This paper considers the statistical analysis of entomological count data from field experiments with genetically modified (GM) plants. Such trials are carried out to assess environmental safety. Potential effects on nontarget organisms (NTOs), as indicators of biodiversity, are investigated. The European Food Safety Authority (EFSA) gives broad guidance on the environmental risk assessment (ERA) of GM plants. Field experiments must contain suitable comparator crops as a benchmark for the assessment of designated endpoints. In this paper, a detailed protocol is proposed to perform data analysis for the purpose of assessing environmental safety. The protocol includes the specification of a list of endpoints and their hierarchical relations, the specification of intended levels of data analysis, and the specification of provisional limits of concern to decide on the need for further investigation. The protocol emphasizes a graphical representation of estimates and confidence intervals for the ratio of mean abundances for the GM plant and its comparator crop. Interpretation relies mainly on equivalence testing in which confidence intervals are compared with the limits of concern. The proposed methodology is illustrated with entomological count data resulting from multiyear, multilocation field trials. A cisgenically modified potato line (with enhanced resistance to late blight disease) was compared to the original conventional potato variety in the Netherlands and Ireland in two successive years (2013, 2014). It is shown that the protocol encompasses alternative schemes for safety assessment resulting from different research questions and/or expert choices. Graphical displays of equivalence testing at several hierarchical levels and their interpretation are presented for one of these schemes. The proposed approaches should be of help in the ERA of GM or other novel plants.

Equivalence analysis to support environmental safety assessment: Using nontarget organism count data from field trials with cisgenically modified potato

Arpaia S.
2019-01-01

Abstract

This paper considers the statistical analysis of entomological count data from field experiments with genetically modified (GM) plants. Such trials are carried out to assess environmental safety. Potential effects on nontarget organisms (NTOs), as indicators of biodiversity, are investigated. The European Food Safety Authority (EFSA) gives broad guidance on the environmental risk assessment (ERA) of GM plants. Field experiments must contain suitable comparator crops as a benchmark for the assessment of designated endpoints. In this paper, a detailed protocol is proposed to perform data analysis for the purpose of assessing environmental safety. The protocol includes the specification of a list of endpoints and their hierarchical relations, the specification of intended levels of data analysis, and the specification of provisional limits of concern to decide on the need for further investigation. The protocol emphasizes a graphical representation of estimates and confidence intervals for the ratio of mean abundances for the GM plant and its comparator crop. Interpretation relies mainly on equivalence testing in which confidence intervals are compared with the limits of concern. The proposed methodology is illustrated with entomological count data resulting from multiyear, multilocation field trials. A cisgenically modified potato line (with enhanced resistance to late blight disease) was compared to the original conventional potato variety in the Netherlands and Ireland in two successive years (2013, 2014). It is shown that the protocol encompasses alternative schemes for safety assessment resulting from different research questions and/or expert choices. Graphical displays of equivalence testing at several hierarchical levels and their interpretation are presented for one of these schemes. The proposed approaches should be of help in the ERA of GM or other novel plants.
2019
environmental risk assessment; equivalence test; hierarchical analysis; limit of concern; multicriteria decision analysis; overdispersed Poisson
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12079/52750
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