77 resultados para Agricultural pests

em eResearch Archive - Queensland Department of Agriculture


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Of the 70 cases of classical biological control for the protection of nature found in our review, there were fewer projects against insect targets (21) than against invasive plants (49), in part, because many insect biological control projects were carried out against agricultural pests, while nearly all projects against plants targeted invasive plants in natural ecosystems. Of 21 insect projects, 81% (17) provided benefits to protection of biodiversity, while 48% (10) protected products harvested from natural systems, and 5% (1) preserved ecosystem services, with many projects contributing to more than one goal. In contrast, of the 49 projects against invasive plants, 98% (48) provided benefits to protection of biodiversity, while 47% (23) protected products, and 25% (12) preserved ecosystem services, again with many projects contributing to several goals. We classified projects into complete control (pest generally no longer important), partial control (control in some areas but not others), and "in progress," for projects in development for which outcomes do not yet exist. For insects, of the 21 projects discussed, 59% (13) achieved complete control of the target pest, 18% (4) provided partial control, and 41% (9) are still in progress. By comparison, of the 49 invasive plant projects considered, 27% (13) achieved complete control, while 33% (16) provided partial control, and 47% (24) are still in progress. For both categories of pests, some projects' success ratings were scored twice when results varied by region. We found approximately twice as many projects directed against invasive plants than insects and that protection of biodiversity was the most frequent benefit of both insect and plant projects. Ecosystem service protection was provided in the fewest cases by either insect or plant biological control agents, but was more likely to be provided by projects directed against invasive plants, likely because of the strong effects plants exert on landscapes. Rates of complete success appeared to be higher for insect than plant targets (59% vs 27%), perhaps because most often herbivores gradually weaken, rather than outright kill, their hosts, which is not the case for natural enemies directed against pest insects. For both insect and plant biological control, nearly half of all projects reviewed were listed as currently in progress, suggesting that the use of biological control for the protection of wildlands is currently very active.

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Develops a new technology for the delivery of biocides against agricultural pests, with biocides contained within silica nanocapsules which are themselves protected by an outer envelope, capable of being selectively broken down by the target pest. Will reduce the amount of biocide escaping into the environment, prolong the life of the biocide, reduce biocide usage rates, and reduce undesirable effects on non-target organisms.

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Extractive components obtained from milling residues of white cypress were studied for chemical identity and bioactivity with a view to developing a commercial use for these components, thus increasing the value of the residues and improving the economics of cypress sawn wood production. Extracts obtained by solvent or steam extraction techniques from cypress sawdust were each fractionated by a range of techniques into groups of similar compounds. Crude extracts and fractions were screened against a range of agricultural pests and diseases, including two fungi, subterranean termites, fruit spotting bugs, two-spotted mites, thrips, heliothis, banana scab moths, silverleaf whiteflies, cattle tick adults and larvae, and ruminant gastrointestinal nematodes. Additional screening was undertaken where encouraging results were achieved, for two-spotted mites, thrips, silverleaf whiteflies, cattle tick adults and ruminant gastrointestinal nematodes. After considering degrees of efficacy against, and economic importance of, the agricultural pests, and likely production costs of extracts and fractions, the crude extract (oil) produced by steam distillation was chosen for further study against silverleaf whitefly. A useful degree of control was achievable when this oil was applied to tomato or eggplant at 0.1%, with much less harmful effects on a beneficial insect. Activity of the oil against silverleaf whitefly was undiminished 3.5 years after it was generated. There was little benefit from supplementing the extract with co-formulated paraffinic oil. From the steam distilled oil, fifty-five compounds were characterised, thirty-five compounds representing 92.478 % of the oil, with guaiol (20.8%) and citronellic acid (15.9%) most abundant. These two compounds, and a group of oxygenated compounds containing bulnesol and a range of eudesmols, were found to account for most of the activity against silverleaf whitefly. This application was recommended for first progression to commercialisation.

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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 methodology 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 this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling 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 clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.

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A list is given of 34 species of Lepidoptera feeding on litchi in northern Queensland, including notes on type of damage and months of activity. Records from outside of Australia are also reviewed.

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This book is a resource for those involved ‘on-the-ground’ with growing plantation trees in Vietnam, identifying the pests and diseases found on them, and managing the impacts of these organisms. The book, supported by AusAID’s Vietnam CARD (Cooperation for Agricultural and Rural Development) Program, and draws on the collective, long-standing experience of forest health scientists in Vietnam, Australia and South Africa. The book provides illustrations and information on 23 pests and 25 diseases of Acacia, Eucalyptus and Pinus for Vietnam; four of these species are important biosecurity threats not yet present in Vietnam.

