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ARS Home Plains Area Lubbock, Texas Cropping Systems Research Laboratory Wind Erosion and Water Conservation Research Research Publications at this Location





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Title:   Author  item
                                            Gitz, Dennisitem
                                            Baker, Jeffreyitem
                                            Mahan, James
  Submitted to: American Journal of Plant Sciences
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 6/24/2015
                                    Publication  Date: 7/16/2015
                                    Citation: Gitz, D.C., Baker, J.T., Mahan, J.R. 2015. Evaluation of a metabolic cotton seedling emergence model. American Journal of Plant Sciences. 6:1727-1733.Interpretive Summary: The earlier crops can be safely planted the greater the yields and profitibility. Deciding when to plant various crops is usually done by time consuming tedious experimentation to prodcue simple models growers can use. Here we report a new method of predicting seedling emergence that less time to develop and better predicts cotton emergence a cross a wider range of temperatures.
                                Technical Abstract: A model for cotton seedling emergence (MaGi) based on malate synthase kinetics was evaluated in the field at two locations, Lubbock and Big Spring, TX. Cotton, cvar. DP 444, was planted through the early spring and into typical planting times for the areas. Soil temperatures at seed depth was used as inputs into Magi and a commonly used seedling emergence model based on heat unit accumulation. Time to 50% emergence was calculated and compared to predicted emergence using MaGi and a commonly employed degree day model based on heat unit accumulation. MaGi yielded predictive capability without the need to resort to lengthy experimentation required by traditional methods. As with other seed emergence models, MaGi may benefit from soil moisture input. The results suggest a semi-empirical approach incorporating both enzyme kinetics and whole plant temperature responses might be useful for constructing seedling emergence models.


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