CN105973840A - Method for quickly detecting fermented grain physicochemical indexes of Maotai-flavor liquor - Google Patents
Method for quickly detecting fermented grain physicochemical indexes of Maotai-flavor liquor Download PDFInfo
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- CN105973840A CN105973840A CN201610606417.1A CN201610606417A CN105973840A CN 105973840 A CN105973840 A CN 105973840A CN 201610606417 A CN201610606417 A CN 201610606417A CN 105973840 A CN105973840 A CN 105973840A
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- fermented grain
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- chemical index
- maotai
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- 239000000796 flavoring agent Substances 0.000 title claims abstract description 59
- 238000000034 method Methods 0.000 title claims abstract description 44
- 238000001514 detection method Methods 0.000 claims abstract description 24
- 229920002472 Starch Polymers 0.000 claims abstract description 23
- 235000019698 starch Nutrition 0.000 claims abstract description 23
- 239000008107 starch Substances 0.000 claims abstract description 23
- 239000000126 substance Substances 0.000 claims description 134
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 34
- 230000003595 spectral effect Effects 0.000 claims description 26
- 238000004458 analytical method Methods 0.000 claims description 24
- 238000012795 verification Methods 0.000 claims description 24
- 238000005259 measurement Methods 0.000 claims description 22
- 238000001228 spectrum Methods 0.000 claims description 19
- 239000000203 mixture Substances 0.000 claims description 17
- 238000003556 assay Methods 0.000 claims description 10
- 238000002329 infrared spectrum Methods 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 9
- 230000008859 change Effects 0.000 claims description 8
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 claims description 6
- 238000005070 sampling Methods 0.000 claims description 6
- 230000005856 abnormality Effects 0.000 claims description 4
- 239000001569 carbon dioxide Substances 0.000 claims description 3
- 229910002092 carbon dioxide Inorganic materials 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 abstract description 20
- 239000000243 solution Substances 0.000 description 56
- HEMHJVSKTPXQMS-UHFFFAOYSA-M Sodium hydroxide Chemical compound [OH-].[Na+] HEMHJVSKTPXQMS-UHFFFAOYSA-M 0.000 description 36
- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 description 34
- 239000008103 glucose Substances 0.000 description 34
- 239000007788 liquid Substances 0.000 description 18
- 239000000706 filtrate Substances 0.000 description 12
- 238000004448 titration Methods 0.000 description 10
- 238000009835 boiling Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 8
- 230000008034 disappearance Effects 0.000 description 8
- 235000015096 spirit Nutrition 0.000 description 7
- VEXZGXHMUGYJMC-UHFFFAOYSA-N Hydrochloric acid Chemical compound Cl VEXZGXHMUGYJMC-UHFFFAOYSA-N 0.000 description 6
- 238000002512 chemotherapy Methods 0.000 description 6
- 238000012937 correction Methods 0.000 description 6
- 238000001704 evaporation Methods 0.000 description 6
- 238000012360 testing method Methods 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 5
- RBTBFTRPCNLSDE-UHFFFAOYSA-N 3,7-bis(dimethylamino)phenothiazin-5-ium Chemical compound C1=CC(N(C)C)=CC2=[S+]C3=CC(N(C)C)=CC=C3N=C21 RBTBFTRPCNLSDE-UHFFFAOYSA-N 0.000 description 4
- 229920000742 Cotton Polymers 0.000 description 4
- 241001411320 Eriogonum inflatum Species 0.000 description 4
- GZCGUPFRVQAUEE-SLPGGIOYSA-N aldehydo-D-glucose Chemical compound OC[C@@H](O)[C@@H](O)[C@H](O)[C@@H](O)C=O GZCGUPFRVQAUEE-SLPGGIOYSA-N 0.000 description 4
- 229910000365 copper sulfate Inorganic materials 0.000 description 4
- ARUVKPQLZAKDPS-UHFFFAOYSA-L copper(II) sulfate Chemical compound [Cu+2].[O-][S+2]([O-])([O-])[O-] ARUVKPQLZAKDPS-UHFFFAOYSA-L 0.000 description 4
- JZCCFEFSEZPSOG-UHFFFAOYSA-L copper(II) sulfate pentahydrate Chemical compound O.O.O.O.O.[Cu+2].[O-]S([O-])(=O)=O JZCCFEFSEZPSOG-UHFFFAOYSA-L 0.000 description 4
- 238000009826 distribution Methods 0.000 description 4
- 229960000907 methylthioninium chloride Drugs 0.000 description 4
- KJFMBFZCATUALV-UHFFFAOYSA-N phenolphthalein Chemical compound C1=CC(O)=CC=C1C1(C=2C=CC(O)=CC=2)C2=CC=CC=C2C(=O)O1 KJFMBFZCATUALV-UHFFFAOYSA-N 0.000 description 4
- 239000012086 standard solution Substances 0.000 description 4
- 238000003756 stirring Methods 0.000 description 4
- 239000003795 chemical substances by application Substances 0.000 description 3
- 235000019634 flavors Nutrition 0.000 description 3
- 239000000463 material Substances 0.000 description 3
- 238000002156 mixing Methods 0.000 description 3
- CWYNVVGOOAEACU-UHFFFAOYSA-N Fe2+ Chemical compound [Fe+2] CWYNVVGOOAEACU-UHFFFAOYSA-N 0.000 description 2
- ZLMJMSJWJFRBEC-UHFFFAOYSA-N Potassium Chemical compound [K] ZLMJMSJWJFRBEC-UHFFFAOYSA-N 0.000 description 2
- 235000009392 Vitis Nutrition 0.000 description 2
- 241000219095 Vitis Species 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 2
- 239000002671 adjuvant Substances 0.000 description 2
- 239000007864 aqueous solution Substances 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000001816 cooling Methods 0.000 description 2
- 238000004090 dissolution Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000000855 fermentation Methods 0.000 description 2
- 230000004151 fermentation Effects 0.000 description 2
- 238000001914 filtration Methods 0.000 description 2
- 235000011389 fruit/vegetable juice Nutrition 0.000 description 2
- JMANVNJQNLATNU-UHFFFAOYSA-N glycolonitrile Natural products N#CC#N JMANVNJQNLATNU-UHFFFAOYSA-N 0.000 description 2
- 238000009499 grossing Methods 0.000 description 2
- 238000010438 heat treatment Methods 0.000 description 2
- XEEYBQQBJWHFJM-UHFFFAOYSA-N iron Substances [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
- 238000003333 near-infrared imaging Methods 0.000 description 2
- 229910052700 potassium Inorganic materials 0.000 description 2
- 239000011591 potassium Substances 0.000 description 2
- VZOPRCCTKLAGPN-ZFJVMAEJSA-L potassium;sodium;(2r,3r)-2,3-dihydroxybutanedioate;tetrahydrate Chemical compound O.O.O.O.[Na+].[K+].[O-]C(=O)[C@H](O)[C@@H](O)C([O-])=O VZOPRCCTKLAGPN-ZFJVMAEJSA-L 0.000 description 2
- 238000002360 preparation method Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 239000000047 product Substances 0.000 description 2
- 239000002893 slag Substances 0.000 description 2
- 229940074446 sodium potassium tartrate tetrahydrate Drugs 0.000 description 2
- 238000005406 washing Methods 0.000 description 2
- 238000013396 workstream Methods 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 125000003118 aryl group Chemical group 0.000 description 1
- 238000013124 brewing process Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000004821 distillation Methods 0.000 description 1
- 239000004615 ingredient Substances 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 235000020068 maotai Nutrition 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 238000002203 pretreatment Methods 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 239000011265 semifinished product Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
Abstract
The invention provides a method for quickly detecting fermented grain physicochemical indexes of Maotai-flavor liquor. The method for quickly detecting the fermented grain physicochemical indexes of the Maotai-flavor liquor is simple and convenient. Pool outlet fermented grain sample sets and pool inlet fermented grain sample sets of seven turns of the Maotai-flavor liquor are measured, fourteen sets of fermented grain physicochemical index calibration models of the Maotai-flavor liquor are obtained, and accurate forecast can be quickly carried out on Maotai-flavor pool outlet fermented grain characters or pool inlet fermented grain characters. The set of near-infrared quick detection method suitable for physicochemical indexes such as moisture, acidity, residual sugar and starch of seven turns of pool outlet fermented grains and pool inlet fermented grains in the production of the Maotai-flavor liquor is established, and unknown samples can be accurately detected according to the different characters of the samples through the calibration models. The invention further discloses a near-infrared quick detection method for residual sugar indexes in cellar outlet fermented grains and cellar inlet fermented grains of the Maotai-flavor liquor.
