Fast fourier analysis of structural organization in decellularized cartilage-on-bone laminates

Denaturation of tissues can provide a unique biological environment for regenerative medicine application only if minimal disruption of their microarchitecture is achieved during the decellularization process. The goal is to keep the structural integrity of such a construct as functional as the tissues from which they were derived. In this work, cartilage-on-bone laminates were decellularized through enzymatic, non-ionic and ionic protocols. This work investigated the effects of decellularization process on the microarchitecture of cartiligous extracellular matrix; determining the extent of how each process deteriorated the structural organization of the network. High resolution microscopy was used to capture cross-sectional images of samples prior to and after treatment. The variation of the microarchitecture was then analysed using a well defined fast Fourier image processing algorithm. Statistical analysis of the results revealed how significant the alternations among aforementioned protocols were (p < 0.05). Ranking the treatments by their effectiveness in disrupting the ECM integrity, they were ordered as: Trypsin> SDS> Triton X-100.

Rapid and quantitative detection of the microbial spoilage of meat by Fourier Transform Infrared Spectroscopy and machine learning

Ellis, D. I., Broadhurst, D., Kell, D. B., Rowland, J. J., Goodacre, R. (2002). Rapid and quantitative detection of the microbial spoilage of meat by Fourier Transform Infrared Spectroscopy and machine learning. ? Applied and Environmental Microbiology, 68, (6), 2822-2828 Sponsorship: BBSRC

Forensic analysis of architectural finishes using Fourier transform infrared and Raman spectroscopy, Part I: The resin bases

The ability of Raman spectroscopy and Fourier transform infrared (FT-IR) microscopy to discriminate between resins used for the manufacture of architectural finishes was examined in a study of 39 samples taken from a commercial resin library. Both Raman and FT-IR were able to discriminate between different types of resin and both split the samples into several groups (six for FT-IR, six for Raman), each of which gave similar, but not identical, spectra. In addition, three resins gave unique Raman spectra (four in FTIR). However, approximately half the library comprised samples that were sufficiently similar that they fell into a single large group, whether classified using FT-IR or Raman, although the remaining samples fell into much smaller groups. Further sub-division of the FT-IR groups was not possible because the experimental uncertainty was of similar magnitude to the within-group variation. In contrast, Raman spectroscopy was able to further discriminate between resins that fell within the same groups because the differences in the relative band intensities of the resins, although small, were larger than the experimental uncertainty.

Forensic analysis of architectural finishes using fourier transform infrared and raman spectroscopy, part II:White paint

White household paints are commonly encountered as evidence in the forensic laboratory but they often cannot be readily distinguished by color alone so Fourier transform infrared (FT-IR) microscopy is used since it can sometimes discriminate between paints prepared with different organic resins. Here we report the first comparative study of FT-IR and Raman spectroscopy for forensic analysis of white paint. Both techniques allowed the 51 white paint samples in the study to be classified by inspection as either belonging to distinct groups or as unique samples. FT-IR gave five groups and four unique samples; Raman gave seven groups and six unique samples. The basis for this discrimination was the type of resin and/ or inorganic pigments/extenders present. Although this allowed approximately half of the white paints to be distinguished by inspection, the other half were all based on a similar resin and did not contain the distinctive modifiers/pigments and extenders that allowed the other samples to be identified. The experimental uncertainty in the relative band intensities measured using FT-IR was similar to the variation within this large group, so no further discrimination was possible. However, the variation in the Raman spectra was larger than the uncertainty, which allowed the large group to be divided into three subgroups and four distinct spectra, based on relative band intensities. The combination of increased discrimination and higher sample throughput means that the Raman method is superior to FT-IR for samples of this type. © 2005 Society for Applied Spectroscopy.

