Optical peanut yield monitor: Development and testing

An optical peanut yield monitor was developed, fabricated, and field-tested. The overall system includes an optical mass-flow sensor, a GPS receiver, and a data acquisition system. The concept for the mass-flow sensor is based on that of the cotton yield-monitor sensor developed previously by Thomasson and Sui (2000). A modified version of the sensor was designed to be specific to peanut mass-flow measurement. Field testing of the peanut yield monitor was conducted in Australia during the May 2003 harvest. After subsequent minor modifications, the system was more extensively tested in Mississippi in October of 2003 and November of 2004. Test results showed that the output of the peanut mass-flow sensor was very strongly correlated with the harvested load weight, and the system's performance was stable and reliable during the tests.

Use of optical density as a measure of Claviceps africana conidial suspension concentration

Sorghum ergot, caused by Claviceps africana, has remained a major disease problem in Australia since it was first recorded in 1996, and is the focus of a range of biological and integrated management research. Artificial inoculation using conidial suspensions is an important tool in this research. Ergot infection is greatly influenced by environmental factors, so it is important to reduce controllable sources of variation such as inoculum concentration. The use of optical density was tested as a method of quantifying conidial suspensions of C. africana, as an alternative to haemocytometer counts. This method was found to be accurate and time efficient, with possible applications in other disease systems.

Online identification guides for Australian smut fungi (Ustilaginomycotina) and rust fungi (Pucciniales)

Interactive identification keys for Australian smut fungi (Ustilaginomycotina and Pucciniomycotina, Microbotryales) and rust fungi (Pucciniomycotina, Pucciniales) are available online at http://collections.daff.qld.gov.au. The keys were built using Lucid software, and facilitate the identification of all known Australian smut fungi (317 species in 37 genera) and 100 rust fungi (from approximately 360 species in 37 genera). The smut and rust keys are illustrated with over 1,600 and 570 images respectively. The keys are designed to assist a wide range of end-users including mycologists, plant health diagnosticians, biosecurity scientists, plant pathologists, and university students. The keys are dynamic and will be regularly updated to include taxonomic changes and incorporate new detections, taxa, distributions and images. Researchers working with Australian smut and rust fungi are encouraged to participate in the on-going development and improvement of these keys.