CN103424521B - Device and method for detecting freshness of beef - Google Patents
Device and method for detecting freshness of beef Download PDFInfo
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- CN103424521B CN103424521B CN201310332580.XA CN201310332580A CN103424521B CN 103424521 B CN103424521 B CN 103424521B CN 201310332580 A CN201310332580 A CN 201310332580A CN 103424521 B CN103424521 B CN 103424521B
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Abstract
The invention discloses a device and a method for detecting freshness of beef. The method comprises the following steps: selecting three carrier gases to detect the volatile gas generated from a newly slaughtered cattle; selecting a predictive model for the beef freshness; detecting the beef to be detected W through a sensor array to obtain maximum signal-to-noise ratio SNRW; calculating storage day numerical value t of the beef W utilizing the predictive model for the beef freshness; judging whether the freshness of the beef W is qualified or disqualified. The invention has the characteristics of quick and high speed detection, good economy, and capability of providing reliable data support for manufacturing food using beef with qualified freshness.
Description
Technical field
The present invention relates to identifying meat freshness technical field, especially relate to the degree of beef freshness pick-up unit and detection method that can detect that beef is whether corrupt accurately and rapidly.
Background technology
Beef has nutritious and that mouthfeel is good feature, dark liking by consumers in general.
But beef is easy to polluted and go bad.In storage process, along with propagation and a series of physicochemical change of microorganism, the freshness of beef decreases.The nutritional labeling that protein, fat and carbohydrates etc. enrich is utilized by bacterium and enzyme, produces the sour gas of ammonia, sulfuration ammonia, aldehydic acid, aldehyde, ketone, ethanethio, alcohol and carboxylic acid.Aldehyde in metabolic product, ketone, ester and other low molecular compound make beef produce peculiar smell.
People are judged by the quality of sense organ to food usually, and this judgement is usually with very strong subjectivity, and evaluation analysis result, often along with the difference of age, experience, exists larger difference.Even if same person also can due to health, emotional change and draw Different Results.Moreover it is a volatile substance suction process that sense of smell is differentiated, long-term experiment can work the mischief to the health of human body, and some bad smell can make the personnel of judging responsive especially and make result wrong; In addition, often need have the composition of personnel of the experience of judging to judge group in a large number in sensory evaluation process, process is comparatively loaded down with trivial details, and evaluation result does not often have repeatability.
And beef is a kind of raw-food material, at present, there is no the freshness of effective method to beef to detect.
Chinese patent Authorization Notice No.: CN101769889A, authorized announcement date on July 7th, 2010, disclose the electric nasus system that a kind of quality of agricultural product detects, comprise one and mainly complete gas enrichment module to low concentration odor trap, one air chamber gas path module and the sensor array mainly olfactory signal being converted into electric signal, one mainly carries out filtering to sensor array output signal, analog to digital conversion, the Conditioning Circuits of Sensor of feature extraction and data preprocessing module, a pair signal carries out identifying and judging, and with the embedded system that data store, one display and result output module, described gas enrichment module is formed by being filled with the adsorption tube of adsorbent, heating wire and attemperating unit.This invention has function singleness, the deficiency that detection time is long.
Summary of the invention
The present invention judges to overcome food of the prior art that the length consuming time of method, cost are high, the deficiency of apparatus expensive, provides a kind ofly to detect beef whether corrupt degree of beef freshness pick-up unit and detection method accurately and rapidly.
To achieve these goals, the present invention is by the following technical solutions:
A kind of degree of beef freshness pick-up unit, comprises gas extractor and surveys device of air; Described gas extractor comprises gas collecting chamber, sample cavity, the lower communicating tube being located at the upper communicating pipe between gas collecting chamber and sample cavity top and being located between gas collecting chamber and sample cavity bottom; Gas collecting chamber is provided with draft tube, and draft tube is provided with the first solenoid valve, upper communicating pipe be provided with the second solenoid valve and the first air pump away from position, gas collecting chamber; Be provided with sample tray in described sample cavity, sample tray is provided with several air holes, and the gas outlet of lower communicating tube is positioned at the below of sample tray;
The sensor array that described survey device of air comprises sampling probe, cleaning probe, digital signal processor and is made up of each gas sensors some; Sampling probe and cleaning probe are equipped with the second air pump,
Each sensor lays respectively at independently in air chamber; Sensor array is electrically connected with digital signal processor, the first solenoid valve, the second solenoid valve, the first air pump, the second air pump and digital signal processor is equipped with the data-interface for being electrically connected with computing machine.
