Redesigning IT systems for specific user groups encompasses a lot of effort with respect to analysing and understanding user behaviour. The goal of this paper is to provide insights into patterns of behaviour of agricultural users, during the usage of a decision support system called OPTIRas (TM). This system aids agricultural users in their cultivar selection activities. We analyse logs resulting from OPTIRas (TM), and we get insights into user's navigational patterns. We claim that the results of our analysis can be used to support the redesign of decision support systems in order to address specific agricultural users' characteristics.
Creating adaptive systems becomes increasingly attractive in the context of specific groups of users, such as agricultural users. This group of users seems to differ with respect to information processing, knowledge management and learning styles. In this work we aim to offer directions toward increasing decision support systems usability, by tailoring toward user learning styles. The results show that decision support systems need to be redesigned toward providing agricultural users with a more efficient time management and study environment, and facilitating group interaction.
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Agricultural by-products, that is primary residue, industrial by-products and animal manure, are an important source of nutrients and carbon for maintaining soil quality and crop production but can also be valorised through treatment pathways such as fermentation, incineration or a combination of these called bio-refinery. Here, we provide an overview of opportunity to reduce environmental impact of valorising agricultural by-products. We estimate the available by-products in Northwestern Europe as a case study and the maximum and realistic greenhouse gas reduction potentials. Availability, collectability, the original use and environmental impact including land use changes, soil carbon sequestration and pollution swapping are discussed as critical factors when valorising agricultural by-products.
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