Dudeni-Tlhone, NRamoelo, AbelCho, Moses ADebba, PraveshMathieu, Renaud SA2010-11-222010-11-222010-10Dudeni-Tlhone, N., Ramoelo, A., Cho, M.A. et al. 2010. Modelling nutrient concentration to determine the environmental factors influencing grass quality. Proceedings of the 52nd Annual Conference of the South Statistical Association for 2010 (SASA 2010), North-West University: Potchefstroom Campus, 10-12 November 2010, pp 7978-0-620-48-708-5http://hdl.handle.net/10204/4575Proceedings of the 52nd Annual Conference of the South Statistical Association for 2010 (SASA 2010), North-West University: Potchefstroom Campus, 10-12 November 2010This paper uses the spatial and the least squares (Analysis of Covariance-ANCOVA) regression methods to evaluate the important environmental factors in estimating quality grass for grazing (based on the nitrogen (N) content in grass). The environmental variables such as those based on climate (temperature and precipitation), land-use, geology, slope, aspect and altitude were specifically evaluated in these models. Spatial regression accounted for higher variability (61%) when compared to the 41% variability explained by the ANCOVA model. The models indicate that some environmental variables are useful in assessing N variability. This provides an opportunity for the design of an intergraded system to incorporate both the environmental and remote sensing variables in the estimation and mapping of nitrogen content in grazing grass across the Kruger National Park (KNP) and the surrounding areas.enNitrogenRegressionGrass qualityEnvironmental factorsSpatial regressionGrazing animalsSASA 2010Modelling nutrient concentration to determine the environmental factors influencing grass qualityConference PresentationDudeni-Tlhone, N., Ramoelo, A., Cho, M. A., Debba, P., & Mathieu, R. S. (2010). Modelling nutrient concentration to determine the environmental factors influencing grass quality. http://hdl.handle.net/10204/4575Dudeni-Tlhone, N, Abel Ramoelo, Moses A Cho, Pravesh Debba, and Renaud SA Mathieu. "Modelling nutrient concentration to determine the environmental factors influencing grass quality." (2010): http://hdl.handle.net/10204/4575Dudeni-Tlhone N, Ramoelo A, Cho MA, Debba P, Mathieu RS, Modelling nutrient concentration to determine the environmental factors influencing grass quality; 2010. http://hdl.handle.net/10204/4575 .TY - Conference Presentation AU - Dudeni-Tlhone, N AU - Ramoelo, Abel AU - Cho, Moses A AU - Debba, Pravesh AU - Mathieu, Renaud SA AB - This paper uses the spatial and the least squares (Analysis of Covariance-ANCOVA) regression methods to evaluate the important environmental factors in estimating quality grass for grazing (based on the nitrogen (N) content in grass). The environmental variables such as those based on climate (temperature and precipitation), land-use, geology, slope, aspect and altitude were specifically evaluated in these models. Spatial regression accounted for higher variability (61%) when compared to the 41% variability explained by the ANCOVA model. The models indicate that some environmental variables are useful in assessing N variability. This provides an opportunity for the design of an intergraded system to incorporate both the environmental and remote sensing variables in the estimation and mapping of nitrogen content in grazing grass across the Kruger National Park (KNP) and the surrounding areas. DA - 2010-10 DB - ResearchSpace DP - CSIR KW - Nitrogen KW - Regression KW - Grass quality KW - Environmental factors KW - Spatial regression KW - Grazing animals KW - SASA 2010 LK - https://researchspace.csir.co.za PY - 2010 SM - 978-0-620-48-708-5 T1 - Modelling nutrient concentration to determine the environmental factors influencing grass quality TI - Modelling nutrient concentration to determine the environmental factors influencing grass quality UR - http://hdl.handle.net/10204/4575 ER -