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Comparing Digital Image Analysis and other Turf Quality Measurements in the Evaluation of "SMART" Irrigation Technologies

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2010 Pittsburgh, Pennsylvania, June 20 - June 23, 2010  1009924.(doi:10.13031/2013.30018)
Authors:   Ihab E Ghali, Garry L Grabow, Rodney L Huffman, Grady L Miller
Keywords:   Keywords: Tall fescue, Turf quality, Digital image analysis, Canopy spectral reflectance, Visual rating, Canopy-air temperature differentials, Dark green color index.

An efficiently managed irrigation system is important in order to achieve the dual goals of water conservation and acceptable turf quality. The main objective of this study was to identify changes and correlations among turf visual rating, canopy reflectance, canopy temperature and digital imagery index in evaluating turfgrass quality under different irrigation treatments. A study of ten irrigation treatments on tall fescue plots combining controller technology (a standard time-based system, two soil-moisture-based systems, and an evapotranspiration based system) and watering frequency (once per week, twice per week and seven days per week) replicated four times in a randomized complete block design was done at the North Carolina State University Lake Wheeler Turf Field Laboratories. Different turf quality measurements were taken on a weekly basis during the summer of 2008 and 2009. An imagery analysis index, dark green color index (DGCI), was strongly and positively correlated with a visual rating index(r = 0.67 and 0.85, for 2008 and 2009 respectively) and normalized difference vegetation index (NDVI) (r = 0.83 and 0.87, for 2008 and 2009 respectively), but negatively and weakly correlated with canopy and ambient air temperature differentials (ΔT) (r = -0.06 and -0.24, for 2008 and 2009 respectively). Because of their objective measurements, digital imagery analysis and canopy spectral reflectance techniques can be used effectively to evaluate the variability in turf quality under different irrigation treatments (technology x frequency), thus improving irrigation management finding the treatment has low water-use with acceptable turf quality.

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