Objectives I. Continue to develop entomoLOGIC and related management packages incorporating the latest research results and management practices. 2. Validate entomoLOGIC and demonstrate IPM systems on a commercial scale. 3. Promote the continued adoption of entomoLOGIC and provide training and support for growers and consultants in all regions.

The aim of this project is to generate and evaluate transgenic cotton plants that are expected to have improved tolerance to fungal disease, in particular Verticillium and Fusarium wilts.

This study is a baseline biodiversity survey of the principal soil faunal groups found in irrigated cotton fields of north western New South Wales. Field work was conducted on commercial cotton fanns located in the Macquarie. lower Narnoi, and Gwydir valleys. The various growers and agronomists involved were practitioners of innovative and 'best managemenf practices. Detailed infonnation pertaining to soil properties, cropping history, and calendar of operations were collated for all fields. Fields sampled differed in (i) the age of cotton production and (ii) the crop protection practices used to control insect pests. Specific objectives of this project were: (1) to characterise and compare the relative abundance and species diversity of dominant ecological groups of soil meso-and macrofauna in irrigated cotton fields and their respective adjoining remnant sites; (2) to monitor short-tenn seasonal dynamics of these soil surface-active and in-situ invertebrate populations during the different phenological phases of the cotton crop; and (3) to devise a sampling protocol that is both repeatable and feasible.

The purpose of the tour was to study and experience through participation the development and extension methodologies and practices used in the transfer and adoption of new technology in the American cotton industry by extension personnel, consultants and growers by the cooperative extension systems of the Universities and the USDA. The objective was to seek, learn and experience methodologies and practices which have potential application to enhance the technology transfer and adoption programs of the Qld. Department of Primary Industries and the Cooperative Research Centre for Sustainable Cotton production of which DPI is a core partner. Simultaneously, cotton crop management practices, particularly those related to reduced tillage and integrated pest management, were investigated

Objectives The aim of the project is to maintain the upgraded DEC computing facility at Myall Vale for the term of the project.

Objectives (i) To provide full time management of the computer system at Australian Cotton Research Institute. (ii) To ensure optimal provision and use of computer resources for research and industry.

This project upgraded the harvesting equipment for CSIRO cotton breeding experiments, particularly for those sites located off the Australian Cotton Research Institute. The previous method of harvesting was heavily reliant on manual labour and bagging of samples from research plots. The new method is automated and computerised to speed up harvest.

Objectives: To purchase a new nitrogen analyser in order to provide faster, more accurate analysis of cotton samples for a wide range of projects

Over the period from 1990 to 1993, research was carried out investigating the regrowth of Australian cotton varieties after damage by haiI. The work was funded by the Cotton Research and Development Corporation and carried out in co-operation with the loss adjusters to the Australian cotton industry, Agricultural Loss Management Group. By comparing the regrowth characteristics of Australian cotton varieties, following simulated hail damage at various stages of plant development, the aim was to test the accuracy of the loss assessment procedures currently used in cotton hail loss adjustment and determine whether it was appropriate to apply these procedures to loss adjustment for the whole range of Australian bred varieties now grown.

A vision guidance system has been designed, built and commissioned which steers a tractor relative to the rows of a crop such as cotton. It was required to be insensitive to additional visual "noise" from weeds, while tolerating the fading out of one or more rows in a barren patch of the field. The system integrates data from several crop rows, testing for image quality. At the same time, the data processing requirements have been limited by the use of frame sequential strategies to reduce the image space which must be processed. The current prototype employs an embedded 386 PC notebook computer and shows great promise of cost effective commercial exploitation. Experimental results are reported and further sensing systems are explored to enhance performance in difficult environments.