Abstract
Non-targeted methods (NTMs) are being increasingly developed and adopted to detect food fraud and identify the authenticity of the food. Method validation is a critical step before bringing the NTMs to the routine to be assured of method performance and trust that its outcomes are reliable. However, the paucity of well structured and harmonized validation strategies has been one of the hurdles, withholding the exploitation of NTMs. This report aims to describe a validation framework for methods that involve binary classification, which are prevalent in non-targeted workflows. We foresee this work to contribute to filling the current gap in the provisions for NTM method validation; perhaps also push the dialogue further to collectively resolve existing challenges.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Updated mathematical formulation and experimental designs; added new Figures 3 and 4, and relevant discussion aspects around them.