CN104677878A - Nitrogen nutrition environment monitoring method based on Raman spectra technique in combination with microalgae grease peaks - Google Patents
Nitrogen nutrition environment monitoring method based on Raman spectra technique in combination with microalgae grease peaks Download PDFInfo
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- CN104677878A CN104677878A CN201510042258.2A CN201510042258A CN104677878A CN 104677878 A CN104677878 A CN 104677878A CN 201510042258 A CN201510042258 A CN 201510042258A CN 104677878 A CN104677878 A CN 104677878A
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Abstract
The invention discloses a nitrogen nutrition environment monitoring method based on a Raman spectra technique in combination with microalgae grease peaks. The method comprises the following steps: (1) obtaining the Raman spectra original information of a living chlorella pyrenoidosa sample under different nitrogen nutrition statuses by use of a Raman spectrometer; (2) preprocessing the obtained Raman spectra original information to obtain a preprocessed spectrogram, and extracting Raman strength values corresponding to a plurality of spectra peaks in the spectrogram, including the Raman strength values at 1442cm-1, 1301cm-1 and 1270cm-1; (3) establishing a judgment model with the Raman strength values of the corresponding microalgae characteristic peaks as inputs and the different nitrogen nutrition statuses as outputs; (4) taking a living algae liquid to be monitored, obtaining the corresponding Raman strength values by virtue of the processing in the step (1) and the step (2) and inputting the values into the judgment model, thereby obtaining the nitrogen nutrition status of the algae liquid to be monitored. With the method disclosed by the invention, the problems that in the existing detection method, a sample needs to be subjected to dyeing or complicated chemical treatment, so that the operation is complicated, and wastes time and labor are solved.
Description
Technical field
The present invention relates to micro algae growth environmental monitoring technology field, particularly relate to a kind of based on the nitrogen nutrition method of environmental monitoring of Raman spectroscopy in conjunction with microalgae grease peak.
Background technology,
The bioactive molecule of micro-algae to be a class can be by carbon dioxide conversion potential bio-fuel, food, feed and high value also can carry out photosynthetic eukaryotic microorganisms.Micro-algae has ecology and biological value, is a kind of important biomass resource.
Chlorella is a class monoplast green alga, belongs to Chlorophyta, Chlorophyceae (Chlorophyceae), Chlorococcale, Ruan Nang algae section, Chlorella, is distributed widely in nature, most species in freshwater.The known chlorella of current global range has about 15 kinds, and has the mutation of nearly more than hundred kinds.Chlorella cells shape is generally spherical or elliposoidal, diameter 2-12 μm.There are some researches show, chlorella is containing rich in protein, lipid, polysaccharide, dietary fibre, vitamin, trace element and active metabolite.In recent years, China has started the exploitation paying attention to chlorella.In sum, chlorella has important economy and scientific research value, has broad application prospects.
Raman spectrum is a kind of scattering spectrum, it is a kind of spectrographic technique of research molecular vibration, its principle is different from infrared spectrum with mechanism, and infrared spectrum has very strong Detection capability to polar group, and non-polar group such as C=C, C-C etc. then have very strong Raman active.But the structural information that they provide is similar, all about the various molecular vibrational frequency of intramolecule and the situation about vibrational energy level, so the difference on sample chemical composition and molecular structure can be reflected from molecular level, realize " fingerprint verification " of some chemical bond and functional group in molecule.The Raman scattering of water is very faint in addition produces undesired signal hardly, makes the Non-Destructive Testing of the living body biological of Raman in research aqueous solution has the incomparable advantage of other molecular spectrums.
Summary of the invention
The invention provides a kind of based on the nitrogen nutrition method of environmental monitoring of Raman spectroscopy in conjunction with microalgae grease peak, solving existing detection method needs to dye to sample or the chemical treatment of complexity, operates problem that is relatively loaded down with trivial details, consuming time, effort.Raman spectrum strength value easily passes generation decomposition etc. in time impact by micro-algae Different growth phases, different exposure time and pigment is overcome by carrying out pre-service to the Raman signal collected.
Based on the nitrogen nutrition method of environmental monitoring of Raman spectroscopy in conjunction with microalgae grease peak, comprise the following steps:
(1) adopt Raman spectrometer, obtain the Raman spectrum raw information of live body algae fluid samples under different nitrogen nutrition state;
(2) pre-service is carried out to the Raman spectrum raw information obtained in step (1), obtain pre-service spectrogram, extract the raman scattering intensity value that in spectrogram, multiple spectrum peak is corresponding;
(3) using the raman scattering intensity value in step (2) as input, different nitrogen nutrition state, as output, sets up the discrimination model based on multivariate regression algorithm;
(4) get live body algae liquid to be monitored, input described discrimination model by the raman scattering intensity value at this live body algae liquid characteristic peak place of process of step (1) and step (2), obtain the nitrogen nutrition state of algae liquid to be monitored.
In the present invention, Raman spectrometer specifically selects Reinshaw microscopic confocal Raman spectrometer, when carrying out information acquisition to sample, all carries out under constant temperature (about 25 DEG C) condition.
