CN101308086A - Fruit internal quality on-line checking method and apparatus based on near infrared spectra technology - Google Patents
Fruit internal quality on-line checking method and apparatus based on near infrared spectra technology Download PDFInfo
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Abstract
The invention relates to a fruit internal quality on-line detection method and an apparatus thereof. The detection method comprises: implementing the spectral scanning to the fruit to be detected and collecting a near infrared spectrum of the fruit to be detected; and putting acquired spectrum signals into a pre-established model and getting the internal quality index of the fruit to be detected. The detection apparatus includes a spectrum collection device and a computer; wherein, the spectrum collection device is used in spectral scanning to the fruit to be detected and collection of near infrared spectrum signals of the fruit to be detected so as to transmit the signals to the computer; and the computer is used for putting the received spectrum signals into the pre-established model for data analysis so as to obtain the internal quality index of the fruit to be detected. The method applies the optical detection means based on near infrared to the detection process of fruit internal quality, and can release the labor force, and the method also has advantages of high detection precision, good consistency of results and high degree of automation, and creates the conditions for the standardized classification of internal quality of fruit products.
Description
Technical Field
The invention relates to a detection method for the internal quality of fruits, in particular to a near infrared spectrum-based online detection method and device for the internal quality of fruits.
Background
China is a world fruit production big country, the variety resources are rich, and the yield stably stays in the world first in recent years. However, in the international market, compared with developed countries, there is a gap between the export quantity of fruits and the deep processing of fruits, and the gap is mainly caused by low commercialization degree and uneven internal quality of fruits. For example, the taste and flavor of the same fruit batch are greatly different, and the indexes such as hardness, solid content, sugar-acid ratio and the like of the fruits are not controlled within the standard. Therefore, it is necessary to quantify the internal quality index of the fruit to create conditions for standardized classification of internal quality of fruit products.
At present, the quality detection of the internal quality of most fruits still adopts artificial sensory evaluation methods and conventional chemical analysis methods. Conventional chemical analysis has high accuracy and reliability, but belongs to destructive detection, and the detection time is long, which is not suitable for online detection of the quality of agricultural products. The manual detection is usually completed by trained and experienced experts through sensory evaluation, and the detection result has strong subjectivity and poor consistency; meanwhile, the labor intensity of manual detection is high, and particularly for fruits which are short in storage period and easy to deteriorate, the rapid detection requirement in the agricultural product circulation process cannot be met.
The near infrared spectrum analysis technology has the advantages of no pollution, low consumption, non-destructive property, capability of realizing simultaneous determination and analysis of multiple components, high analysis speed and the like. Nondestructive testing of agricultural products by using a near infrared spectrum analysis technology has been widely researched and applied, such as determination of internal qualities of ripeness, hardness and the like of fruits such as watermelon, pear and the like. In the current research, the detection of the internal quality of the fruit is mainly static, and the method cannot meet the requirement of online detection of the internal quality of the fruit. The online detection of the internal quality of fruits based on near infrared has provided a reliable theoretical basis, but the technology only stays in the laboratory research stage. Therefore, it is necessary to develop a device for detecting the internal quality of fruit based on near infrared spectroscopy analysis technology to meet the large-scale development of fruit deep processing technology.
Disclosure of Invention
In view of the above-mentioned development of the prior art, the present invention aims to provide a near infrared spectrum on-line detection method and device for the internal quality of fruit. The fruit to be detected is scanned by near infrared spectrum, the received spectrum signals are transmitted to a computer by a detector, and then the spectrum signals containing the internal quality characteristic information of the fruit to be detected are substituted into the established relevant model, so that the internal quality indexes of the fruit to be detected, such as the sugar degree, the acidity and the like, can be calculated, and the internal quality of the fruit can be detected on line.
