CN103293045A - Rapid analysis method for freshness of mantis shrimps under cold-storage condition - Google Patents

Abstract

The invention relates to the field of food storage and detection and discloses a rapid analysis method for the freshness of mantis shrimps under the cold-storage condition. An electronic nose with a plurality of sensor arrays is used. The sensor arrays comprise a sulfide sensor, a hydrogen sensor, an ammonia-gas sensor, an alcohol sensor, an alkane sensor, a methane-propane-butane sensor, a propane-butane sensor and a nitric-oxide sensor. The rapid analysis method disclosed by the invention has the advantages that mantis shrimp samples can be detected rapidly, the pertinence is strong, the result is accurate and reliable, the detection result can be obtained without damaging the samples, and the applicability is strong.

Description

Mantis shrimp freshness rapid analysis under the refrigerated condition

Technical field

The present invention relates to the food storage detection range, particularly mantis shrimp freshness rapid analysis under a kind of refrigerated condition.

Background technology

Aquatic products are one of important component parts of human foods, and characteristics such as, delicious flavour nutritious because of it, kind are various are loved by the people.Mantis shrimp is a kind of of aquatic products, mainly originates in the shallow sea in temperate zone, and in Bohai Sea of China, ground such as South Sea, mantis shrimp output is bigger, is a kind of important economic fishery resources.Mantis shrimp is Fresh ﹠ Tender in Texture, and is delicious, mouthfeel is good, be of high nutritive value, and not only rich in protein, and also its amino acid whose composition is very good, and 8 kinds of contained essential amino acid amounts comparison shrimp are also high.Simultaneously, the various trace elements that is rich in the mantis shrimp meat benefits to body metabolism.Therefore, mantis shrimp is a kind of good nutraceutical, is subjected to liking and attention of people day by day.

Yet, identical with most of aquatic products, mantis shrimp moisture, protein content height, in the transportation storage after catching, easily grow each quasi-microorganism and corruption takes place, cause freshness decline, quality to reduce, cause the edible safety problem then, cause the eater clinical diseases such as dizziness, vomiting, diarrhoea to occur, human health is threatened.Therefore, research mantis shrimp freshness situation of change is to guaranteeing the mantis shrimp quality, guaranteeing that edible safety has the meaning that can not despise.Though China has freshness deliberated index and the corresponding detection method of shrimps at present, but still has its restriction and imperfection part, and also there are not a kind of index and method can be used for the special freshness of judging mantis shrimp.What method does of this selection fast and effeciently detect the freshness variation of mantis shrimp so, to determine its quality?

The classic method that detects the aquatic products freshness has organoleptic detection, physics and chemistry detection and microorganism detection etc., above method is widely used as the conventional sense means mostly, but still exist inevitably such as destroy sample, complicated operation, consuming time long, be subject to weak point such as subjective influence, can't satisfy the requirement of freshness, quality fast detecting.In addition, mantis shrimp is a kind of aquatic products that comparatively are easy to generate corruption, but because the shape of a series of volatile matter that its decay process produces is not obvious, mix mutually with other aquatic products easily, therefore use traditional detection method to detect its freshness and storage time effectively, the needed sense cycle of conventional detection is longer simultaneously, can't be rapidly the freshness of mantis shrimp product be detected, detect resulting freshness and often lag behind the current freshness of mantis shrimp product, the quality monitoring in product later stage is had certain negative effect.Therefore be necessary to develop a kind of with strong points, the method that can carry out fast detecting to freshness and the storage time of mantis shrimp product.

Summary of the invention

The present invention is directed to prior art can't be effectively detect freshness and the storage time of mantis shrimp product, shortcomings such as sense cycle is long, provide a kind of can be quick, the novel rapid analysis that the freshness that is in 4 ℃ of mantis shrimp products under the stored under refrigeration situation is detected exactly.

