CN1696663A - Method for quick distinguishing and determining phytoplankton in red tide - Google Patents
Method for quick distinguishing and determining phytoplankton in red tide Download PDFInfo
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- CN1696663A CN1696663A CN 200510043621 CN200510043621A CN1696663A CN 1696663 A CN1696663 A CN 1696663A CN 200510043621 CN200510043621 CN 200510043621 CN 200510043621 A CN200510043621 A CN 200510043621A CN 1696663 A CN1696663 A CN 1696663A
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Abstract
A method for identifying red tide phytoplankton quickly includes collecting phytoplankton from Chinese east sea where red tide is frequently occurred and culturing them, measuring 3D fluorescent spectrum under condition of exciting wavelength at 200 - 600 nm and emitting wavelength at 200 - 800 nm, setting up original spectrobank after density is normalized, utilizing singular value decomposition method to eliminate interference factor for setting up characteristics spectrobank of fluorescent spectrum, using finally prepared spectrobank as a base to determine out kind and quantity of phytoplankton contained in measured sample.
Description
Technical field
The invention belongs to and utilize fluorometry to differentiate and measure the technical field of phytoplankton.
Background technology
Red tide mainly is meant under " improper " environmental baseline, and a certain or several specific harmful swim alga biomasss increase suddenly in a Dinghai District scope and assemble on extra large surface and make the ecological abnormal occurrence of discoloured water.Monitor and monitor the generation of harmful algal quickly and accurately, particularly phytoplankton species identification and takeoff in the red tide generating and vanishing process, be not only the condition precedent of prediction, the generation of forecast red tide, also be generation, development and the extinction rule of grasping the red tide disaster, and the important step of sea area phytoplankton population fluctuation and number change rule thereof take place in red tide.Fluorometry has advantages such as instrument is simple, highly sensitive, good stability, is suitable for on-the-spot fast monitored.Different phytoplanktons, its pigment is formed and the relative content difference, thereby show and have specific exciting-emitting fluorescence spectrum, like this according to the phytoplankton fluorescence spectral characteristic, can determine the kind recognition methods of phytoplankton, and the relation of or area and its quantity strong according to the emitting fluorescence characteristic peak can be determined its quantity.
At present phytoplankton classification and takeoff aspect obtain extensive concern to fluorescence analysis at the scene.The American Studies person is divided into five big classes, diatom, dinoflagellate, ballstone algae, brown alga and green alga according to the pigment ratio with the main marine phytoplankton of different waters.Cowles and Hoge etc. have inferred the variation that contains phycoerythrin phytoplankton species and abundance in the seawater by the displacement of in-site measurement phycoerythrin fluorescence emission spectrum wavelength.2002, M.Beutler and K.H.wiltshire etc. utilized two-dimensional fluorescence spectrum (ex=450,525,570,590,610; Em=685) phytoplankton is divided into four classes: blue-green algae, green alga, latent algae and mixed algae (diatom and dinoflagellate), realized Fast Classification monitoring to the phytoplankton class.In view of the above, Germany bbe-moldaenke company has made fluorescence algae analyser (Bbe Algae Analyzer), stored the characteristic fluorescence spectrum of four class phytoplanktons, utilize characteristic fluorescence spectrum to the phytoplankton monitoring of classifying, just can provide composition and the content of phytoplankton after several seconds, but bbe still can not distinguish diatom and dinoflagellate, and diatom and the dinoflagellate main phytoplankton species that is CHINESE OFFSHORE seems very important with dinoflagellate and diatom classification monitoring.
Summary of the invention
The purpose of this invention is to provide a kind of quick, sensitive phytoplankton in red tide and differentiate and assay method, can measure phytoplankton qualitative simultaneously, quantitatively, and be devoted to red tide algae diatom and dinoflagellate that CHINESE OFFSHORE is main and distinguish.
