Enumerative and binomial sequential sampling plans for soybean aphid (Homoptera: Aphididae) in soybean

Since the discovery of the soybean aphid, Aphis glycines Matsumura, in midwestern U.S. soybean, Glycine max L., in 2000, the aphid has become a significant economic pest. Basic information about estimating population density within fields is unknown. Therefore, we developed two sampling plans to efficiently characterize A. glycines densities. Enumerative and binomial sequential plans were developed using 89 data sets collected from 10 commercial fields sampled during 2001-2003. Re-sampling software was used to validate the enumerative plan on whole plant counts, based on Taylor's power law parameters (a = 9.157 and b = 1.543). For research applications, the enumerative plan was modified to provide an actual precision level of 0.10 (SE/mean), which resulted in an average sample number of 310 individual plants. For integrated pest management (IPM) purposes, we developed an enumerative plan with an actual precision of 0.25, which resulted in an average sample number of 38 individual plants. For IPM applications, the binomial plan will likely be more practical. Binomial plans were developed using two tally thresholds at five action thresholds. Final analysis of the operating characteristic curve for each plan indicated that the tally threshold of > or = 40 aphids per plant, and an action threshold of 0.837 (84% of the plants infested) provided the most correct treat (4%) and no-treat (95%) decisions, with very low incorrect treat (0.5%) and no-treat (0.5%) decisions. A tally threshold of > or = 40 aphids per plant and action thresholds of 84% of plants infested is equivalent to a mean density of 250 aphids per plant, a recently recommended economic threshold. Using this threshold, the minimum required sample number for the binomial plan was 11 plants.     

Effects of reducing sample size on density estimates of citrus rust mite (Acari: Eriophyidae) on citrus fruit: simulated sampling

The consequence of reducing sample size on the accuracy and precision of estimates of citrus rust mite, Phyllocoptruta oleivora (Ashmead), densities on oranges was investigated. The sample unit was a 1-cm2 surface area on fruit. Sampling plans consisting of 360, 300, 200, 160, 80, 48, 36, or 20 samples per 4 ha were evaluated through computer simulations by using real count data from 32 data sets of 600 sample units per 4 ha. The original and reduced sampling plans were hierarchical with different numbers of sample areas per 4 ha, trees per area, fruit per tree, and samples per fruit. Individual estimates (n=100 simulations per data set) using each plan were sometimes considerably below or above target densities. In an original set of count data with a mean of six mites per cm2, simulations of 36 samples per 4 ha produced individual estimates ranging from one to 16 mites per cm2, whereas 80 samples per 4 ha produced estimates ranging from two to 10 mites per cm2. The plans consisting of 36 or more samples were projected to provide precision levels of 0.25 (SEM/mean) or better at densities of five or more mites per cm2 based on log-data, a projection that needs to be verified under real-grove situations. Each plan consistently provided mite detection in these sampling simulations except those consisting of 20 or 36 samples, which sometimes failed to detect mites when the target density was less than five mites per cm2. The study provided insight into the probable precision, accuracy and detection thresholds for eight candidate sampling plans varying from relatively low to high resource input.     

Cascading tripartite binomial classification plans to monitor European red mite (Acari,Tetranychidae) through a season; development and evaluation of a new methodology for pest monitoring