Fourier transform infrared microspectroscopy as a tool to identify macroalgal propagules

Understanding of macroalgal dispersal has been hindered by the difficulty in identifying propagules. Different carrageenans typically occur in gametophytes and tetrasporophytes of the red algal family Gigartinaceae, and we may expect that carpospores and tetraspores also differ in composition of carrageenans. Using Fourier transform infrared (FT-IR) microspectroscopy, we tested the model that differences in carrageenans and other cellular constituents between nuclear phases should allow us to discriminate carpospores and tetraspores of <i>Chondrus verrucosus</i> Mikami.&nbsp;Spectral data suggest that carposporophytes isolated from the pericarp and female gametophytes contained&nbsp;&kappa;-carrageenan, whereas tetrasporophytes contained&nbsp;&lambda;-carrageenan. However, both carpospores and tetraspores exhibited absorbances in wave bands characteristic of &kappa;-,&iota;-, and&nbsp;&lambda;-carrageenans. Carpospores contained more proteins and may be more photosynthetically active than tetraspores, which contained more lipid reserves. We draw analogies to planktotrophic and lecithotrophic larvae. These differences in cellular chemistry allowed reliable discrimination of spores, but pretreatment of spectral data affected the accuracy of classification. The best classification of spores was achieved with extended multiplicative signal correction (EMSC) pretreatment using partial least squares discrimination analysis, with correct classification of 86% of carpospores and 83% of tetraspores. Classification may be further improved by using synchrotron FT-IR microspectroscopy because of its inherently higher signal-to-noise ratio compared with microspectroscopy using conventional sources of IR. This study demonstrates that FT-IR microspectroscopy and bioinformatics are useful tools to advance our understanding of algal dispersal ecology through discrimination of morphologically similar propagules both within and potentially between species.

Brain-Computer Interfaces: Desarrollo de un sistema de identificación de estados mentales alfa

