CN109100322A - Food near-infrared spectrum rapid detection method and portable detector based on temperature self-correcting - Google Patents
Food near-infrared spectrum rapid detection method and portable detector based on temperature self-correcting Download PDFInfo
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- CN109100322A CN109100322A CN201810938817.1A CN201810938817A CN109100322A CN 109100322 A CN109100322 A CN 109100322A CN 201810938817 A CN201810938817 A CN 201810938817A CN 109100322 A CN109100322 A CN 109100322A
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- 235000013305 food Nutrition 0.000 title claims abstract description 53
- 238000001514 detection method Methods 0.000 title claims abstract description 51
- 238000002329 infrared spectrum Methods 0.000 title claims abstract description 28
- 238000001228 spectrum Methods 0.000 claims abstract description 26
- 238000004611 spectroscopical analysis Methods 0.000 claims abstract description 20
- 238000012360 testing method Methods 0.000 claims abstract description 19
- 238000007600 charging Methods 0.000 claims abstract description 15
- 238000007689 inspection Methods 0.000 claims abstract description 14
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 claims abstract description 12
- 229910052744 lithium Inorganic materials 0.000 claims abstract description 12
- 230000005540 biological transmission Effects 0.000 claims abstract description 8
- 239000011159 matrix material Substances 0.000 claims description 32
- 238000000034 method Methods 0.000 claims description 20
- 229910052736 halogen Inorganic materials 0.000 claims description 6
- 230000003287 optical effect Effects 0.000 claims description 6
- 229910052721 tungsten Inorganic materials 0.000 claims description 6
- 239000010937 tungsten Substances 0.000 claims description 6
- -1 tungsten halogen Chemical class 0.000 claims description 5
- 239000000203 mixture Substances 0.000 claims description 4
- 238000000354 decomposition reaction Methods 0.000 claims description 3
- 238000013461 design Methods 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 229920001296 polysiloxane Polymers 0.000 claims description 3
- 238000010561 standard procedure Methods 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 3
- 239000006185 dispersion Substances 0.000 claims description 2
- 238000006467 substitution reaction Methods 0.000 claims description 2
- 150000002367 halogens Chemical class 0.000 claims 1
- WFKWXMTUELFFGS-UHFFFAOYSA-N tungsten Chemical compound [W] WFKWXMTUELFFGS-UHFFFAOYSA-N 0.000 claims 1
- 241000167854 Bourreria succulenta Species 0.000 description 18
- 235000019693 cherries Nutrition 0.000 description 18
- 235000007688 Lycopersicon esculentum Nutrition 0.000 description 17
- 240000003768 Solanum lycopersicum Species 0.000 description 17
- 239000007787 solid Substances 0.000 description 10
- 238000010586 diagram Methods 0.000 description 3
- 238000012549 training Methods 0.000 description 3
- 238000002835 absorbance Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
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- 230000004313 glare Effects 0.000 description 2
- 238000005286 illumination Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 244000061458 Solanum melongena Species 0.000 description 1
- 235000002597 Solanum melongena Nutrition 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000013100 final test Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000005464 sample preparation method Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2201/00—Features of devices classified in G01N21/00
- G01N2201/06—Illumination; Optics
- G01N2201/061—Sources
- G01N2201/06166—Line selective sources
- G01N2201/0618—Halogene sources
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2201/00—Features of devices classified in G01N21/00
- G01N2201/12—Circuits of general importance; Signal processing
- G01N2201/121—Correction signals
- G01N2201/1211—Correction signals for temperature
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2201/00—Features of devices classified in G01N21/00
- G01N2201/12—Circuits of general importance; Signal processing
- G01N2201/126—Microprocessor processing
Abstract
The invention discloses a kind of food near-infrared spectrum rapid detection method and portable detector based on temperature self-correcting.Detection device includes shell, detection window, profiling rubber gasket, master switch, radiator fan, charging interface, battery capacity indication lamp, intelligent mobile terminal and the lithium battery being built in shell, power control circuit, miniature integrated near infrared spectrometer；Detection method is that the near infrared spectrum data of food object to be measured is acquired using portable detector, data pass through Bluetooth transmission to intelligent mobile terminal, spectroscopic data is updated in the established food inspection model being affected by temperature after lesser temperature self-correcting, the testing result of food to be measured is obtained, testing result is shown on intelligent mobile terminal interface.Portable detector of the invention has many advantages, such as that integrated level is high, small in size, detection speed is fast, at low cost, and the present invention can reduce influence of the different detection temperature to testing result by carrying out temperature self-correcting to spectrum.