Gas extractor has the effect of the escaping gas enrichment sent by sample to be detected, cycling time extends the concentration that can increase the escaping gas that sample sends, and cycling time is longer, and gas concentration is larger, the detection signal of sensor can be strengthened, thus ensure that the accuracy of detection.
First the present invention chooses the escaping gas that 3 kinds of carrier gas detect the beef generation of just having slaughtered, according to the fitting precision of the detection model of each carrier gas, the concentration of escaping gas is judged, 0.9 is less than when only having a R value in 3 kinds of carrier gas, then the concentration of this escaping gas is most suitable, can ensure the accuracy detected.And selected degree of beef freshness forecast model.
Sensor array of the present invention produces reaction to the escaping gas that beef W to be detected produces and generates analog response signal, and analog response signal is converted to digital response signal eNOSE (t), will
in input stochastic resonance system model, stochastic resonance system model is made to produce accidental resonance; Obtain the signal to noise ratio (S/N ratio) maximal value SNR of beef W
w; Computing machine utilizes degree of beef freshness forecast model to calculate the storage sky numerical value t of beef W; According to storage environment and the N of detected beef; Set freshness limit value N in a computer
1, and make the defective or qualified judgement of beef sample freshness.
Degree of beef freshness pick-up unit of the present invention and detection method with manually judge compared with method, the speed of detection is faster, and the data of detection are more objective, accurate; The slight change of the escaping gas of beef sample can be detected, thus ensure reliably, accurately to detect degree of beef freshness, for food production producer adopts the qualified Beef production food of freshness to provide reliable Data support.
As preferably, described sample tray is hemispherical in what arch upward downwards, be connected with sample cavity by rotating shaft bottom sample tray, sample tray outer peripheral face top is provided with several blades for driving sample tray to rotate along rotating shaft, and the angle of rotating shaft and surface level is acute angle.
As preferably, the angle between described rotating shaft and surface level is 32 degree to 48 degree.
As preferably, described sensor array comprises 8 gas sensors, be respectively the first sensor for detecting sulfide, for detecting the second sensor of hydrogen, for detecting the 3rd sensor of ammonia, for detecting the four-sensor of alcohol, toluene, dimethylbenzene, for detecting the 5th sensor of hydrocarbon component gas, for detecting the 6th sensor of methane, for detecting the 7th sensor of propane, butane, for detecting the 8th sensor of oxides of nitrogen.
A detection method for degree of beef freshness pick-up unit, comprises the steps:
(5-1) according to CNS GB/T 5009.44-2003, detect the total volatile basic nitrogen TVB-N value of difference beef sample storage time, obtain the degree of beef freshness threshold value N under different storage condition, degree of beef freshness threshold value N is stored in computing machine; Setting stores number of days limit value is in a computer m, and setting stores number of days t=0;
(5-2) successively using the air of air, activated carbon filtration and nitrogen as carrier gas, detect:
(5-2-1) the first and second solenoid valves are opened by computing machine, and carrier gas to pass in gas collecting chamber 30 to 40 minutes by draft tube;
(5-2-2) beef of just having slaughtered is put into sample standing groove, computing machine controls first, second closed electromagnetic valve, and starts the first air pump; The escaping gas that first air pump drives beef to produce is at upper and lower communicating pipe, gas collecting chamber and sample cavity Inner eycle 35 to 45 minutes;
(5-2-3) computing machine controls the second air pump work on cleaning probe, and pure air sucks in each air chamber by cleaning probe, cleans each sensor;
(5-2-4) the first solenoid valve is opened by computing machine, sampling probe inserts in gas collecting chamber by draft tube, computing machine controls the second air pump work on sampling probe, the escaping gas that beef produces sucks in each air chamber by sampling probe, escaping gas and the sensor contacts be located in air chamber, each sensor produces analog response signal respectively; Computing machine is averaged each analog response signal, obtains the response signal of sensor array;
