122 resultados para Region growing algorithms


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Objectives: The aim of this study was to determine the antimicrobial resistance patterns of 125 Campylobacter jejuni and 27 Campylobacter coli isolates from 39 Queensland broiler farms. Methods: Two methods, a disc diffusion assay and an agar-based MIC assay, were used. The disc diffusion was performed and interpreted as previously described (Huysmans MB, Turnidge JD. Disc susceptibility testing for thermophilic campylobacters. Pathology 1997; 29: 209–16), whereas the MIC assay was performed according to CLSI (formerly NCCLS) methods and interpreted using DANMAP criteria. Results: In both assays, no C. jejuni or C. coli isolates were resistant to ciprofloxacin or chloramphenicol, no C. coli were resistant to nalidixic acid, and no C. jejuni were resistant to erythromycin. In the MIC assay, no C. jejuni isolate was resistant to nalidixic acid, whereas three isolates (2.4%) were resistant in the disc assay. The highest levels of resistance of the C. jejuni isolates were recorded for tetracycline (19.2% by MIC and 18.4% by disc) and ampicillin (19.2% by MIC and 17.6% by disc). The C. coli isolates gave very similar results (tetracycline resistance 14.8% by both MIC and disc; ampicillin resistance 7.4% by MIC and 14.8% by disc). Conclusions: This work has shown that the majority of C. jejuni and C. coli isolates were susceptible to the six antibiotics tested by both disc diffusion and MIC methods. Disc diffusion represents a suitable alternative methodology to agar-based MIC methods for poultry Campylobacter isolates.

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Barley hull plays an important role in malt and feed quality and processing. In this study we measured the variation in hull con-tent along with other grain quality traits namely, kernel discolouration and degree of pre-harvest sprouting, in a single map-ping population. There were significant (p < 0.05) genetic as well as environment effects. In addition, heritability was calculated for hull content to be 29% and 47% for two years’ data. From the analysis, major QTL markers were identified in con-trolling the expression of hull content on chromosomes 2 (2H), and 6 (6H) with significant (P < 0.05) LOD scores of 5.4 and 3.46 respectively. Minor QTLs were identified on 1 (7H), 4 (4H), 5 (1H) and 7 (5H). The region at marker Bmac310 on 4(4H) could be associated with dormancy gene SD4. A number of the QTLs also coincided with regions for either kernel discolouration or preharvest sprouting resistance (dormancy). The results indicate that variation exists for hull content, which is influenced by both growing environment as well as genetically, although the genetic variance explained less than half of the total variance. Further, hull content also impacts on other grain quality attributes including dormancy, sprouting resistance and kernel appearance.

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In dryland agricultural systems of the subtropical, semi-arid region of north-eastern Australia, water is the most limiting resource. Crop productivity depends on the efficient use of rainfall and available water stored in the soil during fallow. Agronomic management practices including a period of fallow, stubble retention, and reduced tillage enhance reserves of soil water. However, access to stored water in these soils may be restricted by the presence of growth-limiting conditions in the rooting zone of the crop. These have been termed as subsoil constraints. Subsoil constraints may include compacted or gravel layers (physical), sodicity, salinity, acidity, nutrient deficiencies, presence of toxic elements (chemical) and low microbial activity (biological). Several of these constraints may occur together in some soils. Farmers have often not been able to obtain the potential yield determined by their prevailing climatic conditions in the marginal rainfall areas of the northern grains region. In the past, the adoption of soil management practices had been largely restricted to the top 100 mm soil layer. Exploitation of the subsoil as a source of water and nutrients has largely been overlooked. The key towards realising potential yields would be to gain better understanding of subsoils and their limitations, then develop options to manage them practically and economically. Due to the complex nature of the causal factors of these constraints, efforts are required for a combination of management approaches rather than individual options, with the aim to combat these constraints for sustainable crop production, managing natural resources and avoiding environmental damage.

