FIELD AND FORAGE CROPS Sampling Strategies for Square and Boll-Feeding Plant Bugs (: ) Occurring on Cotton

MICHAEL J. BREWER,1,2 DARWIN J. ANDERSON,1 J. SCOTT ARMSTRONG,3 4 AND RAUL T. VILLANUEVA

J. Econ. Entomol. 105(3): 896Ð905 (2012); DOI: http://dx.doi.org/10.1603/EC12109 ABSTRACT Sampling methods for square and boll-feeding plant bugs (Hemiptera: Miridae) oc- curring on cotton, Gossypium hirsutum L., were compared with the intent to assess if one approach was viable for two species occurring from early-season squaring to late bloom in 25 Þelds located along the coastal cotton growing region of south Texas. Cotton ßeaphopper, Pseudatomoscelis seriatus (Reuter), damages squares early-season and dominated collections using Þve sampling methods (Ϸ99% of collected). A major species composition shift occurred beginning at peak bloom in coastal Þelds, when verde plant bug, signatus Distant, represented 55Ð65% of collections. SigniÞcantly more cotton ßeahoppers were captured by experienced samplers with the beat bucket and sweep net than with the other methods (30Ð100% more). There were more than twice as many verde plant bugs captured by experienced and inexperienced samplers with the beat bucket and sweep net than captured with the KISS and visual methods. Using a beat bucket or sweep net reduced sampling time compared with the visual method for the experienced samplers. For both species, comparing regressions of beat bucket-based counts to counts from the traditional visual method across nine cultivar and water regime combinations resulted in only one combination differing from the rest, suggesting broad applicability and ability to translate established visual-based economic thresholds to beat bucket-based thresholds. In a Þrst look at sample size considerations, 40 plants (four 10-plant samples) per Þeld site was no more variable than variation associated with larger sample sizes. Overall, the beat bucket is much more effective in sampling for cotton ßeahopper and verde plant bug than the traditional visual method, it is more suited to cotton ßeahopper sampling early-season when plants are small, it transitions well to sample for verde plant bug during bloom, and it performs well under a variety of soil moisture conditions and cultivar selections.

KEY WORDS cotton ßeahopper, Pseudatomoscelis seriatus, verde plant bug, Creontiades signatus, pest sampling

Visual inspection of the upper third of a cotton plant, (bolls). As a complex, these pests occurred in central Gossypium hirsutum L., including terminals had been and south Texas and less frequently in the southern a recommended method for monitoring three key High Plains and mid-south. A Þxed sample size was pests on cotton: adults of boll weevil, Anthonomus also recommended (Benedict et al. 1989), because grandis grandis Boheman (Coleoptera: Curculion- there were technical and practical difÞculties in using idae), eggs and small larvae of heliothines (Lepidop- more efÞcient methods, such as simultaneously using tera: Noctuidae), and nymphs and adults of the cot- sequential sampling plans designed for individual spe- ton ßeahopper, Pseudatomoscelis seriatus (Reuter) cies (Allen et al. 1972, Pieters and Sterling 1974, Wil- (Hemiptera: Miridae) (see review by Benedict et al. son 1994). In south Texas as an example, the impor- 1989 and citations within). This inspection may be tance of this pest complex and the simplicity of the combined with visual assessment of damage to cotton sampling protocol (i.e., no equipment for visual sam- ßower buds (squares) and young fruiting bodies pling and consistency of effort using a Þxed sample size) led to long-standing recommendation of this 1 Corresponding author: Texas AgriLife Research and Department protocol for public-based (Extension Service) inte- of Entomology, Texas AgriLife Research and Extension Center at grated pest management (IPM) agents and commer- Corpus Christi, 10345 State Hwy. 44, Corpus Christi, TX 78406 (e-mail: cial pest management consultants (Drees 1985, Parker [email protected]). 2 Corresponding author, e-mail: [email protected]. et al. 2009). 3 USDAÐARS BeneÞcial Research Unit, Kika de la Garza With beltwide adoption of transgenic Bt (Bacillus Subtropical Agricultural Research Center, 2413 E. Hwy. 83, Weslaco, thuringiensis)-cotton for heliothine (Lepidoptera: TX 78596. Noctuidae) control (Edge et al. 2001) and success in 4 Texas AgriLife Extension and Department of Entomology, Texas AgriLife Research and Extension Center at Weslaco, 2401 East Hwy. boll weevil eradication (Allen 2008), pest sampling has 83, Weslaco, TX 78596. been revisited with a focus on improving protocols for

0022-0493/12/0896Ð0905$04.00/0 ᭧ 2012 Entomological Society of America June 2012 BREWER ET AL.: SAMPLING STRATEGIES FOR PLANT BUGS ON COTTON 897

Table 1. Description of sampling procedures for six methods used to sample square and boll-feeding sucking bugs on cotton, 2010 and 2011, coastal growing region of south Texas

