Grain inspection device and cultivation management system using said device

Abstract

To provide a grain inspection device that can determine a defective grains mix ratio of the whole raw material including waste grains, and to provide a growth management system that is useful for farming families to manage growth of rice for the next year by making an effective use of data of the grain inspection device.SOLUTION: The grain inspection device includes: a rice selection machine for selecting a raw material according to the particle of grains and dividing the raw material into first defect-free grains and second defective grains, and measuring the respective weight values of the first defect-free grains and the second defective grains; and an optical selection machine for optically selecting the first defect-free grains and dividing the first defect-free grains into second defect-free grains and second defective grains. The grain inspection device also includes calculation means for calculating the mix ratio of the first defective grains of the second defective grains of the first defect-free grains and for calculating the mix ratio of the second defective grains of the first and second defective grains of the raw material on the basis of the weight value of the first defect-free grains measured by the particle size regulation means, the weight value of the first defective items measured by the waste particles measuring means, and the mix ratio of the first defective grains.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a grain inspection device for inspecting the quality of grain produced by farms and the like, and a cultivation management system using the device. [Background technology]

[0002] Until now, the quality inspection of grains (for example, brown rice and polished rice) produced by farmers and other such entities (grain inspection after shipping from the farm) has been stipulated in national law as "rice producers may undergo quality inspection" (Article 3 of the Agricultural Products Inspection Act). In other words, the current situation is that farmers and other rice producers proactively undergo quality inspections at JA (agricultural cooperatives) and other organizations with the aim of conducting fair and smooth transactions, ensuring traceability along the rice distribution route, and gaining trust in the quality of their rice.

[0003] At JA (agricultural cooperatives) and other organizations, agricultural product inspectors currently inspect quality and other aspects of produce visually, but recently progress has been made in the development of grain quality discriminators that can measure the proportion (rate) of colored grains and other contaminants (see, for example, Patent Document 1), and measuring devices are now being used as a supplement. Also, color sorters for removing colored grains and other contaminants have been made smaller and cheaper for use by farmers and other users, and models with improved performance have also appeared (see, for example, Patent Document 2).

[0004] However, the optical sorting machine described in Patent Document 2 above categorizes discolored grains caused by pests, grains damaged by discolored rice, immature green grains, unhulled rice, milky grains, and foreign objects such as pebbles as all together as defective products and distinguishes them from good products (with regular grain size). Furthermore, in the optical sorting machine described in Patent Document 3, the weight of non-defective products is compared with the weight of defective products to calculate the rate of defective products mixed into the raw material, which is used for quality inspection.

[0005] In other words, conventional optical sorting machines were unable to distinguish between defective products containing discolored grains caused by pests, grains damaged by discolored rice, immature green grains, unhulled rice, milky grains, and foreign matter such as pebbles, and to determine the rate of contamination with each defective factor. Analysis of quality discrimination such as the contamination rate has been carried out by placing the selected defective products in a black carton and visually inspecting them, or by using the above-mentioned grain quality discriminator.

[0006] In addition, farmers and others install rice sorting machines that sort grain size, etc., before the optical sorting machine, and then optically sort the raw material after sorting by the rice sorting machine using the optical sorting machine (for example, Patent Document 4). However, the scraps removed by the sorting using the rice sorting machine are not used in calculating the contamination rate, which means that it is not possible to confirm the contamination rate of defective products in the entire raw material fed to the sorting device.

[0007] Furthermore, with conventional optical sorting machines, the criteria for identifying defective products change based on user adjustments, so it was not possible to provide farmers with feedback on color-sorted sorting data, such as the rice cultivation conditions in the field for the following year, to help with cultivation management for the following year. [Prior art documents] [Patent documents]

[0008] [Patent Document 1] Japanese Patent Application Laid-Open No. 2016-125867 [Patent Document 2] Patent No. 6052287 [Patent Document 3] Japanese Patent Application Publication No. 10-216650 [Patent Document 4] Japanese Patent Application Laid-Open No. 2010-184226 Summary of the Invention [Problem to be solved by the invention]

[0009] In consideration of the above problems, the present invention aims to provide a grain inspection device that can distinguish between good and bad grains fed into an optical sorter, while simultaneously identifying the various defect factors of the bad grains, and that can also determine the rate of bad grains mixed into the entire raw material, including scrap grains. Another technical objective is to provide a cultivation management system that effectively utilizes the data from this grain inspection device to help farmers manage their rice cultivation for the following year. [Means for solving the problem]

[0010] In order to solve the above problems, the present invention provides a grain inspection device including a rice sorting machine that sorts raw materials into first good products and first defective products by grain thickness, and an optical sorting machine that optically distinguishes the first good products into second good products and second defective products, The rice sorting machine is Weight and the first defective product Weight and a particle size adjusting and measuring means for measuring the particles. 、 A means for measuring the amount of waste; 、 is provided, The optical sorting machine includes an imaging means for imaging the first non-defective product, and a discrimination means for discriminating the first non-defective product into a second non-defective product and a second defective product based on an imaging signal acquired by the imaging means. an ejector means for selectively removing the second defective product based on the discrimination result of the discrimination means; is provided, The grain inspection apparatus further includes: Calculating a first defective product mixing rate, which is the ratio of the second defective products contained in the first non-defective products, based on the discrimination result of the discrimination means; the weight value of the first non-defective product measured by the particle size measuring means; 、 the weight value of the first defective product measured by the waste particle measuring means; 、 The first defective product mixing rate; 、 a calculation means for calculating a second defective product mixing rate, which is a ratio of the first defective product and the second defective product contained in the raw material, based on the but, Preparation It is This technical measure was taken.

[0011] The invention of claim 2 provides a grain inspection device including a rice sorting machine that sorts raw material by grain thickness and sorts it into first good products and first defective products, an optical sorting machine that optically distinguishes the first good products into second good products and second defective products, and a quality weighing means that weighs the second good products, The optical sorting machine is provided with a defective product weighing means for weighing the second defective product, while the rice sorting machine is provided with a defective product weighing means for weighing the first defective product. Weight A dust particle measuring means is provided for measuring the dust particle, Furthermore, the optical sorting machine is provided with an imaging means for imaging the first non-defective product, a discrimination means for discriminating the first non-defective product into a second non-defective product and a second defective product based on an imaging signal acquired by the imaging means, and an ejector means for selectively excluding the second defective product based on a discrimination result by the discrimination means, The grain inspection device includes: a weight value of the first non-defective product is obtained by adding together the weight value of the second non-defective product weighed by the quality product weighing means and the weight value of the second defective product weighed by the defective product weighing means, and a first defective product mixing rate, which is the proportion of second defective products contained in the first non-defective products, is calculated based on the discrimination result of the discrimination means; calculating a calculated weight value of the second non-defective product and a calculated weight value of the second defective product from the first defective product contamination rate and the weight value of the first non-defective product, respectively; the calculated non-defective product weight value and the calculated defective product weight value are calculated in order to eliminate a weighing error caused by the second non-defective product being mixed with the second defective product when the second defective product is sorted out and removed by the ejector means, a calculation means for calculating a second defective product mixing rate, which is the ratio of the first defective products and the second defective products contained in the raw material, from the weight value of the first defective products weighed by the waste particle weighing means, the calculated weight value of the non-defective products, and the calculated weight value of the defective products; but, Preparation It is This technical measure was taken.

