Spatial Reflectance at Sub-Leaf Scale Discriminating NPK Stress Characteristics in Barley Using Multiway Regression (N-PLS)

Non-destructive stress diagnostics is essential to optimise variable nutrient application with a minimal environmental load. The identifying characteristics when spectrally determining nitrogen, phosphorous and potassium stress in a canopy are dominantly nonspecific symptoms expressed as varying levels of chlorophyll in the leaves. The challenge is spectrally based discrimination between N, P and K stress. This paper introduces a methodology able to discriminate between N, P and K stress symptoms utilising both the spectral and spatial dimension simultaneously. The methodology was tested on spring barley grown under controlled conditions. The spectral range used was 450-1000 nm. Nine spectral measurement were carried out on each plant. The measuring points were spatially located at The authors are solely responsible for the content of this technical presentation. The technical presentation does not necessarily reflect the official position of the American Society of Agricultural Engineers (ASAE), and its printing and distribution does not constitute an endorsement of views which may be expressed. Technical presentations are not subject to the formal peer review process by ASAE editorial committees; therefore, they are not to be presented as refereed publications. Citation of this work should state that it is from an ASAE meeting paper EXAMPLE: Author's Last Name, Initials. 2003. Title of Presentation. ASAE Paper No. 03xxxx. St. Joseph, Mich.: ASAE. For information about securing permission to reprint or reproduce a technical presentation, please contact ASAE at [email protected] or 269-429-0300 (2950 Niles Road, St. Joseph, MI 49085-9659 USA). the tip, middle and base of the three last fully developed leaves. This design generated a fourdimensional data set consisting of the specific plant, the spectral dimension, the plant leaf position, and position on the leaf. Sequential mutiway Partial Least Squares Regression model (N-PLS) analysis with dummy variables was able to correctly classify the four nutrient conditions with 92% accuracy regardless of the respective growth stages within a time window of two weeks. Thus inclusion of the spatial dimension to the spectral dimension was shown to be a promissing nutrient diagnostic tool.