Phenolic compounds in 46 Spanish cider apple varieties were determined by RP-HPLC with direct injection. Several pattern recognition procedures, including principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares (PLS-1), were applied to the data in an attempt to classify the samples into bitter and nonbitter categories. Reliable decision rules were obtai...

A method for the simultaneous spectrophotometric determination of nickel, cobalt and copper based on theformation of their complexes with 2-(2-Thiazolylazo)-p-Cresol (TAC) in micellar media of Triton X-100 isproposed. The absorbance spectra were recorded in the range of 500 to 800 nm. The linear concentrationrange for nickel, cobalt and copper in solution calibration sets were 0.05–1.80, 0.10–6...

Microarray data usually contain missing values, thus estimating these missing values is an important preprocessing step. This paper proposes an estimation method of missing values based on Partial Least Squares (PLS) regression. The method is feasible for microarray data, because of the characteristics of PLS regression. We compared our method with three methods, including ROWaverage, KNNimpute...

We provide an overview of how the underlying philosophy of chemometrics is integrated throughout metabonomic studies. Four steps are demonstrated: (1) definition of the aim, (2) selection of objects, (3) sample preparation and characterization, and (4) evaluation of the collected data. This includes the tools applied for linear modeling, for example, Statistical Experimental Design (SED), Princ...

The application of maximum likelihood multivariate calibration methods to the  uorescence emission spectra of mixtures of acenaphthylene, naphthalene, and phenanthrene in acetonitrile is described. Maximum likelihood principal components regression (MLPCR) takes into account the measurement error structure in the spectral data in constructing the calibration model. Measurement errors for the ...

An Instrument Surveillance and Calibration Verification (ISCV) system primarily consists of a process model, which is used to verify the output of the measurement instruments in that process. Artificial Neural Networks (ANNs) and Partial Least Squares (PLS) are two methods, which can be used for model development. The linear transformation of the PLS method provides a supervised reduction of th...

High order partial least squares (HOPLS) is a novel data processing method. It is highly suitable for building prediction model which has tensor input and output. The objective of this study is to build a prediction model of the relationship between sinoatrial node field potential and high glucose using HOPLS. The three sub-signals of the sinoatrial node field potential made up the model's inpu...

Early detection of cancer is crucial for successful treatments. In this paper, we propose a multiclass Logistic Partial Least Squares (LPLS) algorithm for classification of normal vs. cancer using Mass Spectrometry (MS). LPLS combines the multiclass logistic regression with Partial Least Squares (PLS) algorithm. Wavelet decomposition is also proposed for pre-processing of original data. Wavelet...

ATR-FTIR (Attenuated Total Reflectance Fourier Transform Infrared) spectra of prehardened epoxies with varying amounts of hardener and resin (mix ratio) have been acquired on a Midac FTIR spectrometer. The spectra form a set of training spectra for partial least-squares (PLS) analysis which was then used to analyze a series of epoxies of unknown mix ratio. The PLS model predicted the unknown mi...