78 resultados para cotton fibre


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Partial virus genome sequence with high nucleotide identity to Cotton leafroll dwarf virus (CLRDV) was identified from two cotton (Gossypium hirsutum) samples from Thailand displaying typical cotton leaf roll disease symptoms. We developed and validated a PCR assay for the detection of CLRDV isolates from Thailand and Brazil.

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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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Soilborne diseases such as Fusarium wilt, Black root rot and Verticillium wilt have significant impact on cotton production. Fungi are an important component of soil biota with capacity to affect pathogen inoculum levels and their disease causing potential. Very little is known about the soil fungal community structure and management effects in Australian cotton soils. We analysed surface soils from ongoing field experiments monitoring cotton performance and disease incidence in three cotton growing regions, collected prior to 2013 planting, for the genetic diversity and abundance as influenced by soil type, environment and management practices and link it with disease incidence and suppression. Results from the 28S LSU rRNA sequencing based analysis indicated a total of 370 fungal genera in all the cotton soils and the top 25 genera in abundance accounted for the major portion of total fungal community. There were significant differences in the composition and genetic diversity of soil fungi between the different field sites from the three cotton growing regions. Results for diversity indices showed significantly greater diversity in the long-term crop rotation experiment at Narrabri (F6E) and experiments at Cowan and Goondiwindi compared to the Biofumigation and D1 field experiments at ACRI, Narrabri. Diversity was lowest in the soils under brassica crop rotation in Biofumigation experiment. Overall, the diversity and abundance of soil fungal community varied significantly in the three cotton growing regions indicating soil type and environmental effects. These results suggest that changes in soil fungal community may play a notable role in soilborne disease incidence in cotton.

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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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Like all high yielding farming systems nitrogen (N) is a key component to their productivity and profitability and Australian irrigated cotton growers are tending to apply more N than is required for the level of lint yield that is being achieved. This suggests either over application of N or inefficient systems limiting the response of cotton to N inputs. To investigate this four replicated trials were established in commercial fields during the 2014/15 season. The trials were aiming to measure the difference in response of irrigated cotton to the application of N under flood and overhead irrigation systems. The application treatments utilized eight upfront rates of applied N, ranging from 0 N kg/ha to a maximum of 410 kg N/ha, with three of the fours trials receiving a growerdetermined in-crop application of N in the irrigation water. The two flood irrigation systems had lower lint yields from similar levels of N input compared to one of the overhead irrigated sites; the result from the second overhead site was impacted by disease. This paper discusses the response of plant N uptake, lint yield and fertilizer N recovery to N application..

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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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Composts can provide a source of organic carbon and nutrients for soil biota and increase soil fertility as well as provide other biological and structural benefits hence compost addition to cotton soils is seen as a way to improve cotton soil biological health and fertility. In a six month incubation experiment we analysed the changes in microbial populations and activities related to C and N cycling following the application of feedlot, poultry manure and gin trash compost materials. A significant variation in the chemical composition, e.g. major nutrients and trace elements, was found between the three compost products. The feedlot compost generally contained higher levels of dissolved organic carbon, total nitrogen and bicarbonate extractable phosphorus whereas the Gin trash compost had lower carbon and nutrient concentrations. The effect of compost addition @ 5 and 10t/ha generally increased microbial activity but the effect was only evident during the first two weeks of incubation. Composts effects on the abundance of total bacteria (16S), nitrifying (amoA), nitrogen fixing (nifH) and denitrifying bacteria (nosZ) and total fungi (ITS gene) varied between different composts. The addition of feedlot and poultry compost material significantly increased the levels of dissolved organic carbon (DOC) and nitrogen (DON) in soil compared to that in control soils while ‘Gin trash’ compost had no effect. These differences reflected in the microbial catabolic diversity changes in the compost amended soils. Therefore, chemical analysis of the compost material before application is recommended to more fully consider its’ potential benefits.

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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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Yield loss in crops is often associated with plant disease or external factors such as environment, water supply and nutrient availability. Improper agricultural practices can also introduce risks into the equation. Herbicide drift can be a combination of improper practices and environmental conditions which can create a potential yield loss. As traditional assessment of plant damage is often imprecise and time consuming, the ability of remote and proximal sensing techniques to monitor various bio-chemical alterations in the plant may offer a faster, non-destructive and reliable approach to predict yield loss caused by herbicide drift. This paper examines the prediction capabilities of partial least squares regression (PLS-R) models for estimating yield. Models were constructed with hyperspectral data of a cotton crop sprayed with three simulated doses of the phenoxy herbicide 2,4-D at three different growth stages. Fibre quality, photosynthesis, conductance, and two main hormones, indole acetic acid (IAA) and abscisic acid (ABA) were also analysed. Except for fibre quality and ABA, Spearman correlations have shown that these variables were highly affected by the chemical. Four PLS-R models for predicting yield were developed according to four timings of data collection: 2, 7, 14 and 28 days after the exposure (DAE). As indicated by the model performance, the analysis revealed that 7 DAE was the best time for data collection purposes (RMSEP = 2.6 and R2 = 0.88), followed by 28 DAE (RMSEP = 3.2 and R2 = 0.84). In summary, the results of this study show that it is possible to accurately predict yield after a simulated herbicide drift of 2,4-D on a cotton crop, through the analysis of hyperspectral data, thereby providing a reliable, effective and non-destructive alternative based on the internal response of the cotton leaves.

