Datenbestand vom 13. Juni 2019
Tel: 089 / 66060798
Mo - Fr, 9 - 12 Uhr
Fax: 089 / 66060799
DER VERLAG IST IN DER ZEIT VOM 12.06.2019 BIS 23.06.2019 AUSCHLIESSLICH PER EMAIL ERREICHBAR.
aktualisiert am 13. Juni 2019
978-3-8439-0417-9, Reihe Informatik
A Collaborative Knowledge Management Approach to Provide Better Agricultural Decision Support
283 Seiten, Dissertation Technische Universität Kaiserslautern (2012), Hardcover, B5
According to the Food and Agriculture Organization of the United Nations, with the world population projected to surpass 9 billion people by 2050, agriculture is facing huge challenges in providing enough food to the extra two billion people, and although increasing the agricultural food production in the past has been mostly done by increasing the surface or arable land, 90 percent of the extra production in industrial countries must be achieved through higher crop yields alone.
The agricultural sector is highly competitive and farmers not only have to consider agricultural and ecological but also economical and political factors. In Europe, public agricultural institutions provide farmers with the necessary decision support to help them optimize their production while considering those factors. To further improve the crop yields, forecasts need to be more accurate and geographically more differentiated to reveal local optimization opportunities. However, public agricultural institutions are currently facing critical knowledge management issues in the development and the maintenance of these decision support tools, which prevent them from providing more accurate forecasts.
The aim of this thesis is to make a contribution to fighting world hunger by supporting the development of better agricultural decision support tools to help farmers increase their crop yields. I analyze the current knowledge issues between public agricultural institutions and farmers and show that these institutions lack the required accurate geo-data to provide farmers with better decision support, but also that farmers could potentially contribute to the acquisition of this geo-data.