JPH0264439A - Estimating method and apparatus for shelf life - Google Patents

Abstract

PURPOSE:To estimate the shelf life of a sample to be measured simply and in a short time by substituting into a regression equation the amount of chemical emission measured from the sample of measurement. CONSTITUTION:A temperature in a sample chamber 11a is fixed by a control element 17 and a shutter 14 is controlled to be opened or closed. Chemical emission from a sample in a cell 13 is sensed in a staged manner by a photodetector 12 and counted by a counter 18, and thereby the amount of increase in the emission with a rise in the temperature is determined. Then, a regression equation and correlation of a count value of a measuring time, the amount of increase in the emission and a shelf life determined by a functional inspection are determined by operation. The regression equation (coefficient value) having large correlation is stored in a memory 21. Next, the chemical emission generated from a material of measurement is measured, the amount of the measured emission is substituted into the regression equation and the shelf life of the material for measurement is calculated therefrom.

Description

[Detailed Description of the Invention] [Objective of the Invention] (Industrial Application Field) This invention quantitatively measures shelf life (storage stability) by measuring chemiluminescence generated from samples such as fresh fish. The present invention relates to a method and a prediction device for making predictions.

(Prior Art) In general, the shelf life of foods is predicted by focusing on the content of food components or using the oxidation stability of contained lipids as an index. However, these conventional shelf life predictions require a long time and cannot be easily predicted in a short period of time.

(Problems to be Solved by the Invention) This invention solves the problem that it takes a long time to predict the shelf life of a CI constant sample, and its purpose is to easily and easily predict the shelf life of a measurement sample. The present invention aims to provide a shelf life prediction method and a prediction device that can predict shelf life in a short period of time.

[Structure of the Invention] (Means for Solving the Problems) This invention measures the amount of chemiluminescence generated from a reference sample, and performs regression based on the measured amount of light emission and a preset shelf life of the reference sample. An equation is calculated, the amount of chemiluminescence generated from the measurement sample is determined, and the shelf life of the measurement sample is determined based on the regression equation.

Further, the present invention stores a regression equation obtained from the amount of chemiluminescence generated from a reference sample and a preset shelf life of this reference sample in the storage means, and calculates the amount of chemiluminescence generated from the measurement sample by the measuring means. The shelf life of the sample to be measured is determined by the control means from the measured luminescence amount and the regression equation stored in the storage means.

(Function) This invention confirms that there is a strong correlation between the amount of chemiluminescence generated from a reference sample and the shelf life of the reference sample set in advance, and performs regression analysis based on the relationship between the amount of chemiluminescence and shelf life of the reference sample. The equation was calculated. By measuring the amount of chemiluminescence generated from the measurement sample and substituting it into the regression equation, the shelf life of the measurement sample can be easily and quickly pre-M1.

Furthermore, a regression equation obtained from the relationship between the amount of chemiluminescence generated from the reference sample and the shelf life of the reference sample set in advance is stored in the storage means, and the amount of chemiluminescence from the measurement sample measured by the measuring means is stored. By substituting the equation into the regression equation using the control means, the shelf life of the measurement sample can be predicted easily and in a short time.

(Example) Hereinafter, an example of the present invention will be described with reference to the drawings.

In this example, the shelf life of fish meat was predicted. In predicting this shelf life, first of all,
The shelf life of fish meat as a reference sample was predicted by sensory testing.

This sensory test was conducted on six types of fish meat (sardine, red sea bream, tuna, kichiji, masapa, and millet), sardine meat with the antioxidant BHA (butylated hydroxyanisole) added at 0.02%, and sodium dehydroacetate added. 3.5.8.10.13 before saving and from the start of saving
．． After 15 days, odor measurements were taken. The storage temperature at this time was set to 00C.

That is, in this sensory test, 12 panelists were asked to judge the intensity of each of fish odor, oxidation odor, and putrid odor using the test paper shown in FIG. 2.

Then, only the oxidative odor was calculated using equation (1) using the odor intensity as a point, and was used as an index of oxidative deterioration.

Point -2X (++) +IX (+) /N(N
:Number of panelists) (1) As a result of the above sensory test, there was almost no influence of putrid odor until the latter half of the storage period. In addition, there was no significant difference in odor between sardine meat with sodium dehydroacetate added and sardine meat without the additive, so the influence of putrid odor on oxidized odor is
It seemed that it was not during this period.