Description
Technical field
The present invention relates to Maotai-flavor liquor and analyze detection field, quickly detect Maotai-flavor wine brewing in particular to one
The method of fermented grain physical and chemical index.
Background technology
The production technology of paste flavor wine is the most special, is different from Production of Luzhou-flavor Liquor technique, and what it was peculiar brewages work
Skill, i.e. " throw for twice grain, eight take turns add koji fermentation, take wine seven times " and the brewing method of " four high two is long " and the blending and tasting skill of exquisiteness
Art, creates the paste flavor style that wine body is special.Just because of Maotai-flavor liquor produces " taking wine seven times ", so production in 1 year
Cycle just has 7 times opens cellar for storing things and 7 envelope cellar for storing things techniques, and each pit has 7 times go out pond and enter the process in pond for 7 times.In order to accurately slap
Hold production ingredient information the most appropriate rationally, need the reason indexs such as the moisture of pond fermented grain, acidity, residual sugar, starch that come in and go out are carried out
Fractional analysis, it is simple to sum up a production round adjuvant collocation and the most appropriately and adjust this production round auxiliary material proportion.
In prior art, the going out pond fermented grain and enter the reason indexing analysis such as pond fermented grain moisture, acidity, residual sugar, starch of the same day
Data take second day could report result, and brew house is production of working continuously, it is impossible to the assays such as stopping production are out allocated
Produce again after ratio of adjuvant, there is time-consuming length, the shortcoming that the same day, this pond produced can not be instructed in time, cause analysis number
According to serious hysteresis, quality problems are not prevented the control action of essence.
Near infrared technology is that the one that the sixties in 20th century occurs, the later stage eighties develops rapidly is quick, easy, green
The composition detection technology of color.Near-infrared spectrum technique may be used with nearly all sample physico-chemical properties relevant with hydric group and divides
Analysis, and only require few sample pretreatment or be not required to pretreatment and be directly analyzed, so considerably reduce artificial by mistake
Difference, makes analysis result the most accurately and reliably.This kind of technology has many good qualities simultaneously, and it can be in tens seconds or a few minutes, only
The collection being completed a near infrared spectrum by sample is measured, and can complete the mensuration of its multinomial performance index.Spectrum is surveyed
Need not during amount analysis sample is carried out pre-treatment；Do not consume other material during analysis or destroy sample；Analyze repeatability
Good, pollution-free, convenient and swift；Multicomponent detects simultaneously, finding speed is fast, investment and operating cost are low after modeling.
It addition, process for brewing white liquor of Maotai flavor is different from other aromatic white spirit technique, the production having seven rounds in 1 year, and
There is bigger difference in each round discrepancy pond wine fermented grain physical and chemical index, if in this way Maotai-flavor liquor is brewageed seven
One group of near infrared band spectral information of composition such as the discrepancy pond fermented grain moisture of round, acidity, residual sugar, starch is set up fermented grain physics and chemistry and is referred to
Mark calibration model, is subsequently used for the detection of unknown sample, and the actually detected data obtained are deposited with national standard chemistry assay method
In larger difference.By facts have proved in a large number and repeatedly: art methods cannot be directly used to Maotai-flavor wine brewing produce in 7
The physical and chemical index detection of individual production round fermented grain；Prior art does not have yet near-infrared quickly detect the tool of residual sugar index in fermented grain
Body detecting method and near-infrared analysis model.
In view of this, the special proposition present invention.
Summary of the invention
The method that it is an object of the invention to provide a kind of quick detection Maotai-flavor wine brewing fermented grain physical and chemical index, described is fast
Speed detection Maotai-flavor wine brewing fermented grain physical and chemical index method simple and convenient, can Maotai-flavor fermented grain physical and chemical index be carried out rapid pin
Accurate Prediction.
In order to realize the above-mentioned purpose of the present invention, spy by the following technical solutions:
The method of a kind of quick detection Maotai-flavor wine brewing fermented grain physical and chemical index, comprises the steps:
Step one: set up Maotai-flavor wine brewing fermented grain physical and chemical index calibration model；
Take going out pond and entering pond fermented grain sample composition for the 14 of modeling of Maotai-flavor seven each rounds of round of wine brewing respectively
Individual sample sets (includes pond fermented grain 7 groups, enter pond fermented grain 7 groups)；Measure the reddest respectively for fermented grain sample each in fermented grain sample sets
Outer wave band spectral information, obtains 14 groups of near infrared band spectral informations；Each sample in 14 groups of fermented grain sample sets is measured it respectively
Physical and chemical index chemical measurements, obtains 14 groups of physical and chemical index chemical measurements；
By near infrared band spectral information and the physical and chemical index chemical measurements one_to_one corresponding of all samples in 14 groups, adopt
Set up fermented grain physics and chemistry refer to one group of near infrared band spectral information and one group of physical and chemical index chemical measurements with corresponding relation
Mark calibration model, there are 14 groups of Maotai-flavor wine brewing fermented grain physical and chemical index calibration models；
Step 2: verify described fermented grain physical and chemical index calibration model；
Compare with unknown sample actual analysis result and forecast analysis, it is judged that whether model can be used；
Step 3: the detection of fermented grain sample to be measured；
Fermented grain sample to be measured is carried out near infrared spectrum scanning, it is thus achieved that the near infrared band spectrum letter of fermented grain sample to be measured
Breath, recycles described Maotai-flavor wine brewing fermented grain physical and chemical index calibration model and obtains the reason of described fermented grain to be measured by the way of prediction
Change index.
