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REVIEW & INTERPRETATION

Strategies to Make Use of Plant Sensors-Based Diagnostic Information for Nitrogen Recommendations

^a Warsaw Univ. of Life Sciences, Agronomy, Nowoursynowska Street 159, Warsaw, Poland 02-776
^b Agriculture and Agri-Food Canada, 430 Gouin Blvd., St-Jean-sur-Richelieu, QC, Canada J3B 3E6

^* Corresponding author (stanislaw_samborski{at}sggw.pl).

Improvements of nitrogen use efficiency (NUE) may be achieved through the use of sensing tools for N status determination. Leaf and canopy chlorophyll, as well as leaf polyphenolics concentrations, are characteristics strongly affected by N availability that are often used as a surrogate to direct plant N status estimation. Approaches with near-term operational sensors, handheld and tractor-mounted, for proximal remote measurements are considered in this review. However, the information provided by these tools is unfortunately biased by factors other than N. To overcome this obstacle, normalization procedures such as the well-fertilized reference plot, the no-N reference plot, and relative yield are often used. Methods to establish useful relationships between sensor readings and optimal N rates, such as critical NSI (nitrogen sufficiency index), INSEY (in-season estimated yield), and the relationship between chlorophyll meter readings, grain yield, and sensor-determined CI (chlorophyll index) are also reviewed. In a few cases, algorithms for translating readings into actual N fertilizer recommendation have been developed, but their value still seems limited to conditions similar to the ones where the research was conducted. Near-term operational sensing can benefit from improvements in sensor operational characteristics (size and shape of footprint, positioning) or the choice of light wavebands more suitable for specific conditions (i.e., genotype, growth stage, or crop density). However, one important limitation to their widespread use is the availability of algorithms that would be reliable in a variety of soil and weather conditions.

Abbreviations: CI, chlorophyll index • DFP, days from planting • EONR, economic optimum nitrogen rate • GAI, green area index • GDD, growing degree days • HNT, "Hydro N Tester" (Yara International ASA, Oslo, Norway) • INSEY, in-season estimated yield • LAI, leaf area index • NDVI, normalized difference vegetation index • NIR, near-infrared • NNI, nitrogen nutrition index • NSI, nitrogen sufficiency index • NUE, nitrogen use efficiency • PSNT, pre-sidedress soil nitrate test • RCS, ramped calibration strips • RI, response index • RWC, relative water content • SPAD, SPAD-502 meter (Konica Minolta, Tokyo, Japan)

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Received for publication October 31, 2008.