CN107991396A - A kind of potato full-powder method for quick identification based on flavor analysis - Google Patents
A kind of potato full-powder method for quick identification based on flavor analysis Download PDFInfo
- Publication number
- CN107991396A CN107991396A CN201711005432.1A CN201711005432A CN107991396A CN 107991396 A CN107991396 A CN 107991396A CN 201711005432 A CN201711005432 A CN 201711005432A CN 107991396 A CN107991396 A CN 107991396A
- Authority
- CN
- China
- Prior art keywords
- potato
- powder
- analysis
- flavor
- gas
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/04—Preparation or injection of sample to be analysed
- G01N30/06—Preparation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/04—Preparation or injection of sample to be analysed
- G01N30/06—Preparation
- G01N2030/062—Preparation extracting sample from raw material
Abstract
A kind of potato full-powder method for quick identification based on flavor analysis of the present invention, belong to potato staple food material quality safety testing field, it is proposed to carry out qualitative analysis to potato starch sapidity ingredient based on headspace solid-phase microextraction technology combination gas chromatography mass spectrometry method, build smell intelligent checking system.By the sensing response signal acquisition and extraction and analysis to sample, the discrimination model of potato starch is established in application model recognition methods.The present invention is analyzed as foundation with the flavor characteristics of the potato full-powder of different processing temperatures, and based on intelligent sensory technology, simulation human olfactory carries out intelligent distinguishing to the dehydrated potato raw material of different processing conditions.The present invention provides a kind of quick, lossless, accurate method for the processing of potato full-powder and controlling of quality, it can be applied to multiple links, the quality guarantees for potato staple food product such as the purchasing of raw materials, processing, storage of the production of potato staple food metaplasia and theoretical foundation be provided.
Description
Technical field
The invention belongs to potato staple food material quality safety testing field, more particularly to potato full-powder quickly differentiates
Method and system.
Background technology
Potato is a kind of generally acknowledged Agrifood with high nutritive value in whole world, and the fourth-largest grain work in the world
Thing.In January, 2015 No.1 Central File and the Ministry of Agriculture using potato as staple food grain strategic development, ensureing national food security
With promoting will have more importantly meaning in national socio-economic development.
The production of potato staple food metaplasia is generally matched as primary raw material with dehydrated potato (full powder) and wheat flour,
Potato is processed into the staple food products such as steamed bun and noodles.The processing technology of potato full-powder mainly with drying, crush based on, wherein
Drying temperature has important shadow to the processing quality such as the Starch paste characters of potato full-powder, rheological behavior, protein characteristic index
Ring.Processing temperature is excessive to make farina be gelatinized, is protein-modified, so as to reduce adding for potato staple food raw material dough
Work performance.Processing temperature also has potato staple food products flavor formation certain influence at the same time, and the difference of processing temperature causes
Potato full-powder volatile flavor substance species and content have more apparent difference, and excessive processing temperature can cause to produce heterocycle
Material and bad flavor, so as to influence the organoleptic quality of potato product.Therefore, the flavor of potato full-powder raw material is as Ma Ling
One basic index of quality of potato staple food product, consumer is acted on certain guidance.
From the foregoing, it will be observed that processing temperature is an important factor for influencing potato full-powder processing quality, research at present mainly passes through
Measure Effect On Gelatinization Characteristics and heat analysis and fuzzy Judgment is carried out to starch material processing temperature, and based on flavor characteristics to different processing
The quick discriminating of the potato full-powder raw material of temperature and corresponding intrument are not studied.
The content of the invention
, can be quick the object of the present invention is to provide a kind of potato full-powder discrimination method and system based on flavor analysis
Identify the Volatile flavor components of potato full-powder, identification and classification, behaviour are carried out to the dehydrated potato raw material of different processing temperatures
Make simple and convenient, there is higher sensitivity and accuracy.The present invention is achieved through the following technical solutions：
The present invention is proposed based on headspace solid-phase microextraction technology combination gas chromatographymass spectrum (GS-MS) to potato starch
Sapidity ingredient carries out qualitative analysis, builds smell intelligent checking system.By to the sensing response signal acquisition of sample and extraction
The discrimination model of potato starch is established in analysis, application model recognition methods.