The method that the present invention quickly detects Maotai-flavor wine brewing fermented grain physical and chemical index is simple and convenient, respectively to Maotai-flavor wine brewing seven
Going out pond and entering pond fermented grain sample sets and be measured of each round of individual round, obtains 14 groups of Maotai-flavors wine brewing fermented grain physical and chemical indexs fixed
Mark model, it is possible to rapid pin goes out pond or enters pond fermented grain characteristic and carry out Accurate Prediction different round Maotai-flavors.
Preferably, use there is one group of near infrared band spectral information of corresponding relation and one group of physical and chemical index chemical assay
Value, utilizes near-infrared chemo metric software to set up fermented grain physical and chemical index calibration model.
Preferably, the described condition setting up fermented grain physical and chemical index calibration model includes:
(1) stoechiometric process is selected；
(2) modeling pretreatment；
(3) foundation of calibration model and the verification of calibration model；
(4) rejecting abnormalities sample；
(5) main composition is screened；
(6) select to obtain the light path near infrared band spectral information.
Preferably, described stoechiometric process includes that PLS (PLS) method, main composition return in (PCR) method
One or both.
Preferably, described modeling pretreatment include standard normalized, multiplicative scatter correction, standard normalization correction,
One or more in the change of second derivative correction baseline tilt and smoothing processing.
Preferably, the verification mode of calibration model takes individual authentication collection validation-cross pattern, carries out according to reference concentration
Sequence, selects forecast set sample and calibration set sample in proportion, more preferably by 10:1 ratio select forecast set sample and
Calibration set sample.
Preferably, described rejecting abnormalities sample is to reject tentative abnormal sample to be modeled calculating, then reclaims one by one
Calculate.If after reclaiming a certain sample, model performance is not deteriorated, then retain, otherwise then reject.
Preferably, the selection of main composition can use the predictive ability of model as criterion, is stepped up (or minimizing) main
The number of composition, then calculates the change forecast error whether checking is collected by appreciable impact model of main composition number.
Preferably, described light path includes one or more in constant, MSC and SNV.
Preferably, verify described fermented grain physical and chemical index calibration model to comprise the steps:
(1) sampling has neither part nor lot in the representative verification fermented grain sample of modeling；
(2) gather the acquisition verification near infrared band spectral information of fermented grain sample, and obtain described verification fermented grain sample
The physical and chemical index chemical measurements of product；
(3) according to the near infrared band spectral information of described verification fermented grain sample, the wine that described step one obtains is utilized
Unstrained spirits physical and chemical index calibration model obtains the physical and chemical index predictive value of described verification fermented grain sample；
(4) physical and chemical index chemical measurements and the physical and chemical index predictive value of described verification fermented grain sample are compared, if deviation
In set point, the most described fermented grain physical and chemical index calibration model is available；If deviation exceedes set point, then by verification wine
The fermented grain sample sets for modeling included in by unstrained spirits sample, and adjusts repetition step one and step 2 after modeling conditions, until described wine
Unstrained spirits physical and chemical index calibration model is available.
Preferably, described near infrared band spectrum is averaged spectrum, utilizes software process quality averaged spectrum to reduce sample not
The interference that absolute uniform and dress sample difference are brought, improves accuracy of measurement.
Preferably, the collection to described near infrared band spectrum uses rotary sample cup, integrating sphere diffuse-reflectance detecting system
Scanning obtains.
Described rotary sample cup is preferably 5cm rotary sample cup；Preferably scan 64 by integrating sphere diffuse-reflectance detecting system
More than secondary, preferably 64 times, gather and obtain near infrared band spectrum.
Preferably, the scan mode using continuous wavelength infrared diaphanoscopy obtains described near infrared band spectrum.
Preferably, one or more during described physical and chemical index includes moisture content, acidity, residual sugar and starch.
Preferably, after described step 3, step 4 is also included: optimize and more new model；Base at original forecast model
On plinth, the more new model when increasing a new batch (7 rounds were produced as a batch in 1 year) data, utilize new lot data to enter
The sample that row is analyzed, increases model data amount and new sample characteristics of for example, thus optimizes budget model, its sample sets gradient number abundant
According to, with more adapt to new lot unknown sample analyze, make model possess more excellent gradient and more dense distributed points, possess more accurate
Budgeted capacity.
Maotai-flavor wine brewing produces and belongs to opening production, within annual 12 months, is a production cycle, and each cycle is one batch
Secondary production, because wine brewing process is affected by various factors such as ambient temperature, weather, raw material variety, water quality, steam, produces every year
There is slight difference in the semi-finished product wine gone out, the foundation of model of the present invention preferably strengthens model by being continuously increased new lot data
Data volume and new sample characteristics of for example, thus optimize budget model, its sample sets gradient data abundant, with more adapt to new lot
Unknown sample is analyzed, and makes model possess more excellent gradient and more dense distributed points, possesses more accurate budgeted capacity.
Preferably, it is thus achieved that the condition set by near infrared light spectrogram includes:
(1) detector light source is 15000-20000cm-1Light source.
(2) wavelength band obtained near infrared band spectral information is 10000-4000cm-1；
(3) impact of water in background deduction noise, carbon dioxide and air；
(4) fermented grain spectrogram capture setting is 16cm-1；
(5) sample cup, sampling amount is 80g；
(6) scan mode is rotator rotating acquisition 64 times.
Preferably, physical and chemical index chemical measurements uses standard chemical assay method to be measured.
Preferably, described standard chemical assay method is carried out as follows:
1. moisture:
Weigh 10.00g fermented grain in the clean evaporating dish of known quality, shakeout, put into warmed up to 135 ± 1 DEG C baking ovens
In be dried 1 hour, take out, in exsiccator cool down half an hour, weigh.
In formula: m1Sample and evaporating dish quality, g before being dried；
m2Dried sample and evaporating dish quality, g.
