Fixed-precision Sequential Sampling Plans Research Articles

Studies on the within-plant distribution of whitefly, Bemisia tabaci (Gennadius) in potato and development of a sequential sampling plan

Whitefly, Bemisia tabaci (Gennadius), is a major constraint for seed potato production in India. For its efficient management, the within-plant distribution of B. tabaci was explored, and a sequential sampling plan was developed for potato crops. The highest proportion of B. tabaci adults, nymphs, and eggs was found on leaf numbers 3–7, 6–9, and 2–6, respectively (with leaf numbers beginning at the apical meristem). The count of adults from three leaves (nodes 4, 5, and 6) from the top stratum in a plant is proposed as a sample unit. Green's and Kuno's methods were used to develop fixed precision sequential sampling plans which yielded a similar average required sample size, except at lower densities (≤1 whitefly per plant). This information will enable efficient monitoring of B. tabaci.

Seasonal Population Dynamics, Sampling Distribution, and Fixed-Precision Sequential Sampling of Spectrobates ceratoniae (Lepidoptera: Pyralidae) in Pomegranate Orchards

The carob moth, Spectrobates ceratoniae Zeller, is the most destructive pest of pomegranate groves of Iran. Seasonal population dynamics of the pest was studied in pomegranate orchards of Sirvan, Ilam province, in southwestern Iran for 2 yr (2016/2017). Sampling distribution of the pest larvae on pomegranate fruits was evaluated by Taylor's power law and Iwao's patchiness index, and a fixed-precision sequential sampling plan of the pest was developed using Green's model. The adult population peaked in June. The activity period of the larvae was observed from June to October and peaked in October. Sampling distribution of the larvae on pomegranate fruits was random. Estimated optimum sample sizes ranged from 1 to 44 and 1 to 16 fruits at precision levels of 0.25 and 0.1, respectively.

Effect of weedy culture on population densities, spatial distributions and sampling procedures of Spodoptera exigua and Sesamia cretica (Lep., Noctuidae) in corn fields.

Spodoptera exigua Hübner and Sesamia cretica Led. (Lep., Noctuidae) are two important pests of corn. In this study, the effect of weed bands in the corn field, as weedy culture, on population density and damages of the pests were evaluated during two growing seasons (2016/2017). Cumulative insect days (CID) of each lepidopteran pest in weedy culture were compared with non-weedy culture. Results showed that CIDs of S. exigua and S. cretica in the non-weedy corn culture were significantly higher than the weedy corn culture. There was no significant difference between the total yield in the weedy and non-weedy cultures. Also, determinations of spatial distributions of the pests in the weedy and no-weedy treatments using Taylor's power law (TPL) and Iwao's patchiness (IP) showed that TPL provides a better fit for the data than IP and spatial distributions of both pests on both cultures were aggregative. Moreover, minor differences were observed between spatial distribution parameters of the pests in the weedy and non-weedy cultures. Green's model was used for developing a fixed-precision sequential sampling plan of the pests on the weedy and no-weedy treatments. Optimum sample sizes of S. exigua ranged from 532 to 5370 and 428 to 5296 plants and S. cretica varied from 297 to 2040 and 43 to 186 plants in the non-weedy and weedy cultures based on the desired precision level (0.25-0.1). Estimated stop lines of non-weedy and weedy cultures for S. exigua ranged from 0.000057 to 52.59 and 0.00029 to 58.87 and for S. cretica ranged from 1.59 to 111.5 and 2.09 to 98.03 larval cumulative numbers, respectively (0.25-0.1). The performance of the sampling plan was validated by resampling analysis using RVSP software. Results of the study can be used in the integrated pest management program of corn fields.

