Successive projections algorithm applied to spectral data for the simultaneousdetermination of flavour enhancers

C. ACEBAL; MARCOS GRÜNHUT; ADRIANA G. LISTA; BEATRIZ S. FERNÁNDEZ BAND

TALANTA

ELSEVIER SCIENCE BV

Año: 2010 vol. 82 p. 222 - 226

0039-9140

A novel variable selection strategy for multiple lineal regression (MLR), the successive projections algorithm(SPA), was applied to spectrophotometric data (190–320 nm) for the simultaneous determinationof monosodium glutamate (MSG), guanosine-5-monophosphate (GMP) and inosine-5-monophosphate(IMP) in dehydrated broths samples. This selection method uses simple operations in a vector space tominimize variable collinearity and has become an interesting variable selection strategy for multivariatecalibration. In this work, nine, six and four wavelengths for MSG, GMP and IMP, respectively, wereselected to construct calibrations models in order to solve successfully the serious spectral overlapping insamples containing these analytes. The relative errors of prediction (REP) for the validation set were 2.3%,0.9% and 1.8% for MSG, GMP and IMP, respectively. Commercial samples were analysed and a recoverystudy was carried out to verify the accuracy of the proposed method with satisfactory results. A continuousflow system was used to develop a simple, cheap and rapid method (sample throughput: 200 h−1),without any previous extraction step.