Method for detecting yield rate and practical hatching rate of loose eggs of silkworm seeds

Abstract

The invention discloses a method for detecting the yield rate and the practical hatching rate of silkworm seed loose eggs, which comprises the following steps: S1, sampling the loose eggs, scattering the loose egg samples to a counting disc, distributing a plurality of micro pits on the surface of the counting disc, and making the counting disc from a transparent material; s2, a first image and a second image are obtained, the first image is shot downwards from the upper portion of the counting disc, and the second image is shot from one side of the counting disc to the other side of the counting disc; s3, identifying the first image, determining the micro-pit containing at least one silkworm egg, identifying the corresponding micro-pit containing at least one silkworm egg in the second image, determining the number of the silkworm eggs contained in the micro-pit, and identifying whether the silkworm eggs are good eggs or not; and S4, calculating the total number of silkworm eggs and the number of good eggs according to the identification result of S3, and calculating the rate of good eggs. According to the invention, the efficiency of loose egg detection can be improved, and the detection cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field related to the detection of mulberry silkworm eggs. More specifically, the present invention relates to a method for detecting the good egg rate and practical hatching rate of loose eggs of mulberry silkworms. Background Art

[0002] Currently, the usual process for detecting the good egg rate and practical hatching rate of loose eggs of mulberry silkworm eggs is as follows: Weigh several portions of loose egg samples, each weighing 1 gram, to obtain the number of loose eggs. Then, use the method of manual counting to determine the number of defective eggs, the number of hatched silkworm eggs, and the number of unhatched silkworm eggs, and then calculate the good egg rate and practical hatching rate. This method has a large workload, low efficiency, is greatly affected by human factors, and has large errors. In addition, for the detection of flat-attached eggs, the prior art 202210780334X uses image processing technology, but loose eggs are different from flat-attached eggs, and each silkworm egg is stacked together, so it is difficult to use a similar method for detection. Therefore, it is necessary to design a technical solution that can overcome the above defects. Summary of the Invention

[0003] An object of the present invention is to provide a method for detecting the good egg rate and practical hatching rate of loose eggs of mulberry silkworm eggs, which can improve the detection efficiency and reduce the detection cost.

[0004] To achieve these objects and other advantages of the present invention, according to one aspect of the present invention, there is provided a method for detecting the good egg rate and practical hatching rate of loose eggs of mulberry silkworm eggs, including: S1: Sampling the loose eggs, and spreading the loose egg samples onto a counting plate, the surface of the counting plate is distributed with a plurality of micro-pits, and the counting plate is made of a transparent material; S2: Obtaining a first image and a second image, the first image is taken downward from above the counting plate, and the second image is taken from one side of the counting plate to the other side; S3: Identifying the first image to determine the micro-pits containing at least one silkworm egg, identifying the corresponding micro-pits containing at least one silkworm egg in the second image, determining the number of silkworm eggs contained in the micro-pits, and identifying whether the silkworm eggs are good eggs; S4: Calculating the total number of silkworm eggs and the number of good eggs according to the recognition results of S3, and calculating the good egg rate.

[0005] Further, it further includes: S5: Hatching the silkworm eggs in the counting plate; S6: Obtaining the second images on the first day and the second day of hatching, and removing the hatched silkworm eggs after the first day and the second day of hatching; S7: Using the same method as S1-S3 to determine the number of silkworm eggs contained in the micro-pits, to obtain the number of unhatched silkworm eggs on the first day and the number of unhatched silkworm eggs on the second day; S8: Calculating the number of hatched silkworm eggs on the first day and the number of hatched silkworm eggs on the second day according to S7, and calculating the practical hatching rate.

[0006] Further, in the step S1, the loose egg samples are scattered on the counting plate and vibrated until all the silkworm eggs enter the micropits.

[0007] Further, the micropits are cube-shaped, with a width slightly larger than the size of the silkworm eggs, a length three to four times the size of the silkworm eggs, and a height five to ten times the size of the silkworm eggs.

[0008] Further, the counting plate includes a rectangular frame and a plurality of counting bars. The plurality of counting bars are laid on the rectangular frame and are detachably connected to the rectangular frame at both ends. A plurality of micropits are arranged on the surface of the counting bars along the length direction.

