CN108593861A - A method of prediction fresh-water fishes shelf life - Google Patents
A method of prediction fresh-water fishes shelf life Download PDFInfo
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- 241000251468 Actinopterygii Species 0.000 title claims abstract description 86
- 239000013505 freshwater Substances 0.000 title claims abstract description 48
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000003860 storage Methods 0.000 claims abstract description 19
- 150000001875 compounds Chemical class 0.000 claims abstract description 15
- 238000004458 analytical method Methods 0.000 claims abstract description 11
- -1 compound methyl disulfides Chemical class 0.000 claims abstract description 9
- LRHPLDYGYMQRHN-UHFFFAOYSA-N N-Butanol Chemical compound CCCCO LRHPLDYGYMQRHN-UHFFFAOYSA-N 0.000 claims abstract description 7
- WQOXQRCZOLPYPM-UHFFFAOYSA-N dimethyl disulfide Chemical compound CSSC WQOXQRCZOLPYPM-UHFFFAOYSA-N 0.000 claims description 56
- PHTQWCKDNZKARW-UHFFFAOYSA-N isoamylol Chemical class CC(C)CCO PHTQWCKDNZKARW-UHFFFAOYSA-N 0.000 claims description 28
- 238000006243 chemical reaction Methods 0.000 claims description 26
- 238000011156 evaluation Methods 0.000 claims description 14
- 230000000694 effects Effects 0.000 claims description 11
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- 230000004913 activation Effects 0.000 claims description 5
- 235000013372 meat Nutrition 0.000 claims description 5
- 230000004044 response Effects 0.000 claims description 5
- 238000012795 verification Methods 0.000 claims description 5
- 238000004140 cleaning Methods 0.000 claims description 4
- 241001519451 Abramis brama Species 0.000 claims description 3
- 241000252230 Ctenopharyngodon idella Species 0.000 claims description 3
- 241000252233 Cyprinus carpio Species 0.000 claims description 3
- 241000252234 Hypophthalmichthys nobilis Species 0.000 claims description 3
- 241000252498 Ictalurus punctatus Species 0.000 claims description 3
- 239000002504 physiological saline solution Substances 0.000 claims description 3
- 238000000611 regression analysis Methods 0.000 claims description 3
- 241000703769 Culter Species 0.000 claims description 2
- 241001275898 Mylopharyngodon piceus Species 0.000 claims description 2
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 claims description 2
- 241000404975 Synchiropus splendidus Species 0.000 claims description 2
- 239000005457 ice water Substances 0.000 claims description 2
- 239000010813 municipal solid waste Substances 0.000 claims description 2
- 239000005864 Sulphur Substances 0.000 claims 1
- 230000035943 smell Effects 0.000 claims 1
- 238000001514 detection method Methods 0.000 abstract description 6
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- 244000005700 microbiome Species 0.000 abstract description 3
- 210000000577 adipose tissue Anatomy 0.000 abstract description 2
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 abstract 1
- 125000002496 methyl group Chemical group [H]C([H])([H])* 0.000 abstract 1
- YWAKXRMUMFPDSH-UHFFFAOYSA-N pentene Chemical group CCCC=C YWAKXRMUMFPDSH-UHFFFAOYSA-N 0.000 abstract 1
- 239000003925 fat Substances 0.000 description 6
- 210000001519 tissue Anatomy 0.000 description 4
- OKKJLVBELUTLKV-UHFFFAOYSA-N Methanol Chemical compound OC OKKJLVBELUTLKV-UHFFFAOYSA-N 0.000 description 3
- 238000004949 mass spectrometry Methods 0.000 description 3
- 102000004169 proteins and genes Human genes 0.000 description 3
- 108090000623 proteins and genes Proteins 0.000 description 3
- 238000005070 sampling Methods 0.000 description 3
- QGZKDVFQNNGYKY-UHFFFAOYSA-N Ammonia Chemical group N QGZKDVFQNNGYKY-UHFFFAOYSA-N 0.000 description 2
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 2
- 102000004190 Enzymes Human genes 0.000 description 2
- 108090000790 Enzymes Proteins 0.000 description 2
- 150000001413 amino acids Chemical class 0.000 description 2
- 239000004205 dimethyl polysiloxane Substances 0.000 description 2
- 235000013870 dimethyl polysiloxane Nutrition 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 235000013305 food Nutrition 0.000 description 2
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- CXQXSVUQTKDNFP-UHFFFAOYSA-N octamethyltrisiloxane Chemical compound C[Si](C)(C)O[Si](C)(C)O[Si](C)(C)C CXQXSVUQTKDNFP-UHFFFAOYSA-N 0.000 description 2
- 238000004987 plasma desorption mass spectroscopy Methods 0.000 description 2
- 229920000435 poly(dimethylsiloxane) Polymers 0.000 description 2
- 229920001343 polytetrafluoroethylene Polymers 0.000 description 2
