Joumal oj Chemical Ecology, Vol. 17, No.2, 1991

HOST-DERIVED VOLATILES AS ATTRACTANTS AND PHEROMONE SYNERGISTS FOR DRIEDFRUIT BEETLE, Cmpophilus hemipterusl

PATRICK F. DOWD2.* and ROBERT 1. BARTELT 3

2Mycotoxin and 3BioacTive ConsTituenTs Research UniTs National Cellier jor Agricultural UTilizaTion Research USDA, Agriculrural Research Service Peoria, lllinois 61604

(Received July 10. 1990; accepted September 21, 1990)

Abstract-The attractiveness of representative host materials, host extracts, and individual host volatiles (primarily carboxylic acids, alcohols, and esters) to Carpophilus hemipTerus (L.) (Coleoptera: Nitidulidae) adults in wind-tun­ nel bioassays was examined. Attractiveness of the materials was examined alone and in combination with the aggregation pheromone. Host materials and extracts were often attractive on their own, and the attractancy was syner­ gized when they were combined with the pheromone. Propanoic and butanoic acids, methanol, 2-propanol, I-heptanol, methyl butanoate, and propanal were among the most effective attractants relative to the pheromone, but many other compounds significantly synergized the pheromone (typically three- to four fold). Attractiveness and synergism were influenced by the carbon chain length and branching of the substitutents. Straight-chain compounds that had at least three carbon atoms were generally effective as synergists. Many branched-chain compounds were also effective synergists. In general, the degree of attractiveness and synergism could be predicted fairly well with the physicochemical steric (Es) parameter. although the lipophilicity (Pi) param­ eter also appeared to be useful in explaining the lower activity of short-chain substituems. Thus, many compounds that had only limited attractiveness on their own may nevertheless play and important role in synergizing the pher­ omone. Structure-activity studies appear to be appropriate not only for deter­ mining optimal attractants for these insects, but also for determining effective synergists for the pheromone.

'To whom correspondence should be addressed. I The mention of firms or trade names does not imply that they are endorsed or recommended by the U.S. Department of Agriculture over other firms or similar products not mentioned.

285 286 DOWD AND BARTELT

Key Words-Pheromone, aggregation, synergism, ester, carboxylic acid, alcohol, carboxylic ester, driedfruit beetle, Carpophilus hemiplerus, Coleop­ tera, Nitidulidae.

INTRODUCTION

The use of host-derived volatiles to locate suitable hosts is important in many insects, including the Coleoptera (Metcalf, 1987). Aggregation pheromones also are produced by many Coleoptera (Jones, 1985). Host-derived volatiles and aggregation pheromones also can interact to produce synergized attraction of bark beetles (Jones, 1985). An increasing number of studies (e.g., Walgenbach et aI., 1987; Burkholder, 1988; Oehlschlager et aI., 1988) also have demon­ strated that stored-product beetle attraction is synergistically enhanced by com­ bining aggregation pheromones and host volatiles. However, synergized attraction of insects by combinations of host volatiles and pheromones is just beginning to be appreciated as a widespread phenomenon. The driedfruit beetle, Carpophilus hemipterus, is a cosmopolitan pest of fresh and dried fruit, as well as many fresh and stored grains, spices, drugs, and seeds (Hinton, 1945). Past information indicates these insects also are attracted by host odors (especially fermenting ones) or isolated volatiles (Smi­ lanick et aI., 1978; Blackmer and Phelan, 1988). For example, a 1: 1: 1 com­ bination of ethanol-acetaldehyde-ethyl acetate was a highly effective combination for attracting C. hemipterus (Smilanick et aI., 1978). Fermented baits have been used successfully to reduce populations of this insect when the insects collected by the traps were not immediately killed (Warner, 1960, 1961). However, poisoned attractive baits were not able to outcompete naturally ripe (and presumably fermenting) figs in orchards (Smilanick, 1979). This infor­ mation suggests that a combination ofaggregation pheromone and host volatiles is necessary to equal the attraction of natural host materials with insects present and could potentially involve synergism as well. Bartelt et ai. (1990a) recently reported the first example of an aggregation pheromone from nitidulids, which interacts synergistically with some host volatiles. To further examine this important interaction, host materials, host extracts, and individual host-derived volatiles were combined with the pheromone of C. hemipterus and tested for relative attractiveness versus individual components in wind-tunnel bioassays. Structure-activity studies of individual host components combined with the pheromone extract also were run to determine ifoptimal host-derived individual attractancy, synergism, and overall attractancy could be predicted by quantita­ tive analysis of physiocochemical parameters or use of other structural relation­ ships. DRIEDFRUIT BEETLE PHEROMONE SYNERGISTS 287

METHODS AND MATERIALS

Insects. The C. hemipterus were reared according to previously described methods (Dowd, 1987). Adults used in assays were 7-10 days old. The insects were conditioned for flight by 16 hr starvation (see Bartelt et aI., 1990a). Hosts and Chemicals. Whole oranges, bananas, and apple juice were obtained from a local grocery store. Oranges were squeezed for juice immedi­ ately before the assays. Milk-stage dent com was obtained from greenhouse­ grown plants. The Saccharomyces cerevisae used was a baker's yeast strain (Fleishman's dried activated). The culture of the wild yeast, Zygosaccharo­ myces bailii, a common contaminant of fermenting fruit (NRRL Y-2227), was obtained from the Northern Regional Research Center culture collection. Bananas were fermented with the two yeast strains by sprinkling or loop inoc­ ulating the freshly cut surface and capping in 35 ml cups. The liquid produced by the fermentation (after two months) was used in assays. Fresh S. cerevisae were obtained by sprinkling the dry yeast onto potato dextrose agar and scraping the colonies off the surface after two weeks. These yeast were made up as a 10 % suspension in distilled water. Individual host volatiles and sources are reported in Table 1. A series of acids, alcohols, methyl esters, and acetate esters were used to determine structure-activity relationships. Wind- Tunnel Bioassays. Assays were performed according to previously reported methods (Bartelt et aI., 1990a). Briefly, ca. 300-600 starved insects were assayed at one time. Disks of filter paper (Whatman 541 or related, 7 cm diameter) were folded into quarters, treated with the liquid attractant(s), and hung with binder clips ca. 30 cm apart and 40 cm above the floor in the upwind end of the wind tunnel. The pheromone and host volatile were applied to dif­ ferent areas of the filter paper when tested in combination. For the liquid attrac­ tants, 20-ILI quantities were applied to the folded filter paper. Esters, alcohols, aldehydes, ketones, and acids were applied as 10% solutions/suspensions in mineral oil, since these conditions provided a concentration and release rate previously proven effective in the field (Smilanick et aI., 1978) and found to be effective in our wind-tunnel assays (see Results). When chemicals were com­ bined in solution, the total contribution of an individual chemical was 10 %. The pheromone source was the hydrocarbon fraction from extracts of cultures that contained male beetles (Bartelt et aI., 1990). The concentration of the most abundant pheromone component, (2E,4E,6E,8E)-3,5,7-trimethyl-2,4,6,8­ decatetraene, was ca. 50 pg/ILl when quantitated by gas chromatography; 20 ILl of this extract was used in each test (ca. 1 ng of the major component and proportional amounts of the cooccurring components). Comparisons of this ini­ tial material and an isolated Tenax-trapped volatile extract developed after the start of these assays (Bartelt et aI., 1990a) did not yield significantly different results for representative combinations, so the diet extract was used throughout 288 DOWD AND BARTELT