A kind of potato full-powder discrimination method based on flavor analysis, carries out as steps described below：
(1) extraction of potato full-powder flavor and analysis：Wind in potato starch is extracted using solid phase micro-extraction technique
Taste component, carries out GC-MS analyses to the flavor substance of extraction, obtains the GC-MS total ion currents of potato starch sapidity ingredient
Figure, analyzes and identifies main volatile compound；
(2) olfactory organoleptic's analysis system is built：The potato full-powder volatile ingredient feature of gained is analyzed according to GC-MS,
Gas sensor is screened to build gas sensor array, to parameters such as the gas collection time of smell intelligent checking system and sample sizes
Optimize.
(3) gas sensing signal collection and analysis：Using gas sensor array collection dehydrated potato smell response letter
Number, feature extraction is carried out to air-sensitive response signal.
(4) discrimination model is established：Using the characteristic signal of gas sensing array as input variable, established based on pattern-recognition de-
The discriminating model of water potato.
Wherein described step (1) carries out potato full-powder aroma volatiles analysis as steps described below：
1) using GC-MS respectively to the potato full-powder sample sapidity ingredients of multiple drying temperature gradients (50~90 DEG C) into
Row measure, obtains total ion current figure；
2) the larger shared peak of proof strength refers to as feature from the total ion current figure of step 1) potato full-powder sample
Line peak, using standard finger-print as reference fingerprint, calculates the relative peak area at characteristic fingerprint peak；
3) identify that three kinds of modes carry out not by using NIST library searchings, the contrast of linear retention index and n-compound
Know the identification of compound；Using NIST library searchings, when compound positive match degree >=800 retrieved are optimal.
Smell sensors array described in wherein described step (2) is made of multiple gas sensors, mainly according to step
(1) the potato full-powder sapidity ingredient of GC-MS analyses gained, some and potato full-powder main flavor group is obtained by screening in
The matched Metal Oxide Gas Sensors of split-phase.
Being carried out to parameters such as the gas collection time of smell intelligent checking system and sample sizes described in wherein described step (2) is excellent
Change, choose different gas collection times and sample size and carry out signal contrast analysis, determine that the optimal gas collection time is 30min, sample size
For 2g.
Gas sensing signal collection and analysis described in wherein described step (3), carries out as steps described below：
1) dehydrated potato headspace gas is transported to by reative cell by carrier gas, the gas sensing with structure in step (2)
Device array is reacted, and multiple sensor response signals then are transferred to host computer by signal acquisition module；
2) secondly, the sensing response signal of collection is analyzed by computer, passes through statistical analysis, principal component analysis
The methods of extract the response characteristic value of each gas sensor, the input variable as data model.
Discrimination model is established described in wherein described step (4), is become by input of the response characteristic value of each gas sensor
Amount structure nonlinear discriminant model, Rapid identification is carried out to dehydrated potato.
Compared with prior art, the present invention design it is a kind of based on flavor analysis potato full-powder method for quick identification with
System, is analyzed as foundation with the flavor characteristics of the potato full-powder of different processing temperatures, based on intelligent sensory technology, simulates the mankind
Smell carries out intelligent distinguishing to the dehydrated potato raw material of different processing conditions.Processing and quality of the present invention for potato full-powder
Regulation and control provide a kind of quick, lossless, accurate method, can be applied to the purchasing of raw materials of potato staple food metaplasia production, add
Multiple links such as work, storage, the quality guarantee for potato staple food product provide theoretical foundation.
Brief description of the drawings
Fig. 1 is the smell intelligent checking system schematic diagram that the present invention is built；
Fig. 2 is a kind of quick identification flow figure of potato full-powder based on flavor analysis of the present invention；
Fig. 3 is the total ion current figure that the present invention carries out potato full-powder aroma volatiles analysis；(a) 50 DEG C of drying process (b)
90 DEG C of drying process；
Fig. 4 is the training set and forecast set sample KNN discrimination models that the present invention establishes；(a) training set sample KNN differentiates mould
Type；(b) forecast set sample KNN discrimination models.
Embodiment
With reference to the accompanying drawings and examples, further detailed description is done to the embodiment of the present invention.Following reality
Apply example to be used to illustrate the present invention, but be not limited to the scope of the present invention.
