257 resultados para grain production


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Characterization of drought environment types (ETs) has proven useful for breeding crops for drought-prone regions. Here we consider how changes in climate and atmospheric carbon dioxide (CO2) concentrations will affect drought ET frequencies in sorghum and wheat systems of Northeast Australia. We also modify APSIM (the Agricultural Production Systems Simulator) to incorporate extreme heat effects on grain number and weight, and then evaluate changes in the occurrence of heat-induced yield losses of more than 10%, as well as the co-occurrence of drought and heat. More than six million simulations spanning representative locations, soil types, management systems, and 33 climate projections led to three key findings. First, the projected frequency of drought decreased slightly for most climate projections for both sorghum and wheat, but for different reasons. In sorghum, warming exacerbated drought stresses by raising the atmospheric vapor pressure deficit and reducing transpiration efficiency (TE), but an increase in TE due to elevated CO2 more than offset these effects. In wheat, warming reduced drought stress during spring by hastening development through winter and reducing exposure to terminal drought. Elevated CO2 increased TE but also raised radiation use efficiency and overall growth rates and water use, thereby offsetting much of the drought reduction from warming. Second, adding explicit effects of heat on grain number and grain size often switched projected yield impacts from positive to negative. Finally, although average yield losses associated with drought will remain generally higher than for heat stress for the next half century, the relative importance of heat is steadily growing. This trend, as well as the likely high degree of genetic variability in heat tolerance, suggests that more emphasis on heat tolerance is warranted in breeding programs. At the same time, work on drought tolerance should continue with an emphasis on drought that co-occurs with extreme heat. This article is protected by copyright. All rights reserved.

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This project describes how Streptococcus agalactiae can be transmitted experimentally in Queensland grouper. The implications of this research furthers the relatedness between Australian S. agalactiae strains from animals and humans. Additionally, this research has developed diagnostic tools for Australian State Veterinary Laboratories and Universities, which will assist in State and National aquatic animal disease detection, surveillance, disease monitoring and reporting

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Abstract: Although mainly grown for its sweet flavoured fruit, papaya (Carica papaya) has also been used for pharmacological purposes for many years. The reasons for use are varied with one of the best known being its anti-fungal action. Benzyl isothiocyanate (BITC) is the constituent most often implicated in this activity. Isothiocyanates are formed when the enzyme myrosinase catalyses the hydrolysis of the non-bioactive glucosinolates. This occurs when cellular contents come into contact through chewing, cutting or during extraction processes in the laboratory. While this is common in Brassica vegetables, the glucosinolate-myrosinase system is rare in fruit, papaya being a notable exception. It contains benzyl glucosinolate (BG), the glucosinolate precursor of BITC, in significant quantities. Parameters that determine the amount of BITC formed are duration of hydrolysis, presence/absence of nitrile-specifier proteins and BG content of different cultivars and tissues. We experimented with differing BITC extraction solvents, with the intention of developing a low cost, natural anti-fungal extract based on under-utilised papaya tissues. The findings suggest that papaya seeds, particularly from quarter-ripe fruit, have the potential to produce the highest levels of BITC necessary. Furthermore, they compare well with the nitrile-specifier protein-containing garden cress seeds (Lepidium sativum). To utilise the papaya seeds as a BITC source, an organic solvent such as ethanol is required to extract the largely water-insoluble BITC from the hydrolysed papaya seed mixture.

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Spot measurements of methane emission rate (n = 18 700) by 24 Angus steers fed mixed rations from GrowSafe feeders were made over 3- to 6-min periods by a GreenFeed emission monitoring (GEM) unit. The data were analysed to estimate daily methane production (DMP; g/day) and derived methane yield (MY; g/kg dry matter intake (DMI)). A one-compartment dose model of spot emission rate v. time since the preceding meal was compared with the models of Wood (1967) and Dijkstra et al. (1997) and the average of spot measures. Fitted values for DMP were calculated from the area under the curves. Two methods of relating methane and feed intakes were then studied: the classical calculation of MY as DMP/DMI (kg/day); and a novel method of estimating DMP from time and size of preceding meals using either the data for only the two meals preceding a spot measurement, or all meals for 3 days prior. Two approaches were also used to estimate DMP from spot measurements: fitting of splines on a 'per-animal per-day' basis and an alternate approach of modelling DMP after each feed event by least squares (using Solver), summing (for each animal) the contributions from each feed event by best-fitting a one-compartment model. Time since the preceding meal was of limited value in estimating DMP. Even when the meal sizes and time intervals between a spot measurement and all feeding events in the previous 72 h were assessed, only 16.9% of the variance in spot emission rate measured by GEM was explained by this feeding information. While using the preceding meal alone gave a biased (underestimate) of DMP, allowing for a longer feed history removed this bias. A power analysis taking into account the sources of variation in DMP indicated that to obtain an estimate of DMP with a 95% confidence interval within 5% of the observed 64 days mean of spot measures would require 40 animals measured over 45 days (two spot measurements per day) or 30 animals measured over 55 days. These numbers suggest that spot measurements could be made in association with feed efficiency tests made over 70 days. Spot measurements of enteric emissions can be used to define DMP but the number of animals and samples are larger than are needed when day-long measures are made.

