Journal of Chemical Ecology, Vol. 17, No. 2, 1991

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

AND

Carpophilus hemipterus I

PATRICK F. D O W D 2'* and ROBERT J. BARTELT 3 2Mycotoxin and 3Bioactive Constituents Research Units National Center for Agricultural Utilization Research USDA, Agricultural Research Service Peoria, Illinois 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-tunnel 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 synergized when they were combined with the pheromone. Propanoic and butanoic acids, methanol, 2-propanol, 1-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) parameter also appeared to be useful in explaining the lower activity of short-chain substituents. Thus, many compounds that had only limited attractiveness on their own may nevertheless play and important role in synergizing the pheromone. Structure-activity studies appear to be appropriate not only for determining optimal attractants for these insects, but also for determining effective synergists for the pheromone. *To whom correspondence should be addressed. t 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

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DowD AND BARTELT

Key Words--Pheromone, aggregation, synergism, ester, carboxylic acid, alcohol, carboxylic ester, driedfruit beetle, Carpophilushemipterus, Coleoptera, 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 al., 1987; Burkholder, 1988; Oehlschlager et al., 1988) also have demonstrated that stored-product beetle attraction is synergistically enhanced by combining 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 (Smilanick et al., 1978; Blackmer and Phelan, 1988). For example, a 1 : 1 : 1 combination of ethanol-acetaldehyde-ethyl acetate was a highly effective combination for attracting C. hemipterus (Smilanick et al., 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 information suggests that a combination of aggregation 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 al. (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 if optimal host-derived individual attractancy, synergism, and overall attractancy could be predicted by quantitative analysis of physiocochemical parameters or use of other structural relationships.

DRIEDFRUIT BEETLE PHEROMONE SYNERGISTS METHODS

287

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 al., 1990a). Hosts and Chemicals. Whole oranges, bananas, and apple juice were obtained from a local grocery store. Oranges were squeezed for juice immediately before the assays. Milk-stage dent corn was obtained from greenhousegrown plants. The Saccharomyces cerevisae used was a baker's yeast strain (Fleishman's dried activated). The culture of the wild yeast, Zygosaccharomyces 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 inoculating 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 al., 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 different areas of the filter paper when tested in combination. For the liquid attractants, 20-/xl 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 al., 1978) and found to be effective in our wind-tunnel assays (see Results). When chemicals were combined 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 al., 1990). The concentration of the most abundant pheromone component, (2E,4E,6E,8E)-3,5,7-trimethyl-2,4,6,8decatetraene, was ca. 50 pg//zl when quantitated by gas chromatography; 20/zl 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 initial material and an isolated Tenax-trapped volatile extract developed after the start of these assays (Bartelt et al., 1990a) did not yield significantly different results for representative combinations, so the diet extract was used throughout

DOWD AND BARTELT

288

TABLE 1. CHEMICALS, SOURCES, AND PURITIES a

Compound Alcohols Methanol Ethanol 1-Propanol 2-Propanol (isopropyl alcohol) 1bButanol 2-Methyl-l-propanol (isobutyl alcohol) 2-Butanol (s-butyl alcohol) 2-Methyl-2-propanol (t-butyl alcohol) 2-Methyl- 1-butanol 1-Pentanol

1-Heptanol Acids Formic Acetic Propanoic Butanoic 2-Methylpropanoic (isobutyric) Pentanoic 3-Methylbutanoic (isovaleric) 2-Methylbutanoic 2,2-Dimethylpropanoic 3 -Methylpentanoic 4-Methylpentanoic 2,2-Dimethylbutanoic Acetate esters Methyl acetate Ethyl acetate Propyl acetate 1-Methylethyl (isopropyl) acetate Butyl acetate 2-Methylpropyl (isobutyl) acetate 1-Methylpropyl (s-butyl) acetate 1,1-Dimethylethyl (t-butyl) acetate Pentyl acetate 3-Methylbutyl (isopentyl) acetate 1-Methylbutyl (s-pentyl) acetate 2-Methylbutyl acetate 1-Ethylpropyl acetate Octyl acetate Methyl esters Methyl formate Methyl acetate Methyl propanoate

