933 resultados para SLIM-TREES


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Capsicum chlorosis virus (CaCV) was detected in field grown Capsicum annuum from Kununurra in northeast Western Australia. Identification of the Kununurra isolate (WA-99) was confirmed using sap transmission to indicator hosts, positive reactions with tospovirus serogroup IV-specific antibodies and CaCV-specific primers, and amino acid sequence comparisons that showed >97% identity with published CaCV nucleocapsid gene sequences. The reactions of indicator hosts to infection with WA-99 often differed from those of the type isolate from Queensland. The virus multiplied best when test plants were grown at warm temperatures. CaCV was not detected in samples collected in a survey of C. annuum crops planted in the Perth Metropolitan area.

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Carrot was confirmed as a new natural and experimental host of Watermelon mosaic virus by serology, host reactions and sequence comparisons of the coat protein.

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Table beet production in the Lockyer Valley of south-eastern Queensland is known to be adversely affected by soilborne root disease from infection by Pythium spp. However, little is known regarding the species or genotypes that are the causal agents of both pre- and post-emergence damping off. Based on RFLP analysis with HhaI, HinfI and MboI of the PCR amplified ITS region DNA from soil and diseased plant samples, the majority of 130 Pythium isolates could be grouped into three genotypes, designated LVP A, LVP B and LVP C. These groups comprised 43, 41 and 7% of all isolates, respectively. Deoxyribonucleic acid sequence analysis of the ITS region indicated that LVP A was a strain of Pythium aphanidermatum, with greater than 99% similarity to the corresponding P. aphanidermatum sequences from the publicly accessible databases. The DNA sequences from LVP B and LVP C were most closely related to P. ultimum and P. dissotocum, respectively. Lower frequencies of other distinct isolates with unique RFLP patterns were also obtained with high levels of similarity (>97%) to P. heterothallicum, P. periplocum and genotypes of P. ultimum other than LVP B. Inoculation trials of 1- and 4-week-old beet seedlings indicated that compared with isolates of the LVP B genotype, a higher frequency of LVP A isolates caused disease. Isolates with the LVP A, LVP B and LVP C genotypes were highly sensitive to the fungicide Ridomil MZ, which suppressed radial growth on V8 agar between approximately four and thirty fold at 5 μg/mL metalaxyl and 40 μg/mL mancozeb, a concentration far lower than the recommended field application rate.

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Strawberry lethal yellows (SLY) disease in Australia is associated with the phytoplasmas Candidatus Phytoplasma australiense and tomato big bud, and a rickettsia-like-organism (RLO). Ca. P. australiense is also associated with strawberry green petal (SGP) disease. This study investigated the strength of the association of the different agents with SLY disease. We also documented the location of SLY or SGP plants, and measured whether they were RLO or phytoplasma positive. Symptomatic strawberry plants collected from south-east Queensland (Australia) between January 2000 and October 2002 were screened by PCR for both phytoplasmas and the RLO. Two previously unreported disease symptoms termed severe fruit distortion (SFD) and strawberry leaves from fruit (SLF) were observed during this study but there was no clear association between these symptoms and phytoplasmas or the RLO. Only two SGP diseased plants were observed and collected, compared with 363 plants with SLY disease symptoms. Of the 363 SLY samples, 117 tested positive for the RLO, 67 tested positive for Ca. P. australiense AGY strain and 11 plants tested positive for Ca. P. australiense PYL variant strain. On runner production farms at Stanthorpe, Queensland the RLO was detected in SLY diseased plants more frequently than for the phytoplasmas. On fruit production farms on the Sunshine Coast, Queensland, Ca. P. australiense was detected in SLY disease plants more frequently than the RLO.

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In recent years, dieback of durian has become a major problem in mature orchards in the northern Queensland wet tropics region. A survey of 13 durian orchards was conducted during the dry season (July-September 2001) and following wet season (February-April 2002), with roots and soil from the root zone of affected trees being sampled. Phytophthora palmivora was recovered from the roots of affected trees on 12 of the 13 farms in the dry season, and all farms in the wet season. Pythium vexans was recovered from all 13 farms in both seasons. P. palmivora and P. vexans were recovered from diseased roots of 3-month-old durian seedlings cv. Monthong artificially inoculated with these organisms.

