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Remote sensing techniques to detect nitrogen stress in corn
Abstract
Field spatial variability presents a problem in making nitrogen (N) fertilizer recommendations for corn production. Techniques to identify differences in crop N status within a corn field could lead to improved N fertilizer recommendations. Previous research has shown that chlorophyll meter readings provide a reliable index of N stress. The goal of this research was to test the ability of remote sensing techniques to identify N stress that results in decreased yields. To achieve this goal, reflectance techniques from leaf to field level situations were investigated. Remote sensing measurements were made in both 1992 and 1993 for four irrigated corn (Zea mays, L.) hybrids with five N rates near Shelton, Nebraska. Leaf reflectance was measured from the ear leaf of ten plants per plot for the visible portion of the spectrum in 10-nm increments. Canopy reflectance was measured in the 400 to 1050-nm range for all the plots on clear days with a portable spectroradiometer. Aerial photographs using color print film were used to record field level reflectance. Individual leaf reflectance data showed that reflectance at 550-nm performed as well as a chlorophyll meter in detecting N stress. Canopy reflectance measurements also identified reflectance at the 550-nm wavelength as well as at the 650- and 710-nm wavelengths as a good indicator of N deficiency when reflectance was compared to reflectance of a non-limiting N plot. Aerial images were digitized to generate non-normalized coordinates (digital counts) for the red, green, and blue primary colors in the photographs. Of the three colors, red digital counts provided the best detection of N stress. These findings show that both leaf and canopy reflectance techniques can identify N deficiency. Canopy reflectance recorded with an aerial photograph was able to detect N stress, and identify differences in N status within an entire field with a single image.
Subject Area
Agronomy|Remote sensing
Recommended Citation
Blackmer, Tracy Merrill, "Remote sensing techniques to detect nitrogen stress in corn" (1995). ETD collection for University of Nebraska-Lincoln. AAI9538627.
https://digitalcommons.unl.edu/dissertations/AAI9538627