[0012] In the invention of claim 3, in the grain inspection device of claim 1 or claim 2, the calculation means calculates R, G, B signals of the object to be inspected obtained from the image pickup signal. Each value ofThe method is characterized in that various feature quantities are calculated by using these alone or in combination, and these values ​​are subjected to arithmetic processing such as addition, subtraction, multiplication or division to determine the number of raw materials flowing and the number of defective grains due to each defective factor, and from these results, the contamination rate of each defective factor contained in the second defective products is calculated.

[0013] The invention described in claim 4 is characterized in that the defective factors are a plurality of defective factors selected from grains damaged by pests, etc., grains damaged by discolored rice, etc., green immature grains, unhulled rice, milky grains, or foreign objects.

[0014] The invention of claim 5 provides a cultivation management system that connects via a communication line a grain processing line including at least the grain inspection device, an agricultural data linkage platform that aggregates data related to agriculture, a server that accumulates data on the preparation and processing of brown rice in the grain processing line, and a mobile terminal that provides cultivation management information to farmers, The server is characterized by incorporating a cultivation management program that provides farmers with feedback on this year's brown rice preparation and processing data and agricultural data from the agricultural data linkage platform, and provides them with cultivation management guidelines for the next year.

[0015] In the invention of claim 6, the brown rice preparation and processing data is at least the contamination rate of each defective factor in the sample inspected by the grain inspection device.

[0016] The invention described in claim 7 is characterized in that the server is equipped with a maintenance program that provides farmers with feedback on this year's brown rice preparation and processing data and agricultural data from the agricultural data linkage platform, and provides maintenance information for the machines that make up the grain preparation line. [Effects of the Invention]

[0017] According to the invention of claim 1, there is provided a grain inspection device including a rice sorting machine that sorts raw material by grain thickness and sorts it into first good products and first defective products, and an optical sorting machine that optically sorts the first good products and sorts it into second good products and second defective products, wherein the rice sorting machine is provided with a size regulation measuring means and a waste grain measuring means that weigh the first good products and the first defective products, respectively, and the optical sorting machine is provided with an imaging means that images the first good products and a waste grain measuring means that weighs the first good products and the first defective products based on an imaging signal acquired by the imaging means. The raw material is provided with a discrimination means for discriminating between a non-defective product and a second defective product, and a calculation means for calculating a first defective product mixing rate, which is the ratio of second defective products contained in the first non-defective products, based on the discrimination result of the discrimination means, and a calculation means for calculating a second defective product mixing rate, which is the ratio of the first defective products and the second defective products contained in the raw material, based on the weight value of the first non-defective products measured by the granularity measuring means, the weight value of the first defective products measured by the waste measuring means, and the first defective product mixing rate. Not only can the raw materials being inspected be simply distinguished between good and bad products, but the proportion of the defective products mixed in the raw materials distinguished by the optical sorting machine can be examined in detail. In addition, the second defective product mixing rate is also calculated, taking into account information on the scraps removed by the rice sorting machine, which has the effect of making it possible to know the defective product mixing rate more accurately.

[0018] According to the invention of claim 2, there is provided a grain inspection device including a rice sorting machine that sorts raw material by grain thickness and sorts the raw material into first good products and first defective products, an optical sorting machine that optically distinguishes the first good products into second good products and second defective products, and a quality weighing means that weighs the second good products, The optical sorting machine is provided with a defective product weighing means for weighing the second defective products, while the rice sorting machine is provided with a waste grain weighing means for weighing the first defective products; Furthermore, the optical sorting machine is provided with an imaging means for imaging the first non-defective product, a discrimination means for discriminating the first non-defective product into a second non-defective product and a second defective product based on an imaging signal acquired by the imaging means, and an ejector means for selectively excluding the second defective product based on a discrimination result by the discrimination means, a weight value of the first non-defective product is determined by adding together the weight value of the second non-defective product weighed by the fine product weighing means and the weight value of the second defective product weighed by the defective product weighing means, and a first defective product mixing rate, which is the proportion of second defective products contained in the first non-defective products, is calculated based on the discrimination result of the discrimination means, and a calculated non-defective product weight value of the second non-defective product and a calculated defective product weight value of the second defective product are calculated from the first defective product mixing rate and the weight value, and a calculated non-defective product weight value of the second defective product is calculated from the weight value of the first defective product weighed by the waste weighing means, the calculated non-defective product weight value, and the calculated defective product weight value Since the apparatus is equipped with a calculation means for calculating a second defective product mixing rate, which is the ratio of the first defective products and the second defective products contained in the raw material, it is possible not only to simply distinguish the raw material to be inspected as good or defective, but also to investigate in detail the proportion of the defective products mixed in the raw material identified by the optical sorting machine based on the weight value measured by the precision weighing means, and in addition, since the second defective product mixing rate is also calculated taking into account information on the scrap grains removed by the rice sorting machine, it has the effect of being able to know the defective product mixing rate more accurately.

[0019] According to the invention of claim 3, the calculation means calculates various feature quantities by using each of the R, G, and B signals obtained from the optical detection means, either individually or in combination, and performs addition, subtraction, or the like on these values. Ride The number of raw materials flowing and the number of defective grains due to each defective factor are calculated by performing calculations using addition or division, and the contamination rate of each defective factor is calculated from these results.This makes it easy to distinguish between brown discolored rice and unhulled rice, and between green immature grains and white milky white grains, which were previously difficult to distinguish.

[0020] According to the invention of claim 4, the defective factors can be selected from multiple factors including grains damaged by pests, grains damaged by discolored rice, immature green grains, unhulled rice, milky white grains, and foreign objects, so that instead of simply sorting into good and bad products, it is possible to calculate the contamination rate of multiple defective factors desired by the user depending on the situation. Another advantage is that it is possible to calculate the contamination rate of each defective factor without separately inputting the data into a grain quality classifier.

