Enumerative Sampling Plans Research Articles

Sequential sampling plans for Orgyia trigotephras infesting Quercus coccifera forests in North Africa

AbstractThe tussock moth, Orgyia trigotephras Boisduval (Lepidoptera: Erebidae), is one of the main emerging pests of kermes oak, Quercus coccifera L. (Fagaceae), in the Mediterranean area, where it can cause the defoliation of several hectares of forests during its population outbreaks. Despite this, no specific sampling procedures to properly estimate the population density of this pest have been developed yet. The aims of this research were to develop and compare enumerative and binomial sequential sampling plans to estimate the population density of O. trigotephras in forest environments. Data were collected in four forest stands dominated by Q. coccifera in Tunisia for 7 years (from 2013 to 2019) to take into consideration the potential spatio‐temporal variability in pest density. Plant community composition was determined at the beginning of the experimental trials, and enumerative and binomial sampling plans were developed at precision levels of 0.15 and 0.25. Over the entire sampling period, the average O. trigotephras egg batch density differed significantly among sites. Sample sizes of enumerative sampling plans were approximately 39 and 109 trees to estimate an average density of 0.50 O. trigotephras egg batches per tree at the precision levels of 0.25 and 0.15, respectively. Instead, binomial sequential sampling plans required smaller sampling sizes than the enumerative sampling plan. Our findings represent the baseline to develop a program for monitoring O. trigotephras at a large spatial scale.

Development of Enumerative and Binomial Sequential Sampling Plans for Monitoring Lymantria dispar (L.) (Lepidoptera Erebidae) in Mediterranean Oak Forests

Lymantria dispar is the main threat to Mediterranean forests. Sampling methods used for monitoring the pest population density are generally very time-consuming for practical purposes, such as the delimitation of infested areas for control programs. Enumerative and binomial sequential sampling plans were developed using data collected in cork oak forests in Sardinia (Italy). The Taylor’s power law (TPL) was used to evaluate the degree of aggregation of L. dispar egg masses among trees and to develop enumerative sampling plans at precision levels of 0.10 and 0.25 using the Green’s method. Furthermore, binomial plans were computed by Wald’s sequential probability ratio test. Lymantria dispar egg masses on trees were significantly aggregated and the degree of aggregation was similar in all population development phases. Overall, only 31 cork oak trees are to be monitored at the economic damage threshold of 2.5 egg masses/tree with a precision level of 0.25. Binomial sequential sampling plans also required lower sampling sizes (26.9–31.4 trees) than conventional sampling plans. Enumerative and binomial sampling plans could represent suitable methods for sampling L. dispar egg masses in Mediterranean forests, with the practical advantage of lower cost and time consumption than standard sampling plans.

Sequential and Binomial Sampling Plans to Estimate Thrips tabaci Population Density on Onion.

Simple SummaryThrips are tiny insects that cause significant damage to onion crops worldwide. They feed on the plants and can also transmit plant viral diseases. To prevent damage, it is necessary to estimate the population density (average number of insects per plant), through periodic sampling, and to apply a combination of control tactics to maintain thrips at acceptable levels. Conventional sampling methods are precise but require large investments of time and effort. In this study, binomial and sequential sampling plans were developed to estimate thrips population density in a precise and less time-consuming manner. More than 50 onion plots were sampled, and Thrips tabaci Lindeman was identified as the predominant pest species. The sampling plans reached acceptable levels of precision (D = 0.25) in less time than conventional sampling. Binomial and sequential sampling plans were reliable and easily implemented in practice, but sequential sampling showed better performance than binomial sampling under different field conditions. These findings may help to reduce time and work for T. tabaci sampling and, consequently, improve implementation of crop protection tactics on onion.Thrips tabaci Lindeman is a worldwide onion pest that causes economic losses of 10–60%, depending on many factors. Population sampling is essential for applying control tactics and preventing damage by the insect. Conventional sampling methods are criticized as time consuming, while fixed-precision binomial and sequential sampling plans may allow reliable estimations with a more efficient use of time. The aim of this work was to develop binomial and sequential sampling for fast reliable estimation of T. tabaci density on an onion. Forty-one commercial 1.0-ha onion plots were sampled (sample size n = 200) to characterize the spatial distribution of T. tabaci using Taylor’s power law (a = 2.586 and b = 1.511). Binomial and sequential enumerative sampling plans were then developed with precision levels of 0.10, 0.15 and 0.25. Sampling plans were validated with bootstrap simulations (1000 samples) using 10 independent data sets. Bootstrap simulation indicated that precision was satisfactory for all repetitions of the sequential sampling plan, while binomial sampling met the fixed precision in 80% of cases. Both methods reduced sampling time by around 80% relative to conventional sampling. These precise and less time-consuming sampling methods can contribute to implementation of control tactics within the integrated pest management approach.