A monitoring protocol that schedules future sample bouts based on the outcome of density classification and expected population growth has been developed and applied to monitoring European red mite (Panonychus ulmi Koch) through a growing season. The monitoring protocol is based on concatenating through time tripartite sequential classification sampling plans that use binomial counts in lieu of complete enumeration. Binomial counts are scored positive when the number of organisms (mites) on a sample unit (leaves) exceeds a tally number. At each sample occasion the monitoring procedure leads to one of three possible decisions; intervene when the density is high, sample at the next sample occasion (after one week) when the density is intermediate, and sample at the second next sample occasion (after two weeks) when the density is low. Evaluation of the monitoring protocol under field conditions showed that the protocol with constituent tally 0 binomial count sampling plans was quite successful in timing intervention at the moment when population densities were about to exceed an established threshold that dictated intervention. The performance of this monitoring protocol and another protocol in which constituent sampling plans used binomial counts with a tally number of 4 were compared using simulation. Sampling plans that used a tally number of 4 were more precise than plans that used a tally number of 0. However, the overall performance of the monitoring protocol based on tally 0 sampling plans did not greatly differ from the monitoring protocol based on tally 4 sampling plans. Simulated performance of the tally 0 protocol was corroborated by field evaluation. The monitoring protocol based on tripartite classification required 30 to 45 percent fewer sample bouts than a protocol based on conventional sequential classification at weekly intervals. The monitoring protocol based on tripartite classification was also better able to schedule intervention when needed compared to a protocol based on conventional classification at two week intervals. Using the tally 0 protocol and current thresholds forP. ulmi, cumulative mite density was kept below 300 mite-days per leaf, which is well below levels regarded damaging. A tally 0 protocol with raised thresholds, developed on the basis of this finding, gave the best simulated performance of all protocols evaluated.     

Approaches for sampling the twospotted spider mite (Acari: Tetranychidae) on clementines in Spain

Tetranychus urticae Koch (Acari: Tetranychidae) is an important pest of clementine mandarins, Citrus reticulata Blanco, in Spain. As a first step toward the development of an integrated crop management program for clementines, dispersion patterns of T. urticae females were determined for different types of leaves and fruit. The study was carried out between 2001 and 2003 in different commercial clementine orchards in the provinces of Castelló and Tarragona (northeastern Spain). We found that symptomatic leaves (those exhibiting typical chlorotic spots) harbored 57.1% of the total mite counts. Furthermore, these leaves were representative of mite dynamics on other leaf types. Therefore, symptomatic leaves were selected as a sampling unit. Dispersion patterns generated by Taylor's power law demonstrated the occurrence of aggregated patterns of spatial distribution (b > 1.21) on both leaves and fruit. Based on these results, the incidence (proportion of infested samples) and mean density relationship were developed. We found that optimal binomial sample sizes for estimating low populations of T. urticae on leaves (up to 0.2 female per leaf) were very large. Therefore, enumerative sampling would be more reliable within this range of T. urticae densities. However, binomial sampling was the only valid method for estimating mite density on fruit.     

Spatial distribution and sampling plans for Thrips palmi (Thysanoptera: Thripidae) infesting fall potato in Korea

The spatial distribution of adult and immature Thrips palmi Karny on fall potato, Solanum tuberosum L., on Cheju Island, Korea, was studied over a 2-yr period by visually inspecting potato leaves. The majority of thrips collected from the leaves were observed in the top one-third of the plant. The within-field spatial patterns of adults and immature thrips were aggregated. The slopes and intercepts of Taylor's power law did not differ among adults and immature thrips. A fixed-precision-level sampling plan was developed using the parameters from Taylor's power law and was tested with resampling simulations using eight independent data sets. Over a wide range of densities, the simulation demonstrated that actual sampling precision (d = SEM/mean) values at d = 0.25 averaged < 0.24 in all cases. A binomial sampling plan for estimating mean density was developed using an empirical model evaluated at tally thresholds (the minimum number of insects present before a leaf is considered infested) of one, three, five, and eight thrips per leaf. Increasing sampling size had little effect on the precision of the estimated mean regardless of tally threshold (T). However, increasing T had a dramatic effect on precision. The best tally threshold for estimating thrips density based on the applicable density ranges and the precision of the model was T = 5. A binomial sampling plan with a tally threshold of five and a fixed sample size of 30 leaves should be an effective replacement for enumerative counts when thrips average < 10 per leaf.     

