137 resultados para crop pest
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This article reviews research coordinated by the Australian Cotton Cooperative Research Centre (CRC) that investigated production issues for irrigated cotton at five targeted sites in tropical northern Australia, north of 21°S from Broome in Western Australia to the Burdekin in Queensland. The biotic and abiotic issues for cotton production were investigated with the aim of defining the potential limitations and, where appropriate, building a sustainable technical foundation for a future industry if it were to follow. Key lessons from the Cotton CRC research effort were: (1) limitations thought to be associated with cotton production in northern Australia can be overcome by developing a deep understanding of biotic and environmental constraints, then tailoring and validating production practices; and (2) transplanting of southern farming practices without consideration of local pest, soil and climatic factors is unlikely to succeed. Two grower guides were published which synthesised the research for new growers into a rational blueprint for sustainable cotton production in each region. In addition to crop production and environmental impact issues, the project identified the following as key elements needed to establish new cropping regions in tropical Australia: rigorous quantification of suitable land and sustainable water yields; support from governments; a long-term funding model for locally based research; the inclusion of traditional owners; and development of human capacity.
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Extensive resources are allocated to managing vertebrate pests, yet spatial understanding of pest threats, and how they respond to management, is limited at the regional scale where much decision-making is undertaken. We provide regional-scale spatial models and management guidance for European rabbits (Oryctolagus cuniculus) in a 260,791 km(2) region in Australia by determining habitat suitability, habitat susceptibility and the effects of the primary rabbit management options (barrier fence, shooting and baiting and warren ripping) or changing predation or disease control levels. A participatory modelling approach was used to develop a Bayesian network which captured the main drivers of suitability and spread, which in turn was linked spatially to develop high resolution risk maps. Policy-makers, rabbit managers and technical experts were responsible for defining the questions the model needed to address, and for subsequently developing and parameterising the model. Habitat suitability was determined by conditions required for warren-building and by above-ground requirements, such as food and harbour, and habitat susceptibility by the distance from current distributions, habitat suitability, and the costs of traversing habitats of different quality. At least one-third of the region had a high probability of being highly suitable (support high rabbit densities), with the model supported by validation. Habitat susceptibility was largely restricted by the current known rabbit distribution. Warren ripping was the most effective control option as warrens were considered essential for rabbit persistence. The anticipated increase in disease resistance was predicted to increase the probability of moderately suitable habitat becoming highly suitable, but not increase the at-risk area. We demonstrate that it is possible to build spatial models to guide regional-level management of vertebrate pests which use the best available knowledge and capture fine spatial-scale processes.
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Climatic variability in dryland production environments (E) generates variable yield and crop production risks. Optimal combinations of genotype (G) and management (M) depend strongly on E and thus vary among sites and seasons. Traditional crop improvement seeks broadly adapted genotypes to give best average performance under a standard management regime across the entire production region, with some subsequent manipulation of management regionally in response to average local environmental conditions. This process does not search the full spectrum of potential G × M × E combinations forming the adaptation landscape. Here we examine the potential value (relative to the conventional, broad adaptation approach) of exploiting specific adaptation arising from G × M × E. We present an in-silico analysis for sorghum production in Australia using the APSIM sorghum model. Crop design (G × M) is optimised for subsets of locations within the production region (specific adaptation) and is compared with the optimum G across all environments with locally modified M (broad adaptation). We find that geographic subregions that have frequencies of major environment types substantially different from that for the entire production region show greatest advantage for specific adaptation. Although the specific adaptation approach confers yield and production risk advantages at industry scale, even greater benefits should be achievable with better predictors of environment-type likelihood than that conferred by location alone.
