Measurement system, processor, method for determining measured quality value of fruit, and computer program

Abstract

To provide a technique of easily enhancing the accuracy of measuring the quality of a fruit.SOLUTION: A measurement system 1 according to the present disclosure includes: a first measurement device 2 for measuring the quality of a plurality of fruits; a second measurement device 4 for measuring the quality of fruits K of the fruits, the second measurement device being configured differently from the first measurement device 2; and a management server 8 for determining the measured quality value of a target fruit, KT of the fruits K. The management server 8 has a processing unit 32 for executing processing of determining a measured quality value on the basis of scaling data S showing the correlation between output of the first measurement device 2 and the quality value based on the output of the second measurement device 4 and on the basis of output of the first measurement device 2 when measuring the quality of the target fruit KT.SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] The present disclosure relates to a measurement system, a processing device, a method for obtaining a measured quality value of a fruit, and a computer program.

Background Art

[0002] Patent Document 1 discloses a measuring device that irradiates an object to be measured, such as a fruit, with light and obtains quality values such as the sugar content and acidity of the object to be measured by spectroscopically analyzing the transmitted light. This measuring device includes a sensor unit including a light source and a light receiving unit that receives the transmitted light. The measurement of the quality value by the measuring device is performed by bringing the sensor unit close to the object to be measured. The light source of the sensor unit disposed close to the object to be measured irradiates the object to be measured with light. The light receiving unit of the sensor unit receives the transmitted light that has passed through the object to be measured.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When measuring the quality value using the above-described measuring device, it is necessary to bring the sensor unit close to the object to be measured. Therefore, with the above-described measuring device, it is possible to measure the quality values of some of the fruits among the plurality of fruits borne on a large number of trees planted in a field, but it is difficult to comprehensively measure all the fruits in the field.

[0005] Here, if a spectroscopic camera called a so-called hyperspectral camera or a multispectral camera is used, the same spectroscopic analysis as the above-described measuring device can be performed. In a spectral camera, measurements are made based on captured images in a predetermined wavelength band. Therefore, it is possible to easily measure a relatively wide range. For this reason, it is possible to easily and comprehensively measure a plurality of fruits that have borne on a large number of trees planted in a field. On the other hand, compared with the above-described measuring device, the spectral camera is more likely to have variations in measurement values due to external factors such as time, climate, and location, and it can be said that the measurement accuracy of the spectral camera is lower than that of the above-described measuring device.

[0006] In general, a measuring device with low measurement accuracy has higher convenience than a measuring device with high measurement accuracy. In order to prioritize convenience, the inventor of the present application has found a method for easily improving the quality measurement accuracy even when using a measuring device with a different configuration and relatively low quality measurement accuracy, and has completed the embodiments disclosed below.

Means for Solving the Problems

[0007] The measurement system disclosed herein includes a first measurement device that measures the quality of a plurality of fruits, a second measurement device that measures the quality of some of the plurality of fruits with a configuration different from that of the first measurement device, and a processing device that obtains a measured quality value of a target fruit among the plurality of fruits. The processing device includes a processing unit that executes a process of obtaining the measured quality value based on scaling data indicating a correlation between an output of the first measurement device and a quality value based on an output of the second measurement device, and the output of the first measurement device when measuring the quality of the target fruit.

Advantages of the Invention

[0008] According to the present disclosure, it is possible to easily improve the quality measurement accuracy of fruits.

Brief Description of the Drawings

[0009]

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[0010] First, the contents of the embodiment will be listed and described. [Outline of the Embodiment]

[0011] (1) The measurement system according to the present disclosure includes a first measurement device that measures the quality of a plurality of fruits, a second measurement device that measures the quality of some of the plurality of fruits with a configuration different from that of the first measurement device, and a processing device that obtains a measured quality value of a target fruit among the plurality of fruits. The processing device includes a processing unit that executes a process of obtaining the measured quality value based on scaling data indicating a correlation between the output of the first measurement device and a quality value based on the output of the second measurement device, and the output of the first measurement device when the quality of the target fruit is measured.

[0012] According to the above configuration, based on the scaling data, a quality value of the second measurement device corresponding to the output of the first measurement device when measuring the quality of the target fruit can be obtained, and the obtained quality value of the second measurement device can be used as the measured quality value of the target fruit. Therefore, if the measurement accuracy of the second measurement device is higher than that of the first measurement device, the output of the first measurement device can be corrected to correspond to the quality value of the second measurement device with higher measurement accuracy than the first measurement device, and the quality measurement accuracy can be easily improved.

[0013] (2) In the measurement system of the above (1), it is preferable that the correlation indicated by the scaling is a correlation between a quality value based on the output of the first measurement device and a quality value based on the output of the second measurement device. In this case, the quality value based on the output of the first measurement device can be corrected to correspond to the quality value of the second measurement device.

[0014] (3) In the measurement system of the above (1) or (2), it is preferable that the first measurement device includes a first measurement head that measures the plurality of fruits at a first interval, and the second measurement device includes a second measurement head that measures the some of the fruits at a second interval shorter than the first interval. In this case, since the first measurement head is arranged at a first interval longer than the second interval with respect to the fruit, a wider range of measurement can be performed at one time than with the second measurement head, which is highly convenient. Therefore, according to the above configuration, while enhancing the quality measurement accuracy, the convenience can be enhanced by using the first measurement device.

[0015] (4) In the measurement system of (3) above, a moving mechanism for moving the second measurement head to a measurement position where the interval to the part of the fruit is the second interval may be further provided. In this case, the moving mechanism can move the second measurement head to the measurement position.

[0016] (5) Further, in the measurement system of any one of (1) to (4) above, when the first measurement device includes a spectroscopic camera that receives reflected light from the plurality of fruits, the second measurement device may include a light source that irradiates light to the part of the fruits and a spectroscope that spectroscopically analyzes transmitted light from the part of the fruits. In this case, the first measurement device can perform a wider range of measurement at one time than the second measurement device, which is highly convenient. Therefore, according to the above configuration, while enhancing the convenience by using the first measurement device, the quality measurement accuracy can be enhanced.

[0017] (6) Further, in the measurement system of any one of (1) to (5) above, it is preferable that the processing unit further executes a process of generating the scaling data. In this case, since scaling data according to the environment during measurement by the first measurement device can be obtained, the quality measurement accuracy can be further enhanced.