The near infrared spectrum detection method of the internal quality of the fruit comprises the steps of performing spectrum scanning on the fruit to be detected, and collecting the near infrared spectrum of the fruit to be detected; and substituting the obtained spectrum signal into a pre-established model to calculate the internal quality index of the detected fruit.
A detection device for realizing the detection method comprises a spectrum acquisition device and a computer; wherein,
the spectrum acquisition device is used for performing spectrum scanning on the fruit to be detected, acquiring near infrared spectrum signals of the fruit to be detected and transmitting the near infrared spectrum signals to the computer;
and the computer is used for substituting the received spectrum signals into the pre-established model to carry out data analysis so as to obtain the internal quality index of the detected fruit.
The spectrum collecting device comprises a light source, an optical fiber probe, a spectrometer and a CCD detector, wherein the light source and the optical fiber probe are arranged in a lighting darkroom,
the light source is used for irradiating light on the surface of the fruit to be detected;
the optical fiber probe is used for collecting light diffused and reflected out of the fruit to be detected and transmitting the light to the spectrometer;
the spectrometer is used for decomposing the composite light into monochromatic light with single wavelength;
the detector is used for receiving the spectrum signal of the spectrometer, converting the near infrared light signal into an electric signal, converting the electric signal into a digital signal through A/D and inputting the digital signal into the computer.
In order to realize automatic operation, a rotating platform is also arranged in the lighting darkroom and used for placing fruits to be tested.
The rotating speed of the rotating platform can be controlled by a stepping motor, and the speed of the rotating platform is required to be matched with the exposure time of the CCD detector, namely the equatorial center of a fruit to be detected is basically right below the optical fiber probe in the exposure time of the CCD detector (generally set to be less than 20 ms). Round holes are formed in the rotary platform, fruits to be tested are placed in the round holes, and small baffles are attached to proper positions near the round holes. The small baffle is matched with the trigger for use, and when the small baffle blocks two infrared optical fiber probes of the trigger, the trigger triggers the CCD detector to acquire data.
The light source is a halogen lamp light source, light of the halogen lamp light source is led out by two optical fibers and is irradiated on the position near the equator center of the fruit, and light spots irradiated on the fruit by the two optical fibers are basically overlapped. The fiber probe receiving the spectrum signal is right above the center of the fruit equator. The distance between the light source optical fiber and the optical fiber probe to the center of the equator of the fruit is optimized through earlier static experiments.
The spectrometer mainly plays a role in decomposing the composite light into monochromatic light with single wavelength. The composite light emitted by the halogen lamp light source is projected onto the collimating objective through the entrance slit to form parallel light beams which are projected onto the grating, and the dispersed light is imaged at the exit slit through the focusing lens. When the grating rotates in the anticlockwise direction, the spectrums arranged in the order of wavelength can be obtained in front of the emergent slit surface, and then the required near infrared spectrum interval is selected.
The CCD detector is used for converting a near infrared light signal carrying sample information into an electric signal, and then converting the electric signal into a digital signal through A/D (analog/digital) and inputting the digital signal into a computer. The CCD detector completes the near infrared spectrum scanning of the fruit by adopting an external triggering mode. When the fruit to be detected runs to the position right below the optical fiber probe, the small baffle just blocks the two probes of the trigger, and the trigger triggers the CCD detector to acquire data. When the CCD detector runs to other parts, the two probes of the trigger are always conducted, and the trigger does not trigger the CCD detector to work, so that the spectrum signal cannot be collected.
The model is a correction model of the near infrared spectrum signal value and the fruit internal quality index. The general method of model building is: firstly, selecting a plurality of (generally more than 50) fruits of a certain variety, collecting the near infrared spectrum of all the fruits, then referring to related national standards, measuring the value of a certain index of the internal quality of the fruits by a physicochemical method, screening a plurality of variables by a stepwise regression method to establish a multivariate regression model, wherein the model has high correlation between near infrared spectrum signals and the internal quality index of the fruits. And (4) importing the built model into self-developed near-infrared fruit internal quality detection software.