[0021] According to the invention of claim 5, there is provided a cultivation management system that connects via a communication line a grain preparation line including at least the grain inspection device, an agricultural data linkage platform that aggregates data related to agriculture, a server that accumulates data on the preparation and processing of grain in the grain preparation line, and a mobile terminal that provides cultivation management information to farmers, The server is equipped with a cultivation management program that provides farmers with feedback on this year's grain preparation and processing data and agricultural data from the agricultural data linkage platform, and provides them with cultivation management guidelines for the next year.This means that the data on the contamination rate of each defective factor for the current year measured by the grain inspection device can be effectively used to provide farmers with rice cultivation management guidelines for the next year (for example, the timing of irrigation, fertilization, and pesticide spraying for the following year) to help with cultivation management.

[0022] Furthermore, according to the invention described in claim 6, the grain preparation and processing data will include at least the contamination rate of each defective factor in the grain inspected by the grain inspection device, making it possible to visualize this year's crop situation for farmers and provide it to them in an easy-to-understand manner.

[0023] Furthermore, according to the invention described in claim 7, the server is equipped with a maintenance program that provides farmers with feedback on this year's grain preparation and processing data and agricultural data from the agricultural data linkage platform, and provides maintenance information for the machinery that makes up the grain preparation line.For example, if the grain preparation and processing data is lower than average, this may be an indicator that the capacity of the machinery in the grain preparation line is lower than usual, and an alarm can be issued to notify farmers to adjust and maintain the machinery. [Brief explanation of the drawings]

[0024] [Figure 1] 1 is a block diagram showing a grain inspection device of the present invention incorporated into a grain preparation line and configured as a cultivation management system. [Figure 2] FIG. 1 is a schematic cross-sectional side view of a grain inspection device (optical sorting machine). [Figure 3] FIG. 2 is a block diagram showing a control circuit of the grain inspection device. [Figure 4] 10 is a diagram showing an example of analysis results displayed on the screen of a display unit. [Figure 5] This is an example of cultivation management provided to farmers displayed on the mobile terminal screen of a cultivation management system. [Figure 6] 10 is a diagram showing an example of analysis results displayed on the screen of a display unit. [Figure 7] FIG. 1 is a schematic cross-sectional side view of a grain inspection device (rice sorting machine). [Figure 8] FIG. 10 is a diagram showing the relationship between a first non-defective product, a first defective product, a second non-defective product, and a second defective product. [Figure 9] FIG. 10 is a block diagram showing a control circuit of a grain inspection device according to another embodiment of the present invention. [Figure 10] FIG. 10 is a block diagram illustrating a cultivation management system in which a grain inspection device according to another embodiment of the present invention is incorporated into a grain preparation line. DETAILED DESCRIPTION OF THE INVENTION

[0025] Figure 1 is a block diagram of a cultivation management system configured by incorporating the grain inspection device of the present invention into a grain processing line. This cultivation management system 10 is intended for medium to large-scale farms, such as individual farmers or agricultural corporations, with field areas of approximately 1 to 3 hectares. Reference numeral 205 denotes a grain inspection device, which is composed of a rice sorter 202 and an optical sorter 203.

[0026] In Figure 1, the cultivation management system 10 connects a grain preparation line 20, a server 30 that stores data on the preparation and processing of grain on the grain preparation line 20, a mobile terminal 40, and an agricultural data collaboration platform 50 that aggregates all agricultural data from private or public institutions via a communication line 60. The server 30 may be configured on a cloud.

[0027] The communication line 60 is configured by a network such as a LAN (Local Area Network) or an internet line, etc. This network may be wired or wireless.

[0028] (Grain preparation line) The grain processing line 20 is installed in a barn owned by an individual farmer, or in a building such as a rice center or factory owned by an agricultural corporation. The grain processing line 20 is indoor machinery (barn machinery) that is fixed inside a building, as opposed to field machinery (e.g., combine harvesters) that harvest while moving within the field, and can transport and process the crops harvested by the field machinery. The grain preparation line 20 is configured by connecting, in a single line, a grain dryer (not shown) that dries the grain, a cooling tank (not shown) in which the dried rice dried in the grain dryer is allowed to cool, a huller and sorter 201 that husks the cooled rice and turns it into brown rice, a rice sorter 202 that sorts the brown rice obtained by the huller and sorter 201 into grains that meet the standard and those that do not meet the standard based on the grain diameter (thickness (size)), an optical sorter 203 that optically inspects the grain-sorted brown rice obtained by the rice sorter 202, and a weighing and bagging machine 204 that weighs, bags, and ships the brown rice after it has been inspected by the optical sorter 203.

[0029] The rice huller and sorter 201 is equipped with a husking rate sensor 201a that samples the husked rice, transmits sensor light projected from a light-emitting element to a light-receiving element, and determines whether the rice is brown rice or unhulled rice based on the transmittance of the sensor light through the husked rice. The rice huller and sorter 201 also has an electrical quantity measuring unit 201b that measures the electrical quantities (e.g., current value, power value, or amount of power) of its drive unit. The properties of the unhulled rice supplied to the rice huller and sorter 201 can be determined based on whether the measured values ​​from the husking rate sensor 201a and the electrical quantity measuring unit 201b are within standards.

[0030] The rice sorting machine 202 is equipped with a sorting mesh tube that separates the raw material (brown rice) into sized grains (first-class products) and immature grains (first-class products). If the amount of immature grains mixed in is large, the commercial value decreases. Furthermore, the amount of immature grains mixed in is an indicator of poor rice growth conditions for that year. For example, abnormally low temperatures and extreme lack of sunlight during the rice cultivation period, or abnormally high temperatures due to continuous heat waves during the rice cultivation period, can cause poor rice growth, resulting in extremely poor grains (immature grains) in the rice kernels, or in some cases, sterile grains that do not ripen.

[0031] Here, the terms "first non-defective product," "first defective product," "second non-defective product," and "second defective product" in the present invention will be explained. As shown in FIG. 8, the non-defective rice selected by the rice sorting machine 202 is called the "first non-defective rice," and the defective rice is called the "first defective rice." In the optical sorting machine 203, the first good product determined to be a good product by the comparison circuit 227a described later is designated as a "second good product A1," and the first good product determined to be a defective product is designated as a "second defective product B1." Furthermore, the first non-defective product determined as a non-defective product by the measuring circuit 227b described later is referred to as a "second non-defective product A2," and the first non-defective product determined as a defective product is referred to as a "second defective product B2." Furthermore, the second non-defective product A1 after sorting by the ejector drive device described later is referred to as a "second non-defective product A3," and the second defective product B1 after similar sorting is referred to as a "second defective product B3."