The present invention utilizes phytoplankton three-dimensional fluorescence spectrum and chemometrics method, the quick discriminating and the assay method of East Sea phytoplankton in red tide have been set up, its basic fundamental route is: gather the multiple district of East China Sea red tide marine phytoplankton sociales, phytoplankton in red tide and separation and Culture, use fluorospectrophotometer, under 200-600nm wavelength exciting light, measure the emission spectrum of its 200-800nm scope, after the density normalization, set up phytoplankton fluorescence spectrum original spectrum storehouse; Utilize principal component analytical method (svd) then, eliminate disturbing factor, extract the intrinsic characteristics of phytoplankton three-dimensional fluorescence spectrum, set up phytoplankton fluorescence spectral characteristic spectrum spectrum storehouse.Compose the storehouse based on this, split by the phytoplankton biased sample fluorescence spectrum of multiple regression analysis technology after to svd.Multiple regression analysis technology in this method is to adopt the non-negative least square method of traversal to return, its basic thought is: under given temperature conditions, each species is respectively got a spectrum formation design matrix from the characteristic spectrum storehouse at every turn, spectrum structure multiple linear regression model with potpourri, adopt non-negative least square to provide regression coefficient and residual error, travel through all combinations of characteristic spectrum between different plant species in the characteristic spectrum storehouse then, the pairing regression coefficient of combination of selecting the residual error minimum provides kind and the quantity of contained phytoplankton in institute's test sample product thus as split result.
Advantage of the present invention is directly to measure seawater sample, need not pre-treatment, in several minutes, provide classification and the quantity result of main phytoplankton fast.With similar technology leading in the world---the fluorescence algae analyser of German bbe-moldaenke company is compared, and the present invention can distinguish diatom and dinoflagellate, qualitative rate of accuracy reached to 76%.
Description of drawings
Fig. 1 is the original three-dimensional fluorescence spectrum figure of Alexandrium.
Fig. 2 is the original three-dimensional fluorescence spectrum figure of Isochrysis galbana.
Fig. 3 is the three-dimensional spectrum of Alexandrium after the removal Rayleigh scattering.
Fig. 4 is the three-dimensional spectrum of the Alexandrium of first principal component reconstruct.
Fig. 5 is the three-dimensional spectrum by the Alexandrium of preceding 2 major component reconstruct.
Fig. 6 is the feature spectrogram corresponding to emission spectrum of 13 algae kinds.
Fig. 7 is the feature spectrogram corresponding to excitation spectrum of 13 algae kinds.
Al when Fig. 8 is 25 ℃, Is, Pl, Pr, Ps, the characteristic spectrum DV1 of Sk.
Embodiment
Further specify the present invention below in conjunction with accompanying drawing and by instantiation.
One, fluorescence spectrometry
1. the laboratory cultures of phytoplankton
Phytoplankton sociales, the red tide kind phytoplankton (seeing Table 1) in the multiple district of selected 13 kinds of East China Sea red tides comprise: 3 kinds of dinoflagellates, 6 kinds in diatom, a kind of xanthophyta, 1 kind of blue-green algae, a kind of green alga, a kind of chrysophyceae, provide by 973 red tide project team, by biological expert appraisal purifying algae kind.