Description
Technical field
The invention belongs to food science literature technical fields, and in particular to a kind of food near-infrared based on temperature self-correcting
Spectrum rapid detection method and portable detector.
Background technique
With the continuous improvement of people's lives level and the status of current food products market, so that consumer appoints than previous
When wait and all focuses more on food quality and food safety.However traditional detection food quality and food safety rely primarily on chemistry
Analysis method, although this method detection accuracy is high, that there are sample preparations is cumbersome, detection time is long and testing cost height etc. lacks
Point, it is difficult to realize the Fast nondestructive evaluation to food.
Near-infrared spectrum technique is a kind of quick, lossless, green modern analysis detection technique, in food quality and food
Product safety rapid detection field has obtained certain applications, and accordingly also exploitation has some detection devices.However, current food inspection
Device is mainly there are two problem: 1, device volume it is big, it is expensive, can not carry, be of limited application, mainly apply
In large-scale food enterprise；2, the influence to food object temperature to testing result is not accounted for, so that device is to different temperatures ring
Applicability under border reduces.
It is quickly detected because a kind of integrated level of the invention is high, price is low and can be suitably used for the portable food of different temperatures environment
Device and method has practical significance.
Summary of the invention
In view of the deficiencies in the prior art, the present invention provides that a kind of integrated level is high, price is low and can be suitably used for different temperatures ring
A kind of food near-infrared spectrum rapid detection method and portable detector based on temperature self-correcting in border.
A kind of portable detector of the invention is achieved through the following technical solutions:
A kind of portable detector, the detection device include: shell, detection window, profiling rubber gasket, master switch,
Radiator fan, charging interface, battery capacity indication lamp, intelligent mobile terminal and the lithium battery being built in shell, power supply control electricity
Road, miniature integrated near infrared spectrometer.
The profiling rubber gasket is fixed on the upper surface of shell, and center is overlapped with the center of detection window；It is described always to open
Pass, radiator fan, charging interface, battery capacity indication lamp are each attached on shell；The master switch, radiator fan, charging interface, electricity
Amount indicator light, lithium battery, miniature integrated near infrared spectrometer are all connected on power control circuit.
The miniature integrated near infrared spectrometer includes light source, slit, collimation lens, filter, diffraction grating, focuses thoroughly
Mirror, dmd chip, collection len, single point detector, signal amplifier, AD converter, microprocessor, DMD controller, light source drive
Dynamic device, temperature sensor, humidity sensor, USB port, SD card connector, low-power consumption bluetooth module.The light of light source projects pass through to
Slit is passed sequentially through after sample reflection, collimation lens, filter, is got on diffraction grating, and optical dispersion is to connect by diffraction grating
The light of continuous wavelength, then line focus lens projects are to dmd chip, the DMD controller respectively with dmd chip and microprocessor phase
Even, the continuous light for obtaining Single wavelength of micro mirror rotation, acquired lens on dmd chip are controlled and reach single point detector, reach single-point
The optical signal of detector passes to microprocessor by signal amplifier and AD converter output digit signals；The light source drive
It is connected respectively with light source and microprocessor；The temperature sensor, humidity sensor, USB port, SD card connector, low function
Consumption bluetooth module is connected with microprocessor respectively.
The profiling rubber gasket is molded using food grade silicone, play support food and avoid external environment veiling glare into
The effect for entering detection window, according to different test objects, the shape of profiling rubber gasket can be adjusted.
The battery capacity indication lamp is LED light, to indicate the battery condition of lithium battery.
The light source tool is 1.4W there are two tungsten halogen lamp, the operating power of tungsten halogen lamp, is placed in 40 ° of angles of level, with one
Sample in fixed angular illumination test, acquisition sample diffuse, and avoid the light of acquisition mirror-reflection, while before light source
End is designed to form of lens, and more light are directed to sample testing area from filament.
