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Changes in hyperspectral reflectance signatures of lettuce leaves in response to macronutrient deficiencies
Authors:R.O. Pacumbaba Jr.  C.A. Beyl
Affiliation:1. Department of Plant and Soil Science, Alabama A&M University, P.O. Box 1208, Normal, AL 35762, United States;2. The College of Agriculture Sciences and Natural Resources, University of Tennessee, 2621 Morgan Circle, 125 Morgan Hall, Knoxville, TN 37996, United States
Abstract:The adaptation of specific remote sensing and hyperspectral analysis techniques for the determination of incipient nutrient stress in plants could allow early detection and precision supplementation for remediation, important considerations for minimizing mass of advanced life support systems on space station and long term missions. This experiment was conducted to determine if hyperspectral reflectance could be used to detect nutrient stress in Lactuca sativa L. cv. Black Seeded Simpson. Lettuce seedlings were grown for 90 days in a greenhouse or growth chamber in vermiculite containing modified Hoagland’s nutrient solution with key macronutrient elements removed in order to induce a range of nutrient stresses, including nitrogen, phosphorus, potassium, calcium, and magnesium. Leaf tissue nutrient concentrations were compared with corresponding spectral reflectances taken at the end of 90 days. Spectral reflectances varied with growing location, position on the leaf, and nutrient deficiency treatment. Spectral responses of lettuce leaves under macronutrient deficiency conditions showed an increase in reflectance in the red, near red, and infrared wavelength ranges. The data obtained suggest that spectral reflectance shows the potential as a diagnostic tool in predicting nutrient deficiencies in general. Overlapping of spectral signatures makes the use of wavelengths of narrow bandwidths or individual bands for the discrimination of specific nutrient stresses difficult without further data processing.
Keywords:Lactuca sativa L. cv. Black Seeded Simpson   Remote sensing   Reflectance   Hyperspectral data   Derivative spectra   Macronutrients
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