CN108572154A - A method of quickly detecting peach juice Normal juice content based on near-infrared spectrum technique - Google Patents
A method of quickly detecting peach juice Normal juice content based on near-infrared spectrum technique Download PDFInfo
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- 235000013944 peach juice Nutrition 0.000 title claims abstract description 92
- 238000000034 method Methods 0.000 title claims abstract description 60
- 235000011389 fruit/vegetable juice Nutrition 0.000 title claims abstract description 37
- 238000002329 infrared spectrum Methods 0.000 title claims abstract description 30
- 235000006040 Prunus persica var persica Nutrition 0.000 claims abstract description 72
- 244000144730 Amygdalus persica Species 0.000 claims abstract description 69
- 235000012907 honey Nutrition 0.000 claims abstract description 64
- 238000004445 quantitative analysis Methods 0.000 claims abstract description 31
- 238000000862 absorption spectrum Methods 0.000 claims abstract description 18
- 238000004611 spectroscopical analysis Methods 0.000 claims abstract description 7
- 238000012937 correction Methods 0.000 claims description 13
- 238000004458 analytical method Methods 0.000 claims description 11
- 230000009466 transformation Effects 0.000 claims description 7
- 238000004497 NIR spectroscopy Methods 0.000 claims description 6
- 238000003756 stirring Methods 0.000 claims description 6
- 230000009514 concussion Effects 0.000 claims description 4
- 238000002360 preparation method Methods 0.000 claims description 4
- 239000000047 product Substances 0.000 claims description 4
- 239000006228 supernatant Substances 0.000 claims description 4
- 239000012153 distilled water Substances 0.000 claims description 3
- 238000011156 evaluation Methods 0.000 claims description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical compound O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 3
- 238000001228 spectrum Methods 0.000 claims description 2
- 235000013361 beverage Nutrition 0.000 abstract description 7
- 238000013459 approach Methods 0.000 abstract description 4
- 238000001514 detection method Methods 0.000 description 5
- 238000009826 distribution Methods 0.000 description 5
- 235000013399 edible fruits Nutrition 0.000 description 4
- 235000013305 food Nutrition 0.000 description 4
- 240000005809 Prunus persica Species 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
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- 235000015203 fruit juice Nutrition 0.000 description 3
- 238000004128 high performance liquid chromatography Methods 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 239000010453 quartz Substances 0.000 description 3
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 3
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- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 description 1
- 235000010254 Jasminum officinale Nutrition 0.000 description 1
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- 239000002253 acid Substances 0.000 description 1
- 208000007502 anemia Diseases 0.000 description 1
- 235000015197 apple juice Nutrition 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
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- 238000004364 calculation method Methods 0.000 description 1
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- 229910052799 carbon Inorganic materials 0.000 description 1
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- 229920002678 cellulose Polymers 0.000 description 1
- 239000003153 chemical reaction reagent Substances 0.000 description 1
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- 235000019634 flavors Nutrition 0.000 description 1
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- 238000002290 gas chromatography-mass spectrometry Methods 0.000 description 1
- 230000002496 gastric effect Effects 0.000 description 1
- 239000008103 glucose Substances 0.000 description 1
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 description 1
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- 229910052742 iron Inorganic materials 0.000 description 1
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- 235000009018 li Nutrition 0.000 description 1
- 239000002932 luster Substances 0.000 description 1
- 238000001819 mass spectrum Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000008267 milk Substances 0.000 description 1
- 210000004080 milk Anatomy 0.000 description 1
- 235000013336 milk Nutrition 0.000 description 1
- 229910052757 nitrogen Inorganic materials 0.000 description 1
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- 238000003860 storage Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
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- 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
- G01N21/3577—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing liquids, e.g. polluted water
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- 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
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Abstract
The present invention relates to a kind of methods quickly detecting peach juice Normal juice content based on near-infrared spectrum technique.Step S1, spectroscopic data is obtained：Honey peach peach juice sample is subjected near infrared spectrum scanning, obtains the near-infrared absorption spectrum of honey peach peach juice sample；Step S2, model is established：It is pre-processed according to the near-infrared absorption spectrum of the honey peach peach juice sample obtained in step S1, Quantitative Analysis Model is then established using Partial Least Squares PLS；Step S3, unknown honey peach peach juice sample is predicted：Using the model established in step S2, the peach juice quality of unknown honey peach peach juice sample is predicted.The present invention provides a kind of easy, quick, lossless new method for the quantitative analysis of Normal juice content in peach juice beverage, and a kind of new approaches are provided for Rapid identification peach juice quality.