- 239000004810 polytetrafluoroethylene Substances 0.000 description 2
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- 238000011160 research Methods 0.000 description 2
- 238000002470 solid-phase micro-extraction Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical compound O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- BKOOMYPCSUNDGP-UHFFFAOYSA-N 2-methylbut-2-ene Chemical group CC=C(C)C BKOOMYPCSUNDGP-UHFFFAOYSA-N 0.000 description 1
- 230000009102 absorption Effects 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 150000001298 alcohols Chemical group 0.000 description 1
- 150000001412 amines Chemical group 0.000 description 1
- 229910021529 ammonia Inorganic materials 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
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- 239000012159 carrier gas Substances 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 238000003776 cleavage reaction Methods 0.000 description 1
- 238000000205 computational method Methods 0.000 description 1
- 238000005138 cryopreservation Methods 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 239000008367 deionised water Substances 0.000 description 1
- 229910021641 deionized water Inorganic materials 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011067 equilibration Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000000796 flavoring agent Substances 0.000 description 1
- 235000019634 flavors Nutrition 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 235000015110 jellies Nutrition 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000002906 microbiologic effect Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 229910052757 nitrogen Inorganic materials 0.000 description 1
- QJGQUHMNIGDVPM-UHFFFAOYSA-N nitrogen group Chemical group [N] QJGQUHMNIGDVPM-UHFFFAOYSA-N 0.000 description 1
- 230000001473 noxious effect Effects 0.000 description 1
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- 229910052717 sulfur Chemical group 0.000 description 1
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/02—Food
- G01N33/12—Meat; Fish
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- Engineering & Computer Science (AREA)
- Food Science & Technology (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Medicinal Chemistry (AREA)
- Physics & Mathematics (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
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Abstract
The invention discloses a kind of methods of prediction fresh-water fishes shelf life.This method is that the 3 kinds of odor compound methyl disulfides that will be measured under different temperatures, the concentration of 3 methyl, 1 butanol and 1 amylene, 3 alcohol in the flesh of fish have carried out kinetic model fitting with the changing rule of storage time, fresh-water fishes shelf life forecasting model is established, shelf life forecasting model is then based on and shelf life is evaluated.The method of prediction fresh-water fishes shelf life provided by the invention, the odor compound generated in storage using fish body come to fresh-water fishes degree of spoilage and freshness be detected, and for fish body fat content number, different objects is selected to establish model, predict fresh-water fishes shelf life, analysis detection time is short, operates rapid and convenient, compared to traditional microorganism and chemical index prediction technique, specific aim is stronger.
Description
Technical field
The present invention relates to a kind of prediction techniques of fish shelf life, and in particular to a kind of side of prediction fresh-water fishes shelf life
Method belongs to aquatic products Techniques of preserving field.
Background technology
China is fresh water fish production and consumption big country.Freshwater fish meat is full of nutrition, is rich in protein, amino acid and fat
Fat, easily occurs putrid and deteriorated, and fish body during corruption, destroyed by musculature, and protein is under the action of enzyme point
Solution is amino acid, and the smell distributed also becomes stink from original fishlike smell, and flavor quality reduces, or even will produce noxious material
Jeopardize the health of consumer.With the continuous improvement of living standards, people are also higher and higher to the freshness requirements of fishery -ies product, because
This is very necessary to the detection of its freshness and shelf life in fish body producing and selling and transporting procedures.
