European Bee or Africanized Bee?

Barry Lavine Department of Chemistry Clarkson University Potsdam, N.Y. 13676

Dave Carlson Insects Affecting Man and Animals

Research Laboratory USDA, ARS P.O. Box 14565 Gainesville, Fla. 32604

In 1956 the African honeybee, Apis mellifera scutellata, was brought to Brazil for use in a bee-breeding pro­gram. The variety of honeybee that re­sulted from interbreeding the estab­lished European bee with the newly im­ported African type, referred to as the Africanized bee, has since dominated the bee fauna of Brazil and Venezuela. Swarms of Africanized bees have been found in North American ports aboard freighters arriving from South America and Panama.

Africanized honeybees have received considerable coverage in the popular press, including stories about hordes of bees stinging victims to death. Many reports have stressed the aggressive be­havior of this bee and the inherent dan­ger that Africanized bees pose for both man and domestic animals. The ability of Africanized honeybees to spread throughout much of South and Central America and the likelihood of their spreading into the United States has made them an object of much study.

One of the problems in studying Af­ricanized bees is the difficulty of un-

Species Identification Through Chemical Analysis The concentration of cuticular hydrocarbons can be used to obtain information about the identity of a bee specimen

equivocally identifying a colony (and particularly an individual bee) as Afri­canized or European. The current method of choice for the identification of Africanized bees is morphometric analysis. The morphometric procedure uses body measurements to identify samples of bees as Africanized or Euro­pean. Typically, an entomologist mea­sures the length of the forewing or the width of the metatarsus of an adult bee. On the basis of such measurements, the race of the bee often can be readily as­certained. These phenotypic charac­

ters, however, are not under simple and direct genetic control, which limits the utility of this approach.

We tried a different approach—mea­suring the concentration of cuticular hydrocarbons—to obtain information about the identity of a bee specimen. The cuticle can be viewed as a sheath that covers the entire body of the adult insect. Previous studies have shown that the high molecular weight hydro­carbons comprising the cuticle are of­ten characteristic of the insect's spe­cies. Therefore, use of these hydrocar­bons as taxonomic markers seemed logical. Clearly, with the advent of ad­vanced chemical instrumentation (e.g., computer-controlled capillary gas chromatographs and GC/MS systems), analyses of this type are routine. Fur­thermore, a chemical approach to tax­onomy also offers the added advantage of using characters that are under sim­pler and more direct genetic control.

To evaluate the feasibility of using cuticular hydrocarbons as taxonomic markers for the identification of Afri­canized honeybees, we obtained a large number of Africanized and European honeybee specimens from Central America, Venezuela, and Florida. The specimens, collected by professional apiculturists, were from three different social castes: nest bees, foragers, and drones.

The cuticular hydrocarbons were ob­tained from the bee specimens by first soaking them in hexane for about 15 minutes. The hydrocarbon fraction was then isolated from the concentrated

468 A · ANALYTICAL CHEMISTRY, VOL. 59, NO. 6, MARCH 15, 1987 0003-2700/87/0359-468A/$01.50/0 © 1987 American Chemical Society

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Figure 1. A gas-liquid chromatogram of cuticular paraffins from an individual Africanized forager. Kovat retention indices (Kl) were obtained using authentic fvparaffin stan­dards. The Kl values for the peaks used in the pattern recognition study were 2300, 2675, 2875, 3075, 3100, 3243, 3265, 3300, 3443, and 3465.

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Figure 2. A principal components representation of the pattern space defined by the 10 GC peaks for Venezuelan foragers. The first two principal components account for 65% of the total cumulative variance. The squares represent Africanized foragers, and the inverted trian­gles are European foragers.

ANALYTICAL APPROACH

with authentic η-paraffin standards, and Kovat retention indices (Kl) were assigned to compounds eluting from the gas chromatographic column. These Kl values were used for peak identification. A typical gas chromato­graphic trace for an Africanized honey­bee is shown in Figure 1.

