Evaluation of exclusion netting for insect pest control and fruit quality enhancement in tree crops

This work evaluated the following aspects of the use of exclusion netting in low chill stone fruit: the efficacy of protection from fruit fly for this highly susceptible crop; the effects on environmental factors; and the effects on crop development. Concurrently, an economic viability study on the use of exclusion netting was undertaken. The trial site was a 0.6-ha block of low chill stone fruit at Nambour, south-east Queensland, Australia. In this area, populations of Queensland fruit fly (Bactrocera tryoni) are known to be substantial, particularly in spring and summer. The trial block contained healthy 4-year-old trees as follows: 96 peach trees (Prunus persica cv. Flordaprince) and 80 nectarine trees (40 P. persica var. nucipersica cv. White Satin and 40 P. persica var. nucipersica cv. Sunwright). Exclusion netting was installed over approximately half of the block in february 2001. The net was a UV-stabilized structural knitted fabric made from high-density polyethylene yarn with a 10-year prorated UV degradation warranty. The results demonstrated the efficacy of exclusion netting in the control of fruit flies. Exclusion netting increased maximum temperatures by 4.4 deg C and decreased minimum temperatures by 0.5 deg C. Although exclusion netting reduced irradiance by approximately 20%, it enhanced fruit development by 7-10 days and improved fruit quality by increasing sugar concentration by 20-30% and colour intensity by 20%.

The potential for monitoring and control of insect pests in Southern Hemisphere forestry plantations using semiochemicals

Southern Hemisphere plantation forestry has grown substantially over the past few decades and will play an increasing role in fibre production and carbon sequestration in future. The sustainability of these plantations is, however, increasingly under pressure from introduced pests. This pressure requires an urgent and matching increase in the speed and efficiency at which tools are developed to monitor and control these pests. To consider the potential role of semiochemicals to address the need for more efficient pest control in Southern Hemisphere plantations, particularly by drawing from research in other parts of the world. Semiochemical research in forestry has grown exponentially over the last 40 years but has been almost exclusively focussed on Northern Hemisphere forests. In these forests, semiochemicals have played an important role to enhance the efficiency of integrated pest management programmes. An analysis of semiochemical research from 1970 to 2010 showed a rapid increase over time. It also indicated that pheromones have been the most extensively studied type of semiochemical in forestry, contributing to 92% of the semiochemical literature over this period, compared with research on plant kairomones. This research has led to numerous applications in detection of new invasions, monitoring population levels and spread, in addition to controlling pests by mass trapping or disrupting of aggregation and mating signals. The value of semiochemicals as an environmentally benign and efficient approach to managing forest plantation pests in the Southern Hemisphere seems obvious. There is, however, a lack of research capacity and focus to optimally capture this opportunity. Given the pressure from increasing numbers of pests and reduced opportunities to use pesticides, there is some urgency to develop semiochemical research capacity.

Insect pests in tropical forestry

The layout of this second edition follows that of the first, though the content has been substantially rewritten to reflect 10 years of research and development, as well as the emergence of new pest species. Chapter 1 presents an overview, from a somewhat entomological perspective, of tropical forestry in its many guises. Chapters 2, 3 and 4 then discuss the 'pure' biology and ecology of tropical insects and their co-evolved relationships with the trees and forests in which they live. Chapter 5 is necessarily the largest chapter in the book, looking in detail at a selection of major pest species from all over the tropical world. Chapters 6, 7, 8 and 9 then discuss the theory and practice of insect pest management, starting at the fundamental planning stage, before any seeds hit the soil. Nursery management and stand management were considered in Chapters 7 and 8. Chapter 9 covers the topics of forest health surveillance, quarantine and forest invasive species, topics which again have significance at all stages of forestry but for convenience are presented after nursery and forest management. This, in fact, we attempt to do in the final chapter, Chapter 10, which combines most of the previous nine chapters in examples illustrating the concept of integrated pest management. ©CABI Publishing CABI Publishing

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.

A new gall midge of the genus Dentifibula (Diptera: Cecidomyiidae), a predator of the scale insect Aulacaspis australis feeding on mangrove Bruguiera gymnorrhiza

Dentifibula nigroapicalisKolesik sp. nov., a new species of gall midge, is described whose larvae were found preying on the mangrove scale insect Aulacaspis australisBrimblecombe (Hemiptera: Coccoidea: Diaspididae). The mangrove scale was feeding on leaves of the mangrove Bruguiera gymnorrhiza (Rhizophoraceae) in Queensland. The new species is the first DentifibulaFelt known from Australia. © 2013 Australian Entomological Society.

Cytorhabdovirus phosphoprotein shows RNA silencing suppressor activity in plants, but not in insect cells

RNA silencing in plants and insects provides an antiviral defense and as a countermeasure most viruses encode RNA silencing suppressors (RSS). For the family Rhabdoviridae, no detailed functional RSS studies have been reported in plant hosts and insect vectors. In agroinfiltrated Nicotiana benthamiana leaves we show for the first time for a cytorhabdovirus, lettuce necrotic yellows virus (LNYV), that one of the nucleocapsid core proteins, phosphoprotein (P) has relatively weak local RSS activity and delays systemic silencing of a GFP reporter. Analysis of GFP small RNAs indicated that the P protein did not prevent siRNA accumulation. To explore RSS activity in insects, we used a Flock House virus replicon system in Drosophila S2 cells. In contrast to the plant host, LNYV P protein did not exhibit RSS activity in the insect cells. Taken together our results suggest that P protein may target plant-specific components of RNA silencing post siRNA biogenesis.