Fig. 1 is the smell intelligent checking system schematic diagram that the present invention is built.As shown in Figure 1, smell intelligent checking system bag
Sensing response module, data acquisition and procession module, pattern recognition module etc. are included, hardware components include gas collecting apparatus, sensor
Array reative cell, signal pickup assembly, software section include host computer, signal processing module, pattern recognition module etc..Metal oxygen
Compound gas sensor is placed in reative cell, be respectively TGS813, TGS816, TGS822, TGS825, TGS826, TGS831,
TGS2600、TGS2610、TGS2611、TGS2620.Gas sensor array in reative cell is connected to signal by wiring and adopts
Acquisition means, then host computer is transferred to by the device, sensor response signal is handled and identified by computer.
Fig. 2 is a kind of quick identification flow figure of potato full-powder based on flavor analysis of the present invention.As shown in Fig. 2, using
The method that smell intelligent checking system differentiates potato full-powder, comprises the following steps：
1) dehydrated potato sample is prepared.Dehydrated potato is prepared with reference to the technique for preparing potato starch.It is dehydrated horse
Bell potato preparation process according to cleaning → section → color protection → drying preparation process.Drying temperature is respectively 40,50,60,70,
80、90.Dry processing is completed using hot air drier, and every kind of 15 samples of sample preparation, gather 90, sample altogether.
2) extraction of potato full-powder flavor and analysis：The dehydrated potato sample of different processing temperatures is crushed, mistake
100 mesh sieves, carry out analysis of volatile components.Every kind of sample surveys 3 parallel sampleses.Horse is collected using headspace solid-phase microextraction technology
Flavor components in the full powder of bell potato, carry out GC-MS analyses to the flavor substance of extraction, obtain potato full-powder sapidity ingredient
GC-MS total ion current figures, analyze and identify main volatile compound, as shown in Figure 3.
3) olfactory organoleptic's analysis system is built：According to the full powder flavor characteristic of dehydrated potato of GC-MS analysis gained, screening
Gas sensor is to build gas sensor array.Main volatile flavor substance includes aldehyde in potato drying process
Class, ketone, furans and alcohol derivatives etc., thus build gas sensor array, choose TGS813, TGS816, TGS822,
10 metal oxide sensors such as TGS825, TGS826, TGS831, TGS2600, TGS2610, TGS2611, TGS2620.
The parameters such as the gas collection time of smell intelligent checking system and sample size are optimized.The gas collection time is chosen first
20min, 30min, 40min, 50min, collection takes 1,2, the sample of 3 respectively under each time, compares under same the piece number not
With final detection result after gas collection time-triggered protocol.The result shows that situation is finally gathered under 30min, 40min, 50min gas collection time
Reach consistent, so selecting the 30min gas collection times under conditions of the time is optimized.Secondly sample 1 is chosen, 2,3,4,5, during gas collection
Between 30min, every part of sample does 1,2, the detection of 3 respectively, compares the different horses under 1,2, the sample size of 3 respectively
The differentiation situation of bell potato, chooses the best sample size of discrimination.The result shows that under the sample size of 1 different potatos area
Index optimal.
4) gas sensing signal collection and analysis：Using gas sensor array collection potato starch smell response letter
Number, feature extraction is carried out to air-sensitive response signal.1, sample is taken to seal (2 layers) in 100ml beakers with preservative film rapidly, put
The 30min in 22 DEG C of insulating boxs, collects sample headspace gas to collection chamber.Sample to be tested headspace gas enters under air pump effect
Reative cell, reacts with gas sensor array, and synchronous signal capture card starts to gather the response voltage value of sensor.Each
Sample reads 410 data, and acquisition time is at intervals of 1s.After having gathered sample every time, oxygen 1min need to be passed through and carry out air-sensitive biography
Sensor reduces.
5) discrimination model is established：Gas sensing array signal after collection is pre-processed, take stablize after the 370th~
Data between 400 seconds carry out principal component analysis (principal component analysis, PCA) as input quantity.With gas
The characteristic signal of quick sensor array is input variable, and the discriminating model of potato starch is established based on pattern-recognition, foundation
The results are shown in Figure 4 for KNN identification models.When number of principal components is 3, and number of nodes is 5, the differentiation rate of training set and forecast set reaches
To highest, wherein, training set Model checking rate is 91.67%, and forecast set Model checking rate is 90%.
