Chemometrics and Intelligent Laboratory Systems

The corn dataset

gene datasets

Ozone raw data corresponding to the submitted paper: Chemometrics modelling of temporal changes of ozone half hourly concentrations in different monitoring stations Authoes: Mahsa Dadashi, David Pages Farre, Isabel Hernandez, Romà Tauler

Datasets for Spectra Data Classification: "FTIR_Spectra_instant_coffee.csv": contains a collection of 56 mid infrared diffuse reflectance (MIR-DRIFT) spectra of lyophilized coffee produced from two species: arabica (29 samples) and canephora var. robusta (27 samples). The data are described in full in the journal paper "Near- and Mid-Infrared Spectroscopies in Food Authentication: Coffee Varietal Identification" (Downey G. et al, J. Agric. Food Chem. 45 (11) 4357-4361 (1997)). "MIRFreshMeats.csv": Duplicate acquisitions from 60 independent samples. Raw data matrix size [448 x 120]. Obtained using Fourier transform infrared (FTIR) spectroscopy with attenuated total reflectance (ATR) sampling. As described in "Mid-infrared spectroscopy and authenticity problems in selected meats: a feasibility study" Al-Jowder O, Kemsley E K, Wilson R. H.(1997) Food Chemistry 59 195-20. "MIR_Fruit_Purees.csv": contains a collection of 983 Mid-infrared spectra collected from different authenticated fruit purees in one of two classes: "Strawberry" (purees prepared from fresh whole fruits by the researchers) and "NON-Strawberry" (diverse collection of other purees, including: strawberry adulterated with other fruits and sugar solutions; raspberry; apple; blackcurrant; blackberry; plum; cherry; apricot; grape juice and mixtures of these.Spectra were acquired from each puree using attenuated total reflectance (ATR) sampling. The acquisition order was randomized with respect to sample type. The data are described in more detail in the journal paper "Use of Fourier transform infrared spectroscopy and partial least squares regression for the detection of adulteration of strawberry purees" Holland JK, Kemsley EK, Wilson RH. (1998). Journal of the Science of Food and Agriculture, 76, 263-269 "FTIR_Spectra_olive_oils.csv": contains a collection of 120 Mid-infrared spectra collected from 60 different authenticated extra virgin olive oils, supplied to the Institute of Food Research, UK, by the International Olive Oil Council.Spectra were acquired from each oil using attenuated total reflectance (ATR) sampling. The acquisition order was randomized with respect to the country of origin code. Once all the samples had been examined once, a second acquisition session commenced, to produce a second spectrum from each sample. Again the acquisition order was randomized with respect to country of origin. thus, duplicate spectra were collected from all samples. The data are described in full in the journal paper "FTIR spectroscopy and multivariate analysis can distinguish the geographic origin of extra virgin olive oils" (Tapp H.S. et al, J. Agric. Food Chem. 51 (21) 6110-5 (2003)). These data are free to analyse and redistribute for academic purpose; if you do so, please acknowledge the original sources (webpage and/or citation above).

In those datasets, (X1,yy1), (X2,yy2), (X3,yy3) and (X4,yy4) are SIM1, SIM2, SIM3 and SIM4, respectively. In each dataset, X and yy are easy and hard to measure variables, respectively.

These images represent microorganisms culture experiments in Petri dishes using the SP-SDS technique. The images were acquired in a laboratory and include shadows, reflections, bubbles and agar contamination, including experiments with failed or unexpected results.

This is the author's dataset created to test the EEMlab application. It is composed by mixtures components (phenols and polyphenols) to test the EEMlab identifying and isolating them. Data for: EEMlab: a graphical user-firendly interface for fluorimetry experiments based on the drEEM toolbox Experimental dataset. The EEMs of the samples are acquired with a QuantaMaster fluorometer in order to illustrate how EEMlab manages different formats of files. Then, there are two important features in the dataset to consider: (i) the TXT formatted samples and (ii) the automatic spectral correction made by the acquisition device. It becomes also important that absorbance scans for IFE correction be acquired in CSV format with a Hitachi spectrophotometer. The original dataset is composed by: 34 EEM files, 34 absorbance files, 11 blank files, 11 water Raman scans and the slope of a Quinine sulfate dilution series. The Raman normalization is set in 350 nm excitation wavelength. All the files in the dataset are distributed into the correspondent folders’ structure. It is also provided de SampleLog file in where all the dependencies between the original files are detailed. In addition, some (Matlab formatted) examples of the processed dataset are provided in the 'OutputFiles' folder.

Software for first-order multivariate calibration developed as a MATLAB graphical user interface (GUI)

This spreadsheet demonstrates errors of partial integration of Gaussian peak using different rules. Peak section is digitized using 3,5,7,9,11 or 15 points. Integration is performed using Trapezoidal, Simpson's, and rules based on Euler-Maclaurin formula. Column with the name Euler-Maclaurin contains rule with properly calculated first derivative term. Columns Average rule 1, Average rule 2 and (Av.rule 1 + Av.rule2)/2 correspond to Euler-Maclaurin formula with 1st derivative calculated using finite differences as described in Theory section of the paper. True Euler-Maclaurin rule is always the best. Trapezoidal rule is preferable at very low data rates (less than 0.7 pts/sigma) and full area integration. Errors of Simpson's 1/3 and Average rule1, 2 and (Av.1+Av.2)/2 rules are comparable, as all of them account for the second derivative term of Taylor series and use finite differences.

Raman spectra collected from a 12 mm tablet using a LabRAM HR Evolution (HORIBA UK Ltd., Stanmore, UK) spectrometer system plus analysis script to annihilate spikes using a newly developed algorithm