Method for estimating surface water activity in a product being dried

Abstract

A method for estimating the surface water activity aws of a dryer and a product being dried, the dryer being equipped with at least one dryer atmosphere relative humidity HR probe and a temperature probe.

Description

Technical Field

[0001] The present invention relates to a method for estimating the surface water activity in a product being dried and drying facilities for carrying out the method.

Background Art

[0002] Air drying is used in many products. For example, foods such as cheese, especially sausages, particularly cured sausages. For example, sausages such as salami are subjected to a long and highly controlled drying process in a drying chamber until the desired degree of ripeness is obtained. In order to finally obtain sausages with optimal properties, it is essential to control the ripening and drying processes in these chambers.

[0003] For example, in the preparation of salami, first, desired additives are added to the meat mixture, and this is filled into, for example, a high-caliber casing. Meat products originally have a high water activity (aw), and it is necessary to gradually and continuously lower the aw to obtain a low-aw meat product with high preservability and microbiological stability. The drying process must be carried out with great care regarding the time, temperature (T), and relative humidity (HR%) in the chamber to ensure gentle drying of the product. Because if not sufficiently controlled, a defect called "crusting" can occur. In fact, the purpose is also to make the drying as fast as commercially possible, for example, within a few weeks or months, and at a drying rate such that the surface of the sausage does not dry out too much and prevent the core of the sausage from gradually drying out completely.

[0004] For an object in contact with an atmosphere to dry, the aw of the object (e.g., aw ≈ 0.56) must be greater than the HR% of the contacting atmosphere (e.g., 50% HR), or the object must be placed in an equivalent form of the atmosphere such that it is comparable to aw ≈ 0.50. In this case, drying of the object by the atmosphere occurs until an equilibrium state is reached where the aw of both the atmosphere and the object is the same. For example, if the mass of the object is very small and it is placed in an infinite volume of atmosphere with an HR% of 50% (equivalent to aw ≈ 0.50), ultimately the object will dry to aw ≈ 0.50 and reach an equilibrium state with the atmosphere having an HR% of 50%. This is the case for an object with a constant and small aw.

[0005] However, in a drying object such as a thick sausage like salami, for example, if it takes 28 days to dry, there can be a gradient of aw within the object from the aw of the core of the salami (initially very close to the initial aw of the sausage meat product) to the aw of the surface of the salami (aws), which tends to equilibrate with the aw of the contacting atmosphere. This gradient is dynamic and depends on the drying of the surface layer where the aw is decreasing, promoting the drying of the adjacent internal layers and resulting in a net movement towards the outside and thus net drying. The profile of aw within the sausage changes during drying and depends on the history of the drying processes carried out so far, and thus the drying process follows a non-static, stepwise and dynamic process.

[0006] The driving force for the drying process is the aw gradient existing between the aw of the atmosphere and the aw of the sausage. When this gradient is 0, that is, when "the aw of the atmosphere ≒ the aw of the sausage", both components (the atmosphere and the sausage) reach an equilibrium state, and no net flow of matter occurs between the atmosphere and the sausage. On the other hand, when "the aw of the atmosphere << the aw of the sausage", strong drying of the sausage towards the atmosphere occurs, and the greater the net difference in aw at the contact surface, the stronger the drying. In this process, the aw of the sausage related to this effect is the aw of the sausage surface (i.e., aws). This is because this region is in contact with the atmosphere. On the other hand, the aw inside the sausage (e.g., the core of the sausage) does not directly interact with the aw of the external atmosphere, so it can only result in indirect and slow drying through diffusion through all the inner layers of the sausage.

[0007] Therefore, in order to follow the drying process of products such as sausages, it is essential to control the aw of the atmosphere in contact with the sausage surface and the aw (aws) of the sausage surface.

[0008] In the production of classical sausages, the drying process of sausages has been managed by the craftsmanship of sausage manufacturers. Sausage manufacturers continuously monitor the apparent dryness of the sausages and the drying atmosphere, and deal with it by all empirical and traditional methods, such as opening or closing the windows of the drying chamber to accelerate or decelerate the drying process.

[0009] In modern times, this process has already begun to be more strictly managed by technical means.

[0010] For example, the first item (the aw of the atmosphere) is continuously measured by an HR% probe such as a sensor inside the drying chamber, and the HR% and temperature (T) of the air are measured and recorded throughout the process.