[0009] Further, in the step S2, after each counting bar is disassembled, its second image is obtained.

[0010] Further, in the step S2, for each micropit, the second image is binarized to obtain a binarized image. The connected regions in the binarized image are counted, the areas of the connected regions are calculated, and combined with the area of a single silkworm egg determined in advance, the number of silkworm eggs contained in each micropit is calculated.

[0011] Further, in the step S2, according to the color characteristics of the good eggs extracted in advance, it is identified whether the silkworm eggs are good eggs.

[0012] The present invention has at least the following beneficial effects: In the present invention, loose egg samples are scattered on the counting plate, and then the first image and the second image are obtained. The first image is taken from above the counting plate, and the second image is taken from one side of the counting plate to the other side. The micropits containing at least one silkworm egg are identified in the first image, the corresponding micropits containing at least one silkworm egg in the second image are identified, the number of silkworm eggs contained in the micropits is determined, and it is identified whether the silkworm eggs are good eggs. According to the identification results, the total number of silkworm eggs and the number of good eggs are calculated, and the good egg rate is calculated. The present invention combines the counting plate and the image recognition technology, improves the detection efficiency of loose egg seeds, and reduces the detection cost.

[0013] Other advantages, objectives, and features of the present invention will be partially reflected by the following description, and partially will be understood by those skilled in the art through the research and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a flowchart of an embodiment of the present application; Figure 2 is a schematic structural diagram of a counting plate according to an embodiment of the present application; Figure 3 is a schematic structural diagram of a counting bar according to an embodiment of the present application.. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] The following further elaborates on the present invention in conjunction with the accompanying drawings, so that those skilled in the art can implement it with reference to the text of the specification.

[0016] It should be understood that terms such as "having", "comprising", and "including" used in the embodiments of the present application do not exclude the presence or addition of one or more other elements or their combinations. All directional indications (such as up, down, left, right, front, back...) in the embodiments of the present application are only used to explain the relative positional relationship and movement conditions between components in a specific posture. If the specific posture changes, the directional indications will also change accordingly. When an element is referred to as being "fixed to" or "disposed on" another element, it can be directly on the other element or there may be an intermediate element at the same time. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or indirectly connected to the other element through an intermediate element. The descriptions in the embodiments of the present application involving "first", "second", etc. are only for descriptive purposes and should not be construed as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, features defined with "first", "second" may explicitly or implicitly include at least one such feature.

[0017] It should be noted that the technical solutions between the various embodiments of the present application can be combined with each other, but it must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present application.