Methoda Equipment Sampling procedure Sweep net Standard 38-cm-diameter Þeld net made from thick Vigorous 10 pendulum sweeps across the top of the canopy white fabric, 90 cm wood handle along one row, down to base of small plants and into 20Ð25 cm of top growth of large plantsb Beat cloth One m2 white cloth framed with wood dowels on Placed on soil surface with one edge at the base on one two parallel sides row of cotton; 3Ð4 plants are quickly shakenc Beat bucket White 18-liter plastic bucket, 27 cm in diameter and Held at a tilt toward the plants, plantsc are grasped at the 37 cm in depth stem and bent into the bucket. 2Ð3 plants are quickly shakend Visual None Examine plant separating terminal growth and leaves to detect nymphsc,d KISS Leaf blower with 12.7- by 40.6-cm opening of net The blower and net are placed on opposite sides of plant held 30 cm from blower by a wire frame row. Insects are blown from 3.05 m of rowb,c Cage Whole plant cage made from organza fabric, 1.07 m Two people quickly cover 3Ð5 plants, cut plants at base, in diameter and 1.65 m in height and tie cage. Keep cool, freeze cages to chill insects, shake plants, and inspect cage fabric

a In 2010 the sweep net, beat cloth, beat bucket, visual, and KISS (Beerwinkle et al. 1999) methods were used; in 2011 the beat bucket, visual, and cage methods were used. b Counts adjusted to a per plant basis based on stand count. c Sample entire plant during early-season squaring and upper 20Ð25 cm (terminal growth) thereafter. d Continue to another section of row until 10 plants are sampled. stink bugs (Hemiptera: Pentatomidae) in the mid- damage (Armstrong et al. 2009). The situation pre- south and southeast (Musser et al. 2007, Reay-Jones et sented a challenge in sampling one species of the al. 2009). A complex of stink bug species (Hemiptera: traditional complex that threatened early-season Pentatomidae) injure cotton by feeding on bolls. Ex- squares (cotton ßeahopper) and another species that ternal and internal wounds of the carpel wall have occurred later in plant growth and threatened bolls been used as indicators of stink bug feeding (Toews et (verde plant bug), because visual sampling may al. 2009, Reay-Jones et al. 2010). For insect density change in efÞciency and effectiveness as the plant estimation, beat cloths have been found to be more matures. effective in sampling adults, while the sweep net was The cotton pest management industry is accus- more effective in sampling nymphs (Reay-Jones et al. tomed to a one-size-Þts-all sampling approach for the 2009). traditional pest complex. We propose that a sampling In contrast, the cotton insect pest complex along the protocol for cotton ßeahopper and verde plant bug south Texas coastal cotton growing region appears would be attractive to the industry if one method was to be composed mainly of plant bugs: the tradition- used for both species. To determine feasibility of this ally-occurring cotton ßeahopper and the more re- approach, our objectives were to compare insect sam- cent verde plant bug, Creontiades signatus Distant pling methods for these two square and boll-feeding (Hemiptera: Miridae). Boll-feeding stink bugs plant bug species from early-season squaring through (Hemiptera: Pentatomidae) also occur, although their late bloom. For selected sampling methods, we also abundance is variable, generally skewed toward low considered relationship to an existing economic densities, and greater in the upper Texas coastal areas threshold and sample size recommendations. where soybean is grown (Hopkins et al. 2009). Adults and nymphs of cotton ßeahopper feed on squares and Methods and Materials very young bolls, which results in excessive abscission (Ring et al. 1993). In investigating alternatives to vi- Growth Stage, Methods, and Experience Compar- sual inspection for cotton ßeahopper, the beat sheet ison. Sucking bugs (Hemiptera: Miridae, and Pentato- and beat bucket were favored over the sweep net and midae) were sampled along the coastal cotton grow- visual observation as measured by time required to ing regions of south Texas. In 2010, 25 cotton Þelds sample and numbers of insects caught (Pyke et al. were sampled using Þve sampling methods (Table 1) 1980). The sweep net was preferred by Parajulee et al. during three cotton growth periods (early-season (2006) based on Þxed precision cost reliability, but squaring, early bloom, and peak through late bloom) when considering other operational factors the beat and by samplers differing in experience (with prior bucket was recommended for commercial pest mon- years of sampling experience or no experience). All itoring use. Boll feeding by verde plant bug is con- samplers were provided 30 min of Þeld training on centrated on young bolls during peak to late bloom, methods and given background of the project. At least resulting in lint and seed damage (Armstrong et al. two samplers representing the two experience levels 2009). Sampling approaches included visual inspec- randomly sampled groupings of at least 10 plants with tion during bloom to determine if verde plant bug was the Þve methods at four locations in each Þeld. Lo- present, if bolls showed signs of feeding, and if bolls cations were no closer than 25 m from a Þeld edge to had reached an age when they were less prone to avoid edge effects. The plant bugs were identiÞed and 898 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 105, no. 3 counted in the Þeld, and counts were adjusted to a per was detected. TukeyÕs test was used in all subsequent plant basis using actual plant counts or stand count means separation tests in this study. estimates (Table 1). Time to sample for all species was Comparison to a Whole Plant Caging Method. In recorded at 22 of the Þelds, which consisted of time to 2011, sampling methods chosen as the most promising take the sample, counting all insects, and recording the used by experienced samplers (i.e., beat bucket and counts. For verde plant bug, nymphs and adults were sweep net) were compared with a whole plant caging counted separately to assess potential sampling method (Table 1). Whole plant caging has been used method biases for this new pest. For cotton ßeahopper to approximate an absolute count in some crop appli- and other species, nymphs and adults were recorded cations including cotton (Knutson et al. 2008). The as a sum total. The Þelds were selected randomly from whole plant caging method was of special interest to a group identiÞed as having plant bug activity by see if stink bugs were detected, because they were cooperating pest consultants. Locations by Texas rarely detected with the Þve methods used in 2010. county and GPS coordinates were Calhoun County The sampling procedures from the 2010 methods were (28.580Њ N, 96.664Њ W, 28.551Њ N, 96.645Њ W, and 28.550Њ used with the following modiÞcation: seven Þelds N, 96.65Њ W), Aransas County (28.098Њ N, 97.218Њ W), were visited, sampling was done by experienced sam- Nueces County (27.781Њ N, 97.561Њ W, 27.786Њ N, plers, time to sample data were not taken, nymphs and 97.560Њ W, 27.776Њ N, 97.562Њ W, 27.770Њ N, 97.562Њ W, adults were counted together, and the caged plants 27.725Њ N, 97.668Њ W, 27.708Њ N, 97.668Њ W, 27.708Њ N, were taken to the laboratory and chilled before count- 97.668Њ W, 27.708Њ N, 97.644Њ W), Kleberg County ing the insects. Fields were in the same area as those (27.437Њ N, 97.848Њ W, 27.426Њ N, 97.875Њ W, and 27.446Њ visited in 2010. Insect count adjustment to a per plant N, 97.910Њ W) and Cameron County (26.210Њ N, basis, count data transformation, and data averaging 97.480Њ W, 26.204Њ N, 97.953Њ W, 26.243Њ N, 97.651Њ W, across samplers were done as in 2010. 