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A detached-leaf bioassay was developed and used to screen five durian (Durio zibethinus) cultivars against Phytophthora palmivora isolates from a trunk canker, root and fruit. The fruit isolate was less aggressive than the canker and root isolates. The bioassay using the canker isolate was later used to determine the variation in resistance of D. macarantha and nineteen cultivars of D. zibethinus. The cultivars displayed a range of responses with Parung and Gob being most tolerant, with Gaan Yaow, Chanee and Penang 88 being susceptible. The remaining germplasm fell between Gaan Yaow and Penang 88 in susceptibility. The leaf bioassay was found to be a rapid and reliable method for assessing the susceptibility of durian cultivars.

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Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.

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The potential of beef producers to profitably produce 500-kg steers at 2.5 years of age in northern Australia's dry tropics to meet specifications of high-value markets, using a high-input management (HIM) system was examined. HIM included targeted high levels of fortified molasses supplementation, short seasonal mating and the use of growth promotants. Using herds of 300-400 females plus steer progeny at three sites, HIM was compared at a business level to prevailing best-practice, strategic low-input management (SLIM) in which there is a relatively low usage of energy concentrates to supplement pasture intake. The data presented for each breeding-age cohort within management system at each site includes: annual pregnancy rates (range: 14-99%), time of conception, mortalities (range: 0-10%), progeny losses between confirmed pregnancy and weaning (range: 0-29%), and weaning rates (range: 14-92%) over the 2-year observation. Annual changes in weight and relative net worth were calculated for all breeding and non-breeding cohorts. Reasons for outcomes are discussed. Compared with SLIM herds, both weaning weights and annual growth were >= 30 kg higher, enabling 86-100% of HIM steers to exceed 500 kg at 2.5 years of age. Very few contemporary SLIM steers reached this target. HIM was most profitably applied to steers. Where HIM was able to achieve high pregnancy rates in yearlings, its application was recommended in females. Well managed, appropriate HIM systems increased profits by around $15/adult equivalent at prevailing beef and supplement prices. However, a 20% supplement price rise without a commensurate increase in values for young slaughter steers would generally eliminate this advantage. This study demonstrated the complexity of pro. table application of research outcomes to commercial business, even when component research suggests that specific strategies may increase growth and reproductive efficiency and/or be more pro. table. Because of the higher level of management required, higher costs and returns, and higher susceptibility to market changes and disease, HIM systems should only be applied after SLIM systems are well developed. To increase profitability, any strategy must ultimately either increase steer growth and sale values and/or enable a shift to high pregnancy rates in yearling heifers.

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To improve compatibility between chemical and biological controls, the use of selective insecticides such as insect growth regulators (IGRs) is crucial. In cucurbits, the use of pyriproxyfen (an IGR) has been shown by others to be an effective method of reducing the number of sap-sucking insects, especially silverleaf whitefly, Bemisia tabaci (Gennadius) Biotype B (SLW). Therefore, we compared pyriproxyfen and buprofezin (an IGR) with that of no treatment (control) in a bitter melon crop for the control of populations of SLW and for their effects on fruit production. Pyriproxyfen controlled SLW and tended to have heavier fruits than the control treatment and reduced the abundance of nymphs and exuvia. Buprofezin showed no evidence in controlling SLW compared with the pyriproxyfen and control treatments. Neither pyriproxyfen nor buprofezin had any effect on the number of harvested fruit or overall fruit yield, but the average weight per fruit was higher than the control treatment. Pyriproxyfen was effective in controlling whitefly populations in bitter melons, and both pyriproxyfen and buprofezin may have the potential to increase yield. Their longer-term use may increase predation by natural enemies as they are species-specific and could favour build up of natural enemies of SLW. Thus, the judicious use of pyriproxyfen may provide an effective alternative to broad-spectrum insecticides in small-scale cucurbit production.

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Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.

