A method for monitoring the growth state of lentinus edodes based on temperature data

Abstract

The present application relates to the technical field of image processing, in particular to a kind of monitoring method of shiitake mushroom growth state based on temperature data, the method comprises: obtaining the cover image of shiitake mushroom at different temperatures and other growth environments are same, and obtaining crack area in shiitake mushroom cover image, the included angle of the edge point on the edge line of crack area and transverse coordinate axis direction is obtained, the angle range of the included angle of crack area edge point is equally divided into four angle intervals, the energy eigenvalue of each direction's gray level co-occurrence matrix and energy eigenvalue weight are obtained, and comprehensive energy eigenvalue is obtained, the curve of temperature-feature value is constructed, the slope difference of two adjacent lines on the curve is obtained to obtain temperature saturation interval, and the optimal temperature interval is obtained, the texture of shiitake mushroom cover is accurately obtained, so as to accurately determine the optimal temperature interval.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of image processing, in particular to a method for monitoring growth state of Lentinula edodes based on temperature data. BACKGROUND

[0002] Lentinula edodes is a temperature-dependent edible fungus, and the temperature effect is very large in the whole growth and development process, especially in the process of fruiting body formation. Too high or too low temperature will cause adverse effects, even death. Different Lentinula edodes varieties have different sensitivities to temperature in spore germination, mycelium growth or fruiting body formation. The shape, color, quality and growth rate of Lentinula edodes fruiting body are closely related to temperature. Under appropriate high temperature, Lentinula edodes grows rapidly, the cap is easy to open, the shape is not round, the cap is rough, the color is slightly white, and the quality is poor. In low temperature environment, Lentinula edodes grows slowly, the body is round and correct, the color is dark, the texture is dense, and it is easy to form flower mushroom in low temperature and dry environment, and the quality is also good.

[0003] At present, the detection technology for the growth environment of Lentinula edodes is to set a suitable temperature range of 22-26℃ by experience, so that Lentinula edodes grows and develops in this temperature range. However, the highest quality of Lentinula edodes cannot be reached. Therefore, the precision of temperature setting in the prior art is low, resulting in low quality of Lentinula edodes. SUMMARY

[0004] The present application provides a method for monitoring the growth state of Lentinula edodes based on temperature data to solve the problem of inaccurate temperature setting.

[0005] The method for monitoring the growth state of Lentinula edodes based on temperature data provided by the present application adopts the following technical scheme:

[0006] Obtain the cap surface image of Lentinula edodes under different temperatures and other growth environments, and obtain the crack area in the cap surface image of Lentinula edodes;

[0007] According to the coordinates of each edge point in the crack area, the angle between the edge point on each edge line and the horizontal coordinate axis direction is obtained, the angle range of all edge point angles of the crack area is equally divided into four angle intervals, and the four angle intervals are one-to-one corresponding to the four directions of the gray level co-occurrence matrix;

[0008] Obtain the energy eigenvalue of the gray level co-occurrence matrix of the cap surface image in each direction, obtain the energy eigenvalue weight of the gray level co-occurrence matrix in the corresponding direction according to the number of edge points corresponding to the inclination angle in each angle interval and the total number of pixel points of the cap surface image of Lentinula edodes, and obtain the comprehensive energy eigenvalue according to the energy eigenvalue weight and the energy eigenvalue;

[0009] The cover surface images of the shiitake mushrooms at different temperatures are taken as a group of images, a corresponding temperature-feature value curve is constructed according to a corresponding comprehensive energy feature value of each group of images at each temperature, a slope of a line connecting each two adjacent points on the curve is obtained, and whether a temperature interval corresponding to two end points of the two adjacent lines is a temperature saturation interval is determined according to a slope difference value of each two adjacent lines and a preset difference value threshold.

[0010] An intersection interval is obtained by taking an intersection of the temperature saturation intervals corresponding to all the groups of images, and the intersection interval is taken as an optimal temperature interval.

[0011] Preferably, the method further comprises:

[0012] A length of the edge line in the crack region is obtained.

[0013] A circle is fitted to the cover surface contour of the shiitake mushroom, and a half of a radius of the circle is taken as a length threshold of the edge line.

