Spatial Patterns and Sequential Sampling Plans for Estimating Densities of Stink Bugs (Hemiptera: Pentatomidae) in Soybean in the North Central Region of the United States

Stink bugs are an emerging threat to soybean (Fabales: Fabaceae) in the North Central Region of the United States. Consequently, region-specific scouting recommendations for stink bugs are needed. The aim of this study was to characterize the spatial pattern and to develop sampling plans to estimate stink bug population density in soybean fields. In 2016 and 2017, 125 fields distributed across nine states were sampled using sweep nets. Regression analyses were used to determine the effects of stink bug species [Chinavia hilaris (Say) (Hemiptera: Pentatomidae) and Euschistus spp. (Hemiptera: Pentatomidae)], life stages (nymphs and adults), and field locations (edge and interior) on spatial pattern as represented by variance–mean relationships. Results showed that stink bugs were aggregated. Sequential sampling plans were developed for each combination of species, life stage, and location and for all the data combined. Results for required sample size showed that an average of 40–42 sample units (sets of 25 sweeps) would be necessary to achieve a precision of 0.25 for stink bug densities commonly encountered across the region. However, based on the observed geographic gradient of stink bug densities, more practical sample sizes (5–10 sample units) may be sufficient in states in the southeastern part of the region, whereas impractical sample sizes (\u3e100 sample units) may be required in the northwestern part of the region. Our findings provide research-based sampling recommendations for estimating densities of these emerging pests in soybean

Object Relations in the Museum: A Psychosocial Perspective

This article theorises museum engagement from a psychosocial perspective. With the aid of selected concepts from object relations theory, it explains how the museum visitor can establish a personal relation to museum objects, making use of them as an ‘aesthetic third’ to symbolise experience. Since such objects are at the same time cultural resources, interacting with them helps the individual to feel part of a shared culture. The article elaborates an example drawn from a research project that aimed to make museum collections available to people with physical and mental health problems. It draws on the work of the British psychoanalysts Donald Winnicott and Wilfred Bion to explain the salience of the concepts of object use, potential space, containment and reverie within a museum context. It also refers to the work of the contemporary psychoanalyst Christopher Bollas on how objects can become evocative for individuals both by virtue of their intrinsic qualities and by the way they are used to express personal idiom

Community Composition, Abundance, and Phenology of Stink Bugs (Hemiptera: Pentatomidae) in Soybean in the North Central Region of the United States

Stink bugs (Hemiptera: Pentatomidae) are an increasing threat to soybean (Fabales: Fabaceae) production in the North Central Region of the United States, which accounts for 80% of the country’s total soybean production. Characterization of the stink bug community is essential for development of management programs for these pests. However, the composition of the stink bug community in the region is not well defined. This study aimed to address this gap with a 2-yr, 9-state survey. Specifically, we characterized the relative abundance, richness, and diversity of taxa in this community, and assessed phenological differences in abundance of herbivorous and predatory stink bugs. Overall, the stink bug community was dominated by Euschistus spp. (Hemiptera: Pentatomidae) and Chinavia hilaris (Say) (Hemiptera: Pentatomidae). Euschistus variolarius (Palisot de Beauvois) (Hemiptera: Pentatomidae), C. hilaris and Halyomorpha halys (Stål) (Hemiptera: Pentatomidae) were more abundant in the northwestern, southeastern and eastern parts, respectively, of the North Central Region of the United States. Economically significant infestations of herbivorous species occurred in fields in southern parts of the region. Species richness differed across states, while diversity was the same across the region. Herbivorous and predatory species were more abundant during later soybean growth stages. Our results represent the first regional characterization of the stink bug community in soybean fields and will be fundamental for the development of state- and region-specific management programs for these pests in the North Central Region of the United States

Spatial Patterns and Sequential Sampling Plans for Estimating Densities of Stink Bugs (Hemiptera: Pentatomidae) in Soybean in the North Central Region of the United States

