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.

Avaliação das propriedades das fibras de algodões coloridos naturalmente e ecologicamente corretas cultivados nos assentamentos do município de Guamaré/RN

In this work evaluate the technical characteristics of the fibers grown in settlements Guamaré, colored cotton seeds were donated existing in the Germplasm Bank of Embrapa Cotton. We sought through the breeding program, raising the resistance, fineness, length and uniformity of cotton fibers, as well as stabilize the staining of fibers in the BRS Topaz, BRS Brown and BRS Green shades and raise their productivity in the field. First, the individual selections to test progeny seeds, and thereafter the hybridization method followed by family selection to obtain variations in the color tones were performed. The BRS Topaz, BRS Brown and BRS Green varieties were produced, analyzed and compared with existing cottons in the region which is the White cotton. The properties amount of impurities and neps, length, length uniformity, short fiber content, fineness and tensile strength of the fibers were sized in Classifiber, NATI, Pressley and Micronaire devices. 10 trials each with 10 tests for all four fiber types were carried out. The White and Topaz fibers showed greater length (32-34mm) and greater resistance (7.94 lb/mg and 7.97 lb/mg respectively) and showed finesse with lower micronaire index 3,71μg/inch and 3, 73μg/inch and a low rate of short fibers. The results were very promising for the use of genetically improved cotton in the manufacturing of fabric and yarn in the textile industry. The fibers were brown colored cotton used in the manufacture of a composite fiber with thermoplastic resin

What influences fungal communities in cotton soils

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.

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..