TABLE 1. CHEMICALS. SOURCES. AND PURITIES"

Purity Compound Source (%)

Alcohols Methanol EM Labs 99.9 Ethanol USICC 100 I-Propanol Aldrich 99.7 2-Propanol (isopropyl alcohol) Baker 99.8 I-Butanol Fisher 99.95 2-Methyl-I-propanol (isobutyl alcohol) Aldrich 99.9 2-Butanol (s-butyl alcohol) Aldrich 99+ 2-Methyl-2-propanol (I-butyl alcohol) Aldrich 99+ 2-Methyl-l-butanol Aldrich 99+ I-Pentanol Aldrich 99+ l-Heptanol Sigma 99 Acids Formic Aldrich 95 Acetic EM Labs 99.7 Propanoic Sigma 99 Butanoic Aldrich 99+ 2-Methylpropanoic (isobutyric) Aldrich 99+ Pentanoic Kodak 98 3-Methylbutanoic (isovaleric) Aldrich 99 2-Methylbutanoic Kodak 99 2.2-Dimethylpropanoic Aldrich 99 3-Methylpentanoic Aldrich 97 4-Methylpentanoic Kodak 99 2.2-Dimethylbutanoic Aldrich 96 Acetate esters Methyl acetate PolySciences 98+ Ethyl acetate MCB 99.5 Propyl acetate PolySciences 98+ I-Methylethyl (isopropyl) acetate PolySciences 98+ Butyl acetate Aldrich 99+ 2-Methylpropyl (isobutyl) acetate PolySciences 98+ I-Methylpropyl (s-butyl) acetate PolySciences 98+ 1.I-Dimethylethyl (I-butyl) acetate PolySciences 98+ Pentyl acetate MCB 98 3-Methylbutyl (isopentyl) acetate PolySciences 98+ I-Methylbutyl (s-pentyl) acetate PolySciences 98+ 2-Methylbutyl acetate PolySciences 98+ I-Ethylpropyl acetate PolySciences 98+ OctyI acetate Aldrich 99+ Methyl esters Methyl formate PolySciences 98+ Methyl acetate PolySciences 98+ Methyl propanoate PolySciences 98+ DRIEDFRUIT BEETLE PHEROMONE SYNERGISTS 289

TABLE 1. Continued

Purity Compound Source (%)

Methyl butanoate PolySciences 98+ Methyl 2-methylpropanoate (isobutyrate) PolySciences 98+ Methyl pentanoate PolySciences 98+ Methyl 3-methylbutanoate (isovalerate) PolySciences 98+ Methyl 2-methylbutanoate PolySciences 98+ Methyl 2.2-dimethylpropanoate (I-valerate) PolySciences 98+ Methyl 4-methylpentanoate PolySciences 98+ Other esters Ethyl propanoate Sigma 99+ Ethyl butanoate Aldrich 99+ Ethyl 2-methylpropanoate (isobutyrate) Aldrich 99+ Ethyl 3-methylbutanoate (isovalerate) Sigma NS PropyI propanoate Aldrich 99+ Heptyl hexanoate (caproate) Pfaltz & Bauer NS Other compounds Water In-house 99+ Acetaldehyde Baker NS Propanal Aldrich 99+ Pentanal Aldrich 99 2-Pentanone Aldrich 97 2-Hydroxypropanoic acid (lactic acid) Fisher 85

a Branched compounds listed as methyl or ethyl derivitives for ease of considering location of branching to synergistic effects. NS = not specified. this study for the sake of consistency. Two treatments were always compared in the wind tunnel at one time. The test duration was always 3 min. The number of beetles landing on each treatment was recorded. Experimental Design. To evaluate each host volatile for attractiveness and synergistic activity, an experiment was conducted involving three treatments: the host volatile (A), the pheromone (P), and the host volatile plus the phero­ mone (A + P). These treatments were compared two at a time, and all possible combinations were tested an equal number of times (a balanced, incomplete block design). In general, each treatment was used a total of eight times. Treat­ ment positions in the wind tunnel were reversed in successive replications to eliminate potential bias due to position effects. The pheromone served as a relative control in these experiments. Our experience has been that counts for a particular treatment over the 3-min bioassay period varied widely over different days, depending on the num­ ber of beetles in the wind tunnel. The paired experimental design was used to 290 DOWD AND BARTELT compensate for this variability, and the ratio of counts for two paired treatments tended to remain very constant despite changes in overall beetle numbers or activity. Three ratios were of particular interest in this study. The first ratio, the bioassay count for the test volatile alone plus the bioassay count for the pher­ omone alone, divided by the counts for the pheromone treatments alone (rela­ tive attractancy, RA), expressed the activity of the volatiles relative to a "standard" attractant (the pheromone). An RA of 1.0 indicated no attractancy of the attractant by itself. The second value, the synergist ratio (SR), was the bioassay count for the pheromone combined with the host volatile, divided by the sum of the counts for the separated pheromone and volatile treatments. This ratio expressed the degree that the activity of the combined attractants exceeded the total activity of the separate attractants. An SR of 1.0 indicated the absence of synergism, in this case the resulting attractancy was merely additive. The third value, the total attractancy (TA), is the same as the relative attractancy times the synergist ratio. It is defined as the counts for the pheromone combined with the host volatile divided by the counts for the pheromone alone. Once again, a TA value of 1.0 indicated no attractancy relative to the pheromone. These values are more fully defined in the Results section, where actual data are examined. One initial test involved a filter paper blank to see if a blank yielded useful information. Two additional experiments were run to evaluate the stability of beetle activity and the relative attractiveness of a treatment over time. Stability of these values is necessary to make relevant comparisons of synergistic activ­ ity. The first of these two experiments involved examining the attractancy of apple juice and the pheromone over time after the insects were released directly into the cage. The activity was examined at constant intervals until a few hours after the number of responses peaked (22 total hr). Three 3-min tests were run every half hour, with 15 min between each group of tests. The second experiment involved pheromone, octyl acetate, and octyl ace­ tate plus pheromone in the balanced, incomplete block design and was run repeatedly for eight consecutive hours after starving the beetles overnight in the same manner as described for the apple juice assays. RA, SR, and TA ratios were calculated for each hourly segment (see Results). The bulk of the study involved testing host materials, extracts, and vola­ tiles in a balanced, incomplete block design such that there were eight repli­ cations of each treatment per hour (twelve 3-min tests per hour, with 2 min between tests). In cases where responses to the compounds were weak, the response of the insects was retested with a complex known to be effective (e.g., pheromone plus propyl acetate or octyl acetate) in order to ensure the insects were in a responsive mode. DRIEDFRUIT BEETLE PHEROMONE SYNERGISTS 291

