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ARS Home » Northeast Area » University Park, Pennsylvania » Pasture Systems & Watershed Management Research » Research » Publications at this Location » Publication #257215
Title: Improving in-season nitrogen recommendations for maize using an active sensor

Author
item Schmidt, John
item BEEGLE, DOUG - Pennsylvania State University
item ZHU, QING - Pennsylvania State University
item SRIPADA, RAVI - Monsanto Corporation

Submitted to: Field Crops Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/9/2010
Publication Date: 10/19/2010
Citation: Schmidt, J.P., Beegle, D., Zhu, Q., Sripada, R. 2010. Improving in-season nitrogen recommendations for maize using an active sensor. Field Crops Research. DOI: 10.1016/j.fcr.2010.09.005.

Interpretive Summary: Too much N fertilizer is applied to corn (Zea mays L.) that is unused by the growing crop, and consequently leaves the field and causes a cascade of environmental problems related to N enrichment. Recent technological advances in reflectance sensors promises the possibility of developing improved N recommendations for corn with an opportunity to variably apply N fertilizer based on spatially and temporally dependent factors. We compared N recommendations based on a sensor to more traditional and somewhat static methods, such as the presidedress nitrate test (PSNT) and chlorophyll meter (SPAD). Crop canopy reflectance information obtained when the corn was at the 6th-7th mature leaf stage was as an effective indicator of optimum N rate for corn as was PSNT or SPAD. While using the sensor to make N recommendations for corn might represent a technological hurdle for some producers, routine implementation after adoption would be simpler, more efficient, and more effective than either PSNT or SPAD. Applying the optimum N rate throughout a field, across the farm, and throughout a watershed would be more likely with the widespread adoption of this technology.

Technical Abstract: An active crop canopy reflectance sensor could be used to increase N-use efficiency in corn (Zea mays L.), if temporal and spatial variability in soil N availability and plant demand are adequately accounted for with an in-season N application. Our objective was to evaluate the success of using an active canopy sensor for developing corn N recommendations. This study was conducted in 21 farmers’ fields from 2007 to 2009, representing the corn production regions of east central and southeastern Pennsylvania, USA. Four blocks at each site included seven sidedress N rates (0 to 280 kg N per ha) and one at-planting N rate of 280 kg N per ha. Canopy reflectance in the 590 nm and 880 nm wavelengths, soil samples, chlorophyll meter (SPAD) measurements and above-ground biomass were collected at the 6th-7th-leaf growth stage (V6-V7). Relative Green Normalized Difference Vegetative Index (GNDVIrelative) and relative SPAD (SPADrelative) were determined based on the relative measurements from the zero sidedress treatment to the 280 kg N per ha at-planting treatment. Observations from the current study were compared to relationships between economic optimum N rate (EONR) and GNDVIrelative, presidedress nitrate test (PSNT), or SPADrelative that were developed from a previous study. These comparisons were based on an absolute mean difference (AMD) between observed EONR and the previously determined predicted relationships. The AMD for the relationship between EONR and GNDVIrelative in the current study was 46.3 kg N per ha. Neither the PSNT (AMD = 66 kg N per ha) nor the SPADrelative (AMD = 71.8 kg N per ha) provided as good an indicator of EONR. When using all the observations from the two studies for the relationships between EONR and the various measurements, GNDVIrelative (R2 = 0.65) provided a better estimate of EONR than PSNT (R2 = 0.49) or SPADrelative (not significant). Crop reflectance captured similar information as the PSNT and SPADrelative, as reflected in strong relationships (R2 greater than 0.60) among these variables. Crop canopy reflectance using an active sensor (i.e. GNDVIrelative) provided as good or better an indicator of EONR than PSNT or SPADrelative, and provides an opportunity to easily adjust in-season N applications spatially.