Claims (6)
1. a kind of potato full-powder discrimination method based on flavor analysis, it is characterised in that carry out as steps described below：
(1) extraction of potato full-powder flavor and analysis：Using solid phase micro-extraction technique extract potato starch in flavor into
Point, GC-MS analyses are carried out to the flavor substance of extraction, obtain the GC-MS total ion current figures of potato starch sapidity ingredient, it is right
Main volatile compound is analyzed and identified；
(2) olfactory organoleptic's analysis system is built：According to the potato full-powder volatile ingredient feature of GC-MS analysis gained, screening
Gas sensor carries out the parameters such as the gas collection time of smell intelligent checking system and sample size with building gas sensor array
Optimization；
(3) gas sensing signal collection and analysis：Dehydrated potato smell response signal is gathered using gas sensor array, it is right
Air-sensitive response signal carries out feature extraction；
(4) discrimination model is established：Using the characteristic signal of gas sensing array as input variable, dehydration horse is established based on pattern-recognition
The discriminating model of bell potato.
2. a kind of potato full-powder discrimination method based on flavor analysis according to claim 1, it is characterised in that wherein
The step (1) carries out potato full-powder aroma volatiles analysis as steps described below：
1) the potato full-powder sample sapidity ingredient of multiple drying temperature gradients (50~90 DEG C) is surveyed respectively using GC-MS
It is fixed, obtain total ion current figure；
2) from the total ion current figure of step 1) potato full-powder sample the larger shared peak of proof strength as characteristic fingerprint peak,
Using standard finger-print as reference fingerprint, the relative peak area at characteristic fingerprint peak is calculated；
3) identify that three kinds of modes carry out unknownization by using NIST library searchings, the contrast of linear retention index and n-compound
The identification of compound；Using NIST library searchings, when compound positive match degree >=800 retrieved are optimal.
3. a kind of potato full-powder discrimination method based on flavor analysis according to claim 1, it is characterised in that wherein
Smell sensors array described in the step (2) is made of multiple gas sensors, mainly according to GC-MS in step (1) points
The potato full-powder sapidity ingredient of gained is analysed, some gold to match with potato full-powder main flavor component are obtained by screening
Belong to Oxide Gas Sensors.
4. a kind of potato full-powder discrimination method based on flavor analysis according to claim 1, it is characterised in that wherein
Being optimized to parameters such as the gas collection time of smell intelligent checking system and sample sizes described in the step (2), chooses different
Gas collection time and sample size carry out signal contrast analysis, and it is 30min, sample size 2g to determine the optimal gas collection time.
5. a kind of potato full-powder discrimination method based on flavor analysis according to claim 1, it is characterised in that wherein
Gas sensing signal collection and analysis described in the step (3), carries out as steps described below：
1) dehydrated potato headspace gas is transported to by reative cell by carrier gas, the gas sensor battle array with structure in step (2)
Row are reacted, and multiple sensor response signals then are transferred to host computer by signal acquisition module；
2) secondly, the sensing response signal of collection is analyzed by computer, passes through the side such as statistical analysis, principal component analysis
Method extracts the response characteristic value of each gas sensor, the input variable as data model.
6. a kind of potato full-powder discrimination method based on flavor analysis according to claim 1, it is characterised in that wherein
Discrimination model is established described in the step (4), is built using the response characteristic value of each gas sensor as input variable non-linear
Discrimination model, Rapid identification is carried out to dehydrated potato.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711005432.1A CN107991396A (en) | 2017-10-25 | 2017-10-25 | A kind of potato full-powder method for quick identification based on flavor analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711005432.1A CN107991396A (en) | 2017-10-25 | 2017-10-25 | A kind of potato full-powder method for quick identification based on flavor analysis |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107991396A true CN107991396A (en) | 2018-05-04 |
Family
ID=62030009