In the final series of experiments, octyle acetate was used as a standard attractant for evaluating the relative synergistic activity of other host volatiles. The three treatments were: the pheromone, octyl acetate plus the pheromone, and the host volatile plus the pheromone. Once again, the balanced, incomplete block design was used. Statistical Analyses. All bioassay experiments were analyzed by categori­ cal methods (chi-square tests) applying a model of quasiindependence to the incomplete block designs (Fienberg, 1977; Bartelt et aI., 1990b). Statistical tests were performed first to determine whether departures from this model were within allowable limits. A small chi-square statistic (large P value) for the model of quasiindependence indicated the model described the data set adequately. In our large series of experiments, we expected 95 % of the chi-square statistics to have P values >0.05. This expectation was largely met (P > 0.05 for 109 of 116 experiments), validating subsequent tests on treatment effects. Thus, cat­ egorical analysis appeared to be appropriate for our data. The use of ratios of fitted values to summarize treatment effects followed naturally from the qua­ siindependence model. Conditional G 2 tests (analogous to t tests in analysis of variance; see Feinberg, 1977, p. 47) were used to test for the equivalence of treatments or the importance of other effects of interest, such as blocking effects. The treatments were concluded to differ if P < 0.05 when this statistic was compared with the chi-square distribution. Further details and examples of the statistical tests are provided in the Results. Since prior work (Bartelt et aI., 1990a) indicated synergism between the pheromone and host-derived volatiles could occur, we wished to determine when synergism was statistically significant. The presence of synergism could be tested for if the number of beetles responding to a treatment remained effec­ tively constant within each set of three consecutive tests [P vs. A, P vs. (P + A), and A vs. (P + A)], regardless of what the treatment was paired with (in other words, if the six data values could be viewed as coming from one large block rather than three incomplete blocks-without inflating residual variance). Conditional tests indicated this interpretation was usually justified. A condi­ tional G2 statistic was constructed to determine whether the total responses to P plus the total responses to A differed from the total for (P + A) (i.e., whether SR > 1). Quantitative Structure-Activity Analysis. The use of physiocochemical parameters to allow mathematical correlation between chemical structure and biological activity permits a better understanding of biological phenomena as influenced by chemical perturbation. Due to the obvious influence of branching and chain length on different types of attractancy (RA, SR, and TA), we con­ centrated on use of the sigma * electronic parameter, the Taft steric parameter (Es), and the Pi constant, respectively, in an attempt to evaluate the quantitative contribution of these types of modifications to the relative activity of alcohols, 292 DOWD AND BARTELT acids, and esters tested. Values from the monograph of Hansch and Leo (1979) were used to attempt to evaluate activity based on electronic, steric, and lipo­ philic influences. Values were not available for all compounds that were tested. Initially, values were plotted to determine appropriate models for correlation analyses (e.g., linear, logarithmic) and to determine appropriate portions to consider in substituent analysis (e.g., include or exclude the carbon atom with the functional group in the carbon chain length). The MAXR STEPWISE pro­ cedure (SAS Institute, 1985) was used to obtain substituent constants for one­ and two-parameter models and included reports of correlation coefficients and probability values. Plots were examined in light ofcorrelation values to visually determine outliers, which might obscure underlying relationships. The proce­ dure then was rerun without these values to see if better correlation resulted­ up to an r 2 of 0.7 or 0.8. Typically, this only involved the removal of one or two points.

RESULTS

Properties ofBioassays One property of the bioassay is that beetles land extremely rarely on filter paper blanks. The mean count for such a control was near zero in all cases we observed. For example, during 54 min or bioassay time in one experiment, 579 beetles landed at a combination of pheromone plus coattractant, but only one landed on the filter paper blank (Table 2). The filter paper blank did not provide any information on the activity of the beetles during the bioassays or any infor­ mation on the relative attractiveness of other treatments. Thus, it was generally excluded in the experiments, and the response to the pheromone treatment was used as a standard (as described previously). As our previous observations indicated (Bartelt et aI., 1990a), a starvation period was necessary for the beetles to respond. The beetles did not respond to the apple juice, or pheromone, or even take flight, for several hours after being

TABLE 2. RESPONSIVENESS OF C. hemipterus TO FILTER PAPER BLANK

Total Mean count Treatment count (N = 18)

Filter paper blank I 0.06 Pheromone 92 5.11 Ethanol + ethyl acetate + acetaldehyde 172 9.56 Ethanol + ethyl acetate + acetaldehyde + pheromone 579 32.17 DRIEDFRUIT BEETLE PHEROMONE SYNERGISTS 293 transferred from rearing cups into the wind tunnel (Figure 1). After this time, the response level increased steadily until at 9-13 hr after release, an average of over 25 beetles responded to the apple juice-pheromone combination per 3-min test. During this period, the dramatic enhancement of the attraction of the apple juice by the pheromone was clearly evident, as we observed previ­ ously (Bartelt et al., 1990a). After 13 hr, however, the response level decreased again and became more erratic. This study demonstrated that ratios of numbers of beetles responding to the different attractants was quite consistent over a 6-hr period (between 7 and 13 hr after release). The quasiindependence model described the experiment adequately when just one parameter for each treatment was fitted over the entire 6-hr period (G 2 = 46.82, 34 df, P > 0.05), indicating essentially the same results could be expected at any interval during the 6-hr period. In addition, there was no significant interaction between the treatments and the time period (G 2 = 7.38,4 df, P > 0.10), again indicating that the data obtained at any instant over the 6-hr time period would be reasonable. For this experiment, the fitted ratios were: apple juice/pheromone = 0.35, pheromone + apple juice/apple juice = 12.42, and pheromone + apple juice/pheromone = 4.37 (note that the product of the first two ratios essentially equals the third ratio; this is implicit in the quasiindependence model). The activity profile illus­ trated in Figure 1 is throught not to represent a circadian activity rhythm because the time of greatest activity depended more on when the beetles were separated from their food than on the time of day (see below). The peak activity period could be adjusted so that it occurred at a more convenient time if the beetles were placed in the wind tunnel in the evening before the day the tests were to be run, with lights and fan off (see Methods and Materials). When the lights and fan were turned on the following morning, the beetles usually began to fly actively within 1 hr and responded consistently

30

.... 25 z 0-0 AJ+PHER ::> 0 6--6 PHER u 20 0- - -0 AJ ?;: Vl 15 Vl« 0 iii z 10 w« :::;: 5

0 0 4 8 12 16 20 TIME (HOURS INTO EXPERIMENT)

FIG. 1. Response of C. hemipterus adults to attractants over time in the wind-tunnel assays. AJ = apple juice, PHER = pheromone. 294 DOWD AND BARTELT for about 6 hr once they became active (Table 3). Although there were obvious overall differences in the response to the different treatments (Gz = 512.7,2 df, P « 0.001), the treatment by hour interaction was not significant (G z = 16.47, 10 df, P ;::: 0.05). Thus, the bioassay could give reliable data for as long as 6 hr in one day. The column for the TA in Table 3 represents an "acceptable" degree of variability, one that is not statistically significant. Finally, the appropriateness of the 10 % formulation of the coattractants in mineral oil was investigated. Methyl butyrate was used because it was one of the most active single compounds tested. This ester appeared to be inactive at a 0.1 % concentration and exhibited only slight activity at 1.0% (Table 3). Thus, use of a 10% formulation appeared appropriate. Representative compounds also were tested on different days, and vari­ ability remained within a reasonable range. For example, trials on completely different days yielded synergist ratios of 0.69 and 1.34 for 2-methylpropionic acid, 2.93 and 4.32 for 2-methylbutyric acid, 3.63 and 2.69 for ethanol, 1.75 and 1.68 for 3-methylpropionic acid. Thus, the values appear to be generally reliable ±20% of the synergist ratio.