(5-3) response signal of the sensor array obtained as carrier gas using the air of air, activated carbon filtration and nitrogen is handled as follows successively:
(5-3-1) digital signal processor is sampled to response signal, obtains digital response signal eNOSE (t);
(5-3-2) stochastic resonance system model is provided with in advance in digital signal processor
will
in input stochastic resonance system model, stochastic resonance system model is made to produce accidental resonance;
Computing machine utilizes formula
calculate output signal-to-noise ratio SNR; Wherein, A, M are constant, and t is the Brownian movement Particles Moving time, and x is the coordinate of Particles Moving, f is signal frequency, and D is external noise intensity, and N (t) grasps noise in being, Δ U is barrier height, a and b is bistable state potential well parameter, and ξ (t) is input external noise;
(5-3-3) the maximal value SNR of the output signal-to-noise ratio SNR of computer calculate beef sample
max, and by SNR
maxbe stored in computing machine;
(5-4) as t < m, make t value increase by 1, and beef sample is put into cold storage plant refrigeration 24 hours, repeat step (5-2) to (5-3);
Obtain m+1 the SNR be associated with storage time
max, by SNR
maxpoint (SNR is formed with t storage time associated with it
max, t), according to m+1 point (SNR
max, t) simulate detection model, and digital simulation precision R;
(5-5) when the fitting precision R of 3 kinds of carrier gas is all greater than 0.9, then repeat step (5-2) and gather escaping gas, and by the escaping gas of 3 kinds of carrier gas all according to after the dilution proportion of 1: 18, again escaping gas is passed in each air chamber, and repeat step (5-3) to (5-4);
When the R of 3 kinds of carrier gas be all less than 0.9 or the R of 2 kind of carrier gas be less than 0.9, then repeat step (5-2) and gather escaping gas, wherein, the escaping gas in step (5-2-2) increases by 10 to 20 minutes the cycling time in upper and lower communicating pipe, gas collecting chamber and sample cavity Inner eycle; And repeat step (5-3) to (5-4);
When only having a R value to be less than 0.9 in 3 kinds of carrier gas, then the detection model that computer selecting R value is maximum is as degree of beef freshness forecast model;
(5-6) choose beef W to be detected, select the carrier gas identical with degree of beef freshness forecast model, repeat step (5-2) to (5-3), obtain the signal to noise ratio (S/N ratio) maximal value SNR of beef W
w;
(5-7) computing machine utilizes degree of beef freshness forecast model to calculate the storage sky numerical value t of beef W; According to storage environment and the N of detected beef; Set freshness limit value N in a computer
1,
As t>=N
1, then the underproof judgement of beef W freshness made by computing machine;
As t < N
1, then the qualified judgement of beef W freshness made by computing machine.
As preferably, in described step (5-2-3), clean probe and pure air is sucked in air chamber, to each sensor cleaning 30 to 60 minutes.
As preferably, in described step (5-2-4), the escaping gas that beef produces sucks in each air chamber and detects 50 seconds to 70 seconds by sampling probe.
As preferably, in described step (5-2-3), pure air cleans sensor with the flow velocity of 740mL/min to 1200mL/min.
As preferably, in step (5-2-4), escaping gas sucks in each air chamber with the speed of 360mL/min to 600mL/min.
Therefore, the present invention has following beneficial effect: it is accurate, objective, quick that (1) is detected; (2) good economy performance; (3) authentic data support is provided for using the qualified beef of freshness to make food.
Accompanying drawing explanation
Fig. 1 is a kind of process flow diagram of detection method of the present invention;
Fig. 2 is the signal to noise ratio (S/N ratio) curve map of detected beef W of the present invention;
Fig. 3 is total volatile basic nitrogen TVB-N assay figure of the present invention;
Fig. 4 is of the present invention using activated carbon filtration air as carrier gas linear regression fit curve map;
Fig. 5 is a kind of structural representation of gas extractor of the present invention;
Fig. 6 is a kind of theory diagram of the present invention.