26.165Њ N, 97.652Њ W, 26.289Њ N, 97.862Њ W, 26.243Њ N, The cotton ßeahopper was the focus during early- 97.651Њ W, 26.191Њ N, 97.367Њ W, 26.207Њ N, 97.856Њ W, season squaring, and the verde plant bug was the focus 26.242Њ N, 97.872Њ W, and 26.239Њ N, 97.758Њ W). The during peak to late bloom; therefore, the analyses Þelds were planted to multiple cultivars adapted to the were performed separately by species for the respec- region. Insecticides were used occasionally for plant tive cotton growth periods. Insect counts of nymphs and adults of each species for each method were based bug control, but sampling occurred before spraying or on a 10-plant sample in each plot and adjusted to a per at least two weeks after an application. plant basis. Relative sampling efÞciency of the visual Summing counts across all Þelds, relative number of and beat bucket methods to the whole plant caging cotton ßeahopper, verde plant bug, and other square method was calculated (mean count [visual or beat and boll-feeding species collected were compared for bucket] divided by mean count whole plant caging). each method and growth stage by using a ␹2 test of After transformation as described in the previous sec- equality (Freund and Walpole 1980). Based on this tion, measurements were also analyzed in a single analysis, counts of predominant species and corre- factor (sampling methods) ANOVA replicated across sponding time to sample data were analyzed sepa- seven Þelds (cotton ßeahopper) and four Þelds (verde rately with analysis of variance (ANOVA). Data were plant bug). Field was used as a blocking factor in the averaged across samplers of the same experience level analysis. If the method factor was signiÞcant, numbers before analysis. These data were adjusted to a per of collected insects using the three methods were plant basis (insect counts) and 10-plant basis (time to compared using TukeyÕs mean separation test. sample), and insect counts were transformed by the Relationship of Visual and Beat Bucket Methods ϩ square root of (x 0.5). across Growing Conditions. In 2011 at one Þeld, ex- The ANOVA followed a split-split-plot design. The perienced samplers used the beat bucket and visual main plot was the plant growth stage factor (three methods for cotton ßeahopper and verde plant bug levels), the Þrst split was the experience of the sampler sampling. Sampling was done on three cultivars (i.e., (two levels), and the second split was the sampling Phytogen 367 WRF [PhytoGen Seed, Dow AgroSci- method (Þve levels). Field replication was used as a ences, Indianapolis, IN], Deltapine 1032 B2RF [Del- blocking factor in the analysis. The levels were con- tapine, Monsanto, St. Louis, MO], and Stoneville 5458 sidered Þxed, and three error terms were used to test B2RF [Bayer CropScience, Research Triangle Park, the main factors and their interactions (Neter et al. NC]) under three water regimes (i.e., dryland, irri- 1985). Because verde plant bug was only detected at gation scheduled at 75% of evapotranspiration re- 15 Þelds during peak to late bloom, the ANOVA con- placement, and irrigation scheduled at 90% of evapo- formed to a split-plot design using two error terms transpiration replacement) and planted on two dates (Neter et al. 1985). Comparison of the Þve methods (i.e., 1 April representing a common date for the re- was the primary interest; therefore mean separation gion, and 20 April representing a late date for the tests (TukeyÕs Honest SigniÞcant Difference (Littell region). The treatment combinations represented a et al. 1991)) were performed on the Þve methods by broad range of moisture conditions, planting dates, slicing data by the two experience levels and three and cultivar selections in the growing region. The cotton growth stages whenever a method interaction intent was to compare the promising beat bucket with these factors were detected. TukeyÕs test also was method to the traditional visual method across varying done to separate method means when no interaction conditions in a replicated experimental setting that June 2012 BREWER ET AL.: SAMPLING STRATEGIES FOR PLANT BUGS ON COTTON 899 reßects various conditions a grower may experience an economic threshold for verde plant bug was not but was not be experienced in our larger survey of available and using multiple sequential sampling plans commercial Þelds. Treatments were arranged in a split for different species can be problematic (Wilson plot design of Þve replications, with water regime as 1994). Data used were from experienced samplers in the main plot and the six combinations of cultivar and 2010 focusing on cotton ßeahopper at early-season planting date as the split plot. Each plot measured squaring and focusing on verde plant bug at peak to 30.5 m by four rows. Land cultivation, fertilization, and late bloom. Means, standard errors, and coefÞcients of planting were standard for the growing region. No variation (CV, as a percentage of the mean) for insect insecticides were used. Data were taken on the inner counts (per plant) and time to sample (per 10 plants) two rows. Drought conditions were severe: Ϸ7.6 cm of were calculated across Þelds. These descriptive sta- rainfall 1 April through 30 August compared with 45.7 tistics were calculated for verde plant bug using 120, cm in 2010 and a 35.5 cm average over 125 yr (National 80, and 40 plants taken in groups of 10 plants and for Weather Service 2011). Insect colonization was de- cotton ßeahopper using 80 and 40 plants taken in layed; therefore insect counts were used only for the groups of 10 plants. Therefore, variation estimates late planting. were based on 10-plant observation units of 12, 8, and Cotton ßeahopper was the focus of three consec- 4, drawn sequentially from the data set (i.e., each utive weeks of sampling from early-season squaring Þeld) and taking a single draw from the beginning of through early bloom, and verde plant bug was the the data set to have the same number of values to focus of three weeks of sampling beginning at peak generate the mean estimates. For each species and bloom. Insect counts of nymphs and adults of each sample size scenario, means and CVs of the three species for each method were based on a 10-plant methods were compared using a one-way ANOVA, sample in each plot, adjusted to a per plant basis, and with Þeld as a blocking factor, followed by TukeyÕs transformed before regression analyses. Correlation means separation test if the methods factor was sig- analysis was used to compare separate counts of niÞcant. nymphs and adults to the total count. Using trans- formed data across all weeks of targeted sampling periods and from the nine combinations of the cultivar Results and Discussion and water regime factors, simple linear regression was used to regress density estimates using the beat bucket Growth Stage, Methods, and Experience Compar- method to density estimates using the visual method. ison. In collections from 25 coastal and inland Þelds in To test sensitivity of the summary regression across 2010, over 99% of the insects collected using all Þve these nine combinations, an indicator variable was sampling methods were cotton ßeahopper during ear- used to compare a regression line estimated from each ly-season squaring through early bloom. But for the 12 cultivar/water regime treatment combination to a re- coastal Þelds during peak to late bloom, 55Ð65% of the gression line estimated from the data representing the insects collected were verde plant for each method remaining cultivars and water regimes (Neter et al. (Fig. 1), while verde plant bug was not detected in 1985). As an additional analysis check, an analysis of inland Þelds. Cotton ßeahopper and verde plant bug covariance (ANCOVA) approach was taken compar- dominated the collections, as judged by the signiÞcant ing the nine treatment combinations of cultivar and ␹2 tests of equality for the three growth stages (early- irrigation regime, using transformed beat bucket season and early bloom for all methods: df ϭ 1, ␹2 Ͼ counts as the dependent variable and visual counts as 100, P Ͻ 0.005; peak/late bloom for all methods: df ϭ the covariate and disregarding the replication and 2, ␹2 Ͼ 20; P Ͻ 0.005) and the large cell contributions observation date structure of the design (Littell et al. for cotton ßeahopper (all growth stages) and verde 1991). A cotton ßeahopper economic threshold of 15 plant bug (peak/late bloom). cotton ßeahoppers per 100 plants using the visual Cotton Fleahopper. In comparing growth stage, ex- method in south Texas (Benedict et al. 1989) was perience level, and sampling method, the 3-way in- translated to its equivalent using the beat bucket teraction was not signiÞcant (P ϭ 0.18). One two-way method using a common regression or separate re- interaction was signiÞcant (sampling method by ex- gressions depending upon the outcome of the analy- perience level: P ϭ 0.009, Table 2) and one two-way ses. This procedure was not done for verde plant bug interaction was nearly signiÞcant (sampling method because an economic threshold is currently not es- by plant growth stage: P ϭ 0.06, Table 2). The beat tablished. Use of the verde plant bug regression still bucket and sweep net methods accounted for more remains valuable for those using the visual method and captures than the other methods, especially starting at considering adopting the beat bucket method. early bloom (Fig. 2A). For experienced samplers, sig- Sample Size Considerations. For the beat bucket niÞcantly more cotton ßeahoppers were captured and sweep net methods, variation associated with with the beat bucket and sweep net than with the mean estimates of cotton ßeahopper and verde plant other methods (Fig. 2B). Inexperienced samplers de- bug was explored across several Þxed sample sizes and tected fewer cotton ßeahoppers, and their counts compared with variation associated with mean esti- were uniformly low among the methods (Fig. 2B). mates of the visual method. Sequential sampling for This is not an uncommon result for inexperienced classiÞcation, where sample size is a random variable samplings, and points out the importance of well- and error rates are Þxed, was not considered because trained samplers (Hoff et al. 2002). 900 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 105, no. 3

