his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Wheat variety identification using genetic variations
University of Skövde, Department of Computer Science.
2003 (English)Independent thesis Advanced level (degree of Master (One Year))Student thesis
Abstract [sv]

There is a continuous development of different crop varieties in the crop trade. The cultivated crops tend to be more and more alike which require an effective method for crop identification. Crop type and crop type purity has become a quality measure in crop trade both nationally and internationally. A number of well known quality attributes of interest in the crop trade can be correlated to the specific crop type and therefore it is of great importance to reliably be able to identify different crop varieties. It is well known from the literature that there exist genomic variations at the nucleotide level between different crop varieties and these variations might potentially be useful for automated variety identification.

This project deals with the crop variety identification area where the possibilities of distinguishing between different wheat varieties are investigated. Experience from performing wheat variety identification at protein level has shown unsatisfactory results and therefore DNA-based techniques are proposed instead. DNA-based techniques are dependent upon the availability of sequence data from the wheat genome and some work has concerned examining the availability of sequence data from wheat. But the focus of the work has been on defining a method for computational detection of single nucleotide variations in ESTs from wheat and to experimentally test that method. Results from these experiments show that the method defined in this project detects polymorphic variations that can be correlated to variety variations

Place, publisher, year, edition, pages
Skövde: Institutionen för datavetenskap , 2003. , 173 p.
Keyword [en]
single nucleotide polymorphism (SNP), wheat variety identification, clustering, alignment
National Category
Computer Science
Identifiers
URN: urn:nbn:se:his:diva-821OAI: oai:DiVA.org:his-821DiVA: diva2:3233
Presentation
(English)
Uppsok
Technology
Supervisors
Available from: 2008-02-15 Created: 2008-02-15 Last updated: 2010-02-11

Open Access in DiVA

fulltext(14457 kB)126 downloads
File information
File name FULLTEXT02.pdfFile size 14457 kBChecksum SHA-512
6d4022ff491ac7a044cdfcf6bf8beceea8163764554f9ede36cac94e1d3faa77c49576b8b27b878572a98a80280a7bed6c981014168ce7f047756a76e0fb569b
Type fulltextMimetype application/pdf

By organisation
Department of Computer Science
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 217 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 710 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf