Ozone indicator and method for estimating CT value

Abstract

To provide an ozone indicator capable of estimating a CT value in the middle of treatment and the CT value at the end of treatment in sterilization by ozone gas, decomposition of a harmful substance, deodorization, and the like.SOLUTION: An ozone indicator 1 comprises a sheet-like base material 11, and a sensitive portion 12 and a comparison portion 13 that are formed on a surface of the base material so as not to overlap. The sensitive portion is formed by including a coloring matter whose color tone is changed by exposure to ozone gas. The comparison portion is composed of a plurality of CT indexes 16a, ..., and 16g in which the color tone of the sensitive portion in a CT value when reaching a plurality of CT values different from each other in an ozone gas exposure process to the sensitive portion are reproduced by printing and which do not overlap each other.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an indicator for easily confirming the completion of treatment such as sterilization, decomposition of harmful substances, and decolorization using ozone gas. [Background technology]

[0002] For example, since the beginning of the 21st century, there have been epidemics of infectious diseases caused by bacteria, such as Severe Acute Respiratory Syndrome (SARS) and highly pathogenic avian influenza viruses, and outbreaks of avian influenza have been reported frequently at short intervals. Furthermore, in recent years, there have been repeated peaks in infections of the novel coronavirus (COVID-19) every few months each year, and the epidemic has yet to end in Japan.

[0003] There is a high possibility that the equipment and tools used in the testing and treatment of such infectious diseases are contaminated by the pathogens. Therefore, sterilization is required whether the equipment or tools are reused or disposed of as medical waste. In addition, waiting rooms and treatment rooms in internal medicine clinics and hospitals may also be contaminated by pathogens, so it is preferable to sterilize them constantly or periodically.

[0004] It is widely known that ozone gas has a sterilizing effect and can be used to sterilize medical equipment, medical instruments, waiting rooms, treatment rooms, etc., and it has been reported that ozone gas also weakens its activity against the new coronavirus (Non-Patent Document 1). The progress of a sterilization process using such ozone gas, for example of a pathogen, is usually managed by the CT value, which is the product of the ozone gas concentration (ppm) and the contact time (minutes), and such CT value management must be performed using a dedicated CT value management device including an ozone concentration meter. On the other hand, an ozone indicator has been proposed that may enable the progress of a sterilization process using ozone gas to be managed without using such a CT value management device (Patent Document 1). [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent Publication No. 2022-122597 [Non-patent literature]

[0006] [Non-Patent Document 1] (World's first) Inactivation of the new coronavirus by ozone confirmed, February 14, 2020, Nara Medical University, MBT Consortium (Internet, URL: http: / / www.naramed-u.ac.jp / university / kenkyu-sangakukan / oshirase / r2nendo / documents / press_2.pdf) Summary of the Invention [Problem to be solved by the invention]

[0007] The ozone indicator described in Patent Document 1 is arranged in, for example, a sterilization environment using ozone gas, and is formed so that "after sterilization processing, it is possible to easily evaluate by visual inspection whether the processing has been performed appropriately as intended." When the space in which sterilization processing or the like is performed is large and it is not easy to spread ozone gas evenly throughout the entire processing space, the ozone indicator described in Patent Document 1 is arranged in place of an ozone concentration meter (+CT calculator) in multiple locations where ozone gas is unlikely to reach and where there is concern about stagnation, and is suitable for determining whether sterilization or the like has been completed as intended even in locations where there is concern about stagnation (becoming equal to or greater than the end CT value).

[0008] Therefore, the ozone indicator described in Patent Document 1 is not capable of estimating the CT value itself during or at the end of the treatment with ozone gas.

[0009] The present invention has been made in consideration of the above-mentioned problems, and aims to provide an ozone indicator capable of estimating the CT value during or at the end of processing in sterilization, decomposition or deodorization of harmful substances using ozone gas, and a method for estimating the CT value from the ozone indicator. [Means for solving the problem]

[0010] The ozone indicator according to the present invention has a sheet-like substrate, and a sensitive part and a comparative part formed on the surface of the substrate without overlapping. The sensitive part is formed containing a dye whose color tone changes when exposed to ozone gas. The comparative part is composed of a plurality of CT indicators that do not overlap each other and reproduce the color tone of the sensitive part at a plurality of different CT values ​​when the sensitive part reaches the CT value during the ozone gas exposure process. The term "sheet-like" that defines the substrate means a material that has a large surface area compared to its thickness, and includes materials that are not flexible. "Color tone" refers to "the sensory appearance of a color due to the relationship between lightness and saturation," "lightness" refers to "the degree of brightness of a color," and "saturation" refers to "the degree of vividness of a color."

[0011] The ozone indicator preferably has a plurality of CT indicators with a CT value corresponding to the CT indicator written thereon as a numerical value adjacent to the CT indicator.

[0012] Another ozone indicator according to the present invention has a sheet-like substrate, and a sensitive part, a comparison part, and a QR code (registered trademark) formed on the surface of the substrate without overlapping. The sensitive part is formed containing a dye whose color tone changes when exposed to ozone gas. The comparison part is composed of a plurality of CT indicators that do not overlap each other and reproduce the color tones of the sensitive part at a plurality of different CT values ​​reached during the ozone gas exposure process by printing. The QR code (registered trademark) records information for calculating the CT value from the color tone of the sensitive part that changes when exposed to ozone gas and the color tones of the plurality of CT indicators.