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Fusarium wilt of cotton, caused by the fungus Fusarium oxysporum Schlechtend. f. sp. vasinfectum (Atk.) Snyd. & Hans, was first identified in 1892 in cotton growing in sandy acid soils in Alabama (8). Although the disease was soon discovered in other major cotton-producing areas, it did not become global until the end of the next century. After its original discovery, Fusarium wilt of cotton was reported in Egypt (1902) (30), India (1908) (60), Tanzania (1954) (110), California (1959) (33), Sudan (1960) (44), Israel (1970) (27), Brazil (1978) (5), China (1981) (17), and Australia (1993) (56). In addition to a worldwide distribution, Fusarium wilt occurs in all four of the domesticated cottons, Gossypium arboretum L., G. barbadense L., G. herbaceum L., and G. hirsutum L. (4,30). Disease losses in cotton are highly variable within a country or region. In severely infested fields planted with susceptible cultivars, yield losses can be high. In California, complete crop losses in individual fields have been observed (R. M. Davis, unpublished). Disease loss estimates prepared by the National Cotton Disease Council indicate losses of over 109,000 bales (227 kg or 500 lb) in the United States in 2004 (12).

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Synthetic backcrossed-derived bread wheats (SBWs) from CIMMYT were grown in the Northwest of Mexico at Centro de Investigaciones Agrícolas del Noroeste (CIANO) and sites across Australia during three seasons. During three consecutive years Australia received “shipments” of different SBWs from CIMMYT for evaluation. A different set of lines was evaluated each season, as new materials became available from the CIMMYT crop enhancement program. These consisted of approximately 100 advanced lines (F7) per year. SBWs had been top and backcrossed to CIMMYT cultivars in the first two shipments and to Australian wheat cultivars in the third one. At CIANO, the SBWs were trialled under receding soil moisture conditions. We evaluated both the performance of each line across all environments and the genotype-by-environment interaction using an analysis that fits a multiplicative mixed model, adjusted for spatial field trends. Data were organised in three groups of multienvironment trials (MET) containing germplasm from shipment 1 (METShip1), 2 (METShip2), and 3 (METShip3), respectively. Large components of variance for the genotype × environment interaction were found for each MET analysis, due to the diversity of environments included and the limited replication over years (only in METShip2, lines were tested over 2 years). The average percentage of genetic variance explained by the factor analytic models with two factors was 50.3% for METShip1, 46.7% for METShip2, and 48.7% for METShip3. Yield comparison focused only on lines that were present in all locations within a METShip, or “core” SBWs. A number of core SBWs, crossed to both Australian and CIMMYT backgrounds, outperformed the local benchmark checks at sites from the northern end of the Australian wheat belt, with reduced success at more southern locations. In general, lines that succeeded in the north were different from those in the south. The moderate positive genetic correlation between CIANO and locations in the northern wheat growing region likely reflects similarities in average temperature during flowering, high evaporative demand, and a short flowering interval. We are currently studying attributes of this germplasm that may contribute to adaptation, with the aim of improving the selection process in both Mexico and Australia.

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Growers working together have proven to be a successful method for improving the utilization of farm resources and accelerating the adoption of the Sugar Yield Decline Joint Venture principles (SYDJV). The Pinnacle Precision Farming Group was formed in 2004 with the aim to bring together the ideas, knowledge and resources of growers in the Herbert region. Along with their common interest in controlled traffic, minimal tillage and crop rotations, the grower group utilize a farm machinery contractor to provide some of their major farming operations. This paper provides an insight into the changes made by the Pinnacle Precision Farming Group and their journey to adopt the new farming system practices. This paper also details the changes made by the group machinery contractor and a comparison of the old and new farming systems used by a group member. A focus point of the document is the impact of the new farming system on the economic, social and environmental components of the farming business. Analysis of the new farming system with a legume crop rotation revealed an increase in the farm gross margin by AU$22 024 and, in addition, a reduction in tractor operation time by 38% across the whole farm. This represents a return on marginal capital of 14.68 times the original capital outlay required by the group member. Using the new farming system without a legume crop will still improve the group members whole of farm gross margin by AU$6 839 and reduce tractor operation time by 43% across the whole farm. The Pinnacle Precision Farming group recognize the need to continually improve their farming businesses and believe that the new farming system principles are critical for the long term viability of the industry. [U$1 = AU$1.19].