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711005432.1A Pending CN107991396A (en) | 2017-10-25 | 2017-10-25 | A kind of potato full-powder method for quick identification based on flavor analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107991396A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109724645A (en) * | 2019-01-07 | 2019-05-07 | 江苏大学 | A kind of portable electric nose system of real-time monitoring gold ear fermentation process state |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1453584A (en) * | 2003-06-02 | 2003-11-05 | 江苏大学 | Fast non-destructive detection method and device of food smell based on gas sensor array technology |
| CN103063813A (en) * | 2012-12-26 | 2013-04-24 | 江苏大学 | Rapid nondestructive on-line detection method and apparatus for freshness of fishes |
| CN103399092A (en) * | 2013-07-15 | 2013-11-20 | 浙江大学 | Method for rapidly evaluating quality of ginseng |
| CN104316660A (en) * | 2014-10-27 | 2015-01-28 | 四川省农业科学院农产品加工研究所 | Method for rapidly detecting flavor and grade of thick broad-bean sauce and product tracing |
-
2017
- 2017-10-25 CN CN201711005432.1A patent/CN107991396A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1453584A (en) * | 2003-06-02 | 2003-11-05 | 江苏大学 | Fast non-destructive detection method and device of food smell based on gas sensor array technology |
| CN103063813A (en) * | 2012-12-26 | 2013-04-24 | 江苏大学 | Rapid nondestructive on-line detection method and apparatus for freshness of fishes |
| CN103399092A (en) * | 2013-07-15 | 2013-11-20 | 浙江大学 | Method for rapidly evaluating quality of ginseng |
| CN104316660A (en) * | 2014-10-27 | 2015-01-28 | 四川省农业科学院农产品加工研究所 | Method for rapidly detecting flavor and grade of thick broad-bean sauce and product tracing |
Non-Patent Citations (1)
| Title |
|---|
| 黄星奕等: "针对鳊鱼新鲜度的气敏传感器筛选与阵列构建", 《食品工业科技》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109724645A (en) * | 2019-01-07 | 2019-05-07 | 江苏大学 | A kind of portable electric nose system of real-time monitoring gold ear fermentation process state |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101881726B (en) | Nondestructive detection method for comprehensive character living bodies of plant seedlings | |
| CN103134850B (en) | A kind of tea leaf quality method for quick based on characteristic perfume | |
| CN103235087B (en) | A kind of discrimination method of the oolong tea original producton location based on sense of smell and taste sensor information fusion | |
| CN101975845A (en) | Automatic detecting system for quality of traditional Chinese medicines | |
| Yuan et al. | Selecting key wavelengths of hyperspectral imagine for nondestructive classification of moldy peanuts using ensemble classifier | |
| Wang et al. | Multivariate statistical analysis combined with e-nose and e-tongue assays simplifies the tracing of geographical origins of Lycium ruthenicum Murray grown in China | |
| CN105954412B (en) | For the sensor array optimization method of hickory nut freshness detection | |
| CN107515203A (en) | The research of near infrared technology quantitative analysis rice single grain amylose content | |
| CN112949984B (en) | Multi-dimensional fusion identification method for fermentation degree of Meixiang fish based on smell visualization | |
| CN103196954B (en) | A kind of zhenjiang vinegar storage time discrimination method based on sense of smell and taste sensor information fusion | |
| CN108195895A (en) | A kind of tea leaf nitrogen content rapid detection method based on electronic nose and spectrophotometric color measurement instrument | |
| CN104807777A (en) | Rapid detection method for areca-nut water content based on near infrared spectrum analysis technology | |
| Chen et al. | Fast detection of cumin and fennel using NIR spectroscopy combined with deep learning algorithms | |
| CN104111274A (en) | Method for identifying producing area of red bayberry juice by using gas sensor array type electronic nose fingerprint analysis system | |
| CN106226267B (en) | A kind of near-infrared assay method of dry chili color value | |
| CN105181761A (en) | Method for rapidly identifying irradiation absorbed dose of tea by using electronic nose | |
| CN107991396A (en) | A kind of potato full-powder method for quick identification based on flavor analysis | |
| CN101231276A (en) | Method for detecting evaporated fat former milk | |
| CN110887921B (en) | Method for efficiently and rapidly analyzing characteristic volatile components of eucommia leaves and fermentation product thereof | |
| Lelono et al. | Comparison of difference, relative and fractional methods for classification of the black tea based on electronic nose | |
| Jana et al. | Classification of aromatic and non-aromatic rice using electronic nose and artificial neural network | |
| Wang et al. | The recognition of different odor using convolutional neural networks extracted from time and temperature features | |
| Liu et al. | Colorimetric sensor array combined with chemometric methods for the assessment of aroma produced during the drying of tencha | |
| Zang et al. | Real‐time detection system for moisture content and color change in jujube slices during drying process | |
| AU2021104058A4 (en) | Analysis Method of Nutritional Quality of Pleurotus Ostreatus |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180504 |