The computer is provided with near-infrared fruit internal quality detection software and is mainly used for controlling the operation of the CCD detector, and displaying the acquired spectrogram and fruit internal quality index numerical value.
During operation, firstly, a spectrometer is arranged, a required spectral range is selected, the speed of a rotating platform is set, a trigger power supply is connected, a near-infrared fruit internal quality detection software system is opened, a CCD detector is triggered and controlled to carry out spectral scanning on fruits to be detected one by one, spectral signal values obtained by the detector are substituted into a model to be calculated to obtain internal quality indexes of each fruit to be detected, corresponding internal quality indexes are displayed on a software interface, and the result of each test is stored in a computer hard disk.
The sample testing was performed as follows:
1. the parameters of the accessories of the device are first set. Such as setting the intensity of the light source, the wavelength range of the spectrometer, the exposure time of the detector, and the rotational speed of the rotating platform.
2. When the fruits are measured, the fruits are placed on the rotating platform in the closed lighting chamber, and when the fruits run to the positions right below the light source and the optical fiber probe, the detector is triggered to collect the near infrared spectrum of the fruits right below the optical fiber probe. The light emitted by the halogen lamp light source irradiates the surface of the fruit to be detected through the optical fiber, diffuse reflection is formed in the fruit, the light reflected in a diffuse way enters the spectrometer through the optical fiber probe to be dispersed and then is received by the CCD detector, the spectral signal value is received by self-developed near-infrared fruit internal quality detection software, the spectral signal value is substituted into a model for calculation, the index value of certain internal quality of the fruit can be displayed on a software system interface, and the fruit test is finished.
3. Along with the rotation of the mobile platform, the next fruit to be measured enters the position right below the optical fiber probe, the operation of the second step is also completed, and by analogy, the internal quality measurement of the fruit to be measured on the mobile platform is completed one by one.
The invention has the beneficial effects that: the invention provides an application basis for standardized grading and automatic production of the internal quality of the fruits, and has stronger objectivity and repeatability compared with the current physicochemical analysis method and manual method for grading the internal quality of the fruits. The device of the invention can measure the internal quality of a fruit to be measured for no more than 50 ms. The invention adopts a rotation simulation production line of the mobile platform, and can be applied to the actual application process by slightly adjusting the device according to the requirement.
The invention applies the optical detection means based on near infrared to the detection process of the internal quality of the fruit, not only can liberate labor force, but also has the advantages of high detection precision, good result consistency, strong automation degree and the like, and creates conditions for standardized classification of the internal quality of the fruit product.
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FIG. 1: the technical scheme of the invention is shown schematically.
FIG. 2: application example implementation hardware schematic diagram of the invention
Wherein, 1, computer; 2. a light source; 3, light source optical fiber; 4. a fiber optic probe; 5. a spectrometer; 6. a detector; 7. an infrared trigger; 8. lighting darkroom; 9, rotating the platform; 10. a small baffle plate; 11. a stepper motor.
Detailed Description
The invention has universality on nondestructive testing of the internal quality of the fruit, but because the fruit is of various types, the invention only provides an implementation example for the red Fuji apple, and the testing of other fruits can be carried out by establishing a new model according to a certain index of the internal quality of the tested fruit by referring to the method of the implementation example.
Embodiment example steps referring to fig. 1, a schematic diagram of a system for detecting apples according to the present invention is shown. Example implementation means see fig. 2. Firstly, selecting a batch of apples (generally more than 50) to establish a model, carrying out spectrum scanning on the apples by using a detection device based on a near infrared spectrum analysis technology, and storing a spectrum signal value obtained by a CCD (charge coupled device) detector in a computer. The physicochemical method for measuring the sugar degree of the apple is strictly executed according to the national standard GB12295-90, peeling and juicing are carried out at the spectrum scanning spot of the apple, and an Abbe refractometer is used for measuring. And then screening out the characteristic signals by adopting a stepwise regression method, and establishing a correlation model between the spectral signal value and the sugar degree of the apple. And importing the model into near infrared fruit internal quality detection software.
