CN105758897B - A kind of white peony fragrance Grade Judgment based on electronic nose detection information - Google Patents
A kind of white peony fragrance Grade Judgment based on electronic nose detection information Download PDFInfo
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- CN105758897B CN105758897B CN201610186734.2A CN201610186734A CN105758897B CN 105758897 B CN105758897 B CN 105758897B CN 201610186734 A CN201610186734 A CN 201610186734A CN 105758897 B CN105758897 B CN 105758897B
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- white peony
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- 239000003205 fragrance Substances 0.000 title claims abstract description 25
- 244000236658 Paeonia lactiflora Species 0.000 title claims abstract description 24
- 235000008598 Paeonia lactiflora Nutrition 0.000 title claims abstract description 24
- 238000001514 detection method Methods 0.000 title claims abstract description 20
- 238000000034 method Methods 0.000 claims abstract description 11
- 238000002360 preparation method Methods 0.000 claims abstract description 5
- 239000007789 gas Substances 0.000 claims description 12
- 229910044991 metal oxide Inorganic materials 0.000 claims description 7
- 150000004706 metal oxides Chemical class 0.000 claims description 7
- 239000000796 flavoring agent Substances 0.000 claims description 6
- 235000019634 flavors Nutrition 0.000 claims description 6
- QGZKDVFQNNGYKY-UHFFFAOYSA-N Ammonia Chemical compound N QGZKDVFQNNGYKY-UHFFFAOYSA-N 0.000 claims description 4
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 claims description 4
- 235000013305 food Nutrition 0.000 claims description 3
- RWSOTUBLDIXVET-UHFFFAOYSA-N Dihydrogen sulfide Chemical compound S RWSOTUBLDIXVET-UHFFFAOYSA-N 0.000 claims description 2
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 claims description 2
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 claims description 2
- 150000001335 aliphatic alkanes Chemical class 0.000 claims description 2
- 150000001412 amines Chemical class 0.000 claims description 2
- 229910021529 ammonia Inorganic materials 0.000 claims description 2
- -1 biogas Natural products 0.000 claims description 2
- 238000010411 cooking Methods 0.000 claims description 2
- 229930195733 hydrocarbon Natural products 0.000 claims description 2
- 150000002430 hydrocarbons Chemical class 0.000 claims description 2
- 239000001257 hydrogen Substances 0.000 claims description 2
- 229910052739 hydrogen Inorganic materials 0.000 claims description 2
- 229910000037 hydrogen sulfide Inorganic materials 0.000 claims description 2
- 239000003350 kerosene Substances 0.000 claims description 2
- 239000005416 organic matter Substances 0.000 claims description 2
- 239000003960 organic solvent Substances 0.000 claims description 2
- UCKMPCXJQFINFW-UHFFFAOYSA-N Sulphide Chemical compound [S-2] UCKMPCXJQFINFW-UHFFFAOYSA-N 0.000 claims 1
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 claims 1
- 239000010931 gold Substances 0.000 claims 1
- 229910052737 gold Inorganic materials 0.000 claims 1
- 238000004458 analytical method Methods 0.000 abstract description 8
- 230000004069 differentiation Effects 0.000 abstract description 4
- 238000011156 evaluation Methods 0.000 abstract description 3
- 238000004519 manufacturing process Methods 0.000 abstract description 2
- 230000001953 sensory effect Effects 0.000 abstract description 2
- 244000269722 Thea sinensis Species 0.000 abstract 1
- 210000001331 nose Anatomy 0.000 description 18
- 235000013616 tea Nutrition 0.000 description 7
- 235000020334 white tea Nutrition 0.000 description 5
- 241001122767 Theaceae Species 0.000 description 4
- 238000007477 logistic regression Methods 0.000 description 4
- VIKNJXKGJWUCNN-XGXHKTLJSA-N norethisterone Chemical compound O=C1CC[C@@H]2[C@H]3CC[C@](C)([C@](CC4)(O)C#C)[C@@H]4[C@@H]3CCC2=C1 VIKNJXKGJWUCNN-XGXHKTLJSA-N 0.000 description 4
- 238000003380 quartz crystal microbalance Methods 0.000 description 3
- 229920001940 conductive polymer Polymers 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000004615 ingredient Substances 0.000 description 2
- 238000010897 surface acoustic wave method Methods 0.000 description 2
- 235000009024 Ceanothus sanguineus Nutrition 0.000 description 1
- 240000003553 Leptospermum scoparium Species 0.000 description 1
- 235000015459 Lycium barbarum Nutrition 0.000 description 1