En el mundo actual las aplicaciones basadas en sistemas biométricos, es decir, aquellas que miden las señales eléctricas de nuestro organismo, están creciendo a un gran ritmo. Todos estos sistemas incorporan sensores biomédicos, que ayudan a los usuarios a controlar mejor diferentes aspectos de la rutina diaria, como podría ser llevar un seguimiento detallado de una rutina deportiva, o de la calidad de los alimentos que ingerimos. Entre estos sistemas biométricos, los que se basan en la interpretación de las señales cerebrales, mediante ensayos de electroencefalografía o EEG están cogiendo cada vez más fuerza para el futuro, aunque están todavía en una situación bastante incipiente, debido a la elevada complejidad del cerebro humano, muy desconocido para los científicos hasta el siglo XXI. Por estas razones, los dispositivos que utilizan la interfaz cerebro-máquina, también conocida como BCI (Brain Computer Interface), están cogiendo cada vez más popularidad. El funcionamiento de un sistema BCI consiste en la captación de las ondas cerebrales de un sujeto para después procesarlas e intentar obtener una representación de una acción o de un pensamiento del individuo. Estos pensamientos, correctamente interpretados, son posteriormente usados para llevar a cabo una acción. Ejemplos de aplicación de sistemas BCI podrían ser mover el motor de una silla de ruedas eléctrica cuando el sujeto realice, por ejemplo, la acción de cerrar un puño, o abrir la cerradura de tu propia casa usando un patrón cerebral propio. Los sistemas de procesamiento de datos están evolucionando muy rápido con el paso del tiempo. Los principales motivos son la alta velocidad de procesamiento y el bajo consumo energético de las FPGAs (Field Programmable Gate Array). Además, las FPGAs cuentan con una arquitectura reconfigurable, lo que las hace más versátiles y potentes que otras unidades de procesamiento como las CPUs o las GPUs.En el CEI (Centro de Electrónica Industrial), donde se lleva a cabo este TFG, se dispone de experiencia en el diseño de sistemas reconfigurables en FPGAs. Este TFG es el segundo de una línea de proyectos en la cual se busca obtener un sistema capaz de procesar correctamente señales cerebrales, para llegar a un patrón común que nos permita actuar en consecuencia. Más concretamente, se busca detectar cuando una persona está quedándose dormida a través de la captación de unas ondas cerebrales, conocidas como ondas alfa, cuya frecuencia está acotada entre los 8 y los 13 Hz. Estas ondas, que aparecen cuando cerramos los ojos y dejamos la mente en blanco, representan un estado de relajación mental. Por tanto, este proyecto comienza como inicio de un sistema global de BCI, el cual servirá como primera toma de contacto con el procesamiento de las ondas cerebrales, para el posterior uso de hardware reconfigurable sobre el cual se implementarán los algoritmos evolutivos. Por ello se vuelve necesario desarrollar un sistema de procesamiento de datos en una FPGA. Estos datos se procesan siguiendo la metodología de procesamiento digital de señales, y en este caso se realiza un análisis de la frecuencia utilizando la transformada rápida de Fourier, o FFT. Una vez desarrollado el sistema de procesamiento de los datos, se integra con otro sistema que se encarga de captar los datos recogidos por un ADC (Analog to Digital Converter), conocido como ADS1299. Este ADC está especialmente diseñado para captar potenciales del cerebro humano. De esta forma, el sistema final capta los datos mediante el ADS1299, y los envía a la FPGA que se encarga de procesarlos. La interpretación es realizada por los usuarios que analizan posteriormente los datos procesados. Para el desarrollo del sistema de procesamiento de los datos, se dispone primariamente de dos plataformas de estudio, a partir de las cuales se captarán los datos para después realizar el procesamiento: 1. La primera consiste en una herramienta comercial desarrollada y distribuida por OpenBCI, proyecto que se dedica a la venta de hardware para la realización de EEG, así como otros ensayos. Esta herramienta está formada por un microprocesador, un módulo de memoria SD para el almacenamiento de datos, y un módulo de comunicación inalámbrica que transmite los datos por Bluetooth. Además cuenta con el mencionado ADC ADS1299. Esta plataforma ofrece una interfaz gráfica que sirve para realizar la investigación previa al diseño del sistema de procesamiento, al permitir tener una primera toma de contacto con el sistema. 2. La segunda plataforma consiste en un kit de evaluación para el ADS1299, desde la cual se pueden acceder a los diferentes puertos de control a través de los pines de comunicación del ADC. Esta plataforma se conectará con la FPGA en el sistema integrado. Para entender cómo funcionan las ondas más simples del cerebro, así como saber cuáles son los requisitos mínimos en el análisis de ondas EEG se realizaron diferentes consultas con el Dr Ceferino Maestu, neurofisiólogo del Centro de Tecnología Biomédica (CTB) de la UPM. Él se encargó de introducirnos en los distintos procedimientos en el análisis de ondas en electroencefalogramas, así como la forma en que se deben de colocar los electrodos en el cráneo. Para terminar con la investigación previa, se realiza en MATLAB un primer modelo de procesamiento de los datos. Una característica muy importante de las ondas cerebrales es la aleatoriedad de las mismas, de forma que el análisis en el dominio del tiempo se vuelve muy complejo. Por ello, el paso más importante en el procesamiento de los datos es el paso del dominio temporal al dominio de la frecuencia, mediante la aplicación de la transformada rápida de Fourier o FFT (Fast Fourier Transform), donde se pueden analizar con mayor precisión los datos recogidos. El modelo desarrollado en MATLAB se utiliza para obtener los primeros resultados del sistema de procesamiento, el cual sigue los siguientes pasos. 1. Se captan los datos desde los electrodos y se escriben en una tabla de datos. 2. Se leen los datos de la tabla. 3. Se elige el tamaño temporal de la muestra a procesar. 4. Se aplica una ventana para evitar las discontinuidades al principio y al final del bloque analizado. 5. Se completa la muestra a convertir con con zero-padding en el dominio del tiempo. 6. Se aplica la FFT al bloque analizado con ventana y zero-padding. 7. Los resultados se llevan a una gráfica para ser analizados. Llegados a este punto, se observa que la captación de ondas alfas resulta muy viable. Aunque es cierto que se presentan ciertos problemas a la hora de interpretar los datos debido a la baja resolución temporal de la plataforma de OpenBCI, este es un problema que se soluciona en el modelo desarrollado, al permitir el kit de evaluación (sistema de captación de datos) actuar sobre la velocidad de captación de los datos, es decir la frecuencia de muestreo, lo que afectará directamente a esta precisión. Una vez llevado a cabo el primer procesamiento y su posterior análisis de los resultados obtenidos, se procede a realizar un modelo en Hardware que siga los mismos pasos que el desarrollado en MATLAB, en la medida que esto sea útil y viable. Para ello se utiliza el programa XPS (Xilinx Platform Studio) contenido en la herramienta EDK (Embedded Development Kit), que nos permite diseñar un sistema embebido. Este sistema cuenta con: Un microprocesador de tipo soft-core llamado MicroBlaze, que se encarga de gestionar y controlar todo el sistema; Un bloque FFT que se encarga de realizar la transformada rápida Fourier; Cuatro bloques de memoria BRAM, donde se almacenan los datos de entrada y salida del bloque FFT y un multiplicador para aplicar la ventana a los datos de entrada al bloque FFT; Un bus PLB, que consiste en un bus de control que se encarga de comunicar el MicroBlaze con los diferentes elementos del sistema. Tras el diseño Hardware se procede al diseño Software utilizando la herramienta SDK(Software Development Kit).También en esta etapa se integra el sistema de captación de datos, el cual se controla mayoritariamente desde el MicroBlaze. Por tanto, desde este entorno se programa el MicroBlaze para gestionar el Hardware que se ha generado. A través del Software se gestiona la comunicación entre ambos sistemas, el de captación y el de procesamiento de los datos. También se realiza la carga de los datos de la ventana a aplicar en la memoria correspondiente. En las primeras etapas de desarrollo del sistema, se comienza con el testeo del bloque FFT, para poder comprobar el funcionamiento del mismo en Hardware. Para este primer ensayo, se carga en la BRAM los datos de entrada al bloque FFT y en otra BRAM los datos de la ventana aplicada. Los datos procesados saldrán a dos BRAM, una para almacenar los valores reales de la transformada y otra para los imaginarios. Tras comprobar el correcto funcionamiento del bloque FFT, se integra junto al sistema de adquisición de datos. Posteriormente se procede a realizar un ensayo de EEG real, para captar ondas alfa. Por otro lado, y para validar el uso de las FPGAs como unidades ideales de procesamiento, se realiza una medición del tiempo que tarda el bloque FFT en realizar la transformada. Este tiempo se compara con el tiempo que tarda MATLAB en realizar la misma transformada a los mismos datos. Esto significa que el sistema desarrollado en Hardware realiza la transformada rápida de Fourier 27 veces más rápido que lo que tarda MATLAB, por lo que se puede ver aquí la gran ventaja competitiva del Hardware en lo que a tiempos de ejecución se refiere. En lo que al aspecto didáctico se refiere, este TFG engloba diferentes campos. En el campo de la electrónica:  Se han mejorado los conocimientos en MATLAB, así como diferentes herramientas que ofrece como FDATool (Filter Design Analysis Tool).  Se han adquirido conocimientos de técnicas de procesado de señal, y en particular, de análisis espectral.  Se han mejorado los conocimientos en VHDL, así como su uso en el entorno ISE de Xilinx.  Se han reforzado los conocimientos en C mediante la programación del MicroBlaze para el control del sistema.  Se ha aprendido a crear sistemas embebidos usando el entorno de desarrollo de Xilinx usando la herramienta EDK (Embedded Development Kit). En el campo de la neurología, se ha aprendido a realizar ensayos EEG, así como a analizar e interpretar los resultados mostrados en el mismo. En cuanto al impacto social, los sistemas BCI afectan a muchos sectores, donde destaca el volumen de personas con discapacidades físicas, para los cuales, este sistema implica una oportunidad de aumentar su autonomía en el día a día. También otro sector importante es el sector de la investigación médica, donde los sistemas BCIs son aplicables en muchas aplicaciones como, por ejemplo, la detección y estudio de enfermedades cognitivas.