And then, the sugar degree of the unknown apples can be measured on line. Putting fruits on a rotating platform 9 in a closed lighting chamber 8, turning on a light source 2, and when the fruits run to the positions right below a light source optical fiber 3 and an optical fiber probe 4, blocking two probes of a trigger 7 by a small baffle plate 10, and triggering a CCD detector 6 by the trigger 7 to acquire data; the light emitted by the halogen lamp light source 2 irradiates the surface of the detected fruit through the optical fiber 3 and forms diffuse reflection in the fruit, the light reflected by the diffuse reflection enters the spectrometer 5 through the optical fiber probe 4 and is split and then received by the CCD detector 6, the CCD detector 6 converts the near infrared light signal carrying the sample information into an electric signal, and then the electric signal is converted into a digital signal through A/D and is input into the computer 1; the computer 1 receives the spectrum signal value and substitutes the spectrum signal value into the model for calculation, and the index value of certain internal quality of the fruit can be displayed on the software system interface until the fruit test is finished. An apple to be tested is placed on the rotating platform 10, when the apple runs under the detection optical fiber probe 4, the trigger 7 starts to trigger the detector 6 to work, spectrum data acquisition of the apple is carried out, the detection software developed autonomously receives the spectrum signal value and substitutes the characteristic signal value into the model for calculation, the sugar degree value of the apple can be displayed on a software system interface, the corresponding result is immediately stored on a computer hard disk, and the test of the apple is finished. Along with the rotation of the mobile platform, the next apple enters the position under the detection optical fiber probe to complete the same operation, and by analogy, the online determination of the sugar degree of the apples to be detected on the mobile platform is completed one by one.
It is intended that the invention not be limited to the disclosed embodiments, but that the invention will cover modifications and equivalent arrangements included within the scope of the appended claims.
Claims (8)
1. A near infrared spectrum detection method for internal quality of fruits is characterized in that spectral scanning is carried out on fruits to be detected, and near infrared spectrum of the fruits to be detected is collected; and substituting the obtained spectrum signal into a pre-established model to obtain the internal quality index of the detected fruit.
2. A detection device for implementing the detection method according to claim 1, comprising a spectrum acquisition device and a computer; wherein,
the spectrum acquisition device is used for performing spectrum scanning on the fruit to be detected, acquiring near infrared spectrum signals of the fruit to be detected and transmitting the near infrared spectrum signals to the computer;
and the computer is used for substituting the received spectrum signals into the pre-established model to carry out data analysis so as to obtain the internal quality index of the detected fruit.
3. The detecting device for detecting the rotation of a motor rotor according to claim 2, wherein the spectrum collecting device comprises a light source, a fiber-optic probe, a spectrograph and a CCD detector, the light source and the fiber-optic probe are arranged in a dark lighting room, wherein,
the light source is used for irradiating light on the surface of the fruit to be detected;
the optical fiber probe is used for collecting light diffused and reflected out of the fruit to be detected and transmitting the light to the spectrometer;
the spectrometer is used for decomposing the composite light into monochromatic light with single wavelength;
the detector is used for receiving the spectrum signal of the spectrometer, converting the near infrared light signal into an electric signal, converting the electric signal into a digital signal through A/D and inputting the digital signal into the computer.
4. The detecting device for detecting the rotation of a motor rotor as claimed in claim 3, wherein said light source is a halogen lamp light source.
5. The apparatus of claim 4, wherein said detector is externally triggered.
6. The detecting device for detecting the fruit juice in the dark room of claim 5, wherein a rotating platform is further arranged in the dark room for placing the fruit to be detected.