[0014] An included angle between an edge point on the edge line with a length greater than or equal to the length threshold and a horizontal coordinate axis direction is calculated.

[0015] Preferably, the step of obtaining the included angle between the edge point and the horizontal coordinate axis direction comprises:

[0016] A coordinate system is established with a center of the shiitake mushroom cover surface at each temperature as a coordinate origin.

[0017] A coordinate of an edge point on the edge line of each crack region is obtained.

[0018] A ratio of a horizontal coordinate to a vertical coordinate of the edge point is obtained.

[0019] An inverse tangent value of the ratio of the horizontal coordinate to the vertical coordinate of the edge point is taken as the included angle between the edge point and the horizontal coordinate axis direction.

[0020] Preferably, the step of obtaining the temperature saturation interval corresponding to each curve comprises:

[0021] When the slope difference value of each two adjacent lines is greater than the preset difference value threshold, a common connection point of the two lines is taken as a saturation point.

[0022] A temperature interval corresponding to two points adjacent to the saturation point on the curve is taken as a temperature saturation interval.

[0023] Preferably, the slope difference value is normalized, the normalized slope difference value is compared with the preset difference value threshold, when the normalized slope difference value of each two adjacent lines is greater than the preset difference value threshold, the common connection point of the two lines is taken as the saturation point, and the temperature interval corresponding to the two points adjacent to the saturation point on the curve is taken as the temperature saturation interval.

[0024] Preferably, the included angle ranges from 0° to 180°, and the range of 0° to 180° is divided into four equal angle intervals.

[0025] Preferably, the steps for obtaining the comprehensive energy characteristic value are as follows:

[0026] The ratio of the number of edge points corresponding to the tilt angle in each angle interval to the total number of pixels in the mushroom cap image is used as the energy feature value weight of the gray-level co-occurrence matrix corresponding to the angle interval.

[0027] The comprehensive energy characteristic value is obtained by weighting and summing the energy characteristic values ​​corresponding to the four angle intervals.

[0028] Preferably, the different temperatures corresponding to the cover image are 22℃, 23℃, 24℃, 25℃, and 26℃.

[0029] Preferably, the method for acquiring the cover image includes:

[0030] Semantic segmentation was performed on each of the acquired shiitake mushroom images after Gaussian filtering and noise reduction to obtain the shiitake mushroom image.

[0031] Image of the mushroom cap.

[0032] Preferably, the preset difference threshold is 0.2.

[0033] The beneficial effects of the method for monitoring the growth status of shiitake mushrooms based on temperature data according to the present invention are:

[0034] By analyzing the texture of shiitake mushrooms, the direction of the texture portion is obtained, and the energy feature value weight under each direction is obtained based on the number of edge points and the total number of pixels in the texture portion. The comprehensive energy feature value is obtained by using the energy feature value and energy feature value weight of the gray-level co-occurrence matrix, thereby accurately reflecting the texture of the shiitake mushroom cap. Then, the temperature-feature value curve is obtained by combining the temperature and the comprehensive energy feature value, and the temperature saturation range of each group of shiitake mushrooms when the texture is maximized is analyzed. Finally, the optimal temperature range is obtained for the temperature saturation range of all groups of shiitake mushrooms, which provides a reference for temperature regulation during the growth process of shiitake mushrooms. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1A flow chart of an embodiment of a method for monitoring the growth state of Lentinula edodes based on temperature data. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0038] An embodiment of a method for monitoring the growth state of Lentinula edodes based on temperature data, as shown in the figure, Figure 1 specifically includes:

[0039] S1, acquiring cap surface images of Lentinula edodes under different temperatures and other growth environments, and acquiring crack regions in the cap surface images of Lentinula edodes.

[0040] Specifically, in the embodiment, the growth temperatures of Lentinula edodes are set to 22℃, 23℃, 24℃, 25℃ and 26℃ in turn, and then the other growth environments and growth stages of Lentinula edodes are controlled to be the same. Then, a camera is used to collect Lentinula edodes images at different growth stages under each growth temperature from the top to the bottom. In order to avoid the influence of pulse noise, mechanical noise and light pollution on the collected images, Gaussian filter denoising processing is performed on the collected Lentinula edodes images, and semantic segmentation is performed on each Lentinula edodes image after Gaussian filter denoising to obtain cap surface images of Lentinula edodes.