[0032] As shown in Figure 7, the rice sorting machine 202 has a raw material input hopper 75 provided at the back of a housing 74, and a sorting net tube 76 for sorting by particle size into waste grains and immature rice (first defective products) and regular grains (first non-defective products) is installed upright within the housing 74. The top of the sorting net tube 76 is closed, and a lifting roll 77 is installed upright within the sorting net tube 76, forming a so-called upward-feeding vertical sorting section. A helical lifting spiral 78 is attached to the outer periphery of the lifting roll 77, and by rotating the lifting roll 77 using a rotary drive means such as an inverter motor 70, the raw material (grains) supplied from the raw material input hopper 75 to the bottom of the sorting net tube 76 rises within the sorting net tube 76 while being subjected to centrifugal force due to the rotation of the lifting spiral 78.

[0033] A large number of sorting holes 79 are formed in the sorting net tube 76, and a waste grain chamber 80 is formed between the sorting net tube 76 and the housing 74. As a result, waste grains (immature grains) are transferred from the raw material (grains) rising inside the sorting net tube 76 while being subjected to the centrifugal force described above to the waste grain chamber 80 through the large number of sorting holes 79, and the waste grains are removed from the raw material depending on the size of the sorting holes 79, and particle size sorting is performed.

[0034] The lower part of the debris chamber 80 is connected to the outside of the housing 74 via the debris discharge gutter 71, and the debris transferred to the debris chamber 80 is discharged to the outside of the housing 74 via the debris discharge gutter 71.

[0035] The waste particles discharged from the waste particle discharge gutter 71 are weighed by the waste particle weigher 202b, and the weighed weight value is sent to a measuring circuit 227b, which will be described later.

[0036] A predetermined number of plate-shaped scraping blades 72 are provided at the upper end of the grain lifting roll 77, and the upper end of the sorting net cylinder 76 is connected to the base end of a grain sorting storage tank 73, which serves as a primary storage tank, and the brown rice transported to the upper end of the sorting net cylinder 76 is thrown into the grain sorting storage tank 73 by the centrifugal force caused by the rotation of the scraping blades 72. Then, the raw material (raw material that does not pass through the sorting net cylinder 76) is discharged from a sizing outlet 81 provided below the grain sorting storage tank 73.

[0037] The raw material discharged from the sizing discharge port 81 is weighed by a sizing weigher 202a that weighs the raw material. The measured weight value is then sent to a measurement circuit 227b, which will be described later.

[0038] By knowing the sorting ratio between the sized grains and the sized grains (immature grains) based on the measured values ​​of the sized grain weigher 202b and the sized grain weigher 202a, it is possible to calculate the yield of sized grains and the mixing ratio of sized grains. In addition, it is also possible to use this as an index for determining the growth status of rice in that year.

[0039] The calculation of the sizing yield and the mixed-in rate of scrap grains can be performed at any time as appropriate. For example, it can be performed for each raw material lot, or for each predetermined amount such as 10 kg or 30 kg. It can also be performed at predetermined time intervals or continuously. The mixed-in rate can be calculated by a control circuit (not shown) of the rice sorter 202 or by a measurement circuit 227b of the grain inspection device 205 described later.

[0040] In this embodiment, the rice sorting machine 202 is shown as being vertical, but it is not limited to being vertical and may be a horizontal type in which the sorting mesh tube 76 is placed horizontally, or one in which the sorting mesh tube 76 is installed at an angle.

[0041] The optical sorting machine 203 sorts the grained brown rice (first good product) that has been sorted by size by the rice sorting machine 202 into good products (second good products) and defective products (second defective products), and can also examine in detail the proportion of each defective factor contained in the raw material, such as discolored grains caused by pests, damaged grains due to discoloration, green immature grains, unhulled rice, milky grains, and small stones.

[0042] 2, the optical sorting machine 203 includes an inspection object supply unit 203a, a chute 203b, an optical sorting unit 203c, and a discharge hopper 203d. The inspection object supply unit 203a includes a tank 210 and a vibrating feeder 211 that supplies the inspection objects to the chute 203b. The supply can also be performed using a rotary valve.

[0043] The chute 203b has a predetermined width and is disposed at an incline below the tip end of the vibrating feeder 211, allowing the objects to be inspected supplied from the vibrating feeder 211 to fall naturally. The optical sorting unit 203c includes a pair of optical detection devices 212a and 212b disposed before and after the trajectory of the objects to be inspected dropping from the bottom end of the chute 203b. The optical sorting machine 203 includes a calculation means 213 that classifies the objects to be inspected as non-defective products (second non-defective products) or defective products (second defective products) based on the image pickup signals of the optical detection devices 212a and 212b. The optical sorting machine 203 also includes an ejector device 215 that rejects the defective products identified by the calculation means 213.

[0044] Reference numeral 214 denotes an ejector drive circuit that outputs an ejection signal from the calculation means 213 to an ejector device 215 .

[0045] The discharge hopper 203d has a non-defective product discharge trough 216 and a defective product discharge trough 217, and separates the inspected products into non-defective products (second non-defective products A3) and defective products (second defective products B3) by an ejector device 215 and discharges them. The discharged second non-defective products A3 are sent to a weighing bagging machine 204 and weighed by a fine product weigher 204a. In the present invention, spirit The quality weigher 204a serves as quality weighing means. The second defective product B3 thus discharged is weighed by the defective product weighing device 301. In the present invention, the defective product weighing device 301 serves as the defective product weighing means.

[0046] The weighing bagging machine 204 places a container 204b such as a rice bag and a bag stand 204c on a quality weighing scale 204a, and by opening a shutter (not shown), the grain is discharged into the container 204b. When the predetermined weight is reached, the shutter automatically closes and the weighing and bagging process is completed.

[0047] In the grain preparation line 20 described above, for example, eight types of sensors and control means shown in FIG.

[0048] (server) The server 30 has general-purpose basic functions such as a web server that transmits and receives information to and from external terminals, a file server that stores various data and functions as a database, and an application server that distributes applications that need to be installed on client computers and tablet terminals. The server 30 is connected to a communication line 60. The server 30 may be provided on the cloud, or may be provided, for example, in a facility where the grain inspection device 205 is installed.

[0049] (Mobile device) The mobile terminals 40 are preferably a plurality of tablet terminals that can be carried and viewed at the site, such as a farm field or a grain preparation line. The tablet terminals may be replaced by general-purpose laptop computers or smartphones. The mobile terminals 40 are connected to a communication line 60.

[0050] (Agricultural data collaboration platform) The Agricultural Data Collaboration Platform50 is hosted by private or public institutions and aims to provide new services that utilize data and enable farmers to make strategic management decisions by organizing and providing public data on agricultural soil, market conditions, weather, etc., as well as various paid data from private companies.

[0051] The agricultural data sharing platform 50 shown in Figure 1 can utilize, for example, "WAGRI," hosted by the National Agriculture and Food Research Organization. This platform 50 is composed of an agricultural database 501 storing past yield data, market data, soil data, and farmland data, a meteorological database 502 storing agricultural meteorological data, and a past history database 503 that allows past history to be referenced. These databases 501, 502, and 503 are provided in the form of an application programming interface (API), and some of the software and applications are made publicly available, allowing software and functions developed by third parties using these databases to be shared. This platform 50 is connected to a communication line 60.