[0018] As Figure 1 、 2 shown, the embodiments of the present application provide a method for detecting the good egg rate and practical hatching rate of loose eggs of silkworm eggs, including: S1: Sampling the loose eggs, and spreading the loose egg sample onto a counting plate. The surface of the counting plate is distributed with a plurality of micropits, and the counting plate is made of a transparent material; Exemplarily, 1 g or 2 g of the loose egg sample is taken for detection; Exemplarily, the loose egg sample is spread onto the counting plate and vibrated until all the silkworm eggs enter the micropits; Exemplarily, the width of the micropits should match the size of the loose eggs, and as much as possible, ensure that the loose eggs are in a planar distribution in the micropits to facilitate image recognition. Each micropit can accommodate several to dozens of silkworm eggs; Exemplarily, the transparent material is a transparent polymer material, such as polycarbonate; S2: Obtain a first image and a second image. The first image is taken downward from above the counting plate, and the second image is taken from one side of the counting plate to the other side; Exemplarily, the first image is obtained by setting a camera above the counting plate, and the second image is obtained by setting a camera on one side of the counting plate. The second image is preferably obtained multiple times and acquired from multiple sides to obtain the side images of each micro-pit; Exemplarily, the shooting direction of the second image should be towards the length direction of the micro-pit; S3: Identify the first image, determine the micro-pits containing at least one silkworm egg, identify the corresponding micro-pits containing at least one silkworm egg in the second image, determine the number of silkworm eggs contained in the micro-pits, and identify whether the silkworm eggs are good eggs; In this step, the number of silkworm eggs dispersed in the micro-pits is identified and counted. Since the silkworm eggs are dispersed, image recognition technology can be used; Exemplarily, each micro-pit can be numbered in advance, the numbers of the micro-pits with silkworm eggs are determined by identifying the first image. Whether there are silkworm eggs in the micro-pits can be judged according to the color characteristics of the silkworm eggs. The corresponding micro-pits in the second image are selected according to the numbers and identified; Exemplarily, for each of the micro-pits, the silkworm eggs in the micro-pit are taken as a whole, and the first image and the second image are used to model the whole silkworm eggs in the micro-pit, that is, the coordinates of each point of the whole silkworm eggs are determined by using the positions occupied by the whole silkworm eggs in the first image and the positions of the silkworm eggs in multiple images, a three-dimensional model of the whole silkworm eggs is established, the volume of the three-dimensional model is estimated, and then combined with the volume of a single silkworm egg to calculate the number of silkworm eggs; Exemplarily, for each of the micro-pits, the second image is binarized to obtain a binarized image, the connected regions in the binarized image are counted, the area of the connected regions is calculated, and combined with the area of a single silkworm egg determined in advance, the number of silkworm eggs contained in each of the micro-pits is calculated; Exemplarily, the connected regions representing single silkworm eggs in the binarized image are counted, their areas are recorded, and the average value is calculated to obtain the area of a single silkworm egg. The area of all connected regions is divided by the area of a single silkworm egg to obtain the number of silkworm eggs contained in the micro-pit; Exemplarily, based on the characteristic that there are differences in the colors of good eggs and bad eggs, according to the color characteristics of good eggs extracted in advance, it is identified whether the silkworm eggs are good eggs. If the method of establishing a three-dimensional model of the whole silkworm eggs is adopted, a similar method can be used to establish a three-dimensional model of good eggs to estimate the number of good eggs Exemplarily, according to the pre-extracted RGB value ranges of the colors of good eggs and bad eggs, it is identified whether the silkworm eggs are good eggs according to the RGB value ranges; S4: Calculate the total number of silkworm eggs and the number of good eggs according to the recognition results of S3, and calculate the good egg rate; Exemplarily, the good seed rate = the number of good eggs / the total number of silkworm eggs. The number of good eggs and the total number of silkworm eggs are obtained by adding up the number of good eggs or the number of silkworm eggs in each micro-pit; It can be seen that, compared with manual counting in the prior art, in this embodiment, the counting tray and image recognition technology are combined, overcoming the defect that the image recognition technology cannot be used in the prior art, improving the detection efficiency of loose eggs and reducing the detection cost.

[0019] In another embodiment, it further includes: S5: Incubate the silkworm eggs in the counting tray; Exemplarily, adjust the temperature, humidity, and light to incubate the silkworm eggs in the counting tray; S6: Obtain the second images on the first day and the second day of incubation, and remove the hatched silkworm eggs after the first day and the second day of incubation; in this step, after the first day and the second day of incubation are completed, the hatched silkworm eggs, that is, the eggshells and young silkworms, are removed. S7: Use the same method as in S1 - S3 to determine the number of silkworm eggs contained in the micro - pits, and obtain the number of unhatched silkworm eggs on the first day and the number of unhatched silkworm eggs on the second day; in this step, the remaining silkworm eggs after removing the hatched silkworm eggs are scattered onto the counting tray, and the first image and the second image are also taken, and the number of silkworm eggs is obtained by the same method, and repeated twice, that is, the number of unhatched silkworm eggs on the first day and the number of unhatched silkworm eggs on the second day are obtained. S8: Calculate the number of hatched silkworm eggs on the first day and the number of hatched silkworm eggs on the second day according to S7, and calculate the practical hatching rate; in this step, according to the total number of silkworm eggs, the number of unhatched silkworm eggs on the first day, and the number of unhatched silkworm eggs on the second day, the number of hatched silkworm eggs on the first day and the number of hatched silkworm eggs on the second day can be obtained, and then the practical hatching rate is calculated according to the formula: practical hatching rate = number of hatched silkworm eggs in two consecutive days / total number of silkworm eggs.

[0020] In another embodiment, the micro - pits are cube - shaped, with a width slightly larger than the size of the silkworm eggs, a length three to four times the size of the silkworm eggs, and a height five to ten times the size of the silkworm eggs; the shape and size of the micro - pits provided in this embodiment can better facilitate the entry of silkworm eggs into the micro - pits, and the silkworm eggs are distributed in a plane in the micro - pits, which is convenient for image recognition using the second image.