[0041] Since Lentinula edodes with cracks, also known as flower mushrooms, is a kind of superior mushroom produced by Lentinula edodes under special environment, and the fact that the cap surface of Lentinula edodes is cracked indicates that more nutrients are accumulated, and the content of protein, amino acid and mineral substance is very high, therefore, the nutritional value of flower mushrooms is higher, and the organization is compact, the flavor is rich, and the taste is tender. The texture of the cap surface of Lentinula edodes is affected by temperature, and the cap surface texture of poor quality Lentinula edodes is dense and smooth; on the contrary, the cap surface of good quality Lentinula edodes is cracked and gully, so in the embodiment, the crack region, i.e. the texture region, in the cap surface image is acquired first.

[0042] S2, obtaining the included angle between each edge point in the crack region and the horizontal coordinate axis direction, equally dividing the angle range of the included angle of the edge points of all crack regions into four angle intervals, and one-to-one corresponding the four angle intervals with the four directions of the gray level co-occurrence matrix.

[0043] Since a conventional image is rectangular, four direction gray level co-occurrence matrices of 0°, 45°, 90° and 135° can be obtained, and then the texture can be described by summing and averaging. However, the surface of a Lentinus edodes cap is approximately circular, and the cracking of the surface of a Lentinus edodes cap is generally in a chrysanthemum shape. Therefore, in order to efficiently and obviously count the gray level pairs and reflect the texture difference between the cracked and uncracked Lentinus edodes caps, the direction statistics of the gray level pairs are obtained according to the direction of the crack region of the Lentinus edodes cap in the embodiment.

[0044] Since the crack has a certain width, there are two edge lines for each crack, and the cracking angle of each crack needs to be calculated by calculating the angle between the upper edge point of the two edge lines corresponding to each crack and the horizontal coordinate axis. In the embodiment, the steps for obtaining the angle between the edge point on each edge line and the horizontal coordinate axis are as follows: establishing a coordinate system with the center of the Lentinus edodes cap at each temperature as the coordinate origin; obtaining the coordinates of the edge point on the edge line of each crack region; obtaining the ratio of the horizontal coordinate and the vertical coordinate of the edge point; and taking the inverse tangent value of the ratio of the horizontal coordinate and the vertical coordinate of the edge point as the angle between the edge point and the horizontal coordinate axis, wherein the calculation formula of the angle between the edge point and the horizontal coordinate axis is:

[0045]

[0046] In the formula, θ i represents the angle between the i th edge point on the edge line and the horizontal coordinate axis;

[0047] x i represents the horizontal coordinate of the i th edge point on the edge line;

[0048] y i represents the horizontal coordinate of the i th edge point on the edge line;

[0049] represents the inverse tangent value of the absolute value of the ratio of the horizontal coordinate and the vertical coordinate, and the purpose is to limit the angle to 0° to 180°.

[0050] Specifically, since the included angle calculated by the calculation formula of the included angle between the edge point and the horizontal coordinate axis direction is limited to 0° to 180°, the four angle intervals are [0°, 44°], [45°, 89°], [90°, 134°], and [135°, 180°] in turn, and the gray level co-occurrence matrix is generally a gray level co-occurrence matrix of 0° direction, a gray level co-occurrence matrix of 45° direction, a gray level co-occurrence matrix of 90° direction, and a gray level co-occurrence matrix of 135° direction, so in the embodiment, the four angle intervals are corresponded to 0° direction, 45° direction, 90° direction, and 135° direction in the following order: [0°, 44°], [45°, 89°], [90°, 134°], and [135°, 180°].