[0052] (Control circuit configuration of grain inspection device (optical sorter 203)) Next, a detailed description will be given of the control circuit of the grain inspection device 205. The control circuit of the optical sorter 203 can be used as the control circuit. The control circuit may be provided separately. The calculation means 213 of the optical sorter 203 classifies the object to be inspected (here, the first non-defective product) into a non-defective product (second non-defective product) and measures the degree (rate) of contamination of the raw material with each defect factor, such as grains discolored by pests etc., grains damaged by discolored rice etc., green immature grains, unhulled rice, discolored grains such as milky white grains, and foreign matter such as pebbles. Here, the calculation means 213 also serves as a control circuit for the grain inspection device 205.

[0053] Fig. 3 is a block diagram showing a control circuit of the optical sorter 203. As shown in Fig. 3, the optical detection device (imaging camera) 212, which serves as an optical detection means, is composed of a CCD line sensor and includes an R element 220, a G element 221, and a B element 222 that are sensitive to the colors R (red), G (green), and B (blue). The light reception signals of the optical detection device (imaging camera) 212 are supplied to the R element 220, G element 221, and B element 222, and are photoelectrically converted into R signals, G signals, and B signals, respectively, and output.

[0054] The R signal, G signal, and B signal are input to amplifiers 223 , 224 , and 225 provided in the calculation means 213 , respectively, and are further input to a signal processing circuit 226 . The signal processing circuit 226 calculates various feature quantities using each of the R, G, and B signals individually or in combination, and also performs addition, subtraction, Ride The signal is converted by performing arithmetic processing such as multiplication or division. This signal conversion characterizes the signal received by the optical detection device (image pickup camera) 212 to identify the object to be inspected, and this signal is input to the comparison circuit 227a, which determines whether the object to be inspected (here, the first non-defective product) is good or bad, and the object is classified as a second non-defective product A1 or a second defective product B1.

[0055] Furthermore, the signal processed by the signal processing circuit 226 is input to the measurement circuit 227b, whereby the first good product is classified into a second good product A2 and a second defective product B2, separately from the pass / fail judgment by the comparison circuit 227a, and the second defective product B2 is further classified into each defective factor. Then, the second non-defective product A2 and the mixing rate of each of the above-mentioned defective factors are calculated. This mixing rate corresponds to the first defective product mixing rate in the present invention. The comparison circuit 227a serves as the determination means in the present invention, and the measurement circuit 227b serves as the calculation means in the present invention. The measuring circuit 227b may also function as the determining means and the calculating means of the present invention, in which case a signal is sent from the measuring circuit 227b to a delay circuit 228, which will be described later.

[0056] Reference numeral 228 denotes a delay circuit, which determines the ejection timing according to the distance between the position where the optical detection device (image pickup camera) 212 observes the object to be inspected and the rejection position where the ejector device 215 rejects defective products. A rejection signal is output from the comparison circuit 227a to the ejector drive circuit 214 via the delay circuit 228. The rejection signal determined by the ejector drive circuit 214 is output to the ejector device 215. Eh The ejector device 215 is the ejector device of the present invention. Ta Become a means.

[0057] (Calculation algorithm for the contamination rate of each defect factor in a grain inspection device) 3 calculates feature amounts for each particle of the object to be inspected from the R, G, and B values ​​using various combinations of spectral ratios such as R / G and R / B. The calculated values ​​are then compared with a discriminant stored in the measurement circuit 227b (see, for example, FIGS. 6 to 10 of Japanese Patent Laid-Open Publication No. 9-292344) to discriminate, for example, into six types of defect factors.

[0058] If a program is set up in advance to classify the six types of defective factors, such as (a) classifying grains damaged by pests (stink bug damaged grains) as good quality and the rest, (b) classifying grains discolored by discolored rice etc. as good quality and the rest, (c) classifying green immature grains as good quality and the rest, (d) classifying milky white grains as good quality and the rest, (e) classifying unhulled grains as good quality and the rest, and (f) classifying foreign matter as good quality and the rest, statistical processing of the degree (rate) of contamination by each defective factor can be performed quickly.

[0059] The measurement circuit 227b (calculation means) shown in Figure 3 calculates the contamination rate (first defective contamination rate) of each defective factor of the second defective product B1 contained in the first good product for raw materials (test objects) that have been classified as good products (second good products A1) and defective products (second defective products B1) by the comparison circuit 227a (discrimination means). The measurement circuit 227b may be used as the discrimination means in the present invention to discriminate the first non-defective product into the second non-defective product A1 and the second defective product B1. The discrimination criteria of the measurement circuit 227b cannot be changed by the user.

[0060] In addition, the measurement circuit 227b can calculate the mixing rate of each of the defective factors (the first defective products and the second defective products B1) contained in the raw material hulled by the rice huller and sorter 201, using the weight values ​​of the sized rice (first non-defective products) and the weight values ​​of the waste rice (first defective products) transmitted from the sized rice weigher 202a and the waste rice weigher 202b of the rice sorter 202. This mixing rate corresponds to the second defective product mixing rate of the present invention.

[0061] The second method for calculating the defective product contamination rate will now be described. For example, first, the rice sorting machine 202 sorts the rice into regular grains (first good products) and scraps (first defective products), and based on the results of weighing each, the measurement circuit 227b calculates the scrap content rate (third defective product content rate) of the raw material fed into the rice sorting machine 202. Next, the sized product (first good product) is discriminated into good products (second good product A1) and defective products (second defective product B1) by the discrimination means of the optical sorting machine 203, and based on the discrimination results, the contamination rate (first defective product contamination rate) of each defective factor of the second defective product B1 contained in the first good product is calculated. This first defective product inclusion rate is determined by detailed discrimination of the sized products (first non-defective products) using the optical sorter 203.

[0062] Then, the second defective product mixing rate can be calculated by reflecting the first defective product mixing rate in the proportion of the first non-defective products in the third defective product mixing rate. Here, the weight value of the first non-defective product is measured by the particle size measuring instrument 202a. Therefore, the weight value of each defective factor contained in the first non-defective product can be calculated by multiplying the weight value of the first non-defective product by the contamination rate of each defective factor in the first defective product contamination rate. Incidentally, the sum of the weight values ​​of each defective factor becomes the weight value of the second defective product B1.