The intelligent mobile terminal has Bluetooth function, can carry out Bluetooth pairing company with the low-power consumption bluetooth module
Connect, the inspection software of designed, designed be installed on intelligent mobile terminal, can control miniature integrated near infrared spectrometer acquisition to
The near infrared spectrum for surveying subject sample, can also detect food to be measured, and will test as the result is shown at intelligent mobile end
It holds on interface, the result of detection can be saved in intelligent mobile terminal.
The lithium battery and power control circuit composition power supply device are whole equipment power supply, can be followed by charging interface
Ring charging.
The temperature sensor and humidity sensor are used to monitor the work temperature and humidity of miniature integrated near infrared spectrometer, temperature
Humidity data passes to intelligent mobile terminal by low-power consumption bluetooth module, and temperature and humidity is not in the work of miniature integrated near infrared spectrometer
When making range, bluetooth connection is disconnected automatically.
The USB port is connected with power control circuit, for miniature integrated near infrared spectrometer power supply；Low-power consumption bluetooth
It is automatically waken up after module for power supply.
A kind of food near-infrared spectrum rapid detection method based on temperature self-correcting of the invention passes through following technical side
Case is realized:
A kind of food near-infrared spectrum rapid detection method based on temperature self-correcting, it is characterised in that: establish by temperature
The lesser food inspection model based on near-infrared spectrum technique is influenced, including using a kind of temperature automatic correcting method to not equality of temperature
Spectroscopic data under degree carries out self-correcting and establishes model using the data of fiducial temperature after self-correcting, and model is implanted to peace
In the inspection software of intelligent mobile terminal.
A kind of method of the temperature self-correcting the following steps are included:
S1. collecting sample near infrared spectrum in the case where different temperatures is horizontal；
S2. the spectrum matrix X=XP+XQ+R acquired, in which: P is the projection matrix of useful part, Q be nonuseable part (by
Temperature influence) projection matrix, R is redundant matrices；
S3. difference spectrum matrix D: d is calculatedi=xi-xj, xiFor collecting sample spectrum mean value under a certain temperature levels,
Middle i=1,2 ... .p, p indicate p temperature levels, xjOn the basis of at a temperature of collecting sample spectrum mean value, wherein j be 1,2 ... p
One of them, difference spectrum matrix D is by diComposition；
S4. it calculates the covariance matrix of D, and carries out singular value decomposition, i.e. SVD (DTD)=USVT, obtain right singular matrix
V；
S5. it takes the preceding c of V to arrange, obtains a subset V of V matrixs；
S6. nonuseable part projection matrix Q:Q=V is calculatedsVs T；
S7. calculating useful part projection matrix P:P=I-Q, I is unit matrix；
S8. all spectroscopic datas are projected into subspace P, the spectroscopic data after obtaining temperature self-correcting, X*=XP.
Foundation be affected by temperature the lesser food inspection model based on near-infrared spectrum technique the following steps are included:
S1. the near infrared spectrum of batch capture object samples to be measured；
S2. the spectrum matrix X after temperature self-correcting is corrected is carried out to obtained spectrum matrix X*, X*=XP；
S3. food inspection index physics and chemistry value to be measured is measured using standard method；
S4. remove obtained in S2 that near infrared spectrum data both ends noise is more, the lower spectroscopic data of signal-to-noise ratio, then
Carry out de-noising pretreatment；
S5. the physical and chemical value that will be measured in spectroscopic data combination S3 pretreated in S4, compares multiple spectrum characteristic wavelength
Filtering algorithm；
S6. using the characteristic wavelength filtered out in S5, food inspection model is established using multivariate calibration methods.
Detection process the following steps are included:
S1. food samples to be measured are placed on profiling rubber gasket；
S2. the master switch of device for opening, power supply device are device power supply, and the low-power consumption bluetooth module in device is called out automatically
It wakes up；
S3. open the inspection software that is mounted on intelligent mobile terminal, with low-power consumption bluetooth module by Bluetooth pairing into
Row connection；
S4. inspection software is operated, control source emissioning light signal projects food surface to be measured and enters inside, and then light passes through
It crosses diffusing reflection and is transferred to miniature integrated near infrared spectrometer, obtain food near-infrared modal data to be measured, will test the spy of model
The spectroscopic data levied under wavelength corresponds to passes through Bluetooth transmission to intelligent mobile terminal；
S5. food inspection index prediction knot to be measured is calculated in the substitution of spectroscopic data obtained in S4 detection model program
Fruit, as the result is shown on the interface of intelligent mobile terminal.