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The tomato I-3 gene introgressed from the Lycopersicon pennellii accession LA716 confers resistance to race 3 of the fusarium wilt pathogen Fusarium oxysporum f. sp. lycopersici. We have improved the high-resolution map of the I-3 region of tomato chromosome 7 with the development and mapping of 31 new PCR-based markers. Recombinants recovered from L. esculentum cv. M82 × IL7-2 F2 and (IL7-2 × IL7-4) × M82 TC1F2 mapping populations, together with recombinants recovered from a previous M82 × IL7-3 F2 mapping population, were used to position these markers. A significantly higher recombination frequency was observed in the (IL7-2 × IL7-4) × M82 TC1F2 mapping population based on a reconstituted L. pennellii chromosome 7 compared to the other two mapping populations based on smaller segments of L. pennellii chromosome 7. A BAC contig consisting of L. esculentum cv. Heinz 1706 BACs covering the I-3 region has also been established. The new high-resolution map places the I-3 gene within a 0.38 cM interval between the molecular markers RGA332 and bP23/gPT with an estimated physical size of 50-60 kb. The I-3 region was found to display almost continuous microsynteny with grape chromosome 12 but interspersed microsynteny with Arabidopsis thaliana chromosomes 1, 2 and 3. An S-receptor-like kinase gene family present in the I-3 region of tomato chromosome 7 was found to be present in the microsyntenous region of grape chromosome 12 but was absent altogether from the A. thaliana genome.

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In 2001, an incursion of Mycosphaerella fijiensis, the causal agent of black Sigatoka, was detected in Australia's largest commercial banana growing region, the Tully Banana Production Area in North Queensland. An intensive surveillance and eradication campaign was undertaken which resulted in the reinstatement of the disease-free status for black Sigatoka in 2005. This was the first time black Sigatoka had ever been eradicated from commercial plantations. The success of the eradication campaign was testament to good working relationships between scientists, growers, crop monitors, quarantine regulatory bodies and industry. A key contributing factor to the success was the deployment of a PCR-based molecular diagnostic assay, developed by the Cooperative Research Centre for Tropical Plant Protection (CRCTPP). This assay complemented morphological identification and allowed high throughput diagnosis of samples facilitating rapid decision-making during the eradication campaign. This paper describes the development and successful deployment of molecular diagnostics for black Sigatoka. Shortcomings in the gel-based assay are discussed and the advantages of highly specific real-time PCR assays, capable of differentiating between Mycosphaerella fijiensis, Mycosphaerella musicola and Mycosphaerella eumusae are outlined. Real-time assays may provide a powerful diagnostic tool for applications in surveillance, disease forecasting and resistance testing for Sigatoka leaf spot diseases.

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The effects of fertilisers on 8 tropical turfgrasses growing in 100-L bags of sand were studied over winter in Murrumba Downs, just north of Brisbane in southern Queensland (latitude 27.4°S, longitude 153.1°E). The species used were: Axonopus compressus (broad-leaf carpetgrass), Cynodon dactylon (bermudagrass 'Winter Green') and C. dactylon x C. transvaalensis hybrid ('Tifgreen'), Digitaria didactyla (Queensland blue couch), Paspalum notatum (bahiagrass '38824'), Stenotaphrum secundatum (buffalograss 'Palmetto'), Eremochloa ophiuroides (centipedegrass 'Centec') and Zoysia japonica (zoysiagrass 'ZT-11'). Control plots were fertilised with complete fertilisers every month from May to September (72 kg N/ha, 31 kg P/ha, 84 kg K/ha, 48 kg S/ha, 30 kg Ca/ha and 7.2 kg Mg/ha), and unfertilised plots received no fertiliser. Carpetgrass and standard bermudagrass were the most sensitive species to nutrient supply, with lower shoot dry weights in the unfertilised plots (shoots mowed to thatch level) compared with the fertilised plots in June. There were lower shoot dry weights in the unfertilised plots in July for all species, except for buffalograss, centipedegrass and zoysiagrass, and lower shoot dry weights in the unfertilised plots in August for all species, except for centipedegrass. At the end of the experiment in September, unfertilised plots were 11% of the shoot dry weights of fertilised plots, with all species affected. Mean shoot nitrogen concentrations fell from 3.2 to 1.7% in the unfertilised plots from May to August, below the sufficiency range for turfgrasses (2.8-3.5%). There were also declines in P (0.45-0.36%), K (2.4-1.5%), S (0.35-0.25%), Mg (0.24-0.18%) and B (9-6 mg/kg), which were all in the sufficiency range. The shoots in the control plots took up the following levels (kg/ha.month) of nutrients: N, 10.0-27.0; P, 1.6-4.0; K, 8.2-19.8; S, 1.0-4.2; Ca, 1.1-3.3; and Mg, 0.8-2.2, compared with applications (kg/ha.month) of: N, 72; P, 31; K, 84; S, 48; Ca, 30; and Mg, 7.2, indicating a recovery of 14-38% for N, 5-13% for P, 10-24% for K, 2-9% for S, 4-11% for Ca and 11-30% for Mg. These results suggest that buffalograss, centipedegrass and zoysiagrass are less sensitive to low nutrient supply than carpetgrass, bermudagrass, blue couch and bahiagrass. Data on nutrient uptake showed that the less sensitive species required only half or less of the nitrogen required to maintain the growth of the other grasses, indicating potential savings for turf managers in fertiliser costs and the environment in terms of nutrients entering waterways.