13 kinds of phytoplanktons that table 1 experiment is selected for use
No. algae kind (Species) belongs to (Genus) class (Division)
1 Alexandrium tamarense Alexandrium Pyrrophyta Dinophyta
Alexandrium?tamarense Alexandrium
Dictyocha Chrysophyta Chrysophyta such as 2 Isochrysis galbanas
Isochrysis?galbana Isochrysis
The big flat algae flat algae of 3 island countries belongs to Chlorophyta Chlorophyta
Platymonas?helgolanidica Platymonas
4 Prorocentrum donghaiense Prorocentrum Pyrrophyta Dinophyta
Prorocentrum?dentatum Prorocentrum
5 spine rhombus algae Nitzschia Bacillariophyta Bacillariophyta
Pseudo-nitzschia?pungens Pseudo-nitzschia
Skeletonemacostatum Skeletonema Bacillariophyta Bacillariophyta in 6
Skeletonema?costatuma Skeletonema
7 Nitzschia closterium minutissima Nitzschia Bacillariophyta Bacillariophyta
Nitzschia?closterium Nitzschia
8 revolve chain Chaetoceros Chaetoceros belongs to Bacillariophyta Bacillariophyta
Chaetoceros?curvisetus Chaetoceros
9 weak Chaetoceros Chaetoceros belong to Bacillariophyta Bacillariophyta
Chaetoceros?debilis Chaetoceros
10 pairs of prominent Chaetoceros Chaetoceros belong to Bacillariophyta Bacillariophyta
Chaetoceros?didymus Chaetoceros
11 unarmored dinoflagellate Gymnodinium Pyrrophyta Dinophyta
Gymnodinium?sp Gymnodinium
The different gulf of 12 Heterosigma akashiwo Heterosigma Trentepohlia Xanthophyta Dinophyta
akashiwo?Hada Heterosigma?akashiwo
13 Synechococcus gather born of the same parents' Trentepohlia Cyanophyta Cyanophyta
Synechococcus?sp. Synechococcus
2. phytoplankton and non-algae particle fluorescence spectral measuring experiment condition
Under a temperature, three illumination conditions, in the whole growth cycle (1-8 days), every day regularly before illumination sampling carry out spectral measurement, every kind of algae measurement finishes, and carries out the spectroscopic assay of mixed algae again.Twice of the parallel sampling and measuring of each sample.Spectrometry condition:
Hitachi F4500 fluorospectrophotometer, the quartzy colorimetric pool of 1cm.
◆ three-dimensional spectrum: excitation wavelength 200-600nm, excite step-length 5nm, emission wavelength 200-800nm, emission step-length 5nm excites slit 5nm, emission slit 5nm, sweep velocity 12000nm/min.
◆ definite (selection of the level and smooth degree of measurement data) of sweep spacing: three-dimensional spectrum sweep spacing, data break 5nm; Behind ASCII Text File (* .txt) data layout, in Matlab, transfer structure matrix (.mat) data type to.
Non-algae aerosol sample is measured the line data of going forward side by side and is handled under similarity condition.
Two, the foundation in phytoplankton fluorescence spectrum spectrum storehouse
1. phytoplankton three-dimensional fluorescence spectrum Study of Feature Extracting Method---svd
The spectral signature extracting method has multiple, and the method for principal component analysis (PCA) is use always a kind of.
Original three-dimensional fluorescence spectrum is owing to contain scattering effect such as Rayleigh scattering (as depicted in figs. 1 and 2, two big peaks on the left side are the Rayleigh scattering peak, the right be the Raman peaks of water, the characteristic absorption intensity of phytoplankton is less relatively), covered the intrinsic characteristics of spectrum, be not easy effectively to extract its spectral signature, if the method with principal component analysis (PCA) is extracted characteristic spectrum, after the svd, only utilize a few major component to express the intrinsic characteristics of spectrum far away, only get 30 more than the major component, substantially the intrinsic characteristics of the former spectrogram of reconstruct.
Choose the original 3D data upper right corner, emission wavelength 620-800nm, (be 85:121,45:81) sub-fraction can be lost bulk information again to excitation wavelength 420-600nm.Therefore, at first with zero setting such as Rayleigh scattered bands in 1872 original three-dimensional spectroscopic datas, the influence of having removed scattering effects such as Rayleigh scattering is carried out svd successively to the matrix after handling again.Get at every turn decompose obtain the first row V1 of the sub matrix first row U1 and loading matrix as candidate feature spectrum, the corresponding emission spectrum of U1, and V1 correspondence fluorescence excitation spectrum.1872 U1 that will obtain respectively divide the algae kind to come in turn with 1872 V1, form the matrix of two 1872 row 81 row, are designated as ERU1 and ERV1, its three-dimensional representation is seen Fig. 6 and Fig. 7, and sample number 1-144 is Al among the figure, and 145-288 is Is, 289-432 is Pl, and 433-576 is Pr, and 577-720 is Ps, 721-864 is Sk, and 865-1008 is Cl, and 1009-1152 is Cu, 1153-1296 is De, and 1297-1440 is Di, and 1441-1584 is Dy, 1585-1728 is Ha, and 1729-1872 is Sy.Obviously, the V1 character pair spectrum between different algae kinds has significant difference, and the spectral signature difference of U1 correspondence is not obvious.Further divide temperature to show as can be seen: Isochrysis galbana Is, big flat algae Pl of island country and middle Skeletonemacostatum Sk, inner spectrum similarity degree height of the same race; Alexandrium tamarense Al, Prorocentrum donghaiense Pr and spine rhombus algae Ps, inner spectral similarity of the same race is poor slightly.