Currently, the prediction technique about fish shelf life mainly has sensory evaluation, microbiological indicator and physical and chemical index, using compared with
More evaluation indexes mainly has Volatile Base Nitrogen, total plate count, K values, TBARS value etc..The detection of these methods is single
Sample is time-consuming longer, cumbersome, can not accomplish quickly to detect.
Smell is one of the important indicator for evaluating Estimation of The Fish Freshness.The flesh of fish is in decay process, due to microorganism and itself
The degradations such as the effect of enzyme, protein and fat will produce nitrogenous, amine, ammonia, alcohols and sulfur-bearing class volatile materials, can be by these
Odor compound is applied to the prediction of Estimation of The Fish Freshness and shelf life, in addition, the fat content of fish body is different, the smell of generation
It closes object will be different, therefore, it is also particularly important that the odor compound for selecting directive property strong is used as evaluation index.
Invention content
The object of the present invention is to provide a kind of methods of prediction fresh-water fishes shelf life, pass through the smell for selecting directive property strong
Object is closed as evaluation index, and establishes prediction model, to realize the reasonable prediction to fresh-water fishes shelf life.
The invention is realized in this way：
A method of prediction fresh-water fishes shelf life, be the 3 kinds of odor compound methyl disulfides that will be measured under different temperatures,
The concentration of 3- methyl-1-butanols and 1-POL in the flesh of fish has carried out kinetic model with the changing rule of storage time
Fitting, establishes fresh-water fishes shelf life forecasting model, shelf life is evaluated and verified based on shelf life forecasting model, specifically
Steps are as follows：
(1) fresh fish is slaughtered into cleaning, back meat is taken to be cut into small pieces, every piece of 20g ± 5g；
(2) by fish it is packaged enter valve bag, and be divided into four groups and be stored under different temperatures respectively, distinguish by intervals
The content of fish 3 kinds of volatile scent compounds methyl disulfides in the block, 3- methyl-1-butanols and 1-POL is measured by sampling,
And carry out subjective appreciation；
(3) data obtained according to step (2), establish containing for methyl disulfide, 3- methyl-1-butanols and 1-POL
Amount obtains the reaction rate constant k of each compound with the kinetic model of storage temperature fluctuation；
(4) Arrhenius equation analysis temperature T and speed response constant k is utilized, to reaction rate constant under different temperatures
K, which carries out curve fitting, obtains the frequency factor k of methyl disulfide, 3- methyl-1-butanols and 1-POL0And reaction activity
EA；
(5) shelf life forecasting model based on methyl disulfide, 3- methyl-1-butanols and 1-POL content is established,
SL is shelf life, and unit d, T are absolute temperature, unit K, A0For the content of initial odor compound, unit
Ng/g, A are the content for storing the odor compound after the t times, unit ng/g, k0Frequency factor, EAReaction activity；
(6) prediction of fresh-water fishes shelf life：Shelf life is predicted with the shelf life forecasting model established.
Further scheme is：
In step (1), cleaning is that fish is put into trash ice, is cleaned with ice water or physiological saline；The fritter flesh of fish is thickness 2cm
Long strip type sample, every piece of block weight 20g ± 5g.
Further scheme is：
In step (4) fresh-water fishes reserve temperature take respectively 271K, 273K, 277K, 281K i.e. -2 DEG C, 0 DEG C, 4 DEG C, 8 DEG C.
0-4 DEG C of selection is refrigerated storage temperature, and -2 DEG C are micro- jellys storages, 8 DEG C be meat in storing etc. entirely logistics progress often
There is chain cleavage, temperature is caused to rise sharply.This 4 temperature are selected to cover in common cryopreservation temperature and transporting procedures
Raised temperature after temperature fluctuation.
Further scheme is：
According to subjective appreciation as shelf life terminal, established in conjunction with Arrhenius equations and first order reaction kinetics model
Shelf life forecasting model based on 3 kinds of odor compound methyl disulfides, 3- methyl-1-butanols and 1-POL.
Further scheme is：
In step (3), with level-one chemical reaction kinetic model to methyl disulfide, 3- methyl-1s-under different reserve temperatures
Butanol and 1-POL carry out regression analysis, and regression equation expression formula is:A=A0×ekt, wherein A, A0, t, k respectively represent
Quality factor number, initial value, time, reaction rate constant.
