Cohen, Y., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet-Dagan, Israel
Alchanatis, V., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet-Dagan, Israel
Zusman, Y., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet-Dagan, Israel, The Seagram Center for Soil and Water Sciences, Hebrew University of Jerusalem, Rehovot, Israel
Dar, Z., Extension Service, The Ministry of Agriculture, Bet-Dagan, Israel
Bonfil, D.J., Field Crops and Natural Resources Department, Agricultural Research Organization, Gilat Research Center, Negev, Israel
Karnieli, A., The Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben Gurion University of the Negev, Sede-Boker Campus, Beersheba, Israel
Zilberman, A., Extension Service, The Ministry of Agriculture, Bet-Dagan, Israel
Moulin, A., Brandon Research Centre, Agriculture and Agri-Food Canada, Brandon, MB, Canada
Ostrovsky, V., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet-Dagan, Israel
Levi, A., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet-Dagan, Israel
Brikman, R., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet-Dagan, Israel
Shenker, M., The Seagram Center for Soil and Water Sciences, Hebrew University of Jerusalem, Rehovot, Israel

Relationships between leaf spectral reflectance at 400-900 nm and nitrogen levels in potato petioles and leaves were studied. Five nitrogen (N) fertilizer treatments were applied to build up levels of nitrogen variation in potato fields in Israel in spring 2006 and 2007. Reflectance of leaves was measured in the field over a spectral range of 400-900 nm. The leaves were sampled and analyzed for petiole NO3-N and leaf percentage N (leaf-%N). Prediction models of leaf nitrogen content were developed based on an optical index named transformed chlorophyll absorption reflectance index (TCARI) and on partial least squares regression (PLSR). Prediction models were also developed based on simulated bands of the future VENμS satellite (Vegetation and Environment monitoring on a New Micro-Satellite). Leaf spectral reflectance correlated better with leaf-%N than with petiole NO3-N. The TCARI provided strong correlations with leaf-%N, but only at the tuber-bulking stage. The PLSR analysis resulted in a stronger correlation than TCARI with leaf-%N. An R2 of 0.95 (p < 0.01) and overall accuracy of 80.5% (Kappa = 74%) were determined for both vegetative and tuber-bulking periods. The simulated VENμS bands gave a similar correlation with leaf-%N to that of the spectrometer spectra. The satellite has significant potential for spatial analysis of nitrogen levels with inexpensive images that cover large areas every 2 days. © 2009 Springer Science+Business Media, LLC.