Field sampling strategies for coffee berry borer (Coleoptera: Curculionidae: Scolytinae) infesting berries in coffee farms in Hawaii

AbstractThe coffee berry borer (CBB),Hypothenemus hampeiFerrari, a recent invader to Hawaii, is impacting coffee growers by reducing yields and quality and increasing production costs. Monitoring strategies are needed to assess infestations and where control operations are warranted, and evaluate their effectiveness. To develop and validate a fixed-precision sequential sampling plan, an intensive CBB sampling programme was conducted in 17 small farms in Kona and Kau districts in the Big Island in 2016/17. At each location, 30 trees/ha were monitored at 2–4 week intervals. Results show that the CBB has an aggregated spatial distribution based on Taylor's power law parameters. According to Green's stop line formula, between 6 and 50 coffee branches per ha (sample unit) are required to estimate infestation rates of 1.5–2.5% infested green berries (suggested economic threshold) with a precision fixed at 10 to 25%. Concurrently, a modified strategy was tested on 14 farms, in which only infested green berries (not total) was counted. The standard and modified sampling methods were highly correlated (R2≥ 0.98), while the modified approach required on average only 35 min (27% less time) to complete, with an additional 24 min taken to observe the position of the CBB inside the berry. Our data also show that berry infestation rates of CBB prior to harvest were a good predictor of the total defects resulting in processed green coffee from these farms (Pearson'srcoefficient of 0.82). Our findings support improved sampling for the CBB under Hawaiian conditions using a simpler and faster monitoring strategy based on counting green infested berries.

Dispersion and Optimization of Sequential Sampling Plans for Coffee Berry Borer (Coleoptera: Curculionidae) Infestations in Hawaii.

Coffee berry borer, Hypothenemus hampei (Ferrari, Coleoptera: Curculionidae) is a serious pest of coffee in most coffee-growing areas of the world. This beetle was first detected in Big Island of Hawaii in 2010 and has since spread to other islands. Being an invasive pest that causes serious economic damage, efforts are in progress in Hawaii to develop an integrated approach to manage this pest. In this study, we sampled commercial coffee orchards from representative coffee-growing regions in the Big Island, Hawaii, to understand dispersion of the pest in the field and develop a reliable sampling plan based on the dispersion characteristics. Analysis of data collected from 12 commercial fields over three growing seasons suggests an aggregated pattern of dispersion of the pest in the field. Two fixed-precision sequential sampling plans based on berry cluster and branch as sample units were modeled and validated using Resampling for Validation of Sampling Plans software. The models suggest that infestation density can be estimated reliably for integrated pest management (IPM) practices with minimal sampling effort by sampling berry clusters or branches using sequential sampling plans. Sequential sampling plan based on berry cluster requires detection of fewer infested berries compared to branch sampling for a reliable estimation of mean density of infested berries and IPM decision making.

A Fixed-Precision Sequential Sampling Plan for the Potato Tuberworm Moth, Phthorimaea operculella Zeller (Lepidoptera: Gelechidae), on Potato Cultivars.

Phthorimaea operculella Zeller is an important pest of potato in Iran. Spatial distribution and fixed-precision sequential sampling for population estimation of the pest on two potato cultivars, Arinda® and Sante®, were studied in two separate potato fields during two growing seasons (2013-2014 and 2014-2015). Spatial distribution was investigated by Taylor's power law and Iwao's patchiness. Results showed that the spatial distribution of eggs and larvae was random. In contrast to Iwao's patchiness, Taylor's power law provided a highly significant relationship between variance and mean density. Therefore, fixed-precision sequential sampling plan was developed by Green's model at two precision levels of 0.25 and 0.1. The optimum sample size on Arinda® and Sante® cultivars at precision level of 0.25 ranged from 151 to 813 and 149 to 802 leaves, respectively. At 0.1 precision level, the sample sizes varied from 5083 to 1054 and 5100 to 1050 leaves for Arinda® and Sante® cultivars, respectively. Therefore, the optimum sample sizes for the cultivars, with different resistance levels, were not significantly different. According to the calculated stop lines, the sampling must be continued until cumulative number of eggs+larvae reached to 15-16 or 96-101 individuals at precision levels of 0.25 or 0.1, respectively. The performance of the sampling plan was validated by resampling analysis using resampling for validation of sampling plans software. The sampling plant provided in this study can be used to obtain a rapid estimate of the pest density with minimal effort.