For achieving the above object, the present invention can take following technical proposals:

Mantis shrimp freshness rapid analysis under the refrigerated condition, use has the Electronic Nose of a plurality of sensor arraies, described sensor display comprises: sulfide sensor, hydrogen gas sensor, ammonia gas sensor, ethanol class sensor, alkanes sensor, the first third butane sensor, the third butane sensor, NOx sensor comprise following concrete steps:

1) the mantis shrimp sample is stored under 4 ℃ of deepfreeze states, take out two every day at random from the mantis shrimp sample, the appearance change situation of record mantis shrimp sample every day;

2) the mantis shrimp sample that step 1 is taken out is decaptitated and is shelled, and gets edible and partly shreds standbyly, takes by weighing the mantis shrimp sample 3-4g of above-mentioned chopping, mix the 0.5gMgO powder after, place in the vapourizing furnace; Adding 50ml concentration in the triangle receiving bottle is the H3BO3 of 2%wt, drips mixed indicator to wherein dripping 2-3, the receiving tube of the distiller of vapourizing furnace is inserted in the triangle receiving bottle, and allow the mouth of pipe of receiving tube be immersed in the H3BO3 solution; Open the steam cock of vapourizing furnace, begin distillation, when treating that liquid level in the triangle receiving bottle is higher than 15ml the triangle receiving bottle is moved down, make the receiving tube mouth of pipe leave liquid level after, continue distillation 0.5m; After stopping distillation, the H3BO3 solution flushing receiving tube mouth of pipe with 2%wt takes off the triangle receiving bottle, carries out titration with 0.1mol/L hydrochloric acid, keeps 30s colour-fast after the arrival titration end-point, reads the amount of the hydrochloric acid that consumes in the titration;

3) from the mantis shrimp sample of step 1, take out multiple sample, every part of weight is 25g ± 3g, described sample is placed the polyethylene specimen bottle respectively, seal with preservative film and bungee, under the room temperature sample bottle is sealed 30min, the sample introduction syringe needle of Electronic Nose and the air intake opening of air cleaner are inserted sample bottle respectively, the unlocking electronic nose sucks the head space gas in the sample bottle air chamber of Electronic Nose, the absorption time of Electronic Nose is 50s, after a sample detection finishes, feed pure air by air cleaner;

4) use principal component analysis (PCA) step 3 gained detection data are analyzed, and obtain the analysis result of the freshness of described mantis shrimp sample; Step 3 gained is detected data input accidental resonance model analyze, detection by electronic nose data input accidental resonance model is obtained signal-to-noise ratio peak, with the following forecast model of signal-to-noise ratio peak input

R=0.95028 obtains predicting the outcome of sample freshness.

As preferably, the principal component analysis (PCA) of described step 4 comprises following concrete steps:

For a test sample, observe p component variable x ₁, x ₂... x _p, then the data information matrix of n sample is: $X=\left(\begin{array}{cccc}{x}_{11}& x_{12}& \&CenterDot;\&CenterDot;\&CenterDot;& x_{1p}\\ x_{21}& x_{22}& \&CenterDot;\&CenterDot;\&CenterDot;& x_{2p}\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ x_{n1}& x_{\mathrm{<figure-callout\; id="2"\; label="n"\; filenames="130627095427.png"\; state="\{\{state\}\}">n</figure-callout>}2}& \&CenterDot;\&CenterDot;\&CenterDot;& x_{\mathrm{np}}\end{array}\right)=(x_1,x_2,\&CenterDot;\&CenterDot;\&CenterDot;x_p),$ Wherein, $x_j=\left(\begin{array}{c}{x}_{1j}\\ x_{2j}\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ x_{\mathrm{nj}}\end{array}\right),$ j＝1,2,…p；

P component variable comprehensively become p generalized variable Fj, (j=1,2 ..., p):

$\left\{\begin{array}{c}{\mathrm{<figure-callout\; id="1"\; label="F"\; filenames="130627095427.png"\; state="\{\{state\}\}">F</figure-callout>}}_1=a_{11}{x}_1+a_{12}{x}_2+\&CenterDot;\&CenterDot;\&CenterDot;+a_{1p}{x}_{\mathrm{<figure-callout\; id="2"\; label="p\; F"\; filenames="130627095427.png"\; state="\{\{state\}\}">p</figure-callout>}}& \\ F_{}{}_2=a_{21}{x}_1+a_{22}{x}_2+\&CenterDot;\&CenterDot;\&CenterDot;+a_{2p}{x}_p\\ \&CenterDot;\&CenterDot;\&CenterDot;\\ F_p=a_{p1}{x}_1+a_{p2}{x}_2+\&CenterDot;\&CenterDot;\&CenterDot;{+a}_{\mathrm{pp}}{x}_p\end{array}\right.,$ Wherein, F _i, F _jMutually uncorrelated (i ≠ j, i, j=1,2 ..., p), F _iVariance greater than F _jVariance (i〉j), a _K1 ²+ a _K2 ²+ ... + a _Kp ²=1k=1,2 ... p.;

