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Quantification of grain dry matter accumulation trends in barley cultivars

Quantification of grain dry matter accumulation trends in barley cultivars Given the physiological significance of nonlinear regression models parameters on crop growth patterns, we used eight nonlinear regression models (Beta1, Beta2, Logistic, Richards, Gompertz, Symmetric Exponential, Cut Exponential and Weibull) to describe the process of cumulative dry matter parameters in barley. An experiment based on randomized complete block design with 4 replications was conducted in Gonbad Kavous University Research Field during 2016–2017 and 2017–2018. The treatments were four barley cultivars of Sahra, Khorram, Fardan and Mahoor. The results of fitting the cumulative dry matter of barley grain showed that coefficient a was significant in Khoram, Fardan and Mahour cultivars in beta 1 model and in Sahara cultivar were beta 1 and beta 2 models. Also, CV and RMSE values were acceptable in all models, and R2 was higher than 97% in most of the models, indicating that all models had good fittings in different barley cultivars. Based on the results, the logistic, cut exponential, symmetric exponential, Richards, Gompertz and Weibull models were slightly better than the beta1 and beta2 models based on the calculated parameters. Also, Khoram and Fardan cultivars had the highest maximum dry matter accumulation in grain and Mahoor and Sahra cultivars had the lowest amount. Further estimated value of parameters (maximum accumulated dry matter, RGR in linear phase, RGR in expolinear phase, missed time to beginning of expolinear phase, slope of dry matter and time of CGRmax) were so practical in simulation studies, cultivars comparing, growth analyses and simulation of growth and production of cereals. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Plant Physiology Reports Springer Journals

Quantification of grain dry matter accumulation trends in barley cultivars

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Publisher
Springer Journals
Copyright
Copyright © Indian Society for Plant Physiology 2022
ISSN
2662-253X
eISSN
2662-2548
DOI
10.1007/s40502-022-00662-z
Publisher site
See Article on Publisher Site

Abstract

Given the physiological significance of nonlinear regression models parameters on crop growth patterns, we used eight nonlinear regression models (Beta1, Beta2, Logistic, Richards, Gompertz, Symmetric Exponential, Cut Exponential and Weibull) to describe the process of cumulative dry matter parameters in barley. An experiment based on randomized complete block design with 4 replications was conducted in Gonbad Kavous University Research Field during 2016–2017 and 2017–2018. The treatments were four barley cultivars of Sahra, Khorram, Fardan and Mahoor. The results of fitting the cumulative dry matter of barley grain showed that coefficient a was significant in Khoram, Fardan and Mahour cultivars in beta 1 model and in Sahara cultivar were beta 1 and beta 2 models. Also, CV and RMSE values were acceptable in all models, and R2 was higher than 97% in most of the models, indicating that all models had good fittings in different barley cultivars. Based on the results, the logistic, cut exponential, symmetric exponential, Richards, Gompertz and Weibull models were slightly better than the beta1 and beta2 models based on the calculated parameters. Also, Khoram and Fardan cultivars had the highest maximum dry matter accumulation in grain and Mahoor and Sahra cultivars had the lowest amount. Further estimated value of parameters (maximum accumulated dry matter, RGR in linear phase, RGR in expolinear phase, missed time to beginning of expolinear phase, slope of dry matter and time of CGRmax) were so practical in simulation studies, cultivars comparing, growth analyses and simulation of growth and production of cereals.

Journal

Plant Physiology ReportsSpringer Journals

Published: Jun 1, 2022

Keywords: Barely; Grain dry matter; Maximum cumulative dry matter; Model

References