BINOMIAL COUNT ANALYSIS BASED ON THE SPATIAL DISTRIBUTION AND POPULATION DENSITY ESTIMATION OF COTTON APHIDS1)

Abstract  Based on field population sampling of Aphis gossypii on cotton seedlings in Quzhou Experiment Station of China Agricultural University in Hebei Province in 1991, we obtained a data set consisting of 24 estimates of mean aphid density ( m , number of aphids per plant), variance (s²) and the proportion of plants (P_T) with no more than T aphids (T=0, 1, 2,…, 8, 10, 15, 20, respectively and defined as tally threshold). Taylor's power law fitted the data well (r²= 0. 958). The resulting slope (1. 515) was significantly greater than 1, indicating that the spatial distribution of this aphid was in aggregated pattern. An empirical relationship between m and Pr was developed for each T value using the parameters from the linear regression In( m )= a +bln[- ln( P_T )}]. The importance of the T values in reduction of sampling errors and their application to binomial sampling plans are discussed. Small T values, particularly aphid-free plant (T = 0, conventional binomial sample), could lead to spurious estimates of m from P_T . A value of T from 10 to 15 was recommended to develop binomial sampling plans for the aphids on cotton seedlings because of the relatively small sampling errors.     

Operating characteristics of full count and binomial sampling plans for green peach aphid (Hemiptera: Aphididae) in potato

Counts of green peach aphid, Myzus persicae (Sulzer) (Hemiptera: Aphididae), in potato, Solanum tuberosum L., fields were used to evaluate the performance of the sampling plan from a pest management company. The counts were further used to develop a binomial sampling method, and both full count and binomial plans were evaluated using operating characteristic curves. Taylor's power law provided a good fit of the data (r2 = 0.95), with the relationship between the variance (s2) and mean (m) as ln(s2) = 1.81(+/- 0.02) + 1.55(+/- 0.01) ln(m). A binomial sampling method was developed using the empirical model ln(m) = c + dln(-ln(1 - P(T))), to which the data fit well for tally numbers (T) of 0, 1, 3, 5, 7, and 10. Although T = 3 was considered the most reasonable given its operating characteristics and presumed ease of classification above or below critical densities (i.e., action thresholds) of one and 10 M. persicae per leaf, the full count method is shown to be superior. The mean number of sample sites per field visit by the pest management company was 42 +/- 19, with more than one-half (54%) of the field visits involving sampling 31-50 sample sites, which was acceptable in the context of operating characteristic curves for a critical density of 10 M. persicae per leaf. Based on operating characteristics, actual sample sizes used by the pest management company can be reduced by at least 50%, on average, for a critical density of 10 M. persicae per leaf. For a critical density of one M. persicae per leaf used to avert the spread of potato leaf roll virus, sample sizes from 50 to 100 were considered more suitable.     

Differential levels of mite infestation of wheat and barley in Czech grain stores

Abstract  While mites are able to utilize numerous food sources, the suitability of the food strongly influences population growth. The different suitabilities of various stored agricultural products will thus affect the level of infestation. In this study, we compared field mite infestation rates in two stored cereals: wheat and barley. We analyzed mite abundance, frequency and species composition in samples of grain obtained from 79 selected Czech grain stores. Stored barley seemed to be more vulnerable to mite attack than wheat, as we consistently found more infested samples, more species and higher mean and median mite abundance per sample in barley as compared to wheat. The mean mite abundance per sample were 55 and 506 individuals for wheat and barley, respectively. In barley, 10% of samples exceeded allergen risk threshold (i.e., 1 000 individuals per kg of grain). Altogether, 25 species were identified from approximately 35 000 individuals. The most frequently identified species were the same in wheat and barley, that is, Tydeus interruptus Sig Thor, Acarus siro L., Tarsonemus granarius Lindquist, Lepidoglyphus destructor (Schrank) and Tyrophagus putrescentiae (Schrank). Based on principal components analysis, we found a closer association of T. interruptus , T. putrescentiae , L. destructor and Cheyletus eruditus (Schrank) with barley samples, corresponding to the high frequency and abundance values of these mites. The probable reasons for the higher infestation, especially mite abundance in barley, are discussed in relation to the higher proportion of crushed parts, which may release favorable nutrient sources and amplify the abundance values.     