[0018] (7) Further, in the measurement system of (1) or (6) above, it is preferable that the scaling data is obtained based on a plurality of outputs of the first measurement device and a plurality of reference quality values based on a plurality of outputs of the second measurement device, which are obtained when the part of the fruits are measured by both the first measurement device and the second measurement device. In this case, the output of the first measuring device and the quality value of the second measuring device are associated with each other by some fruits. Therefore, the accuracy of the scaling data can be further improved.

[0019] (8) Also, in the measuring system of (7) above, the scaling data may be obtained based on the maximum value and the minimum value among the plurality of outputs of the first measuring device, and the maximum value and the minimum value among the plurality of reference quality values of the second measuring device. In this case, the output of the first measuring device and the quality value of the second measuring device are associated with each other based on at least the respective maximum value and minimum value. Therefore, the scaling data can be easily obtained without degrading the accuracy.

[0020] (9) Also, in the measuring system according to any one of (1) to (8) above, the agricultural machine equipped with the first measuring device and the second measuring device may be further provided. In this case, the quality measurement of the fruits can be performed while running the agricultural machine in the field where the fruit trees are cultivated. For example, the quality of the fruits of the fruit trees cultivated in the field can be efficiently measured.

[0021] (10) Also, from another perspective, the present disclosure is a processing device that obtains the measured quality value of the target fruit among a plurality of fruits. This processing device includes a processing unit that executes a process of obtaining the measured quality value based on the scaling data indicating the correlation between the output of the first measuring device that measures the quality of the plurality of fruits and the quality value based on the output of the second measuring device that measures the quality of some of the plurality of fruits with a configuration different from that of the first measuring device, and the output of the first measuring device when the quality of the target fruit is measured.

[0022] (11) From another perspective, the present disclosure is a method for obtaining a measured quality value of a target fruit among a plurality of fruits. This method includes a step of obtaining the measured quality value based on scaling data indicating a correlation relationship between an output of a first measuring device that measures the quality of the plurality of fruits and a quality value based on an output of a second measuring device that measures the quality of some of the plurality of fruits with a configuration different from that of the first measuring device, and an output of the first measuring device when measuring the quality of the target fruit.

[0023] (12) From another perspective, the present disclosure is a computer program for causing a computer to execute a process of obtaining a measured quality value of a target fruit among a plurality of fruits. This computer program causes the computer to execute a step of obtaining the measured quality value based on scaling data indicating a correlation relationship between an output of a first measuring device that measures the quality of the plurality of fruits and a quality value based on an output of a second measuring device that measures the quality of some of the plurality of fruits with a configuration different from that of the first measuring device, and an output of the first measuring device when measuring the quality of the target fruit.

[0024] [Details of Embodiments] Hereinafter, preferred embodiments will be described with reference to the drawings. Note that at least a part of each of the embodiments described below may be arbitrarily combined.

[0025] [Regarding the Overall Configuration of the Measurement System] FIG. 1 is a diagram showing an example of the overall configuration of a measurement system according to an embodiment. In FIG. 1, a measurement system 1 has a function of measuring the quality value of fruits of fruit trees cultivated in a field F. The field F of the present embodiment is, for example, a vineyard for cultivating grapes that are raw materials for wine. Therefore, a plurality of trees T are cultivated in the field F. The plurality of trees T are fruit trees and are grape trees. The plurality of trees T are cultivated in a plurality of rows. The measurement system 1 has a function of measuring the quality value of grapes that bear fruit on the tree T. More specifically, the measurement system 1 obtains the quality value of the fruit by analysis using near-infrared light. The quality value of the fruit is a value based on various components representing the quality of the fruit. The quality value includes sugar content, acidity, pH, polyphenols, etc.

[0026] The measurement system 1 includes a first measurement device 2, a second measurement device 4, an agricultural machine 6, a management server 8, a management terminal 10, and a manipulator 12. The first measurement device 2 and the second measurement device 4 are mounted on the agricultural machine 6. The manipulator 12 has a function of moving the second measurement head 26 (described later) of the second measurement device 4. The first measurement device 2 and the second measurement device 4 are devices for measuring the quality of the fruit. The first measurement device 2 and the second measurement device 4 have a function of acquiring spectral information in the near-infrared region included in the reflected light or transmitted light of the fruit. The spectral information in the near-infrared region includes information indicating the quality value of the fruit. Therefore, the first measurement device 2 and the second measurement device 4 output the spectral information in the near-infrared region as the quality measurement result. The first measurement device 2 and the second measurement device 4 will be described in detail later.

[0027] The agricultural machine 6, the management server 8, and the management terminal 10 are connected to be communicable with each other via a public network NW such as the Internet. The agricultural machine 6 has, for example, a communication function by a mobile communication system. The agricultural machine 6 is connected to the public network NW via a radio base station BS of the mobile communication system.

[0028] The management server 8 has a function of performing a process of obtaining the quality value of the fruit based on the output of the first measurement device 2 and the output of the second measurement device 4. The management terminal 10 is a terminal operated by the operator 14 of the measurement system 1. The management terminal 10 has a function of receiving an operation on the measurement system 1 by the operator 14 and a function of outputting the quality value and the like obtained by the management server 8 to the operator 14.

[0029] The agricultural machine 6 is, for example, a tractor. The agricultural machine 6 is capable of traveling within the field F. The agricultural machine 6 can travel between rows of a plurality of trees T in the field F and approach all the trees T in the field F. The agricultural machine 6 can also travel through the field F by manual operation by an operator, or can travel within the field F by automatic driving based on a control command from the management server 8 or a control command from the management terminal 10 based on an input from the operator 14.

[0030] FIG. 2 is a block diagram showing a main part of the agricultural machine 6. As shown in FIG. 2, the agricultural machine 6 includes a communication device 18 and a vehicle control device 20. The communication device 18 has a function as a mobile terminal in a mobile communication system. Therefore, the communication device 18 performs wireless communication with a radio base station BS. The vehicle control device 20 has a function of controlling each part of the agricultural machine 6. The vehicle control device 20 is connected to the public network NW via the communication device 18. Therefore, the vehicle control device 20 is communicably connected to the management server 8 and the management terminal 10. The vehicle control device 20 exchanges necessary information with the management server 8 and the management terminal 10 via the public network NW. When the agricultural machine 6 is capable of automatic driving, the vehicle control device 20 controls a camera and sensors for grasping the surroundings of the agricultural machine 6, a drive system, and a steering system of the agricultural machine 6 based on a control command or the like from the management server 8 or the management terminal 10, and performs processing for executing automatic driving.

