Genetika 2018 Volume 50, Issue 3, Pages: 1045-1054
https://doi.org/10.2298/GENSR1803045C
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Evaluation of different sigmoidal growth models and climate parameters for dry matter accumulation of oat

Coşkun Yalçın (Çanakkale Onsekiz Mart University, Lapseki Vocational College, Çanakkale, Turkey)

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 Yeniçeri oat variety were obtained in Çanakkale 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 R2 values (over 99%) and low mean square errors, Weibull model fitted lower than others for first year with an R2 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.

Keywords: dry matter, growth models, oat, stepwise regression, temperature