Abstract

Most of the quality indicators regulated by the standard for seed potato certification are determined by the subjective component, that is, the competence of the personnel. However, the regulatory framework does not establish criteria for assessing competence, which poses uncontrolled risks in the laboratory. The purpose of the study is to develop and investigate the methodology for assessing the competence of laboratory personnel involved in the testing of seed potatoes and determine the extent of application of the methodology. The methods of probability theory and mathematical statistics are used for the tasks of selection and research of statistical criteria that correspond to the law of distribution of the obtained data and provide the necessary reliability for the available sample volumes. The statistics and the method of determining the threshold value, which mathematically describes the decision-making on competence, are provided for the binomial distribution law. The properties of the proposed statistical method for assessing the competence of personnel in terms of finding the maximum differences in the results of the analysis, at which the personnel are recognised as competent, are investigated. The study demonstrates the dependence of the method capacity on the data volume. It is determined that to obtain a confidence probability of 0.95 for quality indicators, the content of which in the average sample according to the technical conditions is minimal, the sample size should be 600-1000 tubers. At the same time, up to 100 tubers are sufficient for indicators whose content is under 5%. The method proposed by the authors showed that the average sample of 250 tubers recommended by the standard is entirely justified in terms of attracting resources during certification but must be adjusted during competence monitoring in a testing laboratory that confirms its competence by the requirements of DSTU ISO IEC 17025:2019. The findings presented can be used by the personnel in the seed testing laboratories as a measure to minimise the risks caused by the impact of personnel incompetence

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