Pattern recognition techniques were used in this study to analyze the gas chromatographic data. For pattern rec­ognition analysis, each chromatogram

Visually distinguishing the African­ized bee from its European cousin is virtually impossible.

was represented by a data vector X = (%i,x->, X;\, x.), xn), where com­ponent xj is the area of the vth peak. Such a vector also can be considered as a point in an η-dimensional Euclidean space. A set of chromatograms, there­fore, is represented by a set of points in an n-dimensional space. The expecta­tion is that points representing the chromatograms of Africanized honey­bees will cluster in a limited region of the space distant from the points corre­sponding to the European honeybees. Pattern recognition can be summa­rized as a collection of techniques that can help the scientist understand the structure of the data. (The data struc­ture is the overall relation of each sam­ple to every other sample in the data set.)

In this study, only 10 of the chro­matographic bands were considered for pattern recognition analysis (see Fig­ure 1). Compounds comprising these bands have been found in the comb wax produced by nest bees, and the concentration pattern of the wax con­stituents is believed to convey informa­tion about the genetic ancestry of the colony.

The first step was to use mapping and display techniques to examine the structure of the data. These techniques at tempt to illustrate relationships

between the samples and the measurements in the data space

by pictures and graphs. They can provide information about trends

present in the data. We used a technique called principal

components analysis to visualize the relative position of the data points (chromatograms) in the high-dimen­sional space. This technique can be summarized as a method for trans­forming the original variables (GC peak areas in our case) into new, uncor-related variables. The new variables are called principal components. Each principal component is a linear combi­nation of the original variables. The most informative principal component is the first, and the least informative is the last. Typically, the first two princi­pal components are used to generate a plot representing the relative position of the data points in the high-dimen­sional space.

In Figure 2, the results of a principal components mapping experiment are shown for 60 forager bee specimens from Venezuela. Half of the specimens are Africanized bees; the other half are European. The Africanized bees are well separated from the European bees in the two-dimensional map. These bees were collected from managed colo­nies that were maintained in the same apiary for more than four months. Therefore, differences between the hy­drocarbon profiles of the two groups cannot be attributed to nutritional or environmental factors and must be re­lated to the identity of the bees.

ANALYTICAL CHEMISTRY, VOL. 59, NO. 6, MARCH 15, 1987 · 469 A

hexane washings by a silica gel col-umn. Hexane was used as the elu-ent. The extracted hydrocarbons (equivalent to V25 of a bee) were ^ analyzed with packed column jg^ GC. They were co-injected

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Mapping experiments of this nature were also performed for a set of drone bees from Argentina and a set of nest bees from Panama and Costa Rica. In both experiments the Africanized bees were well separated from the European bees in the principal component space.

Having studied the structure of the data with mapping and display tech­niques, we then developed a classifica­tion rule. Nonparametric linear dis­criminant functions were used for these studies. They can be visualized as decision surfaces dividing a data space into different regions. For a binary classifier, the data space is divided into two regions. Chromatograms repre­senting Africanized honeybees will lie on one side of the decision surface; chromatograms characteristic of Euro­pean honeybees will lie on the other side.

The test data consisted of 109 chro­matograms of cuticular hydrocarbon extracts obtained from Africanized and European bee specimens (49 African­ized, 60 European). Foragers and nest bees were included in the training set. A discriminant function was developed from the 10 GC peaks for the purpose of separating Africanized bees from European honeybees. When the linear learning machine method was applied to the 10 GC peaks, it could correctly classify every sample in the training set. To further test the predictive abili­ty of these descriptors and the linear discriminant associated with them, a prediction set of 55 chromatograms (15 Africanized, 40 European) was em­ployed. The classification rule devel­oped from our training set (109 chro­matograms) correctly classified every chromatogram in the prediction set. These results demonstrate that infor­mation derived solely from the cuticu­lar hydrocarbons could correctly cate­gorize the bees by race (Africanized or European), which implies a direct rela­tionship between the concentration pattern of these compounds and the race of the bees.

The results of this study clearly dem­onstrate that the concentration pat­tern of cuticular hydrocarbons for honeybees conveys important taxo-nomic information. Thus an entomolo­gist can correctly identify the race of a given bee specimen simply by measur­ing the concentration of only a few hy­drocarbons. This approach to taxon­omy provides the biologist with a pow­erful new tool for investigating com­plex entomological systems. Further­more, species identification can now be placed firmly on a chemical basis.

Acknowledgments This research was supported by the Molecular Design Limited Corpora­tion. The authors thank Douglas Henry for critically reviewing the manuscript.

470 A · ANALYTICAL CHEMISTRY, VOL. 59, NO. 6, MARCH 15, 1987

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