Uncertainty and associated risks in the analysis of pesticides in homogeneous paprika samples

José Manuel Veiga-Del-Baño; Juan José Cuenca-Martínez; Pedro Andreo-Martínez; Miguel Ángel Cámara; José Oliva; Miguel Motas

doi:10.1016/j.foodchem.2023.136963

Uncertainty and associated risks in the analysis of pesticides in homogeneous paprika samples

Food Chem. 2023 Dec 15:429:136963. doi: 10.1016/j.foodchem.2023.136963. Epub 2023 Jul 21.

Authors

José Manuel Veiga-Del-Baño¹, Juan José Cuenca-Martínez¹, Pedro Andreo-Martínez², Miguel Ángel Cámara¹, José Oliva¹, Miguel Motas³

Affiliations

¹ Department of Agricultural Chemistry, Faculty of Chemistry, University of Murcia, Campus of Espinardo, 30100 Murcia, Spain.
² Department of Agricultural Chemistry, Faculty of Chemistry, University of Murcia, Campus of Espinardo, 30100 Murcia, Spain. Electronic address: pam11@um.es.
³ Department of Toxicology, Faculty of Veterinary, University of Murcia, Campus of Espinardo, 30100 Murcia, Spain.

PMID: 37499508
DOI: 10.1016/j.foodchem.2023.136963

Abstract

In this study, risk estimation based on sampling and subsampling uncertainty was performed for pesticide analysis in homogeneous spice products such as paprika. The results of the subsampling were also used to estimate the minimum weight necessary in subsampling to minimize overall uncertainty. The results show that subsampling has more uncertainty than sampling in the product due to high homogeneity in the manufacturer's batch. On the other hand, results using the Monte Carlo (MC) simulation on the size of the subsample indicate that uncertainty is lower for weights between 20 and 30 g and increases for sample sizes of 100 g. A sample size of 30 g was used for saffron, and the values simulated with the MC method were confirmed.

Keywords: Homogeneity; Pesticide residue analysis; Risk; Spice; Uncertainty.

MeSH terms

Capsicum*
Computer Simulation
Monte Carlo Method
Pesticides*
Uncertainty

Substances

Pesticides