An Active Sensor Algorithm for Corn Nitrogen Recommendations Based on a Chlorophyll Meter Algorithm

In previous research we found active canopy sensor reflectance assessments of corn ( Zea mays L.) N status have potential for directing in‐season N applications, but emphasized an algorithm was needed to translate sensor readings into appropriate N application (N app ) rates. The objectives of this work were to: (i) develop an active canopy sensor algorithm based on a SPAD chlorophyll meter algorithm and (ii) validate the active canopy sensor algorithm using data collected from a companion study. We derived the sensor algorithm using a linear relationship between sensor sufficiency index (SI sensor ) and SI SPAD values established in the previous research and a published SPAD algorithm employing a quadratic equation to calculate N app as a function of SI SPAD . The resulting equation: represents the function for translating SI sensor to N app . To validate the algorithm, SI sensor values collected from small plots receiving varying N amounts were converted into N app using the algorithm. Then N app was converted into crop N balance (N balance ) estimates, where N balance = applied N‐N app . Negative N balance values indicate N deficiency while positive values indicate excess N. The N balance values were compared with relative yields and a quadratic‐plateau model fit to the data set for both growth stages (V11 and V15), producing an R 2 of 0.66. Relative yields plateaued at an N balance near zero (−11 kg N ha −1 ), indicating the algorithm provided reasonable estimates of N app for maximizing yields. The equation provides a basis for the use of active crop canopy sensors for in‐season N management of irrigated corn