Description
Technical field
The present invention relates to a kind of methods quickly detecting peach juice Normal juice content based on near-infrared spectrum technique.
Background technology
Peach heat and acid sweet in flavor, contain abundant nutritive value.There is the effect of benefiting qi and nourishing blood, Xie Laore, quench one's thirst of promoting the production of body fluid.
In addition, peach can increase gastrointestinal peristalsis, and its iron-holder is higher containing more organic acid and cellulose, can auxiliary treatment lack
Iron anaemia.And peach is easy with its result morning, high efficiency, management, becomes the forestry plantation project quickly grown in recent years.
It is counted according to FAO (Food and Agriculture Organization of the United Nation), for the current cultivated area of China peach up to 6,000,000 mu, more than 300 ten thousand tons of annual output, is world peach fruit
First big producer[1].Short in view of ripe peach fruit storage period, most of peaches are made into peach juice and are sold.Currently, market
Sold peach juice beverage is mostly peach juice.It is squeezed however, peach juice is more difficult in real production process, commercially available peach juice is caused to be drunk
Expect that Normal juice content difference is larger, peach juice quality is irregular.Therefore, the detection and analysis of commercially available peach juice are most important.Currently, detection
The conventional method of fruit juice quality mainly has atomic absorption spectrophotometer（Atomic absorption
Spectrophotometer, AAS）[2], gas chromatography-mass spectrum technology (Gas Chromatography-Mass
Spectrometer, GC-MS) [3], high performance liquid chromatography（High performance liquid chromatography,
HPLC）[4]Deng although these method testing results are accurate, the above method needs complicated pretreatment, and time-consuming, testing cost
The shortcomings of expensive.It would therefore be highly desirable to develop more quick, easy, cheap, accurate analysis sides for being suitable for peach juice Quality Detection
Method.
Near infrared spectrum（Near Infrared Spectroscopy, NIRs）Analytical technology have it is efficient, take it is short,
It is environmentally protective, can online non-destructive testing the advantages that, mainly pass through detect sample to be tested hydric group（X-H, X are：C, O, N, S
Deng）The characteristic information of chemical bond (X-H) vibration, rotation of stretching vibration frequency multiplication and sum of fundamental frequencies etc. near infrared band, it has also become
The effective tool for identifying active constituent content etc. in food quality, analysis food, is widely used in camellia oil[5], milk[6]、
Honey[7-8], cider[9]Etc. Quality Detections.However, due to fruit juice constituents complexity, near infrared spectrum overlapping is serious, therefore limits
Application of the near-infrared spectrum technique in terms of fruit juice quartile length.
In consideration of it, utilizing near-infrared spectrum technique combination Partial Least Squares herein（Partial Least Squares,
PLS）Peach Normal juice content in peach juice beverage is analyzed, a kind of determining for Normal juice content quickly, in non-destructive determination peach juice beverage is established
Quantity measuring method has good reference value in practical applications.
Invention content
The purpose of the present invention is to provide a kind of method quickly detecting peach juice Normal juice content based on near-infrared spectrum technique,
A kind of easy, quick, lossless new method is provided for the quantitative analysis of Normal juice content in peach juice beverage, is Rapid identification peach juice
Quality provides a kind of new approaches.
To achieve the above object, the technical scheme is that：One kind quickly detecting peach juice based on near-infrared spectrum technique
The method of Normal juice content, includes the following steps：
Step S1, spectroscopic data is obtained：Honey peach peach juice sample is subjected near infrared spectrum scanning, obtains honey peach peach juice sample
Near-infrared absorption spectrum；
Step S2, model is established：Located in advance according to the near-infrared absorption spectrum of the honey peach peach juice sample obtained in step S1
Reason, then establishes Quantitative Analysis Model using Partial Least Squares PLS；
Step S3, unknown honey peach peach juice sample is predicted：Using the model established in step S2, unknown honey peach peach juice sample is predicted
The peach juice quality of product.
In an embodiment of the present invention, in the step S1, Fourier Transformation Near-Infrared Spectroscopy Analysis instrument is to juicy peach
Juice sample carries out near infrared spectrum scanning, sets scanning range as 10000 ~ 4000 cm-1, resolution ratio is 16 cm-1, Mei Geshui
Honey peach peach juice Sample Scan 3 times, takes its average value as the near-infrared absorption spectrum of honey peach peach juice sample.
