/AnMtgsAbsts2009.55227 Canopy Reflectance-Based Algorithm for in-Season Estimation of Rice Grain Yield.

Monday, November 2, 2009: 10:45 AM
Convention Center, Room 319, Third Floor

Brenda Tubana, School of Plant Environmental and Soil Sciences, Louisiana State Univ., AgCenter, Baton Rouge, LA, Dustin Harrell, 1373 Caffey Road, Louisiana State Univ., AgCenter, Rayne, LA, Timothy Walker, Mississippi State Univ., Stoneville, MS and Steve Phillips, Intl. Plant Nutrition Inst., Owens Cross Roads, AL
Abstract:
The use of canopy reflectance in evaluating crop nitrogen (N) status has resulted in the development of remote sensor-based N decision tools for wheat and corn production. This study was initiated in 2008 to establish the major component required for the development of a remote sensor-based N decision tool for rice production in the mid-southern United States. It is essential to determine the optimal sensing dates where a predictive equation for rice yield potential (YP0) can be established thus collection of normalized difference vegetation index (NDVI) readings using the GreenSeekerTM handheld sensor from multiple variety x nitrogen trials located in Crowley and Rayville, LA, and Stoneville, MS was conducted at different growth stages. Sensor readings were collected on a weekly basis for five consecutive weeks starting at panicle initiation stage from rice plots planted with Catahoula, Neptune and Clearfield 131 varieties. For different growth stages, the association of in-season estimated yield (INSEY, NDVI/number of days from seeding to sensing- DAS) and actual grain yield was evaluated. Between 70-90 DAS, strong associations between INSEY and grain yield were obtained with r2 values that ranged from 0.64 to 0.70, the highest of which was obtained from the sensing dates between 70-75 DAS. From these findings, the initial predictive equation, YP0 = 1668164.14*INSEY, was established from NDVI readings collected between 70-75 DAS.  With the inclusion of more data points and introduction of correction procedures using thermal time (growing degree days), opportunities exist for further refinement of the canopy reflectance-based YP0 algorithm for rice.