2. acidity:
Weigh 10.00g fermented grain in 250mL beaker, add 100.00mL water, stir evenly, be at room temperature standing and soak for 30 clocks, in
Between every 15 minutes stirring once.Filter with absorbent cotton, access filtrate with 250mL triangular flask, discard just filtrate about 20mL, connect
Take filtrate standby.Absorption 10.00mL filtrate, in 250mL triangular flask, adds 20mL water, adds 2 1% phenolphthalein instructions after shaking up
Agent, being titrated to solution with the standard solution of sodium hydroxide of 0.1moL/L is that blush does not takes off for 30 seconds, and record sodium hydroxide standard is molten
Liquid consumption.Result represents and is calculated as follows:
Result is to represent containing a sour mM number in 10 grams of fermented grains:
Acidity (mmolH+/ 10g)=100/10nv==10nv
In formula: n Concentration of Sodium Hydroxide Solution Standard, moL/L；
V titration consumes standard solution of sodium hydroxide volume, mL.
3. residual sugar:
Weigh 75.00g copper sulfate (CuSO4.5H2O), 0.250g methylene blue indicator soluble in water, and be diluted to
5000.00mL。
Solution A: weigh 75.00g copper sulfate (CuSO4.5H2O), 0.250g methylene blue indicator soluble in water, and dilute
To 5000.00mL.
Second liquid: weigh 250.00g sodium potassium tartrate tetrahydrate (KNaC4H4O6.4H2O), 270g sodium hydroxide and 40.00g ferrous iron cyanogen
Change potassium [K4Fe(CN)6·3H2O] soluble in water and dilute as 5000.00mL.
Face the used time, above-mentioned two solution are respectively taken 5.00mL mixing.
0.1% (m/v) Glucose standards solution
Accurately weigh the pure glucose of cooling after 5.0000g fermented grain is dried 2 hours in 103～105 DEG C of baking ovens, use water dissolution
Rear addition 25mL hydrochloric acid, adds water and is settled to 5000.00mL.
Pre-titration: drawing the micromethod Fei Linshi solution each 5.00mL of first, second liquid, (conical flask is with striking to insert 150mL conical flask
Conical flask used during Lin Shi standardization of solution is the identical lot number of same manufacturer production) in, add water 10mL, adds appropriate preparation
Good sample, shakes up.Put and heat on electric furnace, control to seethe with excitement in 2 minutes, and keep micro-boiling 2 minutes, use under fluidized state
0.1% (m/v) Standard glucose solution be titrated to blue disappearance with the speed of 1 per second and in light yellow, record standard Fructus Vitis viniferae
Sugar liquid consumption.
Formal titration: drawing the micromethod Fei Linshi solution each 5mL of first, second liquid, (conical flask is with striking to insert 150mL conical flask
Conical flask used during Lin Shi standardization of solution is the identical lot number of same manufacturer production) in, add water 10mL, adds and titrates in advance
The sample of the same volume added, adds the pre-0.1% Glucose standards solution titrating few 1mL of ratio, shakes up.Add on electric furnace
Heat was seethed with excitement in 2 minutes, and kept seething with excitement 2 minutes.With 0.1% (m/v) Standard glucose solution with 1 per second under fluidized state
Speed be titrated to blue disappearance and in light yellow, record standard Glucose Liquid total amount consumed v2mL。
Calculate:
Residual sugar (with glucose meter, %)={ [(v1-v2)×c/[10.00×(v3/100)]}×100
In formula: v1Quota of expenditure glucose solution volume, mL in Fei Linshi standardization of solution；
v2Sample formally titrate in quota of expenditure glucose solution volume, mL；
C Standard glucose solution concentration, g/mL；
v3Sample titrates in advance or formally titrates the volume of sample of addition, mL；
10.00 sample mass, g；
100 samples prepare volume, mL.
4. starch:
Accurately weigh 5.00g sample, be placed in 250mL conical flask, add 60mL (1+4) HCl solution, be shaken gently for taper
Bottle, makes sample be sufficiently humidified so as to.Bottleneck loads onto bottle stopper, and on bottle stopper, band is about the glass-tube of 1 meter, puts and boils on electric furnace, micro-boiling 30 minutes
After, take out, cool down with flowing water.Filtering with absorbent cotton, filtrate receives with 500mL volumetric flask, fully washs conical flask and residual with water
Slag, washing liquid is all filtered in volumetric flask, is diluted with water to scale, shakes up.Then with pipette, extract 50mL hydrolyzed solution in 100mL
In volumetric flask, neutralize with 20% sodium hydroxide solution, test with accurate pH test paper, make the pH value of aqueous solution be about 7, finally add water
To scale, shake up.
Pre-titration: drawing the micromethod Fei Linshi solution each 5mL of first, second liquid, insert in 150mL conical flask, add water 10mL, then
Add the sample prepared in right amount, shake up.Put and heat on electric furnace, control to seethe with excitement in 2 minutes, and keep micro-boiling 2 minutes, in boiling
Rise be titrated to blue disappearance with 0.1% (m/v) Standard glucose solution with the speed of 1 per second under state and in light yellow, note
Record standard glucose sugar liquid consumption.
Formal titration: drawing the micromethod Fei Linshi solution each 5mL of first, second liquid, insert in 250mL conical flask, add water 10mL,
The sample of the same volume added and titrate addition in advance, adds the pre-0.1% Glucose standards solution titrating few 1mL of ratio,
Shake up.Seethe with excitement in heating 2 minutes on electric furnace, and keep seething with excitement 2 minutes.With 0.1% (m/v) standard glucose under fluidized state
Sugar juice be titrated to blue disappearance with the speed of 1 per second and in light yellow, record standard Glucose Liquid total amount consumed v2mL。
In formula: v1Quota of expenditure glucose solution volume, mL in Fei Linshi standardization of solution；
v2Sample formally titrate in quota of expenditure glucose solution volume, mL；
C Standard glucose solution concentration, g/mL.
5.00 sample masses, g；
50/500 draws 50mL from 500mL filtrate puts in 100mL volumetric flask and rear constant volume；
v3Sample titrates in advance or formally titrates the volume of sample of addition, mL；
0.9 glucose is scaled the coefficient of starch.
Compared with prior art, the invention have the benefit that
The method that the present invention quickly detects Maotai-flavor wine brewing fermented grain physical and chemical index is simple and convenient, respectively to Maotai-flavor wine brewing seven
Going out pond and entering pond fermented grain sample sets and be measured of each round of individual round, obtains 14 groups of Maotai-flavors wine brewing fermented grain physical and chemical indexs fixed
Mark model, it is possible to rapid pin goes out pond or enters pond fermented grain characteristic and carry out Accurate Prediction different round Maotai-flavors.The present invention establishes
A set of it be suitable for seven rounds during Maotai-flavor wine brewing produces and go out pond and enter the physics and chemistry such as the moisture of pond fermented grain, acidity, residual sugar, starch and refer to
Target near-infrared method for quick, and unknown sample can accurately be detected with calibration model according to the different qualities of sample.This
Invention also add Maotai-flavor liquor and goes out cellar for storing things and enter to store the near-infrared method for quick of residual sugar index in fermented grain.
