Assessment of Rice Yield and Nitrogen Nutrition Using Canopy Spectral Reflectance.

Monday, February 2, 2009: 11:15 AM
Westin Peachtree Plaza, International Room C
Jason M. Satterfield, Delta Research and Extension Center, Mississippi State University, Stoneville, MS, Timothy Walker, Mississippi State University, Stoneville, MS, Jac Varco, Mississippi State University, Mississippi State, MS, Richard J. Norman, Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR and Dustin Harrell, 1373 Caffey Road, Louisiana State University Agricultural Center, Rayne, LA
The price for Nitrogen (N) fertilizer has increased dramatically in recent years.  The increase can be largely attributed to an increase in demand by developing countries.  Intensive rice cultivation, such as that of the southern USA rice growing region, requires large amounts of N; therefore, the cost of production has increased.  As a means to offset production costs as well as minimize environmental effects attributed to over fertilization, methods are needed to make more informed decisions about N fertilization in rice.  The objective of this study was to evaluate the potential for using spectrophotometry as a non-destructive measurement to assess yield potential and nitrogen nutrition in rice.

 Three rice cultivars (Cocodrie, Wells, and XL723) were produced in a delayed-flood culture on Sharkey (very fine, smectitic, thermic, Chromic Epiaquerts) clay soil in 2007 and 2008.  Six preflood N rates (0, 67, 101, 134, 168, and 202 kg N ha-1) were arranged in an RCB design and replicated four times.  At PD, canopy spectral reflectance (350 – 1050 nm) was measured from each plot using a handheld GER 1500 spectrophotometer.  Two vegetative indices, GNDVI and NDVI, were calculated from the measured canopy reflectance values.   Above ground biomass was harvested from 0.9 m of row and analyzed for total dry matter (TDM) and % N content.  Rice grain yield was determined at harvest maturity.   All response variables were subjected to correlation analysis to determine relationships that could potentially be modeled.

 Based on correlation analyses, a strong relationship existed between GNDVI and both rice grain yield and TNU.  For all cultivars, rice grain yield as a function of GNDVI and TNU as a function of GNDVI were best explained by exponential relationships (R2 ≥ 0.8 and 0.7, respectively).  Since canopy reflectance is strongly related to major yield contributing factors, this technology should be further investigated for its potential to determine the optimum N rate needed at PD for positive economic returns.