Kernel Lot Distribution Assessment (KeLDA): a Comparative Study of Protein and DNA-Based Detection Methods for GMO Testing

Monitoring of market products for detection of genetically modified organisms (GMO) is needed to comply with legislation in force in many regions of the world, to enforce traceability and to allow official control along the production and the distribution chains. This objective can be more easily achieved if reliable, time and cost-effective analytical methods are available. A GMO can be detected using either DNA-based or protein-based methods; both present advantages and disadvantages. The objective of this work was to assess the performance of a protein-based (lateral flow strips—LFT) and of a DNA-based (polymerase chain reaction—PCR) detection method for GMO analysis. One thousand five hundred samples of soybean, deriving from the sampling of 15 independent bulk lots in large shipments, were analysed to assess and compare the performance of the analytical methods and evaluate their suitability for GMO testing. Several indicators were used to compare the performance of the methods, including the percentage correlation between the PCR and LFT results. The GMO content of the samples ranged from 0 up to 100 %, allowing a full assessment of both analytical approaches with respect to all possible GMO content scenarios. The study revealed a very similar performance of the two methodologies, with low false-negative and false-positive results, and a very satisfactory capacity of both methods in detecting low amounts of target. While determining the fitness for purpose of both analytical approaches, this study also underlines the importance of alternative method characteristics, like costs and time.