Predicting time trend of dry matter accumulation and leaf area index of winter cereals under nitrogen limitation by non-linear models
2021
Rahemi-Karizaki, Ali | Khaliliaghdam, Nabi | Biabani, Abbas
Physiological importance of some non-linear regression models parameters (Beta 1, Beta 2, Logistic, Richards, Gompertz, Symmetrical sigmoid pattern, cut linear exponential, and Weibull) were studied in describing the time trend of accumulated dry matter and LAI of winter cereals under two nitrogen levels. Thus, a factorial experiment based on Randomized Complete Block design with four replications was performed. Treatments were zero, and optimum nitrogen levels (150, 120, 150, 120, 210 and 240 kg/ha for bread wheat, durum wheat, hull less barley, two-rowed barley, six-rowed barley and triticale, respectively), and winter cereals including durum and bread wheat (cv. Koohdasht), barley (Hordeum vulgare L.), two-rowed barley (cv. Khorram), six-rowed (cv. Sahra), hull less barley (line 17), and triticale (Triticum wittmak L.). The experiment was performed during the 2013/2014 and 2014/2015 seasons at the research field of Gonbad Kavous University, Iran. Results revealed for LAI that in Koohdasht cultivar, according to MAE, the prediction of both Logistic (0.32) and Beta (0.38) models in the zero nitrogen was better than nitrogen consumption while in wheat drum, no difference was observed between the models in both conditions. All models could describe time trend of accumulated dry matter under both fertilizer levels, but Gompertz, symmetrical expo linear models shown slightly better than others. Enhancement estimation of parameters of these models (maximum accumulated dry matter, RGR in linear phase, RGR in Expo linear phase, lost time to beginning of Expo linear phase, slope of dry matter and time of CGR max) are very crucial in modelling studies, cultivars comparison, growth analyses and simulation of growth and production of winter cereals.
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