With F1, F2 ..., Fp is defined as first principal component successively, Second principal component, ..., p major component obtains the major component matrix of coefficients $\text{A=}\left(\begin{array}{cccc}{a}_{11}& a_{12}& \&CenterDot;\&CenterDot;\&CenterDot;& a_{1p}\\ a_{21}& a_{22}& \&CenterDot;\&CenterDot;\&CenterDot;& a_{2p}\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ a_{p1}& a_{\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="130627095427.png"\; state="\{\{state\}\}">p</figure-callout>}2}& \&CenterDot;\&CenterDot;\&CenterDot;& a_{\mathrm{pp}}\end{array}\right)=\left(\begin{array}{c}{a}_1\\ {\mathrm{<figure-callout\; id="2"\; label="a"\; filenames="130627095427.png"\; state="\{\{state\}\}">a</figure-callout>}}_2\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ a_p\end{array}\right).$

As preferably, in the described step 3, the sealing time lengthening of sample bottle is 1h under the room temperature.

Compared with prior art the invention has the beneficial effects as follows: the present invention is directed to the specificity gas that the mantis shrimp sample volatilizes under 4 ℃ of low-temperature storage conditions, select gas sensor array for use, and structure signal excitation and acquisition system, be exclusively used in the detection of mantis shrimp sample storage life, overcome because the influence that the unique texture of mantis shrimp detects existing electric nasus system, overcome the freshness that existing electric nasus system can't accurately obtain the mantis shrimp product, be difficult to the defective that the shelf-life of mantis shrimp product is predicted.

The present invention detects the mantis shrimp product by the Electronic Nose with a plurality of sensor arraies, testing process does not have invasive, can not cause damage to the mantis shrimp product, is applicable to transportation, real-time, fast detecting in the storage, its detection method has stronger applicability.

The further beneficial effect of the method for the invention is: by prolonging the sealing and standing time of mantis shrimp sample, improved the concentration of volatile ingredient in the head space gas, the sensitivity of gas sampling and the accuracy of detection data have been improved, reduced the error in the data acquisition, made testing result more accurate.

Description of drawings

Fig. 1 is the structural representation of Electronic Nose.

Fig. 2 is the TVB-N change curve of 4 ℃ of following mantis shrimp samples among the embodiment 1.

Fig. 3 is the Electronic Nose response curve of 4 ℃ of following mantis shrimp samples among the embodiment 1.

Fig. 4 is 4 ℃ of principal component analysis (PCA) result schematic diagrams of descending mantis shrimp sample under the different storage times among the embodiment 1.

Embodiment

The present invention is described in further detail below in conjunction with embodiment.

Embodiment 1

Experimental raw: fresh mantis shrimp, available from market.The selection build is close, and springing is flexible, and the mantis shrimp alive that limbs are complete is experimental raw, and the average weight of mantis shrimp is 13g ± 2g.

Experimental article: freshness protection package, preservative film, polyethylene specimen bottle, bungee.(above article all pass through ultraviolet-sterilization before using).

Experiment reagent:

(1) NaOH (Tianjin Da Mao chemical reagent factory analyzes pure)

(2) dense HCl (huge state, Quzhou reagent company limited analyzes pure)

(3) H3BO3 (Dongguan Dongjiang chemical reagent company limited analyzes pure)

(4) MgO (the logical wide fine chemistry industry in Beijing company analyzes pure)

(5) mixed indicator: (Tianjin benchmark chemical reagent company limited)+1g/L methylene blue (Shanghai San'aisi Reagent Co., Ltd.) (1:1) for the 2g/L methyl red

(6) straight alcohol (Chemical Reagent Co., Ltd., Sinopharm Group analyzes pure)

(7) ultrapure water

Experimental apparatus:

(1) the double single face clean work station of SW-CJ-2FD type (containing uviol lamp) (Purifying Equipment Co., Ltd., Suzhou)

(2) R134a refrigerator-freezer (Qingdao HaiEr Co., Ltd)

(3) DW-FL362 type superfreeze reserve tank (U.S. water chestnut low temperature Science and Technology Ltd. of middle section)

(4) kjeldahl apparatus (Shanghai flood discipline instrument and equipment company limited) KDN-08A(04A)

(5) DIGITAL IXUS40 digital camera (company limited of Canon)