Therefore, from Figure 3, which shows the change in the intensity of oxidation odor expressed by the points mentioned above, we calculated the number of days required to reach points -0 and 5, at which half of the panelists recognized the oxidation odor, at 0'' CC storage oxidation. Based on this setting, the shelf life of the six types of fish is 1,8 days for millet baskets, 4,4 days for sardines, 5.5 days for masapar, 10,0 days for red sea bream, and 10,0 days for red sea bream. -13,0 days,
Tuna - 13.2 days old.

Next, the measurement of the amount of chemiluminescence generated from fish meat and the prediction of shelf life based on the measured amount of luminescence will be explained.

It is known that extremely weak chemiluminescence occurs as fats and oils deteriorate, and chemiluminescence is also known to be generated from fish meat. In this example, the amount of chemiluminescence generated from fish meat as a reference sample was measured, and the correlation between the measured amount of luminescence and the shelf life of each fish species determined by the sensory test was determined. The shelf life of the 711+ standard sample is predicted based on the luminescence amount measured from the measurement sample.

FIG. 1 shows a device for this purpose.

The housing 11 is a dark room, and a photodetector 12 made of, for example, a photomultiplier tube is provided inside the housing 11. This photodetector 12 receives light output from a sample housed in a cell 13.
A shutter 14 is provided between the photodetector 3 and the photodetector 12. The shutter 14 is used to prevent strong external light from entering the photodetector 12 when it is opened and closed at an arbitrary time when measuring light emitted from a sample, or when the cell 13 is moved in and out of the housing 11. This is to ensure that this does not occur. Further, inside the housing 11, there are provided a temperature detector 15 that detects the temperature inside the sample chamber (the part where the cell 13 is housed) 11a, and a heater 16 that sets the temperature inside the sample chamber 11a as a set temperature. .

On the other hand, the control section 17 controls the entire apparatus, and is composed of, for example, a microcomputer. This control section 17 includes a counter 18 that counts the detection output of the photodetector 12, a shutter drive section 19 that drives the shutter 14 to open and close, the temperature sensor 15, and a counter that counts the detection output of the photodetector 12. A memory 21 in which various information is stored, such as a heater drive section 20 that controls the heating of the heater 16, an operation program for the control section 17, a shelf life according to the fish species set by the sensory test, a display section 22, and a keyboard. Operation panel 2 composed of 23
4 are connected.

From the keyboard 23, the measurement time by the photodetector 12, the opening/closing timing of the shutter 14, and the temperature inside the sample chamber 11a can be specified, and the control section 17 can control each section according to the instructions from the keyboard 23. It is designed to be controlled.

In the above configuration, the operation for predicting the shelf life of fish meat will be explained with reference to FIG.

The operation of predicting the shelf life of fish meat is performed by the control unit 17 as follows.

(1) The control unit 17 makes the temperature T in the sample chamber 11a constant by the heater 16 and the heater drive unit 2o;
1Jlj The shutter 14 is controlled to open and close several times by the shutter drive unit 19 during a certain period of time t, and extremely weak chemiluminescence (measurement wavelength 300 nm to 650 nm) generated from the sample accommodated in the cell 13 is detected as a light beam. The light is received by the detector 12 in several stages, and the output of the received light is counted by the counter 18 (step 5TI).

(2) Y (t) is the count value after t hours from the start of measurement, Y (A) is the integrated value of counts for 1 hour from the start of measurement, and Δ from 11 hours to t2 hours (tl<t2≦t) is time. Find the increase JWY (Δt) in the light emission amount (Step 5
T2).

(3) Find the increase in light emission amount ff1Y (ΔT) when the temperature T is increased from T1 to T2 (step 5T3).

(4) Y(Δt) Y(t) Y(A) found above
, Y (ΔT) and the shelf life determined by the above-mentioned sensory test.
The correlation between the value of Δt) Y(t) Y(A)Y(ΔT) and the shelf life determined by the sensory test is determined (Step 5T4).

(5) The regression equation (coefficient value) with a large correlation is stored in the memory 21 (step 5T5).

(6) chemiluminescence generated from flll + constant sample, (1
) or measure in the same manner as (3) (step 5T6
).

(7) Substitute the Al1 constant luminescence amount into the regression equation to calculate the shelf life of the ΔllI constant sample (step 5T7).

In the actual measurement, according to the above measurement method, chemiluminescence of the six types of fish meat mentioned above was first determined at 71 pI with a constant temperature of 35'C in the sample chamber 11a, and 30 minutes after the start of the measurement. Luminescence ff increased in 1o minute
Y(Δt), luminescence 30 minutes after the start of measurement, ff1Y(t)
, and the integrated value Y (A
) were calculated respectively.

In addition, each sample was minced, and about 5 (g) was minced into a diameter of 5.3
The cells 13 of (am) were flattened and tightened so that no gaps were formed.