[0011] However, with respect to paragraph 2, measuring the aw of the sausage is not as simple as measuring the aw of the atmosphere in paragraph 1. In fact, while a thermometer probe can easily and continuously record the T and HR% of an air sample, in order to obtain the equilibrium HR% of the air chamber between the probe and the product after reaching a certain equilibrium state, for example, the probe must be in contact with the sausage surface. After that, since the probe will interfere with the drying process of the sausage surface itself, it needs to be removed before the next measurement. Therefore, measuring the aw of the sausage becomes complicated and difficult, especially when it is carried out continuously.

Summary of the Invention

Problems to be Solved by the Invention

[0012] Therefore, in order to follow the drying process, it is desirable to obtain a simple and fast method for estimating the aw of the product being dried. The present invention satisfies such a need.

Means for Solving the Problems

[0013] The advantages of the present invention are as follows: - The aw of the product during drying can be estimated with a conventional HR% probe for a drying oven, without the need for an expensive surface probe for the sausage; - The process of the present invention is simple and takes little time, so it can be used for controlling the drying process of products, especially foods and sausages, particularly cured sausages.

[0014] - In the process of the present invention, complex measurements of meat products such as surface temperature measurement by an infrared probe or measurement of aw or heat flux by a surface humidity probe are not used. Instead, with general drying equipment (such as an internal temperature probe and an HR% probe in the drying atmosphere), parameters corresponding to the product (such as the aw of the product and the evaporation rate (TE)) are indirectly estimated. Therefore, it can assist in the management and control of a sufficient drying process and an aging process, such as for salami.

[0015] Therefore, as a first aspect, the present invention relates to a method for estimating the surface water activity aws of food being dried in a dryer, and the steps of the present invention include the following steps executed by computer means.

[0016] Obtaining a plurality of relative humidity HRi and / or absolute humidity Habs of the atmosphere in the dryer at the time point ti of the product drying process, and obtaining a set of a plurality of representative relative humidity HRri values based on the relative humidity HRi values during the product drying process. i The method further includes obtaining a set of a plurality of evaporation rate TE

[0017] values based on the set of HR i (%), and / or Habs i and ti values. i The method also includes obtaining a regression line of the function F(α,β)=F(HRri,TE

[0018] ) such that α = HReq, β = 0 or α = 0, β = TEmax. i In a preferred embodiment, the variable α is represented on the X-axis, the variable β is represented on the Y-axis, F(X,Y)=F(HRri,TE

[0019] ) where X = Hreq, Y = 0 or Y = TEmax, X = 0). i In the formula, HReq is the relative humidity when the dried air and the product surface are in an equilibrium state, and TEmax is the maximum evaporation rate when the HR of the air in the dryer is 0.

[0020] The method finally includes estimating the aws value of the dried product based on HReq such that aws = HReq / 100.

[0021]

[0022] ​As a second aspect, the present invention relates to a dryer for estimating the surface water activity aws of a dried food, the dryer comprising at least one relative humidity HR% probe of the air of the dryer, a temperature probe, and a plurality of relative humidities HRi and / or absolute humidities Habs of the air in the dryer at a point in time during the product drying process i and computer means configured to be obtained by a probe for obtaining values.

[0023] In addition, the aforementioned calculation means is configured to obtain a set of representative values of the relative humidity HR ri (%).

[0024] Furthermore, the aforementioned calculation means is configured to obtain a set of evaporation rate TE i values based on HRi and / or Habs i and ti values.

[0025] In addition, the aforementioned calculation means is configured to obtain a regression line of the function F(α,β)=F(HRri,TE i ) such that α = HReq, β = 0 or α = 0, β = TEmax.

[0026] In a preferred embodiment, the variable α is represented on the X-axis, the variable β is represented on the Y-axis, and F(X,Y)=F(HRri,TE i ), where X = Hreq, Y = 0 or Y = TEmax, X = 0 where HReq is the relative humidity when the air and the surface of the dried product are in equilibrium, and TEmax is the maximum evaporation rate when the HR of the air in the dryer is 0.

[0027] In addition, the aforementioned computer means is configured to obtain the aws value of the dried product based on HReq such that aws = HReq / 100.

[0028] In a preferred embodiment, the set of representative relative humidity HR ri (%) values is such that HR ri (%)=(HRi +HR i+1 ) / 2 is expressed as

[0029] In a preferred embodiment, the representative relative humidity HR ri (%) value set is such that HR ri (%) = HR i ; or HR ri (%) = HR i+1 is expressed as

[0030] In a preferred embodiment, the representative relative humidity HR ri (%) value set is such that HR ri (%) = Me(HR i +HR i+1 …HR i+1 ) where Me has an arithmetic meaning, N is an integer, for example N = 100.

