Spectroscopic imaging near-infrared

Therefore, during the past 30 years, numerous vibrational spectroscopic methods (near infrared, NIR infrared, IR and Raman spectroscopy) have been introduced as very efficient alternatives, which are widely used today to determine fats, proteins, and carbohydrates and also numerous secondary plant substances occurring in agricultural products. For authentication purposes, the mentioned spectroscopic techniques can provide the valuable data in a few minutes, allowing the discrimination of different agrofood samples. Also new developments of IR and Raman microscopes have considerably extended the field of application. These sophisticated techniques allow to perform point-by-point measurements (mapping) or to acquire simultaneously spectra (imaging) from a small sample area. 

P. J. Treado, I. W. Levin, and E. N. Lewis, Near-infrared acousto-optic filtered spectroscopic microscopy A solid-state approach to chemical, Imaging. Appl. Sped. 46, 553-559 (1991). 

Treado, P.J. Levin, I.W. Lewis, E.N., Near-Infrared Acousto-Optic Spectroscopic Microscopy A Solid-State Approach to Chemical Imaging Appl. Spectrosc. 1992, 46(4), 553-559. 

Near-infrared chemical imaging using multichannel detectors inherits many of the attributes of conventional NIR spectroscopy using a single-channel detector. In addition to its well-documented capabilities as a spectroscopic technique, in comparison to other vibrational imaging approaches, it has unparalleled flexibility in terms of managing widely varying sample size, placement, shape and color. As has been shown with the three examples presented in this chapter, the technique easily... 

Becker, A., Chance, B., and Semmler, W. (2000) Hydrophilic cyanine dyes as contrast agents for near-infrared tumor imaging synthesis, photophysical properties and spectroscopic in vivo characterization, Photochem Photobiol 72, 392-398. 

Valous, N. A. Mendoza, F. Sun, D.W. (2010). Emerging non-contact imaging, spectroscopic and colorimetric technologies for quality evaluation and control of hams a review. Trends in Food Science Technology Vol.21, pp. 26-43 Williams, P. C. Sobering, D. (1996). Haw do we do it A brief summary of the methods we use in developing near infrared calibrations. In A. M. C. Davies P. C. Williams (Eds.), Near infrared spectroscopy the future waves (pp. 185-188). Chichester NIR Publications Wilson, A. D. Baietto, M. (2009). Applications and advances in electronic-nose technologies. Sensors Vol.9, pp. 5099-5148... 

Macromotecular Symposia Vol.119, July 1997, p.1-13 APPLICATIONS OF TWO-DIMENSIONAL CORRELATION SPECTROSCOPY IN DEPTHPROFILING PHOTOACOUSTIC SPECTROSCOPY, NEAR-INFRARED DYNAMIC RHEO-OPTICS, AND SPECTROSCOPIC IMAGING MICROSCOPY Noda I Story G M Dowrey A E Reeder R C ... 

M. Attas, M. Hewko, J. Payette, T. Posthumus, M. Sowa, and H. Mantsch, Visualization of Cutaneous Hemoglobin Oxygenation and Skin Hydration Using Near-Infrared Spectroscopic Imaging, Skin Res. Technol., 7,238 (2001). 

I. Noda, G. M. Story, A. E. Dowrey, R. C. Reeder, C. Marcott. Applications of two-dimensional correlation spectroscopy in depth profiling photoacoustic spectroscopy, near-infrared dynamic rheooptics, and spectroscopic imaging microscopy. Makwmol Chem Macromol Symp 119 1,1997. 

Infrared microspectroscopy has been reviewed [436,444 47] and theory and applications have been described in several recent books [393,417-419], An introduction to step-scan FTIR is available [448]. The role of IR and Raman microscopy/ microprobe spectroscopic techniques in the characterisation of polymers, their products, and composites was reviewed [449]. McClure [450] has described NIR imaging spectroscopy and a recent review on time-resolved studies of polymers by mid-and near-infrared spectroscopy has appeared [451]. Near-infrared microspectroscopy and its applications have been reviewed [452]. 

Meder, R. and Meglenb, R.R. (2012) Near infrared spectroscopic and hyperspectral imaging of compression wood in Pinus radiata D. Don. /. Near Infrared Spectrosc., 20 (5), 583-589. Fernandes, A. et oL (2013) Comparison between neural networks and partial least squares for intra-growth ring wood density measurement with hyperspectral imaging. Comput. Electron. Agric., 94, 71-81. 

Figure 10 Near-infrared spectroscopic imaging. A series of A/images is acquired using a CCD-array camera, using optical filtering to step successively through the near infrared (800-1100 nm in this illustration). An Af-point near-infrared spectrum may then be reconstructed for each pixel in the image. Courtesy of Jim Mansfield.

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