Prediction model for shelf life of instant fish maw product

Abstract

The invention relates to an instant fish maw product shelf life prediction model, which comprises the following steps: 1, in order to research the relationship between storage quality index change and time, obtaining a chemical reaction rate by using a primary kinetic equation, and establishing an Arrhenius equation so as to predict the shelf life of a product; 2, an Arrhenius equation can reflect the relation between the change rate constant k and the thermodynamic temperature T; 3, taking a logarithm of the expression obtained in the step 2; and step 4, plotting 1 / T by using lnk to fit a linear equation with a straight line with a slope of-Ea / R and a Y-axis intercept of lnk0, namely calculating reaction activation energy Ea and a pre-factor k0, and combining a primary kinetic equation with an Arrhenius equation to obtain a shelf life prediction model. The shelf life model established by the invention provides an important reference basis for quality monitoring and shelf life research of the instant fish maw, and has practical guiding significance for production, storage and transportation of the instant fish maw.

Description

Technical Field

[0001] The present invention belongs to the field of predicting the shelf life of fish maw, and specifically relates to a prediction model for the shelf life of ready-to-eat fish maw products. Background Art

[0002] Fish maw, also known as fish glue, is a dried product of fresh fish swim bladders and is a nourishing tonic that can be used both as food and medicine. Fish maw is an ideal food with high protein and low fat, with a protein content as high as about 80%. It is rich in collagen and essential amino acids and has the effects of beautifying the skin, anti-aging, anti-inflammatory, hemostasis and repair. In recent years, with the pursuit of a healthy lifestyle by people, the market demand for fish maw products has been continuously expanding, enriching the application categories of fish maw products. Existing fish maw products include dried fish maw, ready-to-eat fish maw, freshly stewed fish maw, fish maw porridge, fish maw chicken, fish maw beverages, etc. Among them, ready-to-eat fish maw products are increasingly favored due to their portability and high nutritional value. However, for ready-to-eat fish maw products prepared by high-temperature and high-pressure steam sterilization to achieve commercial sterility, once the conditions are not properly controlled during storage, transportation or sales, problems such as fish maw dissolution, soft texture, spoilage and deterioration are likely to occur, which will reduce the product quality and shorten the product shelf life, greatly limiting the application of fish maw products in the food industry. Therefore, monitoring the quality changes and remaining shelf life of ready-to-eat fish maw during storage and circulation has important practical significance for controlling the edible value and commercial value of fish maw products. Summary of the Invention

[0003] The present invention provides a prediction model for the shelf life of ready-to-eat fish maw products to solve the defects in the prior art.

[0004] The present invention is realized through the following technical solutions:

[0005] A prediction model for the shelf life of ready-to-eat fish maw products includes the following steps:

[0006] Step 1: To study the relationship between the change of storage quality indicators and time, the chemical reaction rate is obtained by using the first-order kinetic equation, and the Arrhenius equation is established to predict the shelf life of the product. The first-order kinetic equation is:

[0007] A = A0e kt

[0008] where A and A0 are the observed quality indicator values at the t-th day and 0-th day of storage, respectively; k is the change rate constant of the storage quality indicator; t is the storage time of the sample, in days;

[0009] Step 2: The Arrhenius equation can reflect the relationship between the change rate constant k and the thermodynamic temperature T, and the specific expression is:

[0010]

[0011] Step 3: The expression obtained by taking the logarithm of the expression obtained in Step 2 is as follows:

[0012]

[0013] where k is the reaction rate constant; Ea is the activation energy of the reaction, kJ / mol; T is the absolute storage temperature, K; k0 is the pre-exponential factor; R is the gas constant, 8.314×10-3 kJ / (mol·K);

[0014] Step 4: Plotting lnk against 1 / T can fit a linear equation with a slope of -Ea / R and a Y-axis intercept of lnk0, and thus the reaction activation energy Ea and the pre-exponential factor k0 can be calculated. Combining the first-order kinetic equation and the Arrhenius equation, a shelf-life prediction model is obtained. As long as the storage quality index value and a certain storage temperature are determined, the shelf life can be theoretically predicted, and its calculation formula is as follows:

[0015]

[0016] where SL is the shelf life, in days.

[0017] For the shelf-life prediction model of the instant fish maw product as described above, the activation energy Ea of the reaction is 113.244 KJ / mol.

[0018] For the shelf-life prediction model of the instant fish maw product as described above, the pre-exponential factor k0 = 1.927x10 17 .