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Weeds are a hidden foe for crop plants, interfering with their functions and suppressing their growth and development. Yield losses of ∼34 are caused by weeds among the major crops, which are grown worldwide. These yield losses are higher than the losses caused by other pests in the crops. Sustainable weed management is needed in the wake of a huge decline in crop outputs due to weed pressure. A diversity in weed management tools ensures sustainable weed control and reduces chances of herbicide resistance development in weeds. Allelopathy as a tool, can be importantly used to combat the challenges of environmental pollution and herbicide resistance development. This review article provides a recent update regarding the practical application of allelopathy for weed control in agricultural systems. Several studies elaborate on the significance of allelopathy for weed management. Rye, sorghum, rice, sunflower, rape seed, and wheat have been documented as important allelopathic crops. These crops express their allelopathic potential by releasing allelochemicals which not only suppress weeds, but also promote underground microbial activities. Crop cultivars with allelopathic potentials can be grown to suppress weeds under field conditions. Further, several types of allelopathic plants can be intercropped with other crops to smother weeds. The use of allelopathic cover crops and mulches can reduce weed pressure in field crops. Rotating a routine crop with an allelopathic crop for one season is another method of allelopathic weed control. Importantly, plant breeding can be explored to improve the allelopathic potential of crop cultivars. In conclusion, allelopathy can be utilized for suppressing weeds in field crops. Allelopathy has a pertinent significance for ecological, sustainable, and integrated weed management systems.

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Fortunately, plants have developed highly effective mechanisms with which to defend themselves when attacked by potentially disease-causing microorganisms. If not, then they would succumb to the many pathogenic fungi, bacteria, viruses, nematodes and insect pests, and disease would prevail. These natural defence systems of plants can be deliberately activated to provide some protection against the major pathogens responsible for causing severe yield losses in agricultural and horticultural crops. This is the basis of what is known as ‘induced’ or ‘acquired’ disease resistance in plants. Although the phenomenon of induced resistance has been known amongst plant pathologists for over 100 years, its inclusion into pest and disease management programmes has been a relatively recent development, ie. within the last 5 years. This review will discuss very briefly some of the characteristics of the induced resistance phenomenon, outline some of the advantages and limitations to its implementation and provide some examples within a postharvest pathology context. Finally some approaches being investigated by the fruit pathology team at DPI Indooroopilly and collaborators will be outlined.

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1 Five experiments were conducted during 1995-99 in stone fruit orchards on the Central Coast and in inland New South Wales, Australia, on the use of synthetic aggregation pheromones and a coattractant to suppress populations of the ripening fruit pests Carpophilus spp. (Coleoptera: Nitidulidae). 2 Perimeter-based suppression traps baited with pheromone and coattractant placed at 3m intervals around small fruit blocks, caught large numbers of Carpophilus spp. Very small populations of Carpophilus spp. occurred within blocks, and fruit damage was minimal. 3 Carpophilus spp. populations in stone fruit blocks 15-370m from suppression traps were also small and non-damaging, indicating a large zone of pheromone attractivity. 4 Pheromone/coattractant-baited suppression traps appeared to divert Carpophilus spp. from nearby (130 m) ripening stone fruit. Ten metal drums containing decomposing fruit, baited with pheromone and treated with insecticide, attracted Carpophilus spp. and appeared to reduce populations and damage to ripening fruit at distances of 200-500 m. Populations and damage were significantly greater within 200m of the drums and may have been caused by ineffective poisoning or poor quality/overcrowding of fruit resources in the drums. 5 Suppression of Carpophilus spp. populations using synthetic aggregation pheromones and a coattractant appears to be a realistic management option in stone fruit orchards. Pheromone-mediated diversion of beetle populations from ripening fruit may be more practical than perimeter trapping, but more research is needed on the effective range of Carpophilus pheromones and the relative merits of trapping compared to attraction to insecticide-treated areas.

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Predatory insects and spiders are key elements of integrated pest management (IPM) programmes in agricultural crops such as cotton. Management decisions in IPM programmes should to be based on a reliable and efficient method for counting both predators and pests. Knowledge of the temporal constraints that influence sampling is required because arthropod abundance estimates are likely to vary over a growing season and within a day. Few studies have adequately quantified this effect using the beat sheet, a potentially important sampling method. We compared the commonly used methods of suction and visual sampling to the beat sheet, with reference to an absolute cage clamp method for determining the abundance of various arthropod taxa over 5 weeks. There were significantly more entomophagous arthropods recorded using the beat sheet and cage clamp methods than by using suction or visual sampling, and these differences were more pronounced as the plants grew. In a second trial, relative estimates of entomophagous and phytophagous arthropod abundance were made using beat sheet samples collected over a day. Beat sheet estimates of the abundance of only eight of the 43 taxa examined were found to vary significantly over a day. Beat sheet sampling is recommended in further studies of arthropod abundance in cotton, but researchers and pest management advisors should bear in mind the time of season and time of day effects.