Source

Purity ( %)

EM Labs USICC Aldrich Baker Fisher Aldrich Aldrich Aldrich Aldrich Aldrich Sigma

99.9 100 99.7 99.8 99.95 99.9 99 + 99 + 99 + 99 + 99

Aldrich EM Labs Sigma Aldrich Aldrich Kodak Aldrich Kodak Aldrich Aldrich Kodak Aldrich

95 99.7 99 99 + 99+ 98 99 99 99 97 99 96

PolySciences MCB PolySciences PolySciences Aldrich PolySciences PolySciences PolySciences MCB PolySciences PolySciences PolySciences PolySciences Aldrich

98 + 99.5 98 + 98 + 99 + 98 + 98 + 98 + 98 98 + 98 + 98 + 98 + 99 +

PolySciences PolySciences PolySciences

98 + 98 + 98 +

DRIEDFRUIT BEETLE PHEROMONE SYNERGISTS

289

TABLE 1. Continued

Compound Methyl butanoate Methyl 2-methylpropanoate (isobutyrate) Methyl pentanoate Methyl 3-methylbutanoate (isovalerate) Methyl 2-methylbutanoate Methyl 2,2-dimethylpropanoate (t-valerate) Methyl 4-methylpentanoate Other esters Ethyl propanoate Ethyl butanoate Ethyl 2-methylpropanoate (isobutyrate) Ethyl 3-methylbutanoate (isovalerate) Propyl propanoate Heptyl hexanoate (caproate) Other compounds Water Acetaldehyde Propanal Pentanal 2-Pentanone 2-Hydroxypropanoic acid (lactic acid)

Source

Purity ( %)

PolySciences PolySciences PolySciences PolySciences PolySciences PolySciences PolySciences

98+ 98+ 98+ 98+ 98+ 98+ 98+

Sigma Aldrich Aldrich Sigma Aldrich Pfaltz & Bauer

99 + 99 + 99 + NS 99 + NS

In-house Baker Aldrich Aldrich Aldrich Fisher

99+ NS 99+ 99 97 85

aBranched 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 pheromone (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. Treatment 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-rain bioassay period varied widely over different days, depending on the number 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 pheromone alone, divided by the counts for the pheromone treatments alone (relative 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 activity. 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 acetate 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 volatiles in a balanced, incomplete block design such that there were eight replications 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 categorical methods (chi-square tests) applying a model of quasiindependence to the incomplete block designs (Fienberg, 1977; Bartelt et al., 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, categorical analysis appeared to be appropriate for our data. The use of ratios of fitted values to summarize treatment effects followed naturally from the quasiindependence 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 al., i990a) 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 effectively 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 conditional G 2 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 concentrated 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 lipophilic 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 M A X R STEPWISE procedure (SAS Institute, 1985) was used to obtain substituent constants for oneand two-parameter models and included reports of correlation coefficients and probability values. Plots were examined in light o f correlation values to visually determine outliers, which might obscure underlying relationships. The procedure 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 of Bioassays One property o f 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 information 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 al., 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

TABLE2. RESPONSIVENESS OF C.

hemipterusTO FILTER PAPER BLANK

Treatment

Total count

Mean count ( N = 18)

Filter paper blank Pheromone Ethanol + ethyl acetate + acetaldehyde Ethanol + ethyl acetate + acetaldehyde + pheromone

1 92 172 579

0.06 5.11 9.56 32.17

293

D R I E D F R U I T BEETLE P H E R O M O N E SYNERGISTS

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 previously (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 dr, 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 illustrated 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

/

~ 20 o

\

o--o

/''\

AJ+PHER

A---~. PHER

15 o_ m

10

Z

,. 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 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 2 x 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 experiment, 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 attractants/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 comparison vs. pheromone plus octyl acetate may also prove useful for rapid determinations 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 1-methylbutyl and 2-methylbutyl. Lipophilic parameters were only available for 1- to 4-carbon compounds, 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, 1-methylpropyl, 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 1-methylethyl value was included. Correlation for all included values was much better for the SR, but elimination of 1-methylpropyl and 1-methylethyl was necessary to get a significantly 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