Accompanying drawing explanation
In order to be illustrated more clearly that the specific embodiment of the invention or technical scheme of the prior art, below will be to specifically
In embodiment or description of the prior art, the required accompanying drawing used is briefly described, it should be apparent that, in describing below
Accompanying drawing is some embodiments of the present invention, for those of ordinary skill in the art, before not paying creative work
Put, it is also possible to obtain other accompanying drawing according to these accompanying drawings.
Fig. 1 is that the embodiment of the present invention 1 fourth round time goes out pond fermented grain sample near infrared light spectrogram；
Fig. 2 is that the embodiment of the present invention 1 fourth round time goes out pond fermented grain sample moisture calibration model line diagram；
Fig. 3 is that the embodiment of the present invention 1 fourth round time goes out pond fermented grain sample acidity calibration model line diagram；
Fig. 4 is that the embodiment of the present invention 1 fourth round time goes out pond fermented grain sample residual sugar calibration model line diagram；
Fig. 5 is that the embodiment of the present invention 1 fourth round time goes out pond fermented grain sample starch calibration model line diagram；
Fig. 6 is that the embodiment of the present invention 2 fourth round time enters pond fermented grain sample near infrared light spectrogram；
Fig. 7 is that the embodiment of the present invention 2 fourth round time enters pond fermented grain sample moisture calibration model line diagram；
Fig. 8 is that the embodiment of the present invention 2 fourth round time enters pond fermented grain sample acidity calibration model line diagram；
Fig. 9 is that the embodiment of the present invention 2 fourth round time enters pond fermented grain sample residual sugar calibration model line diagram；
Figure 10 is that the embodiment of the present invention 2 fourth round time enters pond fermented grain sample starch calibration model line diagram.
Detailed description of the invention
Below in conjunction with the drawings and specific embodiments, technical scheme is clearly and completely described, but
It is to it will be understood to those of skill in the art that following described embodiment is a part of embodiment of the present invention rather than whole
Embodiment, is merely to illustrate the present invention, and is not construed as limiting the scope of the present invention.Based on the embodiment in the present invention, ability
The every other embodiment that territory those of ordinary skill is obtained under not making creative work premise, broadly falls into the present invention and protects
The scope protected.Unreceipted actual conditions person in embodiment, the condition advised according to normal condition or manufacturer is carried out.Agents useful for same
Or instrument unreceipted production firm person, being can be by the commercially available conventional products bought and obtain.
The method that the invention provides a kind of quick detection Maotai-flavor wine brewing fermented grain physical and chemical index, comprises the steps:
Step one: set up Maotai-flavor wine brewing fermented grain physical and chemical index calibration model；
Take going out pond and/or entering the pond fermented grain sample composition sample sets for modeling of the required round of Maotai-flavor wine brewing；For
In fermented grain sample sets, each fermented grain sample measures near infrared band spectral information respectively, obtains near infrared band spectral information；To wine
In unstrained spirits sample sets, each sample measures its physical and chemical index chemical measurements respectively, obtains physical and chemical index chemical measurements；
By near infrared band spectral information and the physical and chemical index chemical measurements one_to_one corresponding of all samples, it is right that employing has
The one group of near infrared band spectral information that should be related to and one group of physical and chemical index chemical measurements, utilize near-infrared Chemical Measurement soft
Part sets up fermented grain physical and chemical index calibration model；
The described condition setting up fermented grain physical and chemical index calibration model includes:
(1) selecting stoechiometric process is PLS (PLS) method or main composition recurrence (PCR) method；
(2) standard normalized, multiplicative scatter correction, standard normal correction, second derivative correction baseline is used to incline
Tiltedly change or smoothing processing are modeled pretreatment；
(3) foundation of calibration model and the verification of calibration model, take individual authentication collection validation-cross pattern, according to reference
Concentration is ranked up, and selects forecast set sample and calibration set sample in 10:1 ratio；
(4) rejecting abnormalities sample, rejects tentative abnormal sample and is modeled calculating, then reclaim calculating one by one；If returning
After receiving a certain sample, model performance is not deteriorated, then retain, otherwise then rejects；
(5) main composition (including) is screened, the selection of main composition can use the predictive ability of model as criterion,
Being stepped up the number of (or reduce) main composition, whether appreciable impact model is to checking collection then to calculate the change of main composition number
Forecast error；
(6) select to obtain the light path (including constant, MSC or SNV) near infrared band spectral information；
Step 2: verify described fermented grain physical and chemical index calibration model；
Compare with unknown sample actual analysis result and forecast analysis, it is judged that whether model can be used；
Verify described fermented grain physical and chemical index calibration model to comprise the steps:
(1) sampling has neither part nor lot in the representative verification fermented grain sample of modeling；
(2) use 5cm rotary sample cup, scanned 64 times by integrating sphere diffuse-reflectance detecting system, gather to obtain to verify and use
The near infrared band averaged spectrum information of fermented grain sample, and obtain the physical and chemical index chemical assay of described verification fermented grain sample
Value；
(3) according to the near infrared band averaged spectrum information of described verification fermented grain sample, described step one acquisition is utilized
Fermented grain physical and chemical index calibration model obtain described verification fermented grain sample physical and chemical index predictive value；
(4) physical and chemical index chemical measurements and the physical and chemical index predictive value of described verification fermented grain sample are compared, if deviation
In set point, the most described fermented grain physical and chemical index calibration model is available；If deviation exceedes set point, then by verification wine
The fermented grain sample sets for modeling included in by unstrained spirits sample, and adjusts repetition step one and step 2 after modeling conditions, until described wine
Unstrained spirits physical and chemical index calibration model is available；
Step 3: the detection of fermented grain sample to be measured；
The scan mode that fermented grain sample to be measured uses continuous wavelength infrared diaphanoscopy is carried out near-infrared averaged spectrum scanning,
Obtain the near infrared band spectral information of fermented grain sample to be measured, recycle described Maotai-flavor wine brewing fermented grain physical and chemical index calibration model
The physical and chemical index of described fermented grain to be measured is obtained by the way of prediction.
The condition set by near infrared light spectrogram that obtains includes:
(1) detector light source is 15000-20000cm-1Light source.
(2) wavelength band obtained near infrared band spectral information is 10000-4000cm-1；
(3) impact of water in background deduction noise, carbon dioxide and air；
(4) fermented grain spectrogram capture setting is 16cm-1；
(5) sample cup, sampling amount is 80g；
(6) scan mode is rotator rotating acquisition 64 times.
Described physical and chemical index includes one or more in moisture content, acidity, residual sugar and starch.
Described physical and chemical index chemical measurements uses standard chemical assay method to be measured.
