Detection limits for blood on four fabric types using infrared diffuse reflection spectroscopy in mid- and near-infrared spectral windows.

Detection limits (DL) for blood on four fabric types were estimated for calibrations derived using partial least squares regression applied to infrared (IR) diffuse reflection spectra. Samples were prepared by dip-coating acrylic, cotton, nylon, and polyester fabrics from solutions of diluted rat blood. While DLs often appear in terms of dilution factor in the forensic community, mass percentage, coverage (mass per unit area), or film thickness are often more relevant when comparing experimental methods. These alternate DL units are related to one another and presented here. The best IR diffuse reflection DLs for blood on acrylic and cotton fabrics were in the mid-IR spectral window corresponding to the protein Amide I/II absorption bands. These DLs were dilution by a factor of 2300 (0.019% w/w blood solids) for acrylic and a factor of 610 (0.055% w/w blood solids) for cotton. The best DL for blood on polyester was found in the mid-IR spectral window corresponding to the protein Amide A absorption band at dilution by a factor of 900 (0.034% w/w blood solids). Because of the similarity between the IR spectra of blood solids and nylon fabrics, no satisfactory IR DLs were determined for the calibration of blood on nylon. We compare our values to DLs reported for blood detection using the standard luminol method. The most commonly reported luminol DLs are of the order of 1000-fold dilution, which we estimate are a factor of 2-7 lower than our reported IR DLs on a coverage basis.

Focus-independent particle size measurement from streak images: a comparison of multivariate methods.

Our laboratories have recently developed a flow-through imaging photometer to characterize and classify fluorescent particles between 3 and 47 µm in size. The wide aperture of the objective lens (0.7 NA) required for measuring spectral fluorescence of single particles restricts the depth of field, such that a large sample volume results in many particles that are out of focus. Here, we describe numerical methods for determining the size of these objects, regardless of their distance from the focal plane, using image processing and multivariate calibration. An intensity profile is extracted from the images and is used as the input for a variety of calibration methods, including partial least squares, neural networks, and support vector machines. The capabilities of these methods are examined to establish the best method for particle sizing that is independent of focus. We found that support vector machines provided the best results, with size estimation error of ±3.1 µm.

Chemical contrast observed in thermal images of blood-stained fabrics exposed to steam.

Thermal imaging is not ordinarily a good way to visualize chemical contrast. In recent work, however, we observed strong and reproducible images with chemical contrasts on blood-stained fabrics, especially on more hydrophobic fabrics like acrylic and polyester.

Attenuated Total Reflection (ATR) Sampling in Infrared Spectroscopy of Heterogeneous Materials Requires Reproducible Pressure Control.

Attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy, in which the sample is pressed against an internal reflection element, is a popular technique for rapid IR spectral collection. However, depending on the accessory design, the pressure applied to the sample is not always well controlled. While collecting data from fabrics with heterogeneous coatings, we have observed systematic pressure-dependent changes in spectra that can be eliminated by more reproducible pressure control. We also described a pressure sensor adapted to work with an ATR tower to enable more precise control of pressure during ATR sampling.

Detection Limits for Blood on Fabrics Using Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) Spectroscopy and Derivative Processing.

Attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) was used to detect blood stains based on signature protein absorption in the mid-IR region, where intensity changes in the spectrum can be related to blood concentration. Partial least squares regression (PLSR) was applied for multivariate calibrations of IR spectra of blood dilutions on four types of fabric (acrylic, nylon, polyester, and cotton). Gap derivatives (GDs) were applied as a preprocessing technique to optimize the performance of calibration models. We report a much improved IR detection limit (DL) for blood on cotton (2700× in dilution factor units) and the first IR DL reported for blood on nylon (250×). Due to sample heterogeneity caused by fabric hydrophobicity, acrylic fabric produced variable ATR FT-IR spectra that caused poor DLs in concentration units compared to previous work. Polyester showed a similar problem at low blood concentrations that lead to a relatively poor DL as well. However, the increased surface sensitivity and decreased penetration depth of ATR FT-IR make it an excellent choice for detection of small quantities of blood on the front surface of all fabrics tested (0.0010 µg for cotton, 0.0077 µg for nylon, 0.011 µg for acrylic, and 0.0066 µg for polyester).

A quantitative method for determining a representative detection limit of the forensic luminol test for latent bloodstains.

The luminol test has been used for over 60 years by forensic investigators for presumptive identification of blood and visualization of blood splatter patterns. Multiple studies have estimated the limit of detection (LD) for bloodstains when luminol is employed, with results ranging from 100× to 5,000,000× dilute. However, these studies typically have not identified and controlled important experimental variables which may affect the luminol LD for bloodstains. Without control of experimental parameters in the laboratory, variables which affect the potential of presumptive bloodstain test methods remain largely unknown, and comparisons required to establish new, more powerful detection methods are simply impossible. We have developed a quantitative method to determine the relationship between the amount of blood present and its reaction with luminol by measuring, under controlled conditions, the resulting chemiluminescent intensity with a video camera, combined with processing of the digital intensity data. The method resulted in an estimated LD for bloodstains on cotton fabric at ∼200,000× diluted blood with a specific luminol formulation. Although luminol is the focus of this study, the experimental protocol used could be modified to study effects of variables using other blood detection reagents.

Reversible Gap Derivatives and Their Integration.

Higher-order gap derivatives are sometimes avoided as a preprocessing method for multivariate calibration despite their numerous advantages. One reason that they are avoided is the difficulty in interpreting the complex processed spectra and the regression vectors that arise from common calibration procedures like principal components regression or partial least squares regression. In this report we offer a method of calculating gap derivatives of any order with the aim of retrieving zero-order spectral information via numerical integration. This method is also extended to the integration of the accompanying regression vectors to aid in the interpretation of multivariate calibration models.

An Improved-Efficiency Compact Lamp for the Thermal Infrared.

A major type of infrared camera is sensitive to wavelengths in the 8-14 µm band and is mainly used for thermal imaging. Such cameras can also be used for general broadband infrared reflectance imaging when provided with a suitable light source. We report the design and properties of an infrared lamp using a heated alumina emitter suitable for active thermal infrared imaging, as well as comparisons to existing commercial light sources for this purpose. We find that the alumina lamp is a broadband non-blackbody source with a lower out-of-band emission intensity and therefore higher electrical efficiency for this application than existing commercial sources.

Optimization of gap derivatives for measuring blood concentration of fabric using vibrational spectroscopy.

Derivatives are common preprocessing tools, typically implemented as Savitzky-Golay (SG) smoothing derivatives. This work discusses the implementation and optimization of fourth-order gap derivatives (GDs) as an alternative to SG derivatives for processing infrared spectra before multivariate calibration. Gap derivatives approximate the analytical derivative by calculating finite differences of spectra without curve fitting. Gap derivatives offer an advantage of tunability for spectral data as the distance (gap) over which this finite difference is calculated can be varied. Gap selection is a compromise between signal attenuation, noise amplification, and spectral resolution. A method and discussion of the importance of fourth derivative gap selections are presented as well as a comparison to SG preprocessing and lower-order GDs in the context of multivariate calibration. In most cases, we found that optimized GDs led to calibration models performing comparably to or better than SG derivatives, and that optimized fourth-order GDs behaved similarly to matched filters.