CN102519903B - Method for measuring whiteness value of Agaricus bisporus by using near infrared spectrum - Google Patents
Method for measuring whiteness value of Agaricus bisporus by using near infrared spectrum Download PDFInfo
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Abstract
The invention relates to a method for rapidly, simply and conveniently detecting a whiteness value of Agaricus bisporus and an application of the method. The method mainly comprises the following steps of: (1) collecting Agaricus bisporus samples; (2) utilizing a color difference meter to respectively measure the whiteness values of mushroom skins and mushroom flesh of the Agaricus bisporus; (3) collecting an near infrared spectrum of the Agaricus bisporus samples; (4) pre-processing the near infrared spectrum, eliminating interference factors and selecting a wavelength range; (5) respectively establishing a correction model between the whiteness values of the mushroom skins and the mushroom flesh of the Agaricus bisporus samples and the near infrared spectrum, and checking; (6) collecting the near infrared spectrum of samples to be detected; and (7) utilizing the model to predict the whiteness values of the mushroom skins and the mushroom flesh of the Agaricus bisporus to be detected. The method provided by the invention has the advantages of no need of pre-treatment, high analysis speed, environmental friendliness and the like; and meanwhile, the whiteness values of the mushroom skins and the mushroom flesh of the Agaricus bisporus to be detected can be predicted, and the results are reliable and ideal.
Description
Technical field
The present invention relates to a kind of spectrographic technique of measuring the agaricus bisporus whiteness value, particularly relate to a kind of method of measuring whiteness value of Agaricus bisporus by using near infrared spectrum.
Background technology
Agaricus bisporus is the high edible fungus of a kind of nutritive value, its delicious flavour, nutritious being well received by consumers.The cultivation amount of China's agaricus bisporus occupies first place, the world.Directly come into the market after most of agaricus bisporus is plucked, fail to carry out quality grading, reduced commodity value; Another part is used for selling after the storage, but fails in time to understand the variation of its duration of storage quality, causes unnecessary economic loss.The brown stain degree is one of important symbol of reflection agaricus bisporus quality, and significant at transportation, storage and selling period.Traditional conventional sense method is that agaricus bisporus is cut, and the whiteness value of measuring respectively mushroom skin and mushroom meat with colour difference meter again represents its browning degree, causes greatly wastage of material.Therefore, how effectively, fast, nondestructively the whiteness value of estimating agaricus bisporus becomes the concerned issue of mushroom farming, agaricus bisporus manufacturing enterprise and storage machining sector.
Near infrared (Near Infrared, NIR) the light wavelength scope is about 780～2500nm, the electromagnetic wave between visible range and middle infrared, by with material in the effect of hydric group X-H key of organic molecule, form frequency multiplication and the sum of fundamental frequencies absorption spectrum of organic molecule.The information characteristics such as the position that occurs according to these near infrared absorption frequency spectrums, absorption intensity are made qualitative and quantitative analysis in conjunction with mathematical statistics to this composition.Compare the more Chemical Measurement algorithm of this Technology Need and software engineering with conventional analysis.Along with the development of computer technology, Chemical Measurement research deeply reach the day by day perfect of near infrared spectroscopy instrument manufacturing technology, near-infrared spectral analysis technology is developed by leaps and bounds.Owing to having fast, be widely used in the fields such as agricultural product, food, chemistry, medicine, oil without characteristics such as pre-treatment, environmental protection, thereby become the most noticeable spectral analysis technique nineties.
Summary of the invention
For addressing the above problem, the purpose of this invention is to provide a kind of near-infrared spectrum method and application thereof of simple, fast detecting agaricus bisporus whiteness value.
The invention provides a kind of method of measuring whiteness value of Agaricus bisporus by using near infrared spectrum, may further comprise the steps: 1) collect the agaricus bisporus sample; 2) record respectively the whiteness value of agaricus bisporus mushroom skin and mushroom meat with colour difference meter; 3) the near infrared light spectrogram of collection agaricus bisporus sample; 4) described near infrared light spectrogram is carried out pre-service, eliminate disturbing factor, chosen wavelength range; 5) whiteness value and the calibration model between the near infrared spectrum of setting up respectively agaricus bisporus sample mushroom skin and mushroom meat are also checked; 6) near infrared spectrum of collection testing sample; 7) with positive model for school building predict the whiteness value of agaricus bisporus mushroom skin to be measured and mushroom meat.