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The emerging carbon economy will have a major impact on grazing businesses because of significant livestock methane and land-use change emissions. Livestock methane emissions alone account for similar to 11% of Australia's reported greenhouse gas emissions. Grazing businesses need to develop an understanding of their greenhouse gas impact and be able to assess the impact of alternative management options. This paper attempts to generate a greenhouse gas budget for two scenarios using a spread sheet model. The first scenario was based on one land-type '20-year-old brigalow regrowth' in the brigalow bioregion of southern-central Queensland. The 50 year analysis demonstrated the substantially different greenhouse gas outcomes and livestock carrying capacity for three alternative regrowth management options: retain regrowth (sequester 71.5 t carbon dioxide equivalents per hectare, CO2-e/ha), clear all regrowth (emit 42.8 t CO2-e/ha) and clear regrowth strips (emit 5.8 t CO2-e/ha). The second scenario was based on a 'remnant eucalypt savanna-woodland' land type in the Einasleigh Uplands bioregion of north Queensland. The four alternative vegetation management options were: retain current woodland structure (emit 7.4 t CO2-e/ha), allow woodland to thicken increasing tree basal area (sequester 20.7 t CO2-e/ha), thin trees less than 10 cm diameter (emit 8.9 t CO2-e/ha), and thin trees <20 cm diameter (emit 12.4 t CO2-e/ha). Significant assumptions were required to complete the budgets due to gaps in current knowledge on the response of woody vegetation, soil carbon and non-CO2 soil emissions to management options and land-type at the property scale. The analyses indicate that there is scope for grazing businesses to choose alternative management options to influence their greenhouse gas budget. However, a key assumption is that accumulation of carbon or avoidance of emissions somewhere on a grazing business (e.g. in woody vegetation or soil) will be recognised as an offset for emissions elsewhere in the business (e.g. livestock methane). This issue will be a challenge for livestock industries and policy makers to work through in the coming years.

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Grazing is a major land use in Australia's rangelands. The 'safe' livestock carrying capacity (LCC) required to maintain resource condition is strongly dependent on climate. We reviewed: the approaches for quantifying LCC; current trends in climate and their effect on components of the grazing system; implications of the 'best estimates' of climate change projections for LCC; the agreement and disagreement between the current trends and projections; and the adequacy of current models of forage production in simulating the impact of climate change. We report the results of a sensitivity study of climate change impacts on forage production across the rangelands, and we discuss the more general issues facing grazing enterprises associated with climate change, such as 'known uncertainties' and adaptation responses (e.g. use of climate risk assessment). We found that the method of quantifying LCC from a combination of estimates (simulations) of long-term (>30 years) forage production and successful grazier experience has been well tested across northern Australian rangelands with different climatic regions. This methodology provides a sound base for the assessment of climate change impacts, even though there are many identified gaps in knowledge. The evaluation of current trends indicated substantial differences in the trends of annual rainfall (and simulated forage production) across Australian rangelands with general increases in most of western Australian rangelands ( including northern regions of the Northern Territory) and decreases in eastern Australian rangelands and south-western Western Australia. Some of the projected changes in rainfall and temperature appear small compared with year-to-year variability. Nevertheless, the impacts on rangeland production systems are expected to be important in terms of required managerial and enterprise adaptations. Some important aspects of climate systems science remain unresolved, and we suggest that a risk-averse approach to rangeland management, based on the 'best estimate' projections, in combination with appropriate responses to short-term (1-5 years) climate variability, would reduce the risk of resource degradation. Climate change projections - including changes in rainfall, temperature, carbon dioxide and other climatic variables - if realised, are likely to affect forage and animal production, and ecosystem functioning. The major known uncertainties in quantifying climate change impacts are: (i) carbon dioxide effects on forage production, quality, nutrient cycling and competition between life forms (e.g. grass, shrubs and trees); and (ii) the future role of woody plants including effects of. re, climatic extremes and management for carbon storage. In a simple example of simulating climate change impacts on forage production, we found that increased temperature (3 degrees C) was likely to result in a decrease in forage production for most rangeland locations (e. g. -21% calculated as an unweighted average across 90 locations). The increase in temperature exacerbated or reduced the effects of a 10% decrease/increase in rainfall respectively (-33% or -9%). Estimates of the beneficial effects of increased CO2 (from 350 to 650 ppm) on forage production and water use efficiency indicated enhanced forage production (+26%). The increase was approximately equivalent to the decline in forage production associated with a 3 degrees C temperature increase. The large magnitude of these opposing effects emphasised the importance of the uncertainties in quantifying the impacts of these components of climate change. We anticipate decreases in LCC given that the 'best estimate' of climate change across the rangelands is for a decline (or little change) in rainfall and an increase in temperature. As a consequence, we suggest that public policy have regard for: the implications for livestock enterprises, regional communities, potential resource damage, animal welfare and human distress. However, the capability to quantify these warnings is yet to be developed and this important task remains as a challenge for rangeland and climate systems science.