(6) Electronic Nose, structure mainly comprise three parts as shown in Figure 1---signals collecting, conditioning and transmission unit, the air chamber at sensor array and place thereof, and air feed propulsion system.The core devices of data acquisition, conditioning and transmission unit adopts embedded microcontroller, can realize functions such as collecting sensor signal, transmission and pump valve unlatching control.Sensor array is made of 8 kinds of semiconductor gas sensors that Japanese Figaro company produces, sensor characteristic is as shown in table 1, and sensor 1-8 respectively is sulfide sensor, hydrogen gas sensor, ammonia gas sensor, ethanol class sensor, alkanes sensor, the first third butane sensor, the third butane sensor, NOx sensor.The air chamber of each sensor is independently, and air chamber is made by exotic material, and gas can evenly pump into the air chamber of each sensor.The advantage of doing like this is to avoid to help to improve accuracy of detection owing to the phase mutual interference that an air chamber forms of coexisting of a plurality of sensors.The air feed propulsion system comprise devices such as sampling pump, scavenging pump, electromagnetic gas valve.

Table 1 Electronic Nose gas sensor array constitutes

Sample pretreatment:

The fresh mantis shrimp of buying is dirty with clear water removal surface, be placed on and cause its death in the frozen water.With the freshness protection package packing mantis shrimp that passes through ultraviolet-sterilization, be stored under 4 ℃ the temperature, take for experiment every day.

Record mantis shrimp appearance change:

At random take out two the mantis shrimp sample under 4 ℃ of storage requirements every day, respectively one positive instead put, and takes with camera, notes the appearance change situation of mantis shrimp sample every day.

TVB-N detects:

Use the mantis shrimp sample TVB-N content under kjeldahl apparatus mensuration different reserve temperatures every day.The required sample grab sample under the situation of mutually noninterfere of each experiment.Mantis shrimp decaptitated shell, get edible muscle parts, shred standby.The mantis shrimp meat and the 0.5gMgO powder that take by weighing 3-4g are put into vapourizing furnace jointly, and it is installed on the azotometer, open water inlet switch, add the distilled water of about 80mL.In 250mL triangle receiving bottle, add 2%H ₃BO ₃About 50mL drips mixed indicator to wherein dripping 2-3, in the receiving tube insertion triangular flask with distiller, and allows the mouth of pipe be immersed in H ₃BO ₃In the solution.Open the steam switch and begin distillation, when treating that the receiving bottle liquid level is higher than 150mL receiving bottle taken off and move, make receiving tube leave liquid level, continue distillation half a minute, use H ₃BO ₃Flush out gas port, take off receiving bottle then, carry out titration with the hydrochloric acid of concentration about 0.1mol/L that has prepared in advance, titration end-point is that solution becomes lavender by grass green, and keeps 30s colour-fast.Do blank test simultaneously.TVB-N value according to hydrochloric acid consumption and blank value calculating mantis shrimp.Computing formula is as follows:

(1) in the formula, V ₁Be HCl reading before the titration, mL; V ₂Be HCl reading after the titration, mL; V _EmptyBe the HCl volume that consumes in the blank assay, mL; c _HClBe HCl concentration, mol/L; M is the mantis shrimp meat quality that takes by weighing, g.

Detection by electronic nose:

Every day, each took out 5 duplicate samples at random from preserving in 4 ℃ mantis shrimp sample, and every part of weight is 25g ± 3g.Other gets 10 polyethylene specimen bottles, with each 5 parts of the mantis shrimps under two temperature, put into bottle, seal with preservative film and bungee, respectively the reserve temperature before bottle shows the mantis shrimp sample and label: 4 ℃ No. 1,4 ℃ No. 2,4 ℃ No. 3,4 ℃ No. 4,4 ℃ No. 5.At room temperature with 10 bottle seal 30min, to accumulate certain volatile matter, just Electronic Nose sample introduction syringe needle inserts in the sample bottle then, inserts the air cleaner that activated charcoal is housed simultaneously.The unlocking electronic nose contacts the head space gas suction air chamber of sample bottle with sensor, the absorption time is 50 seconds.Behind the intact sample of every detection, feed pure air with cleaning sensor, make it get back to the baseline state, then carry out the detection of next sample.The parallel detection of every duplicate samples 3 times.

Data are handled:

After the mantis shrimp TVB-N data of different storage time draw as calculated, use the mapping of Origin7.0 software, obtain the variation broken line graph of the total volatile basic nitrogen of mantis shrimp in storage period.

