|Ko, Jonghan - TEXAS TECH UNIVERSITY|
|Maas, Stephan - TEXAS TECH UNIVERSITY|
|Lascano, Robert - TAES|
Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 19, 2005
Publication Date: September 19, 2005
Citation: Ko, J., Maas, S., Lascano, R., Wanjura, D.F. 2005. Modification of grami model for cotton. Agronomy Journal. 97(5): 1374-1379. Interpretive Summary: Remote sensing and modeling are different techniques for evaluating crop growth and yield. Remote sensing alone provides information that is valid only at the time of image acquisition. Models can provide a continuous description of crop conditions which may not be as accurate as that provided by remote sensing. The objective of this investigation was to extend the capability of the GRAMI model developed for gramineous crops to simulation of irrigated cotton production. The GRAMI model for cotton has relatively simple environmental input requirements compared to process-oriented models. The estimates of crop leaf area index for the model can be obtained from remote sensing observations. Simulated values of cotton growth and lint yield showed reasonable agreement with corresponding measurements under irrigated conditions. The new model not only has simple input requirements but is also easy to use. The model’s use can be expanded to other semiarid regions for irrigated cotton production, and has applicability for regional cotton growth monitoring and lint yield estimation.
Technical Abstract: A new version of the GRAMI crop model capable of being calibrated within season was developed and tested for cotton (Gossypium hirsutum) production in semiarid regions. The model was first verified using field data obtained at Halfway, Texas, USA in 2002. The model was then validated using data sets obtained at Lamesa, Texas in 1999 and 2001, and at Lubbock, Texas in 2002 and 2004. Simulated values of cotton growth and lint yield showed reasonable agreement with corresponding measurements under irrigated conditions. The new model not only has simple input requirements but is also easy to use. Thus, it promises to have applicability to be expanded to other semiarid regions for irrigated cotton production, and applicable to regional cotton growth monitoring and lint yield mapping projects.