299

DRIEDFRUIT BEETLE PHEROMONE SYNERGISTS

TABLE 5. ATTRACTANCY OF PHEROMONE-ATTRACTANT COMBINATIONS TO C.

hemipterus RELATIVE TO OCTYL ACETATE STANDARD a Fitted ratios

Mean beetles attracted Compound

P

C + P

O + P

TAA

TAO

RAO

Propyl acetate 1-Methylethyl acetate 2-Methylpropyl acetate 1-Methylpropyl acetate 1,1-Dimethylethyl acetate Methyl formate Methyl acetate Methyl propanoate Methyl butanoate Methyl pentanoate Propyl propanoate Butyl propanoate Ethanol-ethyl acetateacetaldehyde 1 : 1 : 1 Methanol-propanoic acidmethyl butanoate 1 : 1 : 1

3.4a 2.6a 2.9a 2.4a 2.8a 2.3a 3.6a 3.0a 2.8a 4.0a 6. la 8.5a

13.3b 9.0b 9.3b 3.9a 1.5a 2.3a ll.5b 34.8b 36.3b 26.1b 60.6b 31.1b

11.8b 14.5c 15. lc 10.8b 18.4b 8.0b 28.3c 19.0c 12.9c 18.4c 27.3c 28.3b

4.48 3.76 3.78 1.75 0.54 0.82 3.65 19.26 25.00 7.47 16.66 4.39

4.10 6.19 6.92 4.65 6.65 3.18 10.94 7.29 4.10 5.19 4.92 3.81

1.09 0.61" 0.55* 0.38** 0.08*** 0.26*** 0.33*** 2.64*** 4.70*** 1.44" 3.39*** 1.16

3.0a

58.9b

23.4c

23.15

8.57

2.70***

3.8a

39.4b

16. lc

34.92

8.15

4.28***

aTAA = total attmctancy 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 G2 tests ).

w h e n the m e t h y l and 1 - m e t h y l e t h y l v a l u e s w e r e r e m o v e d . I n c l u s i o n o f the Pi p a r a m e t e r in the m o d e l again did not h e l p to explain the variation. Free Alcohols. T h e R A o f a l c o h o l s was reasonable, but not significant, w h e n all a v a i l a b l e c o m p o u n d s w e r e included. E l i m i n a t i o n o f the m e t h y l group i n c r e a s e d the r e s o m e w h a t , indicating s o m e correlation b e t w e e n (log E s ) / E s and R A . H o w e v e r , i n c l u s i o n o f the Pi p a r a m e t e r y i e l d e d a significant r z o f 0 . 8 8 , indicating both steric and lipophilic functions are important in predicting activity. A similar relationship was n o t e d for the SR, although in this case the Es p a r a m e t e r a l o n e p r o v i d e d a significant correlation. E x c l u s i o n o f the 1-methylethyl g r o u p did p r o v i d e s o m e i m p r o v e m e n t for the Es m o d e l . O n c e again, in the case o f the T A , the Es p a r a m e t e r a p p e a r e d to m o s t effectively d e s c r i b e the relationship. E x c l u s i o n o f the 1 - m e t h y l e t h y l group p r o v i d e d s o m e increase in the r 2, but i n c l u s i o n o f the Pi p a r a m e t e r o n l y slightly i n c r e a s e d the r a. Methyl Esters. T h e relative attractancy o f m e t h y l esters was p o o r l y d e s c r i b e d w h e n all a v a i l a b l e c o m p o u n d s w e r e i n c l u d e d , but e l i m i n a t i o n o f

TABLE 6. REGRESSION EQUATIONS DERIVED FROM PHYSICOCHEMICAL COEFFICIENTSa Coefficients Group Acids RA RA IB,2A,3A RA SR SR 2A,4A SR TA TA 1B,4B TA Alcohols RA RA 4B RA SR SR 4B SR TA TA 4B TA Methyl esters RA RA 1B,5A RA SR SR 2B,4A SR TA TA 1B,5A TA Acetate esters RA RA * RA SR SR 3B SR TA TA 1B,3B TA

