2008 Joint Annual Meeting (5-9 Oct. 2008): Using an Active Sensor to Estimate Orchard Grass (Dactylis glomerata L.) Dry Matter Yield and Quality.

712-6 Using an Active Sensor to Estimate Orchard Grass (Dactylis glomerata L.) Dry Matter Yield and Quality.



Wednesday, 8 October 2008: 9:45 AM
George R. Brown Convention Center, 371C
Ravi Sripada, Building 3702 Curtin Road, USDA-ARS Pasture Systems & Watershed Mgmt Research Unit, Building 3702, Curtin Road, University Park, PA 16802-3702, John Schmidt, USDA-ARS, USDA-ARS-PSWMRU, Curtin Road Building 3702, University Park, PA 16802-3702, Matt Sanderson, USDA-ARS, Pasture Systems and Watershed Management Research Unit, Building 3702 Curtin Road, University Park, PA 16802-3702 and Sarah K. Marshall, USDA-ARS-Pasture Systems and Watershed Management Research Unit, Bldg 3702, Curtin Road, University Park, PA 16802-3702
Remote sensing in the form of active sensors could be used to estimate forage biomass on spatial and temporal scales. The objective of this study is to use canopy reflectance measurements from an active remote sensor to compare different vegetation indices as a means of estimating final dry matter yield and quality parameters for orchard grass. Field experiments were conducted over two years, 2005 and 2006 using a randomized complete block design with different rates of N applied at greenup and after each of the three harvests within a season. Canopy reflectance measurements were obtained using a Crop Circle (Holland Scientific, Lincoln, NE) sensor just before harvest, and biomass and crude protein (CP), neutral detergent fiber (NDF), and digestible neutral detergent fiber (NDFD) were determined at each harvest. Results indicate a significant dry matter yield and spectral response to N applications. Combined over years and harvests, Green Ratio Vegetation Index (GRVI) and Green Normalized Difference Vegetation Index (GNDVI) showed the highest correlation coefficient of 0.67. However, the strength of these relationships increased when analyzed by each year and harvest. In a given year, the strength of association of spectral indices and biomass was higher at the first harvest and decreased with subsequent harvest. The associations of the spectral data with forage quality parameters will also be discussed.