Comparison of Nonlinear Models for Dry Matter Yield of Brachiaria Hybrid cv Cayman in Drought Season by Bootstrapping
- 1 Universidad Nacional de Jaén, Peru
- 2 Universidad Nacional Experimental de los Llanos Occidentales Ezequiel Zamora, Venezuela
- 3 Universidad César Vallejo, Peru
The dynamics of biomass accumulation at different seasons of the year is of vital importance in the production of a forage species. In this study nonlinear models (logistic and gompertz) to describe growth dynamics of plants based on dry matter yield of Brachiaria hybrid Cayman at different interval between cuts in drought season were used. Results for logistic and gompertz model showed an excellent fit to the data set of accumulated dry matter with a R2 close to 1.0. In the dry season the best fitted model to estimate the cumulative dry matter yield was gompertz model. It is possible suggest logistic model use in drought conditions. The empirical distribution of the estimated intrinsic growth rate (K) was symmetric and leptokurtic for the logistic and gompertz model in the intervals (-0.0141; 0.2071 Kg MS ha-1) and -0.00086; 0.724986 Kg MS ha-1), respectively and the empirical distribution of the asymptotic accumulated dry matter yield (B) was asymmetric for the logistic and gompertz models in the intervals (4373; 16980 Kg MS ha-1) and (9840; 26654 Kg MS ha-1), respectively. The empirical distribution of these two parameters reflects the fact that the accumulated dry matter production of this grass is strongly related to the distribution of rainfall, especially in the tropical dry forest. The nitrogen fertilization, interval between cuts, intrinsic growth rate of B. hybrid Cayman as well as other factors affect this species development determine dry matter yield sustainability.
Copyright: © 2021 Danny Villegas Rivas, Nora Valbuena Torres, Manuel Milla Pino, Zadith Garrido Campaña, Martín Grados Vasquez, Erick Delgado Bazan, Cesar Osorio Carrera, Ydalia Velasquez Casana and Wilfredo Ruiz Camacho. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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