N

Es

10 7 8 10 8 8 10 8 8

1.20 3.84 3.26 1.35 2.03 2.22 -5.22 -9.06 -8.85

6 5 6 6 5 6 6 5 6

1.30 1.79 6.74 2.55 2.58 0.82 -6.47 -6.39 -5.26

9 7 8 9 7 8 9 7 8

2.90 5.54 1.97 0.91 1.30 1.27 -6.02 -7.57 - 14.29

13 5 8 13 12 8 13 11 8

0.81 5.43 -0.84 1.58 1.77 2.81 -4.47 -6.76 -7.81

Pi

0.35

1.18

3.35

0.74

-1.41

-0.70

-0.14

0.46

6.18

-0.23

1.13

2.90

INT

r2

Prob > F

1.65 2.39 1.65 5.55 7.36 5.26 7.24 10.77 7.83

0.07 0.81 0.15 0.32 0.70 0.29 0.28 0.78 0.28

0.471 0.014 0.665 0.092 0.010 0.422 0.116 0.004 0.434

1.50 1.67 1.97 6.25 6.54 5.34 5.68 5.93 5.26

0.55 0.60 0.88 0.77 0.96 0.82 0.79 0.91 0.80

0.090 0.123 0.044 0.021 0.004 0.075 0.018 0.012 0.092

2.42 3.03 2.42 4.47 4.89 4.39 8.55 9.02 11.13

0.05 0.79 0.06 0.34 0.81 0.39 0.17 0.72 0.39

0.561 0.007 0.866 0.127 0.006 0.292 0.277 0.016 0.295

1.43 3.00 1.27 5.60 6.14 6.21 6.18 8.21 6.70

0.06 0.86 0.24 0.56 0.79 0.84 0.38 0.75 0.65

0.420 0.023 0.050 0.003 0.0001 0.0103 0.025 0.0005 0.071

aEs = steric parameter, Pi = pi parameter, INT = intercept. RA = relative attractancy = P + A / P ; SR = synergist ratio = (P + A ) / P + A; TA = total attractancy = (P + A ) / P or (RA x SR). Values following group designations indicated those removed from consideration: 1 = methyl, 2 = 1-methylpropyl, 3 = 3-methylbutyl, 4 = 1-methylethyl, 5 = propyl, * = only contains propyl, 1-methylpropyl, 2-methylpropyl, 1-methylethyl, and 2,2-dimethylethyl; A = above, B = below original regression line.

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methyl and propyl groups increased the r z 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 1-methyethyl and 1-methylpropyl was necessary to get a significantly 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 of TA, but again correlation became highly significant when the methyl and propyl values were removed. Inclusion of the 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 of over half the compounds (leaving only 2,2-dimethyl ethyl, 1-methyethyl, propyl, 1-methyl propyl and 2-methylpropyl) was necessary to obtain a significant r 2 of 0.86. 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 variation.

DISCUSSION

Nitidulid Attractants Attractancy. Prior work with C. hemipterus has involved testing a series of "plant" volatiles for field attractancy in fig orchards (Smilanick et al., 1978). Acetaldehyde was at least 10 x 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 acetaldehyde-ethanol-ethyl acetate ( 1 : 1 : 1 ) was more than 10 x better than acetaldehyde 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 corn 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 components also may be involved. Although acetaldehyde, ethanol, and ethyl ace-

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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 information may explain why fermenting materials, which would produce these attractive compounds (especially ethanol) in greater abundance, are more attractive than unfermented materials to these insects. The greater attractancy of fermenting 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 al. (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 distinguish between isobutyl acetate and n-butyl acetate (the branched ester was more attractive). Aim et al. (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 propanal. 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 compounds previously reported (Smilanick et al., 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 attractants 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 al. (1986) suggested an aggregation pheromone 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 al., 1988) and Diptera (Bartelt et al., 1988)]. Our prior results indicated that some representative host volatiles can synergize the attractancy of the pheromone from C. hemipterus (Bartelt et al., 1990a). The present study indicates that for C. hemipterus a wide variety of