Representative Hosts and Host Derivatives Whole host materials, fermented host materials, and host extracts generally exhibited some attractancy on their own; fermented banana was among the most attractive based on the RA value (Table 4). They all acted as effective synergists for the pheromone in spite of the fact that relative attractancy was low in some caes. Significant synergism (SRs) occurred in all cases, and effective com­ pounds were more widely distributed compared to those producing high RAs. Again, one of the fermented materials was most effective. Thus, it is not sur­ prising that the total attractancy (TA) for the fermented banana material was among the greatest since it incorporates both high RA and SR values, although the TA of the orange juice was comparable. Effectiveness of the individual volatiles was even more variable. Other than 2-methylpropanoic acid, many of the mono-branched acids were relatively effective attractants, having RAs above 1.5 (Table 4). The Cz acids and those with greater chain length, except for those that had two methyl groups in the 2-position, were effective synergists. Propanoic and butanoic acid had the great­ est TAs. The pattern for alcohols was somewhat different. Methanol and 2-propanol were particularly effective as individual attractants. Significant synergism was seen in many cases and was of approximately the same level (2-3 X). Most of the C t-C4 straight-chain and branched alcohols, and Cs and longer straight­ chain alcohols were the effective synergists, Methanol, 2-propanol, 1-heptanol, and 1-methyl-2-propanol had greatest TAs. DRIEDFRUIT BEETLE PHEROMONE SYNERGISTS 295

a TABLE 3. TIME AND DOSE-RELATED RESPONSES OF C. hemipterus

Mean beetles attracted Fitted ratios

Treatment P A P+A RA SR TA

Time interval test with octyl acetate Hour I 2.9 1.0 16.0 1.37 4.13 4.44 Hour 2 4.9 2.0 20.4 1.43 2.96 3.10 Hour 3 3.9 1.0 20.1 1.25 4.13 5.44 Hour 4 3.1 1.4 12.0 1.33 2.67 2.59 Hour 5 2.8 1.9 13.4 1.49 2.89 3.04 Hour 6 3.4 0.6 11.5 1.18 2.88 4.13 Overall 3.5 1.3 15.6 1.35 3.25 3.54 Concentration test with methyl butyrate (in mineral oil) 0.1% 11.1 a 0.6b 1O.8a 1.06 0.91 0.86 1.0% 3.5a 2.4a 9.5b 1.59 1.62 1.90 10.0% 1.8a 2.6a 1O.9b 2.52 2.49 5.46 aTreatments whose means are followed by the same letter are not significantly different (P > 0.05. conditional G2 tests). The means were not used in calculation of statistical tests but are presented to show the magnitude of the biological responses.

Of the methyl esters, methyl butanoate had the greatest individual attrac­ tancy, followed distantly by methyl propanoate. Once again, significant syn­ ergism occurred in many cases, and generally was 2-3 x. Methyl esters with straight-chain acids other than formate and branched-acid moieties having no more than one methyl group tended to be effective synergists. As would be expected by the high RAs, methyl butanoate and methyl propanoate had very high TAs. For the acetate esters, pentyl acetate and propyl acetate had the highest RAs. Those acetate esters with straight-chain substitutions longer than methyl, as well as I-methylethyl and 2-methylpropyl-substituted compounds were effec­ tive synergists, while those with other branched or secondary alcohols were not effective. Synergist ratios were fairly consistent for all of the linear esters, but some branched esters appeared antagonistic. Pentyl acetate and ethyl acetate had the highest TAs. Other esters with notable TAs were ethyl butanoate, ethyl propanoate, and heptyl hexanoate; all three had high and significant SRs. Of the additional compounds, propanal had the highest RA of any individ­ ual compound tested. The aldehydes, ketones, hydroxy acid, and even water showed significant synergism. Propanal, 2-pentanone, and acetaldehyde had highest TAs. The mixtures of components all had very high individual attrac­ tancy. Synergist ratios were significant and comparable except for that of the ethanol-ethyl butanoate-2-hydroxypropanoic acid combination, which was at 296 DOWD AND BARTELT

TABLE 4. HOST EXTRACTS, AND REPRESENTATIVE COMPOUNDS AS C. hemipterus ATTRACTANTS AND PHEROMONE SYNERGISTSll

Mean beetles attracted Fitted ratios

Attractant PA P+A RA SR TA

Natural materials Apple juice 4.9a 1.9b 22.0c 1.34 3.24*** 4.37 Orange juice I.la 0.6a Il.5b 1.50 6.57"""* 6.73 Com juice 2.0a O.Ob 6.3c 1.00 2.56*** 2.89 Baker's yeast 2.6a 0.6b 6.6c 1.26 2.04** 4.53 S.c./> banana 3.5a 2.3a 30Ab 1.50 5.24* 7.64 Z.b. /> banana 3.0a 3.3a 24.8b 1.92 3.94* 7.59 Acids Formic 1.6a O.lb 2.0a 1.09 1.14 1.80 Acetic 3Aa OAb 9Ac 1.09 2.50*""" 1.94 Propanoic 9.9a 6.8b 76.5c 1.68 4.60*** 9.91 Butanoic 3.3a 0.5b 20.3c 1.17 5040**" 6.68 2-MethyIpropanoic 17.7a OAb 22Ac 1.02 1.24* 1.29 Pentanoic 6Aa 1.9b 27.9c 1.26 3.38*** 3.84 3-Methylbutanoic 7Aa LOb 22.0c 1.13 2.63"*'" 2.83 2-Methylbutanoic 4.6a 4.6b 27.5c 1.53 3.73*** 5.03 2,2-Dimethylpropanoic 6.9a O.lb 6.8a 1.02 0.96 0.79 3-Methylpentanoic 6.0a 3.3a 37Ab 1.62 4.04*** 4.83 4-Methylpentanoic 4.la 3Aa 25.5b 1.91 3040*"" 6.52 2.2-Dimethylbutanoic 11.9a O.lb 16.9a 1.01 1041 * 1.23 Alcohols Methanol 2.6a 3.9a 15.0b 2.51 2.33**" 7.93 Ethanol 6.0a I.3b 26.0c 1.22 3.61 *,',,', 4.25 I-Propanol 16.0a 5Ab 62.5c 1.37 2.92""'* 5.01 2-Propanol 9Aa 7.5a 42.0b 1.86 2049*** 5.63 Butanol 3.3a O.lb 8.3c 1.04 2.44*"* 2.26 2-Methyl-I-propanol 35.5a 0.3b 25.5a 1.01 0.71(*) 0.79 2-Butanol 8.la 0.5b 18.6c 1.07 2.16*** 3.21 2-Methyl-2-propanol 8.5a 1.6b 37.8c 1.22 3.73*** 5.28 2-Methyl-l-bUlanol 5.0a 0.3b 3.6a 1.05 0.69 0.78 3-Methyl-I-butanol 17.0a 1.6b 12.0c 1.12 0.64(*) 0.78 I-Heptanol 1.8a 0.3b 6.0c 1.17 3.0"*" 5045 Methyl esters Formate 17.la 2.lb 20.0a 1.15 1.04 l.l0 Acetate 6.5a 1.8b 24.lc 1.23 2.92*"* 2046 Propanoate 6.9a 6.9a 45.lb 2.05 3.28*** 8.20 Butanoate 3.6a 1O.0a 37.3b 3.75 2.73*** 14.01 2-Methylpropanoate 3Aa I.3b 16.lc 1.39 3049*** 5.79 Pentanoate 6.5a 1.5b 26.6c 1.26 3.33*** 5.13 3-Methylbutanoate 6.1a O.lb 1O.lc 1.02 1.62*** 1.75 2-Methylbutanoate 4.5a OAb 17.lc 1.09 3.51*** 3.63 2,2-Dimethylpropanoate 3.la OAb 4.9a 1.12 1.39 1.56 4-Methylpentanoate 6.9a 0.9b 22.8c 1.12 2.94"** 3.60 DRIEDFRUIT BEETLE PHEROMONE SYNERGISTS 297