teractions of sampling method by growth stage (P ϭ 0.006, Table 2) and sampling method by experience level (P Ͻ 0.0001, Table 2). Even though fewer plant bugs were collected on a per plant basis, the KISS and visual methods took longer to perform than the other methods with some variation detected across sampling periods (Fig. 4A). It took nearly twice the time for experienced sampler to visually inspect plants, espe- cially the older plants, compared with when experi- enced samplers used the beat cloth, beat bucket, and sweep net (Fig. 4B). Using a beat cloth, beat bucket, or sweep net was key to reducing sampling time for the experienced samplers (Fig. 4B). Wilson et al. (1989) also noted that fatigue and lack of insect knowledge may result in under-estimation of densities by inex- perienced samplers. Comparison to Whole Plant Caging Method. In 2011, severe drought limited surveys to seven Þelds where plant bugs were detected. When using the whole plant caging method, very few stink bugs were detected relative to verde plant bug and cotton ßea- hopper (Ͻ0.1% of total insects collected). This very low percentage was similar to last yearÕs results, sug- gesting an infrequent occurrence of stink bugs and not a sampling method bias. Stink bugs previously had been found in low densities in our study area, while they were more commonly found north of our study area where soybean was grown (Hopkins et al. 2009). Further analyses centered on cotton ßeahopper during early-season squaring and verde plant bug dur- ing peak to late bloom. The visual method detected about half the number of cotton ßeahopper and verde plant bug than detected with the whole plant caging method (relative sampling efÞciency to the absolute sampling was 0.48 and 0.45, respectively) (Table 3). In contrast, the relative sampling efÞciency was 0.74 us- ing the beat bucket method to sample for cotton ßea- phopper, while the beat bucket actually captured more verde plant bugs than the whole plant caging method (relative sampling efÞciency was 1.57, Table 3). We suspect the relative sampling efÞciency would have been closer to 1.0 if the cages had been set at the Fig. 1. The proportion of each species collected, sum- base of the plant the day before and then quickly ming data across samplers for the Þve sampling methods pulled up over the plant to reduce insect escapes. during early-season squaring for all Þelds (A), early bloom Despite this concern, the high sampling efÞciency for all Þelds (B), and peak through late bloom for coastal substantiated that the beat bucket was particularly Þelds (C) in 2010. Above each bar is the total collected. Dark useful in sampling verde plant bug compared with the gray ϭ verde plant bug, Light gray ϭ cotton ßeahopper, Black ϭ Combined Lygus spp., rice stink bug, and green stink visual method (Fig. 3). Parajulee et al. (2006) previ- bug. ously recommended this method in a commercial set- ting where ease of use and local availability of buckets make it especially attractive. The methods factor in the Verde Plant Bug. The two-way interaction between ANOVA was not signiÞcant, likely because of high sampling method and experience level was not signif- variation in the counts (Table 3). icant (P ϭ 0.35). Averaging across experience, there Visual/Beat Bucket Regressions and Relationship were more than twice as many verde plant bugs cap- to a Cotton Fleahopper Economic Threshold. Strong tured with the beat bucket and sweep net than cap- correlations of cotton ßeahopper nymphs and adults tured with the KISS and visual methods (P ϭ 0.0015, to the total count were seen for visual and beat bucket Table 2) (Fig. 3). sampling methods (n Ն540, r Ͼ 0.86, P Ͻ 0.001 for all Time to Sample. The three-way interaction be- four comparisons). The counts of verde plant bug tween growth stage, experience level, and sampling nymphs and adults to the total count were signiÞcantly method was signiÞcant (P ϭ 0.03, Table 2). The great- correlated when using the beat bucket (n ϭ 270; cor- est contributions to variation were the two-way in- relation between nymphs and total counts: r ϭ 0.90, June 2012 BREWER ET AL.: SAMPLING STRATEGIES FOR PLANT BUGS ON COTTON 901