Stink bugs are an emerging threat to soybean (Fabales: Fabaceae) in the North Central Region of the United States. Consequently, region-specific scouting recommendations for stink bugs are needed. The aim of this study was to characterize the spatial pattern and to develop sampling plans to estimate stink bug population density in soybean fields. In 2016 and 2017, 125 fields distributed across nine states were sampled using sweep nets. Regression analyses were used to determine the effects of stink bug species [Chinavia hilaris (Say) (Hemiptera: Pentatomidae) and Euschistus spp. (Hemiptera: Pentatomidae)], life stages (nymphs and adults), and field locations (edge and interior) on spatial pattern as represented by variance–mean relationships. Results showed that stink bugs were aggregated. Sequential sampling plans were developed for each combination of species, life stage, and location and for all the data combined. Results for required sample size showed that an average of 40–42 sample units (sets of 25 sweeps) would be necessary to achieve a precision of 0.25 for stink bug densities commonly encountered across the region. However, based on the observed geographic gradient of stink bug densities, more practical sample sizes (5–10 sample units) may be sufficient in states in the southeastern part of the region, whereas impractical sample sizes (\u3e100 sample units) may be required in the northwestern part of the region. Our findings provide research-based sampling recommendations for estimating densities of these emerging pests in soybean

Parasitism of Adult Pentatomidae by Tachinidae in Soybean in the North Central Region of the United StatesPheylan

Stink bugs (Hemiptera: Pentatomidae) are agricultural pests of increasing significance in the North Central Region of the United States, posing a threat to major crops such as soybean. Biological control can reduce the need for insecticides to manage these pests, but the parasitism of stink bugs byTachinidae (Diptera) is poorly characterized in this region. The objective of this study was to evaluate the rate of parasitism of stink bugs by tachinids over 2 yr from nine states across the North Central Region. Parasitism was assessed by quantifying tachinid eggs on the integument of stink bug adults. Parasitism rates (i.e., percent of adult stink bugs with tachinid eggs) were compared across stink bug species, states, stink bug sex, and years.The mean percent parasitism of stink bugs by tachinids was about 6% across the region and did not differ among stink bug species. Mean percent parasitism was significantly higher in Missouri than in northern and western states. In addition, male stink bugs had significantly higher mean percent parasitism than females. Stink bug species commonly found in soybean in the region showed some parasitism and are therefore potentially vulnerable to oviposition by these parasitoids.This is the first study to characterize the level of parasitism of stink bugs by tachinids across the North Central Region

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

Mass spectrometry protein expression profiles in colorectal cancer tissue associated with clinico-pathological features of disease

Background: Studies of several tumour types have shown that expression profiling of cellular protein extracted from surgical tissue specimens by direct mass spectrometry analysis can accurately discriminate tumour from normal tissue and in some cases can sub-classify disease. We have evaluated the potential value of this approach to classify various clinico-pathological features in colorectal cancer by employing matrix-assisted laser desorption ionisation time of-flight-mass spectrometry (MALDI-TOF MS). Methods: Protein extracts from 31 tumour and 33 normal mucosa specimens were purified, subjected to MALDI-Tof MS and then analysed using the `GenePattern' suite of computational tools (Broad Institute, MIT, USA). Comparative Gene Marker Selection with either a t-test or a signal-to-noise ratio (SNR) test statistic was used to identify and rank differentially expressed marker peaks. The k-nearest neighbours algorithm was used to build classification models either using separate training and test datasets or else by using an iterative, `leave-one-out' cross-validation method. Results: 73 protein peaks in the mass range 1800-16000Da were differentially expressed in tumour verses adjacent normal mucosa tissue (P <= 0.01, false discovery rate <= 0.05). Unsupervised hierarchical cluster analysis classified most tumour and normal mucosa into distinct cluster groups. Supervised prediction correctly classified the tumour/normal mucosa status of specimens in an independent test spectra dataset with 100\% sensitivity and specificity (95\% confidence interval: 67.9-99.2\%). Supervised prediction using `leave-one-out' cross validation algorithms for tumour spectra correctly classified 10/13 poorly differentiated and 16/18 well/moderately differentiated tumours (P = < 0.001; receiver-operator characteristics - ROC - error, 0.171); disease recurrence was correctly predicted in 5/6 cases and disease-free survival (median follow-up time, 25 months) was correctly predicted in 22/23 cases (P = < 0.001; ROC error, 0.105). A similar analysis of normal mucosa spectra correctly predicted 11/14 patients with, and 15/19 patients without lymph node involvement (P = 0.001; ROC error, 0.212). Conclusions: Protein expression profiling of surgically resected CRC tissue extracts by MALDI-TOF MS has potential value in studies aimed at improved molecular classification of this disease. Further studies, with longer follow-up times and larger patient cohorts, that would permit independent validation of supervised classification models, would be required to confirm the predictive value of tumour spectra for disease recurrence/patient survival