[0031] The first measuring device 2 and the second measuring device 4 are connected to the communication device 18 of the agricultural machine 6. The first measuring device 2 and the second measuring device 4 are connected to the public network NW by the communication device 18. Therefore, the first measuring device 2 and the second measuring device 4 are also communicably connected to the management server 8 and the management terminal 10. Furthermore, the manipulator 12 is also connected to the communication device 18 and is communicably connected to the management server 8 and the management terminal 10. The first measuring device 2, the second measuring device 4, and the manipulator 12 are given control commands and the like from the management server 8 and the management terminal 10. Therefore, the first measuring device 2, the second measuring device 4, and the manipulator 12 are controlled by the management server 8 and the management terminal 10. In addition, the first measuring device 2, the second measuring device 4, and the manipulator 12 can provide necessary information to the management server 8 and the management terminal 10.

[0032] 〔Regarding the first measuring device 2 and the second measuring device 4〕 FIG. 3 is a block diagram showing an example of the first measuring device 2. As described above, the first measuring device 2 is a device that measures the quality of fruits, and outputs spectral information in the near-infrared region as a measurement result of the quality. The first measuring device 2 receives the reflected light from the fruit and outputs spectral information obtained by splitting the received reflected light. Note that the spectral information refers to information indicating the relationship between the wavelength and the light intensity in the near-infrared region.

[0033] As shown in FIG. 3, the first measuring device 2 includes a first measurement head 22 and a first control unit 24. The first measurement head 22 includes, for example, a hyperspectral camera. The hyperspectral camera is a spectroscopic camera having a plurality of detection wavelength bands capable of detecting the intensity of light. The first measurement head 22 (hyperspectral camera) has a plurality of detection wavelength bands in the near-infrared region. The first measurement head 22 images a predetermined imaging region to acquire a two-dimensional image. That is, the first measurement head 22 receives the reflected light when the object existing in the imaging region is irradiated with sunlight and acquires a two-dimensional image. The pixels constituting this two-dimensional image have information indicating the light intensity of a plurality of detection wavelength bands as luminance. Therefore, the image acquired by the first measurement head 22 has spectral information in the near-infrared region for each pixel. Hereinafter, the image acquired by the first measurement head 22 is also referred to as a spectral image. In this way, the first measurement head 22 can acquire spectral information in the near-infrared region in units of imaging regions.

[0034] The first measurement head 22 is used for imaging the grape fruit K which is the object to be measured. The first measurement head 22 is a camera capable of imaging a two-dimensional image. Therefore, when imaging the fruit K with the first measurement head 22, a predetermined first interval D1 is provided between the first measurement head 22 and the grape fruit K. The first interval D1 is, for example, about 30 cm ± 5 cm. In this embodiment, the grape fruit K refers to a cluster including a plurality of fruit grains k1. The imaging area A of the first measurement head 22 when the first interval D1 is provided has a size capable of imaging a plurality of fruits K scattered among the branches and leaves of one tree T. Therefore, the spectral image captured by the first measurement head 22 includes a plurality of fruits K. The first measurement head 22 outputs a spectral image in which a plurality of fruits K are imaged. That is, the first measurement head 22 receives the reflected light from a plurality of fruits K and outputs a spectral image.

[0035] The first measurement head 22 provides the captured spectral image to the first control unit 24. The first control unit 24 is connected to the communication device 18 of the agricultural machine 6. The first control unit 24 has a function of controlling the first measurement head 22 based on control commands and the like given from the management server 8 or the management terminal 10. In addition, the first control unit 24 has an input unit (not shown) for receiving operation inputs, and also has a function of controlling the first measurement head 22 based on the operation inputs of the operator. In addition, the first control unit 24 transmits the spectral image provided from the first measurement head 22 to the management server 8. That is, the spectral image acquired by the first measurement head 22 is provided to the management server 8 as the output (measurement result) of the first measuring device 2.

[0036] FIG. 4A is a block diagram showing an example of the second measuring device 4. As described above, the second measuring device 4 is a device for measuring the quality of the fruit K, and outputs spectral information in the near-infrared region as a quality measurement result. The second measuring device 4 irradiates the fruit K with light, receives the transmitted light that has passed through the fruit K, and outputs spectral information obtained by spectroscopically analyzing the transmitted light.

[0037] As shown in FIG. 4A, the second measuring device 4 includes a second measuring head 26, a light source 27, a spectroscope 28, and a second control unit 30. The second measuring head 26 has a light projecting unit 26a and a light receiving unit 26b. The light projecting unit 26a and the light source 27 are connected by an optical fiber. The light source 27 is, for example, a halogen lamp. The light from the light source 27 is guided through the optical fiber to the light projecting unit 26a of the second measuring head 26. The light projecting unit 26a irradiates the fruit K, which is the object to be measured, with the light from the light source 27.

[0038] The light receiving unit 26b receives the transmitted light that has passed through the fruit K. The transmitted light received by the light receiving unit 26b is generated when the light from the light projecting unit 26a irradiates the fruit K. The light receiving unit 26b and the spectroscope 28 are connected by an optical fiber. The transmitted light received by the light receiving unit 26b is guided through the optical fiber to the spectroscope 28.

[0039] FIG. 4B is a cross-sectional view of the second measuring head 26. As shown in FIG. 4B, the second measuring head 26 has a head body 26c. The head body 26c is an annular member formed of resin or the like. The head body 26c is fixed to the tip of the manipulator 12. Therefore, the second measuring head 26 is movable by the manipulator 12.

[0040] The light projecting unit 26a is provided on the annular tip surface 26c1 of the head body 26c. The light projecting unit 26a is annular. When the light from the light source 27 is applied to the light projecting unit 26a, it scatters inside and is uniformly irradiated from the light projecting unit 26a. The light from the light projecting unit 26a irradiates the fruit grains k1 of the fruit K, and transmitted light that has passed through the fruit grains k1 and reflected light reflected from the surface of the fruit grains k1 are generated. The light receiving part 26b is provided in the hole part 26c2 of the head main body 26c. The light receiving part 26b receives the transmitted light that has passed through the hole part 26c2. Note that the light receiving part 26b mainly receives transmitted light, but also receives reflected light.