[0019] The advantages of the present invention are as follows: The shelf-life model established by the present invention provides an important reference basis for the quality monitoring and shelf-life research of instant fish maw, and has practical guiding significance for its production, storage and transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0021] Figure 1 is a line graph showing the influence of different storage temperatures on the sensory score of instant fish maw in the verification test of the present invention;

[0022] Figure 2 is a line graph showing the influence of different storage temperatures on the solid content mass fraction of instant fish maw in the verification test of the present invention;

[0023] Figure 3 It is a broken line schematic diagram of the influence of different storage temperatures on the elasticity and hardness of instant fish maw in the verification test of the present invention;

[0024] Figure 4 It is a broken line schematic diagram of the influence of different storage temperatures on the total number of colonies of instant fish maw in the verification test of the present invention;

[0025] Figure 5 It is a schematic diagram of the linear regression equation of the solid content mass fraction of the present invention with respect to the Arrhenius equation. Detailed implementation manners

[0026] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0027] An instant fish maw product shelf life prediction model includes the following steps:

[0028] Step 1: To study the relationship between the change of storage quality indicators and time, the chemical reaction rate is obtained by using the first-order kinetic equation, and the Arrhenius equation is established to predict the shelf life of the product. The first-order kinetic equation is:

[0029] A = A0e kt

[0030] where A and A0 are the observed quality indicator values at the t-th day and 0 d of storage respectively; k is the storage quality indicator change rate constant; t is the storage time of the sample, in d;

[0031] Step 2: The Arrhenius equation can reflect the relationship between the change rate constant k and the thermodynamic temperature T. The specific expression is:

[0032]

[0033] Step 3: The expression after taking the logarithm of the expression obtained in Step 2 is:

[0034]

[0035] where k is the flavor reaction rate constant; Ea is the activation energy of the reaction, in kJ / mol; T is the absolute temperature of storage, in K; k0 is the pre-exponential factor; R is the gas constant, 8.314×10-3 kJ / (mol·K);

[0036] Step 4: Plot lnk against 1 / T to fit a straight line with a slope of -Ea / R and a Y-axis intercept of lnk0, obtaining a linear equation. Then, the activation energy Ea and the pre-exponential factor k0 can be calculated. Combining the first-order kinetic equation and the Arrhenius equation, a shelf-life prediction model is obtained. As long as the storage quality index value and a certain storage temperature are determined, the shelf life can be theoretically predicted. The calculation formula is as follows:

[0037]

[0038] Where, SL is the shelf life, in days.

[0039] Specifically, for the reaction in this example, the activation energy Ea = 113.244 KJ / mol.

[0040] Specifically, for the pre-exponential factor k0 in this example, k0 = 1.927x10 17 。

[0041] Verification test

[0042] Explore the influencing factors of the shelf life of fish maw.

[0043] 1 Select the following influencing factors and their corresponding standards or detection methods

[0044] 1.1 Storage conditions

[0045] Randomly divide the ready-to-eat fish maw products into 3 groups, with 24 bottles in each group (2 bottles are sampled at each time point for index determination), and store them in test chambers at three temperatures of 25, 37, and 45 °C respectively. Samples are taken every 7 days for the determination of relevant indexes.

[0046] 1.2 Sensory evaluation

[0047] Use the sensory evaluation method to evaluate the taste and state of the fish maw. The sensory evaluation panel consists of 20 sensory evaluators who have received professional sensory scoring training, with 10 males and 10 females. The specific scoring criteria are shown in Table 1.

[0048] Table 1 Sensory quality evaluation criteria for ready-to-eat fish maw

[0049]

[0050] 1.3 Determination of the mass fraction of solids

[0051] Heat the product in a water bath at 50 ± 5 °C for 1 to 5 minutes until the product liquid is completely melted. After opening the lid, pour the fish maw content onto a round sieve, connect a funnel under the round sieve, place it on a container with an appropriate capacity, without stirring the product, drain for 3 minutes, then pick out the non-fish maw raw materials recognizable by the naked eye (such as grains, edible flowers, fruits, vegetables, etc.), weigh the fish maw content, record it as m, and the calculation formula is as follows. Calculate the mass fraction X of the fish maw solids, and its value is expressed in %.

[0052]

[0053] Where: X is the mass fraction of fish maw solids, %; m is the mass of the fish maw content, g; M is the net content marked on the product, g.

