1. Organic Carbon (Ranney Paper, OC conversion) 

www.co2now.org

Brazil C-Stocks

Nutrient Content of Crops, USDA

2. History of Yield Potential

3. Nitrogen

4. Nitrogen Accumulation Page (NUE.okstate.edu,
Articles at the bottom)

5. Amino Sugar N test (J. Bushong)

6. Rice NUE, (J. Bushong)

N Cycle (dial)

7. Nitrogen Use Efficiency (Review)

8. Theoretical Applications

Appendix 8:  Phosphorus Solubility

(NO3-N, NH4-N with time)

502, SBNRC, 100 pre

502 Yield Differences over time

9. Nitrogen Fertilization Optimization Algorithm and the use of CV's

10. R.A. Olson, Soil Testing  (Commercial Labs versus University Labs) 
        Who is serving as the Judge?  Law?

Steven Chu
Check Plots  

N Cycle

Paul Hodgen (Uptake of 15N by Neighboring Corn Plants)
What does this look like?  Corn plants spaced 7 in (18cm) apart?
Drawing/Illustration)

 PHOSPHORUS

(P Web Page) DUAL PLACEMENT

Horizontal Bands
Phosphorus Solubility

Broadcast Preplant versus Banded P
Maintenance versus Sufficiency (Roger Bray)

 Buildup versus Maintenance

A Nutrient Mobility Concept of Soil Plant Relationships (Roger H. Bray, Univ. of Illinois) Sufficiency

 BY-PLANT, CORN

12. By Plant Variability (46 Transects)
also included is the 2005 AJ publication

13. By Plant Prediction (bottom of page)

13A. By-plant corn excavations (bottom)

14. NCR-rate recommendations, 1 Bundy

15. Catch UP (go to conclusions), Brixey 2006  Dependent on CV of

CV-RI (excel file, sensitivity analysis, homework)

Concept, CV-RI (excel file)

CV RI Homework

SAS Programs Examples/homework (LAST week of class)

ABSTRACT EXERCISE

N DEMAND, ABSTRACT
Maize (Zea mays L.) grain yield levels and the response to fertilizer nitrogen (N) are expected to change from year to year and location to location.  Because yield level and N response have been documented to be independent, and known to influence N demand, optimum N rates at the same location are expected to change each year due to unpredictable changes in the environment. The objective was to further analyze maize grain yield levels and optimum fertilizer N rates from published data in the Central Great Plains of the United States. Optimum N rates were determined by calculating the difference in N uptake between the highest yielding plot and the check plot (no N applied). The difference in grain N uptake between the fertilized and zero-N check plot was then divided by 0.33 (average N use efficiency) to estimate optimum N rate, by site and year. For the 198 site-years of data included, grain yields in both the high N rate, and check (0-N) plots were highly variable.  Also, optimum N rates fluctuated from year to year at all locations. Optimum N rates were not highly correlated with the high N rate yield (R2=0.20) or zero-N check yield (R2=0.16). The wide range in optimum N rates observed in all maize experiments suggests the need to adjust N rates by year and location. This is possible using mid-season sensor based technologies that can accurately predict yield potential (expected yield level), and simultaneously encumber N responsiveness known to be independent of yield. 

SENSOR BASED ALGORITHMS, ABSTRACT
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. The development and promotion of fee-based modeling approaches for nutrient management continues.  Nonetheless, several algorithms using active sensors for in-season N management are available from state and government sources at no cost and that have been extensively field tested and can be modified by producers...... 

For Iowa (largest tonnage of fertilizer N purchased and applied in the US), this has become somewhat uncomfortable as within-state lawsuits have been filed against maize (Zea mays L.) producers surrounding the Des Moines and Raccoon rivers for over applying N (Charles, 2015). Solutions exist but involve practices that will require a significant investment in equipment and management (Roberts et al., 2012).

What did The Check Plots Yield?  (WORD DOCUMENT with SAS)

In long-term experiments, grain yields of the check plot (no N applied) can reveal added information about the environment when studied alone.  The objective of this work was to further evaluate check plot yields and how they changed over time.  Furthermore, changes in check plot yields were expected to provide a better understanding of fertilizer N response and yield potential.  Two long-term experiments, were targeted for added analysis, Experiment 222 near Stillwater, OK, and Experiment 502, just west of Lahoma, OK.   Check plots had the same variability over years as did the nitrogen (N) fertilized plots, with CV’s for both near 30%.  Means and standard deviations (Experiment 502) were 1.76 ±0.53 and 2.95±0.92 Mg/ha for check and N fertilized plots, respectively. 

World Phosphorus use Efficiency in Cereal Crops, ABSTRACT

A current estimate of global phosphorus use efficiency for cereal production is not available. The objective of this paper was to estimate P use efficiency for cereal crops grown in the world today. Phosphorus use efficiency (PUE) was determined using world cereal harvested area, production, and P fertilizer consumption from 1961 to 2013, in addition to assumptions established from previous literature. World PUE of cereal crops was calculated as the amount of cereal grain P removed minus P in the grain coming from the soil and divided by the amount of P fertilizer applied. Utilized in this analysis was the value for cereal production, accounting for 47.9% to 61.3% of the total agricultural land. Cereal grain yields increased from 1.35 Mg ha-1 to 3.90 Mg ha-1 between 1961 and 2013. In 1961, the world’s fertilizer P consumption was 4,765,810 Mg and increased to 17,678,101 Mg of P fertilizer by 2013. This represents a 371% increase in P fertilizer consumption over 52 years. This study shows that world PUE of cereal crops are generally low, with considerable opportunity to promote improvements in the use of P fertilizers. Global PUE for cereal crops has ranged from 12 to 20% (1980 and 2008, respectively) with present estimates of 21 % in 2013.