[0041] In the measurement of the fruit K by the second measuring device 4, since it is necessary to irradiate the fruit grain k1 with light by the light projecting part 26a, it is necessary to bring the second measuring head 26 close to the fruit grain k1 of the fruit K. When measuring the fruit K by the second measuring device 4, the second measuring head 26 is arranged at the measurement position as shown in FIG. 4B. The measurement position shown in FIG. 4B refers to the position where the distance between the second measuring head 26 and the fruit grain k1 is the second interval D2. The second interval D2 is shorter than the first interval D1 (see FIG. 3). The second interval D2 is, for example, about 0 cm to 1 cm. Note that the state where the second interval D2 is 0 cm means the state where the second measuring head 26 is in contact with the fruit grain k1.

[0042] The second measuring head 26 is arranged at the measurement position by the manipulator 12. In this way, the manipulator 12 functions as a moving mechanism for moving the second measuring head 26 to the measurement position.

[0043] When the second measuring head 26 is brought close to the fruit grain k1 and arranged at the measurement position, the fruit grain k1 is irradiated with light from the light projecting part 26a. The light irradiated on the fruit grain k1 passes through the fruit grain k1 as shown by the arrow in FIG. 4B, and transmitted light is generated. The transmitted light passes through the hole part 26c2 and is received by the light receiving part 26b.

[0044] In FIG. 4A, the spectroscope 28 has a function of splitting the transmitted light and a light receiving function of converting the split spectrum into a signal. When the transmitted light received by the light receiving part 26b is given to the spectroscope 28, the spectroscope 28 outputs spectrum information obtained by splitting the transmitted light. The spectrum information output by the spectroscope 28 is given to the second control part 30.

[0045] The second control unit 30 is connected to the communication device 18 of the agricultural machine 6. The second control unit 30 has a function of controlling the light source 27 and the spectroscope 28 based on control commands and the like given from the management server 8 and the management terminal 10. Further, the second control unit 30 has an input unit (not shown) for receiving operation inputs, and also has a function of controlling the light source 27 and the spectroscope 28 based on the operation inputs of the operator.

[0046] In addition, the second control unit 30 transmits the spectral information given from the spectroscope 28 to the management server 8. That is, the spectral information acquired by the spectroscope 28 is given to the management server 8 as the output (measurement result) of the second measuring device 4.

[0047] As described above, the configuration of the first measuring device 2 and the configuration of the second measuring device 4 are different in terms of the presence or absence of a spectral camera, the presence or absence of a light source, and the like. Further, in the first measuring device 2, the qualities of a plurality of fruits K are measured together, while in the second measuring device 4, the quality of one fruit grain k1 is measured. Here, the measurement accuracy as the quality value indicated by the spectral information output by the second measuring device 4 is higher than the measurement accuracy as the quality value indicated by the spectral image (spectral information) output by the first measuring device 2. In the measurement by the second measuring device 4, since the second measurement head 26 is brought close to the fruit grain k1 and spectral information is acquired from the transmitted light when irradiated with light, it is hardly affected by the surrounding environment. On the other hand, in the measurement by the first measuring device 2, since spectral information is acquired from the reflected light of the fruit K, it is easily affected by the surrounding environment. As a result, the measurement accuracy of the second measuring device 4 is higher than the measurement accuracy of the first measuring device 2.

[0048] 〔Regarding the management server 8〕 FIG. 5 is a block diagram showing a configuration example of the management server 8. As shown in FIG. 5, the management server 8 (processing device) is a kind of information processing device having a processing unit 32, a storage unit 34, and a communication device 36. The communication device 36 is a communication interface capable of communicating with an external device via the public network NW. The processing unit 32 is various processors suitable for computer control, such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), etc.

[0049] The storage unit 34 is, for example, a flash memory, a hard disk, a ROM (Read Only Memory), a RAM (Random Access Memory), etc. The storage unit 34 stores a computer program for causing the processing unit 32 to execute and necessary information. The processing unit 32 realizes various processing functions that the processing unit 32 has by executing the computer program stored in a computer-readable non-transitory recording medium such as the storage unit 34.

[0050] Also, the storage unit 34 stores a plurality of first calibration curve data C1, a plurality of second calibration curve data C2, and a plurality of scaling data S. The plurality of first calibration curve data C1 is data for obtaining a quality value (first quality value) based on the output of the first measuring device 2. The plurality of second calibration curve data C2 is data for obtaining a quality value (second quality value) based on the output of the second measuring device 4. The plurality of scaling data S is data indicating the correlation between the first quality value and the second quality value. The plurality of scaling data S is generated in the quality value calculation process 32a executed by the processing unit 32.

[0051] The processing unit 32 has a function of executing a quality value calculation process 32a and a quality value management process 32b. The quality value calculation process 32a is a process of obtaining the measured quality value of the target fruit KT based on the scaling data S and the first quality value of the target fruit KT. The target fruit KT is the fruit for which the measured quality value is to be obtained among the fruits K. Also, the measured quality value is the quality value obtained by the quality value calculation process 32a, which corrects the first quality value of the target fruit KT obtained based on the output of the first measuring device 2 and has a higher accuracy than the first quality value.

[0052] Also, the quality value management process 32b is a process of managing the measured quality value obtained by the quality value calculation process 32a. These processes will be described in detail later.

[0053] [Regarding the quality measurement work of the fruit K in the field F] FIG. 6 is a flowchart showing an example of the quality measurement work of the fruit K in the field F. As shown in FIG. 6, in the quality measurement work of the fruit K, first, quality measurement is performed by the first measuring device 2 and the second measuring device 4 (in FIG. 6, step S1).

[0054] FIG. 7 is a plan view of the field F. In FIG. 7, two mutually perpendicular directions are defined as the X direction and the Y direction. As shown in FIG. 7, one direction in the X direction is the X1 direction, and the opposite direction of the X1 direction is the X2 direction. One direction in the Y direction is the Y1 direction, and the opposite direction of the Y1 direction is the Y2 direction. The quality measurement of the measuring devices 2 and 4 is performed by running the agricultural machine 6 in the field F. In the field F shown in FIG. 7, for example, a plurality of trees T (15 in the illustration) are cultivated. The trees T are arranged in 5 rows in the Y direction and 3 rows in the X direction. When the Y direction is the column direction, the trees T are arranged in 3 columns. One column is composed of 5 trees T. Each of the 15 trees T cultivated in the field F is assigned an ID as identification information. The integers from 1 to 15 are assigned as IDs to the 15 trees T. The quality measurement work of the fruit K in the field F is performed for all 15 trees T in the field F. Of the 15 trees T, the hatched trees T (trees T with IDs 2, 4, 8, 12, and 14) are the trees T for which the quality of the fruits K is measured by both the first measuring device 2 and the second measuring device 4. The other trees T are the trees T for which the quality of the fruits K is measured only by the first measuring device 2. That is, the first measuring device 2 measures the quality of the fruits K in all the trees T, and the second measuring device 4 measures the quality of the fruits K in some of the trees T in the field F.

