Mid-IR and near-IR chemical imaging: Complementary for biological materials
- 作者：David L. Wetzel ; dwetzel@ksu.edu
- 关键词：Infrared chemical imaging ; Hyperspectral imaging ; Quantitative imaging ; Pixel counting
- 刊名：Vibrational Spectroscopy
- 出版年：2012
- 期刊代码：113_09242031
- 类别：ms
- 出版时间：May, 2012
- 卷：60
- 期：Complete
- 页码：29-33
- 文件大小：372 K
摘要
Practical applications of microspectroscopic mid-IR and near-IR imaging are cited. Included are imaging applications that reveal pathological differences between diseased and normal tissue, genetic expression, germination of seeds, change in protein secondary structure with heat treatment, misfolded proteins in diseased tissue, homogeneity after mixing of commodities and separation of botanical parts of grain kernels. The two imaging techniques complement each other having reciprocal strengths and limitations. The mid-IR, although readily interpreted based on six decades of serious well documented classical IR investigations, have the practical limitation of thin specimen path length of 6-8 渭m and difficult sample preparation. In contrast, near-IR imaging data is more readily obtained with minimal sample preparation. It provides deeper sample penetration applicable to bulk analysis. However, interpretation usually requires statistical multivariate data treatment because broader overlapping near-IR absorption bands are the norm. Diffraction limited spatial resolution imaging is now routine for mid-IR microspectroscopy after nearly two decades of instrumental advances. They include single detector raster scanning with confocal image plane masking, focal plane array parallel spectral acquisition, and the use of synchrotron radiation sources. Near-IR commercial imaging systems are available with either a pushbroom linear detector array or a rectangular 320 脳 256 detector element focal plane array that acquires a 81,920 pixel image. For the latter, image contrast is assisted with statistical treatment and single pixel identification via discriminant multivariate pattern recognition that enables quantitative image analysis via pixel counting.