The quantity of the described agaricus bisporus sample of step 1) is at least 80, the agaricus bisporus sample source is true, and the agaricus bisporus sample is divided into calibration set sample and checking collection sample at random, wherein, the calibration set sample is for setting up calibration model, and checking collection sample is for testing model.
Step 2) described method with aberration instrumentation agaricus bisporus whiteness value is: adopt the full-automatic colour difference meter of SC-80 C type to measure, with standard ceramic plate (X=81.75, Y=86.40, Z=90.89) as working stamndard, measure the whiteness value of agaricus bisporus fructification surface, inner mushroom meat tissue tangent plane, represent that with L L=0 is black, L=100 is white.
Use N-200 near infrared attributional analysis instrument and gather the agaricus bisporus sample, scanning times is: 78 times; Spectral scan scope: 10000cm
-1～4000cm
-1, resolution: 2cm
-1, replication three times is averaged spectrum.Instrument self with the software with NIRs collection, storage, processing capacity or other generally acknowledged statistical software process spectrogram, for example can adopt NIRcal software.
Original spectrum is carried out preprocess method to be comprised: first order derivative, second derivative, polynary scatter correction, vector normalization etc.These methods can be used separately or a plurality ofly unite use, to reach best pretreating effect.
The chemometrics method of setting up the calibration model between NIR spectrum and the agaricus bisporus whiteness value comprises: partial least square method (PLS), multiple linear regression (MLR), principal component regression (PCR) etc.With related coefficient (R
2), validation-cross standard deviation (RMSECV) or prediction mean square deviation (RMSEP) evaluation model performance.
With chemical score (numerical value that namely records with colour difference meter, lower same) sample corresponding to input, in conjunction with spectrogram, set up agaricus bisporus whiteness value quantitative math-model with partial least square method or other chemometrics method, with related coefficient (R
2), validation-cross standard deviation (RMSECV) evaluation model is good and bad.Related coefficient is maximum, the model of standard deviation minimum, best results.
Related coefficient
The validation-cross standard deviation
, wherein: Differ
iRepresent the poor of the chemical score of i sample and NIR predicted value, M is the calibration set sample number, y
iBe the chemical score of i sample, y
mThe mean value of m sample NIR predicted value.
Investigate quantitatively sample of model with checking collection sample, with prediction standard deviation (RMSEP), and predict the outcome with chemical gauging result and NIR and to compare, the significance of difference of two kinds of methods of check, this model of the inapparent explanation of difference can replace classic method.
The test statistics computing formula of described T check is as follows:
The spectra collection method of testing sample gathers the method for spectrum during with modeling, with the whiteness value of the model fast prediction agaricus bisporus of setting up.
The application of near-infrared spectrum method of the present invention in measuring the agaricus bisporus whiteness value.
The present invention has following beneficial effect: 1) the present invention adopts N-200 near infrared attributional analysis instrument, has the advantages such as the pre-treatment of need not, analysis speed are fast, guarantor.The present invention can detect the whiteness value of agaricus bisporus mushroom skin and mushroom meat simultaneously, has solved time-consuming, the waste problem of conventional method of analysis, has improved analysis efficiency, is a kind of quick novel detection method that the agaricus bisporus whiteness value is analyzed.2) utilize the diffuse reflection near-infrared spectral analysis technology to analyze the whiteness value of agaricus bisporus, set up the calibration model of agaricus bisporus mushroom skin and mushroom meat whiteness value and near infrared spectrum in conjunction with the PLS method, by predicting unknown sample, reliable results, ideal.Therefore, this technology can be promoted, especially save a large amount of human and material resources for agaricus bisporus manufacturing enterprise and storage machining sector carry out Real-Time Monitoring to product, be the support that provides the necessary technical of agaricus bisporus rapid classification.
Embodiment
Following examples are used for explanation the present invention, but are not used for limiting the scope of the invention.
The near infrared light spectrogram of embodiment 1 agaricus bisporus sample.