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Fiji leaf gall, caused the Fiji disease virus (genus Fijivirus, family Reoviridae, FDV), is a serious disease of sugarcane, Saccharum officinarum L., in Australia and several other Asia-Pacific countries. In Australia FDV is transmitted only by the planthopper Perkinsiella saccharicida Kirkaldy (Hemiptera: Delphacidae), in a propagative manner. Successful transmission of FDV by single planthoppers confined to individual virus free plants is highly variable, even under controlled conditions. The research reported here addresses two possible sources of this variation: 1) gender, wing form, and life stage of the planthopper; and 2) genotype of the source plant. The acquisition of FDV by macropterous males, macropterous females, brachypterous females, and nymphs of P. saccharicida from infected plants was investigated using reverse transcription-polymerase chain reaction to diagnose FDV infection in the vector. The proportion of individuals infected with FDV was not statistically related to life stage, gender, or adult wing form of the vector. The acquisition of FDV by P. saccharicida from four cultivars of sugarcane was compared to assess the influence of plant genotype on acquisition. Those planthopper populations reared on diseased 'NCo310' plants had twice as many infected planthoppers as those reared on 'Q110', 'WD1', and 'WD2'. Therefore, variation in FDV acquisition in this system is not the result of variation in the gender, wing form and life stage of the P. saccharicida vectors. The cultivar used as the source plant to rear vector populations does affect the proportion of infected planthoppers in a population.

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Stephen Setter, Melissa Setter, Michael Graham and Joe Vitelli recently published their paper 'Buoyancy and germination of pond apple (Annona glabra L.) propagules in fresh and salt water' in Proceedings of the 16th Australian Weeds Conference. Stephen also presented this paper at the conference. Pond apple is an aggressive woody weed which has invaded many wetlands, drainage lines and riparian systems across the Wet Tropics bioregion of Far North Queensland. Most fruit and seed produced by pond apple during the summer wet season fall directly into creeks, river banks, flood plains and swamps from where they are dispersed. They reported that pond apple seeds can float for up to 12 months in either fresh or salt water, with approximately 38% of these seeds germinating in a soil medium once removed from the experimental water tanks at South Johnstone. Their study suggested that the removal of reproductive trees from areas adjacent to creeks and rivers will have an immediate impact on potential spread of pond apple by limiting seed input into flowing water bodies.

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The efficacy of insecticides in controlling Sceliodes cordalis, eggfruit caterpillar, in eggplant was tested in four small plot trials because there has been a very limited range of insecticides available to manage this pest. Weekly applications of bifenthrin, flubendiamide, methoxyfenozide, chlorantraniliprole and spinosad and twice weekly applications of methomyl provided control as measured by a percentage of damaged fruit significantly lower than that in an untreated control. Twice weekly applications of methoxyfenozide, chlorantraniliprole or spinosad were not significantly more effective than weekly applications. Bacillus thuringiensis kurstaki, emamectin benzoate, indoxacarb, methomyl and pyridalyl applied weekly were ineffective, with percentages of damaged fruit not significantly different from the untreated control. These trials have identified a number of insecticides that could be used to manage S. cordalis, including several that would be compatible with integrated pest management programs in eggplant.