[0063] Each of the defective factors is a second defective product B1, which is included in the first non-defective products sorted by the rice sorting machine. Therefore, by subtracting the weight value of each defective factor from the weight value of the first non-defective products, the weight value of the second non-defective products A1, which is the first non-defective products minus the second defective products B1, can be calculated. The second defective product inclusion rate can then be calculated from the weight value of the second non-defective products A1, the weight values ​​of each defective factor, and the weight value of the first non-defective products. The weight value obtained by adding together the weight value of the second non-defective product A1, the weight values ​​of each defective factor, and the weight value of the first defective product is the weight value of the raw material, so it is possible to calculate the second defective product contamination rate from these values.

[0064] It is desirable that the calculation means does not allow the user to change the discrimination criteria. By fixing the discrimination criteria as unchangeable, it becomes easy to provide the farmers with feedback on the color-sorted sorting data, such as the rice cultivation conditions in the field for the next year, to use for the cultivation management for the next year. In the present invention, a comparison circuit 227a whose discrimination criteria can be changed by the user and a measurement circuit 227b whose discrimination criteria cannot be changed are provided.

[0065] The location of the calculation means is not particularly limited as long as it can receive signals from the signal processing device 226. Therefore, it may be arranged inside the optical sorting machine 203 as shown in the embodiment, or may be arranged separately in the building where the optical sorting machine 203 is installed. line It may be provided on the server 30 via 60, or it may be provided on the cloud.

[0066] (Communication unit of grain inspection device) Reference numeral 230 in FIG. 3 denotes a communication unit of the grain inspection device, which transmits the measured contamination level (rate) of each defective factor to the server 30 as part of the preparation and processing data. line It is transmitted via 60. The data stored in the server 30 can be checked using the mobile terminal 40. In addition, the Communications Department 2 30 is the communication means in the present invention.

[0067] FIG. 4 is an example of the analysis results displayed on the screen 40a of the mobile terminal 40. The results shown in FIG. 4(a) are based on the discrimination results obtained by the optical sorter 203. The results are shown for "(e) Classifying the inspected objects into unhulled and other unhulled as good products," and in this example, 93% of the inspected objects were good products, while 7% were unhulled, which are defective products. FIG. 4(b) shows the results (pie chart) of a detailed analysis of the defective factors contained in the raw material obtained by tallying up measurements using six types of defective factors. In this example, 93% of the inspected objects were good products, while 7% were defective products, and of the defective products, 2% were unripe green rice, and 1% each were due to the remaining defective factors.

[0068] Fig. 6 is an example of the analysis results displayed on the screen 40a of the mobile terminal 40, which also takes into account the weighing results of the scraps removed by the rice sorter 202. The display example in Fig. 4(b) above shows the discrimination results of the optical sorter 203, but the display example shown in Fig. 6 adds the weighing results of the scraps removed by the rice sorter 202 to the discrimination results of the optical sorter 203. Since the mixing rate of the scraps is also included, it is possible to obtain more accurate information on the mixing rate of each defective factor. For example, by managing this information for each drying lot in the drying process, it is possible to evaluate the "crop yield" of each rice grain fed into the dryer.

[0069] The weight of the sized rice may be the value obtained by sorting with the rice sorter 202 and weighing with the sized rice weigher 202a, or the weighing result of the refined rice weigher 204a may be used.

[0070] (Cultivation management system) A cultivation management program that provides farmers with cultivation management guidelines for the next year is incorporated into the server 30 of the cultivation management system 10 shown in Figure 1. In other words, this cultivation management program references data obtained from the various processing machines on the grain processing line 20 and data obtained from the various servers of the agricultural data linkage platform 50, and provides feedback to farmers on the current year's rice cultivation conditions in their fields, which can be used for next year's cultivation management (for example, the timing of irrigation, fertilization, and pesticide spraying for the following year).

[0071] Figure 5 shows an example of cultivation management provided to a farmer, displayed on the screen 40a of the mobile terminal 40 of the cultivation management system 10. In Figure 5, the farmer is provided with feedback on the field number, various data on the grain harvested from this field number after processing on the grain processing line 10, and data obtained from the agricultural data linkage platform 50, and advice on cultivation management for the next year is provided based on this.

[0072] For example, in Figure 5, in field No. 1, the results of grain preparation and processing are obtained and recorded from various data on the grain preparation line 10. From this record, if the rice sorter 202 finds that the proportion of broken grains is higher than average, and the grain inspection device 205 finds that the proportion of immature grains is higher than average, the reasons and factors for this can be obtained by referencing the agricultural data linkage platform 50. From the above, as measures for the next year, cultivation management guidelines (advice) can be provided to farmers that take into account "fertilization management" and "harvesting timing."

[0073] Similarly, for field No. 2 in Figure 5, the farmer can be provided with cultivation management guidelines (advice) for the next year to consider "pre- and post-harvest management" taking into account rainfall at harvest time, and for field No. 3, the farmer can be provided with cultivation management guidelines (advice) for the next year to emphasize "seed rice disinfection and pest control plans."

[0074] In addition to such cultivation management guidelines (advice), if the husking rate of the rice husker and sorter 201 is lower than average and the rate of unhulled rice in the grain inspection device 205 is higher than average, an alarm can be issued on the screen 40a of the mobile terminal 40. If the husking rate is lower than average, the performance of the rice husker and sorter 201 may be inferior to normal, so it is advisable to issue an alarm to inform the farmer to adjust or maintain the rice husker and sorter 201.

[0075] (Another embodiment of the present invention) A grain inspection device 305 according to another embodiment of the present invention will be described with reference to Figures 9 and 10. Note that, in the grain inspection device 305 according to this embodiment, some of the same features as those of the above-described grain inspection device 205 will not be described again.

[0076] 10 is a block diagram of a cultivation management system configured by incorporating a grain inspection device 305 into a grain preparation line 301. Reference numeral 305 denotes the grain inspection device, which is composed of a rice sorter 202, an optical sorter 203, and a weighing bagger 204.

[0077] In the grain preparation line 301 described above, for example, eight types of sensors and control means shown in FIG.

[0078] (Control circuit configuration of grain inspection device (optical sorter 203)) Next, a detailed description will be given of the control circuit of the grain inspection device 305. The control circuit of the optical sorter 203 can be used as the control circuit. The control circuit may be provided separately. The calculation means 213 of the optical sorter 203 distinguishes the object to be inspected (first non-defective product) into a non-defective product (second non-defective product) and a defective product (second defective product), and measures the degree (rate) of contamination of the raw material with each defective factor, such as grains discolored by pests, grains damaged by discolored rice, green immature grains, unhulled rice, discolored grains such as milky white grains, and foreign matter such as pebbles. Here, the calculation means 213 also serves as a control circuit for the grain inspection device 305.

