Potential Class Projects    
Class Publications

Nitrogen Use Efficiency, Nitrogen Fertilizers, NUE, Nitrogen and the Environment




Seed orientation determined at planting   www.nue.okstate.edu/Nitrogen_Conference2010/1st_Guillie_.pptx



  Class Projects / Research Ideas

1. Is cereal NUE for the world going down? (now have enough FAO data)
    Nitrogen Use Efficiency Definitions (NUE Web Site)

Improving Nitrogen Use Efficiency for Cereal Production  Agron. J. 91:357-363
   Response to Reviewers, Keeney 1982 Justification

World Phosphorus Use Efficiency in Cereal Crops
   Response to Reviewers 1
   Response to Reviewers 2
   Response to Reviewers 3  PUE Abstract
   Response to the Editor  PUE-PPT

2. Review, How Nitrogen Use Efficiency Can be Determined.  Methods for Estimating Nitrogen Use Efficiency in Cereal Crops (bottom of NUE Definitions Page)

Why are RI and YP0 independent?  (Why is this important)

4. Global Warming, Review and Interpretation of Contrasting Estimates

5. Sensitivity analysis, How important is Grain N? 

6. Updated NDVI-RI versus Yield-RI

7. Global warming gases from Animal Agriculture
   essential literature review example abstract World numbers Beef (grain fed) (grass fed)   Pork Chicken by-animal emissions/estimate (literature) Regional, USA, World

8. Bray's Mobility Concept/Sufficiency, 60 years later

9. What did the check plots yield? (Long Term Trials), Magruder Data    

( This should embed, Difference in Yield (delta yield) between high N and check )

10. How can yields be increased using less inputs?  Review, Theory

11. Historic NUE values for mid-season, sidedress N in Wheat and Corn

12. Bare soil, changing OM, add moisture -> resultant NDVI chart

13. Nitrogen Uptake with Time (various plant components) - show where "loss" can take place.

14. Potassium and Sulfur Use Efficiency in Cereals

15. Early season NDVI.  How can this be used (delta value versus actual value)

16. Global Warming Review, Agriculture's Accountability

17. Sensitivity Analysis? How important is Grain N?

18. Adoption Metrics in Corn and Wheat (What are the yield differences needed for producers to adopt, x-technology)

19. Monitor Organic Carbon decline in a small plot within three cemetery's that are within 70 miles of each other. Subsurface inorganic nitrogen accumulation as a result of first-time tillage (implemented in a historical site, graveyard, park area)

Math and Physics in High Yield Agriculture ______________________________


Gwen Weymeyer


GHG (Greenhouse Gas)




CO2 (carbon dioxide)




CH4 (methane)




CO2 (carbon dioxide)

6-25% (mean: 15.5%)



CO2 (carbon dioxide)




CO2 (carbon dioxide)







A. Biello, David. "The Carbon Capture Fallacy." Scientific American (2016): 58-65.
B. "Global Greenhouse Gas Emissions Data." 11 December 2012. United States Environmental Protection Agency . http://www3.epa.gov/climatechange/ghgemissions/global.html. 18 January 2016.
C. Kathleen Hogan, Michael Gibbs. "Methane." EPA (1990): 23-26.
D. R. W. Mullen, W. E. Thomason, W.R. Raun. "Estimated Increase in Atmospheric Carbon Dioxide Due to Worldwide Decrease in Soil Organic Matter ." Communication Soil Science Plant Analysis (1999): 1713-1719.
E. "Seven Environmental Threats ." Scholastic Update (1992): 6-7.
F. Singh, Hambir. "Climate Change: A Global Issue ." Special Focus on Carbon Dioxide (2010 ): 42-48.
G. "The Role of Livestock in Climate Change ." n.d. Food and Agriculture Organization of the United States . http://www.fao.org/agriculture/lead/themes0/climate/en/. 18 January 2016.