TABLE 4. Continued

Mean beetles attracted Fitted ratios

Attractant P A P+A RA SR TA

Acetate esters Methyl 6.5a 1.8b 24.lc 1.23 2.92*** 2046 Ethyl 3.3a OAb 15.1c 1.12 4.17*** 6.01 Propyl 3.3a lAb 18.3c 1.47 3.91*** SAl I-Methylethyl 7.la 1.6b 26.3c 1.22 3.00*** 3.32 Butyl 3.0a O.lb 1O.8c 1.04 3.44*** 3.58 2-Methylpropyl 2.9a O.Ob 9.3c 1.00 3.21 *** 3.78 I-Methylpropyl 2Aa 0.3b 3.9a 1.11 1048 1.75 I.I-Dimethylethyl 2.8a O.Ob 1.5a 1.00 0.55 0.55 Pentyl 3.1a 2.0a 14.6c 1.71 2.85*** 7.13 3-Methylbutyl 5.la 0.3b 5Aa 1.06 1.01 lAS 2-Methylbutyl 5.9a O.Ob 3Aa 1.00 0.57(*) 0.90 I-Methylbutyl 6Aa LOb 1O.3c 1.18 1.39 2.16 I-Ethylpropyl 6.3a OAb 5.0a 1.10 0.75 0.97 Octyl 3.3a 0.5b 14Ac 1.16 3.83**" 5.78 Benzyl LOa O.lb 2.0a 1.11 1.78 2.13 Other esters Ethyl 3-methylbutanoate 5.la OAb 4.9a 1.08 0.89 0.89 Ethyl 2-methylpropanoate 1.8a O.lb 3.8a 1.05 2.00" 1.18 Ethyl propanoate 5.9a 1.8b 37.9c 1.31 4.97*** 7.57 Ethyl butanoate 2.9a 0.5b 19.0c 1.20 5.63*** 8.34 Heptyl hexanoate lAa OAa 9Ab 1.32 5.36"** 6.72 Other compounds Acetaldehyde 2.6a O.Ob 9.0c 1.00 3.43*** 5.14 Propanal LOa 2.9b 7.3c 4.54 1.87"* 6.62 2-Pentanone 0.3a LOa 8.lb 1.31 6.50*** 6.53 2-0H-propanoic acid 4.3a 0.3b 9.4a 1.06 2.08*** 1.84 Water 6.3a 0.3b 10.9c 1.04 1.67** 1.64 Mixtures Ethanol-ethyl acetate- acetaldehyde 5.la 9.6b 32.2c 3.73 2.19*** 8.29 Ethanol-ethyl propanoate- acetaldehyde 3.9a 7.6b 32.6c 2.88 2.84*** 7.03 Ethanol-ethyl propanoate- propanoic acid 5.8a 9.9b 43.3c 2.70 2.77*** 9.37 Ethanol-ethyl butanoate- hydroxypropanoic acid 2.5a 2Aa 33.3b 2.03 6.82*** 19.30

"Treatments whose means are followed by the same letter are not significantly different (P ~ 0.05, conditional G 2 tests). The means were not used in the calculation of statistical tests but are pre- sented to show the magnitude of the biological responses. The symbols *, **, *** indicate that synergism was significant at the 0.05,0.01. or 0.001 level. respectively (conditional G 2 tests). (*) indicates that the response to the mixture was significant less than an "additive" response. b Saccharomyces cerevisae and Zygosaccharomyces bailii. 298 DOWD AND BARTELT least 2x the others. This mixture also had the highest TA, but TAs for other mixtures were generally higher than those of any individual components. Many of these combinations were included in octyl acetate comparisons and yielded relative attractancy values that might be expected based on the previous results. The TA for octyl acetate did fluctuate throughout the experi­ ment, but generally averaged around 6.0 (Table 5). As would be expected, the most potent individual compound tested, methyl butanoate, gave the highest attractancy relative to the octyl acetate, and one of the highest TAs. Poor attrac­ tants/synergists as revealed in prior assays, such as methyl formate, were again proven poor relative to octyl acetate. Thus, using the pheromone alone for a benchmark appeared generally reliable, although a simple combined compari­ son vs. pheromone plus octyl acetate may also prove useful for rapid determi­ nations of relative effectiveness.

