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dc.contributor.authorSarabia Peinador, Luis Antonio 
dc.contributor.authorValencia García, Olga 
dc.contributor.authorOrtiz Fernández, Mª Cruz 
dc.date.accessioned2023-07-13T11:53:08Z
dc.date.available2023-07-13T11:53:08Z
dc.date.issued2023-09
dc.identifier.issn0169-7439
dc.identifier.urihttp://hdl.handle.net/10259/7757
dc.description.abstractWhen the prevalence of positive samples in a whole population is low, the pooling of samples to detect them has been widely used for epidemic control. However, its usefulness for applying analytical screening procedures in food safety (microbiological or allergen control), fraud detection or environmental monitoring is also evident. The expected number of tests per individual sample that is necessary to identify all ‘positives’ is a measure of the efficiency of a sample pooling strategy. Reducing this figure is key to an effective use of available resources in environmental control and food safety. This reduction becomes critical when the availability of analytical tests is limited, as the SARS-CoV-2 pandemic showed. The outcome of the qualitative analytical test is binary. Therefore, the operation governing the outcome of the pooled samples is not an algebraic sum of the individual results but the logical operator (‘or’ in natural language). Consequently, the problem of using pooled samples to identify positive samples naturally leads to proposing a system of logical equations. Therefore, this work suggests a new strategy of sample pooling based on: i) A half-fraction of a Placket-Burman design to make the pooled samples and ii) The logical resolution, not numerical, to identify the positive samples from the outcomes of the analysis of the pooled samples. For a prevalence of ‘positive’ equal to 0.05 and 10 original samples to be pooled, the algorithm presented here results in an expected value per individual equal to 0.37, meaning a 63% reduction in the expected number of tests per individual sample. With sensitivities and specificities of the analytical test ranging from 0.90 to 0.99, the expected number of tests per individual ranges from 0.332 to 0.416, always higher than other pooled testing algorithms. In addition, the accuracy of the algorithm proposed is better or similar to that of other published algorithms, with an expected number of hits ranging from 99.16 to 99.90%. The procedure is applied to the detection of food samples contaminated with a pathogen (Listeria monocytogenes) and others contaminated with an allergen (Pistachio) by means of Polymerase Chain Reaction, PCR, test.en
dc.description.sponsorshipThis work was supported by Consejería de Educación de la Junta de Castilla y León through project BU052P20 co-financed with European Regional Development Funds. The authors thank Dr. Laura Rubio for applying the double-blind protocol to dope the samples and AGROLAB S.L.U, Burgos (Spain) for the careful preparation of the pooled samples.en
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofChemometrics and Intelligent Laboratory Systems. 2023, V. 240, 104902en
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectSample poolingen
dc.subjectSupersaturated designsen
dc.subjectLogical modelingen
dc.subjectAllergen (Pistachio)en
dc.subjectPathogen (Listeria monocytogenes)en
dc.subjectPolymerase chain reactionen
dc.subject.otherQuímica analíticaes
dc.subject.otherChemistry, Analyticen
dc.subject.otherMatemáticases
dc.subject.otherMathematicsen
dc.titleLogical analysis of sample pooling for qualitative analytical testingen
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.relation.publisherversionhttps://doi.org/10.1016/j.chemolab.2023.104902es
dc.identifier.doi10.1016/j.chemolab.2023.104902
dc.relation.projectIDinfo:eu-repo/grantAgreement/Junta de Castilla y León//BU052P20//Nuevos desarrollos metodológicos del diseño de experimentos para análisis químicos, bioquímicos y en tecnología analítica de procesoses
dc.journal.titleChemometrics and Intelligent Laboratory Systemsen
dc.volume.number240es
dc.page.initial104902es
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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