[0055] The quality measurement by the first measuring device 2 and the second measuring device 4 in step S1 may be performed by the operation of an operator driving the agricultural machine 6, or may be performed by remote control based on an instruction from the operator 14. When the quality measurement is performed by the operator, the agricultural machine 6 travels by the manual driving of the operator, and further, the first measuring device 2 and the second measuring device 4 perform the quality measurement by the manual operation of the operator. When the quality measurement is performed by remote control based on an instruction from the operator 14, the agricultural machine 6 travels by automatic driving, and the first measuring device 2 and the second measuring device 4 perform the quality measurement by control based on an instruction from the operator 14. In the present embodiment, the case where the operator driving the agricultural machine 6 performs the quality measurement will be described.

[0056] The operator boards the agricultural machine 6 and travels along the dashed line in FIG. 7 on the side of a row of a plurality of trees T in the field F. Therefore, the agricultural machine 6 approaches each tree T in order from the tree T with ID = 1. When the operator reaches the side of each tree T, the operator stops the agricultural machine 6 and performs the quality measurement by the first measuring device 2 and the second measuring device 4. For example, when an operator parks the agricultural machine 6 on the side (the X1 direction side) of the tree T with ID = 1 as shown in FIG. 7, the operator operates the first measuring device 2 to capture an image including a plurality of fruits K of the tree T with ID = 1 in the imaging area. As a result, the first measuring device 2 outputs a spectral image of the plurality of fruits K of the tree T with ID = 1 and provides it to the management server 8. At this time, the first measuring device 2 adds the ID of the tree T to the output spectral image and transmits it. The first measuring device 2 adds the ID of the tree T to the spectral image according to the operator's operation input. When the output (spectral image) of the first measuring device 2 is provided to the management server 8, the quality measurement of the fruit K on the tree T with ID = 1 is completed.

[0057] After finishing the quality measurement of the fruit K on the tree T with ID = 1, the operator moves the agricultural machine 6 in the Y2 direction and parks the agricultural machine 6 on the side (the X1 direction side) of the tree T with ID = 2. Here, the tree T with ID = 2 is a tree on which the quality measurement of the fruit K is performed by both the first measuring device 2 and the second measuring device 4. Therefore, the operator operates the first measuring device 2 to capture an image including a plurality of fruits K on the tree T with ID = 2 in the imaging area. As a result, the first measuring device 2 outputs a spectral image of the plurality of fruits K of the tree T with ID = 2 and provides the spectral image with the ID of the tree T added to the management server 8.

[0058] Furthermore, the operator operates the second measuring device 4 to perform a quality measurement. The operator uses the manipulator 12 to bring the second measuring head 26 of the second measuring device 4 close to the tree T. Among the plurality of fruits K of the tree T, the operator brings the second measuring head 26 close to one fruit K imaged by the first measuring device 2. The operator operates the second measuring device 4 to receive the transmitted light from the fruit K by the second measuring device 4. As a result, the second measuring device 4 outputs the spectral information of the fruit K of the tree T with ID = 2 and provides it to the management server 8. In the following description, the fruit K measured by the second measuring device 4 is also referred to as a reference fruit KR. The second measurement device 4 also adds the ID of the tree T to the output spectral image and transmits it. The second measurement device 4 adds the ID of the tree T to the spectral information according to the operator's operation input. Furthermore, the second measurement device 4 may also add position information indicating the position of the reference fruit KR to the spectral information according to the operator's operation input. When the outputs of the first measurement device 2 and the second measurement device 4 are provided to the management server 8, the quality measurement of the tree T with ID = 2 is completed.

[0059] As described above, the operator performs the quality measurement of the fruits K in a plurality of trees T according to the order of the IDs. The outputs of the first measurement device 2 and the second measurement device 4 (spectral image and spectral information) are stored in the storage unit 34 of the management server 8. Therefore, the storage unit 34 stores the spectral images with IDs = 1 to 15 added, and the spectral information with IDs = 2, 4, 8, 12, and 14 added.

[0060] As shown in FIG. 6, after the quality measurement by the first measurement device 2 and the second measurement device 4 is completed, next, the quality value calculation process by the management server 8 is performed (step S2 in FIG. 6). FIG. 8 is a flowchart showing an example of the quality value calculation process. In the quality value calculation process, the measured quality values of the fruits K of each of the 15 trees T are obtained.

[0061] As shown in FIG. 8, first, the processing unit 32 of the management server 8 obtains the first quality value and the second quality value (step S21 in FIG. 8). The processing unit 32 obtains the first quality value based on the output (spectral image) of the first measurement device 2. Also, the processing unit 32 obtains the second quality value based on the output (spectral information) of the second measurement device 4.

[0062] The processing unit 32 obtains the first quality value and the second quality value by a spectroscopic analysis method using near-infrared light. Quantitative analysis by spectroscopic analysis using near-infrared light is an analytical method that utilizes the fact that the degree of light absorption in a wavelength band where a specific component significantly absorbs light changes according to the content of the specific component. The processing unit 32 obtains the sugar content, acidity, pH, and polyphenol content as the first quality value and the second quality value. The wavelength bands in the near-infrared region used for analyzing each of the sugar content, acidity, pH, and polyphenol content are preset.

[0063] First, the process of obtaining the first quality value will be described. The processing unit 32 obtains a spectroscopic image of a wavelength band corresponding to each quality value from the spectral image that is the output of the first measuring device 2. In the present embodiment, the processing unit 32 obtains a spectroscopic image of a wavelength band corresponding to the sugar content, a spectroscopic image of a wavelength band corresponding to the acidity, a spectroscopic image of a wavelength band corresponding to the pH, and a spectroscopic image of a wavelength band corresponding to the polyphenol. Note that the spectroscopic image is an image in which the luminance of the pixels constituting the image represents the light intensity of a predetermined wavelength band.

