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Insecticide Resistance of Diamondback in A. M. Shelton and J. A. Wyman¹ State Agricultural Experiment Station. Geneva. New York 14456. USA 'University of Wisconsin,. Madison, Wisconsin, 53706, USA

Abstract

The extent and geographic distribution of resistance to methomyl, permethrin and methamidophos in 44 populations of diamondback moth, xylostella (L.) from 19 states within the U.S., Mexico, Canada and Belize was determined in 1988. Widespread resistance to all three was confirmed. Resistance was generally highest in populations originating from southern states but scattered populations with high levels of resistance were also detected in northern states. In most instances where resistance was detected to one , there was also resistance to the other two. Highest levels of resistance were detected for methomyl. During 1989, diamondback moth was imported into New York on southern transplants (seedlings). During June, when most transplants arrived in New York, DBM infestations were as high as 12.8 per 100 transplants on an individual shipment. Compared to a standard susceptible field population, the diamondback moth which were collected from transplants had moderate to high (> 100-fold in one case) levels of resistance to permethrin and methomyl. In 1990, eleven diamondback moth populations were surveyed for susceptibility to two commercial formulations of . High levels of resistance (in some cases > 200-fold) were found in populations which originated from .

Introduction The diamondback moth (DBM) Plutella xylostella (L.) (:Yponomeutidae)is a key pest of cruciferous crops throughout the world. In tropical and subtropical areas, crucifer production has been seriously affected in recent years by DBM which has developed resistance to a wide range of insecticides (Sun et al. 1986). Georghiou (1981) has reported DBM resistance to 36 insecticides in 14 countries. In North America DBM has normally been considered a minor pest in the lepidopteran complex, but in the last 5 years entomologists in several states (including Florida, Georgia, North Carolina, Texas, Wisconsin and New York) have reported economic damage in crucifers as a result of their inability to control DBM. Such control failures may have been influenced by environmental factors (Harcourt 1986; Sastrodihardjo 1986), but when examined on a regional basis, insecticide resistance is the most tractable cause. Our studies on the extent and development of insecticide resistance in DBM within North America occurred in three phases. In 1988 we surveyed the level of susceptibility of DBM to three commonly used synthetic insecticides (methomyl, permethrin and methamidophos) representing the three major classes of insecticides (, carbamates and organophosphates) used within North America. As a result of information gathered in 1988 which indicated high levels of resistance in New York, we initiated a study in 1989 to determine if resistant DBM populations in New York were the result of importing DBM on plants grown in southern states. The third phase of this study surveyed the level of susceptibility of 11 DBM populations to two commercial formulations of Bacillus thuringiensis Berliner. 447 448 Shelton and Wyman

Insecticide Resistance to Methomyl, Permethrin and Methamidophos

In 1988, cooperators were asked to collect 50-150 DBM larvae and pupae from commercial or research cabbage fields in their respective areas. Collections were made in each area during the peak of DBM activity. Forty-four populations from 19 states within the U.S., Mexico, Canada and Belize (Tables 1-3) were evaluated using a leaf dip bioassay similar to Tabashnik et al. (1987) for susceptibility to permethrin (Ambush 2E), methomyl (Lannate 1.8L), and methamidophos (Monitor 4E). We attempted to test all field-collected populations in the first five generations; populations from Geneva, New York, Pulehu, Hawaii, and College Station, Texas, were laboratory colonies and were tested in later generations. Data were analyzed using the POLO procedure (Russell et al. 1977) to obtain LC values. Resistance ratios (RR), the ratio of the LC50 of a given population to that of the standard population, were calculated. The standard population originated from Geneva, New York, in 1988 and was laboratory-reared for 23 generations. DBM populations exhibited extreme variation in susceptibility to methomyl (Table 1). A colony from Greenville, North Carolina had the highest RR of 780, followed by RRs of 362

Table I. Susceptibility to methomyl of DBM larval populations.