The detection data of Electronic Nose are the space matrixs of a multidimensional, principal component analysis (PCA) is handled means as a kind of characteristic signal of classics, the multi-dimensional matrix data can be carried out dimension-reduction treatment, keep a few and can represent the major component of former characteristics of variables as the eigenwert of sample, effectively reduce the complicacy that data are handled.Its mathematical model is as follows:

For a sample data, observe p variable x ₁, x ₂... x _p, the data information battle array of n sample is:

$X=\left(\begin{array}{cccc}{x}_{11}& x_{12}& \&CenterDot;\&CenterDot;\&CenterDot;& x_{1p}\\ x_{21}& x_{22}& \&CenterDot;\&CenterDot;\&CenterDot;& x_{2p}\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ x_{n1}& x_{\mathrm{<figure-callout\; id="2"\; label="n"\; filenames="130627095427.png"\; state="\{\{state\}\}">n</figure-callout>}2}& \&CenterDot;\&CenterDot;\&CenterDot;& x_{\mathrm{np}}\end{array}\right)=(x_1,x_2,\&CenterDot;\&CenterDot;\&CenterDot;x_p),$ Wherein: $x_j=\left(\begin{array}{c}{x}_{1j}\\ x_{2j}\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ x_{\mathrm{nj}}\end{array}\right),$ j＝1,2,…p，

Principal component analysis (PCA) is exactly that p observational variable comprehensively become p new variable (generalized variable), namely $\left\{\begin{array}{c}{\mathrm{<figure-callout\; id="1"\; label="F"\; filenames="130627095427.png"\; state="\{\{state\}\}">F</figure-callout>}}_1=a_{11}{x}_1+a_{12}{x}_2+\&CenterDot;\&CenterDot;\&CenterDot;+a_{1p}{x}_{\mathrm{<figure-callout\; id="2"\; label="p\; F"\; filenames="130627095427.png"\; state="\{\{state\}\}">p</figure-callout>}}& \\ F_{}{}_2=a_{21}{x}_1+a_{22}{x}_2+\&CenterDot;\&CenterDot;\&CenterDot;+a_{2p}{x}_p\\ \&CenterDot;\&CenterDot;\&CenterDot;\\ F_p=a_{p1}{x}_1+a_{p2}{x}_2+\&CenterDot;\&CenterDot;\&CenterDot;{+a}_{\mathrm{pp}}{x}_p\end{array}\right.,$ Be abbreviated as: F _j=α _J1x ₁+ α _J2x ₂+ ... + α _Jpx _p, j=1,2 ..., p.

Require above model need meet following condition simultaneously:

1. F _i, F _jMutually uncorrelated (i ≠ j, i, j=1,2 ..., p)

2. F ₁Variance greater than F ₂Variance, greater than F ₃Variance, and the like

③a _k1 ²+a _k2 ²+…+a _kp ²＝1k＝1,2,…p.

So, claim F ₁Be first principal component, F ₂Be Second principal component,, the rest may be inferred, and p major component arranged.Major component is principal component again.Here a _IjWe are called the major component coefficient.

Above model is as follows with matrix representation: F=AX, wherein $F=\left(\begin{array}{c}{F}_1\\ {\mathrm{<figure-callout\; id="2"\; label="F"\; filenames="130627095427.png"\; state="\{\{state\}\}">F</figure-callout>}}_2\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ F_p\end{array}\right),X=\left(\begin{array}{c}{x}_1\\ x_2\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ x_p\end{array}\right)$

$\text{A=}\left(\begin{array}{cccc}{a}_{11}& a_{12}& \&CenterDot;\&CenterDot;\&CenterDot;& a_{1p}\\ a_{21}& a_{22}& \&CenterDot;\&CenterDot;\&CenterDot;& a_{2p}\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ a_{p1}& a_{\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="130627095427.png"\; state="\{\{state\}\}">p</figure-callout>}2}& \&CenterDot;\&CenterDot;\&CenterDot;& a_{\mathrm{pp}}\end{array}\right)=\left(\begin{array}{c}{a}_1\\ a_2\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ a_p\end{array}\right),$ Wherein A is called the major component matrix of coefficients.