Spatial distribution pattern and sequential sampling plans for Bactrocera oleae (Gmelin) (Dip: Tephritidae) in olive orchards

The distribution of adult and larvae <em>Bactrocera oleae</em> (Diptera: Tephritidae), a key pest of olive, was studied in olive orchards. The first objective was to analyze the dispersion of this insect on olive and the second was to develop sampling plans based on fixed levels of precision for estimating <em>B. oleae</em> populations. The Taylor’s power law and Iwao’s patchiness regression models were used to analyze the data. Our results document that Iwao’s patchiness provided a better description between variance and mean density. Taylor’s <em>b</em> and Iwao’s <em>β</em> were both significantly more than 1, indicating that adults and larvae had aggregated spatial distribution. This result was further supported by the calculated common <em>k</em> of 2.17 and 4.76 for adult and larvae, respectively. Iwao’s a for larvae was significantly less than 0, indicating that the basic distribution component of <em>B. oleae</em> is the individual insect. Optimal sample sizes for fixed precision levels of 0.10 and 0.25 were estimated with Iwao’s patchiness coefficients. The optimum sample size for adult and larvae fluctuated throughout the seasons and depended upon the fly density and desired level of precision. For adult, this generally ranged from 2 to 11 and 7 to 15 traps to achieve precision levels of 0.25 and 0.10, respectively. With respect to optimum sample size, the developed fixed-precision sequential sampling plans was suitable for estimating flies density at a precision level of D=0.25. Sampling plans, presented here, should be a tool for research on pest management decisions of <em>B. oleae</em>.

Optimizing a fixed-precision sequential sampling plan for adult Acrotomopus atropunctellus (Boheman) (Coleoptera: Curculionidae), new pest on sugarcane

Sugarcane weevil borer, Acrotomopus atropunctellus (Boheman) (Coleoptera: Curculionidae) has been detected across all sugarcane planting areas in the Argentinian Northwest with increasing population densities. The monitoring for its occurrence and the population density usually is made by visual inspection and consequently demands much effort and time. The objectives of this study were 1) to describe the sampling distribution pattern of A. atropunctellus adults 2) to develop and validate a fixed-precision sequential sampling plan for density estimation, and 3) to find the optimum inspection time for each sampling unit. On-farm data collection was performed at sugarcane fields located in Ranchillos (Tucumán, Argentina) during 2011–2012 to 2013–2014 sugarcane growing seasons. Thirty sampling units consisting on one meter of sugarcane furrow were randomly selected at 1-wk intervals. Within each sampling unit, weevils were counted and recorded independently for five increasing examination time per sampling unit (ETSU) (2, 4, 6, 8 and 10 min). For each ETSU, the sampling distribution pattern was assessed by Taylor's power law (TPL). The average sample number (ASN) and sampling stop lines were calculated according to Green's sequential sampling model, based on TPL estimated parameters, for fixed precision levels, C = 0.1 and C = 0.25. The resampling for validation of sample plans (RVSP) program was used to evaluate the performance of the different sampling plans. Parameters a and b from TPL regressions did not vary significantly between different ETSUs. All estimates of b coefficients were significantly >1 which can indicate an aggregated sampling distribution pattern. For each precision level, Green's sequential plans predicted very similar ASN between ETSU. This was confirmed through the validation process, with the five sampling protocols providing very similar mean sample sizes and mean precision levels. Variability of these parameters from validation results did not vary significantly among the different ETSUs. The relative net precision was the only performance parameter that varied with the ETSU, with the shortest ETSU resulting in the most efficient sampling plan. We conclude that A. atropunctellus has an aggregated sampling distribution and that the fixed precision sequential sampling plan developed using Green's model and based on a two-minute inspection of the sampling unit is the most convenient choice for estimating its population density in sugarcane. Our analysis of the ETSU effect on the performance of sugarcane weevil sampling protocols could contribute to develop more efficient monitoring plans for other arthropods.