[0079] Fig. 9 is a block diagram showing a control circuit of the optical sorter 203. As shown in Fig. 9, the optical detection device (imaging camera) 212, which serves as an optical detection means, is composed of a CCD line sensor and includes an R element 220, a G element 221, and a B element 222 that are sensitive to the colors R (red), G (green), and B (blue). The light reception signals of the optical detection device (imaging camera) 212 are supplied to the R element 220, G element 221, and B element 222, and are photoelectrically converted into R signals, G signals, and B signals, respectively, and output.

[0080] The R signal, G signal, and B signal are input to amplifiers 223 , 224 , and 225 provided in the calculation means 213 , respectively, and are further input to a signal processing circuit 226 . The signal processing circuit 226 calculates various feature quantities using each of the R, G, and B signals individually or in combination, and also performs addition, subtraction, Ride The signal is converted by performing arithmetic processing such as multiplication or division. This signal conversion characterizes the signal received by the optical detection device (image pickup camera) 212 to identify the object to be inspected, and this signal is input to the comparison circuit 227a, which determines whether the object to be inspected (here, the first non-defective product) is good or bad, and the object is classified as a second non-defective product A1 or a second defective product B1.

[0081] Furthermore, the signal processed by the signal processing circuit 226 is input to the measurement circuit 227b, whereby the first non-defective product is classified into a second non-defective product A2 and a second defective product B2, and the second defective product B2 is further classified into each defective factor, separately from the pass / fail judgment by the comparison circuit 227a. Then, the mixing rate of the second non-defective product A2 and each defective factor is calculated. This mixing rate corresponds to the first defective product mixing rate in the present invention. The comparison circuit 227a serves as a determination means, and the measurement circuit 227b serves as a calculation means. The measuring circuit 227b may also function as both the determining means and the calculating means, in which case a signal is sent from the measuring circuit 227b to a delay circuit 228, which will be described later.

[0082] A delay circuit 228 determines the ejection timing according to the distance between the position where the object to be inspected is observed by the optical detection device (imaging camera) 212 and the rejection position where the second defective product B1 is rejected by the ejector device 215. A rejection signal is output from the comparison circuit 227a to the ejector drive circuit 214 via the delay circuit 228. The rejection signal determined by the ejector drive circuit 214 is output to the ejector device 215.

[0083] (Calculation algorithm for the contamination rate of each defect factor in the grain inspection device 305) 9 calculates feature amounts for each particle of the object to be inspected from the R, G, and B values ​​using various combinations of spectral ratios such as R / G and R / B. The calculated values ​​are then compared with a discriminant stored in the measurement circuit 227b (see, for example, FIGS. 6 to 10 of Japanese Patent Laid-Open Publication No. 9-292344) to discriminate between, for example, six types of defect factors.

[0084] If a program is set up in advance to classify the six types of defective factors, such as (a) classifying grains damaged by pests (stink bug damaged grains) as good quality and the rest, (b) classifying grains discolored by discolored rice etc. as good quality and the rest, (c) classifying green immature grains as good quality and the rest, (d) classifying milky white grains as good quality and the rest, (e) classifying unhulled grains as good quality and the rest, and (f) classifying foreign matter as good quality and the rest, statistical processing of the degree (rate) of contamination by each defective factor can be performed quickly.

[0085] The measurement circuit 227b (calculation means) shown in Figure 9 calculates the contamination rate (first defective contamination rate) of each defective factor of the defective product (second defective product B1) contained in the raw material (first non-defective product) that has been classified as a non-defective product (second non-defective product A1) or a defective product (second defective product B1) by the comparison circuit 227a (discrimination means). The measuring circuit 227b may be used as the determining means in the present invention, and the measuring circuit 227b may determine the first non-defective product as the second non-defective product A1 or the second defective product B1.

[0086] In addition, the measurement circuit 227b can calculate the mixing rate of each of the defective factors (the first defective products and the second defective products B2) contained in the raw material hulled by the rice huller and sorter 201, using the weight value of the waste grains (first defective products) transmitted from the waste grain weigher 202b of the rice sorter 202. This mixing rate corresponds to the second defective product mixing rate in the above embodiment.

[0087] The second method for calculating the defective product contamination rate will now be described. For example, first, the raw material is sorted into regular grains (first non-defective products) and scraps (first defective products) by the rice sorter 202, and the first defective products discharged from the scrap discharge gutter 71 are weighed by the scrap weigher 202b. Then, the weight value of the weighed first defective products is transmitted to the measurement circuit 227b.

[0088] Next, the first non-defective product is classified into a non-defective product (second non-defective product A1) and a defective product (second defective product B1) by the optical sorter 203, and based on the classification result, the second defective product B3 that has been sorted out and removed by the ejector means and discharged from the defective product discharge gutter 217 is weighed by the defective product weigher 301 to determine the weight value of the second defective product B3. Furthermore, the second non-defective product A3 after the second defective product B3 has been sorted out and removed is weighed by the fine product weigher 204a to determine the weight value of the second non-defective product A3. Then, the measuring circuit 227b adds up the weight value of the second defective product B3 and the weight value of the second non-defective product A3 to determine the weight value of the first non-defective product.

[0089] Separately, based on the discrimination result, the mixing rate of each defect factor of the second defective products B1 contained in the first non-defective products (first defective product mixing rate) is calculated. This first defective product mixing rate is determined by thoroughly distinguishing the first non-defective products using the optical sorting machine 203 .

[0090] The calculated weight value of the second non-defective product A1 and the calculated weight value of the second defective product B1 are calculated from the weight value of the first non-defective product and the first defective product inclusion rate. Specifically, the calculated weight value of the first non-defective product A1 and the calculated defective product weight value of the second defective product B1 are calculated by multiplying the weight value of the first non-defective product by the first defective product inclusion rate.

[0091] Here, the reason for calculating the calculated weight value of the non-defective product and the calculated weight value of the defective product will be explained. Ta When sorting by the device 215, the second defective product B1 may be mixed with the second non-defective product A1. Therefore, the weight value of the second defective product B3 after the sorting out, measured by the defective product weigher 301, includes the second non-defective product A1. Furthermore, the weight value of the second non-defective products A3 after the sorting, measured by the non-defective product weighing machine 204a, does not include the second non-defective products A1 that have been mixed into the second defective products B3 by the sorting. Therefore, in order to eliminate the weighing error caused by the inclusion of these substances, the calculated non-defective product weight value and the calculated defective product weight value are calculated.

[0092] Then, the calculation means calculates a second defective product contamination rate, which is the proportion of the first defective product and the second defective product B1 contained in the raw material fed into the rice sorting machine 202, from the calculated good product weight value of the second good product A1, the calculated defective product weight value of the second defective product B1, and the weight value of the first defective product (measured by the waste grain weighing device 202b). The weight value obtained by adding together the calculated good product weight value of the second good product A1, the calculated defective product weight value of the second defective product B1, and the weight value of the first defective product is the weight value of the raw material, so it is possible to calculate the second defective product contamination rate from these values.