In addition, the 7111 constant temperature adjusts the temperature inside the sample chamber 11a by 25
' C, 35' C, 45'' C, and as a result of measuring the luminescence amount of fresh fish, the increase in luminescence amount was almost linear when it was 359C, so it is clear that there is a difference in luminescence amount depending on the fish species. , this temperature was adopted.

Figure 5 shows Y(Δt) corresponding to the fish meat of the reference samples (6 types).
), Y(t), and Y(A) and the shelf life determined by the above-mentioned sensory test. The sample is
Fish purchased from the market is minced in the mouth, and the amount of luminescence can be considered to be measured at the time the sample is obtained, and the shelf life from that point on can be predicted.

Here, the integrated value Y (A
) and shelf life is shown in Figure 6, and the regression equation expressing this relationship is Y=5.46X1
06, e-0-278XX; Shelf life (days) Y: Chemiluminescence amount (number of counts) (2). The correlation coefficient between this integrated value and shelf life is r
--0,976, and there was a very strong correlation.

Similarly, a regression equation for the relationship between the amount of luminescence increased over 10 minutes and shelf life is calculated as follows: Y=5.47xlQ3 ee-0,168XX: Shelf life (days) Y: Chemiluminescence amount (number of counts) /30 seconds)...(3) The correlation coefficient was r--0,699.

Here, the regression equation was obtained when excluding the yellow locust, which has a very fast oxidation rate and a large amount of luminescence compared to other fish, and showed a strong correlation when the yellow locust was excluded.

Furthermore, when calculating the regression equation for the relationship between the luminescence ff1Y(t) and the shelf life 30 minutes after the start of measurement, Y-9,90X104, e-0-263×X: Shelf Life (Japan) Y: Chemistry Luminescence amount (number of counts/30 seconds) (5) r=-0,970, and a strong correlation was observed.

On the other hand, the temperature in the sample chamber 11a (measured temperature) was set to 25°C.
Comparing the amount of light emitted after 30 minutes when set to 45'C and 45'C, the increased amount of light emitted (counts/30 seconds) by increasing the measurement temperature by 20'C is: : 6782 Kichiji : 15007 Masaba : 30617 Kibinago : 62780. When a regression equation is calculated for the relationship between these values and the shelf life of each fish, Y-9,48
X104・e−0・” ”X: Shelf life (days) Y: Chemiluminescence amount (number of counts/30 seconds)... (6) The correlation coefficient is r--0,994, which is very I was surprised that there was a strong correlation.

As mentioned above, there is a strong correlation between the amount of chemiluminescence generated from the sample and the shelf life determined by the sensory test, and the coefficient ASb of the regression equation Y-Ae-bX -= (7) is determined. It was confirmed that by counting the amount of chemiluminescence Y generated from the measurement sample, it is possible to predict the shelf life X of the measurement sample.

Next, a case will be described in which the shelf life of a measurement sample is predicted using the regression equation obtained as described above.

To predict the shelf life of a measurement sample, the above-mentioned 1.
Luminescence ff1Y(Δt) increased during 0 minutes, 3 after start of measurement
It is possible to use the luminescence ff1Y(t) after 0 minutes, the integrated value Y (A) of the luminescence amount for 30 minutes after the start of measurement, and the luminescence ff1Y(ΔT) when the measurement temperature is changed, but
Here, we will use the integrated value Y (A) of the luminescence amount for 30 minutes after the start of measurement, which has a high correlation coefficient and a short measurement time. Therefore, the memory 21 stores the coefficient value of the regression equation shown in equation (2) among the plurality of regression equations obtained, and the shelf life of the fish meat obtained by the sensory test.

In this state, for example, when predicting the shelf life of tuna as a measurement sample, minced tuna as a sample is packed in the cell 13 and set in the sample chamber 11a. Then, information indicating the measurement of tuna is inputted from the keyboard 23 of the operation panel 24, and an instruction to start the measurement is given.

Then, the control unit 17 lowers the temperature inside the sample chamber 11a to 35
The heater drive section 20 is controlled according to the detection output of the temperature detector 15 so that the temperature is constant. With the temperature in the sample chamber 11a controlled in this manner, the shutter 14 is opened at predetermined time intervals by the shutter drive section 19, and chemiluminescence generated from the sample is received by the photodetector 12. The light receiving output of this photodetector 12 is counted by a counter 18, and this counted value is supplied to a control section 17. Then, after 30 minutes set as the measurement time have elapsed, equation (2) is calculated using the count value of the counter 18 and the coefficient values A and b stored in the memory 21, and the tuna sample as a sample is Shelf life X is required.