In figure: gas collecting chamber 1, sample cavity 2, upper communicating pipe 3, lower communicating tube 4, draft tube 5, first solenoid valve 6, second solenoid valve 7, first air pump 8, sample tray 9, sampling probe 10, cleaning probe 11, digital signal processor 12, sensor array 13, second air pump 14, computing machine 15, rotating shaft 16, blade 17, air hole 18.
Embodiment
Below in conjunction with the drawings and specific embodiments, the present invention will be further described.
Embodiment is as shown in Figure 5 a kind of degree of beef freshness pick-up unit, comprises gas extractor and surveys device of air; Gas extractor comprises gas collecting chamber 1, sample cavity 2, the lower communicating tube 4 being located at the upper communicating pipe 3 between gas collecting chamber and sample cavity top and being located between gas collecting chamber and sample cavity bottom; Gas collecting chamber is provided with draft tube 5, and draft tube is provided with the first solenoid valve 6, upper communicating pipe be provided with the second solenoid valve 7 and the first air pump 8 away from position, gas collecting chamber; Be provided with sample tray in sample cavity, sample tray is provided with equally distributed air hole 18, and the gas outlet of lower communicating tube is positioned at the below of sample tray 9;
Sample tray is hemispherical in what arch upward downwards, and be connected with sample cavity by rotating shaft 16 bottom sample tray, sample tray outer peripheral face top is provided with the blade 17 for driving sample tray to rotate along rotating shaft, and the angle of rotating shaft and surface level is 48 degree.
As shown in Figure 6, the sensor array 13 that device of air comprises sampling probe 10, cleaning probe 11, digital signal processor 12 and is made up of 8 gas sensors is surveyed; Sampling probe and cleaning probe are equipped with the second air pump 14,
Each sensor lays respectively at independently in air chamber; Sensor array is electrically connected with digital signal processor, the first solenoid valve, the second solenoid valve, the first air pump, the second air pump and digital signal processor is equipped with the data-interface for being electrically connected with computing machine 15.
8 gas sensors are respectively the first sensor for detecting sulfide, for detecting the second sensor of hydrogen, for detecting the 3rd sensor of ammonia, for detecting the four-sensor of alcohol, toluene, dimethylbenzene, for detecting the 5th sensor of hydrocarbon component gas, for detecting the 6th sensor of methane, for detecting the 7th sensor of propane, butane, for detecting the 8th sensor of oxides of nitrogen.
In the present embodiment, sample cavity is provided with gland bonnet, when needs add or change sample in sample cavity, opens gland bonnet and operates.
As shown in Figure 1, a kind of detection method of degree of beef freshness pick-up unit, comprises the steps:
Step 100, according to CNS GB/T 5009.44-2003, detects the total volatile basic nitrogen TVB-N value of difference beef sample storage time, obtains the degree of beef freshness threshold value N under different storage condition, be stored in computing machine by degree of beef freshness threshold value N; Setting stores number of days limit value m=9 in a computer, and setting stores number of days t=0;
Such as: being stored in the beef sample under 4 DEG C of environment and being stored in the TVB-N testing result of beef sample of room temperature as shown in Figure 3.
At room temperature, TVB-N value increases sharply.The initial value of TVB-N is about 6.9mgN/100g.The TVB-N value of storage beef sample at room temperature the 1st day and the 2nd day is about 28.9mgN/100g and 51mgN/100g respectively.According to the analytical approach of GB/T5009.44-2003 meat quail hygienic standard, the beef sample at room temperature storing more than 1 day is stale.Therefore, the degree of beef freshness threshold value N=1 under room temperature storage environment.
The beef sample stored under 4 DEG C of conditions, the initial value of its TVB-N is about 6.9mgN/100g.The TVB-N value of the 1st day is about 7.8mgN/100g.Afterwards, TVB-N value constantly increases, and reaches maximal value (about 48.3mgN/100g) at the 9th day.
According to the analytical approach of GB/T5009.44-2003 meat quail hygienic standard, the beef sample storing more than 2 days under 4 DEG C of conditions is stale.Therefore, the degree of beef freshness threshold value N=2 under 4 DEG C of storage conditions.
