Common pillar across the risk assessment strategies implemented worldwide for genetically modified plants is the comparison of their compositional profile to that of conventional counterparts deemed safe. If differences are observed, those that cannot be attributed to natural variation are further evaluated for their safety relevance. This principle is clear, but its implementation is challenging. Here we first discuss the difficulties of estimating natural variation of crop-specific compositional end-points and the various attempts made, together with their advantages and limitations. Second we present the empirical distribution curves of compositional end-points for two crops bearing a large commercial interest worldwide, maize and soybean. These curves provide novel information on end-point specific variability relevant for further progressing in the risk assessment process.
Keywords: compositional analysis; empirical distribution; equivalence testing; food safety; maize; natural variability; soybean.