We have further investigated the v1 that removes the capable svd of 95-99 of 3D data after the Rayleigh scattering, v2, u1, u2, the characteristic spectrum char_Dv1 of s12.Utilize this spectrum storehouse that test specimen is carried out discriminatory analysis, obtained ideal effect, this work is to split as characteristic spectrum with char_Dv1.
2. phytoplankton fluorescence spectrum similarity measurement
If spectrum is similar, then the spectrum measuring data matrix of He Binging is tending towards order 1, and its first singular value should be much larger than all the other singular values (second largest singular value).Thus, available second largest singular value is measured spectral similarity with the ratio S2/S1 (or first singular value accounts for the ratio S1/S of singular value summation) of first singular value.
Index: S2/S1, more little, spectral similarity is high more.
3. the foundation in phytoplankton standard fluorescence spectrum spectrum storehouse
The selection of 3-1 three-dimensional fluorescence spectrum characteristic spectrum
Through relatively, according to the principle of " high as far as possible with algae kind similarity degree, the similarity degree of different algae kinds is low as far as possible ", we select for use the major component char_Dv1 that removes the capable svd of 95-99 of 3D data after the Rayleigh scattering as characteristic spectrum.Following fractionation work promptly is to utilize this characteristic spectrum.
Al when Fig. 8 is 25 ℃, Is, Pl, Pr, Ps, the characteristic spectrum DV1 of Sk, per 1 algae kind 8 days has 3 illumination, so 24 spectrums are arranged.1-24 is the characteristic spectrum of Al among the figure, and 25-48 is the characteristic spectrum of Is, and 49-72 is the characteristic spectrum of Pl, and 73-96 is the characteristic spectrum of Pr, and 97-120 is the characteristic spectrum of Ps, and 121-144 is the characteristic spectrum of Sk.
3-2 standard fluorescence spectrum is composed the thinking of setting up in storehouse
(1) spectrum storehouse: the characteristic spectrum of depositing pure species three-dimensional fluorescence spectrum.Normal conditions, every kind of algae has 3 standard fluorescence spectrum, is respectively the common trait of characteristic spectrum under three temperature.The algae kind that the spectrum similarity degree is high under the various conditions, as Is, Pl, Sk can have only 1 standard fluorescence spectrum; The algae kind internal similarity difference that has, as Al, Ps etc. can refinement deposit 9 standard fluorescence spectrum.
(2) coding key: Al000
Species represented in the front two letter,
The 3rd bit digital representation temperature, 0 represents spectrum temperature independent, and 1 represents 25 ℃, and 2 represent 20 ℃, and 3 represent 15 ℃;
4-digit number is represented illumination, and on behalf of spectrum and light intensity, 0 have nothing to do, and 1 represents 7000Lux, and 2 represent 4000Lux, and on behalf of 1410Lux, 3 hang down light intensity;
Five digit number is represented growth period, and on behalf of spectrum and growth period, 0 have nothing to do, and 1 represents initial period, and 2 represent exponential phase; 3 represent the stage of stable development; 4 represent decline phase;
For example: Al210 represents 20 ℃, the standard fluorescence spectrum of Al during 7000Lux.
Three, phytoplankton fluorescence spectrum method for splitting research
The analysis of phytoplankton species and quantity belongs to " black analysis system ", promptly all knows nothing for the algae kind number and the concentration range thereof that contain in the seawater sample.The task of analytical chemistry is at first to determine its species number, and then parses the spectrogram of each pure species, carries out quantitative test then.In theory, be difficult to obtain unique the separating of physical significance by the method for polynary resolution.Therefore we count n by the given possible species of elder generation, just can draw unique separating.Provide below the non-negative least square method of traversal (NNLS) the fractionation algorithm, and analysis result discussed.
