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Please note this is a comparison between Version 1 by Mikhail Shank and Version 2 by Beatrix Zheng.
Various types of vibrational spectroscopy (generally, it includes various variants of Raman and infrared spectroscopy) have been used for a long time to evaluate a variety of biological objects. Moreover, using vibrational spectroscopy, it is possible to evaluate individual compounds, cells, tissues, multicellular organisms (both living and fixed), and the products of their vital activity. These techniques are used for the assessment of the qualitative and quantitative composition of substances in studied biological objects and the conformations of compounds composing them. Among the advantages of these methods, one can mention their relative non-invasiveness, their significant experience in the subsequent analysis of results, and the possibility to perform in situ and in vivo measurements.
- infrared spectroscopy
- Raman spectroscopy
- vibrational spectroscopy in environmental studies
1. Application of Raman Spectroscopy
Since the second half of the 20th century laser-excited Raman spectroscopy as fast non-invasive and slightly damaging method has been widely used in investigation of different biological objects. During this time, in general, two main problems can be formulated for the use of Raman spectroscopy to study biological samples: (1) very low signal intensity of the Raman spectrum bands that requires enhanced laser power and a well-developed mathematical apparatus for treatment of spectra; and (2) rapid damage of radiated samples that requires a very careful selection of the radiation power and duration for each biological object. Unfortunately, due to these peculiarities, not all types of Raman spectroscopy are effective when working with biological objects. The solution of these problems is critical for the successful use of Raman spectroscopy. However, the aforementioned problems do not prevent the use of different methods of Raman spectroscopy for various biological and environmental studies.
Table 1Table 3 shows some examples of substances and objects that were detected using different methods of Raman spectroscopy.
Table 13.
Substances in cells observed using Raman spectroscopy.
| Substance | Objects | Methods | Bands, cm | −1 | Used for Estimation | Ref. |
|---|---|---|---|---|---|---|
| Carotenoids and other polyenes (e.g., β-carotene, lutein, lycopene, astaxanthin) | Microalgae, extremophiles, lichens; Watermelon, hot pepper, skin |
Resonance Raman spectroscopy, Raman microscopy; SERS |
~1530, ~1120–1200, and ~1000 | Carotenoids detection; Cell detection; Stress detection Concentration of carotenoids; Maturity degree |
[1][2][3][4][5][6][7][8][9][10][11][12][13][14] | [42,43,44,45,46,47,48,49,50,51,52,53,54,55] |
| Chlorophyll | Microorganisms (algae, bacteria, lichens, and endoliths) | Raman spectroscopy, Resonance Raman spectroscopy, Raman microscopy |
Wide range e.g., ~1640, ~1554, ~1437, ~1325, ~1289, ~1233, ~1186, ~1173, ~1020, ~986, ~915 | Organisms’ condition | Reviewed in [ | |
| 65 | ||||||
| , | ||||||
| 66 | ||||||
| ] | ||||||
[36][37][38][39][4,5,92,93]). Moreover, IR spectroscopy is a cheap method compared to its analogues [37][5]. A study of biological samples usually requires the use of near-infrared (1000–2500 nm, 10,000–4000 cm−1) and mid-infrared (2500–25,000 nm, 4000–400 cm−1) spectroscopy [36][4]. Unfortunately, the low sensitivity of near-infrared (NIR) spectroscopy and the limitations of mid-IR spectroscopy in the case of dealing with aqueous solutions, as well as the lower resolution of the method compared to Raman spectroscopy [40][3], result in significant problems with microscopic studies [36][4] that limit the potential of the method in relation to living objects and environmental studies.
The result of measuring biological samples is an IR spectrum, which, like in the case of Raman spectroscopy, represents a superposition of numerous overlapping peaks, whose presence and intensity depend on the chemical bonds in the studied compounds and their conformation. Based on the presence of typical chemical groups, it is possible to determine the presence of proteins, amino acids, fatty acids, polysaccharides, phenolic compounds, etc. However, such a large number of peaks significantly complicates their interpretation and requires the use of special mathematical apparatus, which (in contrast to Raman spectroscopy) has already been developed. The obtained spectral data are treated using various multiparametric analysis methods, such as principal component analysis (PCA), soft independent modeling of class analogy (SIMCA), hierarchical clustering analysis (HCA), canonical variation analysis (CVA), factor discriminant analysis (FDA), partial least squares discriminant analysis (PLSDA), and various regression models, including multiple linear regression (MLR), principal component regression (PCR), partial least squares regression (PLSR), etc. [41][33]. When applying these methods, there is no need to use the values of individual peaks; in these cases, whole (or selected sections of) IR spectra can be used without isolating individual peaks.
Table 2Table 4 shows some examples of using different methods of IR spectroscopy for environmental studies.
Table 24.
Substances in cells observed using IR spectroscopy.
