23 resultados para Current account deficit


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Cereal crops can suffer substantial damage if frosts occur at heading. Identification of post-head-emergence frost (PHEF) resistance in cereals poses a number of unique and difficult challenges. Many decades of research have failed to identify genotypes with PHEF resistance that could offer economically significant benefit to growers. Research and breeding gains have been limited by the available screening systems. Using traditional frost screening systems, genotypes that escape frost injury in trials due to spatial temperature differences and/or small differences in phenology can be misidentified as resistant. We believe that by improving techniques to minimize frost escapes, such ofalse-positive' results can be confidently identified and eliminated. Artificial freezing chambers or manipulated natural frost treatments offer many potential advantages but are not yet at the stage where they can be reliably used for frost screening in breeding programmes. Here we describe the development of a novel photoperiod gradient method (PGM) that facilitates screening of genotypes of different phenology under natural field frosts at matched developmental stages. By identifying frost escapes and increasing the efficiency of field screening, the PGM ensures that research effort can be focused on finding genotypes with improved PHEF resistance. To maximize the likelihood of identifying PHEF resistance, we propose that the PGM form part of an integrated strategy to (i) source germplasm;(ii) facilitate high throughput screening; and (iii) permit detailed validation. PGM may also be useful in other studies where either a range of developmental stages and/or synchronized development are desired.

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The results of research into the water relations and irrigation requirements of lychee are collated and reviewed. The stages of plant development are summarised, with an emphasis on factors influencing the flowering process. This is followed by reviews of plant water relations, water requirements, water productivity and, finally, irrigation systems. The lychee tree is native to the rainforests of southern China and northern Vietnam, and the main centres of production remain close to this area. In contrast, much of the research on the water relations of this crop has been conducted in South Africa, Australia and Israel where the tree is relatively new. Vegetative growth occurs in a series of flushes. Terminal inflorescences are borne on current shoot growth under cool (<15 °C), dry conditions. Trees generally do not produce fruit in the tropics at altitudes below 300 m. Poor and erratic flowering results in low and irregular fruit yields. Drought can enhance flowering in locations with dry winters. Roots can extract water from depths greater than 2 m. Diurnal trends in stomatal conductance closely match those of leaf water status. Both variables mirror changes in the saturation deficit of the air. Very little research on crop water requirements has been reported. Crop responses to irrigation are complex. In areas with low rainfall after harvest, a moderate water deficit before floral initiation can increase flowering and yield. In contrast, fruit set and yield can be reduced by a severe water deficit after flowering, and the risk of fruit splitting increased. Water productivity has not been quantified. Supplementary irrigation in South-east Asia is limited by topography and competition for water from the summer rice crop, but irrigation is practised in Israel, South Africa, Australia and some other places. Research is needed to determine the benefits of irrigation in different growing areas. Copyright © Cambridge University Press 2013.

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The Queensland strawberry (Fragaria ×ananassa) breeding program in subtropical Australia aims to improve sustainable profitability for the producer. Selection must account for the relative economic importance of each trait and the genetic architecture underlying these traits in the breeding population. Our study used estimates of the influence of a trait on production costs and profitability to develop a profitability index (PI) and an economic weight (i.e., change in PI for a unit change in level of trait) for each trait. The economic weights were then combined with the breeding values for 12 plant and fruit traits on over 3000 genotypes that were represented in either the current breeding population or as progenitors in the pedigree of these individuals. The resulting linear combination (i.e., sum of economic weight × breeding value for all 12 traits) estimated the overall economic worth of each genotype as H, the aggregate economic genotype. H values were validated by comparisons among commercial cultivars and were also compared with the estimated gross margins. When the H value of ‘Festival’ was set as zero, the H values of genotypes in the pedigree ranged from –0.36 to +0.28. H was highly correlated (R2 = 0.77) with the year of selection (1945–98). The gross margins were highly linearly related (R2 > 0.98) to H values when the genotype was planted on less than 50% of available area, but the relationship was non-linear [quadratic with a maximum (R2 > 0.96)] when the planted area exceeded 50%. Additionally, with H values above zero, the variation in gross margin increased with increasing H values as the percentage of area planted to a genotype increased. High correlations among some traits allowed the omission of any one of three of the 12 traits with little or no effect on ranking (Spearman’s rank correlation 0.98 or greater). Thus, these traits may be dropped from the aggregate economic genotype, leading to either cost reductions in the breeding program or increased selection intensities for the same resources. H was efficient in identifying economically superior genotypes for breeding and deployment, but because of the non-linear relationship with gross margin, calculation of a gross margin for genotypes with high H is also necessary when cultivars are deployed across more than 50% of the available area.