According to the above example, it was confirmed that there is a strong correlation between the amount of chemiluminescence of fish meat and the shelf life determined by a sensory test, and this correlation value was determined in advance by the ul determination of the reference sample, and The shelf life of the all + constant sample is calculated from the amount of chemiluminescence generated from the sample and this coefficient value. Therefore, by short-term measurement of chemiluminescence generated from a measurement sample, it is possible to easily predict the shelf life of the measurement sample, which can be applied to, for example, shipping adjustment of frozen fresh fish, and is practical. The above effect is significant.

In the above embodiment, the shelf life of the measurement sample is predicted from the luminescence amount of the measurement sample based on the regression equation obtained from the reference sample and the means for calculating the regression equation from the reference sample.
Although we have described a device that is integrated with a means for
However, by configuring these means as separate devices and storing the coefficient values of the regression equation obtained from the reference sample in the device that predicts the shelf life of the 7111+ constant sample, The shelf life of the measurement sample may also be predicted.

With this configuration, the shelf life can be quickly calculated by child CI for a measurement sample for which a regression equation has been determined in advance.
It is something that can be done.

Further, in the above embodiment, only the coefficient value of the regression equation corresponding to the integrated value Y (A) of the luminescence amount for 30 minutes after the start of measurement was stored in the memory 21, but the invention is not limited to this, and for example, Luminescence mY (Δt) increased over 10 minutes
, the luminescence intensity Y (t) for 30 minutes after the start of the measurement, and the coefficient values of the regression equation corresponding to the luminescence intensity Y (ΔT) when the measurement temperature is changed, and the shelf life can be predicted by the operator from the keyboard 23. The u1 method can be selected,
By controlling the shutter 14 and the heater 16 according to the selected prediction method, it is possible to perform the shelf life prediction M1 according to the user's request. That is, it is possible to select and use regression equations that exhibit high correlation coefficients depending on the species of fish.

Further, as the memory 21, for example, an IC card or a memory card can be used, and the coefficient values of the regression equation corresponding to the required measurement sample and the measurement method corresponding to the coefficient values are stored in this IC card or memory card. By storing the information, it is possible to predict the shelf life of various measurement samples using a required measurement method.

Further, in the above embodiment, the shelf life of fish meat was explained, but the present invention is not limited to this, and the shelf life can be predicted by applying the present invention as long as the amount of luminescence changes depending on deterioration. is possible.

Further, in the above embodiment, the amount of light emission is displayed by the number of counts to show the correlation, but the amount of light emission is not limited to this, and it is also possible to display the amount of light by using a current or voltage proportional to the number of counts.

It goes without saying that various other modifications can be made without departing from the gist of the invention.

[Effects of the Invention] As detailed above, according to the present invention, the regression equation obtained from the relationship between the amount of chemiluminescence generated from the reference sample and the preset shelf life of the reference sample is
By substituting the amount of chemiluminescence measured from the No. 11 constant sample, it is possible to provide a shelf life prediction method that allows the shelf life of the measurement sample to be predicted easily and in a short time.

Furthermore, a regression equation obtained from the relationship between the amount of chemiluminescence generated from the reference sample and the shelf life of the reference sample set in advance is stored in the storage means, and the amount of chemiluminescence from the measurement sample measured by the measurement means is stored. By substituting the following into the regression equation by the control means, it is possible to provide a shelf life pre-M1 device that can easily and quickly predict the shelf life of a measurement sample.

[Brief explanation of the drawing]

FIG. 1 is a block diagram showing an embodiment of the present invention, and FIGS. 2 to 6 are diagrams for explaining the invention in detail. 12... Photodetector, 13... Cell, 14... Shutter, 16... Heater, 17... Control unit, 18...
・Counter, 21...Memory. Applicant's agent Patent attorney Takehiko Suzue (6)

Claims (2)

[Claims] (1) Measure the amount of chemiluminescence generated from the reference sample, calculate a regression equation from the measured amount of luminescence and the preset shelf life of the reference sample, and measure the amount of chemiluminescence generated from the measurement sample. A shelf life prediction method characterized in that the shelf life of a measurement sample is determined based on the regression equation. (2) a storage means in which a regression equation determined from the amount of chemiluminescence generated from a reference sample and a preset shelf life of the reference sample is stored; and a measuring means for measuring the amount of chemiluminescence generated from the measurement sample; A shelf life prediction device comprising: a control means for determining the shelf life of a measurement sample from the measured luminescence amount and a regression equation stored in the storage means.