Table 2. Summary statistics from ANOVAs comparing cotton fleahopper counts and time to sample data taken among five sampling methods at two plant growth stages by samplers with two levels of experience

Cotton ßeahoppera Verde plant buga Time to sampleb Source of variation DF F P DF F P DF F P Plant 2, 15 0.16 0.86 2, 11 3.65 0.06 Experience 1, 33 5.03 0.03 1, 10 2.14 0.17 1, 27 0.08 0.78 Plant by experience 2, 33 0.9 0.43 2, 27 1.89 0.17 Method 4, 288 8.10 Ͻ0.0001 4, 56 5.05 0.0015 4, 236 39.34 Ͻ0.0001 Method by plant 8, 288 1.90 0.06 8, 236 2.77 0.006 Method by experience 4, 288 3.47 0.009 4, 40 1.15 0.35 4, 236 42.42 Ͻ0.0001 Method by plant by experience 8, 288 1.43 0.18 8, 236 2.13 0.03

Verde plant bug was found in 15 Þelds at the peak to late bloom plant growth stage; therefore analyses followed a split-plot design. Data taken from 25 Þelds along the Texas coastal cotton growing region, 2010. a Error A ϭ Þeld by plant growth interaction, used to test plant growth factor; Error B ϭ Þeld by plant growth by experience interaction, used to test experience factor and plant growth by experience interaction; Error C ϭ residual, used to test remaining sources of variation. b Error A ϭ Þeld by experience interaction, used to test experience factor; Error B ϭ residual, used to test two-way interaction.

