CN105807017A - Method for discriminating ham grades by using electronic nose - Google Patents
Method for discriminating ham grades by using electronic nose Download PDFInfo
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- CN105807017A CN105807017A CN201410841815.2A CN201410841815A CN105807017A CN 105807017 A CN105807017 A CN 105807017A CN 201410841815 A CN201410841815 A CN 201410841815A CN 105807017 A CN105807017 A CN 105807017A
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- petaso
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Abstract
The invention discloses a method for discriminating ham grades by using an electronic nose. The method comprises the following steps: S101, subjecting ham to frozen storage at a temperature of -20 DEG C, unfreezing the ham at a temperature of 4 DEG C before discrimination, removing a fat layer and a skin layer, then dicing the ham, carrying out uniform mixing, then carrying out mashing so as to obtain form a sample and sealing the sample for subsequent usage; S102, placing 1.00 +/- 0.01 g of the sample into a sample introduction bottle, carrying out balancing at a headspace temperature of 40 to 60 DEG C for 300 to 500 s, and with clean dry air as a carrier, carrying out sample introduction of 400 to 700 [mu]L of gas into the electronic nose by using an injection needle; and S103, after gas sample introduction, allowing the electronic nose to acquire data for 115 to 125 s so as to obtain discrimination result data. The method provided by the invention can rapidly discriminate ham of different grades and from different producing areas, and a novel scientific method and bases are provided for detection of products of the ham industry.
Description
Technical field
The invention belongs to food inspection inspection technology field, particularly relate to a kind of Petaso grade discrimination method.
Background technology
Petaso is the conventional dry marinated meat product that China is famous.All the time, for the place of production and the commonly used sensory evaluation method of ranking of Petaso, this method subjectivity is strong, and poor repeatability is subject to the impact of sense organ person's individual physiological, psychology and experience.And the gas analysis arrangement of routine, such as gas chromatography and mass spectromentry (GC-MS) although can be used to measure abnormal smells from the patient composition and concentration, but the relation between they and aroma effect cannot be set up, and there is process analysis time, the defect such as sample nondestructive degree reduction.Owing to food taste and flavor is increasingly paid attention to by people, ham quality and Sensory Evaluation are had higher requirement；Meanwhile, increase along with Petaso manufacturer, good buckwheat is uneven, the product quality problem such as mix the genuine with the fictitious also gets more and more, some distributors pretend to be a Petaso to sell to reap staggering profits with the Petaso of other son of inferior brand, pretend to be Petaso even with butcher's meat, therefore in the urgent need to one objective, fast and effectively method evaluate Petaso grade.
Electronic Nose is the instrument that a kind of analysis, identification and detection of complex smell taste and volatile ingredient, it analyzes what obtain is not the qualitative and quantitative result of certain or certain several composition in sample, but the Global Information of volatile ingredient in sample, test result can carry out systematization and scientific compareing with the sensory evaluation of people, can overcome again a lot of drawbacks of sensory evaluation simultaneously.On the other hand compared with conventional analytical tool (such as chromatograph, spectrogrph etc.), it is objective, sensitive, accurate that Electronic Nose has, and can realize Non-Destructive Testing, and its application attracts widespread attention.
This method is namely based on Electronic Nose and different grades of Petaso is differentiated and classification, to set up the quick nondestructive evaluation system of a set of reliable Petaso level identification, provides new scientific method and foundation for the detection of Petaso industry product.
Summary of the invention
The technical problem to be solved is a kind of method utilizing Electronic Nose to differentiate Petaso grade, with the deficiency overcoming prior art to exist.
For solving above-mentioned technical problem, the present invention adopts the following technical scheme that:
A kind of method utilizing Electronic Nose to differentiate Petaso grade, it is characterised in that comprise the steps:
S101, first Petaso is placed in cold storage under-20 DEG C of conditions, before discriminating, the Petaso of cold storage is thawed under 4 DEG C of conditions, be cut into little fourth, mixing after removing fat deposit, cortex, then blend, form sample and seal stand-by；
S102, sample 1.00 ± 0.01g is placed in sample injection bottle, at 40-60 DEG C of head space temperature, balances the 300-500 second；With clean dry air for carrier, with entry needle to sample introduction 400-700 μ L gas in Electronic Nose；
After S103, gas sampling, Electronic Nose carries out the data acquisition 115-125 second, obtains identification result data.
