Genetika 2018 Volume 50, Issue 3, Pages: 1045-1054
https://doi.org/10.2298/GENSR1803045C
Full text ( 519 KB)
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