LC50-48h (95% CL) Region Population N Slope ±SE RRª me AI/ml East Lochwood. CT F4 238 0.960 (0.689-1.333) 2.32±0.28 9.06 Derry. NH F3 202 3.430 (2.284-5.072) 1.5 I 20.19 32.4 Litchfield. NH F2 220 3.805 (I.798-6.706) 1.21 20.21 35.9 Fairton. NJ F4 243 4.042 (2.424-5.699) I .87 + 0.34 38. I Albion, NY F5 24 2 36.28 (I5.61-195.4) 0.77±0. 15 342 Davie. NY F1 24 I 0.926 (0.529-1.394) 3.09 ± 0.57 8.74 Geneva, NY F23 242 0.106 (0.084-0.129) 3. 12±0.68 I .00 Long Island, NY F4 25 I 9.419 (7.104-12.51) 2.14±0.33 88.9 Ransomville. NY F3 24 3 9.299 (6.226-14.62) 1.30±0.19 87.7 Dover, DE F8 246 0.883 (0.430-1.722) I .84 ±0. I9 8.33

Midwest Celeryville, OH F3 219 1.176 (0.782-1.742) I .46 ± 0. I6 11.1 Fremont. OH F2 24 I 0.428 (0.144-0.964) 1. 19±0. 15 4.04 Simcoe. ONT F2 237 4.500 (3.152-6.150) 1 .82±0.25 42.4 Lake Co.. IN F2 214 3. I 19 (I.386-6.780) 1.28±0.15 29.4 Purdue, IN F2 240 0.389 (0.268-0.563) 1.90± 0.26 3.67 Holtz. MI F4 235 1.580 (0.841-2.567) 1.90±0.25 14.9 Stolz, MI F4 200 2.905 (I.741-4.507) 1.74±0.22 27.4 Arlington, WI F3 24 I 0.5 10 (0.33 1-0.755) 2.48±0.45 4.81 Funks E. S., WI F3 233 0.287 0.94±0.44 2.71 Funks M. S., WI F3 23 5 0.2 I7 (0.167-0.276) 3.78 ± 0.80 2.05 Heldings, WI F2 237 0.293 (0.I3 1-0.603) 1.84±0.27 2.76 Poynette, WI F2 24 3 3.995 (2.778-5.587) I .68 ± 0.2 I 37.7 Pacific Nakatani, HI F2 239 3.462 (I.925-5.739) 1.55±0.19 32.7 Pulehu, HI F86 206 0.563 (0.383-1.055) 3.07 ± 0.56 5.3 I Mt. Vernon, WA F2 213 0.284 (0.22 1-0.408) 3.25 20.72 2.68 Yakima. WA F4 208 0.424 (0.308-0.637) 2.49±0.4 I 4.00 b Southwest Belize, C.A. F1 239 38.39 7.65 ± 85. I 362 Bixby. OK F2 193 0.358 (0.250-0.545) 2.05 20.33 3.38 South Donna, TX F2 235 5.126 (4.098-6.309) 3.49±0.60 48.4 Tamu. TX F9 24 1 0.544 (0.369-0.908) 2.582 0.36 5.13 Weslaco, TX F1 232 2.500 (1.417-4.1 11) 1.87±0.23 23.6

South Zellwood, FL F1 248 4.039 (2.379-5.783) 2. I3± 0.36 38. I Tifton, GA F1 235 17.96 (12.15-31.37) I.44 ± 0.26 I69 Greenville, NC F1 240 82.73 (27.2-15680) 1.06±0.26 780 Painter, VA F5 235 0.507 (0.333-0.751) 1.43±0. 17 4.78 RR is the resistance ratio determined by dividing the LC50 for a population by the LC50 for the Geneva population. Neither the 95 nor 90% CL could be estimated because g > 0.5. Insecticide Resistance in North America 449

from Belize, and 342 from Albion, New York. When classified by levels of RR, 11% of the populations had an RR > 100, 6% from 50-99, 29% from 25 to 49, 8% from 10 to 24 and 46% < 10. Resistance ratios for permethrin were lower than for methomyl (Table 2). Resistance ratios for permethrin were highest in a population collected from Albion (80.8), followed by Belize, (78.4) and Tifton, Georgia (75.9). When classified by levels of RR, 17% of the populations had RRs > 50, 8% from 25 to 49, 19% from 10 to 24 and 56% < 10. The highest RR for methamidophos was 42.3 for the population collected from Belize (Table 3). When classified by levels of RR, none of the populations had an RR > 50, 3 % from 25 to 49, 13% from 10 to 24 and 83% < 10.

