Near-infrared spectroscopic studies of human scalp hair in a forensic context

Human hair is a relatively inert biopolymer and can survive through natural disasters. It is also found as trace evidence at crime scenes. Previous studies by FTIRMicrospectroscopy and – Attenuated Total Reflectance (ATR) successfully showed that hairs can be matched and discriminated on the basis of gender, race and hair treatment, when interpreted by chemometrics. However, these spectroscopic techniques are difficult to operate at- or on-field. On the other hand, some near infrared spectroscopic (NIRS) instruments equipped with an optical probe, are portable and thus, facilitate the on- or at –field measurements for potential application directly at a crime or disaster scene. This thesis is focused on bulk hair samples, which are free of their roots, and thus, independent of potential DNA contribution for identification. It explores the building of a profile of an individual with the use of the NIRS technique on the basis of information on gender, race and treated hair, i.e. variables which can match and discriminate individuals. The complex spectra collected may be compared and interpreted with the use of chemometrics. These methods can then be used as protocol for further investigations. Water is a common substance present at forensic scenes e.g. at home in a bath, in the swimming pool; it is also common outdoors in the sea, river, dam, puddles and especially during DVI incidents at the seashore after a tsunami. For this reason, the matching and discrimination of bulk hair samples after the water immersion treatment was also explored. Through this research, it was found that Near Infrared Spectroscopy, with the use of an optical probe, has successfully matched and discriminated bulk hair samples to build a profile for the possible application to a crime or disaster scene. Through the interpretation of Chemometrics, such characteristics included Gender and Race. A novel approach was to measure the spectra not only in the usual NIR range (4000 – 7500 cm-1) but also in the Visible NIR (7500 – 12800 cm-1). This proved to be particularly useful in exploring the discrimination of differently coloured hair, e.g. naturally coloured, bleached or dyed. The NIR region is sensitive to molecular vibrations of the hair fibre structure as well as that of the dyes and damage from bleaching. But the Visible NIR region preferentially responds to the natural colourants, the melanin, which involves electronic transitions. This approach was shown to provide improved discrimination between dyed and untreated hair. This thesis is an extensive study of the application of NIRS with the aid of chemometrics, for matching and discrimination of bulk human scalp hair. The work not only indicates the strong potential of this technique in this field but also breaks new ground with the exploration of the use of the NIR and Visible NIR ranges for spectral sampling. It also develops methods for measuring spectra from hair which has been immersed in different water media (sea, river and dam)

The structure of selected magnesium carbonate minerals : a near infrared and mid-infrared spectroscopic study

The approach to remove green house gases by pumping liquid CO2 several kilometres below the ground implies that many carbonate containing minerals will be formed. Among these minerals the formation of dypingite and artinite are possible; thus necessitating a study of such minerals. Two carbonate bearing minerals dypingite and artinite with a hydrotalcite related formulae have been characterised by a combination of infrared and near-infrared spectroscopy. The infrared spectra of both minerals are characterised by OH and water stretching vibrations. Both the first and second fundamental overtones of these bands are observed in the NIR spectra in the 7030 to 7235 cm-1 and 10490 to 10570 cm-1. Intense (CO3)2- symmetric and antisymmetric stretching vibrations confirm the distortion of the carbonate anion. The position of the water bending vibration indicates water is strongly hydrogen bonded to the carbonate anion in the mineral structure. Split NIR bands at around 8675 and 11100 cm-1 indicates that some replacement of magnesium ions by ferrous ions in the mineral structure has occurred.