Binomial sampling plans for estimatingBemisia tabaci populations in cantaloupes

Early season infestations of the sweet potato whitefly, Bemisia tabaci (Gennadius), on cantaloupes, Cucumis melo L., were determined by counts of the number of adults per leaf in fields near Yuma, Arizona. We used these data to develop binomial sampling plans based on the relationship between mean densities of whiteflies per leaf, m, and proportion of leaves infested with more than I whiteflies, P_I, according to the empirical model ln m=a′+b′ ln[−ln(1−P_I)]. The models were developed for the presence-absence approach (I=0) and for a cutoff value of three whiteflies per leaf (I=3). Four independent data sets were used to evaluate the models. Both methods yielded reliable predictions at low infestation levels, but some of the higher m values were overestimated. As the tentative economic threshold for B. tabaci is three adults per leaf, which corresponds to low P_I values, results of the binomial sampling were satisfactory for pest management purposes.     

Presence-absence sequential sampling plan for northern fowl mite, Ornithonyssus sylviarum (Acari: Macronyssidae), on caged-layer hens

Caged-layer hens were scored as infested or uninfested by visual examination of the vent region, and the number of northern fowl mite, Ornithonyssus sylviarum (Canestrini & Fanzago), per hen was estimated. The proportion infested and average number of mites per hen were shown to have a highly significant, positive relationship (r = 0.936). Sampling among houses within a flock, and rows and sections within houses were analyzed to determine the reliability of sampling a representative portion of a flock. Low- and moderate-tolerance treatment thresholds, based on percentage of hens infested with mites, were developed from sampling 1 wk before and 1 wk after acaricide treatments determined necessary by the producer. These thresholds were used to compare a fixed (single) sampling plan, a curtailed procedure of the fixed sampling plan, and a sequential sampling plan based on a sequential probability ratio test, by sampling 174 hens (the maximum number needed for the single sampling plan). The sequential sampling plan required fewer hen examinations on average to reach a treatment decision than did the other plans, depending on the infestation tolerance limits. Using a low tolerance approach in which infestations below 15% are considered noneconomic (safe threshold) and infestations above 25% are considered economically important (action threshold), as few as 5 hens required examination to reach a treatment decision. Sequential sampling plan graphs are presented for 2 tolerance threshold scenarios (a 15% safe-threshold paired with a 25% action threshold and a 35% safe-threshold paired with a 45% action threshold). These sequential sampling plans using presence absence assessments should greatly facilitate monitoring and treatment decisions for this important pest.     

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.     

棉花苗期棉蚜的二项式抽样设计及其精度分析(英文)

1991年4月—7月在河北省北京农业大学曲周试验站的棉花地进行苗期棉蚜（Aphisgossypii）的田间抽样调查,共收集到24组抽样数据。用泰勒幂法则对数据进行拟合,得到棉花苗期棉蚜为聚集分布。利用每样方（株）虫口不超过数阈值T（分别为0,1,2…9,10,15,20,30）头蚜虫的植株比例（PT）与种群密度（m,头／株）的关系,拟合经验关系式ln（m）=a十bln[-ln（PT）],通过对不同数阈值T的回归决定系数（r2）、种群的回归估计方差（Var（m））和抽样精度（用d估计）等进行综合分析,结果表明该蚜虫在数阈值T为15时,回归估计方差最小,回归决定系数和d值最大,因而T=15为该蚜虫的理想数阈值;而小的T值尤其是T为O时,由于产生太大的回归估计方差,很小的回归决定系数和d值即抽样的精度极低,因而不宜在实际中应用于棉蚜的二项式抽样设计。     

Development and validation of a binomial sequential sampling plan for the greenbug (Homoptera: Aphididae) infesting winter wheat in the southern plains