Beneficial effects of the present invention, specific as follows:
First, detection device provided by the invention uses modularized design, intelligent mobile terminal is by Bluetooth communication to dress
Set and controlled, make structure of the detecting device it is simple, it is small in size, light-weight, be convenient for carrying；
Second, the present invention use Bluetooth Low Energy (BLE) Radio Transmission Technology, intelligent mobile terminal by Bluetooth pairing with
Low-power consumption bluetooth module carries out pairing connection, realizes data transmission, and detection device is made to have the characteristics that low-power consumption, while bluetooth
Wireless transmission gets rid of wired constraint, controls device remotely；
Third, during food inspection model foundation, by utilizing the preferably a small amount of characteristic wave of characteristic wavelength filtering algorithm
Length is modeled, and on the one hand be can simplify model, is improved the robustness of model；On the other hand the data of Bluetooth transmission be can reduce
Amount improves bluetooth data transmission speed, so that detection speed be made to be significantly improved；
Fourth, testing result forecasting inaccuracy true problem different for food object temperature, by carrying out temperature to spectrum
Detection model is established in self-correcting, makes model to well adapting to property of temperature.
Detailed description of the invention
Fig. 1 is a kind of portable detector external structure schematic diagram of the invention；
Fig. 2 is a kind of portable detector schematic diagram of internal structure of the invention；
Fig. 3 is the structural schematic diagram of miniature integrated near infrared spectrometer of the invention；
Fig. 4 is near infrared light under 7 different temperatures of No. 25 cherry and tomato after the temperature self-correcting in the embodiment of the present invention
Spectrogram；
Fig. 5 is the characteristic wavelength selection result of the cherry and tomato soluble solid content detection in the embodiment of the present invention
Figure；
Fig. 6 is the cherry and tomato soluble solid content model result figure in the embodiment of the present invention；
In figure: shell 1, detection window 2, profiling rubber gasket 3, master switch 4, radiator fan 5, charging interface 6, battery capacity indication
Lamp 7, intelligent mobile terminal 8, lithium battery 9, power control circuit 10, miniature integrated near infrared spectrometer 11, light source 12, slit
13, collimation lens 14, filter 15, diffraction grating 16, condenser lens 17, dmd chip 18, collection len 19, single point detector
20, signal amplifier 21, AD converter 22, microprocessor 23, DMD controller 24, light source drive 25, temperature sensor 26,
Humidity sensor 27, USB port 28, SD card connector 29, low-power consumption bluetooth module 30.
Specific embodiment
Technical solution of the present invention is described in further detail below with reference to the drawings and specific embodiments:
A kind of portable detector as depicted in figs. 1 and 2, the detection device include: shell 1, detection window 2,
It profiling rubber gasket 3, master switch 4, radiator fan 5, charging interface 6, battery capacity indication lamp 7, intelligent mobile terminal 8 and is built in outer
Lithium battery 9, power control circuit 10, miniature integrated near infrared spectrometer 11 in shell 1.
The profiling rubber gasket 3 is fixed on the upper end of shell 1, and center is overlapped with the center of detection window 2；It is described always to open
4, radiator fan 5, charging interface 6, battery capacity indication lamp 7 is closed to be each attached on shell 1；The master switch 4, radiator fan 5, charging
Interface 6, battery capacity indication lamp 7, lithium battery 9, miniature integrated near infrared spectrometer 11 are all connected on power control circuit 10.
Miniature integrated near infrared spectrometer as shown in Figure 3, the miniature integrated near infrared spectrometer 11 include light source 12,
Slit 13, collimation lens 14, filter 15, diffraction grating 16, condenser lens 17, dmd chip 18, collection len 19, single-point are visited
Survey device 20, signal amplifier 21, AD converter 22, microprocessor 23, DMD controller 24, light source drive 25, temperature sensor
26, humidity sensor 27, USB port 28, SD card connector 29, low-power consumption bluetooth module 30；The light that light source 12 projects is through to be measured
Sample reflection after pass sequentially through slit 13, collimation lens 14, filter 15, diffraction grating 16, condenser lens 17, dmd chip 18,
Collection len 19, single point detector 20, the optical signal for reaching single point detector 20 pass through signal amplifier 21 and AD converter 22
Output digit signals pass to microprocessor 23；The DMD controller 24 is connected with dmd chip 18 and microprocessor 23 respectively, control
Micro mirror rotates on dmd chip processed；The light source drive 25 is connected with light source 12 and microprocessor 23 respectively；The temperature passes
Sensor 26, humidity sensor 27, USB port 28, SD card connector 29, low-power consumption bluetooth module 30 respectively with 23 phase of microprocessor
Even.