Table 2. Susceptibility to permethrin of DBM larval populations.

LC50-48h (95% CL) Region Population N Slope ± SE RRª mg AI/ml East Lochwood, CT F2 248 0.0 I9 (0.0 10-0.030) 1.24±0.20 0.58 Dover, DE F7 I98 0.541 (0.33 1-0.830) 1.66±0.24 16.4 Derry, NH F7 243 0.709 (0.44 I-1 ,003) 1.73±0.33 21.5 Litchfield. NH F2 238 0.452 (0.289-0.699) 1.2920.15 13.7 Fairton. NJ F3 24 3 0.26 1 (0.126-0.470) 2.02±0.24 7.91 Albion, NY F4 248 2.669 (1.949-3.810) 2.41 ±0.59 80.8 Davie. NY F1 I94 0.020 (0.007-0.040) 0.88±0.15 0.61 Geneva, NY F23 I95 0.033 (0.01 7-0.060) I .65±0.35 I .00 Long Island, NY F5 24 I 0.652 (0.520-0.80 I) 3.70±0.64 19.8 Ransomville. NY F2 244 1.614 (0.925-3.359) 1.19±0.20 48.9 Midwest Celeryville, OH F2 24 6 0.940 C 1.03±0.39 28.5 Fremont. OH F1 205 0.005 (0.000-0.003c) 0.4720.12 0.15 Simcoe, ONT F5 234 0.546 (0.269-1.045) 1.2820.17 16.5 Lake Co., IN F1 246 2.070 (0.977-7.630) 1.18±0.18 62.7 Purdue. IN F2 24 I 0.002 (0.000-0.006) 0.88±0.23 0.06 Arlington, WI F1 I56 0.322 (0.147-0.6 IO) 1.59±0.23 9.76 Funks E. S., WI F1 24 I 0.030 (0.018-0.048) 1.61 20.25 0.91 Funks M. S., WI F1 240 0.1 13 (0.060-0.194) 1.40±0.16 3.42 Heldings, WI F1 24 I 0.060 (0.028-0.105) I .74±0.27 I .82 Poynette, WI F1 247 0.3 I5 (0.163-0.497) 2.18±0.31 9.55 Pacific Santa Cruz, CA F4 229 0.004 (0.000-0.0 I2) 0.73±0.17 0.12 Nakatani. HI F3 245 0.097 (0.01 2-0.323 ) 2.02±0.26 2.94 Pulehu. HI F86 20 2 0.033 (0.006-0.097) 1.35±0.20 1.00 Yakima. WA F2 248 0.0 I3 (0.007-0.020) 1.78±0.47 0.39 Southwest Belize, C.A. F2 23 7 2.586 (I.883-3.998) 2.07±0.41 78.4 Celaya, MEX F3 23 9 0. 145 (0.089-0.23 I) 1.44±0.15 4.39 Bixby, OK F3 234 0.024 (0.0 12-0.042) 1.30±0.20 0.73 South Donna, TX F1 23 9 1.868 (I.337-2.737) 2.55±0.41 56.6 Tamu, TX F9 247 0.0 I6 (0.007-0.027) 1.42±0.27 0.48 Weslaco, TX F1 245 0.495 (0.390-0.603) 3.83 20.73 15.0 South Homestead, FL F1 206 0.45 I (0.247-0.836) 1.23±0.14 13.7 Zellwood. FL F1 238 1.162 (0.603-2.37 I) 1.96±0.29 35.2 Tifton. GA F1 246 2.507 (I.753-4.089) 2.03 20.41 75.9 Greenville, NC F2 229 1.654 (I.064-2.930) 1.2320.20 50.1 Painter, VA F5 220 0. I57 (0.087-0.274) 1.61 ±0.18 4.76 ªRR is the re istance ratio determined by dividing the LC50 for a population by the LC50 for the Geneva population. ‘90% CL. The 95% CL could not be estimated because g > 0.5. ‘Neither the 95 nor 90% CL could be estimated because g > 0.5. 450 Shelton and Wyman

Table 3. Susceptibility to methomidophos of DBM larval populations.