- BQCADISMDOOEFD-UHFFFAOYSA-N Silver Chemical compound [Ag] BQCADISMDOOEFD-UHFFFAOYSA-N 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 239000002322 conducting polymer Substances 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 230000003647 oxidation Effects 0.000 description 1
- 238000007254 oxidation reaction Methods 0.000 description 1
- 238000004080 punching Methods 0.000 description 1
- 238000013139 quantization Methods 0.000 description 1
- 238000000611 regression analysis Methods 0.000 description 1
- 210000000697 sensory organ Anatomy 0.000 description 1
- 229910052709 silver Inorganic materials 0.000 description 1
- 239000004332 silver Substances 0.000 description 1
- 238000004073 vulcanization Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
- G01N27/04—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance
- G01N27/12—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance of a solid body in dependence upon absorption of a fluid; of a solid body in dependence upon reaction with a fluid, for detecting components in the fluid
Abstract
The present invention relates to a kind of white peony fragrance Grade Judgments based on electronic nose detection information, are returned including sample preparation, acquisition testing information, structure Logistic and differentiate that contiguous function and each rating sample differentiate probability of outcome.The method of discrimination of the present invention, efficiently solve the problems, such ass that " manually evaluating " process cannot be evaluated for a long time due to " sensory fatigue "；The different differentiation resultant errors evaluated between personnel are preferably eliminated, improve the stability and consistency of white peony fragrance grade assessment result；It is convenient and efficient to evaluate overall process, elapsed time is short, and each sample is completed to differentiate the time after the completion of sample preparation<5min；Modal analysis results show with good stability, are higher than 90% with the consistency of artificial assessment result.The present invention has good practical value, and the evaluation table of application and final tea products quality to automation control means in white peony production process addresses sale circulation and is of great significance.
Description
Technical field
The present invention relates to a kind of tea grades method of discrimination, and in particular to a kind of white peony based on electronic nose detection information
Fragrance Grade Judgment belongs to food technology field.
Background technology
White peony category white tea class, generally use Fuding white tea, the big milli tea in Fuding, the big white tea in Fuan, big white tea etc. of having stable political situation
One leaf of big white tea or one bud of Fujian Shuihsien's tea tree breed, two leaf tender tips are made.Because of its greenery folder silver color pekoe bud likeness in form flower, punching
Greenery support tender shoots after bubble, as if bud is just opened, therefore named " white peony ".
Traditionally the evaluation of fragrance grade needs to complete by " sense organ " for the person of evaluating, and it is longer not only to evaluate the period, Er Qierong
It is vulnerable to various subjective and extraneous factor interference, " consistency " of data and " quantization property " is all insufficient, it is difficult to objective and stable
Ground characterizes border quality in fact, it is therefore necessary to find a kind of standardization and easy-operating means realize the steady of the fragrant grade of white peony milli
It is fixed to differentiate.
Electronic nose is a kind of typical Artificial Olfactory (Artificial Olfactory System, AOS), it by
The electrochemical sensor permutation of certain selectivity and appropriate identification device are formed, and can identify simple and complicated smell.It with
General chemistry instrument is different, and obtained is not that sample ingredient is qualitative and quantitative result, but gives volatility in sample
The Global Information of ingredient, i.e. " finger print data ", it can monitor the gas of specific position continuously, in real time in long time
Taste situation by the comparison of the signal in the database with being established using standard specimen, is identified and judged.