[0064] Hereinafter, the process when the processing unit 32 obtains the sugar content as the first quality value from the spectroscopic image of the wavelength band corresponding to the sugar content will be described. The processing unit 32 specifies the image regions of the portions of a plurality of fruits K in the spectroscopic image of the wavelength band corresponding to the sugar content. The luminance of the pixels included in these plurality of image regions indicates the light intensity of the wavelength band corresponding to the sugar content. In other words, the luminance of the pixel indicates the amount of light absorption.

[0065] The processing unit 32 obtains a representative value of the luminance obtained from one spectroscopic image based on the luminance of the pixels included in the image regions of a plurality of fruits K. For example, the processing unit 32 may use the average value of the luminance of the pixels included in the image regions of a plurality of fruits K as the representative value. Also, in order to specify the image regions of the portions of a plurality of fruits K in the spectroscopic image, a threshold value can be set for the luminance. In this case, the processing unit 32 can specify the region with a luminance equal to or higher than the threshold value as the image region of the fruit K.

[0066] Also, when the reference fruit KR can be identified from the spectroscopic images of the trees T with IDs 2, 4, 8, 12, and 14 based on the position information indicating the position of the reference fruit KR, the processing unit 32 may obtain a representative value of the luminance based on the pixels included in the image region of only the portion of the reference fruit KR. In this case, the luminance of the reference fruit KR can be obtained.

[0067] Next, the processing unit 32 refers to the first calibration curve data C1 and obtains the sugar content based on the luminance (representative value). FIG. 9 is a diagram showing an example of a plurality of first calibration curve data C1. FIG. 9 schematically shows the first calibration curve data C1. As shown in FIG. 9, among the plurality of first calibration curve data C11 to C14, the first calibration curve data C11 shows the correlation between the luminance of the pixels of the spectroscopic image in the wavelength band corresponding to the sugar content and the sugar content. Although omitted in FIG. 9, the first calibration curve data C12 shows the correlation between the luminance of the pixels of the spectroscopic image in the wavelength band corresponding to the acidity and the acidity. The first calibration curve data C13 shows the correlation between the luminance of the pixels of the spectroscopic image in the wavelength band corresponding to the pH and the pH. The first calibration curve data C14 shows the correlation between the luminance of the pixels of the spectroscopic image in the wavelength band corresponding to the polyphenol and the polyphenol content.

[0068] The plurality of first calibration curve data C1 may be data that can obtain the first quality value from the luminance of the pixels of the spectroscopic image, may be a table obtained by experiments, simulations, etc., or may be a linear or non-linear mathematical formula.

[0069] When obtaining the sugar content as the first quality value, the processing unit 32 refers to the first calibration curve data C11 of the sugar content and obtains the sugar content corresponding to the luminance obtained above. This sugar content is the first quality value.

[0070] The processing unit 32 also obtains the acidity, pH, and polyphenol content other than the sugar content by the same method as the method for the sugar content. The processing unit 32 obtains the first quality values (brix, acidity, pH, and polyphenol content) for each of the trees T with IDs = 1 to 15 based on the output of the first measuring device 2 as described above.

[0071] Next, the process of obtaining the second quality value will be described. The processing unit 32 obtains the absorbance in the wavelength band corresponding to each quality value from the spectral information that is the output of the second measuring device 4. Note that the absorbance is a value indicating the degree of light collection in a predetermined wavelength band with respect to the light of the light source 27 as a reference.

[0072] Hereinafter, the process when the processing unit 32 obtains the brix as the first quality value will be described. The processing unit 32 refers to the second calibration data C2 and obtains the brix based on the absorbance (representative value).

[0073] FIG. 10 is a diagram showing an example of a plurality of second calibration data C2. FIG. 10 schematically shows the second calibration data C2. As shown in FIG. 10, among the plurality of second calibration data C21 to C24, the second calibration data C21 shows the correlation between the absorbance in the wavelength band corresponding to the brix and the brix. Although omitted in FIG. 10, the second calibration data C22 shows the correlation between the absorbance in the wavelength band corresponding to the acidity and the acidity. The second calibration data C23 shows the correlation between the absorbance in the wavelength band corresponding to the pH and the pH. The second calibration data C24 shows the correlation between the absorbance in the wavelength band corresponding to the polyphenol and the polyphenol content.

[0074] The plurality of second calibration data C2 may be data that can obtain the second quality value from the absorbance, and may be a table obtained by experiments, simulations, etc., or may be a linear or non-linear mathematical formula.

[0075] When obtaining the brix as the second quality value, the processing unit 32 refers to the second calibration data C21 of the brix and obtains the brix corresponding to the absorbance obtained above. This brix is the second quality value.

[0076] The processing unit 32 also obtains the acidity, pH, and polyphenol content other than the sugar content by the same method as the sugar content method. The processing unit 32 obtains the second quality values (sugar content, acidity, pH, and polyphenol content) in each of the trees T with ID = 2, 4, 8, 12, and 14 based on the output of the second measuring device 4 as described above.

[0077] In the above manner, the processing unit 32 obtains the first quality value in each of the trees T with ID = 1 to 15 and the second quality value in each of the trees T with ID = 2, 4, 8, 12, and 14 (in FIG. 8, step S21). Next, as shown in FIG. 8, the processing unit 32 generates scaling data S (in FIG. 8, step S22).

[0078] The scaling data S is obtained based on the first quality value and the second quality value obtained when a part of the plurality of fruits K (reference fruits KR) are measured by both the first measuring device 2 and the second measuring device 4. That is, the scaling data S is obtained based on the first quality value in each of the trees T with ID = 2, 4, 8, 12, and 14 and the second quality value in each of the trees T with ID = 2, 4, 8, 12, and 14. Hereinafter, the first quality value with ID = 2, 4, 8, 12, and 14 is also referred to as the reference first quality value, and the second quality value with ID = 2, 4, 8, 12, and 14 is also referred to as the reference second quality value.

[0079] Note that the first quality value in each of the trees T with ID = 2, 4, 8, 12, and 14 may be the average of the quality values of a plurality of fruits K including the reference fruit KR. Also, the first quality value in each of the trees T with ID = 2, 4, 8, 12, and 14 may include only the quality value of the reference fruit KR.

