Using multiple natural enemies to manage whiteflies in commercial poinsettia production dataset

Published: 11 March 2021| Version 1 | DOI: 10.17632/vstyv6xtdx.1
Erfan Vafaie,
H. Brent Pemberton,
Mengmeng Gu,
David L. Kerns,
Micky D. Eubanks,
Kevin M. Heinz


Purpose was to determine the effectiveness of using biological control (two natural enemies: a parasitic wasp, Eretmocerus eremicus, and a predatory mite, Amblyseius swirskii) to manage sweetpotato whiteflies (Bemisia tabaci) on poinsettias compared to using regular insecticidal applications in commercial poinsettia production. This trial was conducted at three different commercial greenhouse grower operations in East Texas in 2019, each of which designated one greenhouse as the IPM greenhouse (using biological control) and the other as the conventional insecticide spray program (chemical control). In the biological control houses, natural enemies were released on regular intervals (weekly for E. eremicus and monthly for A. swirskii), whereas growers were able to use any chemical spray programs they were accustomed to in the chemical control house. Fifty randomly selected poinsettias and approximately 50 flagged (and re-visited) poinsettias were inspected weekly (maximum of 20 leaves each) in each greenhouse to quantify the number of whitefly nymphs, pupae, exuviae, and adults, E. eremicus adults and exuviae, and A. swirskii adults. Yellow sticky cards (four per greenhouse) were also established to quantify whiteflies, fungus gnats, or any other problematic pests. A weekly journal was kept to log natural enemy releases and any changes within the greenhouses. In general, the biological control managed greenhouses tended to have higher whitefly densities than their chemically-controlled counterparts; although there was no significant differences in the final density of whiteflies (i.e. last sampling week for biological control vs chemical greenhouses). A similar trend was seen for the proportion of poinsettias infested with whiteflies between the biological control vs chemical greenhouses. High variability in whitefly counts and difference in sampling period length between greenhouses made analysis via repeated measures ANOVA or GLMER unsuitable (i.e., violation of statistical assumptions). To develop a potential binomial sampling plan (i.e., whether proportion of poinsettias infested with whiteflies can predict whitefly density), the relationship between average immature whiteflies observed per plant (log-scale) and proportion of plants infested with whiteflies was modeled. Initial model composed of proportion of plants infested with immature whiteflies as a fixed factor, greenhouse nested within grower, and week number as random factors, and log-transformed mean immature whiteflies per plant as the response variable in a generalized linear mixed model (GLMM) using the lmer (Kuznetsova et al. 2017) function in R Studio (R Studio Team 2015). All random factors were considered non-significant and were removed from the final model. Proportion of poinsettias infested was a strong predictor of both log-transformed average immature whiteflies (p<0.001, adjusted r^2=0.898) and log-transformed maximum number of whiteflies (p<0.001, adjusted r^2=0.777).


Steps to reproduce

See provided R studio file and publication in Journal of Integrated Pest Management (publication information will be updated once available).


Horticulture, Entomology, Insect Pest Management, Biological Control, Integrated Pest Control, Parasitoids, Predators, Whitefly, Greenhouse