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The Cotton and Grain Adoption Program of the Queensland Rural Water Use Efficiency Initiative is targeting five major irrigation regions in the state with the objective to develop better irrigation water use efficiency (WUE) through the adoption of best management practices in irrigation. The major beneficiaries of the program will be industries, irrigators and local communities. The benefits will flow via two avenues: increased production and profit resulting from improved WUE and improved environmental health as a consequence of greatly reduced runoff of irrigation tailwater into rivers and streams. This in turn will reduce the risk of nutrient and pesticide contamination of waterways. As a side effect, the work is likely to contribute to an improved public image of the cotton and grain industries. In each of the five regions, WUE officers have established grower groups to assist in providing local input into the specific objectives of extension and demonstration activities. The groups also assist in developing growers' perceptions of ownership of the work. Activities are based around four on-farm demonstration sites in each region where irrigation management techniques and hardware are showcased. A key theme of the program is monitoring water use. This is applied both to on-farm storage and distribution as well as to application methods and in-field management. This paper describes the project, its activities and successes.

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Considerable concern has been expressed by the Australian wool industry regarding the contamination of the clip with coloured or kempy fibres from imported breeds of sheep. As part of the evaluation of imported sheep meat breeds in western Queensland, a study is examining fibre growth and transfer of fibres and the potential to cause physical contamination of Merino fleeces. The breeds of concern in this study are the Damara, a fat-tailed breed with a hairy, coloured fleece and the Dorper which has both pigmented fibres and a kempy fleece which is shed cyclically. Three groups of Merino 27 ewes were mated to Merino, Damara and Dorper rams respectively and fibre transfer to the Merino ewes during mating, from lambing to weaning and during grazing, assessed. Both a direct field method and a laboratory method (Hatcher 1995) are being used. Those measured by direct count were measured immediately after joining and 2, 4 and 8 weeks subsequently. and the other ewes were shorn and sampled and measured in the laboratory using the dark fibre detector. This paper presents preliminary findings of those ewes monitored by the direct field method. 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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Mounting levels of insecticide resistance within Australian Helicoverpa spp. populations have resulted in the adoption of non-chemical IPM control practices such as trap cropping with chickpea, Cicer arietinum (L.). However, a new leaf blight disease affecting chickpea in Australia has the potential to limit its use as a trap crop. Therefore this paper evaluates the potential of a variety of winter-active legume crops for use as an alternative spring trap crop to chickpea as part of an effort to improve the area-wide management strategy for Helicoverpa spp. in central Queensland’s cotton production region. The densities of Helicoverpa eggs and larvae were compared over three seasons on replicated plantings of chickpea, Cicer arietinum (L.), field pea Pisum sativum (L), vetch, Vicia sativa (L.) and faba bean, Vicia faba (L.). Of these treatments, field pea was found to harbour the highest densities of eggs. A partial life table study of the fate of eggs oviposited on field pea and chickpea suggested that large proportions of the eggs laid on field pea suffered mortality due to dislodgment from the plants after oviposition. Plantings of field pea as a replacement trap crop for chickpea under commercial conditions confirmed the high level of attractiveness of this crop to ovipositing moths. The use of field pea as a trap crop as part of an areawide management programme for Helicoverpa spp. is discussed.

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Alternaria leaf blight is the most prevalent disease of cotton in northern Australia. A trial was conducted at Katherine Research Station, Northern Territory, Australia, to determine the effects of foliar application of potassium nitrate (KNO3) on the suppression of Alternaria leaf blight of cotton. Disease incidence, severity and leaf shedding were assessed at the bottom (1-7 nodes), middle (8-14 nodes) and the top (15+ nodes) of plants at weekly intervals from 7 July to 22 September 2004. Disease incidence, severity and shedding at the middle canopy level were significantly higher for all treatments than those from bottom and top canopies. Foliar KNO3, applied at 13 kg/ha, significantly (P < 0.05) reduced the mean disease incidence, severity and leaf shedding assessed during the trial period. KNO 3 significantly (P < 0.001) reduced the disease severity and leaf shedding at the middle canopy level. Almost all leaves in the middle canopy became infected in the first week of July in contrast to infection levels of 50-65% at the bottom and top of the canopy. Disease severity and leaf shedding in the middle canopy were significantly (P < 0.05) lower in KNO 3-treated plots than the control plots from the second and third weeks of July to the second and third weeks of August. This study demonstrates that foliar application of KNO3 may be effective in reducing the effect of Alternaria leaf blight of cotton in northern Australia.