Further scheme is：
In step (4), with Arrhenius equationsK in formula0：Frequency factor；EA：Activation energy (J/
mol)；T：Temperature (K)；R：Gas constant, 8.3144J/ (molK), analysis temperature T and speed response constant k, will
Arrhenius equations turned is lnk=lnk0-(EA/ RT), 1nk maps 1/T to obtain a straight line, and reaction is found out by straight slope
Activation energyA, frequency factor k is found out by intercept0, the frequency factor k of methyl disulfide, 3- methyl-1-butanols and 1-POL0
With reaction activity EARespectively 4.4 × 108、1.35×108、1.65×109And 48.09kJmol-1、45.29kJ·mol-1、
50.83kJ·mol-1；
Further scheme is：
In step (5), according to methyl disulfide, 3- methyl-1-butanols and 1-POL under 4 reserve temperatures gained
The k arrived0Value and EAValue, is obtained by regression equation and Arrhenius equations:
Calculate shelf life forecasting modelThe k that will be calculated0With reaction activity EAIt substitutes into
This model obtains the shelf life forecasting model of methyl disulfide, 3- methyl-1-butanols and 1-POL；
Further scheme is：
Using the Analyses Methods for Sensory Evaluation Results of back fish block as shelf life terminal under different reserve temperatures, with above-mentioned forecasting shelf life
The predicted value of model verifies shelf life with measured value.
Further scheme is：
For the fresh-water fishes of fat content≤5%, the forecasting shelf life established using methyl disulfide and 3- methyl n-butyl alcohols
Model carries out forecasting shelf life；For fat content>5% fresh-water fishes, the forecasting shelf life mould established using 1-POL
Type carries out forecasting shelf life.
The fat content range of common fresh-water fishes is as follows：
Further scheme is：
The fresh-water fishes are perch, Channel-catfish fishes, mandarin fish, Culter fishes, grass carp, black carp, bighead, silver carp, carp, crucian or bream
Fish.
The method of prediction fresh-water fishes shelf life provided by the invention, the smell chemical combination generated in storage using fish body
Object come to fresh-water fishes degree of spoilage and freshness be detected, and for fish body fat content number, select different mesh
Mark object establishes model, carries out the prediction and verification of fresh-water fishes shelf life, and analysis detection time is short, operates rapid and convenient, compares and passes
The microorganism of system and chemical index prediction technique, specific aim are stronger.
Description of the drawings
Fig. 1 is methyl disulfide in the flesh of fish under different reserve temperatures with the variation of storage time；
Fig. 2 is 3- methyl-1-butanols in the flesh of fish under different reserve temperatures with the variation of storage time；
Fig. 3 is 1-POL in the flesh of fish under different reserve temperatures with the variation of storage time；
Fig. 4 is subjective appreciation in the flesh of fish under different reserve temperatures with the variation of storage time.
Specific implementation mode
With reference to specific embodiment, the present invention is described in further detail.
As the specific embodiment of the present invention, in carrying out the present invention, it is necessary first to be set using following underlying instrument
It is standby, including：
Weighing balance (BS-210, German Sai Duolisi), (XHF-D, Bo Xinzhi biotechnology share have interior cut type refiner
Limit company), constant-temperature heating magnetic stirring apparatus (DF-101s, Wuhan Cole's experimental instruments and equipment limited), SPME extraction equipments
(57330U, Supelco companies of the U.S.), 50/30 μm of DVB/CAR/PDMS of extracting head (Supelco companies of the U.S.), gas phase color
Spectrum-mass spectrometer (GC7890A-MS5975B, Agilent companies of the U.S.).
It is, of course, understood that above-mentioned instrument and equipment is not limitation of the present invention, those skilled in the art can be with
Use other instrument and equipments with same function.
Below to each step of the embodiment of the present invention and corresponding detection, analysis, computational methods detailed description.
