%0 Journal Article %T Application of unsupervised weighting algorithms for identifying important attributes and factors contributing to grain and biological yields of wheat %J Crop Breeding Journal %I Seed and Plant Improvement Institute %Z 2008-868X %A Bijanzadeh, E. %A Emam, Y. %A Ebrahimi, E. %A Ebrahimi, M. %D 2012 %\ 07/01/2012 %V 2 %N 2 %P 111-117 %! Application of unsupervised weighting algorithms for identifying important attributes and factors contributing to grain and biological yields of wheat %K attribute weighting %K Data Mining %K unsupervised model %K Wheat %R 10.22092/cbj.2012.100427 %X To identify important attributes/factors that contribute to grain and biological yields of wheat, 9912 sets of diverse data from field studies were extracted, and supervised attribute-weighting models were employed. Results showed that when biological yield was the output, grain yield, nitrogen applied, rainfall, irrigation regime, and organic content were the most important factors/attributes, highlighted by 9, 7, 5, 3 and 3 weighting models, respectively. In contrast, when grain yield was the output, biological yield, location, and genotype were identified by 8, 6, and 5 weighting models, respectively. Also, five other features (cropping system, organic content, 1000-grain weight, spike number m-2 and soil texture) were selected by three models as the most important factors/attributes. Field water status, such as the irrigation regime or the amount of rainfall, was another important factor related to the biological or grain yield of wheat (weight ≥ 0.5). Our results showed that attribute/factor classification by unsupervised attribute-weighting models can provide a comprehensive view of the important distinguishing attributes/factors that contribute to wheat grain or biological yield. This is the first report on identifying the most important factors/attributes contributing to wheat grain and biological yields-using attribute-weighting algorithms. This study opened a new horizon in wheat production using data mining. %U https://cbjournal.areeo.ac.ir/article_100427_8c7511bf4fc18c57533a93112f7e585d.pdf