Spatial Distribution and Sampling Plans for Grapevine Plant Canopy-Inhabiting Scaphoideus titanus (Hemiptera: Cicadellidae) Nymphs.

The paper deals with the study of the spatial distribution and the design of sampling plans for estimating nymph densities of the grape leafhopper Scaphoideus titanus Ball in vine plant canopies. In a reference vineyard sampled for model parameterization, leaf samples were repeatedly taken according to a multistage, stratified, random sampling procedure, and data were subjected to an ANOVA. There were no significant differences in density neither among the strata within the vineyard nor between the two strata with basal and apical leaves. The significant differences between densities on trunk and productive shoots led to the adoption of two-stage (leaves and plants) and three-stage (leaves, shoots, and plants) sampling plans for trunk shoots- and productive shoots-inhabiting individuals, respectively. The mean crowding to mean relationship used to analyze the nymphs spatial distribution revealed aggregated distributions. In both the enumerative and the sequential enumerative sampling plans, the number of leaves of trunk shoots, and of leaves and shoots of productive shoots, was kept constant while the number of plants varied. In additional vineyards data were collected and used to test the applicability of the distribution model and the sampling plans. The tests confirmed the applicability 1) of the mean crowding to mean regression model on the plant and leaf stages for representing trunk shoot-inhabiting distributions, and on the plant, shoot, and leaf stages for productive shoot-inhabiting nymphs, 2) of the enumerative sampling plan, and 3) of the sequential enumerative sampling plan. In general, sequential enumerative sampling was more cost efficient than enumerative sampling.

Comparison and Field Validation of Binomial Sampling Plans for Oligonychus perseae (Acari: Tetranychidae) on Hass Avocado in Southern California.

Oligonychus perseae Tuttle, Baker, & Abatiello is a foliar pest of 'Hass' avocados [Persea americana Miller (Lauraceae)]. The recommended action threshold is 50-100 motile mites per leaf, but this count range and other ecological factors associated with O. perseae infestations limit the application of enumerative sampling plans in the field. Consequently, a comprehensive modeling approach was implemented to compare the practical application of various binomial sampling models for decision-making of O. perseae in California. An initial set of sequential binomial sampling models were developed using three mean-proportion modeling techniques (i.e., Taylor's power law, maximum likelihood, and an empirical model) in combination with two-leaf infestation tally thresholds of either one or two mites. Model performance was evaluated using a robust mite count database consisting of >20,000 Hass avocado leaves infested with varying densities of O. perseae and collected from multiple locations. Operating characteristic and average sample number results for sequential binomial models were used as the basis to develop and validate a standardized fixed-size binomial sampling model with guidelines on sample tree and leaf selection within blocks of avocado trees. This final validated model requires a leaf sampling cost of 30 leaves and takes into account the spatial dynamics of O. perseae to make reliable mite density classifications for a 50-mite action threshold. Recommendations for implementing this fixed-size binomial sampling plan to assess densities of O. perseae in commercial California avocado orchards are discussed.

Spatial distribution and sequential sampling plans for Tuta absoluta (Lepidoptera: Gelechiidae) in greenhouse tomato crops.