Step 200, successively using the air of air, activated carbon filtration and nitrogen as carrier gas, detects:
Step 201, the first and second solenoid valves are opened by computing machine, and carrier gas to pass in gas collecting chamber 30 minutes by draft tube;
Step 202, puts into sample standing groove by the beef of just having slaughtered, and computing machine controls first, second closed electromagnetic valve, and starts the air pump on communicating pipe; The escaping gas that air pump drives beef to produce is at upper and lower communicating pipe, gas collecting chamber and sample cavity Inner eycle 30 minutes;
Step 203, computing machine controls the air pump work on cleaning probe, and pure air sucks in air chamber by cleaning probe, cleans each sensor;
Step 204, first solenoid valve is opened by computing machine, sampling probe inserts in gas collecting chamber by draft tube, computing machine controls the air pump work on sampling probe, the escaping gas that beef produces sucks in each air chamber by sampling probe, escaping gas and the sensor contacts be located in air chamber, each sensor produces analog response signal respectively; Computing machine is averaged each analog response signal, obtains the response signal of sensor array;
Step 300, is handled as follows successively to the response signal of the sensor array obtained as carrier gas using the air of air, activated carbon filtration and nitrogen:
Step 301, digital signal processor is sampled to response signal, obtains digital response signal eNOSE (t);
Step 400, is provided with stochastic resonance system model in digital signal processor in advance
will
in input stochastic resonance system model, stochastic resonance system model is made to produce accidental resonance;
Computing machine utilizes formula
calculate output signal-to-noise ratio SNR; Wherein, A, M are constant, and t is the Brownian movement Particles Moving time, and x is the coordinate of Particles Moving, f is signal frequency, and D is external noise intensity, and N (t) grasps noise in being, Δ U is barrier height, a and b is bistable state potential well parameter, and ξ (t) is input external noise;
The maximal value SNR of the output signal-to-noise ratio SNR of computer calculate beef sample
max, and by SNR
maxbe stored in computing machine;
Step 400, as t < 9, makes t value increase by 1, and beef is put into cold storage plant refrigeration 24 hours, repeats step 200 to 300;
Obtain 10 SNR be associated with storage time
max, by SNR
maxpoint (SNR is formed with t storage time associated with it
max, t), according to m+1 point (SNR
max, t) simulate detection model, and digital simulation precision R;
In the present embodiment, obtain 10 SNR be associated with storage time using the air of activated carbon filtration as carrier gas
max, by SNR
maxpoint (SNR is formed with t storage time associated with it
max, t), according to 10 point (SNR
max, t) carry out matching and obtain linear regression curves as shown in Figure 4, and obtaining detection model
calculate R=0.99852;
In like manner, obtain taking air as the detection model of carrier gas be
calculating fitting precision R is 0.89408;
The detection model obtaining nitrogen buffer gas is
calculate R=0.99491;
Step 500, when the fitting precision R of 3 kinds of carrier gas is all greater than 0.9, then repeat step 200 gather escaping gas, and by the escaping gas of 3 kinds of carrier gas respectively according to 1: 18 ratio dilute after, again escaping gas is passed in each air chamber, and repeat step 300 to 400;
When the R of 3 kinds of carrier gas be all less than 0.9 or the R of 2 kind of carrier gas be less than 0.9, then repeat step 200 and gather escaping gas, wherein, the escaping gas in step 200 increases by 15 minutes the cycling time in upper and lower communicating pipe, gas collecting chamber and sample cavity Inner eycle; And repeat step 300 to 400;
When only having a R value to be less than 0.9 in 3 kinds of carrier gas, then the detection model that computer selecting R value is maximum is as degree of beef freshness forecast model;
In the present embodiment, select
as degree of beef freshness forecast model;
Step 600, gets the beef W to be detected that 25g stores in 4 DEG C of environment, and the air selecting activated carbon filtration is carrier gas, repeats step 200 to 300, obtains the signal to noise ratio (S/N ratio) maximal value SNR of beef W
w; As shown in Figure 2, the output signal-to-noise ratio maximal value SNR of the beef sample of the present embodiment
max=-71.5dB;
Step 700, computing machine utilizes degree of beef freshness forecast model to calculate the storage sky numerical value t of beef W; In the present embodiment,
my god; In the present embodiment, the storage environment of detected beef is 4 DEG C of environment, therefore, sets freshness limit value N in a computer
1=2; ,
As t>=N
1, then the underproof judgement of beef W freshness made by computing machine;
As t < N
1, then the qualified judgement of beef W freshness made by computing machine.
