The monitoring of the biological growth of field crops is important for planning and scheduling agricultural applications. In order to assess biological growth pattern and, dry matter accumulation of Yeniceri oat variety were obtained 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, Weibull, and Ratkowsky sigmoidal growth models are fitted to actual growth data and their predictions were compared. Results suggested that all sigmoidal growth models successfully explained oat dry matter accumulation a high R-2 values (over 99%) and low mean square errors, Weibull model fitted lower than others for first year with an R-2 value under 99%. Dry matter accumulation was also investigated as a result of average temperature and precipitation with stepwise regression. Results indicated that average weather temperature has a similar pattern across both growing seasons and has a major influence on dry matter accumulation.