reflectivity threshold corresponding to different quality, so that the quality grade of the pricklyash peel sample is determined.
As a simplified embodiment, for example: the quality grades of the pricklyash peel samples are divided into two stages: i.e. the priority and the secondary, only one reflectivity threshold value can be set, and the reflectivity threshold value is assumed to be delta, i.e. the reflectivity of the pricklyash peel sample is more than delta and is secondary and less than delta, and the spectrum average value corresponding to the reflectivity threshold value delta is P δ For different pricklyash peel samples, if the spectrum average value acquired by the portable near infrared spectrum equipment is set as P ε The reflectivity epsilon of the pepper sample can be calculated as:
ε＝δP ε /P δ
and comparing the reflectivity epsilon of the pepper sample with a threshold delta, and further judging the quality difference of the pepper sample.
Finally, it should be noted that the above examples are only preferred embodiments and are not intended to limit the invention. It should be noted that modifications, equivalents, improvements and others may be made by those skilled in the art without departing from the spirit of the invention and the scope of the claims, and are intended to be included within the scope of the invention.
Claims (4)
1. The method for rapidly judging the quality of the peppers based on the near infrared spectrum is characterized by comprising the following steps of:
s1, collecting spectrum data of a pepper sample and performing second-order derivation;
s2, calculating the contribution weight coefficient of each wavelength point in the pepper spectrum data according to the second-order derivative spectrogram of the pepper sample;
s3, calculating a spectrum mean value according to the contribution weight coefficient and the light intensity value of each wavelength point in the spectrum data of the pepper sample;
s4, calculating the reflectivity of the sample according to the corresponding relation between the spectrum average value of the pricklyash peel sample and the reflectivity of the pricklyash peel sample;
s5, judging the quality of the pepper sample according to the reflectivity of the pepper sample;
in step S2, calculating a contribution weight coefficient of each wavelength point in the pepper spectrum data according to the second-order derivative spectrogram of the pepper sample, specifically including:
the difference value between the maximum value and the minimum value of the second derivative is selected as a reference value through the second derivative spectrum diagram, and the second derivative value of each wavelength point is subjected to ratio operation, wherein the ratio is the contribution weight coefficient of each wavelength point;
in step S3, calculating a spectrum mean value according to the contribution weight coefficient and the light intensity value of each wavelength point in the spectrum data of the pepper sample specifically includes:
carrying out product operation on the light intensity value of each wavelength point of the spectrum data of the pepper sample and the corresponding contribution weight coefficient to obtain a specific contribution value of each wavelength point, and carrying out average calculation on all the contribution values to obtain a spectrum average value;
in step S4, the corresponding relationship between the spectrum mean value of the pricklyash peel sample and the reflectivity thereof is as follows: the spectrum average value of the pricklyash peel sample is in linear positive correlation with the reflectivity thereof; and the corresponding relation between the spectral mean value of the pricklyash peel sample and the reflectivity of the pricklyash peel sample can be calculated by combining the illumination intensity of the near infrared illumination, the attenuation rate of the optical cavity and the illumination value received by the spectral sensor.
2. The method for rapidly distinguishing quality of Chinese prickly ash based on near infrared spectrum according to claim 1, wherein,
in the step S1, a wavelength equipartition type portable near infrared spectrometer is adopted to collect spectrum data of pepper samples, the wavelength range is 1350-1850 nm, the resolution is 10nm, the spectrum data comprises 51 wavelength points, and the actual spectrum data of each pepper sample is represented as a matrix set of light intensity values on the 51 wavelength points.
3. The method for rapidly distinguishing quality of Chinese prickly ash based on near infrared spectrum according to claim 1, wherein,
in the step S1, the second order derivation is performed on the spectrum data of the pricklyash peel sample in the following manner: and adopting Savitzky-Golay derivation, setting the half window width to be 5, setting the highest order of the polynomial to be 5, and setting the derivation order to be 2.
4. A method for rapidly determining quality of peppers based on near infrared spectrum according to any one of claims 1-3, wherein in step S5, the quality is determined according to reflectivity of peppers sample, specifically comprising:
and setting reflectivity thresholds corresponding to different quality grades of the pricklyash peel samples, and comparing the reflectivity of the pricklyash peel samples with the reflectivity thresholds corresponding to different qualities, so as to determine the quality grade of the pricklyash peel samples.
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| CN111398212A (en) * | 2020-04-08 | 2020-07-10 | 四川虹微技术有限公司 | Method for establishing pepper detection model based on portable near-infrared spectrometer |
| CN112861907A (en) * | 2020-12-31 | 2021-05-28 | 福建融韵通生态科技有限公司 | Method for tracing origin of white tea |
| CN113686811A (en) * | 2021-08-26 | 2021-11-23 | 四川启睿克科技有限公司 | Spectral data processing method based on double sensors |
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