Assessment of forage biomass and quality parameters of bermudagrass using proximal sensing of pasture canopy reflectance

Assessments of forage productivity and quality during the growing season can help livestock managers make 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 spectroradiometer, in five warm season grass pastures during the 2002 and 2003 growing seasons to develop and validate algorithms to predict above-ground biomass, neutral detergent fiber (NDF), acid detergent fiber (ADF), and crude protein (CP) concentrations and CP availability (i.e. CP concentration x biomass yield) of the pastures. Forage biomass correlated (r2 = 0.36, P < 0.0001) with a 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 NDF and ADF correlated significantly (P < 0.0001) with the reflectance ratios, the best reflectance ratios only explained 13-35% of ADF and NDF variations. 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 predicted using either the reflectances at 10 wavebands or the two-band reflectance ratios. Pasture NDF could also be predicted using the 10-band MAXR equation (r2 = 0.58). Our results suggest that biomass and major quality parameters of warm season grass pastures can be rapidly and nondestructively predicted using canopy reflectance data.