Author
Zhao, Duli | |
Starks, Patrick | |
Brown, Michael | |
Phillips, William | |
Coleman, Samuel |
Submitted to: Agronomy Society of America, Crop Science Society of America, Soil Science Society of America Meeting
Publication Type: Abstract Only Publication Acceptance Date: 6/9/2005 Publication Date: 11/10/2005 Citation: Zhao, D., Starks, P.J., Brown, M.A., Phillips, W.A., Coleman, S.W. 2005. Relationships between forage quality and canopy reflectance of warm season grass pastures [abstract]. Agronomy Society of America, Crop Science Society of America, Soil Science Society of America Meeting. Paper No. 162-7. Interpretive Summary: Abstract Only. Technical Abstract: Timely assessment of forage productivity and quality during the growing season is important in livestock and pasture management. Traditional laboratory determination of forage quality is usually time consuming and costly. Remote sensing of canopy reflectance may be used for the real-time estimation of forage biomass and quality. Canopy hyperspectral reflectance was measured using a portable spectroradiometer in five warm season grass pastures during the 2002 and 2003 growing seasons to determine relationships between forage biomass and quality variables and canopy reflectance. Pasture biomass, crude protein (CP) concentration, and CP availability correlated closely and linearly with the three two-band reflectance ratios (r2 from 0.36 to 0.61, n = 207). Although correlations of neutral detergent fiber (NDF) and acid detergent fiber (ADF) with reflectance ratios were statistically significant (P < 0.0001), the best reflectance ratios could only explain 13 to 35% of NDF and ADF variations (r2 from 0.13 to 0.35). Compared to a simple linear regression of the quality variables with a two-band reflectance ratio, multiple regression (MAXR) with a total of 10-wavebands improved the relationships between forage quality and reflectance values (r2 from 0.27 to 0.74). Validation of developed equations indicated that the forage biomass, CP concentration, and CP availability could be well predicted using either 10-waveband reflectances or the two-band reflectance ratios. Pasture NDF could also be predicted using the MAXR equation. Our results suggest that biomass and major quality parameters of warm season grass pastures can be nondestructively predicted using canopy reflectance measurements. |