Region Population

East Lochwood, CT F1 242 0. 150 (0.109-0.207) 2.19±0.27 2.68 Dover, DE F3 I93 0.224 (0.059-0.344) 2.99±0.84 4.00 Derry, NH F7 245 0.223 (0.154-0.3 I8) 2.26 ± 0.27 3.98 Litchfield, NH F2 170 0.275 (0.150-0.334 ) 4.68± 1 .99 4.9 1 Fairton, NJ F4 230 0.556 (0.3 1 5-0.860b) 3.86±0.56 9.93 Albion, NY F6 239 0.738 (0.575-0.95 1) 2.49 ± 0.3 1 13.2 Davie. NY F1 248 0.209 (0.151-0.291) 2.29 ± 0.27 3.73 Geneva, NY F29 220 0.056 (0.042-0.071) 2.63±0.41 1 .00 Long Island. NY F5 243 0.468 (0.314-0.71 1) 2.44±0.29 8.36 Ransomville. NY F3 243 0.354 (0.273-0.458) 2.8620.36 6.32

Midwest Celeryville. OH F3 I73 0.203 (0.134-0.30 1) 1 .64±0.23 3.63 Fremont, OH F2 23 1 0.046 (0.032-0.060) 2.44±0.43 0.82 Lake Co.. IN F3 24 I 0.131 (0.089-0.179) 2.15±0.32 2.34 Purdue, IN F2 24 5 0. I02 (0.062-0.152) 2.01 ±0.27 1 .82 Holtz, MI F6 I86 0.321 (0.193-0.554) 2.07±0.23 5.73 Mt. Clemens, MI F1 22 I 0.049 (0.034-0.064) 2.74 ± 0.5 1 0.88 Big Lake, MN F2 24 2 0.058 (0.038-0.078) 2.49±0.46 1 .04 Funks E. S., WI F1 236 0.045 (0.024-0.067) 2.17±0.41 0.80 Poynette, WI F1 I49 0.247 (0.133-0.362) 2.70±0.62 4.4 I

Pacific Santa Cruz. CA F5 205 0.560 (0.025-0.092) 1.79±0.30 10.0 Nakatani. HI F2 217 0.920 (0.421 -3.085) 1.62±0.22 16.4 Pulehu. HI F86 I80 0.333 (0.136-0.472) 3.38±0.93 5.95 Yakima. WA F1 I52 0.028 (0.0 12-0.040) 2.75 ± 0.8 1 0.50

Southwest Celaya, MEX F5 200 0.657 (0.475-0.9 18) 3.2520.44 11.7 Belize, C.A. F1 24 I 2.371 C I .90 ± 0.29 42.3 Tamu. TX F16 243 0.057 (0.033-0.082) 2.592 0.48 1 .02 Weslaco, TX F1 240 0. I99 C 11.9± 125 2.13

South Zellwood, FL F2 243 0.096 C 2.21 20.29 1 .71 Tifton. GA F1 240 0.109 (0.075-0.165) 2.78 + 0.37 1 .95 Painter, VA F5 24 1 0. I29 (0.098-0.166) 2.30 ± 0.30 2.30 ªRR is the re istance ratio determined by dividing the LC50 for a population by the LC50 for the Geneva population. The 90% CL could not be estimated because g > 0.5. The 90% CL could not be estimated because g > 0.5.