[0031] In a preferred embodiment, the set of evaporation rate TE values is such that TE i =(HR i+1 -HR i ) / (t i+1 -t i ); or TE i =(Habs i+1 -Habs i ) / (t i+1 -t i ) is expressed as

[0032] Other variations of the present invention The present invention has been described particularly with respect to its application to the field of ripened meat products, such as salami, but the methods described can also be applied to the drying control of products in general, such as dried foods, powders, wood, paper, etc.

[0033] The present invention has been described with respect to applications where the drying time is long, for example over several weeks, but the methods described are also applicable to drying control over much shorter periods, such as a few hours, minutes or adjustments of measured values.

[0034] Although the present invention has described in detail a drying method for the case where the product weight decreases, it can also be applied to the reverse process, i.e., weight increase, or both, i.e., a process passing through a drying stage and a stage other than drying.

[0035] The process according to the present invention is preferably used in a selected section having equivalent conditions (e.g., air flow), and in a closed system that exchanges mass with the outside, such as an outlet, an inlet of external air to a dryer, or by condensation. Otherwise, the resulting results may lack accuracy.

[0036] To supplement the description and make the features of the present estimation method easier to understand, a set of drawings is attached as an essential part of the above description, which relates to a practical preferred example of the implementation of the present estimation method. However, it is merely illustrative and not for the purpose of limitation.

Brief Description of the Drawings

[0037]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Mode for Carrying Out the Invention

[0038] Example 1 Measurement stage FIG. 1 shows a graph (100) of the cycle of the temperature, relative humidity, and wind speed at the lower end of the dryer during each period of the drying process of the meat product. In particular, FIG. 1 corresponds to "Period 4: 86 - 90%, 16 - 18°C" in the drying process.

[0039] As an example, the interval data at the time: 4132 - 4162.5 minutes shown in the graph (100) of FIG. 1 is selected, and the following details are selected from Table 1. The data in minutes is converted to time units.

[0040]

Table 1

[0041] The data in Table 1 is shown in the graph (200) of FIG. 2.

[0042] Calculation stage From the data in Table 1, a continuous interval from one measurement point to the next measurement point is selected. For example, interval 1 corresponding to point 1 and point 2 (time t1 and time t2), interval 2 corresponding to point 2 and point 3, and so on.

[0043] The representative HRr for each interval is taken as the average value of HR between each point and the next point. For example, in the case of interval 1, HRr = (HR1 + HR2) / 2.

[0044] In other embodiments, HRr may be other representative relative humidities instead of the average value. For example, HRr = HR1 or HRr = HR2, etc. may be used, and these are the arithmetic mean Me of a plurality of values of HR.

[0045] The representative TE for each interval is, in this example, taken as the ratio of the difference between HR and t between one point and the next point. For example, in the case of interval 1, TE1 = (HR2 - HR1) / (t2 - t1).

[0046] Therefore, the data in Table 2 can be obtained.

[0047]

Table 2

[0048] Expression and estimation stage In FIG. 3, the data in Table 2 is displayed as a graph (300) of xy coordinates. Here, HRr is shown as the variable x and TE is shown as the variable y. The regression line of the data in Table 2 is also added to the graph (400) of FIG. 4.

[0049] The following points are obtained as the X intercept and Y intercept of the regression line, respectively. X intercept: The HReq value is obtained from the xy coordinates (X = HReq = 93.4%, Y = 0). Y intercept: The TEmax value is obtained from the xy coordinates (X = 0, Y = TEmax = 1228.1).

[0050] Parameter estimation The estimated aws value of the surface of the dried product corresponds to the HReq value of the air obtained in the previous step and is expressed as a percentage (HReq = 93.4%, aws = 93.4 / 100 = 0.934).

[0051] Interpretation: In this case, since TE becomes 0 when the HR of the air in the dryer is 93.4%, it is determined that the aws of the dried product is approximately 0.934, and both the air and the dried product reach equilibrium without evaporation from one to the other. At this equilibrium point, the values of aws and HReq are the same, one corresponding to the surface of the sausage and the other corresponding to the air in the dryer. Therefore, using the method according to the present invention, the aws of the dried product can be indirectly estimated through the parameters of the air in the dryer without direct measurement.