Mantis shrimp TVB-N and appearance change result and analysis:

The mantis shrimp sample total volatile basic nitrogen that is stored under 4 ℃ the results are shown in Figure 2.By picture as can be seen, in 7 days period of storage, the total volatile basic nitrogen numerical value of mantis shrimp sample constantly rises, and day0 is 13.7mgN/100g, has surpassed 30mgN/100g after two days, and numerical value still continues to rise thereafter, finally surpasses 80mgN/100g.This phenomenon and the mantis shrimp corrupt situation after catching has substantial connection, a kind of as aquatic products, mantis shrimp is rich in protein, because the growth and breeding of bacterium and the effect of enzyme, protein is decomposed and the volatile alkaline nitrogen substances of tool such as generation amine and ammonia, along with the growth of time, mantis shrimp decomposes the total volatile basic nitrogen that produces and also progressively rises.4 ℃ is a refrigerated storage temperature commonly used, mantis shrimp is preserved the decline that can delay freshness under this temperature to a certain extent, but the activity of the physiological activity of a lot of bacteriums and part enzyme is still more active under 4 ℃, so the numerical value of TVB-N presents comparatively significantly ascendant trend.According to China GB2733-2005 aquatic foods, freeze animality aquatic products hygienic standard, mantis shrimp is as a kind of seawater shrimps, the preliminary corrupt standard of its total volatile basic nitrogen is 30mgN/100g, therefore, here the total volatile basic nitrogen that mantis shrimp is produced reaches 30mgN/100g as the criterion of mantis shrimp freshness, it seems that with this mantis shrimp sample is at day2, just exceeded this boundary standard in namely the 3rd day.

Mantis shrimp Electronic Nose result and analysis:

The response of Electronic Nose sensor array as shown in Figure 3.Response all concentrates on the initial point place when detecting beginning, and along with the suction of gas, gas acts on the Electronic Nose sensor array, makes each sensor the response of different sizes occur.Response the detection initial stage in time increase and rise, arrive and tend towards stability after saturated, significant change does not take place in time.The response of sensor 4, sensor 1, sensor 5, sensor 7 and sensor 8 is comparatively obvious, wherein the variation of sensor 4 is the most remarkable, the composition that is alcohol in the escaping gas of mantis shrimp, sulfide, hydrocarbon component gas, alkane and oxides of nitrogen is in the majority, its existence can by sensor sensing sense.Mantis shrimp is caught in the dead process in back, a series of chemical change can take place, as protein decomposition, fat oxidation, color and luster go down, stink appearance etc., therefore in storage process, the mantis shrimp sample is corrupt decomposition gradually under each factor effect, produces the escaping gas of complicated component simultaneously.

In order to understand the Changing Pattern of volatility metabolic product in the mantis shrimp freshness decline process, utilize principal component analysis (PCA) by the mode of dimensionality reduction 7 days sample system raw data to be analyzed, this paper selects 2 former data of major component match for use, and the result is as shown in Figure 4.

The analysis result of PCA shows, the contribution rate that first principal component is distinguished is 92.68%, and the contribution rate that Second principal component, is distinguished is that the contribution rate summation that 4.17%, two major component is distinguished is 96.85%, greater than 90%, show that these two major components have represented the main information characteristics of sample substantially.As seen from Figure 4,5 of every day parallel laboratory test data points can be divided into three big blocks.Day0, day1 can be considered fresh mantis shrimp, the point of their point and other fates has obvious differentiation, the total volatile basic nitrogen numerical value that contact is above mentioned, this mantis shrimp of two days shows that Electronic Nose can distinguish fresh mantis shrimp and the mantis shrimp that surpasses the freshness standard exactly preferably still in the fresh boundary of shrimp body is judged by country.Day2, day3, day4 and day5, day6 can divide into two parts, and this two-part differentiation is so obvious not as the differentiation of fresh mantis shrimp, but assembles relatively in the zone, can make a distinction with other samples.Simultaneously, from the overall process that the mantis shrimp freshness descends, the data point of all samples is whole on first principal component PC1 main shaft to be moved along negative direction of principal axis, illustrates that the escaping gas of mantis shrimp under this temperature presents good release rule.The PCA analysis chart of Fig. 4 shows that there is rule in the mantis shrimp escaping gas of different freshnesss and than significant difference, and has proved that fully the Electronic Nose analytical technology has enough sensitivity that these escaping gases are carried out cluster and differentiation.

In addition, in order to carry out a prediction to the freshness of mantis shrimp, the detection by electronic nose data directly can be imported the accidental resonance model and analyze output signal-to-noise ratio, and snr value and storage time carried out the linear fit analysis, obtain the storage time forecast model.Accidental resonance is used widely in fields such as Detection of Weak Signals, and this model comprises three factors: bistable state (or multistable) system, input signal and noise source.Usually in the bistable state potential well, by power-actuated overdamping Brownian movement of cycle particle the accidental resonance characteristic is described with one.