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hosts and host volatiles is capable of synergizing the pheromone. This information 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 generally widespread phenomenon. The broad spectrum of compounds capable of synergism is consistent with the known wide host range of C. hemipterus, 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 heptanol, which is produced in relatively large amounts by corn (Buttery et al., 1978; Flath et al., 1978), is a potent overall attractant for C. hemipterus helps explain how these insects are able to infest corn in the absence of more commonly 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 components (esters) were added (see Discussion on structure-activity relationships). Notably, acetaldehyde was found not to be necessary. This is important to consider 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 Smilanick 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.

Structure-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 1-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-

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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 combined 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 different classes of substituted compounds. If a 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, including compounds such as heptyl caproate, were generally effective, as were some branched compounds. However, the position of the branch affected activity differently depending on which " s i d e " of the carbonyl it was positioned. Branching 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-

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panoate was; the opposite was true for the corresponding methyl esters. Different effectiveness as synergists of corresponding alcohols and acetate esters also occurred for 1-methyl propyl, 2-methylpropyl, and 1,1-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, alcohol, 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 effectiveness. However, since the total attractancy is a function of the relative attractancy 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 pheromone. Theoretically, for the esters this would involve the most attractive alcohol 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 different 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 effective. 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 appropriate compound to incorporate in the mixture. The determination of appropriate ratios would be of value also. Of course, formulation and cost may limit the selection of suitable components, but substituent optimization as it influences the synergist ratio should be considered in developing an appropriate blend.

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We believe the use of the 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. Appropriate 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 provided 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 (Wamer, 1960, 1961). A synergistic combination 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, corn meal, wheat, oats, rice, beans, nuts, peanuts, cotton seed, copra, spices, drugs, bread, sugar, honey, and other items (Hinton, 1945). It is also responsible for vectoring organisms responsible for souring of figs (Hinton, 1945) and fungi that contaminate corn 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 relationships appear to be useful in predicting optimal syuergists for pheromones, a methodology that should prove useful in developing optimal synergistic blend for many other insects. Acknowledgments--We thank C.M. Weber for technical assistance and T.C. Nelsen for suggestions on appropriate statistical analyses.