Estudo e aplicação da transformada de Fourier na regularização de dados sísmicos na exploração de petróleo

In the oil prospection research seismic data are usually irregular and sparsely sampled along the spatial coordinates due to obstacles in placement of geophones. Fourier methods provide a way to make the regularization of seismic data which are efficient if the input data is sampled on a regular grid. However, when these methods are applied to a set of irregularly sampled data, the orthogonality among the Fourier components is broken and the energy of a Fourier component may "leak" to other components, a phenomenon called "spectral leakage". The objective of this research is to study the spectral representation of irregularly sampled data method. In particular, it will be presented the basic structure of representation of the NDFT (nonuniform discrete Fourier transform), study their properties and demonstrate its potential in the processing of the seismic signal. In this way we study the FFT (fast Fourier transform) and the NFFT (nonuniform fast Fourier transform) which rapidly calculate the DFT (discrete Fourier transform) and NDFT. We compare the recovery of the signal using the FFT, DFT and NFFT. We approach the interpolation of seismic trace using the ALFT (antileakage Fourier transform) to overcome the problem of spectral leakage caused by uneven sampling. Applications to synthetic and real data showed that ALFT method works well on complex geology seismic data and suffers little with irregular spatial sampling of the data and edge effects, in addition it is robust and stable with noisy data. However, it is not as efficient as the FFT and its reconstruction is not as good in the case of irregular filling with large holes in the acquisition.

