Abstract
The core of precision crop management is to apply only necessary amount of nitrogen to where it is needed. To determine the site-specific yield potential, various nitrogen stress sensing methods, including aerial image, tissue analysis, soil sampling analysis and SPAD meter readings, are currently used. The efficiency of side-dressing is heavily relied on the capability of detecting nitrogen deficiency on a sprayer. This paper presents the development of a multi-spectral nitrogen deficiency sensor, which uses three channels (green, red, near-infrared) of crop images to determine nitrogen level of the corn. The core of this investigation is the calibration methods between the multi-spectral references and the nitrogen levels in crops measured using a SPAD meter. Some noticeable relationships between the multi-spectral reflectance and SPAD readings were found from this study. Based on field validation tests during corn growing season, the developed multi-spectral nitrogen deficiency sensor was found to be capable of detecting corn nitrogen level reliably in real-time.
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