The within- and between-plant distribution of the tomato leafminer, Tuta absoluta (Meyrick), was investigated in order to define action thresholds based on leaf infestation and to propose enumerative and binomial sequential sampling plans for pest management applications in protected crops. The pest spatial distribution was aggregated between plants, and median leaves were the most suitable sample to evaluate the pest density. Action thresholds of 36 and 48%, 43 and 56% and 60 and 73% infested leaves, corresponding to economic thresholds of 1 and 3% damaged fruits, were defined for tomato cultivars with big, medium and small fruits respectively. Green's method was a more suitable enumerative sampling plan as it required a lower sampling effort. Binomial sampling plans needed lower average sample sizes than enumerative plans to make a treatment decision, with probabilities of error of <0.10. The enumerative sampling plan required 87 or 343 leaves to estimate the population density in extensive or intensive ecological studies respectively. Binomial plans would be more practical and efficient for control purposes, needing average sample sizes of 17, 20 and 14 leaves to take a pest management decision in order to avoid fruit damage higher than 1% in cultivars with big, medium and small fruits respectively.

Binomial and Enumerative Sampling of &lt;I&gt;Tetranychus urticae&lt;/I&gt; (Acari: Tetranychidae) on Peppermint in California

The two-spotted spider mite, Tetranychus urticae Koch, is an economic pest on peppermint [Mentha x piperita (L.), 'Black Mitcham'] grown in California. A sampling plan for T. urticae was developed under Pacific Northwest conditions in the early 1980s and has been used by California growers since approximately 1998. This sampling plan, however, is cumbersome and a poor predictor of T. urticae densities in California. Between June and August, the numbers of immature and adult T. urticae were counted on leaves at three commercial peppermint fields (sites) in 2010 and a single field in 2011. In each of seven locations per site, 45 leaves were sampled, that is, 9 leaves per five stems. Leaf samples were stratified by collecting three leaves from the top, middle, and bottom strata per stem. The on-plant distribution of T. urticae did not significantly differ among the stem strata through the growing season. Binomial and enumerative sampling plans were developed using generic Taylor's power law coefficient values. The best fit of our data for binomial sampling occurred using a tally threshold of T = 0. The optimum number of leaves required for T urticae at the critical density of five mites per leaf was 20 for the binomial and 23 for the enumerative sampling plans, respectively. Sampling models were validated using Resampling for Validation of Sampling Plan Software.

Elaboração de um plano de amostragem para Cigarrinha-Verde (Homoptera: Cicadellidae) em vinha no Vale do Lima

The aims of this work were: to study the spatial patterns of nymphal stages of the green-leafhopper Empoasca vitis using the regression models of Taylor's Power Law and Iwao, in vineyard cvs. Arinto and Vinhao in organic farming and integrated production systems; to develop a binomial sampling (presence-absence). The results showed that: i) Taylor's power law was more appropriate to describe the spatial pattern of E. vitis and indicated a random pattern; no statistically differences were detected between varieties and production systems, ii) the sample size required increases with the degree of accuracy, iii) it is possible to simplify the enumerative sampling plan; and iv) the sample size required to estimate population densities of this pest corresponding to the economic thresholds, ranges from 30 to 57 leaves.

The influence of management practice on the spatial distribution of Lepidopteran pests in Brassica crops in the Democratic People's Republic of Korea: implications for sequential sampling plans

AbstractPlutella xylostella and Pieris rapae are the key components of a pest complex that attacks Brassica crops in the Democratic People's Republic of Korea (DPRK). We examined the spatial distributions of these insects within crops both as individual species and when combined as a standard insect that was derived from their relative feeding rates. The influence of standard co‐operative management practice and an integrated pest management (IPM) strategy on the dispersion of the standard insect was tested. Iwao's m* − m relation was then used to describe the distribution of standard insects by management categories and of Pieris rapae using all data. Pest management practices only affected the distribution of the species when they were combined into standard insects. Enumerative sampling plans were therefore designed for standard insects based on population data derived from IPM‐managed fields and for Pieris rapae from population data from all experimental fields. The presented plans have the potential to make a significant contribution to managing lepidopteran pests in the DPRK. The approach will be useful in the design of sequential sampling plans for other geographical regions where these pests co‐occur and can also contribute to the development of sequential sampling plans for other pest complexes for which standard insects can be derived.

