Visual examination of visually recognisable substances, including microscopy, focus on targets or contaminants such as particles of animal origin, plant seeds, spore bodies of moulds, sclerotia, packaging material, microplastic and 'Besatz' (everything that differs from the norm). The two principal results are counts (numbers) and weights for macroscopic methods, or presence/absence for microscopic methods. The level of detection equals at least the size of one unit, usually with a weight exceeding 1 mg, which is in the range of parts per million (ppm). These parameters do not follow a normal distribution but Poisson (counts), lognormal (weights) or binomial (Booleans) distributions, with effect on the interpretation of validation parameters. As for other domains, examination methods for visual monitoring need to be properly validated and quality control during actual application is needed. In most cases procedures for validation of visual methods are based on principles adopted from other domains, such as chemical analysis. A series of examples from publications show inconsistent or not correct implementations of these validation procedures, which stress the need for dedicated validation procedures. Identification of legal ingredients and composition analysis in the domain of visual examination relies on the expertise of the laboratory staff, therefore validation of a method usually includes the validation of the expert. In the view of these specific circumstances, a Guidance for quality assurance and control of visual methods has been developed, which are being presented and discussed in this paper. The general framework of the Guidance is adopted from ISO standards (17023, 17043, 13528). Part 1 of the Guidance includes the general background, theory and principles. Part 2 presents the actual validation procedures with experimental designs and equations for calculating the relevant parameters, and can be used as blueprint for a SOP in a quality management system. An EURL and NRL network for physical hazards is strongly recommended.
Keywords: Microscopy; in-house validation; particles; quality assurance; visual methods.