Rc. Venette et al., An in-field screen for early detection and monitoring of insect resistanceto Bacillus thuringiensis in transgenic crops, J ECON ENT, 93(4), 2000, pp. 1055-1064
We present a field-based approach to detect and monitor insects with resist
ance to insecticidal toxins produced ty transgenic plants. Out objective is
to estimate the phenotypic frequency of resistance in a population by rela
ting the densities of insects on genetically transformed plants to densitie
s on nontransformed plants. We focus on European corn borer, Ostrinia nubil
alis (Hubner), in sweet corn, Zea mays L., expressing Cry1Ab from Bacillus
thuringiensis subsp. kurstaki Berliner to illustrate principles underlying
the method. Thr probability of detecting one or more rare, resistant larvae
depends on sample size, the density of larvae on nontransformed plants. an
d an assumed frequency of resistant phenotypes in a given population. Proba
bility of detection increases with increases in sample size, background den
sity, or the frequency of resistant individuals. Following binomial probabi
lity theory, if a frequency of 10(-4) is expected. 10(3)-10(4) samples must
Le collected from a B. thuringiensis (Bt) crop to have at least a 95% prob
ability of locating one or more resistant larvae. In-field screens using tr
ansgenic crops have several advantages over traditional laboratory-based me
thods, including exposure to a large number of feral insects, discriminatio
n of resistant individuals based on Bt dosages expressed in the field, inco
rporation of natural and Bt-induced mortality factors, simultaneous monitor
ing for more than one insect species, and ease of use. The approach is amen
able to field survey crews working in research, extension, and within the s
eed corn industry. Estimates of the phenotypic frequency of resistance fron
t the in-field screen can Le useful for estimating Initial frequency of res
istant alleles. Bayesian statistical methods are outlined to estimate pheno
type frequencies, allele frequencies, and associated confidence intervals f
rom field data. Results of the approach are discussed relative to existing
complementary methods currently available for O. nubilalis and corn earworm
, Helicoverpa zea (Boddie).