[0013] Here, "information for calculating the CT value" refers to, for example, all or any of the following: a URL on the cloud that provides an application that estimates the CT value based on the color change of the sensitive part of this ozone indicator, the aspect ratio of the sensitive part and the CT index, and the CT value (numerical value) corresponding to the color tone of the printed CT index.

[0014] The information recorded in the QR code (registered trademark) is related to the activation of an application capable of calculating a CT value corresponding to the color tone of the sensitive part changed by exposure to ozone gas, and is related to the sensitive part and the comparison part. The information recorded in the QR code (registered trademark) may include CT values ​​corresponding to a plurality of CT indices. As the dye that changes color, any one of bromophenol blue, Coomassie brilliant blue, and food dye is used.

[0015] The CT value estimation method according to the present invention starts with reading the above-mentioned ozone indicator with a digital camera of a computing device. The computing device converts the sensitive part and the multiple CT indices in the ozone indicator into image data with the digital camera. The computing device extracts the area of ​​the sensitive part and the multiple CT indices in the image data, and obtains the color tone of each of the sensitive part and the multiple CT indices as brightness data with 256 gradations. Next, the computing device associates the ascending order of the multiple numerical values ​​stored in the computing device as the numerical values ​​of the CT indices with the descending order of the brightness data, and extracts combinations of brightness data of two CT indices that are larger and smaller than the brightness data of the sensitive part and closest to this brightness data, and the numerical values ​​of two CT indices that correspond to these brightness data.

[0016] Finally, the extracted brightness data and the corresponding CT index values ​​were used to estimate the sensitivity. The CT value corresponding to the brightness data of the response part is calculated, and the calculated value is displayed on the display screen of the calculation device. The "digital camera of the calculation device" is, for example, a digital camera attached to a smartphone or a digital camera attached to a device equipped with a calculation function having a CPU and configured to import photographic data taken with a digital camera.

[0017] Another CT value estimation method according to the present invention starts with reading the QR code (registered trademark) of an ozone indicator with a digital camera of a computing device. The sensitive part and multiple CT indices in the ozone indicator are converted into image data by the digital camera, and the sensitive part and multiple CT indices in the image data are extracted based on the information read from the QR code (registered trademark). The color tones of the sensitive part and multiple CT indices extracted into the regions are calculated as brightness data of 256 gradations.

[0018] "Area extraction" refers to cutting out a target area based on, for example, brightness difference and distinguishing it from other areas. "Area extraction" is a well-known technique.

[0019] The ascending order of the multiple values ​​stored as the numerical values ​​of the CT indices in the QR code (registered trademark) is associated with the descending order of the brightness data, and a combination of the brightness data of two CT indices that are larger and smaller than the brightness data of the sensitive part and are closest to this brightness data and the numerical values ​​of the two CT indices corresponding to these brightness data is extracted. A numerical value as a CT value corresponding to the brightness data of the sensitive part is obtained by an interpolation method from the extracted brightness data and the numerical values ​​of the CT indices corresponding to them.

[0020] The brightness data used in the interpolation method for determining the CT value is preferably the color element with the largest value among the RGB brightness data in the sensitive area, or the RGB brightness data converted into grayscale. Effect of the Invention

[0021] According to the present invention, it is possible to provide an ozone indicator and a method for estimating a CT value that can estimate the CT value during and at the end of a process in sterilization, decomposition of harmful substances, deodorization, and the like using ozone gas. [Brief description of the drawings]

[0022] [Figure 1]FIG. 1 is a diagram showing an outline of an ozone indicator. [Diagram 2] FIG. 2 is a front view of a test device for applying ozone gas to a sample. [Diagram 3] FIG. 3 is a plan view of the test apparatus. [Figure 4] FIG. 4 is a diagram showing the concept of extracting a portion for measuring color density from a sample on a filter paper. [Diagram 5] FIG. 5 is a diagram showing the relationship between the CT value and the rate of change in color density in Table 1. [Figure 6] It is. [Figure 7] FIG. 7 is a graph showing the relationship between the CT value and the remaining rate of color density for food dyes that fade quickly. [Figure 8] FIG. 8 shows the relationship between the CT value and the remaining rate of color density for food dyes with a medium fading rate. [Figure 9] FIG. 9 is a graph showing the relationship between the CT value and the remaining rate of color density for food dyes that fade slowly. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0023] Fig. 1 is a diagram showing an overview of an ozone indicator 1. The ozone indicator 1 has a substrate 11, a sensitive part 12, a comparison part 13, and a QR code (registered trademark) 14. The substrate 11 is a basic part of the ozone indicator 1, and is formed of a slightly elongated rectangular sheet of cardboard or a general-purpose resin such as polypropylene or polystyrene. The surface of the substrate 11 having the sensitive part 12, the comparison part 13, and the QR code (registered trademark) 14 is white or a color of high brightness.

