Kavuzsuz yulaf genotiplerinde büyümenin doğrusal olmayan regresyon modelleri ve Zadoks büyüme skalası ile belirlenmesi

Abstract

Increasing popularity of the naked oat (Avena nuda L.) in the food industry promoted the value of its cultivation. Despite the growing demand for the naked oat grain, the research about its agronomy is currently limited. Aim of this study were to evaluate the growth characteristics of naked oat with nonlinear regression models. Field trials were conducted according to the split block design with three replications. Our growth data consisted of weekly dry weight observations covering the entire growth span of four naked oat genotypes (211 samplings in total) for two growing seasons. Curve fitting successfully revealed the genotypic and environmental variations when sampling weeks and Zadoks growth stages were used as time measures in two separate analyses. According to results, last week of tillering stage were found to be critical for naked oat when the rate of growth reached its peak around booting stage. Implementing Zadoks growth stage as time measure in growth analysis had several drawbacks but revealed unique interpretations about the crop development and environmental variation. Logistic, Logistic Power and Ratkowsky models were the best fitting models to assess weekly dry weight increases with the coefficient of determinations ranging from 0.99177 to 0.94206.