ASSESSING NITROGEN STRESS IN CORN VARIETIES OF VARYING COLOR

Summary: Nitrogen (N) is an essential element for crop growth and its accurate assessment in plants is a key to nutrient management. This research was conducted to explore the feasibility of using spectral reflectance to predict nitrogen content in corn plant varieties with varying color. A problem identified by previous researchers is the variability of spectral responses from varieties with different canopy colors. Reflectance was measured for samples from subplots of three different corn varieties (selected for varying leaf color) and 5 N treatments. Multivariate statistical analysis was performed on the spectral responses for each variety and N treatment to determine the ability to predict the actual leaf N content. Partial Least Square (PLS) regression, Principal Component Regression (PCR) and Multiple Linear Regression (MLR) were used to build prediction models. The smallest SEP for the ear leaf was 0.15% for a PCR model, and the smallest SEP for younger leaves was 0.25% for a PLS model.

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