Using perch as raw material, the full fish fats content of perch is 5-6%, is ground in early period for the experiment of the specific embodiment of the invention
Find that different fingerlings are almost the same in the odor compound variation tendency of storage period on the basis of studying carefully, therefore can be according to the present invention
The research of embodiment obtains the model that can promote the use of other type fresh-water fishes forecasting shelf lifes.
A method of prediction fresh-water fishes shelf life, including：
Step 1: pretreatment
It is cleaned with physiological saline after new fresh freshwater fish is slaughtered, removes the peel, back meat is taken to be cut into the strip pattern of thickness 2cm
Product, every piece of 20g；
Step 2: detection and evaluation
By fish block be randomly divided into four be assembled into sterilizing valve bag be stored in tetra- different temperatures of 271K, 273K, 277K, 281K
Under, by the separately sampled measurement of intervals；The time interval of sampling is：Start to sample daily, it is every later from second day
Sampling is primary every two days；
Wherein, odor compound method for measuring is as follows：
It weighs the 6g chopping flesh of fish to be put in 50mL screw socket sample bottles, 12mL deionized waters is added, it is heat-insulated with polytetrafluoroethylene (PTFE)
It seals, water-bath in magnetic stirring apparatus is placed at 60 DEG C and balances 15min, with 50/30 extracting head headspace absorptions of DVB/CAR/PDMS
Extracting head is inserted into GC sample introductions, parses 5min, to be measured, each sample is 3 times parallel by 40min；
Chromatographic condition
Post case DB-WAX (the μ m 0.25mm of 30m × 0.25) equilibration time 1min, using temperature programming pattern, initial temperature
40 DEG C, 5min is kept, 90 DEG C are risen to 3 DEG C/min, 5min is kept, then 180 DEG C are risen to 8 DEG C/min, keeps 5min；Carrier gas
(He) flow velocity 1.0mL/min；250 DEG C of injector temperature, does not shunt；
Mass Spectrometry Conditions
Ionization mode is EI；Mass Spectrometry Conditions are electron energy 70eV, voltage 350V；230 DEG C of ion source temperature, level four bars temperature
150 DEG C of degree, 280 DEG C of transmission line temperature；
Quantitative approach
Methyl disulfide, 3- methyl-1-butanols and 1-POL standard items are dissolved in methanol by a certain percentage to be configured to
After knowing the mixed standard solution of content, 6 concentration gradients are diluted to deionized water, are separately added into wherein；Identical SPME,
Extractive analysis is carried out under chromatographic condition and Mass Spectrometry Conditions, thus method obtains standard curve, according to standard curve and practical measurement
Data calculate the content of methyl disulfide, 3- methyl-1-butanols and 1-POL in fish block；
Subjective appreciation
Color and luster, smell, tissue morphology and the tissue elasticity of the subjective appreciation primary evaluation flesh of fish, evaluating member is by 8 experts
Composition, specific evaluation criteria are as shown in table 1；Experiment uses method of weighting scores, each index weights to be set as：Color and luster 20%, smell
30%, tissue morphology 30%, tissue elasticity 20%.It is the characteristic score value, each characteristic that the average mark of each characteristic, which is multiplied by its weight,
The sum of for subjective appreciation point；
Subjective appreciation is as shown in Fig. 4 with the result of variations of storage time in the flesh of fish under different reserve temperatures；
1 sense organ evaluating meter of table
Step 3: the foundation of shelf life model
The foundation of first order reaction kinetics model
According to methyl disulfide, 3- methyl-1-butanols and 1-POL with storage time changing rule (such as attached drawing 1,
2, shown in 3), kinetic model of this 3 kinds of compounds with storage temperature fluctuation is established, can be the product for predicting and controlling fresh-water fishes
Matter provides reliable theoretical foundation；In food processing and storage process, most of quality comparisons related with food quality are all
Follow 1 grade of pattern；With level-one chemical reaction kinetic model to methyl disulfide under different reserve temperatures, 3- methyl-1-butanols and
1-POL carries out regression analysis, and relevant parameter is shown in Table 2；Regression equation expression formula is:A=A0×ekt(1), wherein A0For
The content of initial odor compound, unit ng/g, A are the content for storing the odor compound after the t times, unit ng/g, when t is
Between, k is reaction rate；
2 first-order kinetics parameter of table
k0And EAThe determination of value
With Arrhenius equations(k in formula0：Frequency factor；EA：Activation energy (J/