DBM Infestations in Transplants In 1989, cabbage transplants (seedlings) were obtained from growers or brokers in Ontario, Yates, Monroe, Orleans and Genesee counties of New York who received shipments of transplants from Florida, Georgia, and Maryland (these states supply most of the transplants to New York). We also obtained locally grown transplants (Phelps, New York). Over the course of the spring and summer we sampled 28 different shipments for DBM and other pests. Sampling began with a shipment of cabbage from Georgia on 25 April and ended with a shipment of locally grown transplants on 29 June. A sample consisted of approximately 1000 transplants. As soon as it was received, each sample of transplants was inspected visually for DBM larvae. In addition, transplants were inspected for , Trichoplusia ni (Hubner), imported cabbageworm, Artogiea rapae (L.), and cabbage webworm, Hellula rogatalis (Hulst). DBM larvae collected during the first inspection were counted and transferred to rape seedlings, Brassica napus, and reared for insecticide assays. The inspected transplants were then placed Insecticide Resistance in North America 45 1 in soil in large pots and kept for two additional weeks, at which time a second inspection was performed to detect larvae that were not eclosed at first inspection. We were able to establish four colonies of DBM from transplants and tested the F2 generation using a leaf dip bioassay similar to Tabashnik et al. (1987) for susceptibility to permethrin and methomyl. Data were analyzed using the POLO procedure (Russell et al. 1977) to obtain LC values. Resistance ratios (RR), the ratio of the LC50 of a given population to that of the standard population, were calculated. The standard population used in this study originated from Painter, Virginia. This was chosen as our standard because it originated from a location which had a susceptible population (Shelton, A.M., unpublished). Infestations varied by source and date of collection (Table 4). Highest average DBM infestations for the season were from a Georgia source (3.44 insects/100 transplants) and a Maryland source (3.50 insects/ 100 transplants). Transplants originating in New York had fewer DBM larvae (0.59-1.10/ 100 transplants) than other states. The highest infestation on an individual shipment was found in a Florida sample which had 12.8 DBM/ 100 transplants. The seasonal average for all sources except Maryland had fewer than 0.50 other insects (imported cabbageworm, cabbage looper, and cabbage webworm) per 100 transplants collected. In 3 out of 4 cases, when transplants were sampled from the same source over several months, later samples had much higher infestations. By June, when most of transplants arrive in New York, infestations were as high as 8.2 DBM/ 100 transplants for a Florida company, and 7.3 DBM/ 100 transplants for a Maryland company. Based on LC50 values, the two Florida populations had RR of 7.3 and 8.3 to permethrin (Table 5), and 33.0 and 111.2 to methomyl (Table 6) in comparison with the standard population. The Georgia population had an RR of 24.1 to permethrin but only 4.6 to methomyl. The Maryland population had an RR of 12.5 and 13.1 to permethrin and methomyl, respectively.

Table 4. Insect infestation rates for cabbage transplants from southern sources, 1989. No. insects found per location sourceª Source No. April May June Season Average PIants DBM other DBM other DBM other DBM other Georgia A 2957 0 0 2.70 0.07 * 1.32 0.03 Georgia B 1059 1.32 0.09 * * 1.32 0.09 Georgia C 1892 4.26 0.22 * * 2.70 0.40 3.44 0.32 Maryland 8755 * * 0.23 0.46 7.30 5.60 3.50 2.80 Florida 5702 0 0 0.27 0.05 8.20 0.06 2.50 0.04 New York A 3 I90 * 1.10 0.16 1.10 0.16 New York B 1039 * 1.06 0.19 1.06 0.19 New York C 512 * * 0.59 0.20 0.59 0.20

ªValues listed are [No. insects/No. plants inspected) x 100]. insects included imported cabbageworm, cabbage looper, and cabbage webworm. No transplants intercepted from source during that particular month.

Table 5. Susceptibility of 3rd instar DBM larvae obtained from southern transplants to permethrin, 1989.

Population source Generation Slope LC50 95%FL (LC50) RRª (mg AI/ml)- Painter, Virginia (standard) F2 1.388 0.083 (0.042-0.146) I .0 Florida Company A F2 2.027 0.607 (0.381-0.982) 7.3 Florida Company B F2 1.717 0.687 (0.182-3.230) 8.3 Maryland F2 1.004 1.041 (0.271-6.230) 12.5 Georgia F2 8.425 2.002 X 24. I ªResistance ratio is the ratio of the LC50 of a given population to that of the standard population. Neither the 95 nor 90% CL could be estimated because g >0.5. 452 Shelton and Wyman

Table 6. Susceptibility of 3rd instar DBM larvae obtained from southern transplants to methomyl, 1989.