P Ͻ 0.001; correlation between adult and total counts: visually inspected, whereas an experienced sampler n ϭ 270, r ϭ 0.82, P Ͻ 0.001) and when using the visual will sample the plant and count captured bugs quickly method (correlation between nymphs and total with the beat bucket resulting in fewer escapes. counts: n ϭ 270, r ϭ 0.81, P Ͻ 0.001; adult/total: n ϭ Total counts were used in the regression analyses 270, r ϭ 0.62, P Ͻ 0.001). For insect density estimation, comparing insect counts using the beat bucket and Reay-Jones et al. (2009) found differences in catch visual sampling methods. For both species, regressing efÞciencies for nymphs and adults of stink bugs when beat bucket-based counts on visual-based counts was using beat cloths and sweep nets. Based on our cor- fairly robust across the nine combinations of cultivar relations, adults were under-represented using the and water regime. Only the regression using data from visual method in comparison to using the beat bucket the Deltapine cultivar/ high irrigation treatment dif- method. A likely explanation is that adult cotton ßea- fered from the composite regression using data from hoppers readily ßy when disturbed as the plant is the remaining eight cultivar/ water regime treatments

Fig. 2. Two-way interactions of sampling method by plant growth stage (A) and sampling method by experience level (B) when estimating densities of cotton ßeahopper from cotton Þelds (n ϭ 26). Lines are SEMs. Means with the same lower case, upper case, and italics lower case letters across methods are not signiÞcantly different (TukeyÕs means separation test, ␣ ϭ 0.05, by slicing data by plant growth stage (A) and experience level (B). 902 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 105, no. 3

Fig. 3. The sampling method factor when estimating densities of verde plant bug from cotton Þelds (n ϭ 12). Lines are SEMs. Means with the same letter across methods are not signiÞcantly different (TukeyÕs means separation test, ␣ ϭ 0.05).

(regression line comparison: P Ͻ 0.02 for cotton ßea- differed from the hypothesis of common relationship hopper and verde plant bug) (Table 4). This regres- among the nine treatment combinations (cotton ßea- sion was conÞrmed using the ANCOVA approach. The hopper: t ϭϪ2.86, df ϭ 260, P ϭ 0.005; verde plant bug: visual count covariate was signiÞcant for both cotton t ϭ 2.10; df ϭ 260; P ϭ 0.04). ßeahopper and verde plant bug (F Ͼ 59; df ϭ 1, 260; An established economic threshold of 15 cotton P Ͻ 0.0001). And as in the regression approach, only ßeahoppers per 100 plants (Benedict et al. 1989) using the beat bucket and visual count parameter estimate the visual method translated to 48 cotton ßeahoppers from the Deltapine cultivar/ high irrigation treatment per 100 plants using the beat bucket method using the

Fig. 4. Two-way interactions of sampling method by plant growth stage (A) and sampling method by experience level (B) when recording time needed to sample square and boll-feeding sucking bugs from cotton Þelds (n ϭ 26). Lines are SEMs. Means with the same lower case, upper case, and italics lower case letters across methods are not signiÞcantly different (TukeyÕs means separation test, ␣ ϭ 0.05, by slicing data by plant growth stage (A) and experience level (B). June 2012 BREWER ET AL.: SAMPLING STRATEGIES FOR PLANT BUGS ON COTTON 903

