Determining the Optimal Timing for Using LAI and NDVI to Predict Rice Yield

Changes in normalized difference vegetation index (NDVI), which calculated from ground-based canopy hyperspectral reflectance data, and leaf area index (LAI), which measured at the time of spectral measurements, were monitored during rice (Oryza sativa L. cv. TNG 67) growth and yields were harvested at maturity so as to determine the NDVI-LAI relationships and the optimal timing to use these two parameters for yield prediction. Field experiments were conducted at the experimental farm of Taiwan Agricultural Research Institute (Wufeng, Taiwan) in the first and the second cropping seasons of 2001-2002. Different levels of nitrogen fertilizer, from 0 to 180 kg ha-1 with 30 kg ha-1 intervals, were applied to produce various scales of grain yield and values of LAI and NDVI. Results showed that there were differential weather conditions between two cropping seasons, and plants grown in first crops had a better growth and yield. Both LAI and NDVI were found curvilinearly distributed during the growing periods, with the maximum values occurred before heading in First Crops and near or after heading in Second Crops. These two parameters can be mutually estimated through an exponential function, which linked spectral remote sensing data with plant growth information. Correlation between yield and LAI was best fitted to a nonlinear function, from about 50 days after transplanting (DAT) with the determining factor (R2) higher than 0.73 (P<0.01). By further analyzing the relations of the cumulative and the mean values of LAI to yield, it indicated that both the accumulated and the mean values of LAI from 15 days before heading (DBH) to 15 days after heading (DAH) can well predict rice yield for the first cropping seasons, while values calculated from 15 DBH to 10 DAH can predict yield for the second cropping seasons. Key Words: Rice, LAI, NDVI, Yield prediction, Optimal timing. 1.