Population source Generation Slope LC50 95%FL (LC50) RRª (mg AI/ml) Painter, VA (standard) F1 0.882 0.256 (0.094-0.605) 1 .0 Florida Company A F2 2.698 8.458 (5.010-14.21) 33.0 Florida Company B F2 2.1 14 28.46 (I6.32-52.12) I I I .2 Maryland F2 0.90 I 3.35 I 13.1 b Georgia F2 0.093 1.164 4.6

ªResistance ratio is the ratio of the LC50 of a given population to that of the standard population. Neither the 95 nor 90% CL could be estimated because g>0.5.

Resistance to Bacillus thuringiensis In 1990, cooperators collected 50-150 DBM larvae and pupae from commercial cabbage fields in their respective areas. Some collections were made in areas where growers had experienced difficulty in controlling DBM with commercial formulations of Bacillus thuringiensis var. kurstaki, as well as other areas in which we did not have specific information on its effectiveness. Eleven populations from six states and Indonesia (Tables 7-8) were evaluated using a leaf dip bioassay similar to Tabashnik et al. (1987) for susceptibility to two B. thuringiensis products (Javelin WG and Dipel 2X) at 72 and 96 hours post-treatment. Data were analyzed using the POLO procedure (Russell et al. 1977) to obtain LC values. Resistance ratios (RR), the ratio of the LC50 of a given population to that of the most susceptible population, were calculated. DBM populations exhibited extreme variation in susceptibility to B. thuringiensis (Tables 7-8). Because we attempted to run all assays in the first generation (previous studies have sometimes shown dramatic declines in susceptibility to some insecticides (Sun et al. 1986 and Shelton, A.M., unpublished data), we were not always able to select the best set of doses to test against a particular population to bracket a 5-95 % response. However, high levels of resistance to the two products were seen in some Florida and New York populations. Conservative resistance ratios (based on the standard having an LC50 value lower than the lowest test rate) indicate an RR for Javelin of 211 and an RR for Dipel 2X of 214 for the Albion, NY, population which originated from transplants grown in Florida. High RRs were also noted in populations from Florida.

Table 7. Susceptibility of diamondback moth larval populations to Javelin WP. LC50 (95% CL) Populationª Slope ± SE Resistanceb mg (AI/l) Belle Glades FL C 0. 1 - Sanford FL 0.54±0.08 4.84 (I.88-12.5) 37 Sarasota FL 0.53 20.09 5.48 (I.94-15.5) 42 Zellwood FL 0.6620. I8 I I .94 (2.17-65.6) 92 Tifton GA C 0. 1 - Fletcher NC 1.21 20.28 0.21 (0. I 1-0.42) 2 Albion NY 0.77±0.22 27.54 (5.08-149) 21 I Hilton NY 0.882 0. 10 0.47 (0.28-0.79) 4 Penasquitos CA C 0. I 3d - Rio Grande TX C 0. I 3d - Bogor Indonesia C 0. I 3d -

ªsample size for each experiment was 150. Mortality was assessed 96 hours after ratio is the LC50 divided by the LC50 of the most susceptible population. Slope for a logit regression could not be estimated because the lowest concentration caused about 100% mortality. 95% CL for the LC50 could not be estimated because of poor fit of the probit regression model. Insecticide Resistance in North America 453

Table 8. Susceptibility of diamondback moth larval populations to Dipel 2X. Resistance Populationª Slope ±SE Ratiob Belle Glades FL 2.14± 2. I2 0. I2 (0.03-0.42) I Sanford FL 0.86±0.08 6.27 (3.72-10.5) 63 Sarasota FL 0.44 ± 0. I 3 6.68 (I .02-43.5) 67 Zellwood FL 0.662 0. I6 4. I5 (0.94- 18.4) 41 Tifton GA C 0. I 3d - Fletcher NC 0.91 20.23 0.23 (0.08-0.64) 2 Albion NY 1.04±0.22 2 I .4 (7.7 1-59.6) 214 Hilton NY 0.942 0.10 0.51 (0.32-0.80) 5 Penasquitos CA C 2. 00d - Rio Grande TX 1.92± 1.69 . 0.10 (0.03-0.36) 1 Bogor Indonesia C 0. I 3d -

