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A high-throughput Raman chemical imaging method was developed for direct inspection of benzoyl peroxide (BPO) mixed in wheat flour. A 5W, 785 nm line laser (240mm long and 1mm wide) was used as a Raman excitation source in a pushbroom Raman imaging system. Hyperspectral Raman images were collected in a wavenumber range of 103-2881 cm-1 from dry wheat flour mixed with BPO at eight concentrations (w/w) from 50 to 6400 ppm. A sample holder with a sampling volume of 150×100×2mm3 was used to present a thin layer (2mm thick) of the powdered sample for line-scan image acquisition with a spatial resolution of 0.2 mm. A baseline correction method based on adaptive iteratively reweighted penalized least squares was used to remove the fluctuating fluorescence signals from the wheat flour. To isolate BPO particles from the flour background, a simple thresholding method was applied to the single-band fluorescence-free images at a unique Raman peak wavenumber (i.e., 1001 cm-1) preselected for the BPO detection. Chemical images were created to detect and map the BPO particles. Limit of detection for the BPO was estimated in the order of 50 ppm, which is on the same level with regulatory standards. Pixel concentrations were calculated from the percentages of the BPO pixels in the chemical images. High correlation was found between the pixel concentrations and the mass concentrations of the BPO, indicating that the Raman chemical imaging method can be used for quantitative detection of the BPO mixed in the wheat flour. [ABSTRACT FROM AUTHOR]

Previous studies showed that two- and three-waveband color-mixing methods perform the optical equivalent of two- and three-wavelength band ratio calculations that are typically implemented using multispectral imaging to enhance target classification and detection. This paper presents a prototype two-waveband color-mixing binocular device for enhancing visual target detection and classification, as tested using Ishihara test cards. Target identification for the test cards in this study was improved by using two-waveband color-mixing binoculars fitted with filters centered at wavelength pairs selected according to the criterion of uniform background. The test-card imaging results demonstrate that color-mixing binoculars can be used to greatly enhance target identification and detection. [ABSTRACT FROM AUTHOR]

Surface-enhanced Raman (SERS) spectra of various batches of bacteria adsorbed on silver colloidal nanoparticles were collected to explore the potential of the SERS technique for rapid and routine identification of E. coli and L. monocytogenes cultures. Relative standard deviation (RSD) of SERS spectra from silver colloidal suspensions and ratios of SERS peaks from small molecules (K3PO4) were used to evaluate the reproducibility, stability, and binding effectiveness of citrate-reduced silver colloids over batch and storage processes. The results suggested consistent reproducibility of silver colloids over batch process and also stability and consistent binding effectiveness over an eight-week storage period. A variety of mixtures of E. coli/L. monocytogenes cultures with different colloidal batches revealed that, despite large variations in relative intensities and positions of SERS active bands, characteristic and unique bands at 712 and 390 cm−1 were consistently observed and were the strongest in E. coli and L. monocytogenes cultures, respectively. Two specific bands were used to develop simple algorithms in the evaluation of binding effectiveness of silver colloids over storage and further to identify E. coli and L. monocytogenes cultures with a 100% success. A single spectrum acquisition took 5∼6 min, and a minimum of 25 μL silver colloid was directly mixed with 25 μL volume of incubated bacterial culture. The short acquisition time and small volume of incubated bacterial culture make silver colloidal nanoparticle based SERS spectroscopy ideal for potential use in the routine and rapid screening of E. coli and L. monocytogenes cultures on large scales. This is the first report of the development of simple and universal algorithms for bacterial identification from the respective exclusive SERS peaks. [ABSTRACT FROM AUTHOR]