CN105241822A - Measurement method of content of anthocyanin in leaves of peony on the basis of hyperspectrum - Google Patents
Measurement method of content of anthocyanin in leaves of peony on the basis of hyperspectrum Download PDFInfo
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- Y02A40/10—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture
Abstract
The invention discloses a measurement method of content of anthocyanin in leaves of peony on the basis of hyperspectrum and belongs to the technical field of lossless monitoring of crop growth information in precision agriculture. The measurement method includes the following steps: fusing reflection spectrum data of leaves of peony with anthocyanin content data; determining a sensitive waveband of the anthocyanin content through correlation analysis; establishing an anthocyanin content spectrum monitoring model based on characteristic wavebands in selected software; measuring the reflection spectrum data in the characteristic wavebands of the peony leaves through a hyperspectrum radiometer; introducing the data into the spectrum monitoring model; and calculating the content of the anthocyanin in the peony leaves. The measurement method, compared with a wet chemical method in the prior art, has following advantages: 1) the method is free of sampling due to on-site measurement, so that the peony leaves are free of damage; 2) the method allows repeated measurement, thereby achieving long-time monitoring; and 3) all effective waveband information being sensitive to the content of anthocyanin are employed, so that the prediction model is high in accuracy and is especially suitable for quickly and accurately estimating the peony leaves being medium or low in content of the anthocyanin.
Description
Technical field
The present invention relates to a kind of peony leaves sheet anthocyanidin content assay method based on EO-1 hyperion, belong to plant growth information lossless monitoring technical field in precision agriculture.
Background technology
In plant leaf blade, pigment content change can not only reflect growth and the nutrition condition of plant, and also can reflect the response of plant to envirment factor, therefore leaf pigment is one of parameter the most often measured in plant research.Anthocyanidin is water miscible flavone compound, and it is the 3rd class primary pigments in pigment in plant leaf, rich content in the immature and ageing leaves of plant.Anthocyanidin can the luminous environment of reblading, has the ability regulating photosynthesis restriction Xanthophyll cycle and photobleaching potentially, and the defence capability to photo damage.Anthocyanidin as osmotic adjustment, can improve the freezing and drought-resistant ability of coercing of Genes For Plant Tolerance.In addition, anthocyanidin also has antioxidation, contributes to the blade after repairing damage.Anthocyanidin is the indicator that plant leaf blade is old and feeble and coerce, and detects and qualitative assessment it, can obtain the important information that plant responds environment-stress and adjusts.
Traditional anthocyanidin content measures and mainly adopts wet chemistry method, and comprise with anthocyanidin in solvent extraction blade, spectrophotometric determination anthocyanidin absorbance in a solvent, converts the absorbance of mensuration the steps such as to anthocyanidin content.The method can the content of anthocyanidin in Accurate Determining blade, but it is large to there is labour intensity, measures time-consuming, effort, needs to destroy blade, can not carry out the problem such as original position duplicate measurements and large regions monitoring.Therefore, a kind of accurate, efficient, practical anthocyanidin content assay method is needed badly.There are some researches show, within the scope of green light band, anthocyanidin content and spectral reflectivity are pole significant correlation, and along with the increase of anthocyanidin content, near 550nm, green reflection rate obviously reduces.Build the spectrum monitoring model of inverting anthocyanidin based on this association, will quick, the non-destructive determination of plant leaf blade anthocyanidin content be conducive to.For peony plant, in florescence, the anthocyanidin content of different cultivars tree peony blade differs greatly, and anthocyanidin content is relatively low, and laboratory measurement is wasted time and energy.At present, the peony leaves sheet anthocyanidin mensuration based on EO-1 hyperion monitoring model have not been reported.
Summary of the invention
The object of this invention is to provide a kind of peony leaves sheet anthocyanidin content assay method based on EO-1 hyperion, the method is simple, efficient, practical, and accuracy is high, in being applicable to, original position, the non invasive estimation of low content anthocyanidin tree peony blade.
In order to realize above object, the technical solution adopted in the present invention is:
Based on the peony leaves sheet anthocyanidin content assay method of EO-1 hyperion, step is as follows: adopt EO-1 hyperion radiation gauge to measure the reflected spectrum data of tree peony blade at characteristic wave bands, the reflected spectrum data recorded is substituted in anthocyanidin content spectrum monitoring model, calculates the anthocyanidin content of tree peony blade.
The foundation of described anthocyanidin content spectrum monitoring model comprises the following steps:
1) sampling and data acquisition
Choose multiple tree peony blade, measure anthocyanidin content and the reflected spectrum data of each tree peony blade respectively, reflected spectrum data is resampled to 1nm again, and by it according to the sequence of anthocyanidin content size, forms a data set;
2) characteristic wave bands is determined
Do correlation analysis to the anthocyanidin content of data centralization and reflected spectrum data, related coefficient is greater than 0.52 and the wave band that two-tailed test reaches the pole level of signifiance is defined as characteristic wave bands;
3) modeling & VVA
Utilize the reflected spectrum data of anthocyanidin content and characteristic wave bands to set up anthocyanidin content spectrum monitoring model, test mould, to obtain final product.
