Rapeseed (Brassica napus) is an important oilseed crop worldwide. In order to get the genetic similarity present in a set of oilseed rape cultivars, 32 cultivars have been analyzed at the DNA level by Random Amplified Polymorphic (RAPD) technique. RAPD analysis was performed with 8 decamer primers to produce reliable polymorphic DNA bands ranging in molecular weight from 238 -961 bp. A total of 72 polymorphic bands from 96 reproducible bands were obtained. Based on these data, genetic similarity (GS) was estimated between 0.608 ("Uspekh" versus "Libritta") and 0.731 ("Libritta" versus "Uspekh"). UPGMA cluster analysis carried out on these data indicates a good fit of the respective clusters to genetic similarity data. The correlation of cluster analyses to pedigree information and the impact on parental genotype selection has been taken into discussion.

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Bio-diesel is a renewable and environmentally friendly alternative fuel that can be used in Diesel engines with little or no modification. Low cost feed stocks, such as waste oils, agricultural products, are important for low cost bio-diesel production. Rape is the most appropriate agricultural culture for this purpose, mainly due to the high fat content. In this study were evaluated the performances of 3 cultivated varieties rapes compared to new commercial types. Both, cultivated varieties and commercial sorts were cultivated using usual technologies on agricultural lands from Iasi County, Romania. The performances evaluation was conducted by analyzing the fat content from seeds for each cultivated varieties and commercial sorts, correlated with seeds production on hectare and calculating the content of fat for each culture, in order to obtain the possible production of biodiesel. The results showed that the three new cultivars are more recommended for bio-diesel production due to a higher content of fat in seeds in comparison with analyzed fat content for commercial sorts. Thus, these new cultivars could be better used for bio-diesel production at industrial level.

Decision making in environments that do not allow much algorithmic modeling is not easy. Even more difficulties arise when part of the knowledge is expressed through linguistic terms instead of numeric values. Agricultural Sciences are such environments and Plant Breeding is one of them. This is why Fuzzy Theories can be very useful in building Decision Support Systems in this field. This chapter presents a number of Fuzzy methods to be used for decision support in the selection phase of Plant Breeding programs. First, the utilization of the Fuzzy Multi-Attribute Decision Model is discussed and a case study is analyzed. Then, two Fuzzy Querying methods are suggested. They can be used when a database must be searched in order to extract the information to be utilized in decision making. In this context, the concept of Fuzzy Similarity is important. Ways to employ it in database querying are suggested.