From 1997 to 1999, Schizaphis graminum (Rondani), intensity (number per tiller) was estimated on 115 occasions from hard red winter wheat fields located throughout the major wheat growing regions of Oklahoma. A total of 32 and 83 fields was sampled during the fall and spring, respectively. The parameters of linear regressions relating the mean number of greenbugs per tiller (m) and the proportion of infested tillers (PT) differed significantly between fall and spring infestations. The PT-m linear model provided a good fit for data on S. graminum for fall and spring infestations at tally thresholds of 0, 1, 2, and 3. A tally threshold (T) represents the number of greenbugs present on a tiller before the tiller is classified as infested by >T greenbugs. A regression model with a tally threshold of 2 was the most precise for classifying S. graminum populations during fall growth of winter wheat because it explained a greater amount of the variation in the PT-m relationship (97%) than models with other tally thresholds. A separate spring model with a tally threshold of 1 was the most precise for classifying S. graminum populations during spring growth of winter wheat. Sequential sampling stop lines based on sequential probability ratio tests were calculated for economic thresholds of 3 or 6 greenbugs per tiller for fall infestations and 6 or 9 greenbugs per tiller for spring infestations. With the newly developed parameters, the average sample number required to classify greenbug populations near economic thresholds (as above or below the economic threshold) varied from 69 to 207. We expect that the sampling plans for greenbugs in winter wheat developed during this study will be efficient and useful tools for consultants and producers in the southern plains.     

Spatial distributions of the red palm mite, Raoiella indica (Acari: Tenuipalpidae) on coconut and their implications for development of efficient sampling plans

The red palm mite (Raoiella indica), an invasive pest of coconut, entered the Western hemisphere in 2004, then rapidly spread through the Caribbean and into Florida, USA. Developing effective sampling methods may aid in the timely detection of the pest in a new area. Studies were conducted to provide and compare intra tree spatial distribution of red palm mite populations on coconut in two different geographical areas, Trinidad and Puerto Rico, recently invaded by the mite. The middle stratum of a palm hosted significantly more mites than fronds from the upper or lower canopy and fronds from the lower stratum, on average, had significantly fewer mites than the two other strata. The mite populations did not vary within a frond. Mite densities on the top section of the pinna had significantly lower mite densities than the two other sections, which were not significantly different from each other. In order to improve future sampling plans for the red palm mite, the data was used to estimate the variance components associated with the various levels of the hierarchical sampling design. Additionally, presence-absence data were used to investigate the probability of no mites being present in a pinna section randomly chosen from a frond inhabited by mites at a certain density. Our results show that the most precise density estimate at the plantation level is to sample one pinna section per tree from as many trees as possible.     

Seasonal dynamics, dispersion, sequential sampling plans and treatment thresholds for the citrus leafminer, Phyllocnistis citrella Stainton (Lepidoptera: Gracillariidae), in a mature lemon block in coastal New South Wales, Australia

Abstract  Studies of citrus leafminer in a coastal orchard in NSW, Australia indicated that an increase in abundance to about one mine per flush was followed during the midseason flush by a rapid increase in population that was related to an increase in the percentage of leaves infested within flushes and the number of mines per leaf. The fits of frequency distributions and Iwao's patchiness regression indicated that populations were highly contagious initially, and as the exponent k of the negative binomial distribution increased with increasing population density, the distribution approached random. Concurrently, the coefficient of variation of mines per flush (which was strongly related to the proportion of un-infested flushes) decreased to about unity as the proportion of un-infested flushes reached zero and fell further as the number of mines per flush increased. Both numerative and binomial sequential sampling plans were developed using a decision threshold based on 1.2 mines per flush. The binomial sampling plan was based on a closely fitting model of the functional relationship between mean density and proportion of infested flushes. Functional relationships using the parameters determined from Iwao's patchiness regression and Taylor's power law were equally satisfactory, and one based on the negative binomial model also fitted well, but the Poisson model did not. The three best fitting models indicated that a decision threshold of 1.2 mines per flush was equivalent to 50% of flushes infested. From a practical point of view, the transition from 25% infestation of flushes through 50% is so rapid that it may be prudent to take action when the 25% level is reached; otherwise, the 50% may be passed before the crop is checked again. For valuable nursery stock should infestation be detected in spring, it may be advisable to apply prophylactic treatment as the midseason flush starts.     