Quantitative Structure-Activity Relationships Initial examinations of the electronic parameter, sigma *, indicated it was of little use in explaining differences of activity in compounds with different substituents, so it was excluded from further consideration. Transformations of the Es parameter were necessary to linearize equations for RA [(natural log of the absolute value of Es)/Es] and TA (natural log of the absolute value of (Es); the relationship between Es and SR appeared linear. In addition, consideration of whether or not to include the functional groups in the carbon count was important. They were excluded for free alcohols, free acids, and methyl esters (in other words, propyl alcohol was considered to have an ethyl substituent, and so on). Steric parameters were available for all linear chains except for heptyl, and all 5-carbon branched chains except for I-methylbutyl and 2-meth­ ylbutyl. Lipophilic parameters were only available for 1- to 4-carbon com­ pounds, but included all branched substitutents. In some cases, visual inspection of plotted curves suggested outliers. Exclusion of these outliers will be detailed for each set of equations. Free Acids. The relative attractancy of acids was poorly described when all available compounds were included, but elimination of methyl, l-methyl­ propyl, and 3-methylbutyl groups increased the r 2 to 0.81 (Table 6), indicating a high correlation between (log Es)/Es and RA. Inclusion of the Pi parameter helped somewhat (probably to compensate for the methyl derivitive), but the relationship was still poorly described when the I-methylethyl value was included. Correlation for all included values was much better for the SR, but elimination of I-methylpropyl and l-methylethyl was necessary to get a signif­ icantly high correlation. Inclusion of the PI value did not appear to compensate for the low activity of the methyl derivative. The log (Es) factor was also a fairly good predictor of TA, but again correlation became highly significant DRlEDFRUIT BEETLE PHEROMONE SYNERGISTS 299

TABLE 5. ATTRACTANCY OF PHEROMONE-ATTRACTANT COMBINATIONS TO C. Izemipterus RELATIVE TO OCTYL ACETATE STANDARD"

Mean beetles attracted Fitted ratios

Compound P C+P O+P TAA TAO RAO

PropyI acetate 3.4a 13.3b 11.8b 4.48 4.10 1.09 I-Methylethyl acetate 2.6a 9.0b 14.5c 3.76 6.19 0.61* 2-Methylpropyl acetate 2.9a 9.3b 15.lc 3.78 6.92 0.55* I-Methylpropyl acetate 2.4a 3.9a 1O.8b 1.75 4.65 0.38** I. 1-DimethylethyI acetate 2.8a 1.5a 18.4b 0.54 6.65 0.08*** Methyl formate 2.3a 2.3a 8.0b 0.82 3.18 0.26*** Methyl acetate 3.6a 11.5b 28.3c 3.65 10.94 0.33*** Methyl propanoate 3.0a 34.8b 19.0c 19.26 7.29 2.64*** Methyl butanoate 2.8a 36.3b 12.9c 25.00 4.10 4.70*** Methyl pentanoate 4.0a 26.lb 18.4c 7.47 5.19 1.44* PropyI propanoate 6.la 60.6b 27.3c 16.66 4.92 3.39*** ButyI propanoate 8.5a 31.1b 28.3b 4.39 3.81 1.16 Ethanol-ethyl acetate- acetaldehyde I: I:I 3.0a 58.9b 23.4c 23.15 8.57 2.70"** Methanol-propanoic acid- methyl butanoate I: I:I 3.8a 39.4b 16.lc 34.92 8.15 4.28***

"TAA = total attractancy of attractant, TAO = total attractancy of octyl acetate, RAO = ratio of attractancy of attractant to octyl acetate. Treatments whose means are followed by the same letter are not significantly different (P ~ 0.05, conditional G 2 tests). The means were not used in the calculation of statistical tests but are presented to show the magnitude of the biological responses. The symbols *, "*. *** indicate that the ratios were significantly different from 1.0 at the 0.05, 0.01. or 0.001 level, respectively (conditional G 2 tests). when the methyl and l-methylethyl values were removed. Inclusion of the Pi parameter in the model again did not help to explain the variation. Free Alcohols. The RA of alcohols was reasonable, but not significant, when all available compounds were included. Elimination of the methyl group increased the r 2 somewhat, indicating some correlation between (log Es)/Es and RA. However, inclusion of the Pi parameter yielded a significant r2 of 0.88, indicating both steric and lipophilic functions are important in predicting activity. A similar relationship was noted for the SR, although in this case the Es parameter alone provided a significant correlation. Exclusion of the l-meth­ ylethyl group did provide some improvement for the Es model. Once again, in the case of the TA, the Es parameter appeared to most effectively describe the relationship. Exclusion of the l-methylethyl group provided some increase in 2 2 the r , but inclusion of the Pi parameter only slightly increased the r • Methyl Esters. The relative attractancy of methyl esters was poorly described when all available compounds were included, but elimination of TABLE 6. REGRESSION EQUATIONS DERIVED FROM PHYSICOCHEMICAL COEFFICIENTS"

Coefficients

Group N Es Pi INT r" Prob > F

Acids RA 10 1.20 1.65 0.07 OA71 RA IB.2A.3A 7 3.84 2.39 0.81 0.014 RA 8 3.26 0.35 1.65 0.15 0.665 SR 10 1.35 5.55 0.32 0.092 SR 2AAA 8 2.03 7.36 0.70 0.010 SR 8 2.22 1.18 5.26 0.29 OA22 TA 10 -5.22 7.24 0.28 0.116 TA 1BAB 8 -9.06 10.77 0.78 0.004 TA 8 -8.85 3.35 7.83 0.28 OA34 Alcohols RA 6 1.30 1.50 0.55 0.090 RA 4B 5 1.79 1.67 0.60 0.123 RA 6 6.74 0.74 1.97 0.88 0.044 SR 6 2.55 6.25 0.77 0.021 SR 4B 5 2.58 6.54 0.96 0.004 SR 6 0.82 -lAI 5.34 0.82 0.075 TA 6 -6A7 5.68 0.79 0.018 TA 4B 5 -6.39 5.93 0.91 0.012 TA 6 -5.26 -0.70 5.26 0.80 0.092 Methyl esters RA 9 2.90 2A2 0.05 0.561 RA IB.5A 7 5.54 3.03 0.79 0.007 RA 8 1.97 -0.14 2A2 0.06 0.866 SR 9 0.91 4A7 0.34 0.127 SR 2BAA 7 1.30 4.89 0.81 0.006 SR 8 1.27 OA6 4.39 0.39 0.292 TA 9 -6.02 8.55 0.17 0.277 TA IB.5A 7 -7.57 9.02 0.72 0.016 TA 8 -14.29 6.18 11.13 0.39 0.295 Acetate esters RA 13 0.81 1.43 0.06 OA20 RA * 5 5A3 3.00 0.86 0.023 RA 8 -0.84 -0.23 1.27 0.24 0.050 SR 13 1.58 5.60 0.56 0.003 SR 3B 12 1.77 6.14 0.79 0.0001 SR 8 2.81 1.13 6.21 0.84 0.0103 TA 13 -4.47 6.18 0.38 0.025 TA IB.3B II -6.76 8.21 0.75 0.0005 TA 8 -7.81 2.90 6.70 0.65 0.071 a Es = steric parameter. Pi = pi parameter. INT = intercept. RA = relative attractancy = P + AlP; SR = synergist ratio = (P + Al/P + A; TA = total attractancy = (P + Al/P or (RA X SRl. Values following group designations indicated those removed from consideration; I = methyl. 2 = I-methylpropyl. 3 = 3-methylbutyl. 4 = I-methylethyl. 5 = propyl. * = only contains propyl. I-methylpropyl. 2-methylpropyl. I-methylethyl, and 2.2-dimethylethyl; A = above. B = below original regression line. DRIEDFRUIT BEETLE PHEROMONE SYNERGISTS 301