Described standard chemical assay method is carried out as follows:
1. moisture:
Weigh 10.00g fermented grain in the clean evaporating dish of known quality, shakeout, put into warmed up to 135 ± 1 DEG C baking ovens
In be dried 1 hour, take out, in exsiccator cool down half an hour, weigh.
In formula: m1Sample and evaporating dish quality, g before being dried；
m2Dried sample and evaporating dish quality, g.
2. acidity:
Weigh 10.00g fermented grain in 250mL beaker, add 100.00mL water, stir evenly, be at room temperature standing and soak for 30 clocks, in
Between every 15 minutes stirring once.Filter with absorbent cotton, access filtrate with 250mL triangular flask, discard just filtrate about 20mL, connect
Take filtrate standby.Absorption 10.00mL filtrate, in 250mL triangular flask, adds 20mL water, adds 2 1% phenolphthalein instructions after shaking up
Agent, being titrated to solution with the standard solution of sodium hydroxide of 0.1moL/L is that blush does not takes off for 30 seconds, and record sodium hydroxide standard is molten
Liquid consumption.Result represents and is calculated as follows:
Result is to represent containing a sour mM number in 10 grams of fermented grains:
Acidity (mmolH+/ 10g)=100/10nv==10nv
In formula: n Concentration of Sodium Hydroxide Solution Standard, moL/L；
V titration consumes standard solution of sodium hydroxide volume, mL.
3. residual sugar:
Weigh 75.00g copper sulfate (CuSO4.5H2O), 0.250g methylene blue indicator soluble in water, and be diluted to
5000.00mL。
Solution A: weigh 75.00g copper sulfate (CuSO4.5H2O), 0.250g methylene blue indicator soluble in water, and dilute
To 5000.00mL.
Second liquid: weigh 250.00g sodium potassium tartrate tetrahydrate (KNaC4H4O6.4H2O), 270g sodium hydroxide and 40.00g ferrous iron cyanogen
Change potassium [K4Fe(CN)6·3H2O] soluble in water and dilute as 5000.00mL.
Face the used time, above-mentioned two solution are respectively taken 5.00mL mixing.
0.1% (m/v) Glucose standards solution
Accurately weigh the pure glucose of cooling after 5.0000g fermented grain is dried 2 hours in 103～105 DEG C of baking ovens, use water dissolution
Rear addition 25mL hydrochloric acid, adds water and is settled to 5000.00mL.
Pre-titration: drawing the micromethod Fei Linshi solution each 5.00mL of first, second liquid, (conical flask is with striking to insert 150mL conical flask
Conical flask used during Lin Shi standardization of solution is the identical lot number of same manufacturer production) in, add water 10mL, adds appropriate preparation
Good sample, shakes up.Put and heat on electric furnace, control to seethe with excitement in 2 minutes, and keep micro-boiling 2 minutes, use under fluidized state
0.1% (m/v) Standard glucose solution be titrated to blue disappearance with the speed of 1 per second and in light yellow, record standard Fructus Vitis viniferae
Sugar liquid consumption.
Formal titration: drawing the micromethod Fei Linshi solution each 5mL of first, second liquid, (conical flask is with striking to insert 150mL conical flask
Conical flask used during Lin Shi standardization of solution is the identical lot number of same manufacturer production) in, add water 10mL, adds and titrates in advance
The sample of the same volume added, adds the pre-0.1% Glucose standards solution titrating few 1mL of ratio, shakes up.Add on electric furnace
Heat was seethed with excitement in 2 minutes, and kept seething with excitement 2 minutes.With 0.1% (m/v) Standard glucose solution with 1 per second under fluidized state
Speed be titrated to blue disappearance and in light yellow, record standard Glucose Liquid total amount consumed v2mL。
Calculate:
Residual sugar (with glucose meter, %)={ [(v1-v2)×c/[10.00×(v3/100)]}×100
In formula: v1Quota of expenditure glucose solution volume, mL in Fei Linshi standardization of solution；
v2Sample formally titrate in quota of expenditure glucose solution volume, mL；
C Standard glucose solution concentration, g/mL；
v3Sample titrates in advance or formally titrates the volume of sample of addition, mL；
10.00 sample mass, g；
100 samples prepare volume, mL.
4. starch:
Accurately weigh 5.00g sample, be placed in 250mL conical flask, add 60mL (1+4) HCl solution, be shaken gently for taper
Bottle, makes sample be sufficiently humidified so as to.Bottleneck loads onto bottle stopper, and on bottle stopper, band is about the glass-tube of 1 meter, puts and boils on electric furnace, micro-boiling 30 minutes
After, take out, cool down with flowing water.Filtering with absorbent cotton, filtrate receives with 500mL volumetric flask, fully washs conical flask and residual with water
Slag, washing liquid is all filtered in volumetric flask, is diluted with water to scale, shakes up.Then with pipette, extract 50mL hydrolyzed solution in 100mL
In volumetric flask, neutralize with 20% sodium hydroxide solution, test with accurate pH test paper, make the pH value of aqueous solution be about 7, finally add water
To scale, shake up.
Pre-titration: drawing the micromethod Fei Linshi solution each 5mL of first, second liquid, insert in 150mL conical flask, add water 10mL, then
Add the sample prepared in right amount, shake up.Put and heat on electric furnace, control to seethe with excitement in 2 minutes, and keep micro-boiling 2 minutes, in boiling
Rise be titrated to blue disappearance with 0.1% (m/v) Standard glucose solution with the speed of 1 per second under state and in light yellow, note
Record standard glucose sugar liquid consumption.
Formal titration: drawing the micromethod Fei Linshi solution each 5mL of first, second liquid, insert in 250mL conical flask, add water 10mL,
The sample of the same volume added and titrate addition in advance, adds the pre-0.1% Glucose standards solution titrating few 1mL of ratio,
Shake up.Seethe with excitement in heating 2 minutes on electric furnace, and keep seething with excitement 2 minutes.With 0.1% (m/v) standard glucose under fluidized state
Sugar juice be titrated to blue disappearance with the speed of 1 per second and in light yellow, record standard Glucose Liquid total amount consumed v2mL。
In formula: v1Quota of expenditure glucose solution volume, mL in Fei Linshi standardization of solution；
v2Sample formally titrate in quota of expenditure glucose solution volume, mL；
C Standard glucose solution concentration, g/mL.
5.00 sample masses, g；
50/500 draws 50mL from 500mL filtrate puts in 100mL volumetric flask and rear constant volume；
v3Sample titrates in advance or formally titrates the volume of sample of addition, mL；
0.9 glucose is scaled the coefficient of starch.
Embodiment 1
Take the fourth round time produced 2016 and go out pond fermented grain as calibration fermented grain sample, use said method to measure respectively
Its moisture content, acidity, residual sugar and amount of starch.