[0052] The TE value at each point of HRr can be obtained by extrapolating the obtained regression line. The estimated value of the maximum value of TE corresponding to the TEmax value obtained in the graph (300) is TEmax = 1228.1.

[0053] In this case, the unit of TEmax corresponds to HR / hour.

[0054] Interpretation: TEmax corresponds to the TE obtained by setting the HR% of the dryer air to HR = 0%. In this case, TE reaches its maximum value when the air in the dryer is completely dry air (HR = 0%) (assuming the remaining conditions remain unchanged). If TEmax is an abnormally small value, it means that the surface of the product being dried is very dry, and even if the air in the dryer is at HR = 0%, the evaporation rate of the product being dried drops significantly, indicating that the HR of the dryer air can only be increased very slowly (TE is very low).

[0055] Example 2 Measurement stage The data interval from 4173.5 to 4211.5 minutes, which is shown as "Period 4: 86 - 90%, 16 - 18°C" in the graph (100) of Figure 1, is selected, and the following detailed points are selected in Table 3. The data t (minutes) is converted to time.

[0056] [Table 3]

[0057] Figure 5 shows the values in Table 3 and the graph (500).

[0058] Calculation stage From the data in Table 3, a continuous interval between a certain point and the next point is selected. Interval 1 corresponds to between point 1 and point 2 (between time t1 and t2), interval 2 corresponds to between point 2 and point 3, and so on.

[0059] The representative HRr for each interval is the average HR of each point and the next point. For example, in the case of interval 1, HRr = (HR1 + HR2) / 2.

[0060] In Example 2, additional data is considered, indicating the versatility of the method of the present invention.

[0061] From the values of HR and T (°C), by using the ordinary humidity equation (psychrometric equation), the Habs of air (g / m 3 ) is calculated. These values are included as an additional column in Table 3.

[0062] In Example 2, the representative TE for each section is the ratio of the difference in Habs and the difference in t between a point and the next point. For example, in the case of Section 1, TE = (Habs2 - Habs1) / (t2 - t1).

[0063] Therefore, the data in Table 4 is obtained.

[0064]

Table 4

[0065] Expression and estimation stage The graph (600) in Figure 6 is an xy graph, and the data in Table 4 is shown. HRr is the variable x, and TE is the variable y. In the graph (700) of Figure 7, the regression line of the data is added.

[0066] By extrapolating the regression line to the X-axis and Y-axis, the following points are obtained. X-intercept: The Hreq value is obtained from the xy coordinates (X = HReq = 93.9%, Y = 0). Y-intercept: The TEmax value is obtained from the xy coordinates (X = 0, Y = TEmax = 302.48).

[0067] Parameter estimation The estimated aws value of the dried product surface corresponds to the HReq value of the air obtained in the previous stage and is expressed as a ratio (HReq = 93.9%, aws = 93.9 / 100 = 0.939).

[0068] Interpretation: In this case, when the HR of the air in the dryer is 93.9%, TE decreases to 0, so the aws of the dried product is determined to be approximately 0.939. And both the air and the surface of the dried product reach an equilibrium state without net evaporation from one to the other. At that equilibrium point, the values of both aws and HReq are the same.

[0069] The TE value at each point of HRr is obtained by extrapolating the regression line obtained.

[0070] The estimated value of the maximum evaporation rate corresponds to the TEmax value obtained in graph (700) (TEmax = 302.48).

[0071] In this case, the units of TE and TEmax are g / m 3 / h. That is, it is the increase per hour (h) of the evaporation amount (g) contained in the unit volume (m 3 ) of the air in the dryer. This enables a quantitative estimation regarding the current TE and TEmax.

[0072] Interpretation: TEmax corresponds to the TE achieved when the HR of the air in the dryer is 0%. In this case, TE is the maximum value reached when completely dry air (HR = 0%) is used in the dryer (if the remaining conditions remain unchanged). If the value of TEmax is abnormally low, it means that the surface of the sausage is very dry and the evaporation rate of the dried product is very slow even if the air in the dryer has 0% HR, and the HR of the air in the dryer rises very slowly (very low TE).

[0073] In addition, when manufacturers of dried products such as salami incorporate additional data such as the air capacity of the dryer, the total mass of the sausages installed in the dryer, the components of the sausage mass, and the total surface of the sausages for that process, the total mass evaporated per unit time, the daily mass reduction of the sausages, the evaporation amount as kg / m 2 / day, etc., a quantitative estimation of that process can be additionally obtained by a simple method.

