Growth and development of three key summer grasses in Australian cotton systems

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.

New developments in UAV remote sensing for pest management and the implications for cotton

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.

Response of irrigated cotton to applied nitrogen

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..

The importance of cotton disease surveys in Queensland for monitoring endemic diseases and detecting new pathogens and pests

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.

Composts addition may improve biology in cotton soils

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.

The case for cotton: a paper read before the Kosmos Club and published by request

The bulletin argues against diversification of lower yielding crops for cotton. The argument is primary economic.

Effects of silicon treatment and inoculation with Fusarium oxysporum f. sp. vasinfectum on cellular defences in root tissues of two cotton cultivars

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.

Hyperspectral sensing to detect the impact of herbicide drift on cotton growth and yield

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.

Considerations about the biodegradation of Cry1Ac protein from Bt cotton by rhizobacteria.

2009

Geminivirus Rep Protein Interferes with the Plant DNA Methylation Machinery and Modifies the Host Epigenome

The apparent simplicity of viruses hides the complexity of their interactions with their hosts. Viruses are masters at circumventing host defenses and manipulating the cellular environment for their own benefit. The replication of the largest known family of single-stranded DNA viruses, Geminiviridae, is impaired by DNA methylation and Arabidopsis mutants affected in cytosine methylation are hypersusceptible to geminivirus infection. This implies that plants might use methylation as a defense against geminiviruses and that the viral genome is a target for plant DNA methyltransferases. We have found a novel counter-defense strategy used by geminiviruses, that reduces the expression of the plant maintenance DNA methyltransferases, MET1 and CMT3, in both, locally and systemically infected tissues. Furthermore, we demonstrated that the virus-mediated repression of these two maintenance DNA methyltransferases is widely spread among different geminivirus species. Additionally, we identified Rep as the geminiviral protein responsible for the repression of MET1 and CMT3, and another viral protein, C4, as an ancillary player in MET1 downregulation. The presence of Rep, suppresses TGS of an Arabidopsis transgene and of host loci whose expression is strongly controlled by CG methylation. Bisulfite sequencing analyses showed that the expression of Rep caused a substantial reduction in the levels of DNA methylation at CG sites. Our findings suggest that Rep, the only viral protein essential for geminiviral replication, displays TGS suppressor activity through a mechanism distinct from the one thus far described for geminiviruses.

Geographic Provenancing of Unprocessed Cotton Using Elemental Analysis and Stable Isotope Ratios

Cotton is the most abundant natural fiber in the world. Many countries are involved in the growing, importation, exportation and production of this commodity. Paper documentation claiming geographic origin is the current method employed at U.S. ports for identifying cotton sources and enforcing tariffs. Because customs documentation can be easily falsified, it is necessary to develop a robust method for authenticating or refuting the source of the cotton commodities. This work presents, for the first time, a comprehensive approach to the chemical characterization of unprocessed cotton in order to provide an independent tool to establish geographic origin. Elemental and stable isotope ratio analysis of unprocessed cotton provides a means to increase the ability to distinguish cotton in addition to any physical and morphological examinations that could be, and are currently performed. Elemental analysis has been conducted using LA-ICP-MS, LA-ICP-OES and LIBS in order to offer a direct comparison of the analytical performance of each technique and determine the utility of each technique for this purpose. Multivariate predictive modeling approaches are used to determine the potential of elemental and stable isotopic information to aide in the geographic provenancing of unprocessed cotton of both domestic and foreign origin. These approaches assess the stability of the profiles to temporal and spatial variation to determine the feasibility of this application. This dissertation also evaluates plasma conditions and ablation processes so as to improve the quality of analytical measurements made using atomic emission spectroscopy techniques. These interactions, in LIBS particularly, are assessed to determine any potential simplification of the instrumental design and method development phases. This is accomplished through the analysis of several matrices representing different physical substrates to determine the potential of adopting universal LIBS parameters for 532 nm and 1064 nm LIBS for some important operating parameters. A novel approach to evaluate both ablation processes and plasma conditions using a single measurement was developed and utilized to determine the “useful ablation efficiency” for different materials. The work presented here demonstrates the potential for an a priori prediction of some probable laser parameters important in analytical LIBS measurement.