[0051] Since the texture of a good quality Lentinula edodes cap surface is dense and smooth, and the texture of a poor quality Lentinula edodes cap surface is cracked and gully, and the quality is good when the edge line is short, in order to reduce the calculation amount, the edge line needs to be screened before calculating the included angle between the edge point on the edge line and the horizontal coordinate axis direction, specifically, the length of the edge line in the crack region is obtained; a circle is fitted to the cap surface contour of Lentinula edodes, and half of the radius of the circle is taken as the length threshold of the edge line; the included angle between the edge point on the edge line with a length greater than or equal to the length threshold and the horizontal coordinate axis direction is calculated, wherein the length threshold is obtained by obtaining the distance from each point on the circle fitted to the cap surface contour of Lentinula edodes to the center of the circle, and then the radius of the circle fitted to the cap surface contour is obtained by averaging all the distances, and then half of the radius is taken as the length threshold of the edge line, and each edge line is judged.

[0052] S3, obtaining the energy feature value of the gray level co-occurrence matrix of the cap surface image in each direction, obtaining the energy feature value weight of the gray level co-occurrence matrix in the direction corresponding to each angle interval according to the number of edge points corresponding to the inclined angle in each angle interval and the total number of pixel points of the Lentinula edodes cap surface image, and obtaining a comprehensive energy feature value according to the energy feature value weight and the energy feature value.

[0053] Since the direction statistics of the gray scale pair of the crack area of the lentinus edodes cap surface is obtained in step S2, different gray scale co-occurrence matrices can be obtained, and then the weight coefficients of the subsequent co-occurrence matrices are obtained according to the frequency of different crack directions. The gray scale pair statistics mode according to the crack direction and frequency can count the lenticular cracking texture characteristics of the lentinus edodes cap surface. That is, when the 0° direction gray scale co-occurrence matrix, the 45° direction gray scale co-occurrence matrix, the 90° direction gray scale co-occurrence matrix and the 135° direction gray scale co-occurrence matrix are obtained, the size of the gray scale co-occurrence matrix is 8*8, the gray scale is quantized to eight levels, that is, [0, 7], the step size of the gray scale pair of the gray scale co-occurrence matrix is 1, and then the 0° direction gray scale co-occurrence matrix, the 45° direction gray scale co-occurrence matrix, the 90° direction gray scale co-occurrence matrix and the 135° direction gray scale co-occurrence matrix corresponding to the four angle intervals are obtained. Specifically, the energy eigenvalue of each direction gray scale co-occurrence matrix is calculated, wherein the calculation formula of the energy eigenvalue is as follows, which is a prior art:

[0054]

[0055] asm θ indicates the energy eigenvalue of the gray scale co-occurrence matrix in the θ direction, θ is 0°, 45°, 90° or 135°;

[0056] (i,j) is the gray scale number of the i-th row and the j-th column in the gray scale co-occurrence matrix corresponding to the θ direction;

[0057] P(i,j) is the frequency of the gray scale pair (i,j) in the gray scale co-occurrence matrix in the θ direction;

[0058] Specifically, in order to make the energy value of the gray scale co-occurrence matrix closer to the real texture of the lentinus edodes cap surface, the energy eigenvalues of all the inclination angles are weighted to obtain a comprehensive energy eigenvalue. Specifically, the ratio of the number of edge points corresponding to the inclination angle in each angle interval to the total number of pixel points of the lentinus edodes cap surface image is taken as the energy eigenvalue weight of the gray scale co-occurrence matrix corresponding to the angle interval. The comprehensive energy eigenvalue is obtained by weighting and summing the energy eigenvalue weights and the energy eigenvalues corresponding to the four angle intervals, wherein the comprehensive energy eigenvalue calculation formula is:

[0059]

[0060] wherein ASM represents the comprehensive energy eigenvalue;

[0061] indicates the energy eigenvalue weight of the gray scale co-occurrence matrix in the θ direction;

[0062] N is the total number of pixels of the lentinus edodes cap surface;

[0063] n θ° the number of edge points corresponding to the gray level co-occurrence matrix of the direction of theta;

[0064] asm θ the energy eigenvalue of the gray level co-occurrence matrix of the direction of theta;

[0065] It should be noted that the embodiment utilizes the comprehensive energy eigenvalue ASM to reflect the texture roughness and depth of the shiitake mushroom cap, and the greater the ASM, the coarser the texture and the more texture present in the image; on the contrary, the smaller the ASM, the finer and less texture of the shiitake mushroom cap.

