Skip to main content
ARS Home » Northeast Area » University Park, Pennsylvania » Pasture Systems & Watershed Management Research » Research » Publications at this Location » Publication #225804
Title: Using an Active Sensor to Estimate Orchard Grass (Dactylis glomerata L.) Dry Matter Yield and Quality

Author
item SRIPADA, RAVI - CANAAN VALLEY INST
item Schmidt, John
item Sanderson, Matt
item Fishel, Sarah - Sarah K Marshall

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 3/31/2008
Publication Date: 10/5/2007
Citation: Sripada, R., Schmidt, J.P., Sanderson, M.A., Fishel, S.K. 2007. Using an Active Sensor to Estimate Orchard Grass (Dactylis glomerata L.) Dry Matter Yield and Quality[abstract]. ASA-CSSA-SSSA Annual Meeting Abstracts. Paper No. 712-6.

Interpretive Summary: An interpretive summary is not required.

Technical Abstract: 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.