In a preferred embodiment of this invention, described head space temperature is 50 DEG C, and equilibration time is 400 seconds, and the sampling volume of described Electronic Nose is 500 μ L, and described Electronic Nose data acquisition time is 120 seconds.
The temperature of described entry needle is 60 DEG C.
Adopting technique scheme, the present invention can quickly differentiate the different brackets of Petaso, provides new scientific method and foundation for the detection of Petaso industry product.
Accompanying drawing explanation
Describe the present invention below in conjunction with the drawings and specific embodiments:
Fig. 1 the is equilibration time principal component analysis figure of different brackets Petaso when being 300s；
The principal component analysis figure of different brackets Petaso when Fig. 2 equilibration time is 400s；
Fig. 3 the is equilibration time principal component analysis figure of different brackets Petaso when being 500s；
Fig. 4 the is sampling volume principal component analysis figure of different brackets Petaso when being 400uL；
Fig. 5 the is sampling volume principal component analysis figure of different brackets Petaso when being 500uL；
Fig. 6 the is sampling volume principal component analysis figure of different brackets Petaso when being 600uL；
Fig. 7 the is sampling volume principal component analysis figure of different brackets Petaso when being 700uL；
Fig. 8 the is equilibrium temperature principal component analysis figure of different brackets Petaso when being 40 DEG C；
Fig. 9 the is equilibrium temperature principal component analysis figure of different brackets Petaso when being 50 DEG C；
Figure 10 the is equilibrium temperature principal component analysis figure of different brackets Petaso when being 60 DEG C；
Figure 11 is that the SIMCA grade being standard sample with Jinhua superfine Petaso differentiates model；
Figure 12 is that the SIMCA grade being standard sample with Jinhua top grade Petaso differentiates model；
Figure 13 is that the SIMCA grade being standard sample with Jinhua one-level Petaso differentiates model；
Figure 14 is that the SIMCA grade being standard sample with Xuanwei one-level Petaso differentiates model；
Figure 15 is that the SIMCA grade being standard sample with two grades, Xuanwei Petaso differentiates model；
Figure 16 is that the SIMCA grade being standard sample with three grades, Xuanwei Petaso differentiates model；
Figure 17 is that the SIMCA grade being standard sample with Rugao one-level Petaso differentiates model；
Figure 18 is that the SIMCA grade being standard sample with two grades, Rugao Petaso differentiates model；
Figure 19 is that the SIMCA grade being standard sample with three grades, Rugao Petaso differentiates model.
Detailed description of the invention
One, instrument.
Electronic Nose (alphmos company of France produces, model fox4000).
Two, material: Xuanwei one-level Petaso, two grades, Xuanwei Petaso, three grades, Xuanwei Petaso, buying is from Xuanwei City, Yunnan Province Xuan Tai Petaso company limited；Jinhua superfine Petaso, Jinhua top grade Petaso, Jinhua one-level Petaso, buying is from Jinzi Ham Co., Ltd of Zhejiang Province；Rugao one-level Petaso, two grades, Rugao Petaso, three grades, Rugao Petaso, buying is from Jiangsu Rugao ham company limited of longevity group.
Petaso sample is the consistent vacuum packaging of profile and bones segmentation block, fetches the refrigerator cold storage being placed on-20 DEG C, until processing when analyzing.
Three, the preparation of sample.
The Xuanwei ham that experiment is used, the sample of selection is that the vacuum packaging belt leather that profile is consistent is boned segmentation block, fetches and is placed on cold storage under-20 DEG C of conditions.To be stored in the one-level of-20 DEG C before experiment, two grades, three grades of Xuanwei hams overnight thaw under 4 DEG C of conditions, are cut into little fourth after removing fat deposit, cortex, mixing, then rub with small meat mincer, seal stand-by.
Four, the investigation of discrimination method.
1, being placed in sample injection bottle by sample, in different head space temperature, ((40 DEG C, 50 DEG C, 60 DEG C) carry out the balance of different time (300s, 400s, 500s)；With clean dry air for carrier, with entry needle to the gas of sample introduction different volumes (400uL, 500uL, 600uL, 700uL) in Electronic Nose, within 1 second, sample introduction is complete；The temperature of entry needle is 600 DEG C；After gas sampling, Electronic Nose carries out data acquisition 120 seconds.