Estudo e aplicação da transformada de Fourier na regularização de dados sísmicos na exploração de petróleo

In the oil prospection research seismic data are usually irregular and sparsely sampled along the spatial coordinates due to obstacles in placement of geophones. Fourier methods provide a way to make the regularization of seismic data which are efficient if the input data is sampled on a regular grid. However, when these methods are applied to a set of irregularly sampled data, the orthogonality among the Fourier components is broken and the energy of a Fourier component may "leak" to other components, a phenomenon called "spectral leakage". The objective of this research is to study the spectral representation of irregularly sampled data method. In particular, it will be presented the basic structure of representation of the NDFT (nonuniform discrete Fourier transform), study their properties and demonstrate its potential in the processing of the seismic signal. In this way we study the FFT (fast Fourier transform) and the NFFT (nonuniform fast Fourier transform) which rapidly calculate the DFT (discrete Fourier transform) and NDFT. We compare the recovery of the signal using the FFT, DFT and NFFT. We approach the interpolation of seismic trace using the ALFT (antileakage Fourier transform) to overcome the problem of spectral leakage caused by uneven sampling. Applications to synthetic and real data showed that ALFT method works well on complex geology seismic data and suffers little with irregular spatial sampling of the data and edge effects, in addition it is robust and stable with noisy data. However, it is not as efficient as the FFT and its reconstruction is not as good in the case of irregular filling with large holes in the acquisition.

Análise eletromiográfica da postura do profissional de saúde no inícioe fim doexpediente de trabalho

Pós-graduação em Engenharia Mecânica - FEG

A novel method for the age estimation of Saddletail snapper (Lutjanus malabaricus) using Fourier Transform-near infrared (FT-NIR) spectroscopy

Near infrared (NIR) spectroscopy was investigated as a potential rapid method of estimating fish age from whole otoliths of Saddletail snapper (Lutjanus malabaricus). Whole otoliths from 209 Saddletail snapper were extracted and the NIR spectral characteristics were acquired over a spectral range of 800–2780 nm. Partial least-squares models (PLS) were developed from the diffuse reflectance spectra and reference-validated age estimates (based on traditional sectioned otolith increments) to predict age for independent otolith samples. Predictive models developed for a specific season and geographical location performed poorly against a different season and geographical location. However, overall PLS regression statistics for predicting a combined population incorporating both geographic location and season variables were: coefficient of determination (R2) = 0.94, root mean square error of prediction (RMSEP) = 1.54 for age estimation, indicating that Saddletail age could be predicted within 1.5 increment counts. This level of accuracy suggests the method warrants further development for Saddletail snapper and may have potential for other fish species. A rapid method of fish age estimation could have the potential to reduce greatly both costs of time and materials in the assessment and management of commercial fisheries.

Systematic analysis of the Fourier transform spectrum of (CH3OH)-C-13 between 400 and 950 cm(-1)

We have investigated a high-resolution Fourier transform (FT) absorption spectrum of the (CH3OH)-C-13 isotopomer of methanol from 400 to 950 cm(-1) with the Ritz program. We present the assignments of 7160 transitions, 3021 of which belong to Asymmetry, and 4139 to E-symmetry. These transitions occur between states labeled by K quantum numbers up to 14, and by torsional quantum numbers n up to 4. The Ritz program evaluated the energies of the 4684 involved levels with an accuracy of the order of 10(-4) cm(-1). All of the assigned lines correspond to transitions involving torsionally excited levels within the ground small-amplitude vibrational state. (c) 2005 Elsevier B.V. All rights reserved.

Breath Testing by Fourier Transform Infrared Spectroscopy for Solvent Intoxication Diagnostics