The profiling rubber gasket 3 is molded using food grade silicone, is played support food and is avoided external environment veiling glare
Into the effect of detection window 2, according to different test objects, the shape of profiling rubber gasket 3 can be adjusted.
The battery capacity indication lamp 7 is LED light, to indicate the battery condition of lithium battery.
The tool of light source 12 is 1.4W there are two tungsten halogen lamp, the operating power of tungsten halogen lamp, is placed in 40 ° of angles of level, with
Sample in certain angular illumination test, acquisition sample diffuse, and avoid the light of acquisition mirror-reflection, while light source 12
Front-end Design at form of lens, more light are directed to sample testing area from filament.
The intelligent mobile terminal 8 has Bluetooth function, can carry out Bluetooth pairing with the low-power consumption bluetooth module 30
It connects, the inspection software of designed, designed is installed on intelligent mobile terminal 8, miniature integrated near infrared spectrometer 11 is can control and adopts
Collect the near infrared spectrum of subject sample to be measured, food to be measured can also be detected, and will test as the result is shown in intelligent sliding
On dynamic 8 interface of terminal, the result of detection can be saved in intelligent mobile terminal 8.
The lithium battery 9 and power control circuit 10 form power supply device as whole equipment power supply, can pass through charging
6 cycle chargings of mouth.
The work that the temperature sensor 26 and humidity sensor 27 are used to monitor miniature integrated near infrared spectrometer is warm and humid
Degree, data of the Temperature and Humidity module pass to intelligent mobile terminal 8 by low-power consumption bluetooth module 30, and temperature and humidity is not in miniature integrated near infrared light
When the working range of spectrometer 11, bluetooth connection is disconnected automatically.
The USB port 28 is connected with power control circuit 10, powers for miniature integrated near infrared spectrometer 11；Low function
Consumption bluetooth module 30 automatically wakes up after powering.
Food inspection object temperature is very big on final testing result influence, so needing to carry out near infrared spectrum temperature to it
Self-correcting is spent, in the present embodiment, the temperature automatic correcting method in the present invention is illustrated by taking cherry and tomato as an example:
(1) 40 cherry and tomatos are acquired under the conditions of 5 DEG C, 10 DEG C, 15 DEG C, 20 DEG C, 25 DEG C, 30 DEG C, 35 DEG C of this 7 temperature
Near infrared spectrum, be denoted as X1、X2、X3、X4、X5、X6、X7, temperature controlled by constant incubator；
(2) X is sought1、X2、X3、X4、X5、X6、X7Averaged spectrum x1、x2、x3、x4、x5、x6、x7；
(3) with 20 DEG C for benchmark temperature, di=xi-x4(i=1,2 ... 7), by d1、d2、d3、d4、d5、d6、d7Form difference
Matrix D；
(4) to DTD carries out singular value decomposition, SVD (DTD)=USVT；
(5) a sub-spaces V of the preceding 3 column composition V of V is takens；
(6) pass through VsVs TCalculate Q；
(7) useful part projection matrix P=I-Q is calculated；
(8) temperature self-correcting: X is carried out to spectroscopic data*=XP；
From fig. 4, it can be seen that utilizing No. 25 light of the cherry and tomato under 7 different temperatures after the method self-correcting
Spectral difference is different smaller.