[0054] 1.4 Determination of texture

[0055] Use a P5 probe to measure hardness and elasticity, and set the parameters: trigger automatic, starting point sensing force 5.0 g, compression ratio 50%, pre-test rate 5 mm / s, test rate 1.0 mm / s, post-test rate 5.0 mm / s, cycle 2 times, and do 3 parallels for each determination.

[0056] 1.5 Determination of total number of colonies

[0057] Perform dilution plate counting according to GB 4789.2-2022 "National Food Safety Standard Food Microbiology Examination Determination of Total Number of Colonies".

[0058] 2 Conduct shelf-life tests for influencing factors

[0059] 2.1 Influence of different storage temperatures on the sensory quality of ready-to-eat fish maw

[0060] Sensory evaluation is closely related to consumers' acceptability and is an intuitive method to judge the shelf life of food. As Figure 1 can be seen, the sensory scores at the three storage temperatures decrease continuously with the extension of time. The higher the temperature, the greater the decline in the sensory score. When the score is lower than 5 points, the gelatinization is incomplete, the taste is soft and mushy, and it is unacceptable in terms of sensory. When stored at 37 °C for 49 days and at 45 °C for 28 days, the gelatin appears to turn into water, the state is flat and small, and it is unacceptable.

[0061] 2.2 Influence of different storage temperatures on the mass fraction of fish maw solids in ready-to-eat fish maw

[0062] As Figure 2As shown in the figure, with the extension of time, the solid content mass fraction of ready-to-eat fish maw showed a downward trend at different storage temperatures. The decline rate of the solid content mass fraction was relatively fast at 45°C and decreased to 44.06% on the 14th day; the decline rate at 37°C was the second, and it decreased to 44.67% on the 42nd day; while the decrease at 25°C was relatively slow and still remained at 59.81% on the 84th day, which was significantly higher than the solid content mass fraction at the end of storage at 37°C and 45°C. It can be seen that low-temperature storage can inhibit the gelatinization water rate of fish maw, delay the decline of the solid content, and extend the shelf life of ready-to-eat fish maw.

[0063] 2.2.3 Effects of Different Storage Temperatures on the Texture of Ready-to-Eat Fish Maw

[0064] Texture is an important index reflecting the taste of food. From Figure 3 It can be seen that at the three storage temperatures, with the extension of storage time, both elasticity and hardness decreased, and the higher the temperature, the faster the decline rate. It can be seen that the elasticity and texture of fish maw are related to the storage temperature. The reason for the rapid change in texture at 37°C and 45°C may be that high temperature affects the stability of collagen, resulting in the instability of the protein structure, causing the fish maw to dissolve and the texture characteristics to decline.

[0065] 2.3 Effects of Different Storage Temperatures on the Total Number of Colonies of Ready-to-Eat Fish Maw

[0066] The total number of colonies can reflect the growth of microorganisms during storage, and the limit value of the total number of colonies, 10 4 CFU / g, was used as the determination end point. From Figure 4 It can be known that at 25°C, the total number of colonies of ready-to-eat fish maw basically showed no obvious growth change, while at 37°C and 45°C, the total number of colonies showed different degrees of increase with the extension of time. The higher the temperature, the faster the growth rate of the total number of colonies. The growth rates at 37°C and 45°C were significantly higher than that at 25°C, indicating that high temperature can promote the growth and reproduction of microorganisms, and low temperature can limit the growth of microorganisms, which is beneficial to the long-term preservation of products. The logarithm values of the total number of colonies of the samples at 37°C and 45°C exceeded 4.0 on the 70th day and 42nd day respectively, indicating that the products had deteriorated and were inedible.

[0067] 2.4 Establishment and Verification of the Kinetic Model of Quality Change during the Storage of Ready-to-Eat Fish Maw

[0068] 2.4.1 Correlation between Sensory Score, Solid Content Mass Fraction, Texture Characteristics and Total Number of Colonies of Ready-to-Eat Fish Maw at Different Storage Temperatures

[0069] Table 2 Analysis of Pearson Correlation Coefficient

[0070]

[0071] Note: "*" indicates a significant correlation (P < 0.05); "**" indicates a highly significant correlation (P < 0.01).

[0072] As can be seen from Table 2, at the three storage temperatures, the correlation coefficients between the sensory score and the solid content mass fraction are all greater than 0.9, and the correlation is extremely significant (P < 0.01). In view of this, the solid content mass fraction is selected as the key factor of the model to construct the shelf-life prediction model.