[0093] It is desirable that the calculation means does not allow the user to change the discrimination criteria. By fixing the discrimination criteria as unchangeable, it becomes easy to provide the farmers with feedback on the color-sorted sorting data, such as the rice cultivation conditions in the field for the next year, to use for the cultivation management for the next year. Therefore, when the user changes the discrimination criteria, the defective product mixing rate can be calculated using the discrimination results of the second non-defective products A2 and the second defective products B2 discriminated by the measuring circuit 227b.

[0094] The location of the calculation means is not particularly limited as long as it can receive signals from the signal processing device 226. Therefore, it may be arranged inside the optical sorting machine 203 as shown in the embodiment, or may be arranged separately in the building where the optical sorting machine 203 is installed. line It may be provided on the server 30 via 60, or it may be provided on the cloud.

[0095] Although several embodiments of the present invention have been described above, the above-described embodiments of the invention are intended to facilitate understanding of the present invention and are not intended to limit the present invention. The present invention may be modified or improved without departing from the spirit thereof, and the present invention includes equivalents thereof. Furthermore, the components described in the claims and specification may be combined or omitted to the extent that at least part of the above-described problems can be solved or at least part of the effects can be achieved. [Explanation of symbols]

[0096] 10 Cultivation management system 20 Grain Preparation Line 30 servers 40 Mobile Devices 50 Agricultural Data Collaboration Platform 60 communication lines 201 Huller and sorter 201a Husking rate sensor 201b Electrical Quantity Measurement Department 202 Rice sorting machine 202a Particle size measuring device 202b Waste grain weigher 203 Optical sorting machine 203a Test object supply section 203b Shoot 203c Optical Sorting Section 203d Discharge hopper 205 Grain inspection equipment 210 Tank 211 Vibration feeder 212a Optical detection device 212b Optical detection device 213 Calculation means 214 Ejector drive circuit 215 Ejector device 216 Good product discharge trough 217 Defective product discharge trough 220 R element 221 G element 222 B element 223 Amplifier 224 Amplifier 225 Amplifier 226 Signal Processing Circuit 227a Comparison circuit 227b Measuring circuit 228 Delay Circuit 230 Communications Department 204 Weighing bagging machine 204a Precision measuring instrument 204b Container 204c Bag stand 501 Database 502 databases 503 Database

Claims

1. A grain inspection device comprising: a rice sorting machine that sorts raw materials by grain thickness into first good products and first defective products; and an optical sorting machine that optically distinguishes the first good products into second good products and second defective products, The rice sorting machine is provided with a sizing and measuring means for measuring the weight of the first non-defective product and the weight of the first defective product, and a waste grain measuring means, The optical sorting machine includes an imaging means for imaging the first non-defective product, a discrimination means for discriminating the first non-defective product into a second non-defective product and a second defective product based on an imaging signal acquired by the imaging means, and an ejector means for selectively removing the second defective product based on a discrimination result by the discrimination means, The grain inspection device further calculates a first defective product mixing rate, which is the ratio of the second defective products contained in the first non-defective products, based on the discrimination result of the discrimination means, in order to eliminate a weighing error caused by the second non-defective products being mixed in with the second defective products when the second defective products are sorted out and rejected by the ejector means, and A grain inspection device characterized by being equipped with a calculation means for calculating a second defective product contamination rate, which is the ratio of the first defective products and the second defective products contained in the raw material, based on the weight value of the first good product measured by the sieving weighing means, the weight value of the first defective product measured by the waste grain weighing means, and the first defective product contamination rate.

2. A grain inspection device comprising: a rice sorting machine that sorts raw material by grain thickness and sorts it into first good products and first defective products; an optical sorting machine that optically distinguishes the first good products into second good products and second defective products; and a quality weighing means that weighs the second good products, The optical sorting machine is provided with a defective product weighing means for weighing the second defective products, while the rice sorting machine is provided with a waste grain weighing means for weighing the first defective products; Furthermore, the optical sorting machine is provided with an imaging means for imaging the first non-defective product, a discrimination means for discriminating the first non-defective product into a second non-defective product and a second defective product based on an imaging signal acquired by the imaging means, and an ejector means for selectively excluding the second defective product based on a discrimination result by the discrimination means, The grain inspection device calculates the weight value of the first non-defective products by adding together the weight value of the second non-defective products weighed by the quality product weighing means and the weight value of the second defective products weighed by the defective product weighing means, and calculates a first defective product mixing rate, which is the proportion of second defective products contained in the first non-defective products, based on the discrimination result of the discrimination means; calculating a calculated weight value of the second non-defective product and a calculated weight value of the second defective product from the first defective product contamination rate and the weight value of the first non-defective product, respectively; the calculated non-defective product weight value and the calculated defective product weight value are calculated in order to eliminate a weighing error caused by the second non-defective product being mixed with the second defective product when the second defective product is sorted out and removed by the ejector means, A grain inspection device characterized by being equipped with a calculation means for calculating a second defective product contamination rate, which is the ratio of the first defective products and the second defective products contained in the raw material, from the weight value of the first defective product weighed by the waste grain weighing means, the calculated weight value of the good products, and the calculated weight value of the defective products.

3. The grain inspection device described in claim 1 or claim 2, wherein the calculation means calculates various feature quantities by using each value of the R, G, and B signals of the object to be inspected obtained from the imaging signal, either alone or in combination, and performs arithmetic processing of these values ​​by adding, subtracting, multiplying, or dividing to determine the number of raw materials flowing and the number of defective grains due to each defective factor, and calculates the contamination rate of each defective factor contained in the second defective products from these results.

4. The grain inspection device according to claim 3, characterized in that the defect factor is at least one defect factor selected from grains damaged by pests, grains damaged by discolored rice, green immature grains, unhulled rice, milky grains, or foreign objects.

5. A cultivation management system in which a grain preparation line including the grain inspection device according to any one of claims 1 to 4, an agricultural data linkage platform that aggregates data related to agriculture, a server that accumulates data on the preparation and processing of brown rice in the grain preparation line, and a mobile terminal that provides cultivation management information to farmers are connected via a communication line, The server is a cultivation management system that incorporates a cultivation management program that provides farmers with feedback on this year's brown rice preparation and processing data and agricultural data from the agricultural data linkage platform, and provides farmers with cultivation management guidelines for the next year.

6. The cultivation management system according to claim 5, wherein the brown rice preparation and processing data is at least the contamination rate of each defective factor in the product inspected by the grain inspection device.

7. The cultivation management system described in claim 5, wherein the server is equipped with a maintenance program that provides farmers with feedback on this year's brown rice preparation and processing data and agricultural data from the agricultural data linkage platform, and provides maintenance information for the machines that make up the grain preparation line.

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