An active sensor algorithm for corn nitrogen recommendations based on a chlorophyll meter algorithm.

TL;DR: In this paper, an active canopy sensor algorithm based on a SPAD chlorophyll meter algorithm and validated the algorithm using data collected from a companion study was developed for in-season N management of irrigated corn.

Abstract: 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: N app = 317√0.97-SI sensor 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 (Nb 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.