[0024] The sensitive part 12 is formed by applying and drying a base liquid that fades when exposed to ozone gas. The base liquid is prepared, for example, as follows: Bromophenol blue (hereinafter sometimes referred to as "BPB") as a colorant is dissolved in 0.025 mol / L phosphate buffer (pH 6.8) so that the concentration is 0.02%. In this document, "%" indicating the percentage of components means "% by weight" unless otherwise specified.

[0025] BPB is a special grade reagent sold by Fujifilm Wako Pure Chemical Industries, Ltd. 0.025 mol / L phosphate buffer is prepared using neutral phosphate standard solution (pH 6.86) from pH standard solution set 101-S in the LAQUA (registered trademark) series sold by Horiba, Ltd. "Base solution" refers to a solution in which BPB is dissolved in phosphate buffer. Coomassie brilliant blue can be used as a coloring agent.

[0026] The sensing part 12 is formed by dropping a base solution onto a hydrophilic membrane made of polyvinylidene fluoride resin (hereinafter referred to as "PVDF") and allowing it to dry naturally (standing indoors). A membrane filter with a pore size of 5.0 μm and a diameter of 47 mm (registered trademark "Durapore") manufactured by Merck is used as the PVDF hydrophilic membrane. The appearance of the sensing part 12 obtained by natural drying is a bluish purple color with blue accents, and does not visually give the impression of moisture.

[0027] In order to delay the fading of the sensitive part 12 that accompanies an increase in the CT value in ozone gas treatment, sodium thiosulfate is added to the base solution. Sodium thiosulfate slows down the increase in brightness of the sensitive part 12 as its concentration in the base solution increases. Patent Document 1 discloses that adding sodium thiosulfate to the base solution slows down the progression of fading (reduction in color density) that accompanies an increase in the CT value (Patent Document 1, Figures 7 to 10). The progression of fading refers to an increase in brightness.

[0028] The sensitive part 12 is a membrane filter coated with a base solution or the like and dried, which is then shaped into a long and narrow rectangle of predetermined dimensions. The longitudinal direction of the sensitive part 12 is aligned with the longitudinal direction of the substrate 11, and the hydrophilic membrane is fixed to a predetermined position on the substrate 11 with an adhesive.

[0029] The comparison section 13 is composed of a plurality of CT indicators 16a, 16b, 16c, 16d, 16e, 16f, 16g with different brightness. Each CT indicator 16a,...,16g is a rectangle with the width dimension of the sensitive section 12 as its longitudinal length, and all of them have the same vertical and horizontal dimensions. The CT indicators 16a,...,16g are formed of dyes or pigments so that each color tone of the sensitive section 12 and each indicator 16a,...,16g become the same color tone for each of several CT values ​​(e.g., 50, 100, 200,...) from the change in color tone (hue) during the CT value increase process in the exposure of the sensitive section 12 to ozone gas, which is obtained in advance, to the completion of fading. The CT indicators 16a,...,16g are arranged in ascending order of brightness below the sensitive part 12 (in Fig. 1), from one side (the left side in Fig. 1) to the other side (the left side in Fig. 1) in the longitudinal direction of the substrate 11. The leftmost CT indicator 16a has the same color tone as the sensitive part 12 before the application of ozone gas (CT value = 0). Note that "color tone" refers to "the sensory appearance of a color due to the relationship between brightness and saturation," "brightness" refers to "the degree of brightness of a color," and "saturation" refers to "the degree of vividness of a color."

[0030] When any of the CT indices 16a,...,16g has a high brightness (close to the brightness of the surface of the substrate 11) and there is concern that it may be difficult to extract an area in the image data using the brightness difference described later, an ozone indicator 1B is adopted in which the high-brightness CT indices are surrounded by a low-brightness color (e.g., black) (see symbols 16Bf, 16Bg in Fig. 1(b)). The sensitive part 12 and each of the CT indices 16a,...,16Bg are arranged on the substrate 11 so as not to contact each other (so that the surface of the substrate 11 is exposed between them).

[0031] Below each CT index 16a,...,16Bg, the CT value when each color tone appears is shown. In other words, the CT value when the sensitive part 12 fades to the color of the CT indicators 16a,...,16Bg above it due to ozone gas is recorded. This CT value recording allows the user to visually estimate the approximate CT value even in a situation where a CT value estimation application (hereinafter sometimes abbreviated as "estimation app") that runs on a smartphone (abbreviated as "smartphone") or the like, which will be described later, cannot be used. The CT value recorded below the CT indicators 16a,...,16Bg is an example, and the overall value will increase or decrease depending on the sensitivity of the sensitive part 12 to fading due to ozone gas. The least significant digit of the CT value recorded as a numerical value, the digit one place above it, etc. do not have to be "0".

[0032] The comparison section 13 is printed on the substrate 11 by an inkjet printer. The comparison section 13 is protected by a non-glare film (non-glossy film) made of ozone gas resistant polyethylene, polypropylene, nylon, or the like, so that the printed ink does not come into direct contact with ozone gas. The comparison section 13 can also be printed by other digital printing or offset printing, but a printing method and ink that cause little change in color tone over time are selected in advance.