[0074] Example 3 Figure 8 shows a 3D graph (800) of a set of regression lines of data obtained by the method of the present invention. These regression lines enable the following partial tracking.

[0075] In the XY plane, the cut-off points of HReq show the trajectory of the progress of aws with respect to time, which is similar to that obtained by direct and detailed measurements of the sausage at different stages of the drying process. The product starts with a high aws (close to the aw of emulsified meat), and gradually decreases until it stabilizes at the aw at the end of the dried product, like a dried meat product.

[0076] In the XZ plane, the cut-off points of TEmax show the trajectory of the progress of TEmax with respect to time, and the trajectory is similar to the graph of the trajectory of the drying rate with respect to time. TEmax is initially very high and is maintained while the internal contribution immediately contributes a sufficient mass to evaporation. From a certain point (such as a critical drying point), TEmax, which is the maximum evaporation rate, begins to decrease because the internal contribution can no longer contribute a sufficient mass to the surface for evaporation. Finally, TE becomes very low when the product is almost dry and in equilibrium with the atmosphere.

[0077] In the YZ plane, the regression lines obtained by the process of the present invention are superimposed. As the product drying stage progresses, it is observed that the regression lines gradually have a cut-off point with the Y-axis at a low value. The slope of the line also changes, and it is gradually observed that the slope is larger in the initial stage of the drying stage and smaller in the final stage when the product is already very dry.

[0078] In the XYZ space, the current drying points HRr, TE, and t are distributed on a bundle of straight lines, and these change the slope of the straight lines. If there are some very high TE values (very strong evaporation), the value of TEmax can decrease (symptom of crusting defects).

[0079] By comparing the regression line of the graph (800) with the lateral locus obtained by projecting the regression line onto the plane, it is possible to compare with an example of a standard process. The appearance of partial loci of points and sections that deviate from the standard locus indicates that there may be exceptional situations in the process that need to be reexamined, such as an abnormal decrease in TEmax due to crusting, or a low TEmax value related to other factors such as the use of DFD (dark firm dry) meat or a weak fermentation that does not sufficiently lower the pH of the meat emulsion, for example, the pH of the meat emulsion.

Claims

1. 1. A method for estimating the surface water activity of a product being dried in a dryer, comprising the steps of: the dryer comprises at least one relative humidity HR probe for the dryer atmosphere; The method is carried out by computer means. obtaining, by said at least one relative humidity HR probe, a set of relative humidity HRi values ​​of the dryer atmosphere at a time ti during the drying process of said product; HR based on the relative humidity HRi value during the drying process of the product ｒｉ obtaining a set of percent representative values; Based on a set of HRi and ti values, the evaporation rate TE ｉ obtaining a set of values ​​(% / h); Function F(α, β)=F(HRri, TE ｉ (% / h)) to obtain a regression line, Wherein, α=HReq, β=0 or β=TEmax(% / h), α=0; where HReq is the relative humidity at equilibrium between the air and the surface of the product being dried; Wherein TEmax (% / h) is the maximum evaporation rate (% / h) when the HR of the dryer air is 0; estimating the aws value of the product being dried based on the HReq, where aws=HReq / 100; The set of representative relative humidity HR ri (%) values ​​is HR ri (%)=(HR i +HR i+1 ) / 2, or HR ri (%)=HR i , or HR ri (%)=HR i+1 , or The method corresponds to HR ri (%)=Me(HR i +HR i+1 +...+HR i+N ), where Me is the arithmetic mean of the data number N+1.