Table 3. Mean (؎ SEM) total (nymphs and adults) insect counts four 10-plant samples in the Þeld when using the beat per plant using the visual, beat bucket, and absolute sampling bucket and sweep net. The sample size is applicable to methods during early-season squaring (cotton fleahopper) and peak bloom (verde plant bug) a location that is homogeneous with respect to plant health, planting time, irrigation, and other agronomic Cotton Verde and environmental conditions. Sequential sampling Method ßeahopper plant bug approaches may be possible given the few species and Mean Ϯ SEM REa Mean Ϯ SEM REa growth stage separation of their occurrence. Sequen- Visual 1.91 Ϯ 0.42 0.48 0.94 Ϯ 0.22 0.45 tial approaches using accepted economic thresholds Beat bucket 2.97 Ϯ 0.58 0.74 3.23 Ϯ 1.49 1.57 may improve sampling quality (Þxed error rates). But Whole plant caging 4.01 Ϯ 1.47 2.08 Ϯ 0.82 sample size reductions likely will be marginal given the practical aspects of sampling in groups (Wald Means differences among methods were not detected in the ANOVA and post-ANOVA contrast statements comparing the visual 1947), such as groups of 10 plants when using a beat and beat bucket means to the absolute mean. bucket in this study. Data taken from seven (cotton ßeahopper) and four (verde plant The general consensus in the literature was that bugs) Þelds along the Texas coastal cotton growing region, 2011. alternative methods to visual inspection of stink bugs a Relative efÞciency: mean count ͓visual or beat bucket͔ divided by mean count whole plant caging. and plant bugs were available. Buckets and drop cloths (beat sheets) usually were identiÞed as effective, and efÞciencies were affected by factors such as crop stage composite regression (Table 4). Our analyses support and insect development stage (Pyke et al. 1980, Reay- use of this relationship in most situations, but consid- Jones et al. 2009). The catch efÞciency of the sweep eration of a higher threshold using the beat bucket net was variable across studies. Some reported poor method is appropriate in well irrigated or high soil catch efÞciencies (Smith et al. 1976) while others moisture Þelds for some cultivars (a beat bucket eco- found the sweep net efÞcient in sampling cotton ßea- nomic threshold of 55 cotton ßeahoppers per 100 hopper and stink bugs under selected conditions (e.g., plants is the equivalent). Given variation associated Parajulee et al. 2006, Reay-Jones et al. 2009). But in our with the regression and use of the sampling methods, system, the sweep net was difÞcult to use when ßea- we propose for Þeld application a low economic hopper sampling is critical for decision-making. The threshold of 40 cotton ßeahoppers per 100 plants using beat bucket was more ßexible for early-season and the beat bucket is appropriate for producers with a low bloom period sampling, and it had comparable catch pest risk and high intensity management perspective. efÞciency to the sweep net (Figs. 2, 3). It was much A higher economic threshold of 55 cotton ßeahoppers more catch efÞcient in collecting verde plant bug per 100 plants is more appropriate for producers using during the bloom period than the visual method (Fig. an IPM approach of frequent Þeld scouting for insects 3). The beat bucket also performed well across a range and square damage, especially when the cotton Þeld of cultivars and soil moisture conditions (Table 4) and is well irrigated or experiencing good moisture con- sample sizes (Table 5). Last, it is effective in sampling ditions. for natural enemies in cotton (Knutson et al. 2008) and Sample Size Considerations. The sweep net and headworms in sorghum (a rotational crop with cot- beat bucket consistently had signiÞcantly higher cap- ton) (Parker et al. 2009). tures of cotton ßeahopper and verde plant bug than In the literature, the shake bucket (similar to the when using the visual sampling method. There were beat bucket but shorter in depth) and beat bucket no capture differences detected for the sweep net and often were viewed as an acceptable sampling method beat bucket under several sample size scenarios (Ta- for cotton insects based on a combination of catch ble 5). Variation was high, resulting in no difference efÞciency, low time requirements to sample, and ease in CVs among sampling methods for each sample size of use (Pyke et al. 1980, Parajulee et al. 2006, Knutson scenario (Table 5). This Þrst look at sample size con- et al. 2008). The visual method generally was the least siderations suggested that sampling could be reduced effective, either in catch efÞciency, time to sample, or to 40 plants without substantial increase in variation of both. In contrast, Parajulee et al. (2006) found the the estimate. The sample size of 40 plants equates to visual method detected more cotton ßeahopper than

Table 4. Linear regressions of density estimates of cotton fleahopper and verde plant bug by using the beat bucket method (dependent variable) to density estimates using the visual method (independent variable)

Insect Regression n Slope Ϯ SE Intercept Ϯ SE Cotton ßeahopper Composite 240 1.63 Ϯ 0.05 0.24 Ϯ 0.08 Deltapine and high irrigation 20 0.86 Ϯ 0.09 0.42 Ϯ 0.17 Verde plant bug Composite 114 0.56 Ϯ 0.16 0.06 Ϯ 0.01 Deltapine and high irrigation 30 1.30 Ϯ 0.83 0.14 Ϯ 0.04

Statistical tests were done using transformed data; slope and intercept estimates are given in untransformed units. The regression of the Deltapine and high irrigation treatment differed from the composite regression from the remaining eight cultivar or water regime treatments for cotton ßeahopper (t ϭ 3.16, df ϭ 1; P ϭ 0.002) and verde plant bug (t ϭϪ2.27, df ϭ 1; P ϭ 0.02). Data taken from one experimental Þeld with treatment combinations representing moisture conditions and cultivar selections in the Texas coastal cotton growing region, 2011. 904 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 105, no. 3

Table 5. Means and coefficients of variation (percentage of the mean) of total counts (nymphs and adults) per plant using the sweep net, beat bucket, and visual sampling methods under several sample size scenarios

Sample Sample N Mean Ϯ SEM CV N Mean Ϯ SEM CV size method 40 Sweep net 10 2.19 Ϯ 0.69a 99.9a 4 10.56 Ϯ 4.04a 76.5a Beat bucket 10 1.61 Ϯ 0.45a 88.9a 4 5.94 Ϯ 2.34ab 78.9a Visual 10 0.98 Ϯ 0.25b 81.4a 4 2.31 Ϯ 1.16b 100.4a 80 Sweep net 10 2.37 Ϯ 0.64a 85.6a 4 9.78 Ϯ 3.71a 75.9a Beat bucket 10 1.75 Ϯ 0.49a 87.9a 4 7.00 Ϯ 3.08ab 87.9a Visual 10 0.95 Ϯ 0.24b 80.4a 4 2.53 Ϯ 1.47b 116.3a 120 Sweep net 4 8.92 Ϯ 3.54a 79.3a Beat bucket 4 7.46 Ϯ 3.17a 85.0a Visual 4 2.58 Ϯ 1.55b 120.3a