REFERENCES

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BARTELT, R.J., DOWD, P.F., PLATTNER, R., and WEISLEDER,D., 1990a. Aggregation pheromone of the driedfruit beetle, Carpophilus hemipterus: Wind-tunnel bioassay and identification of novel tetraene hydrocarbon components. J. Chem. Ecol. 16:1015-1039. BARTELT R.J., McGumE, M.R., and BLACK, D.A. 1990b. Feeding stimulants for the European corn borer (Lepidoptera: Pyralidae): Additives to a starch-based formulation for Bacillus thuringiensis. Environ. Entomol. 19:182-189. BIRCH, M.C. 1984. Aggregation in bark beetles, pp. 331-353 in W.J. Bell and R. J. Card6 (eds.), Chemical Ecology of Insects. Sinauer Assoc. Sunderland, Massachusetts. BLACKMER,J.L., and PHELAN, P.L. 1988. Flight behavior of Carpophilus hemipterus (L.) (Coleoptera: Nitidulidae): Transition from dispersive to vegetative flight. Proceedings XVIII International Congress on Entomology, p. 217. BOUCHIER, R.S., and STEWART, R.K. 1986. Attraction of Glischrochilus quadrisignatus (Coleoptera: Nitidulidae) adults to food plant volatiles. Proc. Entomol. Soc. Manitoba 42:37. BURKHOLDER, W.E. 1988. Some new lures, traps, and sampling techniques for monitoring storedproduct insects. Proceedings XVIII International Congress on Entomology, p. 444. BUTTERY, R.G., LING, L.C., and CHAN, B.G. 1978. Volatiles of corn kernels and husks: possible corn earworm attractants. J. Agric. Food Chem. 26:866-869. BUTTERY, R.G., LING, L.C., and R. TERANISH~, 1980. Volatiles of corn tassels: Possible corn ear worm attractants. J. Agric. Food Chem. 28:771-774. DOWD, P.F. 1987. A labor-saving method for rearing the driedfruit beetle (Coleoptera: Nitidulidae) on pinto bean-based diet. J. Econ. Entomol. 80:1351-1353. DUPAIGNE, P. 1970. The aroma of pineapples. Fruits 25:793-805. FIENUERG, S.E. 1977. The Analysis of Cross-Classified Categorical Data. MIT Press, Cambridge, Massachusetts. 151 pp. FLATH, R.A., FOREY, R.R., JOHN, J.O., and CHAN, B.C. 1978. Volatile components of corn silk (Zea mays L.): Possible Heliothis zea (Boddie) attractants. J. Agric. Food Chem. 26:12901293. FOGLEMAN, J.C. 1982. The role of volatiles in the ecology of cactophilic Drosophila, pp. 191206, in J.S.F. Barker and W.T. Starmer (eds.). Ecological Genetics and Evolution: The Cactus-Yeast-Drosphila Model System. Academic Press, New York. HANSCH, C., and LEO, A. 1979. Substituent Constants for Correlation Analysis in Chemistry and Biology. Wiley, New York. 339 pp. HINTON, H.E. 1945. A Monograph of the Beetles Associated with Stored Products. Jarrold and Sons, Norwich, England. 443 pp. JENNINGS, W.G. 1977. Volatile components of figs. Food Chem. 2:185-191. JONES, O.T. 1985. Chemical mediation of insect behavior, pp. 311-373, in D.H. Hutson and T.R. Roberts (eds.). Progress in Pesticide Biochemistry and Toxicology, Vol. 5, Insecticides. Wiley, New York. LUSSENHOP, J.L., and WlCKLOW, D.T. 1990. Nitidulid beetles as a source of Aspergillus flavus infective inoculum. Trans. Jpn. Mycol. Soc. 31:63-74. MACLEOD, A.J., and DE TROCONIS, N.G. 1982. Volatile flavour components of guava. Phytochemistry 21:1339-1342. METCALF, R.L. 1987. Plant volatiles as insect attractants. C.R.C. Critical Rev. Plant Sci. 5:251300. MILLER, M.W. 1952. Yeast associated with the dried-fruit beetle in figs. Proc. Cal. Fig. Inst. 6:89. MILLER, M.W., and MRAK, E.M. 1954. Yeast associated with dried-fruit beetles in figs. Appl. Environ. Microbiol. 1: 174-178.

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OEHLSCHLAGER, A.C., PIERCE, A.M., PIERCE, H.D., JR. and BORDEN,J.H. 1988. Chemical communication in cucujid grain beetles. J. Chem. Ecol. 14:2071-2098. SAS INSTITUTE. 1985. SAT/STAT Guide for Personal Computers, Version 6. SAS Institute, Cary, North Carolina. SMILANICK,J. 1979. Colonization of ripening figs by Carpophilus spp. J. Econ. Entomol. 72:557559. SMILANICK,J.M., EIJLER, L.E., and BIRCH,M.C. 1978. Attraction of Carpophilus sp. to volatile compounds of figs. J. Chem. Ecol. 4:700-701. WALGENBACH,C.A., BURKHOLDER,W.E., CURTIS,M.J., and KHAN, Z.A. 1987. Laboratory trapping studies with Sitophilus zeamais (Coleoptera: Curculionidae). J. Econ. Entomol. 80:763767. WARNER,R.M. 1960. Area baiting to control Drosophila and nitidulid beetles. Proc. Cal. Fig Inst. 14:35-38. WARNER,R.M. 1961. Area baiting program 1960 results. Proc. Cal. Fig Inst. 15:36-40.

Host-derived volatiles as attractants and pheromone synergists for driedfruit beetleCarpophilus hemipterus.

The attractiveness of representative host materials, host extracts, and individual host volatiles (primarily carboxylic acids, alcohols, and esters) t...
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