Patrick Curl

Determining the top five sources of global warming is dependent upon ones methods for grouping factors involved in global warming. Various methods can be employed to segregate sectors based upon either the type of pollution that contributes to increased greenhouse gases or, the industries themselves and the total emissions that they output. This analysis is based off of the approach of compiling all greenhouse gases produced by similar industries as opposed to entailing the top producers of specific greenhouse gases. As many agencies and parties of interest have conflicting measurements regarding greenhouse gas emission and categorization, this work seeks to find commonality amongst reported global greenhouse gas emission estimates. According to the Environmental Protection Agency of the United States of America, the following five industries represent the sectors who contribute the greatest to global warming in increasing order: buildings, transportation, industry, agriculture/forestry and electricity & heat production. The largest producing sector, electricity, emitted between 24 and 25% of global greenhouse emission in the mid-2000s. This narrowly exceeded the production of greenhouse gases from total global ag/land use, as estimates of 20-24% are generated from this sector. While this sector is extreme in its’ production of carbon dioxide, it also produces large amount of methane and nitrous oxide. Globally, the origin of 19 – 21% of the greenhouse gases emitted is a direct result of industrial manufacturing/production. While this estimate has declined recently, it still serves as an area for continued focus and improvement in lesser developed nations. Another leading producer of emissions, transportation, accounts for roughly 14% of global greenhouse gas emissions. This sector is largely targeted for its’ well known consumption of fossil fuels. Lastly, on-site generation of energy in buildings contributes around 10% of the global greenhouse gas emissions. The majority of emissions produced outside of these sectors can be attributed to indirect consequences of the energy sector. While these estimates are supported by various sources, it could be possible to view the production of greenhouse gases from agriculture or soil/environmental interactions as a more prevalent source for greenhouse gas emission. Based off of the historical loss of soil organic matter and deforestation practices, I would estimate that this industry contributes more greatly to the problem than estimated and could be closer to 30% of the total greenhouse gas production globally. With nearly 7 billion metric tons of carbon dioxide equivalent gases being produced annually, joint efforts will be needed between these major sectors and the countries abroad if outputs are to be reduced.  


Enkvist, P., Naucler, T. and Rosander, J. 2007. A cost curve for greenhouse gas reduction. European Union Commission: The McKinsey Quarterly.

Eurostat. 2015. Greenhouse gas emission by industries and households. United Nations Climate Change Convention. http://ec.europa.eu/eurostat/statistics-explained/index.php/Greenhouse_gas_emissions_by_industries_and_households (accessed 19 Jan. 2016).

International Transport Forum. 2010. Reducing Transport Greenhouse Gas Emissions.      http://www.internationaltransportforum.org/Pub/pdf/10GHGTrends.pdf (accessed 19 Jan. 2016).

IPCC. 2014. Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment. Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. (accessed 19 Jan. 2016).

USEPA. 2014. Climate Change: Source of Greenhouse Gas Emissions. USEPA. http://www3.epa.gov/climatechange/ghgemissions/ (accessed 19 Jan. 2016).

Verge, X.P.C., Kimpe, C.De. and Desjardans, R.L. 2007. Agricultural production, greenhouse gas emissions and mitigation potential. Agricultural and Forest Meteorology. 142:255-269.

Title: 2 lb N/bu (60 lb N/bu wheat) Review and Analysis

50% of N in grain comes from soil/atmospheric deposition, 2.39% N in the grain
____ fertilizer use efficiency

60 * 0.0239 = 1.43 lbs N/bu
1.43*0.5 = 0.715 lbs N from soil
0.715/0.35 = 2.04 lbs N/bu

56 * 0.011 = 0.616 lb N/bu
0.616 * 0.5 = 0.308 lbs N from soil
0.308/0.3 = 1.0 lbs N/bu

Harvest index of 0.5 (grain N / grain + stover N)
Final grain yield level of 10 Mg/ha (160 bu/ac)
Grain percent N = 1.2%
Stover percent N = 0.8%

10,000 kg/ha (20,000 biomas)
10,000*0.012 = 120
10,000* 0.008 = 80
80 kg N/ha accumulated by V12, 80/200 =  40%


Fertilizer N Rate Survey
Corn and Wheat

Sub-meter Spatial Variability

Algorithms for in-season Nutrient Management in Cereals


The demand for improved decision making products for cereal production systems has placed added emphasis on using plant sensors in-season, and that incorporate real-time, site specific, growing environments.

The objectives of this work were to describe validated in-season sensor based algorithms presently being used in cereal grain production systems for improving nitrogen use efficiency (NUE) and cereal grain yields.

A review of research programs in the Central Great Plains that have developed sensor-based nitrogen (N) recommendations for cereal crops was performed. Algorithms included multiple land-grant university, government, and industry programs.

A common thread in this review is the use of active sensors, particularly those using the Normalized Difference Vegetation Index (NDVI) for quantifying differences in fertilized and non-fertilized areas, within a specific cropping season. In-season prediction of yield potential over different sites and years is possible using NDVI, planting date, sensing date, cumulative growing degree days (GDD), and rainfall. Other in-season environment-specific inputs have also been used. Early passive sensors have advanced to by-plant N fertilization using active NDVI and by-plant statistical properties.  Most recently, sensor-based algorithm research has focused on the development of generalized mathematical models for determining optimal crop N application. These algorithms rely on a priori understanding of crop nutrient use related to crop growth and yield.

While development and promotion of fee-based modeling approaches for nutrient management continues, algorithms using active sensors for in-season N management are available, affordable, field tested and that can be modified by producers.