Monitoring biological growth of field crops is important for planning and timing agricultural practices. In order to assess biological growth pattern of dry matter accumulation in triticale Egeyildizi triticale variety were grown in canakkale conditions in 2012-2013 and 2013-2014 growing seasons with continuous plant samplings from seedling emergence until seed maturation. Gompertz, Logistic, Logistic Power and Richards growth models are fitted to actual growth data and their predictions were compared. Results suggested that all sigmoidal growth models successfully explained triticale dry matter accumulation over 98 % R-2 values and low mean square errors, Richards model fitted best for both years with an R-2 value over 99 %. Dry matter accumulation were also investigated as a result of average temperature, precipitation, growth degree days and cumulative growth degree days with stepwise regression. Rresults indicated that average weather temperature had a similar pattern across both growing seasons and had a major influence on dry matter accumulation. Since Richards sigmoidal growth model may be adequately described growth pattern of triticale by generally high R-2 with lower Mean Square Error (MSE) values.