Detecting Nitrogen and Phosphorus Stress in Corn Using Multi-spectral Imagery

Abstract

The ability to evaluate in-season nutrient deficiencies and/or estimate grain yield could be beneficial to producers in helping make various management decisions. Proper nutrient management decisions could lead to decreased environmental pollution due to over fertilization. A field experiment was established to evaluate the use of multi-spectral imagery for estimating in-season plant biomass, plant nitrogen (N) and phosphorus (P) concentration, grain yield, and grain N and P concentration with varying degree of N and P nutrition. The experiment was a randomized complete block design with four replications using a factorial arrangement of treatments in an irrigated continuous corn (Zea may L.) system. There were four N rates (0, 67, 134, and 269 kg N ha−1) and four P rates (0, 22, 45, 67 kg P ha−1). Multi-spectral imagery was collected throughout the growing season using a four [blue, green, red, and near-infrared (NIR)]-band sensor. Grain yield, in-season biomass and N concentration increased with increasing N rate for all sampling dates. Biomass production differences due to P deficiency were present only for the early (June) sampling dates. The 1998 imagery had higher regression correlation for in-season biophysical characteristics and grain yield compared to the 1997 growing season, due to differences in sensor sensitivity and increased plant response to applied nutrients. The normalized difference greenness vegetation index (GNDVI) generally had the highest r 2 with grain yield. This study demonstrated the utility of multi-spectral imagery for estimating grain production and nutrient deficiency this could help producers with in-season management decisions.