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Many forces are driving the global demand for assurance that fruit and vegetables are safe to eat and of the right quality, and are produced and handled in a manner that does not cause harm to the environment and the health, safety and welfare of workers. The impact of these driving forces is that retailer requirements for suppliers to comply with Good Agricultural Practice (GAP) is increasing and governments are strengthening legal requirements for food safety, environmental protection, and worker health, safety and welfare. The implementation of GAP programs currently within the ASEAN (Association of South East Asian Nations) region varies, with some countries having government certified systems and others beginning the journey with awareness programs for farmers. Under a project funded by the ASEAN Australia Development Cooperation Program, a standard for ASEAN GAP has been developed to harmonise GAP Programs in the region. The goal is to facilitate trade between ASEAN countries and to global markets, improve viability for farmers, and help sustain a safe food supply and the environment. ASEAN GAP is an umbrella standard that individual member countries will benchmark their national programs against to gain equivalence. The scope of ASEAN GAP covers the production, harvesting and postharvest handling of fresh fruit and vegetables on farm and postharvest handling in locations where produce is packed for sale. ASEAN GAP consists of four modules covering food safety, environmental management, worker health, safety and welfare, and produce quality. Each module can be used alone or in combination with other modules. This enables progressive implementation of ASEAN GAP, module by module based on individual country priorities.

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A framework using assessments of soil condition, pasture composition and woodland density was applied to describe 14 grazing land types as being in A (100% of original carrying capacity), B (75%), C (45%) or D (20%) condition. We assessed the condition of 260 sites, principally along public and some station roads, to provide a benchmark for current land condition. Land types were also assigned relative grazing values between 10 (best) and 0, reflecting soil fertility and potential biomass production. The method identifies particular, 'at-risk' land types for priority investment of resources, while the rationale behind assessments might point to management interventions to improve the condition of those land types. Across all land types, 47% of sites were in A condition, 34% in B condition, 17% in C condition and only 2% in D condition. Seventy-five percent of land types with grazing values >5 were in A or B condition, compared with 88% for those with grazing values ?5. For Georgetown granites, only 27% of sites were in A or B condition, with values for other land types being: alluvials 59%, black soils 64% and red duplex soils 57%, suggesting that improving management of these land types is a priority issue. On land types with high grazing value, the major discounting factor was pasture composition (72% of sites discounted), while increasing woodland density was the main discount (73% of sites discounted) on low grazing value land types.

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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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Weed management is one of the most important economic and agronomic issues facing farmers in Australia's grain regions. Weed species occurrence and abundance was monitored between 1997 and 2000 on 46 paddocks (sites) across 18 commercial farms located in the Northern Grain Region. The sites generally fell within 4 disjunct regions, from south to north: Liverpool Plains, Moree, Goondiwindi and Kingaroy. While high species richness was found (139 species or species groups), only 8 species occurred in all 4 regions and many (56 species) only occurred at 1 site or region. No species were observed at every site but 7 species (Sonchus spp., Avena spp., Conyza spp., Echinochloa spp., Convolvulus erubescens, Phalaris spp. and Lactuca serriola) were recorded on more than 70% of sites. The average number of species observed within crops after treatment and before harvest was less than 13. Species richness tended to be higher in winter pulse crops, cotton and in fallows, but overall was similar at the different sampling seasons (summer v. winter). Separate species assemblages associated with the Goondiwindi and Kingaroy regions were identified by correspondence analysis but these appeared to form no logical functional group. The species richness and density was generally low, demonstrating that farmers are managing weed populations effectively in both summer and winter cropping phases. Despite the apparent adoption of conservation tillage, an increase in opportunity cropping and the diversity of crops grown (13) there was no obvious effect of management practices on weed species richness or relative abundance. Avena spp. and Sonchus spp. were 2 of the most dominant weeds, particularly in central and southern latitudes of the region; Amaranthus spp. and Raphanus raphanistrum were the most abundant species in the northern part of the region. The ubiquity of these and other species shows that continued vigilance is required to suppress weeds as a management issue.

