Vibrational Spectroscopy Fundamentals¶
Purpose: Understand the physics of Raman, FTIR, and NIR spectroscopy for food science applications.
Audience: Researchers, students; foundational knowledge for preprocessing and feature extraction chapters.
Time: 20–30 minutes to read; reference as needed.
Prerequisites: Basic chemistry (molecular structure, vibrational modes); familiarity with spectral plots.
Overview¶
This page introduces vibrational spectroscopy concepts: what spectra are, how to interpret peaks, why baselines drift, and how modalities differ. It anchors the physics for later preprocessing and chemometrics chapters.
1. What is a spectrum?¶
- A spectrum plots intensity vs wavenumber (cm⁻¹). Wavenumber ( \tilde{\nu} = 1/\lambda ) is preferred because it scales linearly with energy.
- Peaks correspond to vibrational modes of molecules (stretching, bending). Food matrices contain lipids, proteins, carbohydrates, water—each with characteristic bands.
- Always store axes in ascending cm⁻¹ for computational pipelines.
2. Raman vs FTIR vs NIR¶
- Raman (inelastic scattering): Measures shifts relative to laser line (Stokes/anti-Stokes). Good for aqueous samples; sensitive to symmetric stretches (e.g., C=C, CH).
- FTIR (absorption): Measures molecular absorption; ATR-FTIR is common in food labs. Strong for polar bonds (C=O, O–H).
- NIR (overtones/combination bands): Broader, weaker features; useful for bulk composition and rapid QC.
Typical food spectral regions (examples)¶
- Fingerprint (600–1800 cm⁻¹): C–C, C–O, C=O; unsaturation bands (≈1655–1745 cm⁻¹) in oils; amide bands (protein) around 1650/1550 cm⁻¹.
- CH stretching (2800–3100 cm⁻¹): Lipid/protein CH2/CH3 bands.
- OH/NH (3200–3600 cm⁻¹): Water/protein hydrogen bonding (FTIR).
3. Peak shapes, baselines, and artifacts¶
- Peaks/bands: Can be sharp (Raman) or broad (NIR). Shoulders often encode overlapping modes.
- Baseline & fluorescence: Raman often has fluorescence backgrounds; FTIR can show sloping baselines due to ATR contact or scattering.
- Atmospheric lines: Water/CO₂ in FTIR; remove or account for them in preprocessing.
- Noise & scatter: Instrument noise, cosmic rays (Raman spikes), path-length/contact variation.
3a. Vibrational modes and spectral signatures¶
- Stretching vs bending: stretching changes bond length; bending changes bond angles. Raman favors polarizability changes (e.g., C=C), FTIR favors dipole changes (e.g., O–H).
- Food-relevant bands (cm⁻¹, illustrative):
- FTIR synthetic example (generated via
generate_synthetic_ftir_spectrum): O–H stretch (~3300), C–H stretches (2800–3000), ester C=O (~1740), CH₂ bend (~1450), C–O stretch (~1050), fingerprint 800–1500. Plot wavenumber vs absorbance and label each band with the mode and a food interpretation (e.g., ester C=O in lipids). - Raman synthetic example (generated via
generate_synthetic_raman_spectrum): discrete peaks at ~717 (C–C stretch), 1265 (cis =C–H bend), 1440 (CH₂ bend), 1655 (C=C stretch). Annotate peaks and note how intensity shifts relate to unsaturation/saturation. - Interpretation: shifts or intensity changes in these bands map to composition (unsaturation, ester content, moisture). Synthetic plots (see plotting helpers) mirror real bands observed in oils/fats.
- For notation/abbreviations, see the Glossary. For a practical bands/ratios guide, see Feature extraction.
4. Sampling and instrument notes¶
- Laser wavelength (Raman) affects fluorescence and penetration; ATR crystal choice (FTIR) affects depth of penetration.
- Resolution: finer spacing yields more data points but may increase noise.
- Export formats: vendor-specific to TXT/CSV. FoodSpec standardizes via CSV → HDF5; see CSV → HDF5 pipeline.
5. Choosing Spectroscopy Modality for Food Applications¶
- Authentication/adulteration: Raman/FTIR fingerprint region for oils, spices; NIR for rapid screening.
- Heating/oxidation studies: Track unsaturation bands (1650–1750 cm⁻¹) and CH stretches.
- Protein-rich samples (dairy/meat): Amide bands (FTIR/Raman); CH stretches.
- Water-dominated matrices: Raman often preferred to avoid strong water absorption in FTIR.
6. Links to computation¶
- Baseline drift and fluorescence → Baseline correction.
- Scatter/contact effects → Normalization & smoothing and Scatter & cosmic-ray handling.
- High dimensionality → PCA.
Summary¶
- Wavenumber in cm⁻¹ is the standard axis; keep spectra monotonic.
- Raman, FTIR, and NIR emphasize different vibrational modes; choose modality by matrix and question.
- Baselines, fluorescence, atmospheric lines, and scatter are common artifacts to mitigate in preprocessing.
Further reading¶
When Results Cannot Be Trusted¶
⚠️ Red flags for spectroscopy basics application:
- Spectral resolution insufficient for features of interest (broad bands analyzed as if sharp peaks)
- Overlapping peaks unresolved; chemical assignment ambiguous
- Information loss
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Fix: Use higher-resolution spectrometer; deconvolve overlapping peaks; document resolution limits
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Peak assignments based on single literature source without validation
- Literature assignments may be context-dependent (different matrix, conditions)
- Misassignment common
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Fix: Cross-reference multiple sources; validate with isotopic substitution or known standards
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Temperature not controlled (samples measured at varying room temperatures)
- Temperature affects peak positions and intensities
- Introduces uncontrolled variability
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Fix: Control sample temperature; document temperature; use thermostated stage
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Spectral saturation undetected (detector saturated; spectra clipped)
- Saturated spectra lose quantitative information
- Ratios biased by clipping
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Fix: Check detector counts; reduce integration time or laser power if saturated; re-measure
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Fluorescence not distinguished from Raman/FTIR signal (strong background mistaken for chemical information)
- Fluorescence dominates weak Raman; obscures peaks
- Can create false features
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Fix: Use longer-wavelength excitation; subtract fluorescence baseline; validate with fluorescence measurement
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No replicate measurements (single spectrum treated as ground truth)
- Measurement noise unquantified; reproducibility unknown
- Single outlier can bias analysis
- Fix: Measure ≥3 replicates; report SD; average replicates for analysis