[0033] The QR code (registered trademark) 14 is printed or the like on the substrate 11 so as not to overlap the sensitive portion 12 and the comparison portion 13. The QR code (registered trademark) 14 records the URL of the estimation application on the cloud, the aspect ratio (the ratio of the length to the width of the rectangle) of the sensitive portion 12 in the ozone indicator 1, (one) aspect ratio of each of the CT indices 16a,...,16Bg, and each CT value corresponding to each of the CT indices 16a,...,16Bg.

[0034] The ozone indicator 1 is placed in an environment where sterilization or the like is performed using ozone gas, and is intended to estimate the CT value when sterilization or the like is performed. The CT value is estimated by comparing the brightness of the sensitive part 12, which has faded due to ozone gas, with the brightness of each CT index 16a, . . . , 16Bg of the comparison part 13 in the image data, and by using an interpolation method from (the CT values ​​of) two CT indexes having brightness close to that of the sensitive part 12. The comparison of brightness between the sensitive part 12 and the comparison part 13 is performed using appropriate color elements in image data obtained by photographing the ozone indicator 1 with a digital camera such as a smartphone.

[0035] The image sensor of a digital camera detects only the amount of light, not the wavelength (color) of light. Each pixel in the image data is made up of a digital value of one of the red, green, or blue (hereafter referred to as "RGB") colors obtained through a color filter, and the light value of the other colors interpolated using surrounding pixels. Image data is composed of a group of many RGB pixel data (bitmap data) obtained in this way.

[0036] Next, among the RGB image data of the ozone indicator 1 obtained by photographing with a camera such as a smartphone, we examined the colors (R, G, B) suitable for comparison with the sensing part 12 and the comparison part 13 for estimating the CT value. The sample 20 used in the examination was formed using the base solution containing the above-mentioned BPB. In the examination, the sample 20 was placed in an ozone gas environment until the CT value reached 30, 60, and 100, respectively, and the magnitude of change in color density of each of the R, G, and B elements in the image of the sample 20 photographed with a digital camera was compared.

[0037] Fig. 2 is a front view of the test apparatus 2 used to expose the sample 20 to ozone gas, and Fig. 3 is a plan view of the test apparatus 2. The test apparatus 2 consists of a container 21, an ozone generator 22, a humidifier 23, a thermometer, a hygrometer 24, an ozone concentration meter 25, and a CT value recorder. The container 21 is a hollow rectangular box, and the top is closed with a removable lid 26. The container 21 is made of transparent polyvinyl chloride resin so that the inside can be easily observed from the outside.

[0038] The ozone generator 22 includes an ozone lamp (ultraviolet lamp) and a forced circulation fan. The humidifier 23 is a known stationary ozone gas generator. The device vibrates the water by applying an AC voltage of 100 V to the water, which generates ultrasonic waves that generate mist, which is then discharged to the outside from the discharge port 27. The hygrometer 24 measures and displays the humidity inside the container 21. The hygrometer 24 is housed in the container 21 .

[0039] The ozone concentration meter 25 is a known device that is installed in the container 21 and measures the ozone gas concentration in the container 21. The ozone concentration meter 25 has an external control unit (not shown), and the control unit digitizes the measured ozone concentration and transmits it to the CT value recording device. The sample stage 28 in Figures 2 and 3 is for placing the sample 20 on it.

[0040] The CT value recorder calculates the increment of the CT value (=ozone concentration x interval time) from the ozone concentration transmitted from the ozone concentration meter 25 and the transmission interval (time), integrates this increment from the time when the ozone gas exposure treatment started, and displays the integrated value on the display device. A personal computer is used as the CT value recorder.

[0041] The study was performed by placing the sample 20 on the sample stage 28, and controlling the operation of the ozone generator 22 with the control unit of the ozone concentration meter 25 so that the measurement value of the ozone concentration meter 25 reached a predetermined concentration (5 ppm or 30 ppm). The temperature of the air conditioner in the room in which the test device 2 was installed was set so that the temperature inside the container 21 was kept at 20°C, and it was periodically confirmed by a thermocouple inserted inside the container 21 that the temperature inside the container 21 was within this range. The sample 20 was exposed to ozone gas in the test device 2 until the CT values ​​reached 30, 60, and 100, respectively, and the magnitude of change in color density of each of the R, G, and B elements in image data taken with a digital camera of the sample 20 removed from the test device 2 was compared.

[0042] FIG. 4 is a diagram showing the concept of extracting a portion of the sample 20 on the filter paper 31 for measuring color density. The sample 20 exposed to ozone gas is placed on the filter paper 31 after the exposure is completed. The filter paper 31 used is qualitative filter paper No. 2 manufactured by Advantech. The sample 20 placed on the filter paper 31 is photographed under standardized conditions with a digital camera fixed to a stand under fluorescent lighting. "Standardized conditions" means the same (standardized) conditions in terms of the camera, the distance between the camera and the subject, the brightness of the shooting environment, the number of pixels for shooting, the shooting sensitivity, the aperture value, the shutter speed, the white balance, etc.

