Computer image analysis and artificial neuron networks in the qualitative assessment of agricultural products

Article history: Received: June 2015 Received in the revised form: July 2015 Accepted: August 2015 The increasing use of modern information technology in agriculture involves an ever wider range of production, planning, monitoring and marketing processes. Information technologies are being applied in animal and plant production, and recent decades have witnessed a dynamic growth in research into artificial intelligence and thus into advisory (expert) systems such as artificial neuron networks. Obviously this is not the result of a coincidence or a temporary trend, this dynamic development has been made possible thanks to the rapid advancement of computer technology, allowing ever increasing speeds and volumes of data collection and processing. A large number of research-scientific work with the use of computer image analysis, computer-aided decision making and state of the art modelling tools, including artificial neuron networks, is carried out within the scope of agricultural engineering. The computer-aided decision making process in the area of the qualitative assessment of agri-food products is one of those areas using computer image analysis and neuron modelling. The objective of this research project was to develop and describe a computer image analysis method based on the example of carrots and lyophilisation dehydrates for the purpose of the qualitative assessment and classification of individual categories in the analysed sample in terms of quality.