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This paper deals with the application of a new headspace solid-phase microextraction (HS-SPME) method developed in order to analyse the total amount of chloroanisoles in different kinds of cork stoppers (natural, agglomerated and sparkling wine stoppers). This parameter must be determined because these compounds can migrate from cork to wine giving it unpleasant musty taint and, therefore, undermine its organoleptic quality. Unlike the releasable amount of chloroanisoles, the total amount of chloroanisoles has no dependence of the method used for its determination so it can be used as a quality control parameter. The application of this method allowed the simultaneous determination of 2,4-dichloroanisole, 2,6-dichloroanisole, 2,4,6-trichloroanisole, 2,3,4,6-tetrachloroanisole and 2,3,4,5,6-pentachloroanisole.

This paper reports a new approach for validating bias in analytical methods that provide simultaneous results on multiple analytes. The validation process is based on a linear regression technique taking into account errors in both axes. The validation approach is used to individually compare two different chromatographic methods with a reference one. Each of the two methods to be tested is applied on a different set of data composed of two real data sets each. In addition, three different kinds of simulated data sets were used. All three methods are based on RP-high-performance liquid chromatography (HPLC) and are used to quantify eight biogenic amines in wine. The two methods to be tested use different derivatizing procedures: precolumn 6-aminoquinolyl-n-hydroxysuccinimidyl carbamate (AQC) and oncolumn o-phtalaldehyde (OPA), respectively. On the other hand, the reference method uses derivatization with OPA precolumn. Various analytes are determined in a set of samples using each of the methods to be tested and their results are regressed independently against the results of the reference method. Bias is detected in the methods to be tested by applying the joint confidence interval test to the slope and the intercept of the regression line which takes into account uncertainties in the two methods being compared. The conclusions about the trueness of the two methods being tested varied according to whether the joint confidence interval test was applied to data obtained from various biogenic amines considered simultaneously or individually.