Dean Diepeveen

The manual classification of plants’ species based on images of their leaves is timeconsuming and prone to human error. It also requires expert in specific knowledge agricultural domain. The essence of computer-based plants classification system is to augment the manual type so as to increase speed, efficiency, and accuracy of recognition. This study shows the basic principles behind the application of image processing techniques in agriculture. It shows how descriptors are extracted from the images of plant species and further processed for automated image classification of plant species.

This presentation provides a report on two major investments in wheat molecular biology, namely the sequencing of chromosome 7A and the Australia - China Centre for Wheat Improvement (ACCWI). The sequencing of chromosome 7A project (GRDC/BioPlatforms Australia funded) is supported by the International Wheat genome Sequencing Consortium (IWGSC) and has established the physical assembly of BAC clones prepared from flow sorted ditelocentric chromosomes. The Hiseq sequencing of BAC pools (AGRF) is approximately two thirds completed. The BAC pools being sequenced comprise contigs of 1 - 2 Mb genomic DNA which were assembled using the SNAPshot DNA fingerprinting of individual BACs with 5 restriction endonucleases. Anchoring of the sequence assemblies is being achieved using the 9K and 90K SNP chip based molecular genetic maps as well as the standard deletion maps for chromosome 7A and the published 7A genome sequence for Triticum urartu . The new ACCWI will act as the conduit through which in - depth genome sequence information for chromosome 7A as well as the other chromosomes (through the IWGSC) can be integrated into broader molecular breeding initiatives aimed at increasing the accuracy and efficiency with which wheat phenotypes can be defined. The ACCWI core phenotype targets will focus on grain yield and quality with the characterization of individual quality parameters being undertaken through the use of mass spectroscopy to generate grain protein profiles/signatures, the technology of which is dependent on genome sequences to define genes. The ACCWI - strategy for linking grain protein profiles/signatures to agronomic traits of interest to marketers of grains and breeders will be discussed.

Data has been collected over the past 6 years (1996-2001) on wheat grain quality for varieties in the Department of Agriculture’s Crop Variety Testing program of Western Australia. This data has been subjected to multivariate analyses to elucidate GxE features. A key aspect has been the relationship between the Principle Component scores and the dollar values determined by the Golden Rewards scheme.

Key Points Yield losses in wheat from root lesion nematode (RLN) were assessed at up to 5 per cent in 1999. Soil populations vary in different rotations. Differences in susceptibility among different crops can be used to manage soil populations to minimise impact from RLN. Though rare in Western Australia, cereal cyst nematode can have a major effect on yield if populations build up through consecutive cereal cropping. Doolup barley is resistant Aim Hosting ability and its effect on population dynamics of root nematodes is being studied to enable improved management of cereal nematodes.