357-4 Comparison of Leaf Color Chart Observations with Spectral Measurements of Chlorophyll Content in Maize.

Poster Number 207

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Adaptive Nutrient Management: II
Wednesday, November 5, 2014
Long Beach Convention Center, Exhibit Hall ABC
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E. Raymond Hunt Jr., Hydrology and Remote Sensing Lab, USDA-ARS, Beltsville, MD, Jennifer Hawley, USDA ARS, Beltsville, MD and Randall G. Mutters, University of California, Oroville, CA
Crop nitrogen management is important world-wide, as much for small farms as it is for large operations. Developed as a non-destructive, low cost visual aid for estimating nitrogen content in rice crops, leaf color charts are a numbered series of plastic panels that range from yellow-green to dark green. By visual comparison, the panel closest in color to a leaf indicates whether nitrogen is deficient, sufficient or in excess.  One question about leaf color charts is how reproducible are the values, since it depends on subjective decisions by an observer. Calibration of color charts are based on instruments such as the SPAD chlorophyll meter, but chlorophyll meters measure leaf transmittance whereas the observer is estimating leaf reflectance. A nitrogen fertilization experiment with maize was conducted at the Beltsville Agricultural Research Center for two years. Spectral reflectances, SPAD chlorophyll meter values, digital photographs, and chlorophyll content were measured for leaves collected during the experiment.  Color chart panel number was highly correlated with SPAD values and chlorophyll content.  Spectral indices from reflectance measurements were also correlated with panel numbers of the leaf color chart. With the digital photographs, spectral indices and supervised classifications were the least correlated. Therefore, objective spectral reflectances were no better than subjective visual observation using leaf color charts as a standard.
See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Adaptive Nutrient Management: II