In step (1), by the algae drop that makes on microslide, flatten (avoiding producing bubble) with cover glass, then to be fixed on below micro-Raman spectroscopy object lens on objective table, utilize the laser beam that laser intensity is 1mv, and focused on the surface of sample by the object lens of 50X, time shutter 1s, obtain described Raman spectrum raw information.Meanwhile, considering that object of classification is the micro-algae of live body, because the problems such as sample drift or sampled point easily move easily appear in the micro-algae sample of live body when gathering, agar need be adopted to be fixed to the algae liquid on microslide.
In step (2), described pre-service be carry out successively smoothing processing, baseline correction and normalized.
Because original Raman is larger by fluorescence interference, the generation of fluorescence can cover the signal of Raman, therefore first adopt method that is level and smooth and baseline correction to remove the interference of fluorescence, highlight signal, and smoothly and baseline correction process all based on the software WIRE3.3 that Raman spectrometer is subsidiary.Normalized, mainly passing to eliminate micro-algae Different growth phases, different exposure time and pigment the impact producing decomposition etc. in time, adopting software unscrambler 9.7 to realize.
In the present invention, described live body algae fluid samples is chlorella pyrenoidosa.Because this algae kind fat content is higher, the impact easily by environment nitrogen accumulates certain lubricant component, observes under the Individual Size of algae is adapted at microscopic Raman simultaneously.
In described step (3), described multivariate regression algorithm is partial least-squares regression method algorithm, principal component regression algorithm, the Stepwise Regression Algorithm, artificial neural network algorithm, algorithm of support vector machine or LDA model, and preferred multivariate regression algorithm is LDA model.The basic thought of LDA discriminatory analysis is that the pattern sample of higher-dimension is projected to best discriminant technique vector space, to reach the effect extracting classified information and compressive features space dimensionality, after projection, Assured Mode sample has maximum between class distance and minimum inter-object distance in new subspace, and namely pattern has best separability within this space.Therefore, it is a kind of effective Feature Extraction Method.
In step (1) and step (4), nitrogen nutrition state comprises 1/4 nitrogen in micro algae growth process, 1/2 nitrogen, normal nitrogen, 2 times of nitrogen, 4 times of nitrogen.The cultivation of algae generally adopts normal nitrogen to cultivate, and nitrogen nutrition, for experiment purpose, is carried out gradient setting by this research, simultaneously in conjunction with actual cultivation conditions, gradient is set to above-mentioned a few class.
Compared with prior art, beneficial effect of the present invention is:
Present invention achieves based on the nitrogen nutrition method of environmental monitoring of Raman spectroscopy in conjunction with microalgae grease peak, do not need to prepare any solution and chemical assay, enormously simplify operation steps, shorten detection time, it also avoid because operating personnel operate the consequences such as measurement result that unskilled or subjective factor brings is inaccurate.Raman spectrum strength value easily passes generation decomposition etc. in time impact by micro-algae Different growth phases, different exposure time and pigment is overcome by being normalized Raman signal.
Accompanying drawing explanation
Fig. 1 is the original Raman spectrogram of chlorella pyrenoidosa sample under different nitrogen nutrition state.
Fig. 2 is the Raman spectrogram after chlorella pyrenoidosa sample preprocessing under different nitrogen nutrition state.
Embodiment
The present invention is explained further below in conjunction with specific embodiment.
Get the chlorella pyrenoidosa sample under normal nitrogen nutritional status, adopt Reinshaw microscopic confocal Raman spectrometer (inVia – Reflex 532/XYZ), obtain the Raman spectrum raw information of live body algae fluid samples.The algae drop being about to make, on microslide, flattens (avoid produce bubble) with cover glass, and adopts agar to be fixed algae sample, to be then fixed on below micro-Raman spectroscopy object lens on objective table.Wherein the time shutter is set to 1s, and laser intensity is 1mv, and cumulative number once.Whole experimentation all carries out under constant temperature (about 25 DEG C) condition.The original Raman line of (1/4 nitrogen, 1/2 nitrogen, 2 times of nitrogen, 4 times of nitrogen) chlorella pyrenoidosa sample under adopting above-mentioned method to gather different nitrogen nutrition state respectively, as shown in Figure 1.
Because original Raman spectrogram is comparatively large by fluorescence interference, the generation of fluorescence can cover the signal of Raman, therefore first adopts method that is level and smooth and baseline correction to remove the interference of fluorescence, highlights signal.These two kinds of pretreated processes all realize in software WIRE3.3, then adopt normalized easily to pass to overcome raman spectrum strength value the impact producing decomposition etc. in time by micro-algae Different growth phases, different exposure time and pigment, realized by software unscrambler 9.7.Fig. 2 is the Raman spectrogram of chlorella pyrenoidosa sample after pre-service.