[0066] It should be noted that in order to make the energy value of the gray level co-occurrence matrix closer to the real texture of the shiitake mushroom cap, the step S3 classifies the angles of the edge points on the shiitake mushroom cap image and the horizontal coordinate axis direction to obtain four directions of 0°, 45°, 90° and 135°, and then uses the proportion of the texture of the gray level co-occurrence matrix on the entire shiitake mushroom cap as the energy eigenvalue weight of the gray level co-occurrence matrix, so as to obtain the comprehensive energy eigenvalue of the shiitake mushroom cap image according to the energy eigenvalue weight, i.e. the energy eigenvalue of the corresponding direction, so that the comprehensive energy eigenvalue can more accurately reflect the real texture of the shiitake mushroom cap.

[0067] S4, constructing a temperature-eigenvalue curve according to the corresponding comprehensive energy eigenvalue of each group of shiitake mushroom cap images at each temperature, obtaining the slope of each two adjacent lines on the curve, and determining whether the temperature interval between the two endpoints of the two adjacent lines is a temperature saturation interval according to the slope difference of each two adjacent lines and a preset difference threshold.

[0068] Since the energy eigenvalue of the gray level co-occurrence matrix reflects the texture of the shiitake mushroom cap, and the shiitake mushroom with poor quality has dense and smooth cap texture; on the contrary, the shiitake mushroom with good quality has cracked and gully cap, so according to the curve of the comprehensive energy eigenvalue of each group of shiitake mushroom cap images at each temperature, the slope difference of each two adjacent lines on the curve and a preset difference threshold are used to determine whether the temperature interval between the two endpoints of the two adjacent lines is a temperature saturation interval.

[0069] The step of obtaining the temperature saturation interval corresponding to each curve is: when the slope difference of each two adjacent lines is greater than a preset difference threshold, the common connection point of the two lines is taken as a saturation point; the temperature interval corresponding to the two points adjacent to the saturation point on the curve is taken as the temperature saturation interval; specifically, in order to ensure that the slope difference is between 0 and 1, the slope difference is normalized, and the normalized slope difference is compared with the preset difference threshold; when the normalized slope difference of each two adjacent lines is greater than the preset difference threshold, the common connection point of the two lines is taken as a saturation point; the temperature interval corresponding to the two points adjacent to the saturation point on the curve is taken as the temperature saturation interval; in this embodiment, the difference threshold is set to 0.2, when the slope difference of each two adjacent lines is greater than the preset difference threshold 0.2, the common connection point of the two lines is taken as a saturation point; the temperature interval corresponding to the two points adjacent to the saturation point on the curve is taken as the temperature saturation interval.

[0070] S5, the temperature saturation intervals corresponding to the cover surface images of all groups of shiitake mushrooms are intersected to obtain an intersection interval, and the intersection interval is taken as an optimal temperature interval; in order to more accurately obtain the optimal temperature interval so that the growth environment of shiitake mushrooms is the most suitable temperature, thereby obtaining the best quality shiitake mushrooms.

[0071] The present application provides a shiitake mushroom growth state monitoring method based on temperature data, which analyzes the texture of shiitake mushrooms, then obtains the direction of the texture part, and obtains the energy eigenvalue weight in each direction according to the number of edge points of the texture part and the number of all pixel points, uses the energy eigenvalue of the gray level co-occurrence matrix and the energy eigenvalue weight to obtain a comprehensive energy eigenvalue, thereby accurately reflecting the texture condition of the cover surface of shiitake mushrooms, then obtains a temperature-eigenvalue curve by combining temperature and the comprehensive energy eigenvalue, analyzes to obtain the temperature saturation interval of each group of shiitake mushrooms when the texture is maximum, then obtains the optimal temperature interval from the temperature saturation intervals of all groups of shiitake mushrooms, and realizes temperature regulation and improvement reference in the growth process of shiitake mushrooms.