Open near infrared spectrometer preheating 30min at 25 DEG C, solid-state fermented grain sample is loaded specimen cup, i.e. 5cm rotates
Specimen cup, uses continuous wavelength near infrared spectrum scanning, gathers the near infrared spectrum of fermented grain sample, obtains the as shown in Figure 1
Four rounds go out pond fermented grain sample near infrared light spectrogram.
Gained spectrum and corresponding acquired sample physical and chemical index data are joined in chemo metric software, selects
Suitably algorithm, wave band and preprocess method, utilize chemo metric software to process, obtain required calibration model.Fig. 2-Fig. 5 depends on
The secondary fourth round time that is respectively goes out moisture content, acidity, the model of residual sugar and starch gained in the fermented grain sample physical and chemical index of pond, and each physics and chemistry refers to
Mark gained model result is as shown in table 1.
Table 1 fourth round time goes out pond fermented grain sample physical and chemical index calibration model parameter
Described normative forecast deviation (SEP) is the mean absolute error of checking collection sample predictions value and actual value.
The checking of model: the fourth round time taking 50 known physical and chemical indexs goes out the above-mentioned calibration model of pond fermented grain sample survey,
Repeat step 2, the near infrared spectrum of the acquisition calibration model built up is predicted into pond fermented grain physical and chemical index content.To simultaneously
The physical and chemical index content of prediction and known content balance, the results are shown in Table 2, analyze its error whether in allowed band.
Table 2 fourth round time goes out pond fermented grain sample physical and chemical index calibration model predictive value and compares with standard test value
Finding through analyzing contrast, its moisture content, acidity, residual sugar, the predictive value of starch calibration model and actual value, deviation is relatively
Little, all in allowed band, illustrate that the calibration model that the present invention is set up can carry out actual prediction use.
Utilize the model set up to be predicted using, moisture content, acidity, residual sugar, the calibration model of starch are added to spectrum
In collecting work stream, to fermented grain sample to be analyzed, repeat step 3, obtain each physical and chemical index in surveyed solid-state fermented grain and contain
Amount.
Embodiment 2
Take the fourth round time produced 2016 and enter pond fermented grain as calibration fermented grain sample, use said method to measure respectively
Its moisture content, acidity, residual sugar and amount of starch.
Open near infrared spectrometer preheating 30min at 25 DEG C, solid-state fermented grain sample is loaded specimen cup, i.e. 5cm rotates
Specimen cup, uses continuous wavelength near infrared spectrum scanning, gathers the near infrared spectrum of fermented grain sample, obtains the as shown in Figure 6
Four rounds go out pond fermented grain sample near infrared light spectrogram.
Gained spectrum and corresponding acquired sample physical and chemical index data are joined in chemo metric software, selects
Suitably algorithm, wave band and preprocess method, utilize chemo metric software to process, obtain required calibration model.Fig. 7-Figure 10
It respectively is fourth round time and goes out moisture content, acidity, the model of residual sugar and starch gained in the fermented grain sample physical and chemical index of pond, each physics and chemistry
Index gained model result is as shown in table 3.
Table 3 fourth round time enters pond fermented grain sample physical and chemical index calibration model parameter
Described normative forecast deviation (SEP) is the mean absolute error of checking collection sample predictions value and actual value.
The checking of model: the fourth round time taking 50 known physical and chemical indexs goes out the above-mentioned calibration model of pond fermented grain sample survey,
Repeat step 2, the near infrared spectrum of the acquisition calibration model built up is predicted into pond fermented grain physical and chemical index content.To simultaneously
The physical and chemical index content of prediction and known content balance, the results are shown in Table 4, analyze its error whether in allowed band.
Table 4 fourth round time enters pond fermented grain sample physical and chemical index calibration model predictive value and compares with standard test value
Finding through analyzing contrast, its moisture content, acidity, residual sugar, the predictive value of starch calibration model and actual value, deviation is relatively
Little, all in allowed band, illustrate that the calibration model that the present invention is set up can carry out actual prediction use.
Utilize the model set up to be predicted using, moisture content, acidity, residual sugar, the calibration model of starch are added to spectrum
In collecting work stream, to fermented grain sample to be analyzed, repeat step 3, obtain each physical and chemical index in surveyed solid-state fermented grain and contain
Amount.
Further, the present invention can going out pond and entering pond for quite different 7 rounds of Maotai-flavor liquor of physical and chemical index
Fermented grain, sets up the physical and chemical parameter calibration model of correspondence respectively, carries out the physical and chemical index prediction of actual fermented grain sample, quickly obtains
Accurately result.
The present invention is when selecting chemical analysis sample, and single considers sample composition content and gradient.Maotai-flavor liquor wine
Unstrained spirits be not single class pure sample this, its complicated component, comprise a few class material, feature granularity is big, viscosity is big and uneven the most easily leads for it
Cause scattering impact, different production round form, color, granularity, moisture, viscosityes during fermentation and distillation take wine
The most different, there is bigger difference.In order to improve calibration effect, take screen principle and carry out multiple calibration；Take each round,
Go out pond and enter pond and model respectively, to improve calibration effect and the accuracy of assay.
In actual analysis, sample analysis result will produce the biggest error.In modeling, each round is used to build respectively
Mould, the gradient reducing physics and chemistry concentration value divides, and controls its linear distribution scope, to the physical and chemical index forecast analysis in this round more
Targetedly.
In same round, go out pond and the moisture entering pond is clearly distinguished from.Go out pond and enter pond outward appearance and interior
All there is bigger difference on physical and chemical index, use modeling pattern respectively.If going out pond and entering pond comprehensive modeling, linear distribution can go out
Existing disorder, owing to content is the most close, index feature is distinguished inconspicuous, and final calculation result also can deviate actual value largely.
Through checking, will go out pond and enter pond separately modeling, the analysis result accuracy of sample will be improved a lot, sample linear distribution with
Gradient scope all has good embodiment, and owing to content is close, Gradient distribution also keeps within the specific limits, does not have relatively large span,
Distributed points also ratio is more uniform, sample goes out pond and enters two kinds of the pond more targeted discriminant analysis of different qualities sample.Theoretically,
In certain gradient scope, sample size is the abundantest, and scope is concentrated better and better, on this basis, ever-increasing during utilization
The analysis of the unknown sample in this batch also will be the most accurate by sample set.
The present invention brewages 1-7 sample set quantity of each round fermented grain for Maotai-flavor liquor and is held in 500--1000
Above calibration sample, it was predicted that model enumerates each batch of Maotai-flavor fermented grain different characteristics in identical round is fermented, and has very
Wide characteristic range, four physical and chemical indexs (moisture, acidity, residual sugar, starch) for each round fermented grain set up budget mould respectively
Type, during practice, effectiveness comparison is preferable.
In order to ensure the advantage of above complete property, make analysis result more accurate, during Criterion model, tool
Standby following condition:
1) substantial amounts of sample sets, accurately and reliably chemical analysis data.