Spatial distribution and sequential sampling plans for adult Sitona humeralis Stephens (Coleoptera: Curculionidae) in alfalfa

The spatio-temporal distribution of adult Sitona humeralis Stephens (Coleoptera: Curculionidae), a key pest of alfalfa, was studied using sweep netting for two years in alfalfa fields. The first objective was to analyze the distribution of this insect within alfalfa and the second objective was to develop sampling plans based on fixed levels of precision for estimating S. humeralis adult populations. The following models were used to analyze the data: Taylor's power law and Iwao's patchiness regression. Our results document that in both years, Iwao's patchiness provided a better description between variance and mean density. Taylor's b and Iwao's β were both significantly >1, indicating that adults had aggregated spatial distribution. Iwao's α was significantly <0, indicating that the basic distribution component of S. humeralis is the individual insect. Optimal sample sizes for fixed precision levels of 0.10 and 0.25 were estimated. The optimum sample size fluctuated throughout the seasons and depended upon the weevil density and desired level of precision. This generally ranged from 3 to 7×15 sweeps and 16 to 46×15 sweeps to achieve precision levels of 0.25 and 0.10, respectively. With respect to the optimum sample size, the developed fixed-precision sequential sampling plans were suitable for estimating weevil density at a precision level of D=0.25. The sampling plan presented here provides a tool for research on pest management decisions of S. humeralis.

Fixed-precision sequential sampling plans for estimating alfalfa caterpillar, Colias lesbia, egg density in alfalfa, Medicago sativa, fields in Córdoba, Argentina.

The alfalfa caterpillar, Colias lesbia (Fabricius) (Lepidoptera: Pieridae), is a major pest of alfalfa, Medicago sativa L. (Fabales: Fabaceae), crops in Argentina. Its management is based mainly on chemical control of larvae whenever the larvae exceed the action threshold. To develop and validate fixed-precision sequential sampling plans, an intensive sampling programme for C. lesbia eggs was carried out in two alfalfa plots located in the Province of Córdoba, Argentina, from 1999 to 2002. Using Resampling for Validation of Sampling Plans software, 12 additional independent data sets were used to validate the sequential sampling plan with precision levels of 0.10 and 0.25 (SE/mean), respectively. For a range of mean densities of 0.10 to 8.35 eggs/sample, an average sample size of only 27 and 26 sample units was required to achieve a desired precision level of 0.25 for the sampling plans of Green and Kuno, respectively. As the precision level was increased to 0.10, average sample size increased to 161 and 157 sample units for the sampling plans of Green and Kuno, respectively. We recommend using Green's sequential sampling plan because it is less sensitive to changes in egg density. These sampling plans are a valuable tool for researchers to study population dynamics and to evaluate integrated pest management strategies.

Insect population distribution and density estimates in a large rice mill in Portugal – A pilot study

The objectives of this study were to characterize the spatial distribution of the most abundant insect species identified in the rice plant, optimize the sampling program, develop and validate a fixed-precision enumerative sequential sampling plan for the key pests Sitophilus spp. in the rice industry in Portugal. Experiments were carried out from September 2005 to July 2007, using 25 pitfall traps baited with food grade oil and pheromone specific for Sitophilus spp. The traps were observed weekly and the insects were identified and counted. Several species were found but Sitophilus zeamais and Sitophilus oryzae were the most abundant (90% of the total) followed by Tribolium castaneum. Taylor's power law parameters, from the regression of log variance versus log mean, suggest an aggregated distribution for Sitophilus spp. and T. castaneum. A fixed-precision sequential sampling plan was developed for Sitophilus spp., using Green's fixed precisions sampling plan and the Resampling Validation of Sampling Plan, with an action threshold of 0.5 Sitophilus spp. The sampling plan was designed to provide precision levels of 0.20, 0.25 (for pest management purposes), 0.30 and 0.35. The current sample size raised a precision of 0.30, and an increase of the number of traps to 37 would be needed to achieve the desirable precision of 0.25. This fixed-precision sequential sampling plan for Sitophilus spp. populations in rice is demonstrated to be a useful tool in IPM tactics at rice facilities.

