| FTIR spectroscopy |
Popular technique to combine with chemometric methods such as principal component regression (PCR) or partial least squares (PLS) regression. Have been used for successfully determining lignin content in biomass samples |
Calibration required with samples of known concentrations. Large dataset (training and test sets) needed for reliable quantification. Training samples and prediction samples cannot differ greatly. Analyses are sensitive to sample preparation techniques |
76 and 77
|
|
1H/13C 2D NMR |
Extremely detailed information about inter-unit linkages can be obtained. Has allowed for the assignment and quantification of over 80% of linkages in lignin oil from reductive catalytic fractionation of pine wood |
NMR experiments are expensive, instruments found at specialized institutions and universities. Both experiments and data processing can be highly time-consuming |
78 and 79
|
|
31P NMR |
Differentiation of the phenolic OH content of the three monolignols is possible from experiments after derivatization of the OH groups |
Full derivatization of OH-groups is essential for proper quantification. Inverse gated decoupling pulse sequence needed for quantification: reduced sensitivity and increases relaxation time of analysis |
78
|
| UV-vis spectroscopy |
Cruder determination of phenolic OH content is possible by comparing the differences in absorption at specific maxima between neutral and alkaline solutions |
Less accurate than 31P NMR. Affected by incomplete ionization of functional groups. Presence of other ionizable groups can affect results |
78 and 80
|
| Simultaneous conductometric and acid–base titrations |
A fast and cheap alternative to wet-chemical methods for determining both phenolic OH group and carboxylic acid contents |
Heterogeneity of COOH- and OH-groups distorts inflection point. Limited to quantification of COOH- and OH-groups (and possibly other ionizable groups) |
81 and 82
|
| Size exclusion chromatography (SEC) |
Popular technique for obtaining weight and number average molecular weights, Mw and Mn, and for further calculating the polydispersity index (PI) of samples |
Time consuming calibration required. Samples must be within linear range. Acetylation is often used for increased solubility prior to analysis |
78 and 83
|
| Gas chromatography – pyrolysis (GC-Py) |
Analysis of biomass composition, quantification of volatiles, bio-oil and biochar. Can be coupled with TGA and FTIR. |
Variations in inherent metal contents greatly affects the pyrolysis reaction of the biomass |
84 and 85
|
| Coherent anti-Stokes Raman scattering (CARS) microscopy |
Label-free method with high sensitivity and chemical selectivity for imaging of lignin in e.g. plant cell walls |
Interference from other aromatic compounds (phenylalanine, tyrosine) can distort image. Not suited for imaging all tissue types |
58 and 86
|
| Time-of-flight secondary ion mass spectrometry (ToF-SIMS) |
Visualization of monolignol distribution on plant sample cross-sections |
Prone to artefact-generation arising from sample preparation. Fragmentation of lignin during imaging due to high-energy ion bombardment |
87
|