[0043] The entire filter paper 31 including the sample 20 is photographed, and the image data is imported into a computer, and the color density of the sample is calculated using the analysis software ImageJ1.52v (download from URL: https: / / imagej.jaleco.com / ). The imported image is decomposed into the three primary colors (RGB) of light by ImageJ1.52v on the computer, and the density of each of the R (red), G (green), and B (blue) elements of a portion 32 of the sample 20 and a portion 33 of the filter paper 31 with the same area is calculated. The image decomposed into the three RGB elements is monochrome with only light and dark, and the "density" that is calculated is actually the "lightness (actually darkness)" of each element. The "color density" mentioned above is the value obtained by subtracting the "density" value of the filter paper 31 from the "density" value of the sample 20 in each element.

[0044] Table 1 shows the relationship between the CT value and the rate of change in color density of sample 20 when ozone gas is applied to sample 20.

[0045] [Table 1]

[0046] Each value in the "color density change rate" in Table 1 is a value indicating the rate of change (discoloration) of the color density calculated by the method described above (using ImageJ1.52v) multiplied by "-1" relative to the color density of sample 20 (CT value 0 before the application of ozone gas). Also, "pseudo NTSC" in Table 1 was calculated by weighting the R, G, and B elements respectively, imitating the NTSC weighted average method used when converting digital color images to monochrome images (pseudo NTSC = 0.29891 x R element + 0.58661 x G element + 0.11448 x B element).

[0047] The NTSC weighted average method is a processing method related to luminance (brightness of the screen, unrelated to color). Luminance is slightly different from lightness (brightness of the color), but since they are both considered "brightness," the NTSC weighted average method was used as a processing method that takes into account all of the R, G, and B elements.

[0048] FIG. 5 is a diagram showing the relationship between the CT value and the color density change rate in Table 1. From FIG. 5, when bromophenol blue is used as the coloring agent of the sensitive part 12, focusing on the R and G elements, it can be seen that the color density change rate is large and is approximately proportional to the CT value. In addition, the color density change rate by "pseudo NTSC" processing using the NTSC weighted average method used when converting a color image to a monochrome image is also approximately proportional to the CT value. In the ozone indicators 1 and 1B, the CT value after exposure to ozone gas can be estimated by using image data of the R and G elements of the sensitive part 12 or image data processed by imitating the NTSC weighted average method for the three elements R, G, and B.

[0049] Next, we will explain the procedure for estimating the CT value indicated by the fading of the sensitive part 12 using an estimation app from image data taken with a smartphone of the ozone indicator 1 that was placed in an environment treated with ozone gas and then recovered.

[0050] Figure 6 is a flow diagram showing the process of estimating the CT value using an estimation app. First, the QR code (registered trademark) 14 on the ozone indicator 1 is read by a smartphone (S1). The QR code (registered trademark) 14 contains the URL of the estimation app on the cloud and information on the sensing part 12 and CT indicators 16a,...,16Bg of the ozone indicator 1.

[0051] The worker (the person estimating the CT value) launches the estimation app on the cloud from the URL read by the smartphone. The estimation app on the cloud is launched by tapping the URL displayed on the smartphone screen after reading the QR code (registered trademark) 14. The estimation app stores other information recorded in the QR code (registered trademark) in memory as constants (S1). Next, the smartphone's camera function is activated, and the sensor part 12 and comparison part 13 of the ozone indicator 1 are displayed on the screen in full screen. You will be prompted to enter (S1).

[0052] When the smartphone camera captures the sensitive portion 12 and the comparison portion 13 on the entire screen (YES in S3), the estimation application judges whether the sensitive portion 12 and each CT marker 16a,...,16Bg can be individually identified, and if they can be identified (YES in S4), stores the judged image (one frame, still image). The estimation application judges whether they can be identified based on whether it is possible to extract an area (extract a group of pixel data surrounded by an outline with a lower brightness than the base material 11) using the brightness difference from the image data. When the area is extracted, the aspect ratio of the area is calculated, and these aspect ratios are compared with the aspect ratios of the sensitive portion 12 and the CT markers 16a,...,16Bg stored in the memory, and it is determined whether the extracted area is the sensitive portion 12 or the comparison portion 13 (S5). Regarding the comparison units 13, if the number of CT values ​​(e.g., 0, 50, 100, 200, 300, ...) recorded in the QR code (registered trademark) matches the number of comparison units 13 that have been identified, it is determined that the code has been recognized (S5). "Area extraction" refers to cutting out the target area based on, for example, brightness difference and distinguishing it from other areas. "Area extraction" is a well-known technique.

[0053] Once the sensitive area 12 and each area of ​​the CT indicators 16a,...,16Bg are identified, the average brightness of each area is calculated from the pixel data of these areas (S6). For example, in the case of an ozone indicator 1 that uses BPB as a colorant, the brightness is calculated from Table 1 and Figure 5 as either the R and G pixel data or a value indicating the brightness calculated by the NTSC weighted average method. "Brightness" is the amount of light of each pixel expressed as a value between 0 and 255 (higher brightness = larger value).