2) spectrogrph that properties is steady in a long-term, is to ensure that data have the basic demand of good repeatability；
3) multiple functional and calculate chemo metric software accurately, it is the essential tool setting up model and analysis.
4) model that the most also scope of application is sufficiently wide.
Although illustrate and describing the present invention with specific embodiment, but it will be appreciated that various embodiments above is only used
So that technical scheme to be described, it is not intended to limit；It will be understood by those within the art that: without departing substantially from this
In the case of bright spirit and scope, the technical scheme described in foregoing embodiments can be modified, or to wherein
Some or all of technical characteristic carries out equivalent；And these amendments or replacement, do not make the essence of appropriate technical solution
Depart from the scope of various embodiments of the present invention technical scheme；It is, therefore, intended that include in the following claims belonging to the present invention
In the range of all these substitutions and modifications.
Claims (10)
1. the method for a quick detection Maotai-flavor wine brewing fermented grain physical and chemical index, it is characterised in that comprise the steps:
Step one: set up Maotai-flavor wine brewing fermented grain physical and chemical index calibration model；
Take going out pond and entering the pond fermented grain sample composition 14 samples for modeling of Maotai-flavor seven each rounds of round of wine brewing respectively
Product group；Near infrared band spectral information is measured respectively for fermented grain sample each in fermented grain sample sets, obtains 14 groups of near infrared bands
Spectral information；Each sample in 14 groups of fermented grain sample sets is measured its physical and chemical index chemical measurements respectively, obtains 14 groups of physics and chemistry and refer to
Mark chemical measurements；
By near infrared band spectral information and the physical and chemical index chemical measurements one_to_one corresponding of all samples in 14 groups, use tool
The one group of near infrared band spectral information and the one group of physical and chemical index chemical measurements that have corresponding relation are set up fermented grain physical and chemical index and are determined
Mark model, there are 14 groups of Maotai-flavor wine brewing fermented grain physical and chemical index calibration models；
Step 2: verify described fermented grain physical and chemical index calibration model；
Compare with unknown sample actual analysis result and forecast analysis, it is judged that whether model can be used；
Step 3: the detection of fermented grain sample to be measured；
Fermented grain sample to be measured is carried out near infrared spectrum scanning, it is thus achieved that the near infrared band spectral information of fermented grain sample to be measured, then
The physics and chemistry utilizing described Maotai-flavor wine brewing fermented grain physical and chemical index calibration model to obtain described fermented grain to be measured by the way of prediction refers to
Mark.
The method of a kind of quick detection Maotai-flavor the most according to claim 1 wine brewing fermented grain physical and chemical index, it is characterised in that
The described condition setting up fermented grain physical and chemical index calibration model includes:
(1) stoechiometric process is selected；
(2) modeling pretreatment；
(3) foundation of calibration model and the verification of calibration model；
(4) rejecting abnormalities sample；
(5) main composition is screened；
(6) select to obtain the light path near infrared band spectral information.
The method of a kind of quick detection Maotai-flavor the most according to claim 1 wine brewing fermented grain physical and chemical index, it is characterised in that
Verify described fermented grain physical and chemical index calibration model to comprise the steps:
(1) sampling has neither part nor lot in the representative verification fermented grain sample of modeling；
(2) gather the acquisition verification near infrared band spectral information of fermented grain sample, and obtain described verification fermented grain sample
Physical and chemical index chemical measurements；
(3) according to the near infrared band spectral information of described verification fermented grain sample, the fermented grain reason that described step one obtains is utilized
Change index calibration model and obtain the physical and chemical index predictive value of described verification fermented grain sample；
(4) physical and chemical index chemical measurements and the physical and chemical index predictive value of described verification fermented grain sample are compared, if deviation is setting
In the range of Ding, the most described fermented grain physical and chemical index calibration model is available；If deviation exceedes set point, then verification is used fermented grain sample
Product include the fermented grain sample sets for modeling in, and adjust repetition step one and step 2 after modeling conditions, until described fermented grain is managed
It is available for changing index calibration model.
The method of a kind of quick detection Maotai-flavor the most according to claim 1 wine brewing fermented grain physical and chemical index, it is characterised in that
Described near infrared band spectrum is averaged spectrum.
The method of a kind of quick detection Maotai-flavor the most according to claim 1 wine brewing fermented grain physical and chemical index, it is characterised in that
Collection to described near infrared band spectrum uses rotary sample cup, the scanning of integrating sphere diffuse-reflectance detecting system to obtain.
The method of a kind of quick detection Maotai-flavor the most according to claim 1 wine brewing fermented grain physical and chemical index, it is characterised in that
The scan mode using continuous wavelength infrared diaphanoscopy obtains described near infrared band spectrum.
The method of a kind of quick detection Maotai-flavor the most according to claim 1 wine brewing fermented grain physical and chemical index, it is characterised in that
Described physical and chemical index includes one or more in moisture content, acidity, residual sugar and starch.
The method of a kind of quick detection Maotai-flavor the most according to claim 1 wine brewing fermented grain physical and chemical index, it is characterised in that
Step 4 is also included: optimize and more new model after described step 3；On the basis of original forecast model, when increasing new one
More new model during lot data.
The method of a kind of quick detection Maotai-flavor the most according to claim 1 wine brewing fermented grain physical and chemical index, it is characterised in that
The condition set by near infrared light spectrogram that obtains includes:
(1) detector light source is 15000-20000cm-1Light source.
(2) wavelength band obtained near infrared band spectral information is 10000-4000cm-1；
(3) impact of water in background deduction noise, carbon dioxide and air；
(4) fermented grain spectrogram capture setting is 16cm-1；
(5) sample cup, sampling amount is 80g；
(6) scan mode is rotator rotating acquisition 64 times.
The method of a kind of quick detection Maotai-flavor the most according to claim 1 wine brewing fermented grain physical and chemical index, its feature exists
In, physical and chemical index chemical measurements uses standard chemical assay method to be measured.
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| CN111398213A (en) * | 2020-04-08 | 2020-07-10 | 四川虹微技术有限公司 | Method for judging eligibility of fermented grain model |
| CN111721740A (en) * | 2020-06-23 | 2020-09-29 | 佛山市海天（江苏）调味食品有限公司 | Seasoning physical and chemical index detection method based on calibration model |
| CN114544830A (en) * | 2022-02-18 | 2022-05-27 | 四川郎酒股份有限公司 | Method for simultaneously analyzing ethyl carbamate and sweetener in white spirit by using LCMS (liquid crystal display system) |
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| CN114544830A (en) * | 2022-02-18 | 2022-05-27 | 四川郎酒股份有限公司 | Method for simultaneously analyzing ethyl carbamate and sweetener in white spirit by using LCMS (liquid crystal display system) |
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