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Title: Evaluating a wheat grazing model for managing wheat grain and beef production

Author
item Zhang, Xunchang
item SUI, YANYAN - INST SOIL & WATER, CHINA
item Phillips, William
item HORN, GERALD - OKLA STATE UNIV
item EDWARDS, J - OKLA STATE UNIV
item ZHANG, H - OKLA STATE UNIV

Submitted to: Soil and Water Conservation Society
Publication Type: Abstract Only
Publication Acceptance Date: 10/15/2008
Publication Date: 10/20/2008
Citation: Zhang, X.J., Sui, Y., Phillips, W.A., Horn, G.W., Edwards, J., Zhang, H.L. 2008. Evaluating a wheat grazing model for managing wheat grain and beef production[abstract]. Soil and Water Conservation Society, Farming with Grass Conference, October 20-22, 2008, Oklahoma City, Oklahoma. Available: http://www.swcs.org.en.onferences/farming_with_grass/farming_with_grass_poster_presentations/

Interpretive Summary: Abstract Only.

Technical Abstract: Model evaluation and validation are prerequisite to its successful application. The objective of this paper is to evaluate the ability of the newly developed wheat grazing model to predict fall-winter forage and grain yields of winter wheat (Triticum aestivum L.) as well as daily weight gains per steer grazing on wheat pasture using three experimental trials (variety, planting date and steer grazing) conducted at OSU Exp. Station. For the variety TAM 101 and Jagger from the variety trial, the overall model efficiency (ME) was 0.102 for fall-winter forage prediction and 0.367 for grain yield. For the planting date trial, the ME was about 0.615 for predicting fall-winter forage yields and 0.409 for grain yields when a root downward extension rate of 20 mm/d was used instead of the default value of 30 mm/d. In the steer grazing trial, the relationship between average daily weight gain and forage allowance (an indicator of grazing pressure) was adequately represented by the model. The measured and simulated total steer weight gains during the entire grazing periods agreed well for a wide range of stocking rates and grazing durations, with the ME being 0.616. Overall results show that the model, if thoroughly calibrated, has great capability to predict fall-winter forage and grain yield and daily steer weight gain well.