Sequential sampling plans for estimating density of glassy-winged sharpshooter, Homalodisca vitripennis (Hemiptera: Cicadellidae) on citrus

The glassy-winged sharpshooter, Homalodisca vitripennis (Germar), is a serious pest of grapes and other crop and ornamental plants mainly through its role as a vector of the bacterium Xylella fastidiosa Wells. Citrus harbors large populations of this insect throughout much of the year in areas where the pest is problematic and improved understanding of the population dynamics and management of H. vitripennis on citrus may be key to its management in the broader agricultural landscape. In turn, the study of population dynamics and the development of management strategies require effective and efficient sampling methods. Within-tree sampling distribution studies revealed that adults and nymphs were more abundant and less variable in the upper strata of citrus trees (>1.5 m). They occurred in greater numbers on the southern quadrants of trees but relative variability did not differ due to cardinal direction. We developed and validated several fixed-precision sequential sampling plans for estimating the density of nymphs and adults of H. vitripennis using a pole bucket sampling method. Based on validation from resampling of independent data sets, Green’s sequential sampling model, based on the Taylor’s power law, provided the best overall performance in terms of providing mean density estimates with levels of precision equal to or better than the desired precision over a range of possible insect densities. Average sampling costs varied from about 21 to 189 min for a desired precision of 0.25 depending on insect density and whether the goal is to sample nymphs, adults or both stages combined. Further, the sampling plans developed on orange trees were robust, being equally effective on orange and lemon trees and on trees treated or not with insecticides.

Sequential Sampling Plan for Cameraria ohridella (Lepidoptera: Gracillariidae) on Horse Chestnut Tree

A fixed precision sequential sampling plan for estimating the density of the horse chestnut, Aesculus hippocastanum L., leafminer Cameraria ohridella Deschka & Dimic (Lepidoptera: Gracillariidae) was developed. Data were collected from 2002 to 2004 in Turin, northwestern Italy, with the aim of developing a sampling strategy for estimating populations of C. ohridella mines. Taylor’s power law was used as a regression model. Sampling parameters were estimated from 216 data sets, and an additional 110 independent data sets were used to validate the fixed precision sequential sampling plan with resampling software. Covariance analysis indicated that there were not significant differences in the coefficient of Taylor’s power law between heights of the foliage, months, and years. Dispersion patterns of C. ohridella were determined to be aggregated. The parameters of the Taylor’s power law were used to calculate minimum sample sizes and sampling stop lines for different precision levels. Considering a mean density value of five mines per leaf, an average sample number of only 49 leaves was necessary to achieve a desired precision level of 0.25. As the precision level was increased to 0.10, the average sample size increased to 303 leaves. The sequential sampling plan should provide an effective management of C. ohridella in the urban areas, minimizing sampling time and cost, and at the same should be an effective tool to reduce insecticide applications and prevent the esthetic damage.

Sequential Sampling Plan for &lt;I&gt;Cameraria ohridella&lt;/I&gt; (Lepidoptera: Gracillariidae) on Horse Chestnut Tree

A fixed precision sequential sampling plan for estimating the density of the horse chestnut, Aesculus hippocastanum L., leafminer Cameraria ohridella Deschka & Dimic (Lepidoptera: Gracillariidae) was developed. Data were collected from 2002 to 2004 in Turin, northwestern Italy, with the aim of developing a sampling strategy for estimating populations of C. ohridella mines. Taylor's power law was used as a regression model. Sampling parameters were estimated from 216 data sets, and an additional 110 independent data sets were used to validate the fixed precision sequential sampling plan with resampling software. Covariance analysis indicated that there were not significant differences in the coefficient of Taylor's power law between heights of the foliage, months, and years. Dispersion patterns of C. ohridella were determined to be aggregated. The parameters of the Taylor's power law were used to calculate minimum sample sizes and sampling stop lines for different precision levels. Considering a mean density value of five mines per leaf, an average sample number of only 49 leaves was necessary to achieve a desired precision level of 0.25. As the precision level was increased to 0.10, the average sample size increased to 303 leaves. The sequential sampling plan should provide an effective management of C. ohridella in the urban areas, minimizing sampling time and cost, and at the same should be an effective tool to reduce insecticide applications and prevent the esthetic damage.