In an embodiment of the present invention, the honey peach peach juice sample is the different honey peach of honey peach Normal juice mass fraction
Peach juice sample.
In an embodiment of the present invention, the preparation method of the honey peach peach juice sample is：First, honey peach sample is washed
Net stoning, and be cut into fragment and be put in blender, it is stirred 10-15 minutes with 20000 revs/min of rotating speed, through gauze mistake after stirring
Filter 3 times, takes supernatant to be placed in beaker for use；Then, divide with a series of contained honey peach Normal juice quality of distilled water mixed preparing
Different 20 samples of number, i.e., the quality of honey peach peach juice Normal juice is respectively in each sample：5,10,15,20,25,30,35,
40,45,50,55,60,65,70,75,80,85,90,95,100g, concussion shakes up, and each sample is 100g；Randomly select 10
It is a to do calibration set, remaining 10 collection that give a forecast.
In an embodiment of the present invention, in the step S2, the near-infrared absorption spectrum of honey peach peach juice sample is carried out
Pretreated method includes：Multiplicative scatter correction, standard normal variable transformation, the smooth single order of SG convolution, the smooth second order of SG convolution,
Standardization.
In an embodiment of the present invention, in the step S2, Quantitative Analysis Model is being established using Partial Least Squares PLS
Later, it also needs to be used as and built using correction root-mean-square error, predicted root mean square error, correction related coefficient, prediction related coefficient
The evaluation index of vertical Quantitative Analysis Model is carried out with the most suitable near-infrared absorption spectrum to honey peach peach juice sample of determination
Pretreated method, to establish optimal Quantitative Analysis Model.
In an embodiment of the present invention, in the step S2, using the Quantitative Analysis Model of Partial Least Squares PLS foundation
For from the Quantitative Analysis Model of the % of the 0 % ~ 100 Normal juice various concentration gradients of peach juice containing honey peach.
Compared to the prior art, the invention has the advantages that：The present invention is that Normal juice content is determined in peach juice beverage
Amount analysis provides a kind of easy, quick, lossless new method, and a kind of new approaches are provided for Rapid identification peach juice quality.
Description of the drawings
Fig. 1 is the atlas of near infrared spectra of various concentration peach juice.
Fig. 2 is the pretreated near infrared spectrum of distinct methods：(a) Raw (b) 1st (c) 2st (d) SNV (e)
MSC (f) Nor。
Fig. 3 is the predicted value of the PLS models under different pretreatments and true Distribution value：(a) Raw (b) 1st
(c) 2st (d) SNV (e) MSC (f) Nor。
Specific implementation mode
Below in conjunction with the accompanying drawings, technical scheme of the present invention is specifically described.
The present invention provides a kind of method quickly detecting peach juice Normal juice content based on near-infrared spectrum technique, including it is as follows
Step：
Step S1, spectroscopic data is obtained：Honey peach peach juice sample is subjected near infrared spectrum scanning, obtains honey peach peach juice sample
Near-infrared absorption spectrum；
Step S2, model is established：Located in advance according to the near-infrared absorption spectrum of the honey peach peach juice sample obtained in step S1
Reason, then establishes Quantitative Analysis Model using Partial Least Squares PLS；
Step S3, unknown honey peach peach juice sample is predicted：Using the model established in step S2, unknown honey peach peach juice sample is predicted
The peach juice quality of product.
In the step S1, Fourier Transformation Near-Infrared Spectroscopy Analysis instrument carries out near infrared spectrum to honey peach peach juice sample
Scanning, sets scanning range as 10000 ~ 4000 cm-1, resolution ratio is 16 cm-1, each honey peach peach juice Sample Scan 3 times,
Take its average value as the near-infrared absorption spectrum of honey peach peach juice sample.
The honey peach peach juice sample is the different honey peach peach juice sample of honey peach Normal juice mass fraction.The honey peach
The preparation method of peach juice sample is：First, honey peach sample is cleaned into stoning, and is cut into fragment and is put in blender, with 20000
Rev/min rotating speed stir 10-15 minutes, through filtered through gauze 3 times after stirring, supernatant is taken to be placed in beaker for use；Then, with steaming
A series of 20 different samples of contained honey peach Normal juice mass fractions of distilled water mixed preparing, i.e., honey peach peach juice in each sample
The quality of Normal juice is respectively：5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,
100g, concussion shake up, and each sample is 100g；It randomly selects 10 and does calibration set, remaining 10 collection that give a forecast.