ªsample size for each experiment was 150. Mortality was assessed 96 hours after treatment. Resistance ratio is the LC50 divided by the LC50 of the most susceptible population. Slope for a logit regression could not be estimated because the lowest concentration caused about 100% mortality. d95% CL for the LC50 could not be estimated because of poor fit of the probit regression model.

Conclusions

This study is the first one to examine DBM susceptibility over a broad geographic area and the results indicate high levels of resistance to three major classes of synthetic insecticides, as well as two major B. thuringiensis products. Resistance was generally highest in the southern states, but scattered populations with high levels of resistance were also detected in northern states. Insects with high levels of resistance, as indicated by laboratory assays, originated from locations where control failures occurred. This was especially true with populations from Belize, Florida, Georgia, North Carolina, and parts of New York and Wisconsin, the two major cabbage- growing areas in the northern US. Because of the short growing season in New York and Wisconsin and the absence of DBM overwintering in an adjacent area (Ontario, Canada) (Harcourt 1986), high levels of resistance would not be expected in New York and Wisconsin. Our studies indicate that DBM problems in these northern states can originate from DBM which are brought up on transplants grown in southern states. Thus, management of DBM on a regional basis becomes necessary. While it may be possible to restrict the shipment of DBM on plant material, natural migrations into an area may still occur. Information on the abundance of DBM entering into an area by these two methods is needed to determine the population structure of DBM within that area. Additionally, the source locations of DBM from transplants or migrations should be determined so that information on the susceptibility of incoming DBM can be examined. In areas where there is an endemic population which is already resistant to one or more classes of insecticides, the outlook for insecticide resistance management is disquieting. Sun et al. (1986) indicate that resistance does not decline rapidly after the application of this class of insecticides is terminated. With organophosphorus, resistance may be more unstable (Sun et al. 1986), but exploiting this lack of stability requires other options which can be used to economically and effectively manage DBM in the field. In the US, B. thuringiensis has been a viable option, but our data, along with data from the Philippines (Kirsch and Schmutterer 1988) and Hawaii (Tabashnik et al. 1990) indicate DBM resistance to B. thuringiensis. With this information, the success of continued spraying or incorporating the B. thuringiensis gene into plants is questionable. Other compounds with unique modes of action are being developed, but their long-term usefulness depends on careful management, and that feasibility is also questionable. One example is the development of benzoylphenylureas (BPUs) which interfere with chitin synthesis. Unofficial reports from Thailand indicate that DBM has already developed significant resistance to several BPUs only 2-3 years after their introduction (Perng 454 Shelton and Wyman et al. 1988). Development of noninsecticidal options such as cultural controls, biological control, disruption, sterile insect techniques and host plant resistance are urgently needed to allow insecticide resistance management strategies to be developed.

Acknowledgments

The authors would like to thank the following cooperators for collecting DBM from their areas: K. D. Biever, J. Bodnar, J. Bowman, B. Cartwright, R. Chalfant, W. Cranshaw, C. Eastman, J. Edelson, R. Foster, F. Gregory, E. Grafius, C. Hoy, R. Jansson, J. Johnson, G. Leibee, D. Letourneau, J. Linduska, D. Moyer, D. Prostack, T. Quick, T. Radcliffe, M. Sears, C. Simpson, K. Sorensen, J. Speese, B. Stanley, K. Stoner, B. Tabashnik, J. Walgenbach, J. Whalen, K. Short, A. York, T. Youngs, and J. Zender. Additional thanks to K. Apfelbeck, N. Cushing, S. Mahr, W. Wilsey, B. Cooley, and M. Kroening for technical assistance and J. Robertson for statistical assistance. This research was supported in part by a Wisconsin IPM grant and a Cornell IPM grant and the Wisconsin and New York Cabbage Research Associations.

References

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