Application of Raman Spectroscopy for Noninvasive Detection of Target Compounds Kyung-Min Lee Office of the Texas State Chemist, Texas AgriLife Research January 24, 2012 OTSC Seminar OFFICE OF THE TEXAS STATE CHEMIST Texas Feed and Fertilizer Control Service Agriculture Analytical Service
Raman Spectroscopy 1 OFFICE OF THE TEXAS STATE CHEMIST A vibrational technique for identification and analysis of molecular species Irradiate a substance with monochromatic light and to detect the scattered light with a different frequency to the incident beam Raman shifts: differences in the frequencies between the incident and scattered radiation
Raman Spectroscopy 2 Based on the polarity of chemical bonds Provide information about the vibrational motions of the molecule: stretching, bending, wagging, deformation, and others Well-resolved bands molecular structure information of compounds Not fully explored despite of its great possibilities and advantages over other spectroscopic techniques
Instrumentation PerkinElmer RamanStation 400F bench-top spectrometer OFFICE OF THE TEXAS STATE CHEMIST Efficient & easy to use Unique Echellle spectrograph and CCD detector Motorized stage: automatic alignment of samples & high throughput Fiber optic probe: bring the spectrometer to the sample results easier to gather RamanStation 400F Fiber optic probe
Advantages of Raman Spectroscopy OFFICE OF THE TEXAS STATE CHEMIST Little or no sample preparation Small portions of sample Non-destructive technique No water interference Minimal glass interference Higher spectral resolution and more distinctive bands detailed information about structural changes and role of specific components Provide a plenty of qualitative and quantitative information More sensitivity to the symmetrical vibrations of covalent bonds Consideration as a routine method of analysis
Disadvantages of Raman Spectroscopy OFFICE OF THE TEXAS STATE CHEMIST Can not be used for metals or alloys Raman scattering is inherently weak Visible and ultraviolet laser excitation wavelengths interference from fluorescence Sample heating through the intense laser radiation
Development of Raman Spectroscopy For higher sensitivity, improved spatial resolution, and very specific information Surface Enhanced Raman Spectroscopy (SERS) Resonance Raman spectroscopy Surface-Enhanced Resonance Raman Spectroscopy (SERRS) Angle Resolved Raman Spectroscopy Hyper Raman Spontaneous Raman Spectroscopy (SRS) Optical Tweezers Raman Spectroscopy (OTRS) Stimulated Raman Spectroscopy Spatially Offset Raman Spectroscopy (SORS) Coherent anti-stokes Raman spectroscopy (CARS) Raman optical activity (ROA) Transmission Raman Inverse Raman spectroscopy Tip-enhanced Raman Spectroscopy (TERS)
Surface Enhanced Raman Spectroscopy (SERS) Traditional Raman spectroscopy: require bulk samples or concentrated solutions Much more sensitive method LOD to ppb level or even a single molecule level Aid of metallic nanostructures signal enhanced by >10 6 times due to the effects of electromagnetic field and chemical enhancement Faster, simpler, minimum sample preparation satisfactory qualitative and quantitative results
Spectroscopic amplification & Enhancement techniques Chemometrics non-uniform samples: produce spectra irrelevant chemical information mathematical treatments to reduce scatter effects and extract only meaningful information resolution-enhancement techniques such as derivatives (curve-fitting) and deconvolution before applying chemometrics reliable prediction Chemical imaging (Hyperspectral or spectroscopic imaging) spatial and spectral information from the sample Caplet Chemical image of Caplet
Applications OFFICE OF THE TEXAS STATE CHEMIST Applications are fast growing Demonstrated its superiority, or at least equality to infrared and other spectroscopic techniques Modified and Applied to a variety of food and feed samples Capable of analyzing organics, minerals, inorganics, polymers, emulsions, pharmaceuticals, and biomaterials Finding more use and applications: microbiology, art and archaeology, color, electronics, forensics, plant control and reaction following
App App 1 Detection Detection of of aflatoxin aflatoxin in in ground ground corn corn samples samples App App 2 Identification Identification & characterization characterization of of food-grade food-grade tracers tracers for for grain grain tracing tracing system system Use Use of of Raman Raman Spectroscopy in in OTSC OTSC App App 3 Classification Classification of of Bovine Bovine Spongiform Spongiform Encephalopathy Encephalopathy (BSE) (BSE) samples samples App App 4 Quantitation Quantitation and and classification classification of of camphor camphor in in goat goat serum serum
Spectra collection Raman shift range: 200 3500 cm -1 Laser light source: 785 nm at 350 mw 256 1024 pixel CCD detector Spectral resolution: 4 or 8 cm -1 Large sample spot (6 locations around centered 1 location) with an exposure time of 1 sec and 10 scans Baseline correction and normalization Different sample stages
Detection of aflatoxin in ground corn samples 1 Raman spectroscopy coupled with chemometrics 40 samples (11 1,206 ppb) Training data set (30 samples) & test data set (10 samples) Collected spectra baseline corrected and normalized preprocessed mathematically (1 st derivative, 2 nd derivative, and deconvolution algorithms) converted to Excel and exported to SAS chemometrics (PCA, PLS, & MLR) to build calibration models
Detection of aflatoxin in ground corn samples 2 Normalized (MLR) Deconvolution (MLR) 1 st derivative (MLR) 2 nd derivative (MLR) * PCA & PLS models (R 2 ): 0.76-0.86 * Paired sample t-test (HPLC vs Predicted): p = 0.950
Characterization of food-grade tracers 848 401 Processed sugar Bar-coded tracers 2845 Magnesium stearate 1295 1062 2845 Uncoated sucrose-based tracer 1295 1062 PS (3%) coated sucrose-based tracer HPMC (3%) coated sucrose-based tracer Sucrose-based tracers * PS = pregelatinized starch, HPMC = hydroxypropylmethylcellulose
1st derivative 2nd derivative UN = uncoated PS = pregelatinized starch coating HC (HPMC) = hydroxypropylmethylcellulose coating
Classification of BSE samples 620 520 420 Negative Positive 320 PC 1 220 120 20-80 -180-150 -110-70 -30 10 50 90 130 170 210 250 PC 2 * Using preprocessed 2 nd derivative data
Quantification and classification of camphor in goat serum 1 30000 Raman intensity 25000 20000 15000 10000 5000 y = 2352.1x + 4008.5 R 2 = 1 0 0 2 4 6 8 10 12 Camphor concentration (%) * At Raman band 648 cm -1
Quantification and classification of camphor in goat serum 130 90 0.5 ug/ml 1.0 ug/ml 5.0 ug/ml 10.0 ug/ml 50 PC 1 10-30 -70-110 -150-150 -130-110 -90-70 -50-30 -10 10 30 50 70 90 110 PC 2 * SERS application * Using preprocessed 1 st derivative data
Summary & Conclusions Raman spectroscopy: rapid, inexpensive, and convenient Use of SERS technique: discrimination performance & desired sensitivity and specificity OFFICE OF THE TEXAS STATE CHEMIST Analytical method for quick estimation of target compounds at busy locations More rapid qualitative and quantitative characteristics real-time monitoring Successful implementation of a robust model economic benefits Integrated spectra features into chemometrics a great potential for automatic detection & online-monitoring quality control Many new applications in the future
Dr. Tim Herrman All OTSC administratives, chemists, & supporting staffs OFFICE OF THE TEXAS STATE CHEMIST 445 Agronomy Road College Station, TX 77840 (979) 845 1121 http://otsc.tamu.edu