Binding the gap between experiments, statistics, and method comparison: A tutorial for computing limits of detection and quantification in univariate calibration for complex samples

Abstract

The present tutorial aims to review the most frequently reported criteria for the calculation of the limits of detection (LOD) and quantification (LOQ) in univariate calibration, summarizing their fundamentals, advantages, and limitations. The current criteria for estimating LOD and LOQ are based on diverse theoretical and/or empirical assumptions and require different amounts of experimental data, making the calculation rather complex in some cases. Moreover, alternative forms for calculating LOD/LOQ frequently lead to dissimilar results. This scenario might worsen in the case of complex analytical systems. Throughout this tutorial, different forms of calculating LOD/LOQ are illustrated using previously reported experimental datasets in the environmental chemistry field as examples. The influence of the sample matrix during the estimation of LOD/LOQ parameters is investigated through one calibration approache. The discrepancies in the obtained results with different criteria for the calculation of LOD/LOQ are highlighted. Finally, general guidelines and recommendations regarding experimental and data processing issues are proposed, aiming to promote fair criteria for the comparison of different analytical methodologies in terms of prediction ability and detection capability.