A Binomial and Species-Independent Approach to Trap Capture Analysis of Flying Insects

Traps for monitoring of flying insect pests constitute a critical part of integrated pest management strategies. However, interpretation of trap captures is hampered by 1) factors associated with the performance of traps (i.e., lure, trap design, placement); 2) an often poorly defined relationship between trap captures and population density; and 3) interpretation approaches being highly specific to a certain insect species, trapping method, or trapping environment. The main purpose of this study was to identify a trap capture interpretation approach with little sensitivity to characteristics specific to a given data set, which would allow easier comparison of trapping data sets and make it easier to standardize sampling plans across insect pests and trapping environments. Based on fits of trapping data sets to standard distributions (normal, Poisson, and negative binomial), evaluations of the index of aggregation, k, and linear regression coefficients from Taylor's power law, we concluded that these characteristics varied considerably among data sets, which means that enumerative sampling plans may not be appropriate. Across 13 trapping data sets of six insect species, we showed a consistent nonlinear relationship between average trap captures and number of traps with zero captures and that the k can be stabilized by converting trapping data into binomial data. A trap interpretation approach based on number of zero captures is both easy to use, was found to be species-independent, and means that it may be possible to establish meaningful and reliable action thresholds based on trap captures of flying insects. Although developed using trapping data from food facilities, this approach may have application to trapping data from other environments as well.

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.

Population models for threshold-based control of Tetranychus urticae in small-scale Kenyan tomato fields and for evaluating weather and host plant species effects

The spatial distribution of motile life stages of the two-spotted spider mite Tetranychus urticae Koch in Kenyan small-scale tomato fields was described by Taylor's power law and an enumerative sampling plan was designed for research purposes. The exponential increase of T. urticae populations during three growing seasons permits the development and use of a simple exponential model for the design of a threshold-based chemical control system. For this purpose, a critical threshold of 440 motile mites per sample unit at the end of the growing season (12 weeks after transplanting) was translated into a proportion of 0.83 infested units in sample 3, i.e. five weeks after transplanting. A sequential binomial sampling plan with respect to the proportion of 0.83, five weeks after transplanting, was designed. The exponential model was extended to account for the influence of weather and host plant species. Model development and parameter estimation were based on three data sets (Kenyan tomato fields, Italian and Californian strawberry fields). The model satisfactorily predicted a positive influence on growth rates by (i) changing the host plant from tomato to strawberry, and (ii) temperature, while a negative effect resulted from (iii) rainfall; both (ii) and (iii) are controlled by temperature-rainfall interactions. In contrast, the estimated parameter values did not satisfactorily describe the expected responses at specific temperature and rainfall values. Nevertheless, the model allowed the rating of host plant species in the field. A fourth data set from Swiss apple orchards was used to test the model, and population build-up on the apple host plant appeared to be higher than on tomatoes but lower than on strawberry.

Enumerative and Binomial Sampling Plans for Citrus Mealybug (Homoptera: Pseudococcidae) in Citrus Groves

The spatial distribution of the citrus mealybug, Planococcus citri (Risso) (Homoptera: Pseudococcidae), was studied in citrus groves in northeastern Spain. Constant precision sampling plans were designed for all developmental stages of citrus mealybug under the fruit calyx, for late stages on fruit, and for females on trunks and main branches; more than 66, 286, and 101 data sets, respectively, were collected from nine commercial fields during 1992-1998. Dispersion parameters were determined using Taylor's power law, giving aggregated spatial patterns for citrus mealybug populations in three locations of the tree sampled. A significant relationship between the number of insects per organ and the percentage of occupied organs was established using either Wilson and Room's binomial model or Kono and Sugino's empirical formula. Constant precision (E = 0.25) sampling plans (i.e., enumerative plans) for estimating mean densities were developed using Green's equation and the two binomial models. For making management decisions, enumerative counts may be less labor-intensive than binomial sampling. Therefore, we recommend enumerative sampling plans for the use in an integrated pest management program in citrus. Required sample sizes for the range of population densities near current management thresholds, in the three plant locations calyx, fruit, and trunk were 50, 110-330, and 30, respectively. Binomial sampling, especially the empirical model, required a higher sample size to achieve equivalent levels of precision.