During investigation, 1.00 ± 0.01g sample is placed in 10ml sample injection bottle, prepares 5 Duplicate Samples respectively.With arithmetic mean of instantaneous value represent 3 measurement results,
2, the distinguishing assay of Petaso grade is shown in Fig. 1-10 by different condition, in figure: X1 represents Xuanwei one-level Petaso；X2 represents two grades, Xuanwei Petaso；X3 represents three grades, Xuanwei Petaso.
Different equilibration time (300s, 400s, 500s) the differentiation figure of different brackets Petaso is shown in Fig. 1-3 by Electronic Nose, as can be seen from the figure, under three conditions, Xuanwei ham Three Estate can well distinguish, and first, second principal component contributor rate sum (%) has all reached more than 99.94%.As can be seen from the figure, the PCA figure discrimination index that equilibration time is 400s and 500s is all 90, illustrates that the equilibration time of 400s and 500s is identical to the separating capacity of Three Estate Petaso, in order to conservative control test is consuming time, reduce the waiting time of testing sample as far as possible, finally select 400s.
(400uL under different sampling volumes, 500uL, 600uL, 700uL,) under Electronic Nose Fig. 4-7 is shown in the differentiation of different brackets Petaso, under different sampling volumes, its first, second principal component contributor rate sum (%) is more than 99.90%, and when sampling volume is 500uL, discrimination index is 92, reaches optimum.
Different temperatures (40 DEG C, 50 DEG C, 60 DEG C) under Electronic Nose Fig. 8-10 are shown in the differentiation of different brackets Petaso, first, second main constituent sum of sample has also all reached more than 99.91%, but at 50 DEG C, the Petaso sample area separate index number of different stage is the highest, reach 92.
To sum up, from 18 sensors, the separating capacity of different brackets Petaso sample being considered, selecting head space equilibrium temperature is 50 DEG C, and equilibration time 400s, sampling volume 500uL quickly distinguishes the authentication method of different brackets Petaso as Electronic Nose.
3. the checking of authentication method
Figure 11-19 respectively Chinese style three big different grades of SIMCA of dry-cured ham (soft Independent modeling) grade differentiates illustraton of model.X1 represents Xuanwei one-level Petaso；X2 represents two grades, Xuanwei Petaso；X3 represents three grades, Xuanwei Petaso；JT represents Jinhua superfine Petaso；JY represents Jinhua top grade Petaso；J1 represents Jinhua one-level Petaso；R1 represents Rugao one-level Petaso；R2 represents two grades, Rugao Petaso；R3 represents three grades, Rugao Petaso.
Can be seen that from Figure 11-13, in Figure 11 and Figure 12, Jinhua is superfine can judge by accident with Jinhua top grade Petaso, and sample overlap is more, modeling with Jinhua one-level Petaso for standard sample in Figure 13, superfine and top grade all falls within one-level Petaso " acceptable area " outward, thus illustrates, between Jinhua superfine and top grade Petaso, abnormal smells from the patient ratio is relatively similar, erroneous judgement probability is relatively big, and between Jinhua one-level and other two kinds of Petasos, abnormal smells from the patient difference is relatively large, it is possible to accurately identify respective rating sample.
Equally, which no matter can be seen that with grade Petaso for standard sample from Figure 14-16 and Figure 17-19, the Petaso sample of other two grades all falls within outside " acceptable area " of standard sample, illustrate that under the same place of production, different grades of sample abnormal smells from the patient comparison in difference is obvious, set up modelling effect by SIMCA analysis method better.
To sum up, the different brackets dry-cured ham of different sources all can utilize this discrimination method to carry out differentiating to distinguish.
Five. the determination of discrimination method.
May determine that from above-mentioned investigation the step of the method utilizing Electronic Nose discriminating Petaso grade of the present invention is as follows:
S101, first Petaso is placed in cold storage under-20 DEG C of conditions, before discriminating, the Petaso of cold storage is thawed under 4 DEG C of conditions, be cut into little fourth, mixing after removing fat deposit, cortex, then blend, form sample and seal stand-by；
S102, sample 1.00 ± 0.01g is placed in sample injection bottle, at 40-50 DEG C of head space temperature, balances the 300-500 second；With clean dry air for carrier, with entry needle to sample introduction 400-700 μ L gas in Electronic Nose.Wherein, it is preferred that head space temperature is 50 DEG C, equilibration time is 400 seconds, and the sampling volume of Electronic Nose is 500 μ L.Described Electronic Nose data acquisition time is 120 seconds, and the temperature of entry needle is 60 DEG C.