In the step S2, carrying out pretreated method to the near-infrared absorption spectrum of honey peach peach juice sample includes：It is more
First scatter correction, standard normal variable transformation, the smooth single order of SG convolution, the smooth second order of SG convolution, standardization.
In the step S2, after establishing Quantitative Analysis Model using Partial Least Squares PLS, also need equal using correction
Square error, predicted root mean square error, correction related coefficient, prediction related coefficient are commented as the Quantitative Analysis Model established
Valence index carries out pretreated method, to build with the most suitable near-infrared absorption spectrum to honey peach peach juice sample of determination
Found optimal Quantitative Analysis Model.
In the step S2, use the Quantitative Analysis Model that Partial Least Squares PLS is established for from the aqueous honey of the % of 0 % ~ 100
The Quantitative Analysis Model of peach peach juice Normal juice various concentration gradient.
It is the specific implementation process of the present invention below.
1, instrument and reagent
Fourier Transformation Near-Infrared Spectroscopy Analysis instrument（II types of ANTARIS, Thermo companies）；10 mm quartz colorimetric utensils；MATLAB
（R2013a）；N/D, color and luster be good, immaculate honey peach（Local market is purchased）.
2, sample preparation
Honey peach sample is cleaned into stoning, and is cut into fragment and is put in blender, with 20000 revs/min of 10-15 points of rotating speed stirring
Clock takes supernatant to be placed in beaker for use through filtered through gauze 3 times after stirring.Prepare a series of contained honey peach Normal juice quality point
20 different samples of number, i.e., each sample（100 g）The quality of middle peach Normal juice is respectively：5,10,15,20,25,30,35,
40,45,50,55,60,65,70,75,80,85,90,95,100g, concussion shakes up, spare.
3, the acquisition of spectroscopic data
This experiment near infrared spectrum data uses the II type Fourier Transform Near Infrareds of ANTARIS that Thermo companies produce
Analyzer acquires, which is furnished with high sensitivity InGaAs detectors, built-in automatic goldleaf background acquisition mode and configuration sample
Cup circulator and quartz specimen cup integration sphere light source system.Prepared peach juice solution to be measured is contained using 10 mm quartz colorimetric utensils,
Survey its 10000 ~ 4000 cm-1Near infrared spectrum data in range, resolution ratio are 16 cm-1, each sample scans 3 times, takes it
Near-infrared absorption spectrum of the average value as sample, the results are shown in Figure 1 for spectroscopic data.It is to measure background with air, in room temperature
Lower measurement, air humidity are controlled in 65 %, and quantitative analysis is carried out with PLS.The data obtained is in Matlab (R2013a）Middle progress
Analyzing processing.
4, data prediction
The factors such as the granular size of sample to be tested itself, the uniformity of sample interior structure, sample self stability, with close red
It can have a certain impact to result when external spectrum result of calculation.Meanwhile the factors such as noise when instrument detection sample itself can drop
The effective information of the near-infrared spectrogram of low gained sample.For lowering apparatus inherently factor and sample to be tested oneself factor to institute
The influence for building accuracy, stability of Quantitative Analysis Model etc. needs first to use highly selective method near infrared spectrum number
According to being pre-processed, corresponding Quantitative Analysis Model is established on this basis.