Effective intercalation of sodium dodecylsulfate (SDS) into hydrocalumite: Mechanism discussion via near-infrared and mid-infrared investigations

The intercalation of an anionic surfactant, sodium dodecylsulfate (SDS), into hydrocalumite (CaAl-LDH-Cl) was investigated in this study. To understand the intercalation behavior, X-ray diffraction (XRD), mid-infrared spectroscopy (MIR), near-infrared spectroscopy (NIR) and scanning electron microscopy (SEM) were undertaken. The near-infrared spectra indicated a special spectral range from 6000 to 5600cm-1and prominent bands of CaAl-LDH-Cl intercalated with SDS around 8388cm-1. This band was assigned to the second overtone of the first fundamental of CH stretching vibrations of SDS, and it could be used to determinate the result of CaAl-LDH-Cl modified by SDS. Moreover, the results revealed that different adsorption behaviors were observed at different (high and low) concentrations of SDS. When the SDS concentration was around 0.2molL-1, anion exchange intercalation occurred and the interlayer distance expanded to about 3.25nm. When SDS concentration was 0.005molL-1, the surface adsorption of DS- was the major anion exchange event.

Near infrared reflectance as a rapid and inexpensive surrogate measure for fatty acid composition and oil content in peanuts (Arachis hypogaea L.)

The fatty acid composition of ground nuts (Arachis hypogaea L.) commonly known as peanuts, is an important consideration when a new variety is being released. The composition impacts on nutrition and, importantly, self-life of peanut products. To select for suitable breeding material, it was necessary to develop a rapid, non-derstructive and cost-efficient method. Near infrared spectroscopy was chosen as that methodology. Calibrations were developed for two major fatty-acid components, oleic and linoleic acids and two minor components, palmitic and stearic acids, as well as total oil content. Partial least squares models indicated a high level of precision with a squared multiple correlation coefficient of greater than 0.90 for each constitutent. Standard errors for prediction for oleic, linoleic, palmitic, stearic acids and total oil content were 6.4%, 4.5%, 0.8%, 0.9% and 1.3% respectively. The results demonstrated that reasonable calibrations could be developed to predict oil composition and content of peanuts for a breeding programme.

Nuclear and extended spectra of NGC 1068-II. Near-infrared stellar population synthesis

We performed stellar population synthesis on the nuclear and extended regions of NGC 1068 by means of near-infrared spectroscopy to disentangle their spectral energy distribution components. This is the first time that such a technique is applied to the whole 0.8-2.4 mu m wavelength interval in this galaxy. NGC 1068 is one of the nearest and probably the most studied Seyfert 2 galaxy, becoming an excellent laboratory to study the interaction between black holes, the jets that they can produce and the medium in which they propagate. Our main result is that traces of young stellar population are found at similar to 100 pc south of the nucleus. The contribution of a power-law continuum in the centre is about 25 per cent, which is expected if the light is scattered from a Seyfert 1 nucleus. We find peaks in the contribution of the featureless continuum about 100-150 pc from the nucleus on both sides. They might be associated with regions where the jet encounters dense clouds. Further support to this scenario is given by the peaks of hot dust distribution found around these same regions and the H(2) emission-line profile, leading us to propose that the peaks might be associated to regions where stars are being formed. Hot dust also has an important contribution to the nuclear region, reinforcing the idea of the presence of a dense, circumnuclear torus in this galaxy. Cold dust appears mostly in the south direction, which supports the view that the south-west emission is behind the plane of the galaxy and is extinguished very likely by dust in the plane. Intermediate-age stellar population contributes significantly to the continuum, especially in the inner 200 pc.

Near-infrared Raman spectroscopy to detect anti-Toxoplasma gondii antibody in blood sera of domestic cats: quantitative analysis based on partial least-squares multivariate statistics

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The use of handheld near-infrared reflectance spectroscopy (NIRS) for the proximate analysis of poultry feed and to detect melamine adulteration of soya bean meal

The use of handheld near infrared (NIR) instrumentation, as a tool for rapid analysis, has the potential to be used widely in the animal feed sector. A comparison was made between handheld NIR and benchtop instruments in terms of proximate analysis of poultry feed using off-the-shelf calibration models and including statistical analysis. Additionally, melamine adulterated soya bean products were used to develop qualitative and quantitative calibration models from the NIRS spectral data with excellent calibration models and prediction statistics obtained. With regards to the quantitative approach, the coefficients of determination (R2) were found to be 0.94-0.99 with the corresponding values for the root mean square error of calibration and prediction were found to be 0.081-0.215 % and 0.095-0.288 % respectively. In addition, cross validation was used to further validate the models with the root mean square error of cross validation found to be 0.101-0.212 %. Furthermore, by adopting a qualitative approach with the spectral data and applying Principal Component Analysis, it was possible to discriminate between adulterated and pure samples.