methyl and propyl groups increased the r 2 to 0.79 (Table 6), indicating a high correlation between (log Es)/Es and RA. Inclusion of the Pi parameter helped slightly, but the relationship was still poorly described when the propyl value was included. Correlation for all included values was much better for the SR, but elimination of l-methyethyl and 1-methylpropyl was necessary to get a sig­ nificantly high correlation. Inclusion of the Pi value again appeared to help compensate for the low activity of the methyl derivative. The log (Es) factor also was a poor predictor ofTA, but again correlation became highly significant when the methyl and propyl values were removed. Inclusion ofthe Pi parameter in the model helped to explain the variation. Acetate Esters. The relative attractancy of the acetate esters was poorly described when all available compounds were included; elimination ofover half the compounds (leaving only 2,2-dimethyl ethyl, 1-methyethyl, propyl, I-methyl propyl and 2-methylpropyl) was necessary to obtain a significant r 2 ofO. 86. Inclusion of the Pi parameter helped a great deal, but again this involved the elimination of a large part of the values. In contrast, correlation for all included values was much better for the SR and significant, but elimination of the 3-methylbutyl substituent was necessary, to get an r 2 of 0.79. Inclusion of the Pi value again appeared to help a great deal, but at the same time the 3-methylbutyl group was excluded due to the unavailability of the Pi parameter. The log (Es) factor also was a significant predictor of TA, but again correlation became highly significant when the methyl and 3-methylbutyl values were removed. Inclusion of the Pi parameter in the model helped to explain the var­ iation.

DISCUSSION

Nitidulid Attractants Attractancy. Prior work with C. Izemipterus has involved testing a series of "plant" volatiles for field attractancy in fig orchards (Smilanick et al., 1978). Acetaldehyde was at least lOx more effective by itself than any other chemical tested, which included ethyl acetate, propyl acetate, methyl butyrate, ethyl butyrate, ethyl isobutyrate, and ethyl propionate. The combination of acetal­ dehyde-ethanol-ethyl acetate (1 :I: 1) was more than 10 x better than acetal­ dehyde alone. The paper concludes that these insects appear to use a restricted number of "plant" volatiles, which are common to hosts such as fig (Jennings, 1977), and the more tropical pineapple (Dupaigne 1970) and guava (MacLeod and DeTroconis, 1982). However, the volatiles of com tassels, which are highly attractive to these and other nitidulids, contain no acetaldehyde, only a trace of ethyl acetate, and some ethanol (Flath et al., 1978), which suggests other com­ ponents also may be involved. Although acetaldehyde, ethanol, and ethyl ace- 302 DOWD AND BARTELT tate are reported from these fruits, Jennings (1977) indicated that they are probably fermentation products from figs, which suggests the same could be the case for the other fruits. Fogleman (1982) also indicates in a review that these three compounds are common products of fermenting yeast. This infor­ mation may explain why fermenting materials, which would produce these attractive compounds (especially ethanol) in greater abundance, are more attrac­ tive than unfermented materials to these insects. The greater attractancy of fer­ menting material would also be logical, considering C. hemipterus may actually prefer to feed on the yeast as opposed to the plant material (Miller, 1952; Miller and Mrak, 1954). In other studies on individual plant attractants for nitidulids, AIm et ai. (1985, 1986), demonstrated the relatively high attractive specificity of butyl acetate in the field for Glischrochilus guadrisignatus (ca. 14 X ethyl butyrate, the next best). Propyl acetate was similar in effectiveness to butyl acetate. Bouchier and Stewart (1986) reported that G. quadrisignatus could dis­ tinguish between isobutyl acetate and n-butyl acetate (the branched ester was more attractive). AIm et ai. (1986) suggested the receptors are very specific. In the present work, we found that some volatiles were obviously superior attracts when used alone. The most effective (having RAs above 2.0) were methanol, methyl butyrate, methyl propionate, and propanai. However, many other compounds were also obviously attractive on their own. These compounds are different from those previously reported to be effective attractants for C. hemipterus (Smilanick et al., 1978). Acetaldehyde had no attractancy in its own in our study, while methyl butyrate was more potent than any of the other com­ pounds previously reported (Smilanick et aI., 1978) that we also examined. In addition, propanal was found to be extremely attractive on its own. These insects are known to respond to humidity gradients (Amos and Waterhouse, 1967; Amos, 1969), so the attractiveness of water is not unexpected. However, although these particular compounds were very attractive on their own (possibly representing specific interactions), when combined with the pheromone, many other compounds produced a TA that was comparable to that for those attrac­ tants that were very effective on their own. The synergistic interaction with the pheromone was a potent phenomenon that needs to be considered in predicting the overall effect of any particular host volatile. Synergism. Due to differences in relative attractancy of butyl acetate vs. banana baits to the nitidulid G. quadrisignatus when adults were excluded vs. allowed to feed on the baits, AIm et ai. (1986) suggested an aggregation pher­ omone may be present but did not address potential synergism. Synergism between host volatiles and pheromones is reported for some insects [e.g., Coleoptera (Birch, 1984; Oehlschlager et aI., 1988) and Diptera (Bartelt et aI., 1988)]. Our prior results indicated that some representative host volatiles can synergize the attractancy of the pheromone from C. hemipterus (Bartelt et aI., 1990a). The present study indicates that for C. hemipterus a wide variety of DRlEDFRUIT BEETLE PHEROMONE SYNERGISTS 303 hosts and host volatiles is capable of synergizing the pheromone. This infor­ mation suggests that, in contrast to the limited number of individual compounds that act as attractants on their own, synergism in C. hemipterus is a more gen­ erally widespread phenomenon. The broad spectrum of compounds capable of synergism is consistent with the known wide host range of C. hemiptems, which also would be expected to involve a diverse range of volatiles. Nitidulids with a more restricted host range may not be synergistically attracted by such a wide range of potential host volatiles (theoretically being restricted to volatiles in common from suitable hosts). While a few specific volatiles may be effective in initially bringing C. hemipterus to a potential host, once the insects arrive and start producing the aggregation pheromone, the overall attractancy of the host will be dramatically increased due to the interaction of the pheromone with the many host volatiles that are likely to be present. Our discovery that hep­ tanol, which is produced in relatively large amounts by com (Buttery et aI., 1978; Flath et al., 1978), is a potent overall attractant for C. hemipterus helps explain how these insects are able to infest com in the absence of more com­ monly recognized nitidulid attractants such as esters. Attractant Combinations. Substituting components into the complex reported by Smilanick et al. (1978) resulted in little change in synergistic potency in the present study, except when better or worse individual synergistic com­ ponents (esters) were added (see Discussion on structure-activity relationships). Notably, acetaldehyde was found not to be necessary. This is important to con­ sider in formulating a field-oriented synergistic combination, since acetaldehyde is inherently more volatile and unstable than potential ester, alcohol, or acid components. The importance of acetaldehyde as an attractant reported by Srni­ lanick et al. (1978) was not noted in the present study. It is possible that insect strain differences may explain differences in acetaldehyde effects, although the strain used in the present study also was obtained originally from California. However, it is also possible that acetaldehyde oxidized in the field to form acetic acid, which was effective as a synergist in our study.