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Exotic plant pests (EPPs) threaten production, market access and sustainability of Australian plant production systems. For the grains industry there are over 600 identified EPPs of which 54 are considered high priority, posing a significant threat. Despite Australia’s geographical isolation and strong quarantine systems, the threat from EPPs has never been higher with the increasing levels of travel and trade, emphasising the need for improving our efforts in prevention, preparedness and surveillance for EPPs.

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Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

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Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

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The methods for estimating methane emissions from cattle as used in the Australian national inventory are based on older data that have now been superseded by a large amount of more recent data. Recent data suggested that the current inventory emissions estimates can be improved. To address this issue, a total of 1034 individual animal records of daily methane production (MP) was used to reassess the relationship between MP and each of dry matter intake (DMI) and gross energy intake (GEI). Data were restricted to trials conducted in the past 10 years using open-circuit respiration chambers, with cattle fed forage-based diets (forage >70%). Results from diets considered to inhibit methanogenesis were omitted from the dataset. Records were obtained from dairy cattle fed temperate forages (220 records), beef cattle fed temperate forages (680 records) and beef cattle fed tropical forages (133 records). Relationships were very similar for all three production categories and single relationships for MP on a DMI or GEI basis were proposed for national inventory purposes. These relationships were MP (g/day) = 20.7 (±0.28) × DMI (kg/day) (R2 = 0.92, P < 0.001) and MP (MJ/day) = 0.063 (±0.008) × GEI (MJ/day) (R2 = 0.93, P < 0.001). If the revised MP (g/day) approach is used to calculate Australia’s national inventory, it will reduce estimates of emissions of forage-fed cattle by 24%. Assuming a global warming potential of 25 for methane, this represents a 12.6 Mt CO2-e reduction in calculated annual emissions from Australian cattle.

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With the aim of increasing peanut production in Australia, the Australian peanut industry has recently considered growing peanuts in rotation with maize at Katherine in the Northern Territory—a location with a semi-arid tropical climate and surplus irrigation capacity. We used the well-validated APSIM model to examine potential agronomic benefits and long-term risks of this strategy under the current and warmer climates of the new region. Yield of the two crops, irrigation requirement, total soil organic carbon (SOC), nitrogen (N) losses and greenhouse gas (GHG) emissions were simulated. Sixteen climate stressors were used; these were generated by using global climate models ECHAM5, GFDL2.1, GFDL2.0 and MRIGCM232 with a median sensitivity under two Special Report of Emissions Scenarios over the 2030 and 2050 timeframes plus current climate (baseline) for Katherine. Effects were compared at three levels of irrigation and three levels of N fertiliser applied to maize grown in rotations of wet-season peanut and dry-season maize (WPDM), and wet-season maize and dry-season peanut (WMDP). The climate stressors projected average temperature increases of 1°C to 2.8°C in the dry (baseline 24.4°C) and wet (baseline 29.5°C) seasons for the 2030 and 2050 timeframes, respectively. Increased temperature caused a reduction in yield of both crops in both rotations. However, the overall yield advantage of WPDM increased from 41% to up to 53% compared with the industry-preferred sequence of WMDP under the worst climate projection. Increased temperature increased the irrigation requirement by up to 11% in WPDM, but caused a smaller reduction in total SOC accumulation and smaller increases in N losses and GHG emission compared with WMDP. We conclude that although increased temperature will reduce productivity and total SOC accumulation, and increase N losses and GHG emissions in Katherine or similar northern Australian environments, the WPDM sequence should be preferable over the industry-preferred sequence because of its overall yield and sustainability advantages in warmer climates. Any limitations of irrigation resulting from climate change could, however, limit these advantages.

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Sorghum (Sorghum bicolor) is one of the most important cereal crops globally and a potential energy plant for biofuel production. In order to explore genetic gain for a range of important quantitative traits, such as drought and heat tolerance, grain yield, stem sugar accumulation, and biomass production, via the use of molecular breeding and genomic selection strategies, knowledge of the available genetic variation and the underlying sequence polymorphisms, is required.