After S103, gas sampling, Electronic Nose carries out the data acquisition 115-125 second, obtains identification result data.Wherein, it is preferred that Electronic Nose data acquisition time is 120 seconds.
But; those skilled in the art will recognize that; above-mentioned detailed description of the invention is illustrative of; it is to better make to skilled artisans appreciate that this patent; it is not to be construed as the restriction to this patent protection domain; as long as any equivalent change made according to the disclosed spirit of this patent or modification, each fall within the scope of this patent protection.
Claims (4)
1. one kind utilizes the method that Electronic Nose differentiates Petaso grade, it is characterised in that comprise the steps:
S101, first Petaso is placed in cold storage under-20 DEG C of conditions, before discriminating, the Petaso of cold storage is thawed under 4 DEG C of conditions, be cut into little fourth, mixing after removing fat deposit, cortex, then blend, form sample and seal stand-by；
S102, sample 1.00 ± 0.01g is placed in sample injection bottle, at 40-60 DEG C of head space temperature, balances the 300-500 second；With clean dry air for carrier, with entry needle to sample introduction 400-700 μ L gas in Electronic Nose；
After S103, gas sampling, Electronic Nose carries out the data acquisition 115-125 second, obtains identification result data.
2. the method utilizing Electronic Nose to differentiate Petaso grade according to claim 1, it is characterised in that: described head space temperature is 50 DEG C, and equilibration time is 400 seconds, and the sampling volume of described Electronic Nose is 500 μ L, and described Electronic Nose data acquisition time is 120 seconds.
3. the method utilizing Electronic Nose to differentiate Petaso grade according to claim 1 and 2, it is characterised in that: the temperature of described entry needle is 60 DEG C.
4. the method utilizing Electronic Nose to differentiate Petaso grade according to claim 1, it is characterised in that: described Electronic Nose is the Electronic Nose of the model FOX4000 that A Mosi company of France produces.
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| CN201410841815.2A CN105807017A (en) | 2014-12-29 | 2014-12-29 | Method for discriminating ham grades by using electronic nose |
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| CN201410841815.2A CN105807017A (en) | 2014-12-29 | 2014-12-29 | Method for discriminating ham grades by using electronic nose |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110687240A (en) * | 2019-10-25 | 2020-01-14 | 云南农业大学 | Method for rapidly identifying production place of ham |
| CN111693661A (en) * | 2020-06-11 | 2020-09-22 | 上海交通大学 | Intelligent sense organ based dry-cured ham flavor evaluation method |
| CN112285312A (en) * | 2020-10-30 | 2021-01-29 | 浙江大学 | Method for detecting abnormal smell grade of drinking water based on electronic nose |
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| CN102692488A (en) * | 2012-03-22 | 2012-09-26 | 浙江大学 | Jinhua ham grading and identifying method based on electronic nose technology |
| CN104020224A (en) * | 2014-04-29 | 2014-09-03 | 中国肉类食品综合研究中心 | Method for detecting oxidative deterioration of cured meat product |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102692488A (en) * | 2012-03-22 | 2012-09-26 | 浙江大学 | Jinhua ham grading and identifying method based on electronic nose technology |
| CN104020224A (en) * | 2014-04-29 | 2014-09-03 | 中国肉类食品综合研究中心 | Method for detecting oxidative deterioration of cured meat product |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110687240A (en) * | 2019-10-25 | 2020-01-14 | 云南农业大学 | Method for rapidly identifying production place of ham |
| CN110687240B (en) * | 2019-10-25 | 2022-02-18 | 云南农业大学 | Method for rapidly identifying production place of ham |
| CN111693661A (en) * | 2020-06-11 | 2020-09-22 | 上海交通大学 | Intelligent sense organ based dry-cured ham flavor evaluation method |
| CN112285312A (en) * | 2020-10-30 | 2021-01-29 | 浙江大学 | Method for detecting abnormal smell grade of drinking water based on electronic nose |
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