Step 1) in measure anthocyanidin content can adopt this area conventional method, preferred 0.1mol/L hydrochloric acid methanol low temperature lixiviate spectrophotometric method, step is as follows: the tree peony blade of fragmentation is placed in 0.1mol/L hcl acidifying methyl alcohol (often liter methyl alcohol containing 0.1molHCl) lixiviate (as lixiviate 2 times at 45 DEG C, each lixiviate 2h), the complete centrifuging and taking supernatant of lixiviate (or merging supernatant), spectrophotometric determination supernatant (or after supernatant constant volume solution) is in the optical density value of certain wave strong point, (specific wavelength gets 530nm to calculate anthocyanidin content in tree peony blade, 620nm, during 650nm, computing method are see Xiong Qinge, Ye Zhen, Yang Shimin, Deng. plant physiology experiment study course [M]. Chengdu: Sichuan science tech publishing house, 2003:94-95).
Step 1) in measure reflected spectrum data can adopt EO-1 hyperion radiation gauge, as the SVCHR-1024i portable spectrometer that SpectraVista company of the U.S. produces, band value 350 ~ 2500nm, spectral resolution≤the 3.5nm of 350 ~ 1000nm wave band, spectral resolution≤the 9.5nm of 1000 ~ 1850nm wave band, the spectral resolution≤6.5nm of 1850 ~ 2500nm wave band.
Step 1) in the reflected spectrum data of the preferred 350 ~ 1000nm wave band of resampling, this is because anthocyanidin is mainly to ultraviolet, visible light wave range response, its all band can not be done to consider.
Step 2) in correlation analysis can adopt Bivariate analysis in SPSS software.
Step 2) in characteristic wave bands be 510 ~ 585nm.
Step 3) in modeling, test that mould adopts data centralization 2/3 (calibration set) respectively, 1/3 (checking collection) data are carried out.
Step 3) in set up anthocyanidin content spectrum monitoring model and can adopt the softwares such as Unscrambler9.7, Matlab, SAS or SPSS.Preferably, in Unscrambler9.7, adopt PLSR method (partial least squares regression) to set up calibration model, leave one cross validation, adopt multiple correlation coefficient (R simultaneously
2), cross validation related coefficient (R
2), root-mean-square error (RMSE) and prediction residual deviation (RPD) evaluation model, meet coefficient of multiple correlation R
2> 0.8, cross validation coefficient of multiple correlation R
2when > 0.8, RMSE < 0.07 μm of ol/g, RPD > 2, model construction is suitable.Meanwhile, adopt the Stability and veracity of independent sample inspection verification model, evaluation index selects multiple correlation coefficient (R
2), root-mean-square error (RMSE) and prediction residual deviation (RPD), meet R
2model construction success when > 0.8, RMSE < 0.07 μm of ol/g, RPD > 2.
Beneficial effect of the present invention:
Peony leaves sheet anthocyanidin content assay method based on EO-1 hyperion in the present invention is simple, efficient, practical, and accuracy is high, in particularly suitable, original position, the non invasive estimation of low content anthocyanidin blade.The method is merged mutually with anthocyanidin content data tree peony blade reflected spectrum data, by the sensitive band of correlation analysis determination anthocyanidin, the anthocyanidin content spectrum monitoring model of feature based wave band is built in selected software, EO-1 hyperion radiation gauge is adopted to measure the reflected spectrum data of tree peony blade to be measured at characteristic wave bands again, by in data importing spectrum monitoring model, calculate peony leaves sheet anthocyanidin content.Compared with existing wet chemistry method, there is following advantage: 1) in-site detecting, do not need sampling, to tree peony blade not damaged; 2) can replication, reach the object of long term monitoring; 3) utilize all significant wave segment informations to anthocyanidin content sensitivity, precision of forecasting model is high, can realize to peony leaves sheet anthocyanidin content quick, accurately estimate.
Accompanying drawing explanation
Fig. 1 is the structure schematic flow sheet of peony leaves sheet anthocyanidin content spectrum monitoring model in embodiment 1;
Fig. 2 is scatter diagram and the matched curve of anthocyanidin content predicted value and measured value.
