91 resultados para Cotton gins and ginning


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Natural Resource Management project developing reources and supporting best practice management for irrigated cotton and grain growers in Queensland.

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In the northern grain and cotton region of Australia, poor crop growth after long periods of fallow, called 'long-fallow' disorder, is caused by a decline of natural arbuscular-mycorrhizal fungi (AMF). When cotton was grown in large pots containing 22 kg of Vertisol from a field recently harvested from cotton in Central Queensland, plants in pasteurised soil were extremely stunted compared with plants in unpasteurised soil. We tested the hypothesis that this extreme stunting was caused by the absence of AMF and examined whether such stunted plants could recover from subsequent treatment with AMF spores and/or P fertiliser. At 42 days after sowing, the healthy cotton growing in unpasteurised soil had 48% of its root-length colonised with AMF, whereas the stunted cotton had none. After inoculation with AMF spores (6 spores/g soil of Glomus mosseae) and/or application of P fertiliser (50 mg P/kg soil) at 45 days after sowing, the stunted plants commenced to improve about 25 days after treatment, and continued until their total dry matter and seed cotton production equalled that of plants growing in unpasteurised soil with natural AMF. In contrast, non-mycorrhizal cotton grown without P fertiliser remained stunted throughout and produced no bolls and only 1% of the biomass of mycorrhizal cotton. Even with the addition of P fertiliser, non-mycorrhizal cotton produced only 64% of the biomass and 58% of the seed cotton (lint + seed) of mycorrhizal cotton plants. These results show that cotton is highly dependent on AMF for P nutrition and growth in Vertisol (even with high rates of P fertiliser), but can recover from complete lack of AMF and consequent stunting during at least the first 45 days of growth when treated with AMF spores and/or P fertiliser. This corroborates field observations in the northern region that cotton may recover from long-fallow disorder caused by low initial levels of AMF propagules in the soil as the AMF colonisation of its roots increases during the growing season.

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Glyphosate resistance is a rapidly developing threat to profitability in Australian cotton farming. Resistance causes an immediate reduction in the effectiveness of in-crop weed control in glyphosate-resistant transgenic cotton and summer fallows. Although strategies for delaying glyphosate resistance and those for managing resistant populations are qualitatively similar, the longer resistance can be delayed, the longer cotton growers will have choice over which tactics to apply and when to apply them. Effective strategies to avoid, delay, and manage resistance are thus of substantial value. We used a model of glyphosate resistance dynamics to perform simulations of resistance evolution in Sonchus oleraceus (common sowthistle) and Echinochloa colona (awnless barnyard grass) under a range of resistance prevention, delaying, and management strategies. From these simulations, we identified several elements that could contribute to effective glyphosate resistance prevention and management strategies. (i) Controlling glyphosate survivors is the most robust approach to delaying or preventing resistance. High-efficacy, high-frequency survivor control almost doubled the useful lifespan of glyphosate from 13 to 25 years even with glyphosate alone used in summer fallows. (ii) Two non-glyphosate tactics in-crop plus two in-summer fallows is the minimum intervention required for long-term delays in resistance evolution. (iii) Pre-emergence herbicides are important, but should be backed up with non-glyphosate knockdowns and strategic tillage; replacing a late-season, pre-emergence herbicide with inter-row tillage was predicted to delay glyphosate resistance by 4 years in awnless barnyard grass. (iv) Weed species' ecological characteristics, particularly seed bank dynamics, have an impact on the effectiveness of resistance strategies; S. oleraceus, because of its propensity to emerge year-round, was less exposed to selection with glyphosate than E. colona, resulting in an extra 5 years of glyphosate usefulness (18 v. 13 years) even in the most rapid cases of resistance evolution. Delaying tactics are thus available that can provide some or many years of continued glyphosate efficacy. If glyphosate-resistant cotton cropping is to remain profitable in Australian farming systems in the long-term, however, growers must adapt to the probability that they will have to deal with summer weeds that are no longer susceptible to glyphosate. Robust resistance management systems will need to include a diversity of weed control options, used appropriately.

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Cotton bunchy top virus (CBTV) and the related Cotton leafroll dwarf virus (CLRDV) have caused sporadic disease outbreaks in most cotton regions of the world. Until recently, little was known about the diversity of CBTV or its natural host range. Seven natural field hosts and one experimental host of CBTV have now been identified. These include cotton, Malva parviflora (Marshmallow weed), Abutilon theophrasti (Velvetleaf), Anoda cristata (Spurred anoda), Hibiscus sabdariffa (Rosella), Sida rhombifolia (Paddy’s lucerne), Chamaesyce hirta (Asthma plant) and Gossypium australe. These are currently the only eight known hosts of CBTV. However the virus may have a wider host range than originally thought and include further non-Malvaceae species like asthma plant (family Euphorbiaceae). There are two distinct strains of CBTV in Australia, -A and -B, which have been detected in cotton from numerous locations across almost all growing regions. From 105 samples of cotton that have been positive for CBTV, 6 were infections of strain A only, 60 were strain B only and 64 were a mixed infection of strains A and B. These results indicate the symptoms of cotton bunchy top disease are closely associated with the presence of strain CBTV-B. A diagnostic assay for Cotton leafroll dwarf virus (CLRDV - cotton blue disease) is being developed and applied successfully for the detection of CLRDV samples from Brazil and Thailand. This is the first confirmation of CLRDV from SE-Asia, which may pose an increased biosecurity threat to the Australian industry.