$\frac{\mathrm{dx}}{\mathrm{dt}}=-\frac{\mathrm{dV}\left(x\right)}{\mathrm{dx}}+w\sin \left(\mathrm{\&pi;}{f}_{0}t\right)+I\left(t\right)+\sqrt{6D}\mathrm{\&xi;}\left(t\right)---\left(1\right)$

V (x) is non-linear potential function, ξ (t) is white Gaussian noise, its autocorrelation function is: E[ξ (t) ξ (0)]=2D δ (t), w is input signal strength, I (t) is black cloth human relations detection by electronic nose data mean value (8 sensor passage detected values of Electronic Nose is added and average afterwards), f ₀Be frequency modulating signal, D is noise intensity, and a and b are real parameters,

$V\left(x\right)=-\frac{1}{4}{\mathrm{<figure-callout\; id="2"\; label="ax"\; filenames="130627095427.png"\; state="\{\{state\}\}">ax</figure-callout>}}^2+{\mathrm{bx}}^4---\left(2\right)$

Therefore formula (1) can be rewritten as:

$\frac{\mathrm{dx}}{\mathrm{dt}}=\frac{1}{2}\mathrm{ax}-4b{x}^3+w\sin \left(\mathrm{\&pi;}{f}_{0}t\right)+I\left(t\right)+\sqrt{6D}\mathrm{\&xi;}\left(t\right)---\left(3\right)$

At present the most general reaction accidental resonance characteristic is signal to noise ratio (S/N ratio), and we are defined as signal to noise ratio (S/N ratio) here:

$\mathrm{SNR}=2\left[\underset{\mathrm{\&Delta;\&omega;}\&RightArrow;0}{\lim }\underset{\mathrm{\&Omega;}-\mathrm{\&Delta;\&omega;}}{\overset{\mathrm{\&Omega;}+\mathrm{\&Delta;\&omega;}}{\&Integral;}}S\left(\mathrm{\&omega;}\right)\mathrm{d\&omega;}\right]/S_N\left(\mathrm{\&Omega;}\right)---\left(4\right)$

S (ω) is signal spectral density, S _N(Ω) be the interior noise intensity of signal frequency range.

Along with the increase of storage time, system's output signal-to-noise ratio is in continuous increase as can be seen; And under different excitation noise intensity, output signal-to-noise ratio is also different.

We do the linear fit analysis and obtain a forecast model when choosing signal to noise ratio (S/N ratio) to peaking: $\mathrm{Time}=\frac{\mathrm{MaxSNR}+57.32874}{0.74538},R=0.95028,$ The linear dependence of this forecast model is better.

The detection by electronic nose data are obtained signal-to-noise ratio peak MaxSNR=-53.51239 by the output of accidental resonance model, the above-mentioned forecast model of substitution, obtaining predicted value is 5.12, the storage time that can judge the mantis shrimp sample accordingly is 5 days, and the current actual storage time of this predicted value and mantis shrimp sample matches.But contrast the reality storage time of above-mentioned mantis shrimp sample, namely can obtain the residual storage time of this sample, reach the purpose of accurately predicting.

In a word, the above only is preferred embodiment of the present invention, and all equalizations of doing according to the present patent application claim change and modify, and all should belong to the covering scope of patent of the present invention.

Claims (3)

1. mantis shrimp freshness rapid analysis under the refrigerated condition, it is characterized in that, use has the Electronic Nose of a plurality of sensor arraies, described sensor display comprises: sulfide sensor, hydrogen gas sensor, ammonia gas sensor, ethanol class sensor, alkanes sensor, the first third butane sensor, the third butane sensor, NOx sensor comprise following concrete steps:

1) the mantis shrimp sample is stored under 4 ℃ of deepfreeze states, take out two every day at random from the mantis shrimp sample, the appearance change situation of record mantis shrimp sample every day;

2) the mantis shrimp sample that step 1 is taken out is decaptitated and is shelled, and gets edible and partly shreds standbyly, takes by weighing the mantis shrimp sample 3-4g of above-mentioned chopping, mix the 0.5gMgO powder after, place in the vapourizing furnace; Adding 50ml concentration in the triangle receiving bottle is the H of 2%wt ₃BO ₃, drip mixed indicator to wherein dripping 2-3, the receiving tube of the distiller of vapourizing furnace is inserted in the triangle receiving bottle, and allow the mouth of pipe of receiving tube be immersed in H ₃BO ₃In the solution; Open the steam cock of vapourizing furnace, begin distillation, when treating that liquid level in the triangle receiving bottle is higher than 15ml the triangle receiving bottle is moved down, make the receiving tube mouth of pipe leave liquid level after, continue distillation 0.5m; After stopping distillation, with the H of 2%wt ₃BO ₃The solution flushing receiving tube mouth of pipe takes off the triangle receiving bottle, carries out titration with 0.1mol/L hydrochloric acid, keeps 30s colour-fast after the arrival titration end-point, reads the amount of the hydrochloric acid that consumes in the titration;

