Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)The development of a homogeneity study during the preparation of a wheat flour laboratory reference material (LRM) for use in the quantification of metals and metalloids is reported. Inductively coupled plasma optical emission spectrometry (ICP OES) was used with validation performed using a certified reference material of wheat flour furnished by the National Institute of Standards and Technology (NIST) Copper, Iron. manganese, phosphor, strontium and zinc were studied in a within-bottle homogeneity test whereas barium. copper, iron, zinc, manganese, strontium, phosphor and calcium were included in a between batch homogeneity study Standard univariate analysis of variance (ANOVA) was performed for all analytes Furthermore an alternative multivariate analysis for homogeneity is proposed by performing ANOVA of principal component scores and by inspection of principal component score graphs and hierarchical cluster analysis dendrograms The ANOVA F-tests performed on both, the univariate and multivariate parameters, were not significant at the 95% confidence level and indicated homogeneous wheat flour samples A 10kg amount of material was processed, which was distributed in 100 bottles, each containing 100 g For the between-bottle homogeneity test, three replicates were taken from each of 10 bottles selected of the 100 bottles obtained The results were evaluated using an F-test, which demonstrated no significant difference for the between-bottle results It is indicative that this material is homogeneous Afterwards, the influence of the sample mass on the homogeneity of the material was also evaluated by quantification of the elements for 100, 300, 500, 700 and 1000 mg sample masses with all the experiments being performed in triplicate The F-test was also used for evaluation of these results and demonstrated that the material is homogeneous for masses taken in the 100 to 1000 mg range All these results were further evaluated employing the principal component analysis (PCA) and hierarchical cluster analysis (HCA) multivariate techniques Both techniques also demonstrated that the material is perfectly homogeneous for use as laboratory reference material (C) 2009 Published by Elsevier B V952222226Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundacao de Amparo a Pesquisa do Estado da Bahia (FAPESB)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)