At least collect 80 samples (acquisition of agaricus bisporus culturing base), be divided at random calibration set and checking collection (3:1).Agaricus bisporus is transported Storage in cold bank back after plucking, and experiment is taken out the previous day, and room temperature is placed.Adopt N-200 near infrared attributional analysis instrument scanning agaricus bisporus sample.Scanning times is: 78 times; Spectral scan scope: 10000cm
-1～4000cm
-1, resolution: 2cm
-1, replication three times is got its averaged spectrum (see figure 1).
Embodiment 2 agaricus bisporus mushroom skin whiteness value models.
2.1 mushroom skin whiteness value model is set up.
Circumscribed being placed on facing up under the full-automatic colour difference meter of SC-80C of the mushroom meat tissue of agaricus bisporus fructification section, read whiteness value, adopt NIRcal software, the sample spectrum diagram that embodiment 1 is gathered carries out the pre-service of polynary scatter correction spectrum, adopt partial least square method to set up mathematical model, model is carried out cross validation, obtain agaricus bisporus whiteness value NIR predicted value and actual value crosscheck figure.The coefficient of determination (R
2) reaching 0.9486, validation-cross mean square deviation (RMSECV) is 0.312.
2.2 mushroom skin whiteness value model testing.
Agaricus bisporus sample whiteness value is predicted with setting up good model predicting the outcome sees Table 1 with classic method measurement result and deviation thereof.L, a, b predicted root mean square error (RMSEP) are respectively 0.321,0.296,0.313.By pairing T check, the result shows near infrared prediction agaricus bisporus whiteness value and classic method result without significant difference, and it is accurately and reliably that the model of building is used for the detection of agaricus bisporus whiteness value.
Embodiment 3 agaricus bisporus mushroom meat whiteness value models.
2.1 mushroom meat whiteness value model is set up.
The mushroom meat tissue of agaricus bisporus fructification section inscribe is placed under the full-automatic colour difference meter of SC-80C facing up, read whiteness value, adopt NIRcal software, the sample spectrum diagram that embodiment 1 is gathered carries out the pre-service of polynary scatter correction spectrum, adopt partial least square method to set up mathematical model, model is carried out cross validation, obtain agaricus bisporus whiteness value NIR predicted value and actual value crosscheck figure.The coefficient of determination (R
2) reaching 0.9325, validation-cross mean square deviation (RMSECV) is 0.214.
2.2 mushroom meat whiteness value model testing.