Non-destructive evaluation of articular cartilage defects using near-infrared (NIR) spectroscopy in osteoarthritic rat models and its direct relation to Mankin Score

Objective The aim of this study was to demonstrate the potential of near-infrared (NIR) spectroscopy for categorizing cartilage degeneration induced in animal models. Method Three models of osteoarthritic degeneration were induced in laboratory rats via one of the following methods: (i) menisectomy (MSX); (ii) anterior cruciate ligament transaction (ACLT); and (iii) intra-articular injection of mono-ido-acetete (1 mg) (MIA), in the right knee joint, with 12 rats per model group. After 8 weeks, the animals were sacrificed and tibial knee joints were collected. A custom-made nearinfrared (NIR) probe of diameter 5 mm was placed on the cartilage surface and spectral data were acquired from each specimen in the wavenumber range 4 000 – 12 500 cm−1. Following spectral data acquisition, the specimens were fixed and Safranin–O staining was performed to assess disease severity based on the Mankin scoring system. Using multivariate statistical analysis based on principal component analysis and partial least squares regression, the spectral data were then related to the Mankinscores of the samples tested. Results Mild to severe degenerative cartilage changes were observed in the subject animals. The ACLT models showed mild cartilage degeneration, MSX models moderate, and MIA severe cartilage degenerative changes both morphologically and histologically. Our result demonstrate that NIR spectroscopic information is capable of separating the cartilage samples into different groups relative to the severity of degeneration, with NIR correlating significantly with their Mankinscore (R2 = 88.85%). Conclusion We conclude that NIR is a viable tool for evaluating articularcartilage health and physical properties such as change in thickness with degeneration.

Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis.

The use of near infrared (NIR) hyperspectral imaging and hyperspectral image analysis for distinguishing between hard, intermediate and soft maize kernels from inbred lines was evaluated. NIR hyperspectral images of two sets (12 and 24 kernels) of whole maize kernels were acquired using a Spectral Dimensions MatrixNIR camera with a spectral range of 960-1662 nm and a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm. Exploratory principal component analysis (PCA) was used on absorbance images to remove background, bad pixels and shading. On the cleaned images. PCA could be used effectively to find histological classes including glassy (hard) and floury (soft) endosperm. PCA illustrated a distinct difference between glassy and floury endosperm along principal component (PC) three on the MatrixNIR and PC two on the sisuChema with two distinguishable clusters. Subsequently partial least squares discriminant analysis (PLS-DA) was applied to build a classification model. The PLS-DA model from the MatrixNIR image (12 kernels) resulted in root mean square error of prediction (RMSEP) value of 0.18. This was repeated on the MatrixNIR image of the 24 kernels which resulted in RMSEP of 0.18. The sisuChema image yielded RMSEP value of 0.29. The reproducible results obtained with the different data sets indicate that the method proposed in this paper has a real potential for future classification uses.