| Objects | Substances | Methods * | Used for Estimation | Ref. | |||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Plants, fruits | Antioxidants (e.g., phenolic compounds, carotenoids, triterpenoids); organic acids; polysaccharides; essential oils; fatty acids | NIR and IR spectroscopy | Qualitative and quantitative detection | [42][43][48][49][50] | [94,95 | 44] | ,96 | [45] | ,97 | [46] | ,98 | [47] | ,99 | [ | ,100,101,102] | ||||||||||
| Leaves of | C. arabica | Compounds of leaves | NIR spectroscopy | Monitoring of atmospheric CO | 2[51] | [103] | 2] | Reviewed in [43 | [15] | ,56] | |||||||||||||||
| Quinones, flavonoids (polyphenols), pheophytin, cytochromes, hemoglobin et al.; Flexirubins, scytonemin (specific for cyanobacteria) |
Microorganisms (algae, bacteria, lichens, and endoliths) | Raman spectroscopy, Resonance Raman spectroscopy, | |||||||||||||||||||||||
| Wood | Cellulose, lignine, phenolic compounds, and other wood components | Raman microscopy | Wide range | Mainly NIR, DRIFT-MIR | Evaluation chemical structure and physical properties (including in vivo); changes in composition; density; degradation level; humidityOrganisms’ condition Cell detection; |
[52][53][54][55] | [104 | [ | ,105 | 56 | ,106,107 | ] | ,108] | Reviewed in [2][16][17] | Reviewed in [43,57,58] | ||||||||||
| Triglycerides (oil) and fatty acids | |||||||||||||||||||||||||
| Control for: Raw materials; | Algae and microalgae | transesterification process in bioreactor | Oils, fats, free fatty acids; methyl esters;Raman spectroscopy, Resonance Raman spectroscopy, Raman microscopy; SERS |
1650 (unsaturated) and 1440 (saturated) bonds, respectively | Biofuel production; Oil concentration |
NIR and IR spectroscopy | Biodiesel quality control: choice of the raw materials; reduction of cost; control of trans-esterification reaction; determination of the properties, quality, and contaminants of biodiesel |
[20][57][58] | [61,109,110] | [15][18][19][20][21][22] | [56,59,60,61,62,63] | ||||||||||||||
| Ethanol | Lignin and cellulose conversion to bioethanol in bioreactor | Raman spectroscopy | 883 | Biofuel production | |||||||||||||||||||||
| Fungal strains, cyanobacteria, other microorganisms and plants; single cells and biofilms |
Compounds containing C=O groups | IR spectroscopy | Evaluating biosorption of copper, lead, and cadmium ions; control of bioremediation, biodegradation, and biomineralization |
[38][59][60[63] | [92,111 | ][ | ,112 | 61][ | ,113 | 62] | ,114,115] | [18][23] | [59,64] | ||||||||||||
| Glucose and Glucose oligomers and polysaccharides | Lignin and cellulose conversion to bioethanol in bioreactor | Raman spectroscopy | 1120 | ||||||||||||||||||||||
| Microorganisms, strains of microorganisms | Typical glycosidic bond peak at 920–960 | Biofuel production | [ | Compounds (molecules) containing in microorganisms | IR spectroscopy | Rapid identification and classification of microorganisms | Reviewed in [41][64] | Reviewed in [33,116] | 18] | [59] | |||||||||||||||
| Inorganic polyphosphate inclusions | Microalgae | Raman microscopy | |||||||||||||||||||||||
| Agriculture: faeces and manure; agricultural products (including grains and milk) |
Compounds (molecules) containing in studied substances | Peak at ~1160 | NIR (mainly) and IR spectroscopy | Control the quality of agricultural products; control the quality of grain and food rations (including their composition, humidity, homogeneity, etc.); evaluate the composition of faeces and manure for the assessment of the digestion quality in animals and analysis of a stool composition; control of atmospheric emissions of ammonia, nitric oxide, methane, and other volatile organic compounds; control the environmental contamination (ammonia and greenhouse gases)Substance and concentration detection |
[38][65][66] | [92 | [ | ,117 | 67 | ,118 | ][ | ,119 | 68] | ,120 | [69] | ,121] | [24][25] | [ | Nitrogen (crystalline guanine) | Microalgae | Raman microscopy | Maximum at 651 | Substance and concentration detection | [26][27] | [67,68] |
| Starch | Microalgae | Raman microscopy | Maximum ~479 | Substance and concentration detection | [27] | [68] | |||||||||||||||||||
| Lipids | Microalgae | Raman microscopy | Maximum ~2854 | Substance and concentration detection | [27] | [68] | |||||||||||||||||||
| Calcite and aragonite magnesite |
Shells (exoskeletons) | Raman spectroscopy, Raman microscopy |
Peaks at 156, 282, and 1087 (calcite); Peaks at 155, 206, and 1086 (aragonite); Band at 1089 (magnesite) | Assessment of the size and mineralization level | [28][29][30]] | [69,70 | [ | ,71 | 31] | ,72 | [32] | ,73 | [33 | ,74] | |||||||||||
| Microorganisms, strains of micro-organisms | Specific binding cell sites | SERS with special particles containing biorecognition molecules | The peak of particles | Ultrasensitive bacteria (pathogen) detection | [34][35] | [75,76] |
2. Application of Different Types of IR Spectroscopy
As the rwesearchers have already mentioned, the advantages of IR spectroscopy include noninvasiveness, non-damaging or slightly damaging effects (even compared to the Raman spectroscopy), relatively rapid obtaining of results, and (unlike the Raman spectroscopy) the possibility to evaluate polar molecules (alcohols, phenolic compounds, etc.) [36][4]. As a result, different types of IR spectroscopy are quite actively used for the monitoring of environmental pollution as well as for solving different biomedical and other tasks, such as tumor diagnostics (reviewed in
* Also include the special mathematical apparatus for the interpretation of the results of measurement.
All the aforesaid advantages of IR (especially NIR) spectroscopy, as well as the availability of relatively inexpensive and cheap equipment, make it possible to perform environmental studies using IR spectroscopy (reviewed in [70][6]). Since IR and especially NIR spectroscopy provide the possibility of working with aqueous solutions, this method allows for the in vivo qualitative and quantitative assessment of the composition of animals and plants and the evaluation of changes occurring in them. The objects of IR spectroscopy may include single-celled fungi, lichens, microalgae, plant and animal tissues (membranes, bones, plant organs), multicellular plants and animals, and products of their vital activities (consumed food, excretions, feces, etc.) [70][6].