Agaricus bisporus sample whiteness value is predicted with setting up good model predicting the outcome sees Table 1 with classic method measurement result and deviation thereof.L, a, b predicted root mean square error (RMSEP) are respectively 0.223,0.266,0.307.By pairing T check, the result shows near infrared prediction agaricus bisporus whiteness value and classic method result without significant difference, and it is accurately and reliably that the model of building is used for the detection of agaricus bisporus whiteness value.
Table 1 whiteness value NIR predicted value and classic method measured value result are relatively.
| Outer parameter | Measured value | Predicted value | Relative deviation/% | Intrinsic parameter | Measured value | Predicted value | Relative deviation/% |
| L 1 * | 84.28 | 80.76 | 4.1766 | L 1 * | 91.73 | 89.63 | 2.2893 |
| a 1 * | 4.85 | 5.29 | 9.0721 | a 1 * | 2.64 | 2.44 | 6.8702 |
| b 1 * | 19.05 | 17.21 | 9.6588 | b 1 * | 14.32 | 13.39 | 6.4944 |
| L 2 * | 80.45 | 77.49 | 3.6793 | L 2 * | 89.63 | 91.56 | 2.1533 |
| a 2 * | 6.02 | 5.48 | 8.9701 | a 2 * | 4.20 | 3.97 | 5.4762 |
| b 2 * | 20.83 | 22.31 | 7.1051 | b 2 * | 16.78 | 18.29 | 8.9988 |
| L 3 * | 79.64 | 77.22 | 3.0387 | L 3 * | 84.57 | 82.54 | 2.4004 |
| a 3 * | 5.97 | 5.39 | 9.7152 | a 3 * | 7.29 | 6.97 | 4.3896 |
| b 3 * | 22.46 | 20.78 | 7.4780 | b 3 * | 19.38 | 18.06 | 6.8111 |
| L 4 * | 77.13 | 79.06 | 2.5022 | L 4 * | 86.49 | 84.76 | 2.0001 |
| a 4 * | 6.32 | 5.94 | 6.0127 | a 4 * | 5.34 | 4.99 | 6.5543 |
| b 4 * | 24.62 | 23.14 | 6.0117 | b 4 * | 18.32 | 17.04 | 6.9869 |
| L 5 * | 79.65 | 77.82 | 2.2976 | L 5 * | 80.45 | 79.01 | 1.7899 |
| a 5 * | 5.84 | 5.63 | 3.5959 | a 5 * | 9.78 | 9.21 | 5.8282 |
| b 5 * | 26.75 | 28.23 | 5.5327 | b 5 * | 18.79 | 17.34 | 7.7169 |
| L 6 * | 75.43 | 76.95 | 2.0151 | L 6 * | 76.54 | 74.52 | 2.6391 |
| a 6 * | 7.93 | 7.64 | 3.6570 | a 6 * | 10.29 | 11.19 | 8.7464 |
| b 6 * | 26.21 | 24.48 | 6.6005 | b 6 * | 20.65 | 22.31 | 8.0387 |
| L 7 * | 80.79 | 79.02 | 2.1909 | L 7 * | 70.82 | 69.03 | 2.5275 |
| a 7 * | 6.89 | 6.57 | 4.6444 | a 7 * | 14.34 | 13.43 | 6.3459 |
| b 7 * | 19.07 | 17.84 | 6.4500 | b 7 * | 23.21 | 21.32 | 8.1430 |
| L 8 * | 70.26 | 68.46 | 2.5619 | L 8 * | 72.21 | 70.32 | 2.6174 |
| a 8 * | 9.07 | 9.37 | 3.3076 | a 8 * | 15.69 | 14.46 | 7.8394 |
| b 8 * | 22.49 | 24.17 | 7.4700 | b 8 * | 22.14 | 20.65 | 6.7299 |
| L 9 * | 70.63 | 68.53 | 2.9732 | L 9 * | 68.47 | 70.42 | 2.8480 |
| a 9 * | 10.02 | 9.79 | 2.2954 | a 9 * | 16.76 | 17.97 | 7.2196 |
| b 9 * | 25.04 | 27.12 | 8.3067 | b 9 * | 24.89 | 22.50 | 9.6022 |
| L 10 * | 62.87 | 60.95 | 3.0539 | L 10 * | 64.87 | 66.97 | 3.2372 |
| a 10 * | 16.79 | 17.96 | 6.9684 | a 10 * | 16.97 | 16.05 | 5.4213 |
| b 10 * | 30.01 | 31.28 | 4.2319 | b 10 * | 26.83 | 27.92 | 4.0626 |
Inside and outside parameter represents respectively mushroom skin and the corresponding parameter of mushroom meat.
The whiteness value of embodiment 4 prediction agaricus bisporus samples.
Unknown agaricus bisporus sample is scanned, then compare the near infrared spectrum of unknown sample and calibration sample, with the whiteness value of the model prediction agaricus bisporus of setting up above.
