Sensor-Based Algorithm for Mid-Season Nitrogen Application in Corn

Abstract

Applying insufficient nitrogen (N) in a highly responsive crop, such as corn, results in lower grain yield, quality, and profits. On the other hand, when nitrogen is applied in excess of crop needs, profit is reduced and negative environmental consequences are likely. The objective of this study was to develop and employ a sensor-based algorithm to determine the mid-season N requirements for deficit-irrigated corn in Coastal Plain soils. The algorithm was developed using varied prescription rate N plot on two soil types. The test plots received nine different rates of N fertilizer, replicated 5 times in plots of each soil type using a Randomized Complete Block design. A 6-row GreenSeeker optical sensor was used to measure plant NDVI, between the V6 to V8 growth stages. The sensor readings were used to develop an algorithm to be used in the estimation of side-dress N application in corn. The NDVI sensor readings were collected at the V6 to V8 growth stage during the 2015 and 2016 growing seasons correlated with actual corn yields (R 2 > 0.68, p < 0.001). In-Season Estimated yield (INSEY) was used along with the actual yield to produce a yield potential for each growing season for deficit-irrigated corn crop. In summary, the algorithm developed from the NDVI readings reduced N application rates by 21% and 34% in soil types 1 and 2, respectively, compared to the normal grower practice (226 kg N/ha) with no reduction in corn yields.