3 resultados para IGBTs in parallel

em eResearch Archive - Queensland Department of Agriculture


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As failure to control Rhyzopertha dominica (F.) with phosphine is a common problem in the grain-growing regions of Brazil, a study was undertaken to investigate the frequency, distribution and strength of phosphine resistance in R. dominica in Brazil. Nineteen samples of R. dominica were collected between 1991 and 2003 from central storages where phosphine fumigation had failed to control this species. Insects were cultured without selection until testing in 2005. Each sample was tested for resistance to phosphine on the basis of the response of adults to discriminating concentrations of phosphine (20 and 48 h exposures) and full dose-response assays (48 h exposure). Responses of the Brazilian R. dominica samples were compared with reference susceptible, weak-resistance and strong-resistance strains from Australia in parallel assays. All Brazilian population samples showed resistance to phosphine: five were diagnosed with weak resistance and 14 with strong resistance. Five samples showed levels of resistance similar to the reference strong-resistance strain. A representative highly resistant sample was characterised by exposing mixed-age cultures to a range of constant concentrations of phosphine for various exposure periods. Time to population extinction (TPE) and time to 99.9% suppression of population (LT99.9) values of this sample were generally similar to those of the reference strong-resistance strain. For example, at 0.1, 0.5 and 1.0 mg L-1, LT99.9 values for BR33 and the reference strong-resistance strain were respectively 21, 6.4 and 3.7 days and 17, 6.2 and 3.8 days. With both strains, doubling phosphine concentrations to 2 mg L -1 resulted in increased LT99.9 and TPE. High level and frequency of resistance in all population samples, some of which had been cultured without selection for up to 12 years, suggest little or no fitness deficit associated with phosphine resistance. The present research indicates that widespread phosphine resistance may be developing in Brazil. Fumigation practices should be monitored and resistance management plans implemented to alleviate further resistance development.

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The variation in liveweight gain in grazing beef cattle as influenced by pasture type, season and year effects has important economic implications for mixed crop-livestock systems and the ability to better predict such variation would benefit beef producers by providing a guide for decision making. To identify key determinants of liveweight change of Brahman-cross steers grazing subtropical pastures, measurements of pasture quality and quantity, and diet quality in parallel with liveweight were made over two consecutive grazing seasons (48 and 46 weeks, respectively), on mixed Clitoria ternatea/grass, Stylosanthes seabrana/grass and grass swards (grass being a mixture of Bothriochloa insculpta cv. Bisset, Dichanthium sericeum and Panicum maximum var. trichoglume cv. Petrie). Steers grazing the legume-based pastures had the highest growth rate and gained between 64 and 142 kg more than those grazing the grass pastures in under 12 months. Using an exponential model, green leaf mass, green leaf %, adjusted green leaf % (adjusted for inedible woody legume stems), faecal near infrared reflectance spectroscopy predictions of diet crude protein and diet dry matter digestibility, accounted for 77, 74, 80, 63 and 60%, respectively, of the variation in daily weight gain when data were pooled across pasture types and grazing seasons. The standard error of the regressions indicated that 95% prediction intervals were large (+/- 0.42-0.64 kg/head.day) suggesting that derived regression relationships have limited practical application for accurately estimating growth rate. In this study, animal factors, especially compensatory growth effects, appeared to have a major influence on growth rate in relation to pasture and diet attributes. It was concluded that predictions of growth rate based only on pasture or diet attributes are unlikely to be accurate or reliable. Nevertheless, key pasture attributes such as green leaf mass and green leaf% provide a robust indication of what proportion of the potential growth rate of the grazing animals can be achieved.

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Crop models are simplified mathematical representations of the interacting biological and environmental components of the dynamic soil–plant–environment system. Sorghum crop modeling has evolved in parallel with crop modeling capability in general, since its origins in the 1960s and 1970s. Here we briefly review the trajectory in sorghum crop modeling leading to the development of advanced models. We then (i) overview the structure and function of the sorghum model in the Agricultural Production System sIMulator (APSIM) to exemplify advanced modeling concepts that suit both agronomic and breeding applications, (ii) review an example of use of sorghum modeling in supporting agronomic management decisions, (iii) review an example of the use of sorghum modeling in plant breeding, and (iv) consider implications for future roles of sorghum crop modeling. Modeling and simulation provide an avenue to explore consequences of crop management decision options in situations confronted with risks associated with seasonal climate uncertainties. Here we consider the possibility of manipulating planting configuration and density in sorghum as a means to manipulate the productivity–risk trade-off. A simulation analysis of decision options is presented and avenues for its use with decision-makers discussed. Modeling and simulation also provide opportunities to improve breeding efficiency by either dissecting complex traits to more amenable targets for genetics and breeding, or by trait evaluation via phenotypic prediction in target production regions to help prioritize effort and assess breeding strategies. Here we consider studies on the stay-green trait in sorghum, which confers yield advantage in water-limited situations, to exemplify both aspects. The possible future roles of sorghum modeling in agronomy and breeding are discussed as are opportunities related to their synergistic interaction. The potential to add significant value to the revolution in plant breeding associated with genomic technologies is identified as the new modeling frontier.