mol)；T：Temperature (K)；R：Constant, 8.3144J/ (molK)) analysis temperature T and speed response constant k, by the side Arrhenius
Journey is converted into lnk=lnk0-(EA/ RT), 1nk maps to 1/T and a straight line can be obtained, and reaction activity can be found out by straight slope
EA, frequency factor k can be found out by intercept0；Be computed, methyl disulfide, 3- methyl-1-butanols and 1-POL frequency factor
k0With reaction activity EARespectively 4.4 × 108、1.35×108、1.65×109And 48.087kJmol-1、45.286kJ·
mol-1、50.828kJ·mol-1；
Shelf life forecasting model formula
According to methyl disulfide, 3- methyl-1-butanols and 1-POL under 4 reserve temperatures obtained k0Value and EA
Value, can be obtained by publicity (1) and (2):Calculate shelf life forecasting model
The k that will be calculated0With reaction activity EAThis model is substituted into, methyl disulfide, 3- methyl-1-butanols and 1- are obtained
The shelf life forecasting model of amylene -3- alcohol：
Step 4: the verification and evaluation of fresh-water fishes shelf life forecasting model
Sensory evaluation is allocated as the terminal for acceptable minimum gross score as shelf life using 5.When fresh-water fishes block reaches sense
When official refuses point (reaching sensory evaluation 5 minutes), obtained with the content of methyl disulfide, 3- methyl-1-butanols and 1-POL
Predicted value be compared with actual value, shelf life model is verified (such as table 3).When being verified, different fat have been selected
The fish of fat content is verified respectively.
The fish of fat content≤5% is grass carp (271K), and bream (273K), crucian (277K), bighead (281K), fat contains
Amount>5% fish is perch (271K), Channel-catfish fishes (273K), silver carp (277K) and carp (281K).
3 shelf life model verification result of table
Above-mentioned verification result shows, can quickly, relatively reliable in real time using the shelf life forecasting model that this research is established
Predict the shelf life of fresh-water fishes under -2 DEG C of -8 DEG C of holding conditions.For the fresh-water fishes of fat content≤5%, using methyl disulfide and
3- methyl n-butyl alcohols establish shelf life forecasting model error it is smaller (<3%), for fat content>5% fresh-water fishes use
1-POL establish shelf life forecasting model error it is smaller (<3%).
Although reference be made herein to invention has been described for explanatory embodiment of the invention, and above-described embodiment is only this hair
Bright preferable embodiment, embodiment of the present invention are not limited by the above embodiments, it should be appreciated that people in the art
Member can be designed that a lot of other modification and implementations, these modifications and implementations will be fallen in principle disclosed in the present application
Within scope and spirit.
Claims (10)
1. a kind of method of prediction fresh-water fishes shelf life, it is characterised in that：By measured under different temperatures 3 kinds of odor compounds two
Two sulphur of first, the concentration of 3- methyl-1-butanols and 1-POL in the flesh of fish carry out dynamics with the changing rule of storage time
Models fitting, establishes fresh-water fishes shelf life forecasting model, and specific step is：
(1) fresh fish is slaughtered into cleaning, back meat is taken to be cut into small pieces；
(2) by fish it is packaged enter valve bag, and be divided into four groups and be stored under different temperatures respectively, it is separately sampled by intervals
The content for measuring fish 3 kinds of volatile scent compounds methyl disulfides in the block, 3- methyl-1-butanols or 1-POL, goes forward side by side
Row subjective appreciation；
(3) data obtained according to step (2), establish the content of methyl disulfide, 3- methyl-1-butanols and 1-POL with
The kinetic model of storage temperature fluctuation obtains the reaction rate constant k of each compound；
(4) Arrhenius equation analysis temperature T and speed response constant k are utilized, to reaction rate constant k under different temperatures into
Row curve matching obtains the frequency factor k of methyl disulfide, 3- methyl-1-butanols and 1-POL respectively0And reaction activity
EA；
(5) shelf life forecasting model based on methyl disulfide, 3- methyl-1-butanols or 1-POL content is established,
SL is shelf life, unit d, R：Gas constant, 8.3144J/ (molK), T are absolute temperature, unit K, A0It is first
The content of beginning odor compound, unit ng/g, A are the content for storing the odor compound after the t times, unit ng/g；
(6) shelf life forecasting model based on above-mentioned foundation carries out the verification and evaluation of the prediction model of fresh-water fishes shelf life：
Shelf life is verified with measured value with the predicted value of above-mentioned shelf life forecasting model.