In the present embodiment, in detection method modeling method with cherry and tomato establish soluble solid content prediction model into
Row explanation:
(1) near infrared spectrum data of 130 cherry and tomatos, every spectrum are acquired using the portable detector
228 data points, collected is the absorbance data of cherry and tomato；
(2) contained according to National Standard Method using the soluble solid at Abbe refractometer measurement cherry and tomato spectra collection position
Measure the physical and chemical value as modeling；
(3) in spectroscopic data, due to the 211st to No. 228 i.e. this corresponding 18 spectrum of 1650.03nm~1700.93nm
Data noise is very big, signal-to-noise ratio is relatively low, so the corresponding spectroscopic data of this 18 wavelength is removed, is not involved in modeling；
(4) formula X is pressed to spectrum*=XP carries out temperature self-correcting, the spectrum after being corrected；
(5) smoothly spectroscopic data is pre-processed using 7: 2 Savitzky-Golay convolution；
(6) sample is divided into training set and forecast set, i.e. training set 87 according to the ratio of 2:1, training set 43；
(7) using the algorithm screening characteristic wavelength that leapfrogs at random, as shown in figure 5, the variable for taking variable selected probability to be greater than 0.7
As the characteristic wavelength filtered out, filtered out 18 characteristic wavelengths altogether, be respectively 909.41nm, 937.77nm, 946.74nm,
950.57nm、970.96nm、974.77nm、978.57nm、1017.59nm、1084.39nm、1191.22nm、1194.75nm、
1364.25nm,1367.55nm,1381.78nm,1512.10nm,1556.83nm,1616.23nm,1623.04nm；
(8) using the characteristic wavelength filtered out, it is fixed that cherry and tomato soluble solid content is established using PLS modeling method
Model is measured, resulting model equation is Ypre=10.3204-0.4152X1-0.5000X2-0.4946X3-0.4916X4-
0.4650X5-0.4536X6-0.4510X7-0.3815X8-0.2511X9-0.2028X10-0.1984X11+0.0019X12+
0.0285X13+0.1733X14+0.3940X15+0.3944X16+0.3101X17+0.2462X18, wherein Xi(i=1,2,3 ...
It 18) is the corresponding absorbance of 18 characteristic wavelengths, YpreFor the predicted value of the soluble solid content of cherry and tomato；It can from Fig. 6
To find out, the related coefficient of the model of the cherry and tomato soluble solid content of foundation is higher, and root-mean-square error is lower, model
With preferable estimated performance.
In the present embodiment, by taking the soluble solid content for detecting cherry and tomato as an example, detection process is illustrated:
The master switch 4 on portable detector is opened, radiator fan 5 is started to work, miniature integrated near infrared spectrometer
Low-power consumption bluetooth module 30 in 11 automatically turns on, and opens the inspection software being mounted on intelligent mobile terminal 8, and intelligent mobile is whole
The bluetooth and the low-power consumption bluetooth module in integrated micro near infrared spectrometer 11 at end 8 carry out pairing connection, by cherry kind to be measured
Eggplant is placed on profiling rubber gasket 3, clicks the scan button in inspection software operation interface, obtains cherry and tomato near infrared spectrum
The corresponding spectroscopic data of characteristic wavelength is transferred to intelligent mobile terminal 8 by Bluetooth communication, utilizes the detection mould of selection by data
Type detects the soluble solid content of cherry and tomato, and testing result is shown on 8 interface of intelligent mobile terminal.
Table 1
| Sample number into spectrum | Temperature (DEG C) | Measured value (Brix) | Predicted value (Brix) | Error |
| 1 | 8 | 8.2 | 8.03 | 0.17 |
| 2 | 12 | 5.9 | 6.01 | 0.11 |
| 3 | 15 | 7.1 | 7.2 | 0.1 |
| 4 | 20 | 7.5 | 7.28 | 0.22 |
| 5 | 23 | 6.8 | 6.95 | 0.15 |
| 6 | 25 | 8.2 | 8.18 | 0.02 |
| 7 | 29 | 7.9 | 7.69 | 0.21 |
| 8 | 30 | 6.4 | 6.27 | 0.13 |
| 9 | 33 | 7.3 | 7.24 | 0.06 |
| 10 | 35 | 7.9 | 8.09 | 0.19 |
As shown in table 1, using the portable detector, to 10 cherry and tomatos under different temperatures can
Dissolubility solid content is detected, and as can be seen from the table, error is smaller, shows that this device and method detection accuracy is higher,
And different detection temperature environments can be well adapted for.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " illustrative examples ",
The description of " example ", " specific example " or " some examples " etc. means specific features described in conjunction with this embodiment or example, knot
Structure, material or feature are included at least one embodiment or example of the invention.In the present specification, to above-mentioned term
Schematic representation may not refer to the same embodiment or example.Moreover, specific features, structure, material or the spy of description
Point can be combined in any suitable manner in any one or more of the embodiments or examples.