T=3.413 > 2 in the present embodiment, therefore, the underproof judgement of beef W freshness made by computing machine.
Should be understood that the present embodiment is only not used in for illustration of the present invention to limit the scope of the invention.In addition should be understood that those skilled in the art can make various changes or modifications the present invention, and these equivalent form of values fall within the application's appended claims limited range equally after the content of having read the present invention's instruction.
Claims (5)
1. a detection method for degree of beef freshness pick-up unit, is characterized in that, described pick-up unit comprises gas extractor and surveys device of air; Described gas extractor comprises gas collecting chamber (1), sample cavity (2), the lower communicating tube (4) being located at the upper communicating pipe (3) between gas collecting chamber and sample cavity top and being located between gas collecting chamber and sample cavity bottom; Gas collecting chamber is provided with draft tube (5), and draft tube is provided with the first solenoid valve (6), upper communicating pipe be provided with the second solenoid valve (7) and the first air pump (8) away from position, gas collecting chamber; Be provided with sample tray in described sample cavity, sample tray is provided with several air holes (18), and the gas outlet of lower communicating tube is positioned at the below of sample tray (9);
The sensor array (13) that described survey device of air comprises sampling probe (10), cleaning probe (11), digital signal processor (12) and is made up of each gas sensors some; Sampling probe and cleaning probe are equipped with the second air pump (14),
Each sensor lays respectively at independently in air chamber; Sensor array is electrically connected with digital signal processor, the first solenoid valve, the second solenoid valve, the first air pump, the second air pump and digital signal processor is equipped with the data-interface for being electrically connected with computing machine (15);
Described detection method comprises the steps:
(1-1) according to CNS GB/T 5009.44-2003, detect the total volatile basic nitrogen TVB-N value of difference beef sample storage time, obtain the degree of beef freshness threshold value N under different storage condition, degree of beef freshness threshold value N is stored in computing machine; Setting stores number of days limit value is in a computer m, and setting stores number of days t=0;
(1-2) successively using the air of air, activated carbon filtration and nitrogen as carrier gas, detect:
(1-2-1) the first and second solenoid valves are opened by computing machine, and carrier gas to pass in gas collecting chamber 30 to 40 minutes by draft tube;
(1-2-2) beef of just having slaughtered is put into sample standing groove, computing machine controls first, second closed electromagnetic valve, and starts the first air pump; The escaping gas that first air pump drives beef to produce is at upper and lower communicating pipe, gas collecting chamber and sample cavity Inner eycle 35 to 45 minutes;
(1-2-3) computing machine controls the second air pump work on cleaning probe, and pure air sucks in each air chamber by cleaning probe, cleans each sensor;
(1-2-4) the first solenoid valve is opened by computing machine, sampling probe inserts in gas collecting chamber by draft tube, computing machine controls the second air pump work on sampling probe, the escaping gas that beef produces sucks in each air chamber by sampling probe, escaping gas and the sensor contacts be located in air chamber, each sensor produces analog response signal respectively; Computing machine is averaged each analog response signal, obtains the response signal of sensor array;
(1-3) response signal of the sensor array obtained as carrier gas using the air of air, activated carbon filtration and nitrogen is handled as follows successively:
(1-3-1) digital signal processor is sampled to response signal, obtains digital response signal eNOSE (t);
(1-3-2) stochastic resonance system model is provided with in advance in digital signal processor
Will
in input stochastic resonance system model, stochastic resonance system model is made to produce accidental resonance;