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Background: Molecular marker technologies are undergoing a transition from largely serial assays measuring DNA fragment sizes to hybridization-based technologies with high multiplexing levels. Diversity Arrays Technology (DArT) is a hybridization-based technology that is increasingly being adopted by barley researchers. There is a need to integrate the information generated by DArT with previous data produced with gel-based marker technologies. The goal of this study was to build a high-density consensus linkage map from the combined datasets of ten populations, most of which were simultaneously typed with DArT and Simple Sequence Repeat (SSR), Restriction Enzyme Fragment Polymorphism (RFLP) and/or Sequence Tagged Site (STS) markers. Results: The consensus map, built using a combination of JoinMap 3.0 software and several purpose-built perl scripts, comprised 2,935 loci (2,085 DArT, 850 other loci) and spanned 1,161 cM. It contained a total of 1,629 'bins' (unique loci), with an average inter-bin distance of 0.7 ± 1.0 cM (median = 0.3 cM). More than 98% of the map could be covered with a single DArT assay. The arrangement of loci was very similar to, and almost as optimal as, the arrangement of loci in component maps built for individual populations. The locus order of a synthetic map derived from merging the component maps without considering the segregation data was only slightly inferior. The distribution of loci along chromosomes indicated centromeric suppression of recombination in all chromosomes except 5H. DArT markers appeared to have a moderate tendency toward hypomethylated, gene-rich regions in distal chromosome areas. On the average, 14 ± 9 DArT loci were identified within 5 cM on either side of SSR, RFLP or STS loci previously identified as linked to agricultural traits. Conclusion: Our barley consensus map provides a framework for transferring genetic information between different marker systems and for deploying DArT markers in molecular breeding schemes. The study also highlights the need for improved software for building consensus maps from high-density segregation data of multiple populations.

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This paper reports on several studies conducted to better understand the variability between lucerne cultivars and lines, and use this to predict persistence in dryland grazing pastures in eastern Australia. Morphological traits of 20 cultivars/lines were measured in irrigated and dryland spaced plant experiments. Studies were also conducted to describe variation among lucernes in their utilisation of starch and responses to water deficit, pests and diseases. Multiple regression analyses were used to develop simple models where the measured traits could be used to predict persistence of lucerne lines in dryland evaluation experiments. Although there was significant variation among cultivars/lines in most measured traits, no single trait reliably predicted persistence of cultivars/lines in dryland evaluation experiments. However, variation in persistence at both sites could be explained by models developed by multiple regression using differences in the mean lengths of the longest stems at 10% flower in summer and winter. Persistent lucernes were those that had relatively long stems in summer and short stems in winter. Water use efficiencies, starch utilisation patterns and resistances to pests and diseases of different lucernes provided some improvement to this simple model, but these improvements were not consistent.

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An integrated pest management (IPM) approach that relies on an array of tactics is adopted commonly in response to problems with pesticide-based production in many agricultural systems. Host plant resistance is often used as a fundamental component of an IPM system because of the generally compatible, complementary role that pest-resistant crops play with other tactics. Recent research and development in the resistance of legumes and cereals to aphids, sorghum midge resistance, and the resistance of canola varieties to mite and insect pests have shown the prospects of host plant resistance for developing IPM strategies against invertebrate pests in Australian grain crops. Furthermore, continuing advances in biotechnology provide the opportunity of using transgenic plants to enhance host plant resistance in grains.

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To remain competitive, many agricultural systems are now being run along business lines. Systems methodologies are being incorporated, and here evolutionary computation is a valuable tool for identifying more profitable or sustainable solutions. However, agricultural models typically pose some of the more challenging problems for optimisation. This chapter outlines these problems, and then presents a series of three case studies demonstrating how they can be overcome in practice. Firstly, increasingly complex models of Australian livestock enterprises show that evolutionary computation is the only viable optimisation method for these large and difficult problems. On-going research is taking a notably efficient and robust variant, differential evolution, out into real-world systems. Next, models of cropping systems in Australia demonstrate the challenge of dealing with competing objectives, namely maximising farm profit whilst minimising resource degradation. Pareto methods are used to illustrate this trade-off, and these results have proved to be most useful for farm managers in this industry. Finally, land-use planning in the Netherlands demonstrates the size and spatial complexity of real-world problems. Here, GIS-based optimisation techniques are integrated with Pareto methods, producing better solutions which were acceptable to the competing organizations. These three studies all show that evolutionary computation remains the only feasible method for the optimisation of large, complex agricultural problems. An extra benefit is that the resultant population of candidate solutions illustrates trade-offs, and this leads to more informed discussions and better education of the industry decision-makers.

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Specimen-based records of most of the plant pathogens that occur in Australia can be accessed through the Australian Plant Disease Database and the Australian Plant Pest Database. These databases and the herbaria that underpin them are important resources for resolving quarantine and trade issues as well as for the diagnosis of plant diseases. The importance of these collections and databases to Australia's agricultural industries is discussed.