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Canopy reflectance measurements using active optical sensors have emerged as potential solution to draw in-season nitrogen (N) topdressings in cereals. Site-specific need-based N management strategy using a GreenSeeker optical sensor was developed and evaluated in spring maize. Four field experiments were conducted at two locations during 2017 and 2018 to develop an algorithm, and two experiments during 2019 to validate the sensor-based application for improving N use efficiency (NUE) and grain yield. The sensor measurements made at V9 growth stage with R 2  value of 0.61 obtained from the relation between in-season estimate of yield (INSEY) and grain yield rendered better corrective N rate for improving NUE and getting optimum grain yield, whereas sensor measurements at V6, V12 and VT growth stages were not reliable for the purpose. Applying N rate in two splits of 30 kg N ha −1  at planting and 45 kg N ha −1  at V6 growth stage was recommended before applying sensor based corrective N rate at V9 stage. Sensor guided N topdressing produced yields similar to those obtained by following the soil test-based N recommendations but with lower N rates. These results were also reflected in considerable increase in N recovery (8  _ 18%) and agronomic (4  _ 13.5 kg grain kg −1  N) efficiencies in comparison with soil test-based N recommendations, thereby signifying the usefulness of the sensor-based algorithm in optimizing need-based fertilizer N management in spring maize.

Mid-season proximal sensing for site-specific need-based fertilizer nitrogen management in spring maize