According to the difference of gas sensor material type, electronic nose can be substantially divided into three categories, be metal oxidation respectively
Object type (Metal Oxide Sensors, MOS), conductive polymer subtype (Conducting Polymer), mass type：Such as application
Quartz crystal microbalance sensor (Quartz Crystal Microbalance, QCM) and surface acoustic wave sensor (Surface
Acoustic Wave, SAW).
The differentiation of white peony fragrance grade is carried out using metal-oxide electronic nose, mathematics is substantially to electronic nose
" finger print data " obtained carries out classification prediction, and statistics has the analysis method of such problem very much, common solution party
Case mainly has：" Logistic regression analyses " and " techniques of discriminant analysis ".When output variable is two classified variable, using " two
Item Logistic regression analyses ", when output variable is more classified variables, generally use " multinomial Logistic regression analyses ".
It, should when " multinomial Logistic regression analyses " is for solving one or more covariants with an ordered categorization dependent variable relationship
Method is also referred to as " grade regression analysis ".
Invention content
The object of the present invention is to provide a kind of white peony fragrance Grade Judgments based on electronic nose detection information.
The purpose of the present invention is achieved through the following technical solutions.
1st, a kind of white peony fragrance Grade Judgment based on electronic nose detection information, it is characterised in that method of discrimination is such as
Under：
(1) sample preparation：5.0g Tea Samples to be checked are weighed in detecting in bottle, is placed under 45 DEG C of baking ovens and balances 15min, adopt
It is detected with metal-oxide electronic nose；The metal-oxide electronic nose is made of 10 sensors, each sensor
Hindrance function is generated to different types of gas, specific corresponding gas is respectively：S1, ammonia, amine；S2, hydrogen sulfide, vulcanization
Object；S3, hydrogen；S4, alcohol, organic solvent；S5, volatilization gas during cooking food；S6, methane, biogas, hydrocarbons；
S7, imflammable gas；S8, volatile organic matter；S9, oxynitrides, gasoline, kerosene；S10, alkane, imflammable gas；
(2) acquisition testing information：Start the detection information that electronic nose obtains white peony fragrance, which is exported
Afterwards, it is variable X to choose " S1 " sensor response therein1, it is variable X to choose " S3 " sensor response therein2, choose
" S6 " sensor response therein is variable X3, it is variable X to choose " S7 " sensor response therein4, choose therein
" S9 " sensor response is variable X5；The acquisition testing information, with acquisition sample aroma component peak electric signal structure
Build detection information；
(3) structure Logistic, which is returned, differentiates contiguous function, and expression formula is respectively：
Link1 grades=- 13.380+ (2.288X1-6.378X2-5.977X3+6.376X4-9.952X5)；
Link2 grades=- 9.521+ (2.288X1-6.378X2-5.977X3+6.376X4-9.952X5)；
" Link1 grades " the representative sample flavour grade is 1 grade of contiguous function；" Link2 grades " representative sample flavour etc.
Grade is 2 grades of contiguous function；
(4) each rating sample differentiates that probability of outcome formula is：
P1 grade=1/ ﹝ 1+Exp (- Link1 grades of) ﹞；
P2 grades=1/ ﹝ 1+Exp (- Link2 grades of) ﹞-P1 grade；
P3 grades=1-P1 grade-P2 grades；
The P1 grade、P2 grades、P3 gradesNumerical value, for " electronic nose detection information " judgement each flavour grade ownership probability,
The grade of P corresponding to maximum value is the fragrance grade of sample.
