AI Article Synopsis

  • Carrots from different agricultural regions were analyzed using advanced UHPLC-HRMS techniques to identify chemical markers.
  • An in-house workflow helped process data, leading to the development of models for distinguishing carrots from New Aquitaine and Normandy regions, with specific compounds like arginine and 6-methoxymellein identified as potential markers.
  • Discriminating carrots by production mode (organic vs. conventional) proved more difficult, showing only limited trends and unsatisfactory model metrics.

Article Abstract

Carrots produced in different agricultural regions with organic or conventional mode were analyzed by untargeted UHPLC-HRMS using reversed-phase and HILIC modes. Data were first treated separately, and further combined to possibly improve results. An in-house data processing workflow was applied to identify relevant features after peak detection. Based on these features, discrimination models were built using chemometrics. A tentative annotation of chemical markers was performed using online databases and UHPLC-HRMS/MS analyses. An independent set of samples was analyzed to assess the discrimination potential of these markers. Carrots produced in the New Aquitaine region could be successfully discriminated from carrots originating from the Normandy region by an OLPS-DA model. Arginine and 6-methoxymellein could be identified as potential markers with the C18-silica column. Additional markers (N-acetylputrescine, l-carnitine) could be identified thanks to the polar column. Discrimination based on production mode was more challenging: some trend was observed but model metrics remained unsatisfactory.

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Source
http://dx.doi.org/10.1016/j.foodchem.2023.136273DOI Listing

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