The legitimation of development and GM crops: The case of Bt Cotton and Indebtedness in Telangana, India

This study explores the relation between Bt cotton adoption and farmer suicides in India. This is undertaken through comparing the debt levels of Bt cotton cultivators with those adopting alternative organic and Non-Pesticide Management (NPM) methods. The study involves a total of 26 participants in three villages in Telangana, India. It argues that measures of indebtedness need to be adopted as part of assessments of both Bt cotton and development policy.

The legitimation of risk and Bt cotton: a case study of Bantala village in Warangal, Andhra Pradesh, India

This article explores Ulrich Beck’s theorisation of risk society through focusing on the way in which the risk of Bt cotton is legitimated by six cultivators in Bantala, a village in Warangal, Andhra Pradesh, in India. The fieldwork for this study was conducted between June 2010 and March 2011, a duration chosen to coincide with a cotton season. The study explores the experience of the cultivators using the ‘categories of legitimation’ defined by Van Leeuwen. These are authorisation, moral evaluation, rationalisation and mythopoesis. As well as permitting an exploration of the legitimation of Bt cotton by cultivators themselves within the high-risk context of the Indian agrarian crisis, the categories also serve as an analytical framework with which to structure a discourse analysis of participant perspectives. The study examines the complex trade-off, which Renn argues the legitimation of ambiguous risk, such as that associated with Bt technology, entails. The research explores the way in which legitimation of the technology is informed by wider normative conceptualisations of development. This highlights that, in a context where indebtedness is strongly linked to farmer suicides, the potential of Bt cotton for poverty alleviation is traded against the uncertainty associated with the technology’s risks, which include its purported links to animal deaths. The study highlights the way in which the wider legitimation of a neoliberal approach to development in Andhra Pradesh serves to reinforce the choice of Bt cotton, and results in a depoliticisation of risk in Bantala. The research indicates, however, that this trade-off is subject to change over time, as economic benefits wane and risks accumulate. It also highlights the need for caution in relation to the proposed extension of Bt technology to food crops, such as Bt brinjal (aubergine).

Risk definition and the struggle for legitimation: a case study of Bt cotton in Andhra Pradesh, India

This article explores the struggle for legitimation associated with the attempt to define the risk of Bt cotton, a genetically modified crop, in Andhra Pradesh, India. Beck asserts that, given the uncertainty associated with risk society, efforts to define risk are creating the need for a new political culture. This article argues that this political culture emerges from attempts to legitimate power within risk definition. This is examined using critical discourse analysis on interview excerpts with key figures in the Bt cotton debate. Legitimation is explored using the categories of legitimation developed by Van Leeuwen. These are (a) authorisation; (b) moral evaluation; (c) rationalisation; and (d) mythopoesis. The analysis highlights that the political culture which emerges in response to risk society is in a state of constant flux and contingent upon the ongoing struggle for legitimation with regard to the definition of risk.

Development of antibacterial ZnO-loaded cotton fabric based on in situ fabrication

A method provided for the deposition of nanostructured ZnO on cotton fabric to introduce antibacterial functionality was presented in this article. This strategy enabled fabric to be coated with inorganic-based functional materials through in situ synthesis of nanoparticles using ultrasonic irradiation. The amino-terminated silicon sol (AEAPTS) was employed to generate nanostructured ZnO, and the mechanism of the ultrasound-assisted coating was proposed. Antibacterial activities, UV protection and other properties of ZnO-loaded cotton characterized by SEM, FTIR, XRD and TGA were investigated. The results indicated that ZnO-loaded cotton exhibited excellent UV protective property, efficient antibacterial activities, well water-resistant effect, together with moderate cytotoxicity against L929 and lower tensile strength. The developed method provides not only a facile way for in situ synthesis of ZnO on textile but also the production of antibacterial materials for healthcare applications.