2. the method for predicting fresh-water fishes shelf life according to claim 1, it is characterised in that：
In step (1), cleaning is that fish is put into trash ice, is cleaned with ice water or physiological saline；The fritter flesh of fish is the length of thickness 2cm
Stripe shape sample, every piece of block weight 20g ± 5g.
3. the method for predicting fresh-water fishes shelf life according to claim 1, it is characterised in that：
Fresh-water fishes reserve temperature takes 271K, 273K, 277K, 281K respectively in step (2).
4. the method for predicting fresh-water fishes shelf life according to claim 1, it is characterised in that：
In step (3), shelf life terminal is determined according to the results of sensory evaluation of step (2), establishes methyl disulfide, 3- methyl-1s-
The content of butanol and 1-POL with storage temperature fluctuation first order reaction kinetics model, and combine Arrhenius equations
With methyl disulfide of the first order reaction kinetics model foundation based on 3 kinds of smells, the goods of 3- methyl-1-butanols and 1-POL
Frame phase prediction model.
5. the method for predicting fresh-water fishes shelf life according to claim 4, it is characterised in that：
In step (3), with level-one chemical reaction kinetic model to methyl disulfide, 3- methyl-1-butanols under different reserve temperatures
Regression analysis is carried out with 1-POL, regression equation expression formula is:A=A0×ekt, wherein A, A0, t, k respectively represent quality
Because of subnumber, initial value, time, reaction rate constant.
6. the method for predicting fresh-water fishes shelf life according to claim 5, it is characterised in that：
In step (4), with Arrhenius equationsK in formula0：Frequency factor；EA：Activation energy, unit are
J/mol；T：Temperature, unit K；R：Gas constant, 8.3144J/ (molK), analysis temperature T and speed response constant k, will
Arrhenius equations turned is lnk=lnk0-(EA/ RT), 1nk maps 1/T to obtain a straight line, and reaction is found out by straight slope
Activation energyA, frequency factor k is found out by intercept0, the frequency factor k of methyl disulfide, 3- methyl-1-butanols and 1-POL0
With reaction activity EARespectively 4.4 × 108、1.35×108、1.65×109And 48.087kJmol-1、45.286kJ·
mol-1、50.828kJ·mol-1。
7. the method for predicting fresh-water fishes shelf life according to claim 6, it is characterised in that：
In step (5), according to methyl disulfide, 3- methyl-1-butanols and 1-POL under 4 reserve temperatures obtained k0
Value and EAValue, is obtained by regression equation and Arrhenius equationsCalculate shelf
Phase prediction modelThe k that will be calculated0With reaction activity EAThis model is substituted into, is obtained
Shelf life forecasting model based on methyl disulfide, 3- methyl-1-butanols and 1-POL；
8. the method for predicting fresh-water fishes shelf life according to claim 1, it is characterised in that：
It is to use shelf using the Analyses Methods for Sensory Evaluation Results of back fish block as shelf life terminal under different reserve temperatures in step (6)
The predicted value of phase prediction model verifies shelf life with measured value.
9. the method for predicting fresh-water fishes shelf life according to claim 1, it is characterised in that：
For the fresh-water fishes of fat content≤5%, the shelf life forecasting model established using methyl disulfide and 3- methyl n-butyl alcohols
Carry out forecasting shelf life；For fat content>5% fresh-water fishes, using 1-POL establish shelf life forecasting model into
Row forecasting shelf life.
10. according to the method for predicting fresh-water fishes shelf life described in claim 1 to 9 any claim, it is characterised in that：
The fresh-water fishes are perch, Channel-catfish fishes, mandarin fish, Culter fishes, grass carp, black carp, bighead, silver carp, carp, crucian or bream.
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