Title: Nitrogen Management to Increase Profitability and Reduce Environmental Impact: A Case for Sensors Author
Submitted to: No Tillage National Congress in Argentina
Publication Type: Proceedings
Publication Acceptance Date: July 3, 2008
Publication Date: August 12, 2008
Citation: Kitchen, N.R. 2008. Nitrogen Management to Increase Profitability and Reduce Environmental Impact: A Case for Sensors. In: Proceedings of the 16th Congress of Aapresid, August 12-15, 2008, Rosario, Argentina. p. 119-126. Technical Abstract: Since soil types within and between corn (Zea mays L.) fields can be highly variable, the amount of nitrogen (N) provided by those different soil types to support production can also be highly variable. Ideally, the amount of N fertilizer added during a given growing season should be both climate-sensitive and site-specific. Numerous options have been explored for sensing the crop for N needs. Here three approaches are reviewed that are currently being evaluated or used in production agriculture: 1) aerial imaging, 2) hand-held chlorophyll meter, and 3) ground-based canopy reflectance sensors. Emphasis was given to canopy reflectance sensing. In recent years, this type of sensing has been proposed as a technology on which to base side-dress variable-rate N applications. Missouri research was conducted to assess on different soils the use of active crop-canopy reflectance sensors for assessing corn N need and developing algorithms for optimizing economic returns with variable-rate N fertilizer application. A total of 16 field-scale (400 to 800 m in length) experiments were conducted over four growing seasons (2004-2007) in three major soil areas of Missouri: river alluvium, deep loess, and claypan. Multiple blocks of N rate response plots were arranged in a randomized complete block design traversing the length of the field. Each block consisted of 8 N treatments from 0 to 235 kg N/ha on 34 kg /ha increments top-dressed between vegetative growth stage V7 and V12. Crop canopy reflectance sensor measurements were obtained from N response blocks and adjacent N-rich reference strips at the time of N application. Yield response to N rate was modeled using quadratic plateau functions then compared to canopy sensor readings. While this relationship was generally poor when different soils were combined, a profit optimization of these results from which algorithms were developed showed canopy sensing could improve profit. Generally with fertilizer to grain price ratios typical of what producers have seen in the past decade, profit using the sensors and an algorithm that combines all soil types was modest (<$15/ha). In deep loess soils, the profit that could be achieved improved, but this finding come from a smaller dataset and verification is needed. From this analysis, N saved over the producer rate ranged from 0 to 100 kg N/ha, but varied by soil type. This N savings was used in the profit analysis and constitutes and environmental benefit.