Effectiveness of different sampling schemes in predicting adventitious genetically modified maize content in a smallholder farming system.

Abstract

When genetically modified (GM) maize is planted in an open field, it may cross-pollinate with the nearby non-GM maize under certain airflow conditions. Suitable sampling methods are crucial for tracing adventitious GM content. By using field data and bootstrap simulation, we evaluated the performance of common sampling schemes to determine the adventitious GM content in small maize fields in Taiwan. A pollen dispersal model that considered the effect of field borders, which are common in Asian agricultural landscapes, was used to predict the cross-pollination (CP) rate. For the 2009-1 field data, the six-transect (T_six), JM method for low expected flow (JM[L]), JM method for high expected flow (JM[H]), and V-shaped transect (T_V) methods performed comparably to simple random sampling (SRS). T_six, T_V, JM(L), and JM(H) required only 13% or less of the sample size required by SRS. After the simulation and verification of the 2009-2 and 2010-1 field data, we concluded that T_six, T_V, JM(L), and systematic random sampling methods performed equally as well as SRS in CP rate predictions. Our findings can serve as a reference for monitoring the pollen dispersal tendencies of maize in countries with smallholder farming systems.