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Common coral trout Plectropomus leopardus is an iconic fish of the Great Barrier Reef (GBR) and is the most important fish for the commercial fishery there. Most of the catch is exported live to Asia. This stock assessment was undertaken in response to falls in catch sizes and catch rates in recent years, in order to gauge the status of the stock. It is the first stock assessment ever conducted of coral trout on the GBR, and brings together a multitude of different data sources for the first time. The GBR is very large and was divided into a regional structure based on the Bioregions defined by expert committees appointed by the Great Barrier Reef Marine Park Authority (GBRMPA) as part of the 2004 rezoning of the GBR. The regional structure consists of six Regions, from the Far Northern Region in the north to the Swains and Capricorn–Bunker Regions in the south. Regions also closely follow the boundaries between Bioregions. Two of the northern Regions are split into Subregions on the basis of potential changes in fishing intensity between the Subregions; there are nine Subregions altogether, which include four Regions that are not split. Bioregions are split into Subbioregions along the Subregion boundaries. Finally, each Subbioregion is split into a “blue” population which is open to fishing and a “green” population which is closed to fishing. The fishery is unusual in that catch rates as an indicator of abundance of coral trout are heavily influenced by tropical cyclones. After a major cyclone, catch rates fall for two to three years, and rebound after that. This effect is well correlated with the times of occurrence of cyclones, and usually occurs in the same month that the cyclone strikes. However, statistical analyses correlating catch rates with cyclone wind energy did not provide significantly different catch rate trends. Alternative indicators of cyclone strength may explain more of the catch rate decline, and future work should investigate this. Another feature of catch rates is the phenomenon of social learning in coral trout populations, whereby when a population of coral trout is fished, individuals quickly learn not to take bait. Then the catch rate falls sharply even when the population size is still high. The social learning may take place by fish directly observing their fellows being hooked, or perhaps heeding a chemo-sensory cue emitted by fish that are hooked. As part of the assessment, analysis of data from replenishment closures of Boult Reef in the Capricorn–Bunker Region (closed 1983–86) and Bramble Reef in the Townsville Subregion (closed 1992–95) estimated a strong social learning effect. A major data source for the stock assessment was the large collection of underwater visual survey (UVS) data collected by divers who counted the coral trout that they sighted. This allowed estimation of the density of coral trout in the different Bioregions (expressed as a number of fish per hectare). Combined with mapping data of all the 3000 or so reefs making up the GBR, the UVS results provided direct estimates of the population size in each Subbioregion. A regional population dynamic model was developed to account for the intricacies of coral trout population dynamics and catch rates. Because the statistical analysis of catch rates did not attribute much of the decline to tropical cyclones, (and thereby implied “real” declines in biomass), and because in contrast the UVS data indicate relatively stable population sizes, model outputs were unduly influenced by the unlikely hypothesis that falling catch rates are real. The alternative hypothesis that UVS data are closer to the mark and declining catch rates are an artefact of spurious (e.g., cyclone impact) effects is much more probable. Judging by the population size estimates provided by the UVS data, there is no biological problem with the status of coral trout stocks. The estimate of the total number of Plectropomus leopardus on blue zones on the GBR in the mid-1980s (the time of the major UVS series) was 5.34 million legal-sized fish, or about 8400 t exploitable biomass, with an 2 additional 3350 t in green zones (using the current zoning which was introduced on 1 July 2004). For the offshore regions favoured by commercial fishers, the figure was about 4.90 million legal-sized fish in blue zones, or about 7700 t exploitable biomass. There is, however, an economic problem, as indicated by relatively low catch rates and anecdotal information provided by commercial fishers. The costs of fishing the GBR by hook and line (the only method compatible with the GBR’s high conservation status) are high, and commercial fishers are unable to operate profitably when catch rates are depressed (e.g., from a tropical cyclone). The economic problem is compounded by the effect of social learning in coral trout, whereby catch rates fall rapidly if fishers keep returning to the same fishing locations. In response, commercial fishers tend to spread out over the GBR, including the Far Northern and Swains Regions which are far from port and incur higher travel costs. The economic problem provides some logic to a reduction in the TACC. Such a reduction during good times, such as when the fishery is rebounding after a major tropical cyclone, could provide a net benefit to the fishery, as it would provide a margin of stock safety and make the fishery more economically robust by providing higher catch rates during subsequent periods of depressed catches. During hard times when catch rates are low (e.g., shortly after a major tropical cyclone), a change to the TACC would have little effect as even a reduced TACC would not come close to being filled. Quota adjustments based on catch rates should take account of long-term trends in order to mitigate variability and cyclone effects in data.

