5 resultados para 850

em eResearch Archive - Queensland Department of Agriculture


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Aims: To investigate the occurrence and levels of Arcobacter spp. in pig effluent ponds and effluent-treated soil. Methods and Results: A Most Probable Number (MPN) method was developed to assess the levels of Arcobacter spp. in seven pig effluent ponds and six effluent-treated soils, immediately after effluent irrigation. Arcobacter spp. levels in the effluent ponds varied from 6.5 × 105 to 1.1 × 108 MPN 100 ml-1 and in freshly irrigated soils from 9.5 × 102 to 2.8 × 104 MPN g-1 in all piggery environments tested. Eighty-three Arcobacter isolates were subjected to an abbreviated phenotypic test scheme and examined using a multiplex polymerase chain reaction (PCR). The PCR identified 35% of these isolates as Arcobacter butzleri, 49% as Arcobacter cryaerophilus while 16% gave no band. All 13 nonreactive isolates were subjected to partial 16S rDNA sequencing and showed a high similarity (>99%) to Arcobacter cibarius. Conclusions: A. butzleri, A. cryaerophilus and A. cibarius were isolated from both piggery effluent and effluent-irrigated soil, at levels suggestive of good survival in the effluent pond. Significance and Impact of the Study: This is the first study to provide quantitative information on Arcobacter spp. levels in piggery effluent and to associate A. cibarius with pigs and piggery effluent environments.

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Background: Molecular marker technologies are undergoing a transition from largely serial assays measuring DNA fragment sizes to hybridization-based technologies with high multiplexing levels. Diversity Arrays Technology (DArT) is a hybridization-based technology that is increasingly being adopted by barley researchers. There is a need to integrate the information generated by DArT with previous data produced with gel-based marker technologies. The goal of this study was to build a high-density consensus linkage map from the combined datasets of ten populations, most of which were simultaneously typed with DArT and Simple Sequence Repeat (SSR), Restriction Enzyme Fragment Polymorphism (RFLP) and/or Sequence Tagged Site (STS) markers. Results: The consensus map, built using a combination of JoinMap 3.0 software and several purpose-built perl scripts, comprised 2,935 loci (2,085 DArT, 850 other loci) and spanned 1,161 cM. It contained a total of 1,629 'bins' (unique loci), with an average inter-bin distance of 0.7 ± 1.0 cM (median = 0.3 cM). More than 98% of the map could be covered with a single DArT assay. The arrangement of loci was very similar to, and almost as optimal as, the arrangement of loci in component maps built for individual populations. The locus order of a synthetic map derived from merging the component maps without considering the segregation data was only slightly inferior. The distribution of loci along chromosomes indicated centromeric suppression of recombination in all chromosomes except 5H. DArT markers appeared to have a moderate tendency toward hypomethylated, gene-rich regions in distal chromosome areas. On the average, 14 ± 9 DArT loci were identified within 5 cM on either side of SSR, RFLP or STS loci previously identified as linked to agricultural traits. Conclusion: Our barley consensus map provides a framework for transferring genetic information between different marker systems and for deploying DArT markers in molecular breeding schemes. The study also highlights the need for improved software for building consensus maps from high-density segregation data of multiple populations.

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Light interception is a major factor influencing plant development and biomass production. Several methods have been proposed to determine this variable, but its calculation remains difficult in artificial environments with heterogeneous light. We propose a method that uses 3D virtual plant modelling and directional light characterisation to estimate light interception in highly heterogeneous light environments such as growth chambers and glasshouses. Intercepted light was estimated by coupling an architectural model and a light model for different genotypes of the rosette species Arabidopsis thaliana (L.) Heynh and a sunflower crop. The model was applied to plants of contrasting architectures, cultivated in isolation or in canopy, in natural or artificial environments, and under contrasting light conditions. The model gave satisfactory results when compared with observed data and enabled calculation of light interception in situations where direct measurements or classical methods were inefficient, such as young crops, isolated plants or artificial conditions. Furthermore, the model revealed that A. thaliana increased its light interception efficiency when shaded. To conclude, the method can be used to calculate intercepted light at organ, plant and plot levels, in natural and artificial environments, and should be useful in the investigation of genotype-environment interactions for plant architecture and light interception efficiency. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

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One major benefit of land application of biosolids is to supply nitrogen (N) for agricultural crops, and understanding mineralisation processes is the key for better N-management strategies. Field studies were conducted to investigate the process of mineralisation of three biosolids products (aerobic, anaerobic, and thermally dried biosolids) incorporated into four different soils at rates of 7-90 wet t/ha in subtropical Queensland. Two of these studies also examined mineralisation rates of commonly used organic amendments (composts, manures, and sugarcane mill muds). Organic N in all biosolids products mineralised very rapidly under ambient conditions in subtropical Queensland, with rates much faster than from other common amendments. Biosolids mineralisation rates ranged from 30 to 80% of applied N during periods ranging from 3.5 to 18 months after biosolids application; these rates were much higher than those suggested in the biosolids land application guidelines established by the NSW EPA (15% for anaerobic and 25% for aerobic biosolids). There was no consistently significant difference in mineralisation rate between aerobic and anaerobic biosolids in our studies. When applied at similar rates of N addition, other organic amendments supplied much less N to the soil mineral N and plant N pools during the crop season. A significant proportion of the applied biosolids total N (up to 60%) was unaccounted for at the end of the observation period. High rates of N addition in calculated Nitrogen Limited Biosolids Application Rates (850-1250 kg N/ha) resulted in excessive accumulation of mineral N in the soil profile, which increases the environmental risks due to leaching, runoff, or gaseous N losses. Moreover, the rapid mineralisation of the biosolids organic N in these subtropical environments suggests that biosolids should be applied at lower rates than in temperate areas, and that care must be taken with the timing to maximise plant uptake and minimise possible leaching, runoff, or denitrification losses of mineralised N.

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The root-lesion nematode, Pratylenchus thornei, can reduce wheat yields by >50%. Although this nematode has a broad host range, crop rotation can be an effective tool for its management if the host status of crops and cultivars is known. The summer crops grown in the northern grain region of Australia are poorly characterised for their resistance to P. thornei and their role in crop sequencing to improve wheat yields. In a 4-year field experiment, we prepared plots with high or low populations of P. thornei by growing susceptible wheat or partially resistant canaryseed (Phalaris canariensis); after an 11-month, weed-free fallow, several cultivars of eight summer crops were grown. Following another 15-month, weed-free fallow, P. thornei-intolerant wheat cv. Strzelecki was grown. Populations of P. thornei were determined to 150 cm soil depth throughout the experiment. When two partially resistant crops were grown in succession, e.g. canaryseed followed by panicum (Setaria italica), P. thornei populations were <739/kg soil and subsequent wheat yields were 3245 kg/ha. In contrast, after two susceptible crops, e.g. wheat followed by soybean, P. thornei populations were 10 850/kg soil and subsequent wheat yields were just 1383 kg/ha. Regression analysis showed a linear, negative response of wheat biomass and grain yield with increasing P. thornei populations and a predicted loss of 77% for biomass and 62% for grain yield. The best predictor of wheat yield loss was P. thornei populations at 0-90 cm soil depth. Crop rotation can be used to reduce P. thornei populations and increase wheat yield, with greatest gains being made following two partially resistant crops grown sequentially.