[0054] At this stage, the estimation application recognizes that the ozone indicator 1 has seven CT indices 16a,...,16Bg, and recognizes the average brightness value of the extracted region of the sensitive part 12 and each average brightness value of the seven CT indices 16a,...,16Bg. The estimation application arranges the average brightness values ​​of the seven CT indices 16a,...,16Bg in ascending order, and associates them with the seven CT values ​​arranged in ascending order read from the QR code (registered trademark) 14. That is, in the above example, the smallest average brightness is associated with a CT value of 0, the next smallest average brightness with a CT value of 50, and so on (S6).

[0055] The estimation application calculates the average brightness of the pixels in the image data corresponding to the sensitive area 12, and extracts the nearest brightnesses larger and smaller than this brightness and the CT values ​​associated with them (S7). For example, if the average brightness values ​​in 256 gradations of the CT indices 16a,...,16Bg associated with CT values ​​of 0, 50, 100, 200, and 300 are 30, 37, 41, 60, and 75, respectively, and the average brightness value of the sensitive area 12 is 58, then the combination of brightness 41 and CT value 100 and the combination of brightness 60 and CT value 200 are extracted.

[0056] From these two combinations, the estimation app determines the linear coefficient C1 and constant C2 in the linear equation "CT value = C1 × lightness + C2" where the independent variable is lightness and the dependent variable is the CT value (S8). In this example, the linear equation is "CT value = 5.26 × lightness - 115.8", and if the lightness of the sensitive part 12 is 58, for example, 58 is substituted for the lightness to determine the CT value as 189 (S9). The estimation app displays the determined CT estimated value on the smartphone screen and ends the CT estimation process.

[0057] A smartphone operates with a microcomputer (CPU) and can be considered as a "computing device (having a digital camera)" that performs the above processing. The above processing can also be performed by a computing device that has a digital camera and is specialized for estimating CT values.

[0058] The dye in the base liquid used in the sensitive section 12 may be food dye.

[0059] Therefore, we investigated the possibility of using various food dyes as CT indicators, that is, the relationship between the degree of fading due to exposure to ozone gas and the CT value (fading speed, ozone sensitivity). For the investigation, the dyes in the above-mentioned base solution, which uses BPB as a coloring agent, were replaced with various food dyes, and samples were used that were prepared with the same solvent and food dye concentrations as when BPB was used as the dye. In addition, the samples were exposed to ozone gas using the test device 2 shown in Figures 2 and 3, and the exposure conditions were the same as those for sample 20.

[0060] Table 2 shows the color density and applicability to the sensitive part 12 for each RGB element, which was examined by preparing samples using a base solution containing commercially available food coloring.

[0061] [Table 2]

[0062] The food dyes used in Table 2 were as follows: (a) Food coloring test control solution set A sold by Tokyo Chemical Industry Co., Ltd. The following food dyes are each provided as 0.1% solutions in water:

[0063] (A-1) Food Red No. 2 (Amaranth) (A-2) Food Red No. 3 (Erythrosine) (A-3) Food Red No. 40 (Allura Red AC) (A-4) Food Red No. 102 (New Coccin) (A-5) Food Red No. 104 (Phloxine) (A-6) Food Red No. 105 (Rose Bengal) (A-7) Food Red No. 106 (Acid Red) (A-8) Food Yellow No. 4 (Tartrazine) (A-9) Food Yellow No. 5 (Sunset Yellow FCF) (A-10) Food Green No. 3 (Fast Green FCF) (A-11) Food Color Blue No. 1 (Brilliant Blue FCF) (A-12) Food Blue No. 2 (indigo carmine) (b) Food coloring test control solution set B sold by Tokyo Chemical Industry Co., Ltd. The following food dyes are each provided as 0.1% solutions in water:

[0064] (B-3) Ponceau R (formerly Food Red No. 101) (B-4) Eosin (formerly Food Red No. 103) (B-5) Naphthol Yellow S (formerly Food Yellow No. 1) (B-6) Light Green SF Yellow (formerly Food Green No. 2) (B-7) Orange I (formerly Food Orange No. 1) (B-8) Orange II (B-9) Multi-light yellow (B-10) Uranine (B-11) Guinea Green B (formerly Food Green No. 1) (B-12) Brilliant Milling Green (B-13) Azure Blue VX (B-14) Acid Violet 6B (formerly Food Purple No. 1) (c) (B-1) New Coccin (Red No. 1): Fujifilm Wako Pure Chemical (B-2) Tartrazine (Yellow No. 4): Fujifilm Wako Pure Chemical Table 3 shows the relationship between the CT value and the residual rate of color density of each representative color of food coloring when samples prepared using each food coloring in Table 2 as a coloring agent are exposed to ozone gas. Here, the "representative color of food coloring" refers to the color element (of interest) with the largest value (shaded in Table 2) for each food coloring in Table 2.

[0065] [Table 3]

[0066] The color density in Table 2 and the color density retention rate in Table 3 were determined by photographing with a digital camera and using the analysis software ImageJ1.52v in the same manner as in Sample 20, which used BPB as the colorant.