The insecticidal spider toxin SFI1 is a knottin peptide that blocks the pore of insect voltage-gated sodium channels via a large β-hairpin loop

Spider venoms contain a plethora of insecticidal peptides that act on neuronal ion channels and receptors. Because of their high specificity, potency and stability, these peptides have attracted much attention as potential environmentally friendly insecticides. Although many insecticidal spider venom peptides have been isolated, the molecular target, mode of action and structure of only a small minority have been explored. Sf1a, a 46-residue peptide isolated from the venom of the tube-web spider Segesteria florentina, is insecticidal to a wide range of insects, but nontoxic to vertebrates. In order to investigate its structure and mode of action, we developed an efficient bacterial expression system for the production of Sf1a. We determined a high-resolution solution structure of Sf1a using multidimensional 3D/4D NMR spectroscopy. This revealed that Sf1a is a knottin peptide with an unusually large β-hairpin loop that accounts for a third of the peptide length. This loop is delimited by a fourth disulfide bond that is not commonly found in knottin peptides. We showed, through mutagenesis, that this large loop is functionally critical for insecticidal activity. Sf1a was further shown to be a selective inhibitor of insect voltage-gated sodium channels, consistent with its 'depressant' paralytic phenotype in insects. However, in contrast to the majority of spider-derived sodium channel toxins that function as gating modifiers via interaction with one or more of the voltage-sensor domains, Sf1a appears to act as a pore blocker.

Spatial ecology of a specialist insect herbivore : the leaf-mining moth Tischeria ekebladella on the pedunculate oak Quercus robur

Herbivorous insects comprise a major part of terrestrial biodiversity, and their interactions with their host plants and natural enemies are of vast ecological importance. A large body of research demonstrates that the ecology and evolution of these insects may be affected by trophic interactions, by abiotic influences, and by intraspecific processes, but so far research on these individual aspects has rarely been combined. This thesis uses the leaf-mining moth Tischeria ekebladella and the pedunculate oak (Quercus robur) as a case study to assess how spatial variation in trophic interactions and the physical distribution of host trees jointly affect the distribution, dynamics and evolution of a host-specific herbivore. With respect to habitat quality, Tischeria ekebladella experiences abundant variation at several spatial scales. Most of this variation occurs at small scales notably among leaves and shoots within individual trees. While hypothetically this could cause moths to evolve an ability to select leaves and shoots of high quality, I did not find any coupling between female preference and offspring performance. Based on my studies on temporal variation in resource quality I therefore propose that unpredictable temporal changes in the relative rankings of individual resource units may render it difficult for females to predict the fate of their developing offspring. With respect to intraspecific processes, my results suggest that limited moth dispersal in relation to the spatial distribution of oak trees plays a key role in determining the regional distribution of Tischeria ekebladella. The distribution of the moth is aggregated at the landscape level, where local leaf miner populations are less likely to be present where oaks are scarce. A modelling exercise based on empirical dispersal estimates revealed that the moth population on Wattkast an island in south-western Finland is spatially structured overall, but that the relative importance of local and regional processes on tree-specific moth dynamics varies drastically across the landscape. To conclude, my work in the oak-Tischeria ekebladella system demonstrates that the local abundance and regional distribution of a herbivore may be more strongly influenced by the spatial location of host trees than by their relative quality. Hence, it reveals the importance of considering spatial context in the study of herbivorous insects, and forms a bridge between the classical fields of plant-insect interactions and spatial ecology.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.

A generic individual-based spatially explicit model as a novel tool for investigating insect-plant interactions: A case study of the behavioural ecology of frugivorous Tephritidae

Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies’ behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies’ movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of parameters based on targeted experiments.

Assessment of insect occurrence in boreal forests based on satellite imagery and field measurements.

The presence/absence data of twenty-seven forest insect taxa (e.g. Retinia resinella, Formica spp., Pissodes spp., several scolytids) and recorded environmental variation were used to investigate the applicability of modelling insect occurrence based on satellite imagery. The sampling was based on 1800 sample plots (25 m by 25 m) placed along the sides of 30 equilateral triangles (side 1 km) in a fragmented forest area (approximately 100 km2) in Evo, S Finland. The triangles were overlaid on land use maps interpreted from satellite images (Landsat TM 30 m multispectral scanner imagery 1991) and digitized geological maps. Insect occurrence was explained using either environmental variables measured in the field or those interpreted from the land use and geological maps. The fit of logistic regression models varied between species, possibly because some species may be associated with the characteristics of single trees while other species with stand characteristics. The occurrence of certain insect species at least, especially those associated with Scots pine, could be relatively accurately assessed indirectly on the basis of satellite imagery and geological maps. Models based on both remotely sensed and geological data better predicted the distribution of forest insects except in the case of Xylechinus pilosus, Dryocoetes sp. and Trypodendron lineatum, where the differences were relatively small in favour of the models based on field measurements. The number of species was related to habitat compartment size and distance from the habitat edge calculated from the land use maps, but logistic regressions suggested that other environmental variables in general masked the effect of these variables in species occurrence at the present scale.

Characterization of the genome of Oryctes baculovirus, a viral biocide of the insect pest Oryctes rhinoceros

Oryctes baculovirus is a viral biocide exploited for the control of the insect pest Oryctes rhinoceros. We have recently established a physical map of the genome of the Indian isolate of Oryctes baculovirus (OBV-KI). Here we examine the genomic relatedness between OBV-KI and OBV-PV505, the type isolate (originally from the Philippines), by DNA reassociation kinetics and by the use of restriction endonucleases. On the basis of differences in restriction-enzyme profiles between the two genomes, and previously reported differences in protein profiles and antigenic makeup, we propose the taxonomic status of a variant of Oryctes baculovirus for the Indian isolate.