[0080] FIG. 11 is a diagram showing an example of scaling data S. As shown in FIG. 11, among a plurality of scaling data S1 to S4, the scaling data S1 shows the correlation between the sugar content measured by the first measuring device 2 and the sugar content measured by the second measuring device 4. Although omitted in FIG. 11, the scaling data S2 shows the correlation between the acidity measured by the first measuring device 2 and the acidity measured by the second measuring device 4. The scaling data S3 shows the correlation between the pH measured by the first measuring device 2 and the pH measured by the second measuring device 4. The scaling data S4 shows the correlation between the polyphenol content measured by the first measuring device 2 and the polyphenol content measured by the second measuring device 4.

[0081] The scaling data S1 includes a diagram L showing the correlation between the sugar content measured by the first measuring device 2 and the sugar content measured by the second measuring device 4. The horizontal axis in the scaling data S1 is the sugar content (first quality value) measured by the first measuring device 2, and the vertical axis is the sugar content (second measured value) measured by the second measuring device 4. The diagram L is a straight line passing through the point VU and the point VL. The five points in FIG. 11 are the points where the reference fruit KR having the reference first quality value and the reference second quality value are plotted. Among the five points, the point VU is the point of the reference fruit KR having the maximum value of the sugar content (a plurality of reference first quality values) measured by the plurality of first measuring devices 2 and the maximum value of the sugar content (a plurality of reference second quality values) measured by the plurality of second measuring devices 4. The point VL is the point of the reference fruit KR having the minimum value of the sugar content (a plurality of reference first quality values) measured by the plurality of first measuring devices 2 and the minimum value of the sugar content (a plurality of reference second quality values) measured by the plurality of second measuring devices 4.

[0082] Thus, in the present embodiment, the scaling data S1 is obtained based on a plurality of reference first quality values and a plurality of reference second quality values obtained when a plurality of reference fruits KR are measured by both the first measuring device 2 and the second measuring device 4. In this case, the first quality value and the second quality value are associated with each other by the plurality of reference fruits KR. Therefore, the accuracy of the scaling data S can be further improved.

[0083] Further, the scaling data S1 is obtained based on the maximum and minimum values among a plurality of reference first quality values (outputs of the first measuring device 2), and the maximum and minimum values among a plurality of reference second quality values. In this case, the reference first quality value and the reference second quality value are associated based on at least their respective maximum and minimum values. Therefore, the scaling data S1 can be easily obtained without degrading the accuracy.

[0084] Other scaling data S2 to S4 are also obtained in the same manner as the scaling data S1. The scaling data S may be data indicating the correlation between the first quality value (output of the first measuring device 2) and the second quality value, and may be a table or a mathematical formula.

[0085] In the above manner, the processing unit 32 generates the scaling data S (step S22 in FIG. 8). Next, as shown in FIG. 8, the processing unit 32 calculates the measured quality value (step S23 in FIG. 8).

[0086] The processing unit 32 selects the target fruit KT from among the fruits K on the trees T with IDs = 1 to 15, and obtains the measured quality value of the target fruit KT based on the scaling data S and the first quality value of the target fruit KT. The processing unit 32 sequentially selects the target fruit KT from among the fruits K on the trees T with IDs = 1 to 15, and repeatedly obtains the measured quality value. Thereby, the processing unit 32 obtains the measured quality value of each of the fruits K on the trees T with IDs = 1 to 15. The processing unit 32 refers to the scaling data S and obtains the second quality value corresponding to the first quality value of the target fruit KT. The processing unit 32 obtains the second quality value corresponding to this first quality value as the measured quality value of the target fruit KT.

[0087] For example, the case of obtaining the sugar content as the measured quality value of the fruit K on the tree T with ID = 1 will be described. FIG. 12 is a diagram showing an aspect when the processing unit 32 obtains the measurement quality value of the fruit K on the tree T with ID = 1. The processing unit 32 selects the fruit K on the tree T with ID = 1 as the target fruit KT. Next, the processing unit 32 refers to the scaling data S1, and in the diagram L, obtains the sugar content (vertical axis in FIG. 12) by the second measuring device 4 corresponding to the sugar content (horizontal axis in FIG. 12), which is the first quality value of the fruit K (target fruit KT) with ID = 1. The processing unit 32 uses the sugar content measured by the second measuring device 4 corresponding to the first quality value as the measurement quality value. In this way, the vertical axis of the scaling data S1 indicates the sugar content measured by the second measuring device 4 and also indicates the measurement quality value obtained from the first quality value.

[0088] For the acidity, pH, and polyphenol content other than the sugar content among the measurement quality values, the processing unit 32 obtains them by the same method as the method for the sugar content. The processing unit 32 repeats the same process for the fruit K on the trees T with ID = 1 to 15, and obtains the measurement quality value of each fruit K on the trees T with ID = 1 to 15. Regarding the fruit K on the trees T with ID = 2, 4, 8, 12, and 14 including the reference fruit KR, the second quality value measured by the second measuring device 4 may be used as the measurement quality value as it is.

[0089] As described above, the processing unit 32 calculates the measurement quality value (in FIG. 8, step S23). Next, the processing unit 32 proceeds to step S3 in FIG. 6 and executes a quality management process for managing the measurement quality value (in FIG. 6, step S3).

[0090] According to the above configuration, based on the scaling data S, the second quality value corresponding to the first quality value (output of the first measuring device) of the target fruit KT can be obtained, and the obtained second quality value can be used as the measurement quality value of the target fruit KT. As a result, the first quality value of the target fruit KT can be corrected to be equivalent to the quality value of the second measuring device 4 with higher measurement accuracy than the first measuring device 2, and the quality measurement accuracy can be easily improved.

[0091] Further, in the present embodiment, since the first measurement head 22 of the first measurement device 2 is arranged at a first interval D1 that is longer than the second interval D2 of the second measurement head 26 with respect to the fruit K, measurement over a wider range can be performed at one time compared to the second measurement head 26, and the convenience is high. Therefore, according to the present embodiment, while enhancing the quality measurement accuracy, the convenience can be enhanced by measuring the quality of the fruits K in the entire field F using the first measurement device 2.