[0067] Figures 7 to 9 are diagrams showing the relationship between the CT value and the residual rate of color concentration for each food dye shown in Table 3. The fading speed in Table 3 was evaluated as "fast" (Figure 7) for the group with a CT value of less than 800 and a residual rate of 10% or less, "medium" (Figure 8) for the group with a CT value of 800 or more and less than 2600 and a residual rate of 10% or less, and "slow" (Figure 9) for the group with a CT value of 2600 or more and a residual rate of 10% or less.

[0068] When forming the sensitive portion 12 using a single food dye as a coloring agent, if the largest value of any of the RGB elements in the RGB analysis is 10 times or more larger than either of the other two values, then it is preferable as a dye for forming the sensitive portion 12 (Table 2). In estimating the CT value in the "Estimation App," if the image data of the color element with the largest value is processed, the other color elements will not affect the CT value. This is because there is less interference and the accuracy is improved.

[0069] As can be seen from Table 3 and Figures 7 to 9, by selecting an edible dye, it is possible to form an ozone indicator 1 that is suitable for various cases, from cases where sterilization or other processes using ozone gas are completed in a short time (processing is completed with a low CT value) to cases where the process requires a long time (a high CT value is required to complete the process).

[0070] For the sensitive part 12 formed from blue BPB, it was appropriate to process image data of the R and G elements or image data obtained by processing the three elements R, G, and B according to the NTSC weighted average method in the estimation application according to Table 1 and Figure 5. In contrast, when the sensitive part 12 is formed from a food dye that is available (◯) in Table 2, the image data of the color element showing the largest value among RGB or image data obtained by gray-scaling all RGB according to the NTSC weighted average method is used in the estimation application that performs CT value estimation.

[0071] In the ozone indicator 1 in which the sensitive part 12 is formed with an edible dye, information on the "representative color of the edible dye" (for example, the text information "R" or the text information "R, NTSC") is recorded in the QR code (registered trademark) 14, and the estimation application calculates an estimated CT value based on the image data of this recorded color.

[0072] The sensitive part 12 can be formed using two different colors of food dyes that are available in Table 2. The two different colors of food dyes may be any combination of food dyes that fade at approximately the same rate due to ozone gas, or food dyes that fade at different rates. When the sensitive part 12 is formed using food dyes of two colors, the estimation app quantifies the sensitive part 12 and the comparison part 13 using the color element that has the largest value of the color density in Table 2, or a grayscale using the NTSC weighted average method, and uses this to estimate the CT value.

[0073] In particular, the sensitive part 12 using two food dyes with different fading speeds changes in hue and tone during the fading process caused by ozone gas. Therefore, it is easy to visually compare the sensitive part 12 with the comparison part 13, 13B (CT indicators 16a,...,16Bg) without relying on an estimation app, and is suitable for cases where you want to know the approximate CT value. Note that "hue" refers to differences in color such as "red," "yellow," and "blue."

[0074] When the sensitive part 12 of the ozone indicator 1, 1B is formed with food coloring, each CT indicator 16a,...,16Bg of the comparison part 13, 13B expresses each color tone of the fading process of the sensitive part 12 by ozone gas by printing. The ozone indicator 1, 1B can estimate the approximate CT value in the treatment by exposure to ozone gas more easily by visually comparing the sensitive part 12 faded by ozone gas with the CT indicator 16a,...,16Bg. In addition, the ozone indicator 1, 1B can estimate the CT value at the end of the ozone gas treatment with higher accuracy than visual inspection by using an estimation app in combination.

[0075] The estimation of the CT value by visual inspection and the estimation app can be performed even during the exposure process using ozone gas. Under the restriction that the estimation of the CT value is performed only by the brightness (grayscale) using the estimation app, the ozone indicators 1 and 1B can form the CT indicators 16a,...,16Bg in achromatic colors. Even if the color tone of the sensitive part 12, which fades as the CT value increases, cannot be reproduced in the CT indicators 16a,...,16Bg by printing, the CT indicators 16a,...,16Bg are formed in achromatic colors, and the processing by the estimation app is performed only by brightness.

[0076] In the above-mentioned embodiment, the QR code (registered trademark) 14 of the ozone indicator 1, 1B is provided with the product number of the ozone indicator (an icon for distinguishing between multiple types of ozone indicators). The system (system) is recorded, and based on the product number (QR code (registered trademark) 14) read by a smartphone camera or the like, information regarding the number of CT indices 16a,...,16Bg of the comparison units 13, 13B, the CT values ​​corresponding to each of the CT indices 16a,...,16Bg, the aspect ratios of each, etc., required for processing by the estimation app is downloaded from a cloud server.

[0077] If a CT value estimation application is installed in advance on a smartphone, or if a dedicated estimation device incorporating this application is used, there is no need to record the URL of the estimation app on the cloud in the QR code (registered trademark) 14. If there is only one type of ozone indicator 1, 1B, and the number of CT indicators 16a,...,16Bg and the CT value indicated by each CT indicator 16a,...,16Bg are also only one type, each aspect ratio and each CT value is invariant and can be incorporated into the CT value estimation application as a constant. In this case, the QR code (registered trademark) 14 of the ozone indicator 1, 1B is not necessary.