1. data set and structure thereof
(1) characteristic spectrum of pure " species " spectrum storehouse: normalized characteristic spectrum spectrum storehouse char_Dv1.mat is designated as A1.
5 dimension structure collection data sets are deposited the D category feature spectrum of 13 algae kinds in 3 thermogrades, 3 illumination gradients, different growing stages (8 days), and 144 spectrums of each algae kind amount to 1872.Every spectrum is the first principal component of 95-99 row matrix after removing the Rayghlei scattering effect.
(2) characteristic spectrum of potpourri spectrum storehouse: BLS.mat
3 dimension structure data sets are deposited the D category feature of 210 compound samples and are composed and relevant information, amount to 210.
The method of extracting according to the characteristic spectrum of pure " species ", can produce potpourri characteristic spectrum matrix blendDvl, blendDvlm and blending ratio matrix B LSinfo with batch, temperature, growth period information battle array BLScond, wherein blendDvlm is the mixture D category feature spectrum matrix that contains light intensity quantity.
(3) biological counting result data collection cellnum
Biological counting and the linear fitting parameter data set of spectrum storehouse intensity cellnusm.
2. based on the fractionation algorithm of the non-negative least square method of the traversal of characteristic spectrum library searching (NNLS)
(1) characteristic spectrum of taking-up article one potpourri from potpourri eigenmatrix blendDvlm is designated as y;
(2) in normalized characteristic spectrum spectrum storehouse, from the spectrum storehouse of each " species ", extract the representative spectrum that " species " are somebody's turn to do in a conduct, be designated as x
1, x
2... x
n, n is the species number, structure y and x
1, x
2... x
n, regression model:
y＝c
0+c
1x
1+c
2x
2+…+c
nx
n+ε
At constraint c
i〉=0 (i=1,2 ... under condition n), utilize non-negative least-squares algorithm, provide (c
1, c
2... c
n) estimated result, and return residual sum of squares (RSS).
(3) x is composed in the representative of extracting each species in the A1 of characteristic spectrum storehouse again
1', x
2' ... x
n', constitute new regression model with y, give the parameter estimation result (c that makes new advances
1, c
2... c
n) and new residual sum of squares (RSS).Traversal is given all linear combinations of the characteristic spectrum of next each species of fixed temperature, with the combination corresponding parameters estimated result (c of residual sum of squares (RSS) minimum
1, c
2... c
n) as optimal result---" spectrum peak split result ".
(4) with " spectrum peak split result " (area) summation normalization, must compose peak scale-up factor result; Filtering is less than the coefficient (putting 0) of given threshold value, and by the linear fit parametrization data of biology counting with light intensity, the biology of inverting correspondence is counted estimated result.
(5) from potpourri characteristic spectrum matrix, take off a spectrum as y, repeated for 2,3,4 steps, split result that must all potpourris.
3. the species number determines and the principle that splits accuracy
Determining of species number: in the fractionation algorithm of the non-negative least square method of above-mentioned traversal (NNLS), whether surpass a certain given threshold value with normalized spectrum peak coefficient ratio and determine to split species, promptly utilize spectrum peak (light intensity) contribution to determine the species number.
The standard spectrum that 13 algaes and non-algae particle are arranged in the standard spectrum storehouse, it is that belong to together and be a class to revolve these three kinds of chain Chaetoceros, weak Chaetoceros, two prominent Chaetoceros, obtains the standard spectrogram of 12 " species ".Split the accuracy principle:
◆ in the fractionation ratio result of a mixed spectrum, if the ratio of certain species correspondence is more than or equal to given threshold value, and do not exist in the original stock, then this spectrum splits failure, otherwise is counted as merit;
◆ when all split coefficient all less than given threshold value, then split the first principal component existence of coefficient maximum, calculate correct;
◆ dinoflagellate Al, it is right that Pr and Gy are judged to mutually, diatom Ps, Sk, Cl, Cu, it is right that De, Di are judged to mutually.