Claims (7)
1. the method for a measuring whiteness value of Agaricus bisporus by using near infrared spectrum is characterized in that, may further comprise the steps:
1) collect the agaricus bisporus sample, described agaricus bisporus sample is divided into calibration set sample and checking collection sample at random, and wherein, the calibration set sample is for setting up calibration model, and checking collection sample is for testing model;
2) record respectively the whiteness value of agaricus bisporus mushroom skin and mushroom meat with colour difference meter;
3) the near infrared light spectrogram of collection agaricus bisporus sample;
4) described near infrared light spectrogram is carried out pre-service, eliminate disturbing factor, chosen wavelength range;
5) whiteness value and the calibration model between the near infrared spectrum of setting up respectively agaricus bisporus sample mushroom skin and mushroom meat are also checked;
6) near infrared spectrum of collection testing sample;
7) with positive model for school building predict the whiteness value of agaricus bisporus mushroom skin to be measured and mushroom meat;
Wherein, the described calibration model of step 5) adopts partial least square method to set up through the internal chiasma check, the specific algorithm of internal chiasma check: in M sample spectra, take out the 1st sample spectra, set up basic model with M-1 sample spectra, to take out again sample spectra and be used for check, and the error of calculation; The 1st sample spectra put back to, taken out another sample spectra, so repeat, circulate, until each spectrum is verified analysis; By weighing the related coefficient (R between sample near infrared predicted value and chemical score
2) and cross validation mean square deviation (RMSECV) index evaluation model performance, wherein R
2As follows with the computing formula of RMSECV:
Related coefficient
The cross validation mean square deviation
Wherein: Differ
iRepresent the poor of the chemical score of i sample and NIR predicted value, M is the calibration set sample number, y
iBe the chemical score of i sample, y
mThe mean value of m sample NIR predicted value;
With the calibration model prediction checking collection sample of optimizing well, relatively NIR predicted value and chemical score content are used prediction mean square deviation (RMSEP) and matched pair technique T test evaluation model, and the RMSEP formula is as follows:
Wherein: Differ
iRepresent the poor of the chemical score of i sample and NIR predicted value, N is checking collection sample number;
The test statistics computing formula of described T check is as follows:
Wherein:
Represent the poor of chemical score and predicted value mean value,
Standard deviation for average of samples.
2. the method for claim 1 is characterized in that, the quantity of the described agaricus bisporus sample of step 1) is at least 80.
3. the method for claim 1, it is characterized in that, step 2) described method with aberration instrumentation agaricus bisporus whiteness value is: adopt the full-automatic colour difference meter of SC-80C type to measure, with standard ceramic plate (X=81.75, Y=86.40, Z=90.89) as working stamndard, measure the whiteness value of agaricus bisporus fructification surface, inner mushroom meat tissue tangent plane, represent that with L L=0 is black, L=100 is white.
4. the method for claim 1 is characterized in that, uses the near infrared spectrum that N-200 near infrared attributional analysis instrument gathers agaricus bisporus.
5. method as claimed in claim 4 is characterized in that: the near infrared spectrum scanning scope that gathers agaricus bisporus is 10000cm
-1～4000cm
-1, resolution: 2cm
-1, replication three times is averaged spectrum.
6. the method for claim 1 is characterized in that, step 4) is described carries out pretreated method and be selected from first order derivative, second derivative, polynary scatter correction, the vector normalization one or more.
7. such as the application of each described near-infrared spectrum method of claim 1～6 in measuring the agaricus bisporus whiteness value.
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| CN104764718A (en) * | 2015-04-14 | 2015-07-08 | 云南中烟工业有限责任公司 | Method for performing color-difference evaluation on cigarette outside wrapping paper |
| CN107064020A (en) * | 2017-06-09 | 2017-08-18 | 刘胜 | A kind of domestic ceramics raw material whiteness proficiency testing sample |
| CN110006844A (en) * | 2019-05-22 | 2019-07-12 | 安徽大学 | Near infrared spectrum feature extracting method and system based on functionality pivot analysis |
| CN113607681A (en) * | 2021-07-19 | 2021-11-05 | 黑龙江八一农垦大学 | Pleurotus eryngii mycelium detection method and device, electronic equipment and storage medium |
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| CN101769866A (en) * | 2010-01-15 | 2010-07-07 | 中国农业机械化科学研究院 | Device for detecting milk components and method thereof |
| CN102128805A (en) * | 2010-12-23 | 2011-07-20 | 华东交通大学 | Method and device for near infrared spectrum wavelength selection and quick quantitative analysis of fruit |
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| CN101769866A (en) * | 2010-01-15 | 2010-07-07 | 中国农业机械化科学研究院 | Device for detecting milk components and method thereof |
| CN102128805A (en) * | 2010-12-23 | 2011-07-20 | 华东交通大学 | Method and device for near infrared spectrum wavelength selection and quick quantitative analysis of fruit |
Non-Patent Citations (2)
| Title |
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| 可见近红外漫反射光谱法测定赣南脐橙的表面色泽;文建萍等;《安徽农业科学》;20071230;第35卷(第36期);11805-11806页 * |
| 文建萍等.可见近红外漫反射光谱法测定赣南脐橙的表面色泽.《安徽农业科学》.2007,第35卷(第36期),11805-11806页. |
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