Enumerative and Binomial Sequential Sampling Plans for Soybean Aphid (Homoptera: Aphididae) in Soybean

Enumerative and Binomial Sequential Sampling Plans for Soybean Aphid (Homoptera: Aphididae) in Soybean

Spatio-temporal Distribution and Enumerative Sampling of the Pink Borer, Sesamia cretica Led. (Lepidoptera: Noctuidae), in Maize Fields in Egypt

Surveys for population densities of the maize borer Sesamia cretica Led. (Lepidoptera: Noctuidae) were conducted for three consecutive years (1997–1999) in several localities of the Nile delta in Egypt, in order to get a better insight into the population dynamics of the pest and to propose rational basis for its biocontrol using a recently isolated granulovirus. High population densities (more than one borer per plant) were observed only in the first plantings after winter (first fortnight of April). After this peak, populations almost vanished until the end of the crop season (September–October) when a slight increase was observed (0.1 borer per plant). The drastic decrease in population densities in plantings from the end of April occurs because most final instars of the borer leave the plant to pupate in the soil. This behaviour, uncommon in maize borers, results in a very high mortality rate due mainly to pupal parasitism. Only the few larvae pupating in the stem, which are much less parasitised, give rise to adults. Spatial distribution was studied using Taylor’s power laws which enabled the elaboration of enumerative sampling plans for eggs, small larvae (1st and 2nd instars) and older ones. Fixed optimal sample size and sequential sampling plans for different precision levels were developed. The precision of the estimated sample size was checked using resampling of some of the data that were not used to build the models. The validation study showed that the plans were suitable for the entire Nile delta region.

Enumerative sampling plans for grasshopper egg pods in northern Benin

The spatial distributions of egg pods of two grasshopper species, Hieroglyphus daganensis Krauss and Cataloipus fuscocoeruleipes Sjöstedt, collected from three oviposition sites, Piliostigma thonningi (Schumach.) Milne‐Redhead, Vetiveria nigritana (L.) and Sorghum bicolor (L.) Moench, are described using Taylor's power law. Both grasshopper species showed a highly aggregated distribution with Taylor's index of dispersion ranging between 1.380 and 1.709, except for C. fuscocoeruleipes from S. bicolor where an index of dispersion of 0.885 indicated a regular distribution. Enumerative sampling plans incorporating Taylor's power law are presented to estimate mean grasshopper egg pod densities with predefined levels of reliability for future studies. For egg pod densities of &lt; 1.0 m−2, optimal sample sizes at a site consist of 50 P. thonningi shrubs, 125 V nigritana clumps and 150 S bicolor patches with a reliability level of D = 0.3. This would demand a team of seven people to work for approximately 15 h.

Sampling Whiteflies in Cotton: Validation and Analysis of Enumerative and Binomial Plans