About splitting the explanation of accuracy principle: preceding two are correctly based on the major component separation of copulating moth, and back one to be based on separately promptly to be the breakthrough leading in the world that utilizes direct, the quick Measuring Oceanic phytoplankton of photometry with dinoflagellate and diatom.
4. split result
Laboratory mixed algae sample split result: utilize the non-negative least square method of above-mentioned traversal that 210 samples in laboratory are split, split with normalized characteristic spectrum peak, threshold value is 0.25, and obtaining accuracy is 41%.According to actual conditions, it is right that dinoflagellate is judged to mutually, and it is right that diatom is judged to mutually, and splitting accuracy is 76%.Wherein, 2 species mix, and 134 samples are arranged, and accuracy is 72%, and wherein dinoflagellate, diatom mix 39 samples, and accuracy is 89%.3 species mix, and 46 samples are arranged, and accuracy is 82%.4 species or more species mix, and 30 samples are arranged, and accuracy is 87%.
Claims (6)
1. the quick discriminating and the assay method of a phytoplankton in red tide may further comprise the steps:
(1) sets up phytoplankton fluorescence spectrum original spectrum storehouse;
(2) intrinsic characteristics of extraction phytoplankton fluorescence spectrum is set up phytoplankton fluorescence spectral characteristic spectrum spectrum storehouse;
(3) phytoplankton biased sample fluorescence spectrum is split;
(4) split result and characteristic spectrum storehouse are compared, provide kind and the quantity of contained phytoplankton in institute's test sample product.
2. method according to claim 1 is characterized in that described phytoplankton fluorescence spectrum original spectrum storehouse is is 200-600nm in excitation wavelength, and emission wavelength is to measure three-dimensional fluorescence spectrum in the 200-800nm scope, sets up after the density normalization.
3. method according to claim 1 is characterized in that the intrinsic characteristics of described extraction phytoplankton three-dimensional fluorescence spectrum is to utilize principal component analytical method.
4. method according to claim 1 is characterized in that described phytoplankton biased sample fluorescence spectrum is split is to take the multiple regression analysis technology.
5. method according to claim 4 is characterized in that described multiple regression analysis technology is to adopt the non-negative least square method of traversal.
6. method according to claim 1 or 5, it is characterized in that adopting in the fractionation algorithm of the non-negative least square method of traversal is whether to surpass a certain given threshold value with normalized spectrum peak coefficient ratio to determine to split the species number.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103868901A (en) * | 2014-03-14 | 2014-06-18 | 中国科学院合肥物质科学研究院 | Discrete three-dimensional fluorescence spectrum-based phytoplankton identification and measurement method and discrete three-dimensional fluorescence spectrum-based phytoplankton identification and measurement device |
| CN105334198A (en) * | 2015-11-14 | 2016-02-17 | 常州大学 | Method for analyzing DOMs (dissolved organic matters) in water on basis of three-dimensional fluorescence spectra |
| CN108780047A (en) * | 2018-04-13 | 2018-11-09 | 深圳达闼科技控股有限公司 | The detection method and relevant apparatus and computer readable storage medium of material composition |
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2005
- 2005-05-20 CN CN 200510043621 patent/CN1696663A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103868901A (en) * | 2014-03-14 | 2014-06-18 | 中国科学院合肥物质科学研究院 | Discrete three-dimensional fluorescence spectrum-based phytoplankton identification and measurement method and discrete three-dimensional fluorescence spectrum-based phytoplankton identification and measurement device |
| CN105334198A (en) * | 2015-11-14 | 2016-02-17 | 常州大学 | Method for analyzing DOMs (dissolved organic matters) in water on basis of three-dimensional fluorescence spectra |
| CN108780047A (en) * | 2018-04-13 | 2018-11-09 | 深圳达闼科技控股有限公司 | The detection method and relevant apparatus and computer readable storage medium of material composition |
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