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New Zealand's Greenhouse Gas Inventory (the NZ Inventory) currently estimates methane (CH4) emissions from anaerobic dairy effluent ponds by: (1) determining the total pond volume across New Zealand; (2) dividing this volume by depth to obtain the total pond surface area; and (3) multiplying this area by an observational average CH4 flux. Unfortunately, a mathematically erroneous determination of pond volume has led to an imbalanced equation and a geometry error was made when scaling-up the observational CH4 flux. Furthermore, even if these errors are corrected, the nationwide estimate still hinges on field data from a study that used a debatable method to measure pond CH4 emissions at a single site, as well as a potentially inaccurate estimation of the amount of organic waste anaerobically treated. The development of a new methodology is therefore critically needed.

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Prickly acacia, Vachellia nilotica subsp. indica (syn. Acacia nilotica subsp. indica) (Fabaceae), a major weed in the natural grasslands of western Queensland, has been a target of biological control since the 1980s with limited success to date. Surveys in India, based on genetic and climate matching, identified five insects and two rust pathogens as potential agents. Host-specificity tests were conducted for the insects in India and under quarantine conditions in Australia, and for the rust pathogens under quarantine conditions at CABI in the UK. In no-choice tests, the brown leaf-webber, Phycita sp. A, (Lepidoptera: Pyralidae) completed development on 17 non-target plant species. Though the moth showed a clear preference for prickly acacia in oviposition choice trials screening of additional test-plant species was terminated in view of the potential non-target risk. The scale insect Anomalococcus indicus (Hemiptera: Lecanodiaspididae) developed into mature gravid females on 13 out of 58 non-target plant species tested. In the majority of cases very few female scales matured but development was comparable to that on prickly acacia on four of the non-target species. In multiple choice tests, the scale insect showed a significant preference for the target weed over non-target species tested. In a paired-choice trial under field conditions in India, crawler establishment occurred only on prickly acacia and not on the non-target species tested. Further choice trials are to be conducted under natural field conditions in India. A colony of the green leaf-webber Phycita sp. B has been established in quarantine facilities in Australia and host-specificity testing has commenced. The gall-rust Ravenelia acaciae-arabicae and the leaf-rust Ravenelia evansii (Puccineales: Raveneliaceae) both infected and produced viable urediniospores on Vachellia sutherlandii (Fabaceae), a non-target Australian native plant species. Hence, no further testing with the two rust species was pursued. Inoculation trials using the gall mite Aceria liopeltus (Acari: Eriophyidae) from V. nilotica subsp. kraussiana in South Africa resulted in no gall induction on V. nilotica subsp. indica. Future research will focus on the leaf-weevil Dereodus denticollis (Coleoptera: Curculionidae) and the leaf-beetle Pachnephorus sp. (Coleoptera: Chrysomelidae) under quarantine conditions in Australia. Native range surveys for additional potential biological control agents will also be pursued in northern and western Africa.

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Methane is a potent greenhouse gas with a global warming potential ∼28 times that of carbon dioxide. Consequently, sources and sinks that influence the concentration of methane in the atmosphere are of great interest. In Australia, agriculture is the primary source of anthropogenic methane emissions (60.4% of national emissions, or 3260kt-1methaneyear-1, between 1990 and 2011), and cropping and grazing soils represent Australia's largest potential terrestrial methane sink. As of 2011, the expansion of agricultural soils, which are ∼70% less efficient at consuming methane than undisturbed soils, to 59% of Australia's land mass (456Mha) and increasing livestock densities in northern Australia suggest negative implications for national methane flux. Plant biomass burning does not appear to have long-term negative effects on methane flux unless soils are converted for agricultural purposes. Rice cultivation contributes marginally to national methane emissions and this fluctuates depending on water availability. Significant available research into biological, geochemical and agronomic factors has been pertinent for developing effective methane mitigation strategies. We discuss methane-flux feedback mechanisms in relation to climate change drivers such as temperature, atmospheric carbon dioxide and methane concentrations, precipitation and extreme weather events. Future research should focus on quantifying the role of Australian cropping and grazing soils as methane sinks in the national methane budget, linking biodiversity and activity of methane-cycling microbes to environmental factors, and quantifying how a combination of climate change drivers will affect total methane flux in these systems.