Binomial sequential sampling of adult Saccharicoccus sacchari on sugarcane

The between-stalk dispersion characteristics of adults of the pink sugarcane mealybug Saccharicoccus sacchari (Cockerell) were determined in southern Queensland. Iwao's patchiness regression was inappropriate to describe the relationship between mean and variance. Taylor's power law indicated that adults were aggregated, especially at the beginning and end of the ratoon growth period. Binomial data were modelled by the Nachman model; the model of Grout and two models of Wilson & Room were inappropriate to describe the relationship between proportion of stalks infested and mean numbers of adults per stalk. Relationships to determine sample sizes for fixed levels of precision and binomial fixed-precision-level stop lines are developed for different sampling times using Taylor's power law and Nachman's equation.     

Sampling methods as abundance indices for adult Diaprepes abbreviatus (Coleoptera: Curculionidae) in citrus

Beat sampling and two type of traps, cup traps and Tedders traps, were evaluated as sampling methods to detect and estimate population densities of adult Diaprepes abbreviatus L. weevils newly colonizing young citrus trees. The study was conducted over a 65-wk period across a 0.25-ha area of 80 citrus trees [Citrus sinensis (L.) Osbeck] (1.2-1.5 m tall). Beat samples were taken weekly to determine the number of trees infested and number of new adult weevils per tree. Sixteen of the 80 trees studied were each monitored weekly using one of the following trapping methods: cup traps in trees, cup traps on a stake in the ground within the tree drip line, cup traps on a stake in the ground outside of the drip line, Tedders traps on the ground within the drip line, and Tedders traps on the ground outside of the drip line. Weevils collected each week from trees and traps were removed from the study site. Based on the coefficients associated with Taylor's power law, the optimum numbers of trees to sample for an SEM equal to 25% of the mean estimate decreased from 50 trees at a mean of 0.5 new weevils per tree to 30 trees at a mean of 0.8 new weevils per tree. A significant relationship was found between the weekly mean number of new weevils per tree and the proportion of trees infested, a binomial relationship that could be further explored in the search for a sampling program for adult D. abbreviatus. Regression analyses indicated that three of the trapping methods served at least as weak indices of the presence and abundance of new weevils: cup traps in trees, Tedders traps inside the dripline and Tedders traps outside the dripline. Cup traps in trees and Tedders traps inside the dripline captured the most weevils and most frequently detected weevils. Although relatively inefficient as abundance indices of populations of new weevils, these two trapping methods appeared to have some value with respect to signaling when weevils first appeared in trees during the spring.     

Beat sampling accuracy in estimating spruce spider mite (Acari: Tetranychidae) populations and injury on juniper

The use of a standardized beat sampling method for estimating spruce spider mite, Oligonychus ununguis (Jacobi) (Acari: Tetranychidae), densities on a widely used evergreen ornamental plant species, Juniperus chinensis variety 'Sargentii' A. Henry (Cupressaceae), was examined. There was a significant positive relationship between total spruce spider mite densities and spider mite densities from beat sampling on juniper. The slope and intercept of the relationship may be used by pest managers to predict total spider mite densities on plants from beat sample counts. Beat sampling dramatically underestimates the total number of spider mites on a foliage sample. The relationships between spruce spider mite feeding injury and spider mite density estimates from beat sampling juniper foliage and total spider mite counts on foliage were also examined. There was a significant positive relationship between spruce spider mite density as estimated from beat sampling and injury to the plants. There was a similar positive relationship between the total number of spruce spider mites and injury to the plants, suggesting that a pest manager could use beat sampling counts to estimate plant injury and related thresholds. These findings have important implications to decision-making for spruce spider mite control, especially as it relates to threshold levels and determining rates of predator releases. Further assessment of the effectiveness of beat and other sampling methods across multiple spider mite- host plant associations needs to be examined to enable pest managers to select sampling plans that are feasible and reliable.