Probability distribution, sampling unit, data transformations and sequential sampling of European vine moth, Lobesia botrana (Lepidoptera: Tortricidae) larval counts from Northern Greece vineyards

Studies were conducted to investigate the distribution of larvae of the European vine moth, Lobesia botrana (Denis &amp; SchiffermĂźller) (Lepidoptera: Tortricidae), a key vineyard pest of grape cultivars. The data collected were larval densities of the second and third generation of L. botrana on half-vine and entire plants of wine and table cultivars in 2003-2004. No insecticide treatments were applied to plants during the 2-year study. The distribution of L. botrana larvae can be described by a negative binomial. This reveals that the insect aggregates. A common value for the k parameter of the negative binomial distribution of kc = 0.6042, was obtained, using maximum likelihood estimation, and the advantages and cases of use of a common k are discussed. The k-1Sinh-1(ksqrt{x+1/2}) and k-1Sinh-1(ksqrt{x+3/8}) proved to be the best transformations for L. botrana larval counts. An entire vine is recommended as the sampling unit for research purposes, whereas a half-vine, which is suitable for grape vine cultivation in northern Greece, is recommended for practical purposes. We used these findings to develop a fixed precision sequential sampling plan and a sequential sampling program for classifying the pest status of L. botrana larvae.

Spatial distribution and fixed-precision sampling plans for the ladybird Harmonia axyridis in sweet corn

To improve the utilization of the multicolored Asian lady beetle, Harmonia axyridis (Pallas), as a natural enemy in integrated pest management (IPM) programs for sweet corn, Zea mays L., fixed-precision enumerative sequential sampling plans for this coccinellid were developed and validated. Data were collected from sweet corn plots during 2000 to 2004, with means ranging from 0.02 to 11.83 H. axyridis (larvae and adults combined) per plant. Taylor’s power law parameters from the regression of log variance versus log mean suggested an aggregated distribution for larvae and the combined count of larvae and adults in sweet corn. For IPM purposes, a plan was developed for H. axyridis larvae and adults to provide a desired precision level of 0.25 (SEM/mean), resulting in an average sample number of 65 whole plants. However, for the purposes of ecological or applied research (with desired precision = 0.10), an average sample number of 205 plants was necessary.

Spatial Pattern and Sequential Sampling of Squash Bug (Heteroptera: Coreidae) Adults in Watermelon

Spatial distribution patterns of adult squash bugs were determined in watermelon, Citrullus lanatus (Thunberg) Matsumura and Nakai, during 2001 and 2002. Results of analysis using Taylor’s power law regression model indicated that squash bugs were aggregated in watermelon. Taylor’s power law provided a good fit with r2 = 0.94. A fixed precision sequential sampling plan was developed for estimating adult squash bug density at fixed precision levels in watermelon. The plan was tested using a resampling simulation method on nine and 13 independent data sets ranging in density from 0.15 to 2.52 adult squash bugs per plant. Average estimated means obtained in 100 repeated simulation runs were within the 95% CI of the true means for all the data. Average estimated levels of precision were similar to the desired level of precision, particularly when the sampling plan was tested on data having an average mean density of 1.19 adult squash bugs per plant. Also, a sequential sampling for classifying adult squash bug density as below or above economic threshold was developed to assist in the decision-making process. The classification sampling plan is advantageous in that it requires smaller sample sizes to estimate the population status when the population density differs greatly from the action threshold. However, the plan may require excessively large sample sizes when the density is close to the threshold. Therefore, an integrated sequential sampling plan was developed using a combination of a fixed precision and classification sequential sampling plans. The integration of sampling plans can help reduce sampling requirements.

Spatial Pattern and Sequential Sampling of Squash Bug (Heteroptera: Coreidae) Adults in Watermelon

Spatial distribution patterns of adult squash bugs were determined in watermelon, Citrullus lanatus (Thunberg) Matsumura and Nakai, during 2001 and 2002. Results of analysis using Taylor's power law regression model indicated that squash bugs were aggregated in watermelon. Taylor's power law provided a good fit with r2 = 0.94. A fixed precision sequential sampling plan was developed for estimating adult squash bug density at fixed precision levels in watermelon. The plan was tested using a resampling simulation method on nine and 13 independent data sets ranging in density from 0.15 to 2.52 adult squash bugs per plant. Average estimated means obtained in 100 repeated simulation runs were within the 95% CI of the true means for all the data. Average estimated levels of precision were similar to the desired level of precision, particularly when the sampling plan was tested on data having an average mean density of 1.19 adult squash bugs per plant. Also, a sequential sampling for classifying adult squash bug density as below or above economic threshold was developed to assist in the decision-making process. The classification sampling plan is advantageous in that it requires smaller sample sizes to estimate the population status when the population density differs greatly from the action threshold. However, the plan may require excessively large sample sizes when the density is close to the threshold. Therefore, an integrated sequential sampling plan was developed using a combination of a fixed precision and classification sequential sampling plans. The integration of sampling plans can help reduce sampling requirements.