Advantages of the present invention and advantageous effect：
1st, the white peony fragrance Grade Judgment based on metal-oxide electronic nose detection information of the invention, effectively
Solve the problems, such as that " manually evaluating " process cannot be carried out for a long time due to " sensory fatigue "；
2nd, the relative immobility of discrimination standard preferably eliminates the different differentiation resultant errors evaluated between personnel, improves
The stability and consistency of the fragrant grade assessment result of white peony milli；
3rd, evaluate that overall process is convenient and efficient, and elapsed time is short, the sample prepared completes the overall process differentiated and is less than 5min；
4th, since the large sample size tea sample that discrimination model uses the senior person of evaluating of multidigit to be carried out under kilter evaluates number
Structure is completed based on, meanwhile, modal analysis results show that model is with good stability, one with artificial assessment result
Cause property is also above 90%, therefore the differentiation result has good practical value, can assist realizing white peony fragrance well
Consistency, objectivity and the versatility of grade grade scale, to the application of automation control means during Tea Production and
The evaluation table of final tea products quality addresses sale circulation and clears away the obstacles.
Specific embodiment
In order to fully disclose the white peony fragrance Grade Judgment based on electronic nose detection information of the present invention, tie below
Embodiment is closed to be illustrated.
A kind of embodiment 1, fragrant Grade Judgment of white peony milli based on electronic nose detection information, includes the following steps：
(1) sample preparation：5.0g Tea Samples to be checked are weighed in detecting in bottle, is placed under 45 DEG C of baking ovens and balances 15min, adopt
WithSmartnose metal-oxide electronic noses are detected；
(2) acquisition testing information：Start the detection information that electronic nose obtains white peony fragrance, which is exported
Afterwards, " S1 " sensor response variable X therein1=3.44；" S3 " sensor response variable X2=2.32；" S6 " sensor
Response variable X3=2.01；" S7 " sensor response variable X4=2.26；" S9 " sensor response variable X5=2.26；
(3) structure Logistic, which is returned, differentiates contiguous function, and expression formula is respectively：
Link1 grades=- 13.380+ (2.288X1-6.378X2-5.977X3+6.376X4-9.952X5)；
Link2 grades=- 9.521+ (2.288X1-6.378X2-5.977X3+6.376X4-9.952X5)；
" Link1 grades " the representative sample fragrance grade is 1 grade of contiguous function；" Link2 grades " representative sample fragrance etc.
Grade is 2 grades of contiguous function, and result is as follows after bringing data into：
Link1 grades=- 13.380+ (2.288 × 4.088-6.378 × 1.589-5.977 × 2.502+6.376 ×
2.781-9.952×1.371)；
Link2 grades=- 9.521+ (2.288 × 4.088-6.378 × 1.589-5.977 × 2.502+6.376 × 2.781-
9.952×1.371)；
(4) each rating sample differentiates that probability of outcome formula is：
P1 grade=1/ ﹝ 1+Exp (﹝ 1+Exp (- 0.447) ﹞=0.610 of-Link1 grades of) ﹞=1/；
P2 grades=1/ ﹝ 1+Exp (- Link2 grades of) ﹞-P1 grade=0.038；
P3 grades=1-P1 grade-P2 grades=1-0.610-0.038=0.352；
The P1 grade、P2 grades、P3 gradesNumerical value, for " electronic nose detection information " judgement each fragrance grade ownership probability,
The grade of P corresponding to maximum value is the fragrance grade of sample.
Result of calculation is P1 grade=1.350 × 10-11, P2 grades=0.999, P3 grades=6.267 × 10-10, because 0.999>
1.350×10-11>6.267×10-10, so P2 grades>P3 grades>P1 grade, therefore, which is judged as 2 grades of probability most
Greatly, up to 99.9%, therefore the fragrance grade of the determining white peony is 2 grades.
