Location: Pest Management and Biocontrol ResearchTitle: Modeling and regression analysis of semiochemical dose-response curves of insect antennal reception and behavior
Submitted to: Journal of Chemical Ecology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/16/2013
Publication Date: 8/15/2013
Citation: Byers, J.A. 2013. Modeling and regression analysis of semiochemical dose-response curves of insect antennal reception and behavior. Journal of Chemical Ecology. 39(8):1081-1089.
Interpretive Summary: Semiochemicals are released by organisms that when perceived by another organism cause it to change behavior. Insects use semiochemicals for communication, to find mates, or to locate or assess host plants. Many insect species have been studied to determine the relationship between concentration (dose) of a specific semiochemical and the corresponding insect behavioral response. Although it is generally recognized that these dose-response relationships are not linear, little information exists to indicate the true functional relationship between semiochemical dose and insect response. A computer simulation using a hypothetical insect antenna and a wide range of semiochemical doses indicated a family of mathematical equations, or functions, described the dose-response relationship nearly perfectly. The functions are based on kinetics of enzyme reactions that are known to function in reception of semiochemicals by antennae of insects. When more than 90 dose-response relationships extracted from the published literature were analyzed, 96 percent of those relationships were better described by the kinetic functions than by the more commonly used logarithmic function. The routine use of kinetic functions to describe dose-response relationships will allow more accurate predictions of insect behaviors, including captures of insects in traps, in relation to doses of semiochemicals. This research is important to optimize dosage of trap lures when monitoring for pest insects and when controlling them by mass trapping.
Technical Abstract: Dose-response curves with semiochemicals are reported in many articles in insect chemical ecology regarding neurophysiology and behavioral bioassays. Most such curves are shown in figures where the x-axis has order of magnitude increases in dosages versus responses on the y-axis represented by points connected by straight lines. The lack of regression curves indicates that the nature of the dose-response relationship in not well understood. Thus, a computer model was developed to simulate a flux of various numbers of pheromone molecules (1,000 to 5,000,000) passing by 10,000 receptors distributed among 1,000,000 positions along an insect antenna. Each receptor was depolarized by at least one strike by a molecule, and subsequent strikes had no additional effect. The simulations showed that with an increase in pheromone release rate, the antennal response would increase in a convex fashion and not in a logarithmic relation as suggested previously. Non-linear regression showed that a family of kinetic formation functions fit the simulated data nearly perfectly (R2 >0.999). This is reasonable because olfactory receptors are known to have proteins that bind to the pheromone molecule and are expected to exhibit enzyme kinetics. Over 90 dose-response relationships of electroantennographic and behavioral bioassays in the laboratory and field reported in the literature were analyzed by the logarithmic and kinetic formation functions. This analysis showed that in 95% of the cases the kinetic functions explained the relationships better than the logarithmic (mean of about 20% better). The kinetic curves become sigmoid when graphed on a log scale on the x-axis. Dose-catch relationships in the field are similar to dose-EAR (effective attraction radius, in which a spherical radius indicates the trapping effect of a lure) and the circular EARc used in mass trapping models. The use of kinetic formation functions for dose-response curves of attractants, and kinetic decay curves for inhibitors, will allow more accurate predictions of insect catch in monitoring and control programs.