Sampling Methods, Dispersion Patterns, and Fixed Precision Sequential Sampling Plans for Western Flower Thrips (Thysanoptera: Thripidae) and Cotton Fleahoppers (Hemiptera: Miridae) in Cotton

A 2-yr field study was conducted to examine the effectiveness of two sampling methods (visual and plant washing techniques) for western flower thrips, Frankliniella occidentalis (Pergande), and five sampling methods (visual, beat bucket, drop cloth, sweep net, and vacuum) for cotton fleahopper, Pseudatomoscelis seriatus (Reuter), in Texas cotton, Gossypium hirsutum (L.), and to develop sequential sampling plans for each pest. The plant washing technique gave similar results to the visual method in detecting adult thrips, but the washing technique detected significantly higher number of thrips larvae compared with the visual sampling. Visual sampling detected the highest number of fleahoppers followed by beat bucket, drop cloth, vacuum, and sweep net sampling, with no significant difference in catch efficiency between vacuum and sweep net methods. However, based on fixed precision cost reliability, the sweep net sampling was the most cost-effective method followed by vacuum, beat bucket, drop cloth, and visual sampling. Taylor’s Power Law analysis revealed that the field dispersion patterns of both thrips and fleahoppers were aggregated throughout the crop growing season. For thrips management decision based on visual sampling (0.25 precision), 15 plants were estimated to be the minimum sample size when the estimated population density was one thrips per plant, whereas the minimum sample size was nine plants when thrips density approached 10 thrips per plant. The minimum visual sample size for cotton fleahoppers was 16 plants when the density was one fleahopper per plant, but the sample size decreased rapidly with an increase in fleahopper density, requiring only four plants to be sampled when the density was 10 fleahoppers per plant. Sequential sampling plans were developed and validated with independent data for both thrips and cotton fleahoppers.

Sampling Methods, Dispersion Patterns, and Fixed Precision Sequential Sampling Plans for Western Flower Thrips (Thysanoptera: Thripidae) and Cotton Fleahoppers (Hemiptera: Miridae) in Cotton

A 2-yr field study was conducted to examine the effectiveness of two sampling methods (visual and plant washing techniques) for western flower thrips, Frankliniella occidentalis (Pergande), and five sampling methods (visual, beat bucket, drop cloth, sweep net, and vacuum) for cotton fleahopper, Pseudatomoscelis seriatus (Reuter), in Texas cotton, Gossypium hirsutum (L.), and to develop sequential sampling plans for each pest. The plant washing technique gave similar results to the visual method in detecting adult thrips, but the washing technique detected significantly higher number of thrips larvae compared with the visual sampling. Visual sampling detected the highest number of fleahoppers followed by beat bucket, drop cloth, vacuum, and sweep net sampling, with no significant difference in catch efficiency between vacuum and sweep net methods. However, based on fixed precision cost reliability, the sweep net sampling was the most cost-effective method followed by vacuum, beat bucket, drop cloth, and visual sampling. Taylor's Power Law analysis revealed that the field dispersion patterns of both thrips and fleahoppers were aggregated throughout the crop growing season. For thrips management decision based on visual sampling (0.25 precision), 15 plants were estimated to be the minimum sample size when the estimated population density was one thrips per plant, whereas the minimum sample size was nine plants when thrips density approached 10 thrips per plant. The minimum visual sample size for cotton fleahoppers was 16 plants when the density was one fleahopper per plant, but the sample size decreased rapidly with an increase in fleahopper density, requiring only four plants to be sampled when the density was 10 fleahoppers per plant. Sequential sampling plans were developed and validated with independent data for both thrips and cotton fleahoppers.