Linear discriminant analysis (LDA) is a kind of supervised subspace learning technology, is the conventional statistics instrument of feature extraction and classification, is now widely used in computer vision, pattern-recognition and machine learning.LDA seeks a kind of linear transformation, makes to maximize with covariance in class between class after the conversion, and finds differentiation conversion (matrix) distance by maximizing between class distance and minimizing in class.The present invention gathers the Raman spectrum of chlorella pyrenoidosa under different nitrogen nutrition state, by extracting raman scattering intensity value corresponding to grease characteristic peak as input, sets up the discrimination model of different nitrogen nutrition state in conjunction with LDA.
Above-mentioned pre-service is carried out to 75 algae fluid samples, then adopts LDA to set up the discrimination model of different nitrogen nutrition state, wherein 1/4 nitrogen, 1/2 nitrogen, normal nitrogen, 2 times of nitrogen, 4 times of nitrogen are demarcated as " 1 ", " 2 ", " 3 ", " 4 " and " 5 " respectively.Each 10 samples of random selecting above-mentioned nitrogen nutrition state are used for modeling, and 5 samples are used for prediction.Pretreated Raman spectrum is extracted it at 1442cm
-1, 1301cm
-1and 1270cm
-1the raman scattering intensity value that the grease peak located is corresponding, using them as input variable, need the nitrogen nutrition classification judged as output, the sample number of training set is 50, and forecast sample collection is 25 sample numbers, and the differentiation rate obtaining model is 92%.
Different nitrogen nutrition state respectively has 5 forecast samples, for each forecast sample, Reinshaw microscopic confocal Raman spectrometer is adopted to obtain the Raman spectrum raw information of each sample, and to Raman spectrum raw information successively smoothing process, baseline correction and normalized, obtain corresponding pre-service spectrogram, then extract 1442cm
-1, 1301cm
-1and 1270cm
-1the raman scattering intensity value at grease peak place, is inputted LDA model, and the precision obtaining forecast sample is 76%.
Claims (9)
1., based on the nitrogen nutrition method of environmental monitoring of Raman spectroscopy in conjunction with microalgae grease peak, it is characterized in that, comprise the following steps:
(1) adopt Raman spectrometer, obtain the Raman spectrum raw information of live body algae fluid samples under different nitrogen nutrition state;
(2) pre-service is carried out to the Raman spectrum raw information obtained in step (1), obtain pre-service spectrogram, extract the raman scattering intensity value that in spectrogram, multiple spectrum peak is corresponding;
(3) using the raman scattering intensity value in step (2) as input, different nitrogen nutrition state, as output, sets up the discrimination model based on multivariate regression algorithm;
(4) get live body algae liquid to be monitored, input described discrimination model by the raman scattering intensity value at this live body algae liquid characteristic peak place of process of step (1) and step (2), obtain the nitrogen nutrition state of algae liquid to be monitored.
2. as claimed in claim 1 based on the nitrogen nutrition method of environmental monitoring of Raman spectroscopy in conjunction with microalgae grease peak, it is characterized in that, in step (1), by the algae drop that makes on microslide, flatten with cover glass, to be then fixed on below micro-Raman spectroscopy object lens on objective table, utilize the laser beam that laser intensity is 1mv, and focused on the surface of sample by the object lens of 50X, time shutter 1s, obtain described Raman spectrum raw information.
3. as claimed in claim 2 based on the nitrogen nutrition method of environmental monitoring of Raman spectroscopy in conjunction with microalgae grease peak, it is characterized in that, adopt agar to be fixed to the algae liquid on microslide.
4. as claimed in claim 1 based on the nitrogen nutrition method of environmental monitoring of Raman spectroscopy in conjunction with microalgae grease peak, it is characterized in that, in step (2), described pre-service be carry out successively smoothing processing, baseline correction and normalized.
5. as claimed in claim 1 based on the nitrogen nutrition method of environmental monitoring of Raman spectroscopy in conjunction with microalgae grease peak, it is characterized in that, described live body algae fluid samples is chlorella pyrenoidosa.
6. as claimed in claim 6 based on the nitrogen nutrition method of environmental monitoring of Raman spectroscopy in conjunction with microalgae grease peak, it is characterized in that, in step (2), described raman scattering intensity value comprises 1442cm
-1, 1301cm
-1and 1270cm
-1the raman scattering intensity value that the grease peak located is corresponding.
7. as claimed in claim 1 based on the nitrogen nutrition method of environmental monitoring of Raman spectroscopy in conjunction with microalgae grease peak, it is characterized in that, in described step (3), described multivariate regression algorithm is partial least-squares regression method algorithm, principal component regression algorithm, the Stepwise Regression Algorithm, artificial neural network algorithm, algorithm of support vector machine or LDA model.
8. as claimed in claim 7 based on the nitrogen nutrition method of environmental monitoring of Raman spectroscopy in conjunction with microalgae grease peak, it is characterized in that, described multivariate regression algorithm is LDA model.
9. as claimed in claim 1 based on the nitrogen nutrition method of environmental monitoring of Raman spectroscopy in conjunction with microalgae grease peak, it is characterized in that, in step (1) and step (4), nitrogen nutrition state comprises 1/4 nitrogen in micro algae growth process, 1/2 nitrogen, normal nitrogen, 2 times of nitrogen, 4 times of nitrogen.
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