Development of Canopy Reflectance Algorithms for Real‐Time Prediction of Bermudagrass Pasture Biomass and Nutritive Values

Abstract

Timely assessments of forage biomass production and nutritive values during the growing season are important for livestock managers to make decisions for adjusting stocking rate and pasture management. Remote sensing of canopy reflectance may provide a rapid and inexpensive means of estimating pasture nutritive values and biomass. The objective of this study was to determine the relationships between neutral detergent fiber (NDF), acid detergent fiber (ADF), crude protein (CP) concentration, biomass, and CP availability of bermudagrass [Cynodon dactylon (L.) Pers.] pastures and canopy reflectance. An experiment was conducted in the 2002 and 2003 growing seasons using three bermudagrass pastures of ‘Midland’, ‘Ozarka’, and an experimental hybrid, 72x12–12. Pasture CP concentration, biomass and CP availability correlated linearly with the reflectance ratios of R605/R515, R915/R975, and R875/R725 (0.44 ≤ r2 ≤ 0.63) as well as with the first derivatives of reflectance with wavebands centered at 545, 935, and 755 nm (0.49 ≤ r2 ≤ 0.68). Linear equations between each forage variable and the ratios or derivatives of reflectance were developed on the basis of data pooled across years, plant genotypes, and sampling dates. Validation of developed equations indicated that the CP concentration, biomass, and CP availability could be predicted by either the ratios or derivatives of the reflectance. Pasture NDF and ADF had lower correlation with canopy reflectance than other measured variables. Our results suggest that two‐narrow‐waveband reflectance ratios or the first derivatives in visible and near‐infrared spectral regions can be used for real‐time and nondestructive prediction of forage productivity and CP content in bermudagrass pastures.