We tested enumerative and binomial sampling plans developed for Bemisia tabaci (Gennadius) in 3,240 ha of commercial cotton as part of the implementation of a community-wide integrated pest management (IPM) program in Laveen and Tolleson, AZ, in 1994. We compared new field observations to sampling distribution models developed previously for all lifestages, and validated and analyzed die performance of 5 sampling plans based on these models by resampling field data from 129 to 284 sites. Mean–variance relationships for the new data differed statistically from mean-variance models previously developed for adults, but not for eggs or nymphs. Resampling analyses indicated that desired precision (SE to mean ratio) was rarely achieved, on average, by fixed-precision sequential sampling plans. These enumerative sampling plans provided better precision than desired at moderate to high densities of eggs and adults and worse precision than desired at most densities of nymphs. An empirical model relating mean density to the proportion of leaves infested with 3 or more adult B. tabaci was accurate at mean densities < 2 adults per leaf but over-predicted mean density at higher densities. Resampling analysis revealed that a sequential sampling plan based on this empirical model was accurate at classifying population density relative to an action threshold of 5 adults per leaf. At nominal α and β error rates of 0.10, population density was correctly classified ≍87% of the time. Accuracy was not improved by reducing nominal error rates to 0.05. Resampling analysis of a fixed-sample size plan based on n = 30 gave similar results and increasing sample size to 50 increased accuracy only 3%. Further resampling analyses that more closely approximated scouting protocols (15 sample units drawn from each of 2 quadrants in die field) resulted in an average accuracy of ≍70%. Accuracy declined when populations densities differed greatly among quadrants in a field. Most of this error was associated with making a decision to control when pest density was below the action threshold. Based on a robust validation technique using field observations representing a wide range of environmental and agronomic conditions, our sampling plans performed well and should be useful for estimating and classifying population densities of B. tabaci in cotton over a wide area.

Sampling Plans for Mononychellus progresivus and Oligonychus gossypii (Acari: Tetranychidae) on Cassava in Mrica

Sampling plans were developed for 2 phytophagous mites. Mowmychellus progresivns Doreste and Oligonychus gossypii (Zacher), on cassava in Africa. Analysis of intraplant distribution showed a preference of M. progresivus for the apical and middle parts of the plant. and of O. gossypii for the middle and lower plant parts. Thus, the 1st fully developed leaf in the middle part was chosen as the common sampling unit for both species. On this unit, both species displayed aggregated distributions. The proposed binomial and enumerative sampling plans permit reliable estimates of both M. progresivus and O. gossypii densities. Forty fully developed leaves provided satisfactory estimates of the densities of both mite species.

Distribution and sampling of Chilo partellus (Lepidoptera: Pyralidae) in maize and sorghum on the Kenya coast

AbstractThe seasonal occurrence and spatial distribution of the crambine stem borer, Chilo partellus (Swinhoe) were investigated in maize, Zea mays, and sorghum, Sorghum bicolor, fields at the Kenya coast. During the vegetative growth stage, small-sized larvae were typically found behind leaf sheaths and in whorls in maize and sorghum. In reproductive and senescent maize, small-sized larvae were also found feeding in ears. Later immature life stages were located predominantly in stems in sorghum, and in the stems and ears in maize. Density and variance estimates of small, medium-, and large-sized larvae and pupae in maize and sorghum were fitted to Taylor's power law which provided significant regressions in all cases. The between-plant distribution was aggregated in all life stages. In maize, the distribution remained aggregated through the larval and pupal life stages, but in sorghum the distribution became progressively less aggregated as insects aged. The relationship of C. partellus density to the proportion of plants infested also suggested aggregation. Optimal sample sizes were determined for both binomial and enumerative sampling plans at two levels of precision, and a discussion is included on the relationship of optimal sample sizes to economic injury levels. Additionally, a presence/absence sequential sampling plan is proposed.

Estimating Potato Tuberworm (Lepidoptera: Gelechiidae) Damage in Stored Potatoes in Tunisia

Sampling plans based on insect damage (i.e., holes in tubers) were examined. An enumerative sampling plan, considering the precision level, showed that a sample size of 300 tubers randomly taken from a potato heap provides an accurate estimation of the mean number of holes per tuber. On the farmer level, a sequential sampling plan based on an action threshold of 20% of damaged tubers is calculated, and possible farmer decisions are discussed. Taylor’s power law is used to describe the distribution of damage in the potato heaps as slightly aggregated. Nachman’s model is used to relate the proportion of damaged tubers (showing at least one hole) to the density of holes per tuber.