Although an embodiment of the present invention has been shown and described, it will be understood by those skilled in the art that: not
A variety of change, modification, replacement and modification can be carried out to these embodiments in the case where being detached from the principle of the present invention and objective, this
The range of invention is defined by the claims and their equivalents.
Claims (10)
1. a kind of portable detector, which is characterized in that the detection device includes shell (1), detection window (2), profiling
Rubber gasket (3), master switch (4), radiator fan (5), charging interface (6), battery capacity indication lamp (7), intelligent mobile terminal (8) and
Lithium battery (9), the power control circuit (10), miniature integrated near infrared spectrometer (11) being built in shell (1)；
The profiling rubber gasket (3) is fixed on the upper surface of shell (1), and center is overlapped with the center of detection window (2)；It is described
Master switch (4), radiator fan (5), charging interface (6), battery capacity indication lamp (7) are each attached on shell (1)；The master switch
(4), radiator fan (5), charging interface (6), battery capacity indication lamp (7), lithium battery (9), miniature integrated near infrared spectrometer (11)
It is all connected on power control circuit (10)；
The miniature integrated near infrared spectrometer (11) includes light source (12), slit (13), collimation lens (14), filter
(15), diffraction grating (16), condenser lens (17), dmd chip (18), collection len (19), single point detector (20), signal are put
Big device (21), AD converter (22), microprocessor (23), DMD controller (24), light source drive (25), temperature sensor
(26), humidity sensor (27), USB port (28), SD card connector (29), low-power consumption bluetooth module (30)；
Light source (12) projection light passed sequentially through after sample to be tested reflects slit (13), collimation lens (14), filter (15),
It gets on diffraction grating (16), diffraction grating (16) projects optical dispersion for the light of continuous wavelength, then line focus lens (17)
Dmd chip (18), the DMD controller (24) are connected with dmd chip (18) and microprocessor (23) respectively, control dmd chip
(18) the continuous light for obtaining Single wavelength of micro mirror rotation, acquired lens (19) reach single point detector (20) on, reach single-point and visit
The optical signal for surveying device (20) passes to microprocessor (23) by signal amplifier (21) and AD converter (22) output digit signals；
The light source drive (25) is connected with light source (12) and microprocessor (23) respectively；The temperature sensor (26), humidity
Sensor (27), USB port (28), SD card connector (29), low-power consumption bluetooth module (30) respectively with microprocessor (23) phase
Even.
2. a kind of portable detector according to claim 1, it is characterised in that: the profiling rubber gasket (3) uses
Food grade silicone is molded, and according to different test objects, the shape of profiling rubber gasket (3) can be adjusted.
3. a kind of portable detector according to claim 1, it is characterised in that: there are two halogen for light source (12) tool
Tungsten lamp, the operating power of tungsten halogen lamp are 1.4W, are placed in 40 ° of angles of level, and the sample in irradiation test, is adopted at an angle
Collection sample diffuses, while more light are directed to sample from filament and surveyed by the Front-end Design of light source (12) at form of lens
Try region.
4. a kind of portable detector according to claim 1, it is characterised in that: intelligent mobile terminal (8) tool
There is Bluetooth function, carries out Bluetooth pairing connection with the low-power consumption bluetooth module (30), intelligent mobile terminal (8) is micro- for controlling
Type integrates near infrared spectrometer (11) and acquires the near infrared spectrum of subject sample to be measured, while detecting to food to be measured, and
It will test as the result is shown on intelligent mobile terminal (8) interface, the result of detection is saved in intelligent mobile terminal (8).
5. a kind of portable detector according to claim 1, it is characterised in that: the temperature sensor (26) and wet
Degree sensor (27) is used to monitor the work temperature and humidity of miniature integrated near infrared spectrometer (11), and data of the Temperature and Humidity module passes through low-power consumption
Bluetooth module (30) passes to intelligent mobile terminal (8), and temperature and humidity is not in the working range of miniature integrated near infrared spectrometer (11)
When, bluetooth connection is disconnected automatically.
