Discrimination of Fungicide-Contaminated Lettuces Based on Maximum Residue Limits Using Spectroscopy and Chemometrics

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Autor(es): dc.contributorUniversidade Federal de Sergipe (UFS)-
Autor(es): dc.contributorUniversity of Coimbra-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorFederal Rural University of Pernambuco—UFRPE-
Autor(es): dc.creatorSteidle Neto, Antonio José-
Autor(es): dc.creatorde Lima, João L. M. P.-
Autor(es): dc.creatorJardim, Alexandre Maniçoba da Rosa Ferraz-
Autor(es): dc.creatorLopes, Daniela de Carvalho-
Autor(es): dc.creatorSilva, Thieres George Freire da-
Data de aceite: dc.date.accessioned2025-08-21T16:59:09Z-
Data de disponibilização: dc.date.available2025-08-21T16:59:09Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-08-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.3390/horticulturae10080828-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/308000-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/308000-
Descrição: dc.descriptionThe fast and effective monitoring of agrochemical residues is essential for assuring food safety, since many agricultural products are sprayed with pesticides and commercialised without waiting for the pre-harvest interval. In this study, we investigated the use of spectral reflectance combined with principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) to evaluate the discrimination of fungicide-contaminated lettuces, considering three maximum residue limits (MRLs) [3.5, 5, and 7 mg carbon disulphide (CS2) kg−1]. The non-systemic Mancozeb fungicide (dithiocarbamate) was adopted in this research. Spectral reflectance (Vis/NIR) was measured by a hand-held spectrometer connected to a clip probe with an integrating sphere. The lettuce spectra were pre-treated (centring, standard normal variate, and first derivative) before data processing. Our findings suggest that PCA recognised inherent similarities in the fungicide-contaminated lettuce spectra, categorising them into two distinct groups. The PLS-DA models for all MRLs resulted in high accuracy levels, with correct discriminations ranging from 94.5 to 100% for the external validation dataset. Overall, our study demonstrates that spectroscopy combined with discriminating methods is a promising tool for non-destructive and fast discrimination of fungicide-contaminated lettuces. This methodology can be used in industrial food processing, enabling large-scale individual analysis and real-time decision making.-
Descrição: dc.descriptionDepartment of Agrarian Sciences Federal University of São João del-Rei—UFSJ Campus Sete Lagoas, MG-
Descrição: dc.descriptionMarine and Environmental Sciences Centre—MARE Aquatic Research Network—ARNET Department of Civil Engineering Faculty of Sciences and Technology University of Coimbra-
Descrição: dc.descriptionDepartment of Biodiversity Institute of Biosciences São Paulo State University—UNESP, SP-
Descrição: dc.descriptionDepartment of Agricultural Engineering Federal Rural University of Pernambuco—UFRPE, PE-
Descrição: dc.descriptionDepartment of Biodiversity Institute of Biosciences São Paulo State University—UNESP, SP-
Idioma: dc.languageen-
Relação: dc.relationHorticulturae-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectdithiocarbamate-
Palavras-chave: dc.subjectLactuca sativaL-
Palavras-chave: dc.subjectspectral reflectance-
Título: dc.titleDiscrimination of Fungicide-Contaminated Lettuces Based on Maximum Residue Limits Using Spectroscopy and Chemometrics-
Tipo de arquivo: dc.typelivro digital-
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