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Soils with high levels of chloride and/or sodium in their subsurface layers are often referred to as having subsoil constraints (SSCs). There is growing evidence that SSCs affect wheat yields by increasing the lower limit of a crop's available soil water (CLL) and thus reducing the soil's plant-available water capacity (PAWC). This proposal was tested by simulation of 33 farmers' paddocks in south-western Queensland and north-western New South Wales. The simulated results accounted for 79% of observed variation in grain yield, with a root mean squared deviation (RMSD) of 0.50 t/ha. This result was as close as any achieved from sites without SSCs, thus providing strong support for the proposed mechanism that SSCs affect wheat yields by increasing the CLL and thus reducing the soil's PAWC. In order to reduce the need to measure CLL of every paddock or management zone, two additional approaches to simulating the effects of SSCs were tested. In the first approach the CLL of soils was predicted from the 0.3-0.5 m soil layer, which was taken as the reference CLL of a soil regardless of its level of SSCs, while the CLL values of soil layers below 0.5 m depth were calculated as a function of these soils' 0.3-0.5 m CLL values as well as of soil depth plus one of the SSC indices EC, Cl, ESP, or Na. The best estimates of subsoil CLL values were obtained when the effects of SSCs were described by an ESP-dependent function. In the second approach, depth-dependent CLL values were also derived from the CLL values of the 0.3-0.5 m soil layer. However, instead of using SSC indices to further modify CLL, the default values of the water-extraction coefficient (kl) of each depth layer were modified as a function of the SSC indices. The strength of this approach was evaluated on the basis of correlation of observed and simulated grain yields. In this approach the best estimates were obtained when the default kl values were multiplied by a Cl-determined function. The kl approach was also evaluated with respect to simulated soil moisture at anthesis and at grain maturity. Results using this approach were highly correlated with soil moisture results obtained from simulations based on the measured CLL values. This research provides strong evidence that the effects of SSCs on wheat yields are accounted for by the effects of these constraints on wheat CLL values. The study also produced two satisfactory methods for simulating the effects of SSCs on CLL and on grain yield. While Cl and ESP proved to be effective indices of SSCs, EC was not effective due to the confounding effect of the presence of gypsum in some of these soils. This study provides the tools necessary for investigating the effects of SSCs on wheat crop yields and natural resource management (NRM) issues such as runoff, recharge, and nutrient loss through simulation studies. It also facilitates investigation of suggested agronomic adaptations to SSCs.

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The main weeds and weed management practices undertaken in broad acre dryland cropping areas of north-eastern Australia have been identified. The information was collected in a comprehensive postal survey of both growers and agronomists from Dubbo in New South Wales (NSW) through to Clermont in central Queensland, where 237 surveys were returned. A very diverse weed flora of 105 weeds from 91 genera was identified for the three cropping zones within the region (central Queensland, southern Queensland and northern NSW). Twenty-three weeds were common to all cropping zones. The major common weeds were Sonchus oleraceus, Rapistrum rugosum, Echinochloa spp. and Urochloa panicoides. The main weeds were identified for both summer and winter fallows, and sorghum, wheat and chickpea crops for each of the zones, with some commonality as well as floral uniqueness recorded. More genera were recorded in the fallows than in crops, and those in summer fallows exceeded the number in winter. Across the region, weed management relied heavily on herbicides. In fallows, glyphosate and mixes with glyphosate were very common, although the importance of the glyphosate mix partner differed among the cropping zones. Use and importance of pre-emergence herbicides in-crop varied considerably among the zones. In wheat, more graminicides were used in northern NSW than in southern Queensland, and virtually none were used in central Queensland, reflecting the differences in winter grass weed flora across the region. Atrazine was the major herbicide used in sorghum, although metolachlor was also used predominantly in northern NSW. Fallow and inter-row cultivation were used more often in the southern areas of the region. Grazing of fallows was more prominent in northern NSW. High crop seeding rates were not commonly recorded indicating that growers are not using crop competition as a tool for weed management. Although many management practices were recorded overall, few growers were using integrated weed management, and herbicide resistance has been and continues to be an issue for the region.