Computing machine utilizes formula
calculate output signal-to-noise ratio SNR; Wherein, A, M are constant, and t is the Brownian movement Particles Moving time, and x is the coordinate of Particles Moving, f is signal frequency, and D is external noise intensity, and N (t) grasps noise in being, Δ U is barrier height, a and b is bistable state potential well parameter, and ξ (t) is input external noise;
(1-3-3) the maximal value SNR of the output signal-to-noise ratio SNR of computer calculate beef sample
max, and by SNR
maxbe stored in computing machine;
(1-4) as t < m, make t value increase by 1, and beef sample is put into cold storage plant refrigeration 24 hours, repeat step (1-2) to (1-3);
Obtain m+1 the SNR be associated with storage time
max, by SNR
maxpoint (SNR is formed with t storage time associated with it
max, t), according to m+1 point (SNR
max, t) simulate detection model, and digital simulation precision R;
(1-5) when the fitting precision R of 3 kinds of carrier gas is all greater than 0.9, then repeat step (1-2) and gather escaping gas, and by the escaping gas of 3 kinds of carrier gas all according to after the dilution proportion of 1: 18, again escaping gas is passed in each air chamber, and repeat step (1-3) to (1-4);
When the R of 3 kinds of carrier gas be all less than 0.9 or the R of 2 kind of carrier gas be less than 0.9, then repeat step (1-2) and gather escaping gas, wherein, the escaping gas in step (1-2-2) increases by 10 to 20 minutes the cycling time in upper and lower communicating pipe, gas collecting chamber and sample cavity Inner eycle; And repeat step (1-3) to (1-4);
When only having a R value to be less than 0.9 in 3 kinds of carrier gas, then the detection model that computer selecting R value is maximum is as degree of beef freshness forecast model;
(1-6) choose beef W to be detected, select the carrier gas identical with degree of beef freshness forecast model, repeat step (1-2) to (1-3), obtain the signal to noise ratio (S/N ratio) maximal value SNR of beef W
w;
(1-7) computing machine utilizes degree of beef freshness forecast model to calculate the storage sky numerical value t of beef W; According to storage environment and the N of detected beef; Set freshness limit value N in a computer
1,
As t>=N
1, then the underproof judgement of beef W freshness made by computing machine;
As t < N
1, then the qualified judgement of beef W freshness made by computing machine.
2. the detection method of degree of beef freshness pick-up unit according to claim 1, is characterized in that, in described step (1-2-3), pure air sucked in air chamber by cleaning probe, to each sensor cleaning 30 to 60 minutes.
3. the detection method of degree of beef freshness pick-up unit according to claim 1, is characterized in that, in described step (1-2-4), the escaping gas that beef produces sucks in each air chamber and detects 50 seconds to 70 seconds by sampling probe.
4. the detection method of degree of beef freshness pick-up unit according to claim 1, is characterized in that, in described step (1-2-3), pure air cleans sensor with the flow velocity of 740mL/min to 1200mL/min.
5. the detection method of the degree of beef freshness pick-up unit according to claim 1 or 2 or 3 or 4, it is characterized in that, in step (1-2-4), escaping gas sucks in each air chamber with the speed of 360mL/min to 600mL/min.
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| CN105044289B (en) * | 2015-07-30 | 2017-08-04 | 北京仁创科技集团有限公司 | The detection device and method of release flue gas when a kind of precoated sand coremaking or casting |
| CN105891431B (en) * | 2016-04-04 | 2017-10-27 | 浙江理工大学 | A kind of linseed oil quality detecting method |
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| US5609096A (en) * | 1993-12-17 | 1997-03-11 | Goldstar Co., Ltd. | Vegetable freshness keeping device having a sensor |
| JP2000019137A (en) * | 1998-07-01 | 2000-01-21 | Sanyo Electric Co Ltd | Coffee quality measuring device |
| CN2666430Y (en) * | 2003-12-25 | 2004-12-29 | 晨硕实业有限公司 | Apparatus for diffusing odour |
| CN101144780B (en) * | 2006-09-14 | 2011-05-11 | 北京工商大学 | Pork freshness intelligent detection device |
| CN101655471B (en) * | 2009-09-23 | 2012-11-14 | 南京农业大学 | Method for detecting egg freshness by using gas sensor |
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