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With potential to accumulate substantial amounts of above-ground biomass, at maturity an irrigated cotton crop can have taken up more than 20 kg/ha phosphorus and often more than 200 kg/ha of potassium. Despite the size of plant accumulation of P and K, recovery of applied P and K fertilisers by the crop in our field experiment program has poor. Processing large amounts of mature cotton plant material to provide a representative sample for chemical analysis has not been without its challenges, but the questions regarding mechanism of where, how and when the plant is acquiring immobile nutrients remain. Dry matter measured early in the growing season (squaring, first white flower) have demonstrated a 50% increase in crop biomass to applied P (in particular), but it represents only 20% of the total P accumulation by the plant. By first open boll (and onwards), no response in dry matter or P concentration could be detected to P application. A glasshouse study indicated P recovery was greater (to FOB) where it was completely mixed through a profile as opposed to a banded application method suggesting cotton prefers a more diffuse distribution. The relative effects of root morphology, mycorrhizal fungi infection, seasonal growth patterns and how irrigation is applied are areas for future investigation on how, when and where cotton acquires immobile nutrients.

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Awnless barnyard grass, feathertop Rhodes grass, and windmill grass are important weeds in Australian cotton systems. In October 2014, an experiment was established to investigate the phenological plasticity of these species. Seed of these species were planted in a glasshouse every four weeks and each cohort grown for 6 months. A developmental response to day length was observed in barnyard grass but not in the other species. Days to maturity increased with each planting for feathertop Rhodes and windmill grass for the first six cohorts. Barnyard grass showed a similar pattern in growth for seeds planted from October to December with an increase in the onset of maturity from 51 to 58 days. However, the onset of maturity for cohorts planted between January and March decreased to between 50 and 52 days. All species had a decrease in the total number of panicles produced from the first four plantings. Feathertop Rhodes grass planted in October produced 41 panicles compared to those planted at the end of December producing 30 panicles, barnyard grass had a decrease from 99 to 47 panicles and windmill grass 37 to 15 panicles on average. By comparing the development of these key weed species over 12 months, detailed information on the phenological plasticity of these species will be obtained. This information will contribute to more informed management decisions by improving our understanding of appropriate weed control timings or herbicide rates depending on weed emergence and development.

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Efficient crop monitoring and pest damage assessments are key to protecting the Australian agricultural industry and ensuring its leading position internationally. An important element in pest detection is gathering reliable crop data frequently and integrating analysis tools for decision making. Unmanned aerial systems are emerging as a cost-effective solution to a number of precision agriculture challenges. An important advantage of this technology is it provides a non-invasive aerial sensor platform to accurately monitor broad acre crops. In this presentation, we will give an overview on how unmanned aerial systems and machine learning can be combined to address crop protection challenges. A recent 2015 study on insect damage in sorghum will illustrate the effectiveness of this methodology. A UAV platform equipped with a high-resolution camera was deployed to autonomously perform a flight pattern over the target area. We describe the image processing pipeline implemented to create a georeferenced orthoimage and visualize the spatial distribution of the damage. An image analysis tool has been developed to minimize human input requirements. The computer program is based on a machine learning algorithm that automatically creates a meaningful partition of the image into clusters. Results show the algorithm delivers decision boundaries that accurately classify the field into crop health levels. The methodology presented in this paper represents a venue for further research towards automated crop protection assessments in the cotton industry, with applications in detecting, quantifying and monitoring the presence of mealybugs, mites and aphid pests.

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The cotton industry in Australia funds biannual disease surveys conducted by plant pathologists. The objective of these surveys is to monitor the distribution and importance of key endemic pests and record the presence or absence of new or exotic diseases. Surveys have been conducted in Queensland since 2002/03, with surveillance undertaken by experienced plant pathologists. Monitoring of endemic diseases indicates the impact of farming practices on disease incidence and severity. The information collected gives direction to cotton disease research. Routine diagnostics has provided early detection of new disease problems which include 1) the identification of Nematospora coryli, a pathogenic yeast associated with seed and internal boll rot; and 2) Rotylenchulus reniformis, a plant-parasitic nematode. This finding established the need for an intensive survey of the Theodore district revealing that reniform was prevalent across the district at populations causing up to 30% yield loss. Surveys have identified an exotic defoliating strain (VCG 1A) and non-defoliating strains of Verticillium dahliae, which cause Verticillium wilt. An intensive study of the diversity of V. dahliae and the impact these strains have on cotton are underway. Results demonstrate the necessity of general multi-pest surveillance systems in broad acre agriculture in providing (1) an ongoing evaluation of current integrated disease management practices and (2) early detection for a suite of exotic pests and previously unknown pests.