7. The detecting device for detecting the rotation of a CCD detector according to claim 6, wherein the rotating platform rotates at a speed which is matched with the exposure time of the CCD detector; round holes are formed in the rotary platform, fruits to be tested are placed in the round holes, and a small baffle is arranged beside each round hole; the small baffle is matched with the trigger for use, and when the small baffle blocks two infrared optical fiber probes of the trigger, the trigger triggers the CCD detector to acquire data.
8. The apparatus of claim 2, wherein the model is a model for correcting the near infrared spectrum signal value and the internal quality index of the fruit.
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| CN2008101242835A CN101308086B (en) | 2008-06-24 | 2008-06-24 | Fruit internal quality on-line checking apparatus based on near infrared spectra technology |
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Cited By (22)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101907564A (en) * | 2010-06-24 | 2010-12-08 | 江苏大学 | Rapeseed quality non-destructive testing method and device based on near infrared spectrum technology |
| CN101949686A (en) * | 2010-08-02 | 2011-01-19 | 扬州福尔喜果蔬汁机械有限公司 | Online nondestructive testing (NDT) method and device for comprehensive internal/external qualities of fruits |
| CN102735612A (en) * | 2011-04-02 | 2012-10-17 | 北京神农谷科技有限公司 | Light source position detection and positioning system |
| CN103048277A (en) * | 2012-12-14 | 2013-04-17 | 北京农业智能装备技术研究中心 | Non-destructive testing system and method for testing internal quality of fruit by using near-infrared spectra |
| CN103063585A (en) * | 2013-01-05 | 2013-04-24 | 石河子大学 | Rapid nondestructive lemon and fruit maturity testing device and testing system establishment method |
| CN103281459A (en) * | 2013-06-06 | 2013-09-04 | 仝晓萌 | Mobile phone capable of measuring sweetness and PH value of fruit |
| CN103278514A (en) * | 2013-05-02 | 2013-09-04 | 浙江大学 | Modeling method of detection model for internal quality of fruit |
| CN103817085A (en) * | 2014-02-21 | 2014-05-28 | 山东省农业科学院农业质量标准与检测技术研究所 | Near-infrared quality sorting instrument for winter jujube maturity |
| CN105312246A (en) * | 2015-11-26 | 2016-02-10 | 华南农业大学 | Spherical fruit detection device based on high spectrum technology |
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| CN108593600A (en) * | 2018-04-19 | 2018-09-28 | 滨州市沾化区冬枣研究所 | Winter jujube automatic sorting method and apparatus |
| CN108613951A (en) * | 2018-03-21 | 2018-10-02 | 浙江大学 | Portable fruit hardness non-destructive testing device and detection method |
| CN108760743A (en) * | 2018-08-22 | 2018-11-06 | 江西绿萌分选设备有限公司 | A kind of multi-purpose fruits and vegetables inside quality detection device |
| CN109187544A (en) * | 2018-10-26 | 2019-01-11 | 温州大学 | A kind of device and method of Fast nondestructive evaluation fruit quality |
| CN109520970A (en) * | 2018-11-07 | 2019-03-26 | 华南理工大学 | A kind of fruit quality detection device and method based on spectrum |
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| CN101949686A (en) * | 2010-08-02 | 2011-01-19 | 扬州福尔喜果蔬汁机械有限公司 | Online nondestructive testing (NDT) method and device for comprehensive internal/external qualities of fruits |
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| CN112730316A (en) * | 2020-12-04 | 2021-04-30 | 江苏大学 | Small fruit internal quality online dynamic rapid detection method based on near infrared spectrum |
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| CN117007552A (en) * | 2023-10-07 | 2023-11-07 | 北京市农林科学院智能装备技术研究中心 | Watermelon maturity detection method, device, system, electronic equipment and storage medium |
| CN117007552B (en) * | 2023-10-07 | 2024-02-06 | 北京市农林科学院智能装备技术研究中心 | Watermelon maturity detection method, device, system, electronic equipment and storage medium |
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