Claims (3)
1. a kind of white peony fragrance Grade Judgment based on electronic nose detection information, it is characterised in that method of discrimination is as follows：
(1) sample preparation：5.0g Tea Samples to be checked are weighed in detecting in bottle, is placed under 45 DEG C of baking ovens and balances 15min, using gold
Belong to oxide type electronic nose to be detected；
(2) acquisition testing information：Start the detection information that electronic nose obtains white peony fragrance, after which is exported, choosing
It is variable X to take " S1 " sensor response therein1, it is variable X to choose " S3 " sensor response therein2, choose therein
" S6 " sensor response is variable X3, it is variable X to choose " S7 " sensor response therein4, choose " S9 " therein sensing
Device response is variable X5；
(3) structure Logistic, which is returned, differentiates contiguous function, and expression formula is respectively：
Link1 grades=- 13.380+ (2.288X1-6.378X2-5.977X3+6.376X4-9.952X5)；
Link2 grades=- 9.521+ (2.288X1-6.378X2-5.977X3+6.376X4-9.952X5)；
" Link1 grades " the representative sample flavour grade is 1 grade of contiguous function；" Link2 grades " representative sample flavour grade is 2
The contiguous function of grade；
(4) each rating sample differentiates that probability of outcome formula is：
P1 grade=1/ ﹝ 1+Exp (- Link1 grades of) ﹞；
P2 grades=1/ ﹝ 1+Exp (- Link2 grades of) ﹞-P1 grade；
P3 grades=1-P1 grade-P2 grades；
The P1 grade、P2 grades、P3 gradesNumerical value, the probability of each flavour grade ownership for " electronic nose detection information " judgement is maximum
The grade of the corresponding P of value is the fragrance grade of sample.
2. a kind of white peony fragrance Grade Judgment based on electronic nose detection information according to claim 1, special
Sign be the acquisition testing information, with acquisitions sample aroma component peak electric signal build detection information.
3. a kind of white peony fragrance Grade Judgment based on electronic nose detection information according to claim 1, special
Sign is that the electronic nose for metal-oxide electronic nose, is made of, each sensor is to different types of gas 10 sensors
Body generates hindrance function, and specific corresponding gas is respectively：S1, ammonia, amine；S2, hydrogen sulfide, sulfide；S3, hydrogen；S4,
Alcohol, organic solvent；S5, volatilization gas during cooking food；S6, methane, biogas, hydrocarbons；S7, imflammable gas；
S8, volatile organic matter；S9, oxynitrides, gasoline, kerosene；S10, alkane, imflammable gas.
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| CN106353217A (en) * | 2016-08-12 | 2017-01-25 | 泉州市旭丰粉体原料有限公司 | Odor test method |
| CN107843695B (en) * | 2017-10-31 | 2018-08-28 | 华东理工大学 | The electronic nose instrument evaluation method of tobacco and tobacco product aesthetic quality |
| CN111707728A (en) * | 2020-06-29 | 2020-09-25 | 闽江师范高等专科学校 | Method for identifying white peony tea with different grades based on HS-PTR-TOF-MS |
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| CN103134850A (en) * | 2013-03-01 | 2013-06-05 | 河南农业大学 | Tea quality rapid detection apparatus and detection method based on characteristic fragrance |
| CN103499613A (en) * | 2013-07-30 | 2014-01-08 | 中国标准化研究院 | Selection method of intelligent sensory spectrum feature sensors in electronic nose Longjing tea quality detection system |
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| WO2014143291A2 (en) * | 2012-12-21 | 2014-09-18 | Research Triangle Institute | An encased polymer nanofiber-based electronic nose |
| JP5723421B2 (en) * | 2012-07-20 | 2015-05-27 | 福永生物科技股▲ふん▼有限公司ＥＰＳ Ｂｉｏ Ｔｅｃｈｎｏｌｏｇｙ Ｃｏｒｐ． | Electronic nose device |
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| CN103134850A (en) * | 2013-03-01 | 2013-06-05 | 河南农业大学 | Tea quality rapid detection apparatus and detection method based on characteristic fragrance |
| CN103499613A (en) * | 2013-07-30 | 2014-01-08 | 中国标准化研究院 | Selection method of intelligent sensory spectrum feature sensors in electronic nose Longjing tea quality detection system |
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| Title |
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| 信阳毛尖茶品质等级的电子鼻检测;张红梅;《河南农业科学》;20121231;第36-38页 * |
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