Skip to main content
ARS Home » Research » Publications at this Location » Publication #182492


item Zhao, Duli
item Starks, Patrick
item Brown, Michael
item Phillips, William
item Coleman, Samuel

Submitted to: Grassland Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/10/2006
Publication Date: 2/27/2007
Citation: Zhao, D., Starks, P.J., Brown, M.A., Phillips, W.A., Coleman, S.W. 2007. Assessment of forage biomass and quality parameters of bermuda grass using proximal sensing of pasture canopy reflectance. Grassland Science. 53:39-49.

Interpretive Summary: Timely estimates of forage production and quality are important for pasture and livestock management. Traditional methods of determining forage production, crude protein, neutral detergent fiber and acid detergent fiber concentrations require considerable time for collecting and processing vegetation samples, and forage quality analyses can be expensive. The objective of this study was to determine whether remote sensing of canopy reflectance of standing forage in the field is a more efficient approach. Canopy reflectance measurements were compared to direct measurements of forage biomass and conventional laboratory analyses of crude protein, neutral detergent fiber, and acid detergent fiber of Bermudagrass pastures. Canopy reflectance in five to 10 narrow wavebands was closely related to forage biomass, crude protein concentration, and neutral detergent fiber concentration, but the relationship between reflectance and acid detergent fiber concentration was poor, apparently because of the narrow range of variation encountered on the pastures. Our results suggest that remote sensing of canopy reflectance has potential for use in making nondestructive, real-time assessments of forage production and major forage quality variables and can be employed as a tool to better manage pastures and livestock.

Technical Abstract: Assessments of forage productivity and quality during the growing season can help livestock managers make timely decisions for adjusting stocking rate and managing pastures. Traditional laboratory methods of forage quality determination are usually time consuming and costly. Remote sensing may provide a rapid and inexpensive means of estimating forage biomass and quality variables. Canopy reflectance measurements were made, using a portable spectroradiometer, in five warm season grass pastures during the 2002 and 2003 growing seasons to develop and validate algorithms to predict aboveground biomass, neutral detergent fiber (NDF), acid detergent fiber (ADF), and crude protein (CP) concentrations and CP availability. Forage biomass correlated (r2 = 0.36, P<0.0001) with the ratio of reflectance at 1145 and 1205-nm wavebands (R1145/R1205). Crude protein concentration and CP availability correlated linearly with R1695/R605 and R875/R735 (r2 = 0.61 and 0.47, P<0.0001), respectively. Although correlations of NDF and ADF with reflectance ratios were significant (P<0.0001), the best reflectance ratios could only explain 13-35% of ADF and NDF variations (i.e. r2 = 0.13-0.35). Compared to a simple linear regression of the quality variables with a two-waveband reflectance ratio, multiple regression (MAXR) models with a total of 10-waveband entrances improved the relationships between forage quality and canopy reflectance values (r2 = 0.27-0.74, P<0.0001). Validation of developed equations indicated that forage biomass, CP concentration, and CP availability could be well predicted using either the reflectances at 10 wavebands 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 rapidly and nondestructively predicted using canopy reflectance data.