[0092] That is, in the present embodiment, since the first measurement head 22 includes a hyperspectral camera (spectral camera), the first measurement device 2 can perform measurement over a wider range at one time and has higher convenience than the second measurement device 4 including the light source 27 and the spectroscope 28 that splits transmitted light. For this reason, according to the present embodiment, while enhancing the quality measurement accuracy, the convenience can be enhanced by using the first measurement device 2.

[0093] 〔Others〕 It should be considered that the embodiments disclosed this time are illustrative in all respects and not restrictive. For example, in the above embodiment, the scaling data S is obtained based on the reference first quality value and the reference second quality value, and in step S23 in FIG. 8, the case where the measured quality value of the fruit K is obtained based on the first quality value as the output of the first measurement device 2 is illustrated. However, the scaling data S may be obtained based on the luminance of the first measurement device 2 when measuring the reference fruit KR and the reference second quality value, and in step S23 in FIG. 8, the measured quality value of the fruit K may be obtained based on the luminance as the output of the first measurement device 2. In this case, as shown in FIG. 13, the scaling data S becomes data showing a correlation with the luminance of the first measurement device 2 and the second quality value. Also in this case, the first calibration line data C1 becomes unnecessary, and the arithmetic addition in the processing unit 32 can be reduced.

[0094] In the above embodiment, the case where the first measurement head 22 includes a hyperspectral camera has been exemplified. However, the first measurement head 22 may include a multispectral camera instead of the hyperspectral camera. A multispectral camera is a spectroscopic camera that has fewer detection wavelength bands for detecting the intensity of light than a hyperspectral camera. Even if it is a multispectral camera, as long as it can detect the necessary wavelength bands, it can be used in the same manner as a hyperspectral camera.

[0095] Also, in the above embodiment, the diagram L of the scaling data S is exemplified as a straight line passing through the point VU and the point VL, and is obtained based on the maximum value and the minimum value among the plurality of reference first quality values, and the maximum value and the minimum value among the plurality of reference second quality values. However, the present invention is not limited to this. For example, an approximate expression may be obtained using a plurality of points determined by the reference first quality value and the reference second quality value, and this approximate expression may be used as the scaling data S.

[0096] The scope of the present invention is not as described above, but is indicated by the claims, and it is intended that the meaning equivalent to the claims and all modifications within the scope are included.

Explanation of Reference Numerals

[0097] 1 Measurement system 2 First measuring device 4 Second measuring device 6 Agricultural machine 8 Management server 10 Management terminal 12 Manipulator 14 Operator 18 Communication device 20 Vehicle control device 22 First measurement head 24 First control unit 26 Second measurement head 26a Light projecting unit 26b Light receiving unit 26c Head body 26c1 Annular tip surface 26c2 Hole portion 27 Light source 28 Beam splitter 30 Second control unit 32 Processing unit 32a Quality value calculation process 32b Quality value management process 34 Memory unit 36 Communication device A Imaging area BS Wireless base station C1, C11, C12, C13, C14 First calibration curve data C2, C21, C22, C23, C24 Second calibration curve data D1 First interval D2 Second interval F Field K Fruit KT Target fruit KR Reference fruit L Diagram NW Public network S, S1, S2, S3, S4 Scaling data T Tree k1 Granular fruit

Claims

1. A first measuring device for measuring the quality of a plurality of fruits, a second measuring device having a configuration different from that of the first measuring device and measuring the quality of some of the plurality of fruits, and a processing device for obtaining a measured quality value of a target fruit among the plurality of fruits, wherein the processing device comprises a processing unit that executes a process of obtaining the measured quality value based on scaling data indicating a correlation between an output of the first measuring device and a quality value based on an output of the second measuring device, and an output of the first measuring device when measuring the quality of the target fruit measurement system.

2. The correlation indicated by the scaling is a correlation between a quality value based on an output of the first measuring device and a quality value based on an output of the second measuring device The measurement system according to claim 1.

3. The first measuring device includes a first measuring head that measures the plurality of fruits at a first interval, The second measuring device includes a second measuring head that measures the some of the fruits at a second interval shorter than the first interval The measurement system according to claim 1.

4. The measurement system further includes a moving mechanism that moves the second measuring head to a measurement position where the interval to the some of the fruits is the second interval The measurement system according to claim 3.

5. The first measuring device includes a spectroscopic camera that receives reflected light from the plurality of fruits, The second measuring device includes a light source that irradiates light to the some of the fruits, and a spectroscope that spectroscopically analyzes transmitted light from the some of the fruits The measurement system according to claim 1.

6. The processing unit further executes a process of generating the scaling data The measurement system according to claim 1.

7. The scaling data is obtained based on a plurality of outputs of the first measuring device and a plurality of reference quality values based on a plurality of outputs of the second measuring device, which are obtained when the some of the fruits are measured by both the first measuring device and the second measuring device The measurement system according to claim 1 or claim 6.

8. The scaling data is obtained based on a maximum value and a minimum value among the plurality of outputs of the first measuring device, and a maximum value and a minimum value among the plurality of reference quality values of the second measuring device The measurement system according to claim 7.

9. The measurement system further includes an agricultural machine equipped with the first measuring device and the second measuring device The measurement system according to any one of claims 1 to 6.

10. A processing device for obtaining a measured quality value of a target fruit among a plurality of fruits, comprising: a processing unit that executes a process of obtaining the measured quality value based on scaling data indicating a correlation relationship between an output of a first measuring device that measures the quality of the plurality of fruits and a quality value based on an output of a second measuring device that measures the quality of some of the plurality of fruits with a configuration different from that of the first measuring device, and an output of the first measuring device when measuring the quality of the target fruit; A processing device.

11. A method for obtaining a measured quality value of a target fruit among a plurality of fruits, comprising: a step of obtaining the measured quality value based on scaling data indicating a correlation relationship between an output of a first measuring device that measures the quality of the plurality of fruits and a quality value based on an output of a second measuring device that measures the quality of some of the plurality of fruits with a configuration different from that of the first measuring device, and an output of the first measuring device when measuring the quality of the target fruit; A method.

12. A computer program for causing a computer to execute a process of obtaining a measured quality value of a target fruit among a plurality of fruits, the computer program causing the computer to execute a step of obtaining the measured quality value based on scaling data indicating a correlation relationship between an output of a first measuring device that measures the quality of the plurality of fruits and a quality value based on an output of a second measuring device that measures the quality of some of the plurality of fruits with a configuration different from that of the first measuring device, and an output of the first measuring device when measuring the quality of the target fruit; A computer program. ​

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