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BACKGROUND AND AIMS: Silicon has been shown to enhance the resistance of plants to fungal and bacterial pathogens. Here, the effect of potassium silicate was assessed on two cotton (Gossypium hirsutum) cultivars subsequently inoculated with Fusarium oxysporum f. sp. vasinfectum (Fov). Sicot 189 is moderately resistant whilst Sicot F-1 is the second most resistant commercial cultivar presently available in Australia. METHODS: Transmission and light microscopy were used to compare cellular modifications in root cells after these different treatments. The accumulation of phenolic compounds and lignin was measured. KEY RESULTS: Cellular alterations including the deposition of electron-dense material, degradation of fungal hyphae and occlusion of endodermal cells were more rapidly induced and more intense in endodermal and vascular regions of Sicot F-1 plants supplied with potassium silicate followed by inoculation with Fov than in similarly treated Sicot 189 plants or in silicate-treated plants of either cultivar not inoculated with Fov. Significantly more phenolic compounds were present at 7 d post-infection (dpi) in root extracts of Sicot F-1 plants treated with potassium silicate followed by inoculation with Fov compared with plants from all other treatments. The lignin concentration at 3 dpi in root material from Sicot F-1 treated with potassium silicate and inoculated with Fov was significantly higher than that from water-treated and inoculated plants. CONCLUSIONS: This study demonstrates that silicon treatment can affect cellular defence responses in cotton roots subsequently inoculated with Fov, particularly in Sicot F-1, a cultivar with greater inherent resistance to this pathogen. This suggests that silicon may interact with or initiate defence pathways faster in this cultivar than in the less resistant cultivar.

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Decision-making in agriculture is carried out in an uncertain environment with farmers often seeking information to reduce risk. As a result of the extreme variability of rainfall and stream-flows in north-eastern Australia, water supplies for irrigated agriculture are a limiting factor and a source of risk. The present study examined the use of seasonal climate forecasting (SCF) when calculating planting areas for irrigated cotton in the northern Murray Darling Basin. Results show that minimising risk by adjusting plant areas in response to SCF can lead to significant gains in gross margin returns. However, how farmers respond to SCF is dependent on several other factors including irrigators’ attitude towards risk.

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This study investigated the responses by dairy cows grazing Callide Rhodes grass (Chloris gayana cv. Callide) pasture to supplementation with barley or sorghum based concentrates (5 grain:1 cotton seed meal) or barley concentrate plus lucerne (Medicago sativa) hay. It was conducted in summer - autumn 1999 with 20 spring calved cows in 4 treatments in 3 consecutive periods of 4 weeks. Rain grown pastures, heavily stocked at 4.4 cows/ha, provided 22 to 35 kg green DM and 14 to 16 kg green leaf DM/cow.day in periods 1 to 3. Supplements were fed individually twice daily after milking. Cows received 6 kg concentrate/day in period 1, increased by 1 kg/day as barley, sorghum or lucerne chaff in each of periods 2 and 3. The Control treatment received 6 kg barley concentrate in all 3 periods. Milk yields by cows fed sorghum were lower than for cows fed equivalent levels of barley-based concentrate (P<0.05). Faecal starch levels (14, 18 and 17%) for cows fed sorghum concentrate were much higher (P<0.01) than those of cows fed similar levels of barley (2.1, 1.2 and 1.7%) in each period respectively. Additional supplementation as lucerne chaff did not increase milk production (P>0.05). Increased concentrate supplementation did not alleviate the problem of low protein in milk produced by freshly calved Holstein-Friesian cows grazing tropical grass pasture in summer. Animal production for a consuming world : proceedings of 9th Congress of the Asian-Australasian Association of Animal Production Societies [AAAP] and 23rd Biennial Conference of the Australian Society of Animal Production [ASAP] and 17th Annual Symposium of the University of Sydney, Dairy Research Foundation, [DRF]. 2-7 July 2000, Sydney, Australia.

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The ability of adult cotton bollworm, Helicoverpa armigera (Hubner), to distinguish and respond to enantiomers of α-pinene was investigated with electrophysiological and behavioral methods. Electroantennogram recordings using mixtures of the enantiomers at saturating dose levels, and single unit electrophysiology, indicated that the two forms were detected by the same receptor neurons. The relative size of the electroantennogram response was higher for the (−) compared to the (+) form, indicating greater affinity for the (−) form at the level of the dendrites. Behavioral assays investigated the ability of moths to discriminate between, and respond to the (+) and (−) forms of α pinene. Moths with no odor conditioning showed an innate preference for (+)-α-pinene. This preference displayed by naıve moths was not significantly different from the preferences of moths conditioned on (+)-α-pinene. However, we found a significant difference in preference between moths conditioned on the (−) enantiomer compared to naıve moths and moths conditioned on (+)-α-pinene, showing that learning plays an important role in the behavioral response. Moths are less able to distinguish between enantiomers of α-pinene than different odors (e.g., phenylacetaldehyde versus (−)-α-pinene) in learning experiments. The relevance of receptor discrimination of enantiomers and learning ability of the moths in host plant choice is discussed.