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Reducing crop row spacing and delaying time of weed emergence may provide crops a competitive edge over weeds. Field experiments were conducted to evaluate the effects of crop row spacing (11, 15, and 23-cm) and weed emergence time (0, 20, 35, 45, 55, and 60 days after wheat emergence; DAWE) on Galium aparine and Lepidium sativum growth and wheat yield losses. Season-long weed-free and crop-free treatments were also established to compare wheat yield and weed growth, respectively. Row spacing and weed emergence time significantly affected the growth of both weed species and wheat grain yields. For both weed species, the maximum plant height, shoot biomass, and seed production were observed in the crop-free plots, and delayed emergence decreased these variables. In weed-crop competition plots, maximum weed growth was observed when weeds emerged simultaneously with the crop in rows spaced 23-cm apart. Less growth of both weed species was observed in narrow row spacing (11-cm) of wheat as compared with wider rows (15 and 23-cm). These weed species produced less than 5 seeds plant-1 in 11-cm wheat rows when they emerged at 60 DAWE. Presence of weeds in the crop especially at early stages was devastating for wheat yields. Therefore, maximum grain yield (4.91tha-1) was recorded in the weed-free treatment at 11-cm row spacing. Delay in time of weed emergence and narrow row spacing reduced weed growth and seed production and enhanced wheat grain yield, suggesting that these strategies could contribute to weed management in wheat.
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Lower water availability coupled with labor shortage has resulted in the increasing inability of growers to cultivate puddled transplanted rice (PTR). A field study was conducted in the wet season of 2012 and dry season of 2013 to evaluate the performance of five rice establishment methods and four weed control treatments on weed management, and rice yield. Grass weeds were higher in dry-seeded rice (DSR) as compared to PTR and nonpuddled transplanted rice (NPTR). The highest total weed density (225-256plantsm-2) and total weed biomass (315-501gm-2) were recorded in DSR while the lowest (102-129plantsm-2 and 75-387gm-2) in PTR. Compared with the weedy plots, the treatment pretilachlor followed by fenoxaprop plus ethoxysulfuron plus 2,4-D provided excellent weed control. This treatment, however, had a poor performance in NPTR. In both seasons, herbicide efficacy was better in DSR and wet-seeded rice. PTR and DSR produced the maximum rice grain yields. The weed-free plots and herbicide treatments produced 84-614% and 58-504% higher rice grain yield, respectively, than the weedy plots in 2012, and a similar trend was observed in 2013.
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The spot or strip application of poisoned protein bait is a lure-and-kill technique used for the management of fruit flies. Knowledge of where flies occur in the crop environment is an important part of maximizing the efficacy of this tool. Bactrocera tryoni is a polyphagous pest of horticulture for which very little is known about its distribution within crops. With particular reference to edge effects, we monitored the abundance of B. tryoni in two crops of different architecture; strawberry and apple. In strawberries, we found more flies on the crop edge early in the fruiting season, which lessened gradually and eventually disappeared as the season progressed. In apple orchards, no such edge effect was observed and flies were found equally throughout the orchard. We postulated these differences may be due to differences in crop height (high vs. short) and/or crop canopy architecture (opened and branched in apple, dense and closed in strawberry). In a field cage trial, we tested these predictions using artificial plants of different height and canopy condition. Height and canopy structure type had no significant effects on fly oviposition and protein feeding, but the 'apple' type canopy significantly influenced resting. We thus postulate that there was an edge effect in strawberry because the crop was not providing resting sites and flies were doing so in vegetation around the field margins. The finding that B. tryoni shows different resting site preferences based on plant architecture offers the potential for strategic manipulation of the fly through specific border or inter-row plantings. © 2013 Blackwell Verlag GmbH.
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AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.
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NITROUS OXIDE (N2O) IS a potent greenhouse gas and the predominant ozone-depleting substance in the atmosphere. Agricultural nitrogenous fertiliser use is the major source of human-induced N2O emissions. A field experiment was conducted at Bundaberg from October 2012 to September 2014 to examine the impacts of legume crop (soybean) rotation as an alternative nitrogen (N) source on N2O emissions during the fallow period and to investigate low-emission soybean residue management practices. An automatic monitoring system and manual gas sampling chambers were used to measure greenhouse gas emissions from soil. Soybean cropping during the fallow period reduced N2O emissions compared to the bare fallow. Based on the N content in the soybean crop residues, the fertiliser N application rate was reduced by about 120 kg N/ha for the subsequent sugarcane crop. Consequently, emissions of N2O during the sugarcane cropping season were significantly lower from the soybean cropped soil than those from the conventionally fertilised (145 kg N/ha) soil following bare fallow. However, tillage that incorporated the soybean crop residues into soil promoted N2O emissions in the first two months. Spraying a nitrification inhibitor (DMPP) onto the soybean crop residues before tillage effectively prevented the N2O emission spikes. Compared to conventional tillage, practising no-till with or without growing a nitrogen catch crop during the time after soybean harvest and before cane planting also reduced N2O emissions substantially. These results demonstrated that soybean rotation during the fallow period followed with N conservation management practices could offer a promising N2O mitigation strategy in sugarcane farming. Further investigation is required to provide guidance on N and water management following soybean fallow to maintain sugar productivity.