[0021] In another embodiment, as Figure 3 shown, the counting tray 1 includes a rectangular frame 101 and a plurality of counting bars 102. The plurality of counting bars 102 are laid on the rectangular frame 101, and both ends are detachably connected to the rectangular frame 101. A plurality of micro - pits 103 are arranged on the surface of the counting bar 102 along the length direction; preferably, in S2, after each counting bar 102 is disassembled, its second image is obtained; in this embodiment, the counting bar 102 is set to be detachable, which is realized by means of threaded connection, snap - connection, etc., for facilitating the acquisition of the second image, that is, after each counting bar 102 is removed in sequence, the second image is obtained for subsequent identification and statistics of silkworm eggs and good eggs.

[0022] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. It can be fully applied to various fields suitable for the present invention. For those skilled in the art, additional modifications can be easily achieved. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to specific details and the examples shown and described herein.

Claims

1. A method for detecting the good egg rate and practical hatching rate of loose eggs of silkworm seeds, characterized in that, Including: S1: Sampling loose eggs, spreading the loose egg samples onto a counting tray. Multiple micropits are distributed on the surface of the counting tray, and the counting tray is made of a transparent material. S2: Obtaining a first image and a second image. The first image is taken downward from above the counting tray, and the second image is taken from one side of the counting tray to the other side. S3: Identifying the first image to determine the micropits containing at least one silkworm egg, identifying the corresponding micropits containing at least one silkworm egg in the second image, determining the number of silkworm eggs contained in the micropits, and identifying whether the silkworm eggs are good eggs. S4: Calculating the total number of silkworm eggs and the number of good eggs according to the recognition results of S3, and calculating the good egg rate.

2. The method for detecting the good egg rate and practical hatching rate of loose eggs of mulberry silkworm seeds according to claim 1, characterized in that, Also including: S5: Hatching the silkworm eggs in the counting tray. S6: Obtaining the second images on the first day and the second day of hatching. After the first day and the second day of hatching, the hatched silkworm eggs are removed. S7: Using the same method as S1 - S3 to determine the number of silkworm eggs contained in the micropits, obtaining the number of unhatched silkworm eggs on the first day and the number of unhatched silkworm eggs on the second day. S8: Calculating the number of hatched silkworm eggs on the first day and the number of hatched silkworm eggs on the second day according to S7, and calculating the practical hatching rate.

3. The method for detecting the good egg rate and practical hatching rate of loose eggs of silkworm seeds as claimed in claim 2, wherein In S1, spreading the loose egg samples onto the counting tray and vibrating until all silkworm eggs enter the micropits.

4. The method for detecting the good egg rate and practical hatching rate of loose eggs of mulberry silkworm seeds according to claim 2, characterized in that, The micropits are cubic in shape, with a width slightly larger than the size of the silkworm eggs, a length three to four times the size of the silkworm eggs, and a height five to ten times the size of the silkworm eggs.

5. The method for detecting the good egg rate and practical hatching rate of loose eggs of mulberry silkworm seeds according to claim 4, characterized in that, The counting tray includes a rectangular frame and multiple counting bars. The multiple counting bars are laid on the rectangular frame, and both ends are detachably connected to the rectangular frame. Multiple micropits are arranged on the surface of the counting bar along the length direction.

6. The method for detecting the good egg rate and practical hatching rate of loose eggs of silkworm seeds according to claim 4, characterized in that, In S2, after detaching each counting bar, obtaining its second image.

7. The method for detecting the good egg rate and practical hatching rate of loose eggs of silkworm seeds according to claim 4, characterized in that In S2, for each micropit, binarizing the second image to obtain a binarized image, counting the connected regions in the binarized image, calculating the area of the connected regions, and combining with the pre - determined area of a single silkworm egg to calculate the number of silkworm eggs contained in each micropit.

8. The method for detecting the good egg rate and practical hatching rate of loose eggs of mulberry silkworm seeds according to claim 4, characterized in that, In S2, identifying whether the silkworm eggs are good eggs according to the pre - extracted color characteristics of good eggs.

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