6. a kind of portable detector according to claim 1, it is characterised in that: the USB port (28) and power supply
Control circuit (10) is connected, for miniature integrated near infrared spectrometer (11) power supply；After low-power consumption bluetooth module (30) power supply certainly
It is dynamic to wake up.
7. a kind of food quality near infrared spectrum of portable detector described in -6 any one according to claim 1 is quick
Detection method, which comprises the following steps:
S1. food samples to be measured are placed on profiling rubber gasket (3)；
S2. the master switch (4) of device for opening, power supply device are device power supply, and the low-power consumption bluetooth module (30) in device is automatic
It wakes up；
S3. the inspection software being mounted on intelligent mobile terminal (8) is opened, passes through Bluetooth pairing with low-power consumption bluetooth module (30)
It is attached；
S4. inspection software is operated, control light source (12) transmitting optical signal projects food surface to be measured and enters inside, and then light passes through
It crosses diffusing reflection and is transferred to miniature integrated near infrared spectrometer (11), food near-infrared modal data to be measured is obtained, by the spy of model
The spectroscopic data levied under wavelength corresponds to passes through Bluetooth transmission to intelligent mobile terminal (8)；
S5. the substitution detection model of spectroscopic data obtained in S4 is obtained into food inspection Indexs measure to be measured as a result, as the result is shown
On the interface of intelligent mobile terminal (8).
8. the food quality near infrared spectrum rapid detection method of portable detector according to claim 7, special
Sign is, detection model in the S5 specifically: establishes and is affected by temperature the lesser food inspection based on near-infrared spectrum technique
Model is surveyed, including carrying out self-correcting to the spectroscopic data under different temperatures using a kind of temperature automatic correcting method and using self-correcting
The data of fiducial temperature establish model after just, model are implanted in the inspection software for being mounted on intelligent mobile terminal (8).
9. the food quality near infrared spectrum rapid detection method of portable detector according to claim 8, special
Sign is, a kind of temperature automatic correcting method the following steps are included:
S2.1. collecting sample near infrared spectrum in the case where different temperatures is horizontal；
S2.2. the spectrum matrix X=XP+XQ+R acquired, in which: P is the projection matrix of useful part, and Q is the throwing of nonuseable part
Shadow matrix, R are redundant matrices；
S2.3. difference spectrum matrix D: d is calculatedi=xi-xj, xiFor collecting sample spectrum mean value under a certain temperature levels, wherein i
=1,2 ... .p, p indicate p temperature levels, xjOn the basis of at a temperature of collecting sample spectrum mean value, wherein j be 1,2 ... p wherein
One of, difference spectrum matrix D is by diComposition；
S2.4. it calculates the covariance matrix of D, and carries out singular value decomposition, i.e. SVD (DTD)=USVT, U and V are respectively covariance
The left singular matrix and right singular matrix of matrix, S are diagonal matrix, the element on diagonal matrix be arrange from big to small it is unusual
Value；
S2.5. it takes the preceding c of V to arrange, obtains a subset V of V matrixs；
S2.6. nonuseable part projection matrix Q:Q=V is calculatedsVs T；
S2.7. calculating useful part projection matrix P:P=I-Q, I is unit matrix；
S2.8. all spectroscopic datas are projected into subspace P, the spectroscopic data after obtaining temperature self-correcting, X*=XP.
10. the food quality near infrared spectrum rapid detection method of portable detector according to claim 8, special
Sign is, establish model using the data of fiducial temperature after self-correcting the following steps are included:
S3.1. the near infrared spectrum of batch capture object samples to be measured；
S3.2. the spectrum matrix X after temperature self-correcting is corrected is carried out to obtained spectrum matrix X*, X*=XP；
S3.3. food inspection index physics and chemistry value to be measured is measured using standard method；
S3.4. remove obtained in S3.2 that near infrared spectrum data both ends noise is more, the lower spectroscopic data of signal-to-noise ratio, then
Carry out de-noising pretreatment；
S3.5. the physical and chemical value that will be measured in spectroscopic data combination S3.3 pretreated in S3.4, compares multiple spectrum characteristic wave
Long filtering algorithm；
S3.6. using the characteristic wavelength filtered out in S3.5, the quantitative mould of food inspection index is established using multivariate calibration methods
Type.
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