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There is uncertainty over the potential changes to rainfall across northern Australia under climate change. Since rainfall is a key driver of pasture growth, cattle numbers and the resulting animal productivity and beef business profitability, the ability to anticipate possible management strategies within such uncertainty is crucial. The Climate Savvy Grazing project used existing research, expert knowledge and computer modelling to explore the best-bet management strategies within best, median and worse-case future climate scenarios. All three scenarios indicated changes to the environment and resources upon which the grazing industry of northern Australia depends. Well-adapted management strategies under a changing climate are very similar to best practice within current climatic conditions. Maintaining good land condition builds resource resilience, maximises opportunities under higher rainfall years and reduces the risk of degradation during drought and failed wet seasons. Matching stocking rate to the safe long-term carrying capacity of the land is essential; reducing stock numbers in response to poor seasons and conservatively increasing stock numbers in response to better seasons generally improves profitability and maintains land in good condition. Spelling over the summer growing season will improve land condition under a changing climate as it does under current conditions. Six regions were included within the project. Of these, the Victoria River District in the Northern Territory, Gulf country of Queensland and the Kimberley region of Western Australia had projections of similar or higher than current rainfall and the potential for carrying capacity to increase. The Alice Springs, Maranoa-Balonne and Fitzroy regions had projections of generally drying conditions and the greatest risk of reduced pasture growth and carrying capacity. Encouraging producers to consider and act on the risks, opportunities and management options inherent in climate change was a key goal of the project. More than 60,000 beef producers, advisors and stakeholders are now more aware of the management strategies which build resource resilience, and that resilience helps buffer against the effects of variable and changing climatic conditions. Over 700 producers have stated they have improved confidence, skills and knowledge to attempt new practices to build resilience. During the course of the project, more than 165 beef producers reported they have implemented changes to build resource and business resilience.

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Queensland fruit flies Bactrocera tryoni and B. neohumeralis are considered major quarantine pests of tomato, a major crop in the horticultural production district around Bowen, North Queensland, Australia. Preharvest and/or postharvest treatments are required to meet the market access requirements of both domestic and international trading partners. The suspension from use of dimethoate and fenthion, the two insecticides used for fruit fly control, has resulted in the loss of both pre and postharvest uses in fresh tomato. Research undertaken quantitatively at Bowen evaluated the effectiveness of pre-harvest production systems without specific fruit fly controls and postharvest mitigation measures in reducing the risk of fruit fly infestation in tomato. A district-wide trapping using cue-lure baited traps was undertaken to determine fruit fly seasonal patterns in relation to the cropping seasons. A total of 17,626 field-harvested and 11,755 pack-house tomatoes were sampled from ten farms over three cropping seasons (2006-2009). The fruit were incubated and examined for fruit fly infestation. No fruit fly infested fruit were recorded over the three seasons in either the field or the pack-house samples. Statistical analyses showed that upper infestation levels were extremely low (between 0.025 and 0.062%) at the 95% confidence level. The trap catches showed a seasonal pattern in fruit fly activity, with low numbers during the autumn and winter months, rising slightly in spring and peaking in summer. This seasonal pattern was similar over the four seasons. The main two species of fruit fly caught were B. tryoni and B. neohumeralis. Based on the results, it is clear that the risk of fruit fly infestation is extremely low under the current production systems in the Bowen region.

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This project has for the first time demonstrated the feasibility of hatchery production of jungle perch fingerlings. The research on jungle perch production has enabled a hatchery production manual with accompanying videos to be produced. This has given private commercial hatcheries the information needed to produce jungle perch fingerlings. Several hatcheries have already indicated an interest in producing jungle perch and will be assisted to do so in 2016. Currently jungle perch are not a permitted stocking species, so cannot be sold to fish stocking groups. However, hatcheries will be able to sell fingerlings to the aquarium trade or supply grow out facilities that could produce jungle perch for human consumption. Should jungle perch become a permitted species for stocking, this will provide hatcheries with a major new product option to sell to fish stocking groups. It would also benefit anglers by providing another iconic species for impoundment stocking programs. This could have flow-on benefits to regional economies through angler tourism. Should the pilot reintroductions of jungle perch into streams result in self-sustaining jungle perch populations, then there will be three restored jungle perch populations close to major population centres. This will create a new opportunity for anglers not normally able to target jungle perch. Since the majority of anglers who target jungle perch are catch and release fishers, angling is expected to have minimal impact on recovery of the populations. This project led to the development of a hatchery manual for jungle perch production and to a summary brochure. In late 2014 and in 2015 researchers were able to make the first ever releases of jungle perch fingerlings back into rivers and streams within their historical range.