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This guide provides information on how to match nutrient rate to crop needs by varying application rates and timing between blocks, guided by soil tests, crop class, cane variety, soil type, block history, soil conditioners and yield expectations.
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Male fruit fly attractants, cue-lure and methyl eugenol (ME), have been successfully used for the last 50 years in the monitoring and control of Dacini fruit flies (Bactrocera and Dacus species). However, over 50% of Dacini are non-responsive to either lure, including some pest species. A new lure, zingerone, has been found to weakly attract cue- and ME-responsive species in Malaysia. In Australia it attracted a weakly cue-responsive minor pest Bactrocera jarvisi (Tryon) and three non-responsive' species. Similar compounds were tested in Queensland and attracted cue- and ME-responsive species and two non-responsive' species. In this study, 14 novel compounds, including raspberry ketone formate (RKF) (Melolure) and zingerone, were field tested in comparison with cue-lure and ME at 17 sites in north Queensland. The most attractive novel lures were isoeugenol, methyl-isoeugenol, dihydroeugenol and zingerone. Several non-responsive' species responded to the new lures: Bactrocera halfordiae (Tryon), a species of some market access concern, was most attracted to isoeugenol; B.barringtoniae (Tryon), B.bidentata (May) and B.murrayi (Perkins) responded to isoeugenol, methyl-isoeugenol and dihydroeugenol; two new species of Dacus responded to zingerone. Bactrocera kraussi (Hardy), a cue-responsive minor pest in north Queensland, was significantly more attracted to isoeugenol than cue-lure. The cue-responsive D.absonifacies (May) and D.secamoneaeDrew were significantly more attracted to zingerone than cue-lure. Bactrocera yorkensisDrew & Hancock, a ME-responsive species was significantly more attracted to isoeugenol, methyl-isoeugenol and dihydroeugenol than ME. The preferential response to RKF or cue-lure was species specific. Six species were significantly more attracted to RKF, including the pests B.tryoni (Froggatt), B.frauenfeldi (Schiner) and minor pest B.bryoniae (Tryon); eight species were significantly more attracted to cue-lure including the pest B.neohumeralis (Hardy). These findings have significance in the search for optimal male lures for pest species elsewhere in the world.
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Springsure Creek Coal (SCC) intends to develop a coal mine using the long wall mining process under grain farming land near Emerald in Central Queensland (CQ). While this technology will result in some subsidence of the land surface, SCC wishes to maintain productivity of the grain cropping land in the precinct after coal mining. However, the impact of the surface subsidence resulting from that mining process on productivity of cropping land in any Australian landscape is currently unclear. A research protocol to investigate the impacts of subsidence on grain productivity for when the SCC project becomes operational is proposed. The protocol has wider application for other similar mining projects throughout the country. A copy of the full report is accessible on www.aginstitute.com.au.
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Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.
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Management of cucumber fly (Bactrocera cucumis) has relied heavily on cover sprays of broad spectrum insecticides such as dimethoate and fenthion. Long term access to these insecticides is uncertain, and their use can disrupt integrated pest management programs for other pests such as whitefly, aphids and mites. Application of a protein bait spray for fruit fly control is common practice in tree crops. However, vegetable crops present different challenges as fruit flies are thought to enter these crops only to oviposit, spending the majority of their time in roosting sites outside of the cropping area. Perimeter baiting of non-crop vegetation was developed overseas as a technique for control of melon fly (B. cucurbitae) in cucurbits in Hawaii. More recent work has refined the technique further, with certain types of perimeter vegetation proving more attractive to melon fly than the sorghum or corn crops which are commonly utilised. Trials were performed to investigate the potential of developing a similar system for cucumber fly. Commercially available fruit fly baits were compared for attractiveness to cucumber fly. Eight plant species were evaluated for their relative attractiveness to cucumber flies as roosting sites. Differences were observed in the number of flies feeding at protein bait applied to each of the plants. Results are discussed in the context of the development of a perimeter baiting system for cucumber fly in cucurbit crops.