Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 5/20/2010
Publication Date: 7/18/2010
Citation: Kitchen, N.R., Sudduth, K.A., Drummond, S.T. 2010. Is a Nitrogen-rich Reference Needed for Canopy Sensor-based Corn Nitrogen Applications?. International Conference on Precision Agriculture Abstracts & Proceedings. Available: http://www.icpaonline.org/finalpdf/abstract_213.pdf
Interpretive Summary: With increasing costs of nitrogen (N) fertilizer in recent years, corn farmers are interested in better methods to help them more precisely apply this nutrient on fields for optimal profit. Also since N has been tied to environmental and climate change issues, farmer and public interest is high for exploring new technologies for improved corn N management. Light reflectance sensors have been introduced and are used by some farmers as a technology on which to base side-dress variable-rate N applications. Most often sensor readings from a small area of a corn field that has been well fertilized at planting and is known to be non-limiting in N (the N-rich area) is compared to sensor readings as they are taken on the rest of the field. Generally, the greater the difference in sensor measurements between N-rich corn and the area yet to fertilized, the more N fertilizer is applied. The challenge is that establishing N-rich areas is often inconvenient for farmers, since this coincides with other demanding spring operations. Thus we asked the question, is an N-rich reference needed? The objective of this research was to answer that question. We found over many producer fields that canopy sensor values for N-rich corn were lower (meaning they greater biomass and/or greener plants) when compared to sensor readings from unfertilized corn. This result is consistent evidence of the sensor’s ability to detect differences in N status of the crop. We were also able to develop a model that used average sensor readings of unfertilized corn, growth stage at sensing, and the amount of starter N fertilizer applied at planting to successfully predict a reasonable value for N-rich corn. If this model proves consistent once tested on other fields, it will greatly simplify procedures for farmers and thus many more may be willing to adopt canopy sensor technology for N application. Based on other research we have done with these sensors, less N fertilizer will be used, money can be saved by farmers, and N loss to lakes and streams will be reduced.
Technical Abstract: The nitrogen (N) supplying capacity of the soil available to support corn (Zea mays L.) production can be highly variable both among and within fields. In recent years, canopy reflectance sensing has been investigated for in-season assessment of crop N health and fertilization. Typically, the procedure followed compares the crop in an area known to be non-limiting in N (the N-rich area) to the crop in a target area, which may be inadequately fertilized. Measurements from the two areas are used to calculate a relative reflectance to represent the potential need for additional N fertilizer. Establishing in N rich areas or strips is often inconvenient for farmers, since this coincides with other demanding spring operations. Thus the question has been asked, is an N-rich reference needed? The objective of this study was to answer that question. A total of 16 field-scale experiments were conducted over four growing seasons (2004-2007) in three major soil areas of Missouri, USA: river alluvium, deep loess, and claypan. Multiple blocks of randomized N rate response plots traversed the length of each field. Each block consisted of 8 N treatments from 0 to 235 kg N/ha on 34 kg N/ha increments, top-dressed between vegetative growth stages V7 and V11. Adjacent to the response blocks, N-rich (235 kg N/ha) reference strips were applied at or just after planting. Crop canopy reflectance sensor measurements in the format of inverse simple ratio values (Vis/NIR) were obtained from the N response blocks and adjacent treatment strips at the time of top-dress N application. Viewed in frequency distribution diagrams, canopy sensor ISR values for target corn were almost always higher than those for N-rich corn, had a greater range of values, and were more positively skewed. Using multiple linear regression, we developed a model that used only the average sensor readings of unfertilized corn, growth stage, and planting N amount. This model successfully predicted 75% of the variation in average N-rich reference sensor measurements. If this N-rich reference strategy proves consistent and reliable for making in-season N fertilization recommendations, the resulting simplifications may result in more farmers adopting this technology.