Mathematical models to estimate forage production in southeastern Coahuila Mexico

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Perpetuo Álvarez-Vázquez
Fidel M. Peña-Ramos
Antonio Flores-Naveda
Neymar Camposeco-Montejo
Josué I. García-López
Juan de D. Guerrero-Rodríguez

Keywords

Zea mays L., mathematical modeling and goodness of fit.

Resumen

Objective: Calibrate two non-linear models, in three intermediate triple hybrids, by theoretically comparing the accumulation of dry matter in relation to the days after sowing.


Methodology: The cuts were every 14 days, from 30 to 170 das, and were adjusted to the Logistic and Richards models. The experimental design was a randomized block, with three replications.


Results: The models explained most of the total dry matter yield in corn, observed in the field at 83%. The best fit model was the logistic model in cultivar AN447 and the Richards model in cultivar A7573, both with R2=0.98. The maximum yield simulated with the Richards model was shown in AN447 with 22,616 kg DM ha-1 and the lowest in AN388 with 10,970 kg DM ha-1.


Limitations/Implications: Tests of other models in the same conditions and in other environmental conditions with the models under study.


Conclusion: The Logistic model allows to simulate with greater precision the yield of dry matter in corn, by using the days after planting as an independent variable.

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