⌵ was the number of Þelds sampled and was kept constant across sample size scenarios. Only two Þelds had cotton ßeahopper captures for a sample size scenario of 120; therefore it was not considered. Different letters among sampling methods within a sample size indicate signiÞcant differences at ␣ ϭ 0.05 using TukeyÕs means separation test. Analyses based on transformed data, and descriptive statistics based on untransformed data. Data taken from 25 Þelds along the Texas coastal cotton growing region, 2010. the beat bucket when experienced samplers used the References Cited methods, but they concluded that the beat bucket was more appropriate for pest management decision-mak- Allen, J., D. Gonzalez, and D. Gokhale. 1972. Sequential sampling plans for the bollworm, Heliothis zea. Environ. ing partly because it was much more time efÞcient. Entomol. 1: 772Ð780. Wilson et al. (1989) noted that commercial crop ad- Allen, C. T. 2008. Boll weevil eradication: an areawide pest visors often adopted the visual method for stink and management effort, pp. 467Ð559. In O. Koul, G. Cuperus, plant bug sampling because it had been successfully and N. Elliott (eds.), Areawide pest management. CAB used as part of a plant damage and insect monitoring International, Wallingford, United Kingdom. system for cotton boll weevil and heliothines. We Armstrong, J. S., J. J. Admaczyk, and R. J. Coleman. 2009. interpreted this observation as matching a philosophy Determining the relationship between boll age and green of method consistency from an operational, and not a plant bug feeding injury to South Texas cotton, pp. 717Ð sampling efÞciency, perspective. 720. In Proc. Beltwide Cotton Conf., San Antonio, TX. 5Ð8 We propose that advisors may be willing to change Jan. 2009. Natl. Cotton Counc. Am., Memphis, TN. to an alternative method if it meets Þeld operational Beerwinkle, K. R., J. R. Coppedge, and C. Hoffmann. 1999. criteria for sampling methods: a method suitable for all A new mechanical method for sampling selected bene- species of interest, rapid and easy to use, and easily Þcial and pest insects on cornÑthe corn KISS. Southwest. integrated into a Þeld monitoring program (Knutson Entomol. 24: 107Ð113. et al. 2008). From this viewpoint, our results supported Benedict, J. H., K. M. El-Zik, L. R. Oliver, P. A. Roberts, and L. T. Wilson. 1989. Economic injury levels and thresh- use of the beat bucket method, using a common white, olds or pests of cotton, pp. 121Ð151. In R. E. Frisbie, K. M. 18-liter, plastic pail, to sample the plant bug pest com- El-Zik, and L. T. Wilson (eds.), Integrated pest manage- plex found along the coastal cotton growing region of ment systems and cotton production. Wiley, Somerset, Texas. Overall, the beat bucket is much more effective NJ. in sampling for cotton ßeahopper and verde plant bug Drees, B. M. 1985. Management of cotton insects in south than the traditional visual method, it is more suited to and east Texas counties. Bull 1204, Texas Agric. Ext., cotton ßeahopper sampling during early-season squar- College Station, TX. ing than the sweep net, it transitions well to sample for Edge, J. M., J. H. Benedict, J. P. Carroll, and H. K. Reding. verde plant bug during bloom, it performs well under 2001. Bollgard cotton: an assessment of global economic, a variety of soil moisture conditions and cultivar se- environmental, and social beneÞts. J. Cotton Sci. 5: 121Ð lections, and has utility for sampling other insects in 136. cotton and sorghum. Freund, J. E., and R. E. Walpole. 1980. Mathematical sta- tistics, 3rd ed. Prentice-Hall, Englewood Cliffs, NJ. Hoff, K. M., M. J. Brewer, and S. L. Blodgett. 2002. Alfalfa weevil (Coleoptera: Curculionidae) larval sampling: Acknowledgments comparison of shake-bucket and sweep-net methods and We thank J. Martinez, E. Rodriquez, M. Bloemer, and C. the effect of training. J. Econ. Entomol. 95: 748Ð753. Farias for assistance in insect Þeld sampling. Thanks to L. Hopkins, B. W., A. E. Knutson, J. S. Bernal, M. F. Traecy, and Hutchins, J. Norman, S. Hopkins, M. Treacy, J. Trolinger, and C. W. Smith. 2009. Species composition, damage poten- S. Biles for identifying sucking-bug infested Þelds, and we tial, and insecticide susceptibility of sink bugs in cotton in thank Þeld owners (D. Mayo, M. Mutchler, R. Neiman, C. the lower Gulf Coast region of Texas. Southwest. Ento- Neiman, D. Nunley, S. Simmons, L. Simmons, B. Simpson, T. mol. 35: 19Ð32. Ulhorn, and M. Yeary) for allowing Þeld access. Two anon- Knutson, A. E., M. A. Muegge, L. T. Wilson, and S. E. Naranjo. ymous reviews were very helpful in improving this paper. 2008. Evaluation of sampling methods and development This work was partially supported by a Texas State Support of sample plans for estimating predator densities in cot- Committee award (11-845TX) to M.J.B. and J.S.A. ton. J. Econ. Entomol. 101: 1501Ð1509. June 2012 BREWER ET AL.: SAMPLING STRATEGIES FOR PLANT BUGS ON COTTON 905

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