Embodiment
Embodiment 1
Based on the peony leaves sheet anthocyanidin content assay method of EO-1 hyperion in the present embodiment, comprise the following steps:
One, peony leaves sheet anthocyanidin content spectrum monitoring model (schematic flow sheet is shown in Fig. 1) is set up
1) sampling and high-spectral data collection
At the beginning of certain 4 months year in certain university peony garden, bloom in tree peony (PaeoniaSuffruticosa) and gather the tree peony blade of 14 different cultivars early stage, each kind collection at least 3 blades, the SVCHR-1024i portable spectrometer adopting SpectraVista company of the U.S. to produce gathers (band value 350 ~ 2500nm, spectral resolution≤the 3.5nm of 350 ~ 1000nm wave band, spectral resolution≤the 9.5nm of 1000 ~ 1850nm wave band, the spectral resolution≤6.5nm of 1850 ~ 2500nm wave band; Utilize automatic light source type Manual blades spectral detector directly to measure Spectra of The Leaves, light source is built-in halogen tungsten lamp; The front diffuse reflection reference plate of each mensuration optimizes instrument) reflected spectrum data, each Blade measuring 3 positions, each position measurement 1 spectrum, every tree peony measures 3 blades totally 9 spectrum, calculate the mean value of 9 spectrum, and (reflected spectrum data of 350 ~ 1000nm wave band is chosen in resampling to be resampled to 1nm to the reflected spectrum data after average value processing, this is because anthocyanidin is mainly to ultraviolet, visible light wave range response, its all band can not be done to consider), as a sample spectrum, gather 132 sample spectrum altogether;
2) blade anthocyanidin content measures and data prediction
The anthocyanidin content of each blade of Simultaneous Determination, corresponding, every tree peony measures 3 blades, calculate the mean value of 3 blade anthocyanidin contents, one group of sample data is designated as with above-mentioned sample spectrum, by many groups sample data of obtaining according to the ascending sequence of anthocyanidin content, form a data set, as shown in table 1 below;
Table 1 peony leaves sheet anthocyanidin content and spectroscopic data (part)
The assay method of anthocyanidin content is: get tree peony blade and wash impurity elimination, blot, be cut into 2 × 5mm strip fragment, accurately take 0.15g, add 0.1mol/L hcl acidifying methyl alcohol 10mL, lixiviate 2 times at 45 DEG C, extraction time is 2h, centrifuging under 5000r/min after lixiviate, merge 2 centrifuged supernatant, filter, obtain anthocyanidin extract, extract is settled to 50mL, after spectrophotometric determination constant volume, the optical density value of anthocyanidin extract under 530nm, 620nm, 650nm wavelength, calculates anthocyanidin content in tree peony blade;
3) in SPSS software, Bivariate analysis is done to the anthocyanidin content of data centralization and reflected spectrum data, the related coefficient of result display 510 ~ 585nm wave band is greater than 0.52 and two-tailed test reaches the pole level of signifiance, therefore selects 510 ~ 585nm wave band to be characteristic wave bands;
4) modeling & VVA
Choose the data of 2/3 as calibration set in data centralization, the data of 1/3, as checking collection, adopt PLSR method to set up calibration model, leave one cross validation, adopt coefficient of multiple correlation R simultaneously in Unscrambler9.7 software
2, cross validation coefficient R
2, root-mean-square error RMSE and prediction residual deviation RPD evaluation model, the major component of selection is 4, the R of calibration model
2be 0.873, the R of cross validation
2be that 0.857, RMSE and RPD is respectively 0.067 μm of ol/g and 2.512; Adopt the Stability and veracity of independent sample inspection verification model, evaluation index is: coefficient of multiple correlation R simultaneously
2be 0.811, root-mean-square error RMSE be 0.068 μm of ol/g, prediction residual deviation RPD be 2.352; To predict that anthocyanidin content is horizontal ordinate, (see following formula a), Fig. 2 is shown in the scatter diagram of anthocyanidin content predicted value and measured value and matched curve to actual measurement anthocyanidin content for ordinate sets up regression equation;
Formula a:y=0.916x+0.016, R
2=0.817;
In formula, the intercept of regression equation and slope are comparatively close to 0 and 1, illustrate that the prediction effect of this single band model is better;
Two, peony leaves sheet anthocyanidin content measures
The SVCHR-1024i portable spectrometer adopting SpectraVista company of the U.S. to produce measures the reflected spectrum data of tree peony blade to be measured at 510 ~ 585nm characteristic wave bands, the reflected spectrum data recorded is imported in Unscrambler9.7 software, directly call above-mentioned monitoring model, calculate the anthocyanidin content of tree peony blade, see the following form 2.
The anthocyanidin content (part) of table 2 tree peony blade spectroscopic data and prediction, actual measurement
In the present embodiment, the Stability and adaptability of peony leaves sheet anthocyanidin content spectrum monitoring model is good, and accuracy is high, in particularly suitable, original position, the non invasive estimation of low content anthocyanidin blade.
