Dean Diepeveen

This chapter reviews developments in the use of artificial intelligence (AI) techniques to improve the functionality of decision support systems (DSS) in agriculture. It reviews the use of techniques such as data mining, artificial neural networks (ANN), Bayesian networks (BN), support vector machines (SVM) and association rule mining. It includes a number of case studies of practical application of these techniques to support decision making by farmers.

The integration of biotechnology concepts and technologies are now accepted as part of an overall strategy in plant breeding as the multidisciplinary approaches that characterize crop improvement enable a holistic systems approach to the study of expression and regulation of genes (and gene networks). Speedy delivery of new genotypes for planting is crucial and marker-assisted selection applications provide more informative diagnostic probes for identifying favorable combinations of alleles in new germplasm. Components of plant yield and grain quality are complex and this article discusses the technical advances in the context of developing plants that can contribute to increased production to address broader issues of climate change and providing food for an increasing world population.