THE ANALYSIS OF SLAVONIAN WINES WITH APPLICATION OF CLUSTER ANALYSIS

master's thesis

• Author: Ana Jelčić
• Mentor: Mirjana Pejić Bach (mentor)
• Committee member: Ivan Strugar (predsjednik povjerenstva)
• Granter: University of Zagreb; Faculty of Economics and Business; (Department of Informatics); Zagreb
• Defense date and country: 2020-09-23, Croatia
• Scientific / art field, discipline and subdiscipline: SOCIAL SCIENCES; Economics

Abstract

There is ten millennia where people all over the world enjoy in various delicious wines. There are also numerous evidences that ancient people made and drank wine. Wine from our territories was so good that even Greek writer Agatarid in the second century BC wrote:” On Vis island in Adriatic Sea, a wine is produced that is better than all others if compared with it”. There are many details and things that people deal with, but wine falls into the category of creative art in which the winemaker not only creates pleasure for himself but also for others to enjoy the perfect wine. It is a love that involves a lot of care, time and attention, but once you discover it, you become addicted to it. In this thesis two completely unrelated fields are combined - informatics and agronomy. Since they do not have any similar segment, the work is a very different and instructive examination. The purpose of this master thesis was to examine and analyse the wines in Slavonia but with the application of cluster analysis. The original inspiration came by an interest in the breadth of the possibility of testing through cluster analysis and since Slavonia is familiar and offering a large assortment of wines and winemakers, the goal become to do the analysis in that matter.

• Keywords: Slavonian wine; Cluster analysis; White wine; Red wine
• Language: english
• URN:NBN: urn:nbn:hr:148:490600
• Study programme: Title: Economics; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra ekonomije (magistar/magistra ekonomije)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2020-09-24 13:28:34