3) from the mantis shrimp sample of step 1, take out multiple sample, every part of weight is 25g ± 3g, described sample is placed the polyethylene specimen bottle respectively, seal with preservative film and bungee, under the room temperature sample bottle is sealed 30min, the sample introduction syringe needle of Electronic Nose and the air intake opening of air cleaner are inserted sample bottle respectively, the unlocking electronic nose sucks the head space gas in the sample bottle air chamber of Electronic Nose, the absorption time of Electronic Nose is 50s, after a sample detection finishes, feed pure air by air cleaner;

4) use principal component analysis (PCA) step 3 gained detection data are analyzed, and obtain the analysis result of the freshness of described mantis shrimp sample; Step 3 gained is detected data input accidental resonance model analyze, detection by electronic nose data input accidental resonance model is obtained signal-to-noise ratio peak, with the following forecast model of signal-to-noise ratio peak input

R=0.95028 obtains predicting the outcome of sample freshness.

2. according to mantis shrimp freshness rapid analysis under the described refrigerated condition of claim 1, it is characterized in that the principal component analysis (PCA) of described step 4 comprises following concrete steps:

For a test sample, observe p component variable x ₁, x ₂... x _p, the data information square of n sample then

Battle array is: $X=\left(\begin{array}{cccc}{x}_{11}& x_{12}& \&CenterDot;\&CenterDot;\&CenterDot;& x_{1p}\\ x_{21}& x_{22}& \&CenterDot;\&CenterDot;\&CenterDot;& x_{2p}\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ x_{n1}& x_{n2}& \&CenterDot;\&CenterDot;\&CenterDot;& x_{\mathrm{np}}\end{array}\right)=(x_1,x_2,\&CenterDot;\&CenterDot;\&CenterDot;x_p),$ Wherein, $x_j=\left(\begin{array}{c}{x}_{1j}\\ x_{2j}\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ x_{\mathrm{nj}}\end{array}\right),$ j＝1,2,…p；

P component variable comprehensively become p generalized variable Fj, (j=1,2 ..., p):

$\left\{\begin{array}{c}{F}_1=a_{11}{x}_1+a_{12}{x}_2+\&CenterDot;\&CenterDot;\&CenterDot;+a_{1p}{x}_p\\ F_2=a_{21}{x}_1+a_{22}{x}_2+\&CenterDot;\&CenterDot;\&CenterDot;+a_{2p}{x}_p\\ \&CenterDot;\&CenterDot;\&CenterDot;\\ F_p=a_{p1}{x}_1+a_{p2}{x}_2+\&CenterDot;\&CenterDot;\&CenterDot;{+a}_{\mathrm{pp}}{x}_p\end{array}\right.,$ Wherein, F _i, F _jMutually uncorrelated (i ≠ j, i, j=1,2 ..., p), F _i

Variance is greater than F _jVariance (i〉j), a _K1 ²+ a _K2 ²+ ... + a _Kp ²=1k=1,2 ... p.;

With F ₁, F ₂..., F _pBe defined as first principal component successively, Second principal component, ..., p master

Composition obtains the major component matrix of coefficients $\text{A=}\left(\begin{array}{cccc}{a}_{11}& a_{12}& \&CenterDot;\&CenterDot;\&CenterDot;& a_{1p}\\ a_{21}& a_{22}& \&CenterDot;\&CenterDot;\&CenterDot;& a_{2p}\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;& \&CenterDot;& \&CenterDot;\\ a_{p1}& a_{p2}& \&CenterDot;\&CenterDot;\&CenterDot;& a_{\mathrm{pp}}\end{array}\right)=\left(\begin{array}{c}{a}_1\\ a_2\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ a_p\end{array}\right).$

3. mantis shrimp freshness rapid analysis under the refrigerated condition according to claim 1 is characterized in that, in the described step 3, the sealing time lengthening of sample bottle is 1h under the room temperature.

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