[0072] The above only describes the preferred embodiments of the present application and is not intended to limit the present application, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for monitoring the growth status of shiitake mushrooms based on temperature data, characterized in that, The method includes: Obtain cap images of shiitake mushrooms at different temperatures but with the same other growth environments, and extract the cracked areas from the shiitake mushroom cap images; Based on the coordinates of each edge point in the crack region, obtain the angle between the edge point on each edge line and the horizontal axis direction, divide the angle range of the edge points in all crack regions into four angle intervals, and correspond the four angle intervals to the four directions of the gray-level co-occurrence matrix one by one. The energy feature value of the gray-level co-occurrence matrix of the cover image in each direction is obtained. The weight of the energy feature value of the gray-level co-occurrence matrix in the corresponding direction of the angle interval is obtained according to the number of edge points corresponding to the tilt angle in each angle interval and the total number of pixels in the mushroom cover image. The comprehensive energy feature value is obtained according to the weight of the energy feature value and the energy feature value. The images of the shiitake mushroom caps at different temperatures are taken as a set of images. Based on the comprehensive energy feature value of each set of images at each temperature, a temperature-feature value curve is constructed. The slope of the line connecting each two adjacent points on the curve is obtained. Based on the slope difference of each two adjacent lines and the preset difference threshold, it is determined whether the temperature range between the two endpoints of the two adjacent lines is a temperature saturation range. Find the intersection of the temperature saturation intervals corresponding to all groups of images to obtain the intersection interval, and take the intersection interval as the optimal temperature interval.

2. The method for monitoring the growth status of shiitake mushrooms based on temperature data according to claim 1, characterized in that, Also includes: Get the length of the edge line in the crack region; A circle is fitted to the outline of the mushroom cap, and half the radius of the circle is used as the length threshold of the edge line. Calculate the angle between the edge point on the edge line whose length is greater than or equal to the length threshold and the direction of the horizontal coordinate axis.

3. A method for monitoring the growth status of shiitake mushrooms based on temperature data according to claim 1 or 2, characterized in that, The steps to obtain information are as follows: Establish a coordinate system with the center of the shiitake mushroom cap at each temperature as the origin; Obtain the coordinates of the edge points on the edge line of each crack region; Obtain the ratio of the ordinate to the abscissa of the edge point; The arctangent of the ratio of the ordinate to the abscissa of the edge point is used as the angle between the edge point and the abscissa axis.

4. The method for monitoring the growth status of shiitake mushrooms based on temperature data according to claim 1, characterized in that, The steps to obtain the temperature saturation range corresponding to each curve are as follows: When the slope difference between any two adjacent lines is greater than the preset difference threshold, the common connection point of the two lines is taken as the saturation point. The temperature range between two points on the curve adjacent to the saturation point is taken as the temperature saturation range.

5. The method for monitoring the growth status of shiitake mushrooms based on temperature data according to claim 4, characterized in that, The slope difference is normalized, and the normalized slope difference is compared with a preset difference threshold. When the normalized slope difference between any two adjacent lines is greater than the preset difference threshold, the common connection point of the two lines is taken as the saturation point. The temperature range between two points on the curve adjacent to the saturation point is taken as the temperature saturation range.

6. The method for monitoring the growth status of shiitake mushrooms based on temperature data according to claim 1, characterized in that, The included angle ranges from 0° to 180°, and the range from 0° to 180° is divided into four equal angle intervals.

7. The method for monitoring the growth status of shiitake mushrooms based on temperature data according to claim 1, characterized in that, The steps to obtain the comprehensive energy characteristic value are as follows: The ratio of the number of edge points corresponding to the tilt angle in each angle interval to the total number of pixels in the mushroom cap image is used as the energy feature value weight of the gray-level co-occurrence matrix corresponding to the angle interval. The comprehensive energy characteristic value is obtained by weighting and summing the energy characteristic values ​​corresponding to the four angle intervals.

8. The method for monitoring the growth status of shiitake mushrooms based on temperature data according to claim 1, characterized in that, The different temperatures corresponding to the cover images are 22℃, 23℃, 24℃, 25℃, and 26℃.

9. The method for monitoring the growth status of shiitake mushrooms based on temperature data according to claim 1, characterized in that, The method for acquiring the cover image includes: Semantic segmentation was performed on each of the collected shiitake mushroom images after Gaussian filtering and noise reduction to obtain the cap image of the shiitake mushroom.

10. A method for monitoring the growth status of shiitake mushrooms based on temperature data according to claim 5, characterized in that, The preset difference threshold is 0.2.

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