Stmcture-Activity Relationships Overall the Es (bulkiness) parameter was a good predictor for many of the relationships, although an apparent outlier or two had to be removed to give a significant correlation. The outlier was frequently methyl, which appeared to be compensated for when lipophilicity (Pi) was entered into the model. Another frequent outlier was the I-methylethyl moiety, since it became important in some cases for acids, alcohols, and methyl esters. It is possible that specific receptors may exist for these types of compounds. The equations generated were generally similar to each other, although RA equations typically had lower intercepts (probably a function of the linearization), and TA equations had neg- 304 DOWD AND BARTELT ative coefficients (again caused by the transformations). The equations for the RAs tended to be the most variable for the different classes of substituents. The coefficients for the SR equations appeared most similar to one another, although the intercepts were more variable. This information suggests that the receptors, or entire transport-receptor-processing phenomenon is similar for all of the compounds. However, individual differences between attractant class and type of attractancy did exist and are worth considering in more detail. Relative Attractancy. The optimized equations predicting the RA for the methyl esters and acetate esters were very similar, suggesting that the receptor involved in the generalized attractancy is similar and symmetrical (although specific receptors for more attractive "outliers" such as methyl butyrate are likely). The derived optimized equation for the RA of the acids was somewhat similar to those derived for the esters, but different enough to suggest that two different receptors may be involved for acid and ester attractancy. This was even more obvious for the alcohols, where both coefficients for Es and the intercept were very different from those for the esters and acids. The Es parameter appeared to have the greatest influence on the attractancy of the compounds, but lipophilicity (Pi) also appears to be involved. However, of the three types of attractancy examined, the relative attractancy was most difficult to fit with regression equations. This may have been due to the relatively lesser sensitivity of the assays involving the attractants alone, due to the smaller numbers of beetles that were usually attracted compared to when the attractants were com­ bined with the pheromone. Synergism. The synergism between the pheromone and the attractants appeared to be a more generalized phenomenon and, due to the higher counts involved, appears to be more suitable for considering relationships of the dif­ ferent classes of substituted compounds. Ifa single site is assumed for all esters, the binding site would appear to be relatively symmetrical, based on studies with the methyl- and acetate-substituted esters. Long-chain substituents, includ­ ing compounds such as heptyl caproate, were generally effective, as were some branched compounds. However, the position of the branch affected activity dif­ ferently depending on which "side" of the carbonyl it was positioned. Branch­ ing at the 2-position was acceptable for the methyl esters, but not always acceptable for the acetate esters. It is possible that acids, alcohols, and esters were binding to the same site or that esters were hydrolyzed to acids and alcohols that then bound to the same or two different respective sites. However, in spite of the general similarity in effectiveness of the many analogous alcohols, acids, and esters, individual effectiveness of analogous compounds did significantly differ in some cases, suggesting different receptors are involved for all three classes of compounds. For example, 3-methyl butanoate was more active synergist than 2-methyl pro- DRlEDFRUIT BEETLE PHEROMONE SYNERGISTS 305 panoate was; the opposite was true for the corresponding methyl esters. Differ­ ent effectiveness as synergists of corresponding alcohols and acetate esters also occurred for I-methyl propyl, 2-methylpropyl, and 1, I-dimethylethyl analogs. However, highly effective "outliers" such as methyl butyrate suggest specific receptors are also likely to be present. Total Attractancy. Based on structure-activity relationships of acid, alco­ hol, and ester synergists, it is clear that the best synergists are linear compounds and that there is a series of each of these components that is similar in effec­ tiveness. However, since the total attractancy is a function of the relative attrac­ tancy of the individual compound alone coupled with the synergist ratio, the compound with the highest attractancy (RA) and the highest synergist ratio (SR) would be the most effective compound to use in combination with the phero­ mone. Theoretically, for the esters this would involve the most attractive alco­ hol and acid portion. For the methyl esters, clearly this would involve either a propanoate or n-butanoate moiety, since these functional groups had the greatest single attractancy as well as a high synergist ratio and, indeed, the highest TA. For the alcohol portion, this would involve most of the straight-chain moieties. Ethyl acetate was among the most effective esters in terms of total attractancy and was found to be very effective in the field as well (Smilanick et al., 1978). Predictably, propyl propanoate would be one of the most effective compounds to use as a synergist, and it yielded a octyl acetate-ester ratio of 3.26. Only methyl butanoate yielded a comparable ratio, and this is likely to involve a specific attractancy receptor for this compound. For the alcohols, since a dif­ ferent receptor appears to be involved, methanol, 2-propanol, or heptanol would appear to be the most effective alcohols to use, although the fermentatively obvious ethanol is also very effective. Propanoic acid is clearly the superior acid attractant, but butanoic and 4-methylpentanoic acids are also very effec­ tive. Prior success with combinations including an alcohol and ester (Smilanick et al., 1978) may reflect multiple receptor stimulation, which would logically be further enhanced if the acetaldehyde were converted to acetic acid, producing a stimulant for an additional receptor. However, the results of the present study suggest attractancy could be significantly improved by use of the appropriate ester, alcohol, and acid (propanoate). This combination was approximated with ethyl propanoate, ethanol, and propanoic acid, which were readily available. Additional attractancy was achieved by adding water to this mix, which may represent and additional receptor. Propanal also would appear to be an appro­ priate compound to incorporate in the mixture. The determination of appro­ priate ratios would be of value also. Of course, formulation and cost may limit the selection of suitable components, but substituent optimization as it influ­ ences the synergist ratio should be considered in developing an appropriate blend. 306 DOWD AND BARTELT

CONCLUSIONS

We believe the use ofthe pheromone of C. hemipterus in combination with the appropriate esters, alcohols, acids, and potentially other compounds such as water and propanal, is likely to yield a potent attractant for this insect. Appro­ priate selection of the component from a particular class is necessary to obtain optimum attractancy, as indicated by structure-activity relationships reported here. These combinations will be valuable tools for monitoring the population of C. hemipterus as well as controlling them by trapping, a method that pro­ vided economically acceptible control of insects infesting figs. Bait stations with simple fermentation products have been used successfully in the past to increase quality and quantity of figs produced (Warner, 1960, 1961). A synergistic com­ bination of pheromone and host volatiles should overcome problems of poor competition of attractants with natural hosts cited in past reports. However, C. hemipterus is also a pest of other ripe and dried fruit, as well as stored maize, com meal, wheat, oats, rice, beans, nuts, peanuts, cotton seed, copra, spices, drugs, bread, sugar, honey, and other items (Hinton, 1945). It is also respon­ sible for vectoring organisms responsible for souring of figs (Hinton, 1945) and fungi that contaminate com and produce mycotoxins (Lussenhop and Wicklow, 1990). Thus, the utility of the components we have discovered is likely to be widespread and may be applicable to the control of other nitidulids as well. Although specific receptors may sometimes be involved, structure-activity rela­ tionships appear to be useful in predicting optimal synergists for pheromones, a methodology that should prove useful in developing optimal synergistic blend for many other insects.

Acknoll'ledgmellls-We thank C.M. Weber for technical assistance and T.e. Nelsen for sug­ gestions on appropriate statistical analyses.

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