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ARS Home » Southeast Area » Athens, Georgia » U.S. National Poultry Research Center » Quality and Safety Assessment Research Unit » Research » Publications at this Location » Publication #334169

Research Project: Develop Rapid Optical Detection Methods for Food Hazards

Location: Quality and Safety Assessment Research Unit

Title: Methods for hyperspectral microscope calibration and spectra normalization from images of bacteria cells

item Eady, Matthew
item Park, Bosoon
item Yoon, Seung-Chul
item HAIDEKKER, MARK - University Of Georgia
item Lawrence, Kurt

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/15/2017
Publication Date: 4/26/2018
Citation: Eady, M.B., Park, B., Yoon, S.C., Haidekker, M., Lawrence, K.C. 2018. Methods for hyperspectral microscope calibration and spectra normalization from images of bacteria cells. Transactions of the ASABE. 61(2): 437-448.

Interpretive Summary: It is estimated that one in six Americans are impacted by foodborne disease each year. Current detection methods for foodborne bacteria are well proven, but offer disadvantages in terms of the amount of time required for verification of the bacteria or cost associated with rapid testing methods. The use of hyperspectral microscope images has shown potential for rapid detection of foodborne pathogens through proof-of-concept studies. The objective of this study was to develop a calibration method for hyperspectral microscopes. We employ two spectral calibration lamps, and verification of cellular spatial characterizations. A unique benefit of hyperspectral microscopy is the level of detection sensitivity with individual bacteria cells being identified. We show that with a single cell detection method there is a need for minimal preprocessing of data. From hyperspectral microscope system calibration and minor preprocessing treatments we can accurately separate three species of bacteria. This approach has the potential for classifying individual cells of bacteria, potentially removing the need for time consuming cell enumerations.

Technical Abstract: Hyperspectral microscope images (HMIs) have previously shown promise as a means of rapid and early detection for foodborne bacteria at the cellular level. System calibration and data normalization are critical for comparing information obtained from HMIs collected from multiple instruments and system parameters. Here, we implement a multi-ion wavelength and a radiometric calibration for spectral data obtained from a hyperspectral microscope, assess the spatial uniformity of HMIs, and show the need to normalize data from single cell regions of interest. A hyperspectral microscope with a tungsten halogen light source, acousto-optical tunable filter, and electron multiplying camera with variable gain and exposure time settings were used as calibration parameters. HMIs were collected at gain settings of 0, 1.6%, 3.5%, and 5.1% additional gain along with 10 exposure time settings between 100 and 1000 ms with both calibration lamps. Peak shift started to occur at 600 ms for a gain of 1.6%, 400 ms for a gain of 3.5%, and 200 ms for a gain of 5.1%. HMIs of E. coli, S. Typhimurium, and S. sciuri were collected to assess spectral data normalcy and the need for preprocessing of spectra from single bacteria cells. Spatial characteristics of cells were assessed by HMIs of a glass slide with a micrometer for determining pixel size from the field of view. Bacteria were preprocessed by normalizing cell spectra to the light source and applying multiplicative scatter correction. Data normalcy was assessed on both the raw and preprocessed data sets. Preprocessed data were found to have reduced the cell to cell variation of associated with a single cell ROI method, while outliers were detected as possibly physically damaged cells.