Presence–Absence Sampling Plans for Stink Bugs (Hemiptera: Pentatomidae) in the Midwest Region of the United States

Stink bugs represent an increasing risk to soybean production in the Midwest region of the United States. The current sampling protocol for stink bugs in this region is tailored for population density estimation and thus is more relevant to research purposes. A practical decision-making framework with more efficient sampling effort for management of herbivorous stink bugs is needed. Therefore, a binomial sequential sampling plan was developed for herbivorous stink bugs in the Midwest region. A total of 146 soybean fields were sampled across 11 states using sweep nets in 2016, 2017, and 2018. The binomial sequential sampling plans were developed using combinations of five tally thresholds at two proportion infested action thresholds to identify those that provided the best sampling outcomes. Final assessment of the operating characteristic curves for each plan indicated that a tally threshold of 3 stink bugs per 25 sweeps, and proportion infested action thresholds of 0.75 and 0.95 corresponding to the action thresholds of 5 and 10 stink bugs per 25 sweeps, provided the optimal balance between highest probability of correct decisions (≥ 99%) and lowest probability of incorrect decisions (≤ 1%). In addition, the average sample size for both plans (18 and 12 sets of 25 sweeps, respectively) was lower than that for the other proposed plans. The binomial sequential sampling plan can reduce the number of sample units required to achieve a management decision, which is important because it can potentially reduce risk/cost of management for stink bugs in soybean in this region.

Development of a Sequential Sampling Plan using Spatial Attributes of Cercospora Leaf Spot Epidemics of Table Beet in New York

Sampling strategies that effectively assess disease intensity in the field are important to underpin management decisions. To develop a sequential sampling plan for the incidence of Cercospora leaf spot (CLS), caused by Cercospora beticola, 31 table beet fields were assessed in New York. Assessments of CLS incidence were performed in six leaves arbitrarily selected in 51 sampling locations along each of the three to six linear transects per field. Spatial pattern analyses were performed, and results were used to develop sequential sampling estimation and classification models. CLS incidence (p) ranged from 0.13 to 0.92 with a median of 0.31, and beta-binomial distribution, which is reflective of aggregation, best described the spatial patterns observed. Aggregation was commonly detected (>95%) by methods using the point-process approach, runs analyses, and autocorrelation up to the fourth spatial lag. For SADIE, 45% of the datasets were classified as a random pattern. In the sequential sampling estimation and classification models, disease units are sampled until a prespecified target is achieved. For estimation, the goal was sampling CLS incidence with a preselected coefficient of variation (C). Achieving the C = 0.1 was challenging with less than 51 sampling units, and only observed on datasets with an incidence above 0.3. Reducing the level of precision, i.e. increasing C to 0.2, allowed the preselected C be achieved with a lower number of sampling units and with an estimated incidence (p̂) close to the true value of p. For classification, the goal was to classify the datasets above or below prespecified thresholds (pt) used for CLS management. The average sample number (ASN) was determined by Monte Carlo simulations, and was between 20 and 45 at disease incidence values close to pt, and approximately 11 when far from pt. Correct decisions occurred in over 76% of the validation datasets. Results indicated these sequential sampling plans can be used to effectively assess CLS incidence in table beet fields.

Risk Assessment for Tomato Fruitworm in Processing Tomato Crop-Egg Location and Sequential Sampling

Helicoverpa armigera is one of the key pests affecting processing tomatoes and many other crops. A three-year study was conducted to describe the oviposition preferences of this species on determinate tomato plants (mainly the stratum, leaf, leaflet, and leaf side) and the spatial pattern of the eggs in the field, to form a sequential sampling plan. Eggs were found mainly in the exposed canopy, on leaves a (upper stratum) and b (upper-middle stratum) and significantly fewer eggs on leaf c (middle-lower stratum) below flower clusters. This vertical pattern in the plant was found in all phenological growth stages. The spatial pattern was found to be aggregated, with a trend towards a random pattern at lower densities. A sequential sampling plan was developed, based on Iwao’s method with the parameters of Taylor’s power law, with minimum and maximum sample size of 20 and 80 sample units (plants), respectively (two leaves/plant). For its validation, operating characteristic (OC) and average sample number (ASN) curves were calculated by means of simulation with independent data sets. The β-error was higher than desirable in the vicinity of the economic threshold, but this sampling plan is regarded as an improvement both in effort and precision, compared with the fixed sample plan, and further improvements are discussed.

Evaluation of Two-Leaf Sampling Units to Estimate Sugarcane Aphid (Hemiptera: Aphididae) Economic Thresholds in Commercial Grain Sorghum

Sugarcane aphid Melanaphis sacchari Zehntner is a significant economic pest of grain sorghum in the United States. Effective monitoring and early detection are cornerstones for managing invasive pests. The recently developed binomial sequential sampling plan estimates sugarcane aphid economic thresholds (ETs) based on classification whether a 2-leaf sample unit has ≤ or ≥ 50 M. sacchari. In this study, we evaluated eight 2-leaf sampling units for potential use in the sequential sampling plan. From 2016 through 2017, whole plant counts of M. sacchari were recorded non-destructively in situ on sorghum plants from 140 fields located in five states. Plant canopies were stratified into three categories. Two leaves from each stratum were used to compare linear relationships between M. sacchari numbers per two-leaf sample unit and total M. sacchari density per plant. Analysis revealed that two randomly selected leaves from the middle stratum accounted more variation for estimating M. sacchari density when compared to two leaves from the other strata. Comparison of eight two-leaf sampling units within plant growth stages were variable in quantifying variation of M. sacchari densities. When growth stages were combined, the standard uppermost + lowermost leaf sample unit and a unit consisting of two randomly selected leaves from the middle stratum revealed little difference in their enumeration of variation in M. sacchari density. Because other sample units were either less predictive and/or more variable in estimating M. sacchari density, we suggest that the (L1+U1) sample unit remain the preferred method for appraising M. sacchari ETs.

Within-plant distribution and binomial sequential sampling plan for Tetranychus evansi (Acari: Tetranychidae) in greenhouse tomato: implications for management.

The red spider mite, Tetranychus evansi is a critical pest of tomato in the tropics. Control of T. evansi has traditionally depended on acaricide treatments. However, it is only in a handful of crops where monitoring techniques for mites, using statistical methods, have been developed to help farmers decide when to spray. The objective of this study, therefore, was to develop a sampling plan that would help farmers increase accuracy, and reduce the labor and time needed to monitor T. evansi on tomato. The distribution of T. evansi within-plant was aggregated, and intermediate leaves (YFL) was the most appropriate sampling unit to evaluate the mite density. Analysis based on Taylor's Power Law showed an aggregated pattern of distribution of T. evansi, while assessment of the fitness of the binomial model indicated that a tally threshold of 5 mites per YFL provided the best fit. Consequently, binomial sequential sampling plans premised on three action thresholds (0.1, 0.2 and 0.3) were developed. The binomial sequential sampling plan for T. evansi developed in this study has the potential to significantly increase the chance for targeted acaricide applications. This judicious use of pesticides is especially crucial within the context of integrated pest management (IPM).