[0073] 2.4.2 Establishment of the shelf-life model based on the solid content mass fraction

[0074] Table 3 Regression equations of the solid content mass fraction at different storage temperatures

[0075]

[0076] Perform linear regression fitting on the solid content mass fraction at different storage temperatures to obtain the regression coefficient R 2 and the change rate constant k value. The larger the regression coefficient R 2 , the higher the fitting degree of the kinetic model. As shown in Table 3, the regression coefficients R 2 at the three temperatures are all greater than 0.9, indicating that the regression equation has a high fitting degree. According to the reaction rate constant k value and the storage temperature T, calculate Ink and 1 / T, and obtain the linear regression equation of the solid content mass fraction with respect to the Arrhenius equation by plotting (see Figure 5 ), and get the equation y = -13621x + 39.80, R 2 = 0.9120. The activation energy E a calculated from this equation is 113.244 KJ / mol, and the pre-exponential factor k0 is 1.927x10 17 .

[0077] Substitute the activation energy E a and the pre-exponential factor k0 value into the formula to obtain the shelf-life prediction model of ready-to-eat fish maw based on the solid content mass fraction. When the storage temperature, the initial and end solid content mass fractions are determined, the storage shelf-life time of ready-to-eat fish maw under a certain temperature condition can be calculated and predicted.

[0078]

[0079] 2.4.3 Verification of the shelf-life model

[0080] The ready-to-eat fish maw products were stored at 25°C, 37°C, and 45°C respectively to determine their actual shelf lives. Given that the initial solid mass fraction of the ready-to-eat fish maw products was 84.66%, and the final solid mass fraction indicated on the product label was 45%, the values were substituted into the model for verification. The results are shown in Table 4. The relative errors obtained at the three storage temperatures were 8.01%, 7.51%, and 5.46% respectively, and the relative errors were all within 10%, indicating that the shelf life model had good prediction accuracy. Therefore, this shelf life model can be used to accurately predict the theoretical value of the shelf life of ready-to-eat fish maw products. In view of this, the predicted shelf life value of ready-to-eat fish maw at 25°C was calculated to be 262 days, providing certain theoretical guidance for the development and safe storage of ready-to-eat fish maw products.

[0081] Table 4 Comparison of predicted and actual values of product shelf life at different storage temperatures

[0082]

[0083] Note: Relative error / % = (predicted value - measured value) / measured value.

[0084] In summary, this invention studied the quality change laws of ready-to-eat fish maw at 25, 37, and 45°C and established a corresponding shelf life prediction model. At the three storage temperatures, the sensory scores, solid mass fractions, and texture characteristics of ready-to-eat fish maw showed a gradually decreasing trend with the extension of storage time, while the total number of colonies showed a gradually increasing trend with the extension of storage time, and the product quality decreased. The shelf life prediction model constructed based on the solid mass fraction had a high-precision prediction ability, and its error was within 10%.

[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A shelf life prediction model for instant fish maw products, characterized in that: The steps include: Step 1: In order to study the relationship between the change of storage quality index and time, the chemical reaction rate is obtained using the first-order kinetic equation, and the Arrhenius equation is established to predict the shelf life of the product. The first-order kinetic equation is: A=A0e kt Where A and A0 are the observed quality index values ​​at the td and 0d of storage, respectively; k is the storage quality index change rate constant; t is the storage time of the sample, d; Step 2: The Arrhenius equation can reflect the relationship between the change rate constant k and the thermodynamic temperature T. The specific expression is: Step 3: The logarithm of the expression obtained in step 2 is: Where, k is the reaction rate constant; Ea is the activation energy of the reaction, kJ / mol; T is the absolute temperature of the storage, K; k0 is the pre-exponential factor; R is the gas constant, 8.314×10-3kJ / (mol·k); Step 4: Plotting lnk against 1 / T can fit a straight line with a slope of -Ea / R. The linear equation with the Y-axis intercept of lnk0 can be used to calculate the reaction activation energy Ea and the pre-factor k0. Combining the first-order kinetic equation with the Arrhenius equation, a shelf life prediction model is obtained. As long as the storage quality index value and a certain storage temperature are determined, the shelf life can be theoretically predicted. The calculation formula is as follows: Wherein, SL is the shelf life, d.

2. The shelf life prediction model of an instant fish maw product according to claim 1, characterized in that: The activation energy of the reaction is Ea = 113.244 KJ / mol.

3. The shelf life prediction model of an instant fish maw product according to claim 1, characterized in that: The pre-factor k0 = 1.927x10 17 .

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