To make data preferably present, the present invention optimizes data using 5 kinds of different preprocess methods, respectively
Multiplicative scatter correction（Multiplicative scatter correction, MSC）, standard normal variable change（standard
Normal variate, SNV）, the smooth single order of SG convolution（Savitzky-Golay first-derivative, 1st）, SG volumes
The smooth second order of product（Savitzky-Golay second derivative, 2st）, standardization（Normalize, Nor).Through locating in advance
As shown in Fig. 2, wherein Fig. 2 a are data without any pretreated artwork, Fig. 2 b are through 1st methods for data spectrogram after reason
It is pre-processed, Fig. 2 c are pre-processed through 2st methods, and Fig. 2 d are pre-processed through SNV methods, and Fig. 2 e are through the side MSC
Method is pre-processed, and Fig. 2 f are pre-processed through Nor methods.Can intuitively it be found out by 1st by Fig. 2（Fig. 2 b）And 2st（Figure
2c）Pretreated spectrogram is more compared to the burr that other preprocess methods occur, this is because using differential process, signal
While being amplified, noise is also amplified[7]。
5, the foundation of Quantitative Analysis Model
In the Quantitative Analysis Model for establishing near infrared spectrum, PLS is most common data analysing method.PLS analysis methods are beaten
Broken traditional quantitative analytical model, the method for modular form and the method for cognitive-ability are combined, and realize regression modeling and data structure letter
The organic unity of change.For more preferable, more intuitively evaluation model generalization ability, herein mainly using correction root-mean-square error
（Root mean squared error of calibration, RMSEC）, predicted root mean square error（Root Mean
Square Errors of Prediction, RMSEP), correction related coefficient（Correlation Coefficient of
Calibration, Rc）, prediction related coefficient（Correlation Coefficient of Prediction, Rp）As mould
The value of the evaluation index of type, wherein Rp and Rc is bigger, while RMSEP, RMSEC value are smaller, and performance is higher.PLS is used herein
Method carries out quantitative analysis to data, it is intended to find optimum regression curve, establish from the % of 0 % ~ 100 Normal juice containing peach juice various concentration ladder
The Quantitative Analysis Model of degree.
Prepared 20 peach juice samples are randomly selected 10 and do calibration set, remaining 10 collection that give a forecast, for quantitative
The foundation of analysis model.The model that peach juice is established after pretreated is as shown in figure 3, predicted value is distributed in tiltedly with actual value
When on the straight line that rate is 1, show that predicted value is almost identical as actual value, gained model is best, and predictablity rate is close to 100 %.
Middle predicted value and the distribution situation of actual value understand b according to fig. 3, and f distributions are best, and c distributions are worst, almost de- with straight line
From.
Numerical values recited for the preprocess method for selecting best, the present invention Rp, Rc, RMSEP, RMSEC is predicted to weigh
The quality of value and actual value distribution situation, as shown in table 1.From the data in the table, by standardizing pretreated data most
Good, Rp, Rc, RMSEP, RMSEC numerical value is respectively 0.9988,0.9973,0.0140,0.0212.In contrast, by 2st
Data after pretreated are worst, are not suitable for the foundation of peach juice model.
6, it summarizes
The present invention carries out spectral scan by the near-infrared spectrometers sample different to honey peach Normal juice content, then uses
5 kinds of distinct methods are pre-processed, and establish Quantitative Analysis Model using Partial Least Squares, and model is verified with reference to multiple parameters
Accuracy.Result of study shows that the Quantitative Analysis Model that data are established after being pre-processed according to standardization is most steady, Rp, Rc,
RMSEP, RMSEC respectively reach 0.9988,0.9973,0.0140,0.0212, and predicted value is almost identical as actual value.Therefore, originally
Text provides a kind of easy, quick, lossless new method for the quantitative analysis of Normal juice content in peach juice beverage, is Rapid identification peach
Juice quality provides a kind of new approaches.
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35(4):14-16.
[2]Williams AB, Ayejuyo OO, Ogunyale AF. Trace metal levels in fruit
juices and carbonated beverages in Nigeria[J]. Environmental monitoring and
assessment, 2009, 156(1-4): 303-306.
[3] Kang Mingli, Pan Siyi, Fan Gang, wait HS-SPME-GC-MS methods measure differing maturity mandarin orange fruit juice volatility at
Divide ［ J ］ food industry science and technology, 2014,35 (19): 326-330.
[4]Pei M, Huang X. Determination of trace phenolic acids in fruit juice
samples using multiple monolithic fiber solid-phase microextraction coupled
with high-performance liquid chromatography[J]. Analytical Methods, 2016, 8
(18): 3831-3838.
[5] grandson is logical, Wei little Mei, Hu Tian, Xu Wenli, and Liu Mu China visible/near infrared combination MIA variables are preferably and support
Vector machine differentiation camellia oil produces mode [J] food industry science and technology, 2014, 35(20): 62-65.
[6]Moser JK, Singh M, Rennick KA, et al. Detection of Corn Adulteration
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Spectroscopy[J]. Journal of Agricultural & Food Chemistry, 2015.
[7] Chen Lan treasure honey qualities near infrared spectrum assessment technique research [D] the Chinese Academy of Agricultural Sciences, 2010.