Near infrared reflectance spectroscopy (NIRS) to predict biological parameters of maize silage: effects of particle comminution, oven drying temperature and the presence of residual moisture

Maize silage nutritive quality is routinely determined by near infrared reflectance spectroscopy (NIRS). However, little is known about the impact of sample preparation on the accuracy of the calibration to predict biological traits. A sample population of 48 maize silages representing a wide range of physiological maturities was used in a study to determine the impact of different sample preparation procedures (i.e., drying regimes; the presence or absence of residual moisture; the degree of particle comminution) on resultant NIR prediction statistics. All silages were scanned using a total of 12 combinations of sample pre-treatments. Each sample preparation combination was subjected to three multivariate regression techniques to give a total of 36 predictions per biological trait. Increased sample preparations procedure, relative to scanning the unprocessed whole plant (WP) material, always resulted in a numerical minimisation of model statistics. However, the ability of each of the treatments to significantly minimise the model statistics differed. Particle comminution was the most important factor, oven-drying regime was intermediate, and residual moisture presence was the least important. Models to predict various biological parameters of maize silage will be improved if material is subjected to a high degree of particle comminution (i.e., having been passed through a 1 mm screen) and developed on plant material previously dried at 60 degrees C. The extra effort in terms of time and cost required to remove sample residual moisture cannot be justified. (c) 2005 Elsevier B.V. All rights reserved.

Direct Determination of Sugar Cane Quality Parameters by X-ray Spectrometry and Multivariate Analysis

Current methods for quality control of sugar cane are performed in extracted juice using several methodologies, often requiring appreciable time and chemicals (eventually toxic), making the methods not green and expensive. The present study proposes the use of X-ray spectrometry together with chemometric methods as an innovative and alternative technique for determining sugar cane quality parameters, specifically sucrose concentration, POL, and fiber content. Measurements in stem, leaf, and juice were performed, and those applied directly in stem provided the best results. Prediction models for sugar cane stem determinations with a single 60 s irradiation using portable X-ray fluorescence equipment allows estimating the % sucrose, % fiber, and POL simultaneously. Average relative deviations in the prediction step of around 8% are acceptable if considering that field measurements were done. These results may indicate the best period to cut a particular crop as well as for evaluating the quality of sugar cane for the sugar and alcohol industries.

Near infrared for non-destructive testing of articular cartilage

The concept of non-destructive testing (NDT) of materials and structures is of immense importance in engineering and medicine. Several NDT methods including electromagnetic (EM)-based e.g. X-ray and Infrared; ultrasound; and S-waves have been proposed for medical applications. This paper evaluates the viability of near infrared (NIR) spectroscopy, an EM method for rapid non-destructive evaluation of articular cartilage. Specifically, we tested the hypothesis that there is a correlation between the NIR spectrum and the physical and mechanical characteristics of articular cartilage such as thickness, stress and stiffness. Intact, visually normal cartilage-on-bone plugs from 2-3yr old bovine patellae were exposed to NIR light from a diffuse reflectance fibre-optic probe and tested mechanically to obtain their thickness, stress, and stiffness. Multivariate statistical analysis-based predictive models relating articular cartilage NIR spectra to these characterising parameters were developed. Our results show that there is a varying degree of correlation between the different parameters and the NIR spectra of the samples with R2 varying between 65 and 93%. We therefore conclude that NIR can be used to determine, nondestructively, the physical and functional characteristics of articular cartilage.

Spatial mapping of proteoglycan content in articular cartilage using near-infrared (NIR) spectroscopy

Diagnosis of articular cartilage pathology in the early disease stages using current clinical diagnostic imaging modalities is challenging, particularly because there is often no visible change in the tissue surface and matrix content, such as proteoglycans (PG). In this study, we propose the use of near infrared (NIR) spectroscopy to spatially map PG content in articular cartilage. The relationship between NIR spectra and reference data (PG content) obtained from histology of normal and artificially induced PG-depleted cartilage samples was investigated using principal component (PC) and partial least squares (PLS) regression analyses. Significant correlation was obtained between both data (R2 = 91.40%, p<0.0001). The resulting correlation was used to predict PG content from spectra acquired from whole joint sample, this was then employed to spatially map this component of cartilage across the intact sample. We conclude that NIR spectroscopy is a feasible tool for evaluating cartilage contents and mapping their distribution across mammalian joint