Evaluating multiple indices from a canopy reflectance sensor to estimate corn n requirements

0
With the increasing cost of fertilizer N, there is a renewed emphasis on developing new technologies for quantifying in-season N requirements for corn (Zea mays L.). The objectives of this research are (i) to evaluate different vegetative indices derived from an active reflectance sensor in estimating in-season N requirements for corn, and (ii) to consider the influence of the N:Corn price ratio on the economic optimum nitrogen rate (EONR) developed using these indices. Field experiments were conducted at eight site-years in central Pennsylvania. A two-way factorial experiment was implemented as a split-plot randomized complete block (four blocks) design, with different rates of N applied (i) at planting (NPL) to create a range of N supply, corn color, and radiance; and (ii) at V6 (NV6) to measure yield response to NV6. Canopy reflectance measurements were obtained using a Crop Circle (Holland Scientific, Lincoln, NE) sensor just before NV6 applications, and grain yield was determined at harvest. The EONR was determined using a quadratic-plateau yield response function for price ratios from zero to 14:1, then regressed on 21 combinations of absolute and relative spectral bands and indices. The EONR at V6 at 6:1 price ratio ranged from 0 to 221 kg ha–1 among the eight site-years, with a mean of 69 kg ha–1. Better prediction of EONR was obtained by indices calculated relative to a high N plot rather than absolute indices. Relative Green Difference Normalized Vegetation Index by ratio (RGNDVIR) was the best predictor of EONR at V6 when expressed as a linear-floor model (R2 of 0.79). A relationship was developed so that EONR estimates derived using the Crop Circle sensor could be easily adjusted based on the current N:Corn price ratio. When N requirements are high (RGNDVIR = 0.8) and if the price ratio changes from 4:1 to 10:1, the EONR would change from 267 to 214 kg ha–1 N.

Customer comments

No comments were found for Evaluating multiple indices from a canopy reflectance sensor to estimate corn n requirements. Be the first to comment!