Claims (7)
1. based on the peony leaves sheet anthocyanidin content assay method of EO-1 hyperion, it is characterized in that: step is as follows: adopt EO-1 hyperion radiation gauge to measure the reflected spectrum data of tree peony blade at characteristic wave bands, the reflected spectrum data recorded is substituted in anthocyanidin content spectrum monitoring model, calculates the anthocyanidin content of tree peony blade;
The foundation of described anthocyanidin content spectrum monitoring model comprises the following steps:
1) sampling and data acquisition
Choose multiple tree peony blade, measure anthocyanidin content and the reflected spectrum data of each tree peony blade respectively, reflected spectrum data is resampled to 1nm again, and by it according to the sequence of anthocyanidin content size, forms a data set;
2) characteristic wave bands is determined
Do correlation analysis to the anthocyanidin content of data centralization and reflected spectrum data, related coefficient is greater than 0.52 and the wave band that two-tailed test reaches the pole level of signifiance is defined as characteristic wave bands;
3) modeling & VVA
Utilize the reflected spectrum data of anthocyanidin content and characteristic wave bands to set up anthocyanidin content spectrum monitoring model, test mould, to obtain final product.
2. assay method according to claim 1, it is characterized in that: step 1) in measure the method for anthocyanidin content and be: the tree peony blade of fragmentation is placed in the lixiviate of 0.1mol/L hcl acidifying methyl alcohol, the complete centrifuging and taking supernatant of lixiviate, measure supernatant in the optical density value of certain wave strong point, calculate anthocyanidin content in tree peony blade.
3. assay method according to claim 1, it is characterized in that: step 1) middle mensuration reflected spectrum data employing EO-1 hyperion radiation gauge, band value 350 ~ 2500nm, spectral resolution≤the 3.5nm of 350 ~ 1000nm wave band, spectral resolution≤the 9.5nm of 1000 ~ 1850nm wave band, the spectral resolution≤6.5nm of 1850 ~ 2500nm wave band.
4. assay method according to claim 3, is characterized in that: step 1) in resampling choose the reflected spectrum data of 350 ~ 1000nm wave band.
5. assay method according to claim 1, is characterized in that: step 2) in characteristic wave bands be 510 ~ 585nm.
6. assay method according to claim 5, it is characterized in that: step 3) in set up anthocyanidin content spectrum monitoring model and carry out in Unscrambler9.7 software, partial least-squares regression method is adopted to set up calibration model, leave one cross validation, model-evaluation index is: coefficient of multiple correlation R
2> 0.8, cross validation coefficient of multiple correlation R
2> 0.8, RMSE < 0.07 μm of ol/g, RPD > 2.
7. assay method according to claim 6, is characterized in that: step 3) in test mould adopt independent sample inspection, evaluation index is: R
2> 0.8, RMSE < 0.07 μm of ol/g, RPD > 2.
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| CN105954206A (en) * | 2016-04-29 | 2016-09-21 | 北京市农林科学院 | Method for measuring anthocyanin content of purple corn blades, and system thereof |
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| CN106323880A (en) * | 2016-07-29 | 2017-01-11 | 河南科技大学 | Plant leaf anthocyanin content estimation method and device based on SOC hyperspectral index |
| CN109406419A (en) * | 2018-10-31 | 2019-03-01 | 北京中研百草检测认证有限公司 | Method based on P-hydroxybenzoic acid content in high light spectrum image-forming technology prediction fructus lycii |
| CN111650130A (en) * | 2020-03-05 | 2020-09-11 | 广州地理研究所 | Prediction method and prediction system for magnesium content of litchi leaves |
| CN111795932A (en) * | 2020-06-15 | 2020-10-20 | 杭州电子科技大学 | Hyperspectrum-based nondestructive testing method for sugar acidity of waxberry fruits |
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Cited By (8)
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| CN105954206A (en) * | 2016-04-29 | 2016-09-21 | 北京市农林科学院 | Method for measuring anthocyanin content of purple corn blades, and system thereof |
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| CN106323880A (en) * | 2016-07-29 | 2017-01-11 | 河南科技大学 | Plant leaf anthocyanin content estimation method and device based on SOC hyperspectral index |
| CN109406419A (en) * | 2018-10-31 | 2019-03-01 | 北京中研百草检测认证有限公司 | Method based on P-hydroxybenzoic acid content in high light spectrum image-forming technology prediction fructus lycii |
| CN111650130A (en) * | 2020-03-05 | 2020-09-11 | 广州地理研究所 | Prediction method and prediction system for magnesium content of litchi leaves |
| CN111795932A (en) * | 2020-06-15 | 2020-10-20 | 杭州电子科技大学 | Hyperspectrum-based nondestructive testing method for sugar acidity of waxberry fruits |
| CN111795932B (en) * | 2020-06-15 | 2022-11-15 | 杭州电子科技大学 | Hyperspectrum-based nondestructive testing method for sugar acidity of waxberry fruits |
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