[8] Ding Jiaxin, Zhang Qiuhai, Japanese plum jasmine, Liu Hong applications near infrared spectroscopies quickly measure glucose and fruit in honey
Sugared content [J] spectroscopy and spectrum analysis, 2016, (S1).
[9]Ying Li, Yajing Guo, Chang Liu, et al. SPA combined with swarm
intelligence optimization algorithms for wavelength variable selection to
rapidly discriminate the adulteration of apple juice. Food Analytical
Methods, 2017, 10, 1965-1971。
The above are preferred embodiments of the present invention, all any changes made according to the technical solution of the present invention, and generated function is made
When with range without departing from technical solution of the present invention, all belong to the scope of protection of the present invention.
Claims (7)
1. a kind of method quickly detecting peach juice Normal juice content based on near-infrared spectrum technique, which is characterized in that including walking as follows
Suddenly：
Step S1, spectroscopic data is obtained：Honey peach peach juice sample is subjected near infrared spectrum scanning, obtains honey peach peach juice sample
Near-infrared absorption spectrum；
Step S2, model is established：Located in advance according to the near-infrared absorption spectrum of the honey peach peach juice sample obtained in step S1
Reason, then establishes Quantitative Analysis Model using Partial Least Squares PLS；
Step S3, unknown honey peach peach juice sample is predicted：Using the model established in step S2, unknown honey peach peach juice sample is predicted
The peach juice quality of product.
2. a kind of method quickly detecting peach juice Normal juice content based on near-infrared spectrum technique according to claim 1,
It is characterized in that, in the step S1, Fourier Transformation Near-Infrared Spectroscopy Analysis instrument carries out near infrared light to honey peach peach juice sample
Spectrum scanning, sets scanning range as 10000 ~ 4000 cm-1, resolution ratio is 16 cm-1, each honey peach peach juice Sample Scan 3
It is secondary, take its average value as the near-infrared absorption spectrum of honey peach peach juice sample.
3. a kind of method quickly detecting peach juice Normal juice content based on near-infrared spectrum technique according to claim 1 or 2,
It is characterized in that, the honey peach peach juice sample is the different honey peach peach juice sample of honey peach Normal juice mass fraction.
4. a kind of method quickly detecting peach juice Normal juice content based on near-infrared spectrum technique according to claim 1 or 2,
It is characterized in that, the preparation method of the honey peach peach juice sample is：First, honey peach sample is cleaned into stoning, and be cut into broken
Block is put in blender, is stirred 10-15 minutes with 20000 revs/min of rotating speed, through filtered through gauze 3 times after stirring, supernatant is taken to set
It is for use in beaker；Then, 20 samples different from a series of contained honey peach Normal juice mass fractions of distilled water mixed preparing,
The quality of honey peach peach juice Normal juice is respectively in i.e. each sample：5,10,15,20,25,30,35,40,45,50,55,60,65,
70,75,80,85,90,95,100g, concussion shakes up, and each sample is 100g；It randomly selects 10 and does calibration set, residue 10
A collection that gives a forecast.
5. a kind of method quickly detecting peach juice Normal juice content based on near-infrared spectrum technique according to claim 1,
It is characterized in that, in the step S2, carrying out pretreated method to the near-infrared absorption spectrum of honey peach peach juice sample includes：It is more
First scatter correction, standard normal variable transformation, the smooth single order of SG convolution, the smooth second order of SG convolution, standardization.
6. a kind of method quickly detecting peach juice Normal juice content based on near-infrared spectrum technique according to claim 5,
It is characterized in that, in the step S2, after establishing Quantitative Analysis Model using Partial Least Squares PLS, also needs using correction
Root-mean-square error, predicted root mean square error, correction related coefficient, prediction related coefficient are as the Quantitative Analysis Model established
Evaluation index carries out pretreated method with the most suitable near-infrared absorption spectrum to honey peach peach juice sample of determination, to
Establish optimal Quantitative Analysis Model.
7. a kind of method quickly detecting peach juice Normal juice content based on near-infrared spectrum technique according to claim 1,
It is characterized in that, in the step S2, uses the Quantitative Analysis Model that Partial Least Squares PLS is established to be aqueous from the % of 0 % ~ 100
The Quantitative Analysis Model of honey peach peach juice Normal juice various concentration gradient.
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