Technical or contaminated ethanol products are sometimes ingested either accidentally or on purpose. Typical misused products are black-market liquor and automotive products, e.g., windshield washer fluids. In addition to less toxic solvents, these liquids may contain the deadly methanol. Symptoms of even lethal solvent poisoning are often non-specific at the early stage. The present series of studies was carried out to develop a method for solvent intoxication breath diagnostics to speed up the diagnosis procedure conventionally based on blood tests. Especially in the case of methanol ingestion, the analysis method should be sufficiently sensitive and accurate to determine the presence of even small amounts of methanol from the mixture of ethanol and other less-toxic components. In addition to the studies on the FT-IR method, the Dräger 7110 evidential breath analyzer was examined to determine its ability to reveal a coexisting toxic solvent. An industrial Fourier transform infrared analyzer was modified for breath testing. The sample cell fittings were widened and the cell size reduced in order to get an alveolar sample directly from a single exhalation. The performance and the feasibility of the Gasmet FT-IR analyzer were tested in clinical settings and in the laboratory. Actual human breath screening studies were carried out with healthy volunteers, inebriated homeless men, emergency room patients and methanol-intoxicated patients. A number of the breath analysis results were compared to blood test results in order to approximate the blood-breath relationship. In the laboratory experiments, the analytical performance of the Gasmet FT-IR analyzer and Dräger 7110 evidential breath analyzer was evaluated by means of artificial samples resembling exhaled breath. The investigations demonstrated that a successful breath ethanol analysis by Dräger 7110 evidential breath analyzer could exclude any significant methanol intoxication. In contrast, the device did not detect very high levels of acetone, 1-propanol and 2-propanol in simulated breath. The Dräger 7110 evidential breath ethanol analyzer was not equipped to recognize the interfering component. According to the studies the Gasmet FT-IR analyzer was adequately sensitive, selective and accurate for solvent intoxication diagnostics. In addition to diagnostics, the fast breath solvent analysis proved feasible for controlling the ethanol and methanol concentration during haemodialysis treatment. Because of the simplicity of the sampling and analysis procedure, non-laboratory personnel, such as police officers or social workers, could also operate the analyzer for screening purposes.

Fourier transform infrared microspectroscopy identifies protein propionylation in histone deacetylase inhibitor treated glioma cells

Histone deacetylase inhibitors (HDIs) have attracted considerable attention as potential drug molecules in tumour biology. In order to optimise chemotherapy, it is important to understand the mechanisms of regulation of histone deacetylase (HDAC) enzymes and modifications brought by various HDIs. In the present study, we have employed Fourier transform infrared microspectroscopy (FT-IRMS) to evaluate modifications in cellular macromolecules subsequent to treatment with various HDIs. In addition to CH3 (methyl) stretching bands at 2872 and 2960 cm1, which arises due to acetylation, we also found major changes in bands at 2851 and 2922 cm1, which originates from stretching vibrations of CH2 (methylene) groups, in valproic acid treated cells. We further demonstrate that the changes in CH2 stretching are concentration-dependent and also induced by several other HDIs. Recently, HDIs have been shown to induce propionylation besides acetylation [1]. Since propionylation involves CH2 groups, we hypothesized that CH2 vibrational frequency changes seen in HDI treated cells could arise due to propionylation. As verification, pre-treatment of cells with propionyl CoA synthetase inhibitor resulted in loss of CH2 vibrational changes in histones, purified from valproic acid treated cells. This was further proved by western blot using propionyl-lysine specific antibody. Thus we demonstrate for the first time that propionylation could be monitored by studying CH2 stretching using IR spectroscopy and further provide a platform for monitoring HDI induced multiple changes in cells. (C) 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

Studies of the intermolecular DNA triplexes of C+center dot GC and T center dot AT triplets by electrospray ionization Fourier-transform ion cyclotron resonance mass spectrometry

Formation and stabilities of four 14-mer intermolecular DNA triplexes, consisting of third strands with repeating sequence CTCT, CCTT, CTT, or TTT, were studied by electrospray ionization Fourier-transform ion cyclotron resonance mass spectrometry (ESI-FTICR-MS) in the gas phase. The gas-phase stabilities of the triplexes were compared with their CD spectra and melting behaviors in solution, and parallel correlation between two phases were obtained. In the presence of 20 mm NH4+ (pH 5.5), the formation of the TTT triplex was not detected in both solution and the gas phase.

Soil differentiation using fingerprint Fourier transform infrared spectroscopy, chemometrics and genetic algorithm-based feature selection

Elliott, G. N., Worgan, H., Broadhurst, D. I., Draper, J. H., Scullion, J. (2007). Soil differentiation using fingerprint Fourier transform infrared spectroscopy, chemometrics and genetic algorithm-based feature selection. Soil Biology & Biochemistry, 39 (11), 2888-2896. Sponsorship: BBSRC / NERC RAE2008