2. A method for estimating the surface water activity aws of a product being dried in a dryer, wherein the dryer is provided with at least one temperature probe and a relative humidity HR probe for the atmosphere of the dryer, wherein the method is executed by computer means, a step of obtaining a set of the temperature T value of the dryer and the relative humidity HRi value of the atmosphere at a time point ti during the drying process of the product by the at least one temperature probe and the relative humidity HR probe; from the set of the temperature T value and the relative humidity HRi value, the absolute humidity Habs ｉ a step of obtaining a set of values of the dryer atmosphere at a time point ti during the drying process of the product; a step of obtaining a set of HR ｒｉ (%) representative values based on the relative humidity HRi value during the drying process of the product; Habs ｉ a step of obtaining a set of evaporation rate TE ｉ values (g / m3 / h) based on the set of values and ti values; a step of obtaining a regression line of the function F(α, β) = F(HRri, TE ｉ (g / m3 / h)), wherein in the formula, α = HReq, β = 0 or β = TEmax (g / m3 / h), α = 0, wherein HReq is the relative humidity when the air and the surface of the dried product are in an equilibrium state, wherein TEmax (g / m3 / h) is the maximum evaporation rate (g / m3 / h) when the HR of the air in the dryer is 0, the step; a step of estimating the aws value of the dried product based on HReq, wherein aws = HReq / 100, including, the set of the relative humidity HRri (%) representative values is corresponding to HRri (%) = (HRi + HRi+1) / 2, or corresponding to HRri (%) = HRi, or HR ri (%) = corresponding to HR i+1, or, HR ri (%) = corresponding to Me(HR i + HR i+1 + … + HR i+N), where Me is the arithmetic mean of the number of data N+1, method.

3. The evaporation rate TE ｉ The step of obtaining a set of values (% / h) is TE ｉ (% / h) = (HR ｉ＋１ ―HR ｉ ) / (t ｉ＋１ -t ｉ ), the method according to claim 1.

4. The step of obtaining a set of values (g / m 3 / h) of the evaporation rate TE i is TE i (g / m 3 / h) = (Habs i+1 - Habs i ) / (t i+1 - t i ), the method according to claim 2.

5. A dryer for estimating the surface water activity aws of a dried product, The dryer is provided with at least one relative humidity HR probe for the atmosphere of the dryer, The dryer is provided with a computer medium, and the computer medium Obtaining a set of relative humidity HRi values of the atmosphere of the dryer at time ti in the product drying process using the at least one relative humidity HR probe, Obtaining a set of representative values HR ｒｉ (%) based on the relative humidity HRi values in the product drying process, Obtaining a set of evaporation rate TE ｉ values (% / h) based on the set of HRi values and ti values, Obtaining a regression line of the function F(α,β) = F(HR ri, TE ｉ (% / h)), where α = HReq, β = 0 or β = TEmax (% / h), α = 0, where HReq is the relative humidity when the surface of the air and the dried product is in an equilibrium state, Wherein, TEmax (% / h) is the maximum evaporation rate (% / h) when the HR of the air in the dryer is 0, and estimating the aws value of the surface of the product being dried based on HReq, where aws = HReq / 100, and is configured to perform, the set of representative values of the relative humidity HR ri (%) is corresponding to HR ri (%) = (HR i + HR i+1) / 2, or corresponding to HR ri (%) = HR i, or corresponding to HR ri (%) = HR i+1, or corresponding to HR ri (%) = Me(HR i + HR i+1 + … + HR i+N), where Me is the arithmetic mean of the number of data N + 1, a dryer characterized by this.

6. A dryer for estimating the surface water activity aws of a dried product, the dryer includes at least one relative humidity HR probe and a temperature probe for the atmosphere of the dryer, the dryer includes a computer medium, and the computer medium uses the at least one relative humidity HR probe and the temperature probe to obtain a set of temperature T values and relative humidity HRi values of the atmosphere of the dryer at time ti in the product drying process, from the set of temperature T values and relative humidity HRi values, obtaining a set of absolute humidity Habs ｉ values of the atmosphere of the dryer at time ti in the product drying process, obtaining a set of representative values HR ｒｉ (%) based on the relative humidity HRi values in the product drying process, Habs ｉ obtaining a set of evaporation rate TE ｉ (g / m 3 / h) values based on the set of values and ti values, obtaining a regression line of the function F(α, β) = F(HRri, TE ｉ (g / m 3 / h)), and where α = HReq, β = 0 or β = TEmax (g / m³ / h), α = 0, where HReq is the relative humidity when the surface of the air and the dried product is in equilibrium, where TEmax (g / m³ / h) is the maximum evaporation rate (g / m³ / h) when the HR of the air in the dryer is 0, and estimating the aws value of the surface of the dried product based on HReq, where aws = HReq / 100, are configured to be performed, the set of representative values of the relative humidity HRri (%) is, corresponding to HRri (%) = (HRi + HRi+1) / 2, or corresponding to HRri (%) = HRi, or corresponding to HRri (%) = HRi+1, or corresponding to HRri (%) = Me(HRi + HRi+1 + … + HRi+N), where Me is the arithmetic mean of the number of data N + 1, a dryer characterized by this.

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