[0078] The term "color tone" as mentioned above is to be understood as meaning "the sensory appearance of a color due to the three attributes of color: hue, saturation, and brightness" in the case of a discolored area formed by using two different colors of food dyes, in which the hue changes during the fading process caused by ozone gas.

[0079] In the above-mentioned embodiment, the ozone indicators 1 and 1B and the respective components or the overall structure, shape, material, etc. of the ozone indicators 1 and 1B can be appropriately modified in accordance with the spirit of the present invention. In the CT estimation algorithm of the CT value estimation application operated on a smartphone or the like, the procedure for extracting the sensitive part 12 and the comparison part 13 from the digital image data, and the procedure for finding the CT value by comparing the color tone or brightness, etc. of these, can be arbitrarily modified in accordance with the spirit of the present invention. [Industrial Applicability]

[0080] The present invention can be used to estimate the CT value during and at the end of sterilization, decomposition of harmful substances, deodorization, and the like using ozone gas. [Explanation of symbols]

[0081] 1,1B Ozone Indicator 11 Base material 12 Sensory section 13 Comparison section 14 QR Code (registered trademark) 16a,16b,16c,16d,16e,16f,16g,16Bf,16Bg CT index

Claims

1. A sheet-like substrate; A sensitive part and a comparative part formed on the surface of the base material so as to avoid overlapping; having the sensitive portion is formed containing a dye whose color tone changes when exposed to ozone gas, The comparison section is constituted by a plurality of CT indices that do not overlap with each other and reproduce the color tones of the sensitive part at the CT values ​​when the sensitive part reaches a plurality of different CT values ​​during the ozone gas exposure process.

1. An ozone indicator comprising:

2. The CT value corresponding to each of the CT indices is written in a numerical value near each of the CT indices.

2. An ozone indicator according to claim 1.

3. A sheet-like substrate; A sensitive part, a comparative part, and a QR code (registered trademark) formed on the surface of the substrate while avoiding overlapping; having the sensitive portion is formed containing a dye whose color tone changes when exposed to ozone gas, the comparison part is composed of a plurality of CT indices which do not overlap each other and which reproduce by printing the color tones of the sensitive part at the CT values ​​when the CT values ​​reach a plurality of different CT values ​​during the ozone gas exposure process, The QR code (registered trademark) records information for calculating a CT value from the color tone of the sensitive part that changes when exposed to ozone gas and the color tones of the multiple CT indices.

1. An ozone indicator comprising:

4. The information recorded in the QR code is The present invention relates to an application for calculating a CT value corresponding to a color tone of the sensitive part that has changed due to exposure to ozone gas, and a sensitive part and a comparison part.

4. An ozone indicator according to claim 3.

5. The information recorded in the QR code is are CT values ​​corresponding to the plurality of CT indices.

4. An ozone indicator according to claim 3.

6. The dye that changes color is Bromophenol blue, Coomassie brilliant blue, or food coloring 6. An ozone indicator according to any one of claims 1 to 5.

7. The ozone indicator according to claim 1 or 2 is read by a digital camera of a computing device, The sensitive portion and the plurality of CT indices in the ozone indicator are converted into image data by the digital camera; Extracting regions of the sensitive area and the plurality of CT markers in the image data; determining color tones of the sensitive area and the plurality of CT indices as 256-level brightness data; Corresponding the ascending order of the plurality of numerical values ​​stored in the arithmetic device as the numerical values ​​of the CT indices to the descending order of the brightness data; The two C values ​​that are larger and smaller than the brightness data of the sensitive portion and are closest to this brightness data Extracting the brightness data of the T indices and the combinations of the values ​​of the two corresponding CT indices; A CT value corresponding to the brightness data of the sensitive area is calculated by an interpolation method from the extracted brightness data and the corresponding values ​​of the CT index. A method for estimating a CT value comprising:

8. The QR code (registered trademark) of the ozone indicator according to any one of claims 3 to 5 is read by a digital camera of a computing device, The sensitive portion and the plurality of CT indices in the ozone indicator are converted into image data by the digital camera; Extracting regions of the sensitive area and the plurality of CT markers in the image data based on information read from the QR code (registered trademark); determining color tones of the sensitive area and the plurality of CT indices as 256-level brightness data; The ascending order of the plurality of numerical values ​​stored as the numerical values ​​of the CT indices in the QR code is associated with the descending order of the brightness data; Extracting combinations of brightness data of two CT indices that are larger and smaller than the brightness data of the sensitive area and are closest to the brightness data, and the numerical values ​​of the two CT indices corresponding thereto; A CT value corresponding to the brightness data of the sensitive area is calculated by an interpolation method from the extracted brightness data and the corresponding values ​​of the CT index. A method for estimating a CT value comprising:

9. The brightness data used in the interpolation method is the color element having the largest value among the RGB brightness data in the sensitive area, or the RGB brightness data converted into grayscale. The method for estimating a CT value according to claim 7.

10. The brightness data used in the interpolation method is the color element having the largest value among the RGB brightness data in the sensitive area, or the RGB brightness data converted into grayscale. The method for estimating a CT value according to claim 8.

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