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Evaluation and Refinement of the Nitrogen Reflectance Index (NRI) for Site-Specific Fertilizer Management

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  011151,  2001 ASAE Annual Meeting. (doi: 10.13031/2013.7357) @2001
Authors:   Tyler D. Schleicher, Walter C. Bausch, Jorge A. Delgado, Paul D. Ayers
Keywords:   NRI, nitrogen, reflectance, index, indices, site-specific, precision farming, corn, near-infrared, nir, green, remote sensing, radiometer, imagery

Environmental and economic concerns have collectively created a demand for more efficient agricultural fertilizer application. Remote sensing of plant parameters has recently shown the potential to improve fertilizer application efficiency by showing corn (Zea mays L.) producers when and where to apply fertilizers based on crop needs. Previous studies have indicated that a normalized near-infrared over green (nir/green) waveband reflectance ratio, called the Nitrogen Reflectance Index (NRI), could be used to assess in-season corn N status (CNS) in small plots. This study evaluated the NRI using small plot data and then tested possible index improvements in a larger area. Data from four small plot site years indicated that the NRI explained > 70% of the variability occurring with in-season CNS for canopies with Leaf Area Index (LAI) 2. These results led to the development of an early-season feasibility indicator (ESFI) a non-invasive method of assessing LAI. This created a simplistic guideline for appropriate use of the NRI based on minimum ground-cover. The ESFI, calculated by subtracting the green and red reflectance, utilized a minimum threshold level of 0.01 to remove measurements where LAI < 2. Another proposed improvement to the NRI illustrated that the cumulative density function of the nir/green ratio could be used to develop N variability maps and improve fertilizer management. Further testing within a 22.5 ha area was used to determine platform compatibility and performance comparisons of the NRI versus other indices. After filtering with the ESFI, results showed strong compatibility between aerial imagery and ground-based radiometer measurements. Comparing the NRI to the NDVI, Green NDVI, SAVI, and MSAVI showed that all of these indices accurately assessed N variability based on total N uptake measurements collected.

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