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<p>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.</p><p>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</p>

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