1. Lahoma 502, 2015 (on NUE web) SBNRC Testing

SBNRC-IOWA, Russ Linhardt (also, 2010, 2011 wheat) (502 testing of SBNRC?)

Use of GDD, INSEY, Mesonet

World Computation of NUE (Agronomy Journal 1999, 91:357)

Yield Level, N Demand

SED
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STOP, end of material for spring 2016

NUE, Missouri, Nitrogen efficiency in our N systems study fields

9. P Solubility.
PUE Review (4/9/2014)

a. Syers (Efficiency of soil and fertilizer phosphorus use)
b. Johnston (New approach for PUE)

c. Sander et al. (1990)

--------------------------------------------------------------------------------------------------------------------------------------------------------------

(N publications)
(Agronomy Journal, Most Cited)

N Cycle (Yield Level, N Response)

10. SPATIAL N Variability

11. Cereal nitrogen use efficiency in Sub Saharan Africa. J. Plant Nutr. 32:2107-2122

12. Foliar UAN for Mitigating Frost Damage

13. Nitrogen Cycle

Rates of Salt (N+K2O) that can be applied with the seed (1986 Fertilizer Solutions Article)

Spring2014/IMG_x.pdf

14. Argentina, NO-TILL
Success

16. Soil Fertility and Hunger in Africa
Fertilizer costs 2 to 6 times more
Rock phosphate - alternative

Leguminous trees of the genera Sesbania, Tephrosia, Crotalaria, Glyricidia, and Cajanus are interplanted into a young maize crop and allowed to grow as fallows during dry seasons, accumulating 100 to 200 kg N/ha over the period from 6 months to 2 years in subhumid tropical regions of East and Southern Africa. The quantities of nitrogen captured are similar to those applied as fertilizers by commercial farmers to grow maize in
developed countries.

"The approach reported here is effective and more appropriate to current African conditions than those used during the Green Revolution. These “low-tech” but knowledge-intensive technologies should precede the promise of genetic engineering and other “high-tech” approaches, because without available nitrogen and phosphorus in the soil African farmers have no chance of succeeding."

17.  Radioisotopes
supplemental lecture

Increased plant N loss with increasing nitrogen applied in winter wheat observed with 15N.  J. Plant Nutr. 23:219-230. (pdf)

Mass Spec Output

Radiation dose chart

Radioisotopes (List) from Vose

ETHANOL

18. Added Topics, Cellulosic Ethanol,

Biofuels lead to food shortages

Biofools (The Economist)

Difficulty in making ethanol from cellulose

19. Direct Seeding in Argentina (Agustin Bianchini)

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Population 9 Billion

9. Biometrical Applications (class survey)
Stability Analysis (excel)
Stability Analysis 502

REVIEW

(Soybean N Balance, Andres Patrignani, Romulo Lollato.)

Andres Patrignani- Wheat yield plateau

https://www.agronomy.org/publications/aj/view/first-look/aj14-0011.pdf

12. Biofools

13. Ethanol

US Military
(wikipedia)

14. Resurgent Forests Can be Greenhouse Sponges (Science)

15. Corn Farmers Making Money

16. The Magruder Plots, Untangling the Puzzle.  (Agron J. 1191-1198)

17.  The Story of Wheat (from the Economist.com)

How can N2O emissions be reduced?   

Reducing N2O Emissions

Reducing N2O

 Radioisotope Exercise

Independence of YP0 and RI

Independence of YP0 and RI-2

NEWTON
Inverse Distance Square Law
Isaac Newton and 2060
Newton Accomplishments

CLASS READING

1. Estimated  Increase in Atmospheric Carbon Dioxide Due to worldwide decrease in Soil Organic Matter


2. Estimated land area increase of agricultural ecosystems to sequester excess atmospheric carbon dioxide. Commun. Soil Sci. Plant Anal. 32:1803-1812. (pdf)


GMO's    Why people oppose GMO's even though Science says they are safe (Scientific American) read last paragraph


Cheerios USA Today


4. Effect of long-term N fertilization on soil organic C and total N in continuous wheat under conventional tillage in Oklahoma

5. Influence of conservation tillage on soil properties. 1983. R.L.Blevins.   (Harvest Index at high N)

6. Nitrous Oxide Emissions from Continuous Winter Wheat in the Souther Great Plains.

From E.N. Ascencio thesis

7. Effect of long-term fertilization on soil organic C and total N in continuous wheat under conventional tillage in Oklahoma. (Soil Tillage Res. 47:323-330).

8.  Priming Effect of 15N-Labeled Fertilizers on Soil Nitrogen in Field Experiments. SSSAJ, 37:725-727.

9. Evidence of dependence between crop vigor and yield.  Prec. Agric. 13:276-284.

10. Equations for Estimating the Amount of Nitrogen Mineralized from Crop Residues. 1991. SSSAJ,55:757

11.  N fertilizers decrease soil organic C. Mulvaney, Univ. Illinois.

12. JEQ Article, Khan and Mulvaney

13. High N rates can increase soil organic C, Soil and Tillage Research.

14. Corn Yield Response to Nitrogen Rate and Timing in Sandy Irrigated Soils. 2005. Agron. J. 97:1230-1238.

REVIEW (CO2)

Mulvaney: 15. Myth of NItrogen Fertilization for Soil Carbon Sequestration

Mulvaney: 16.  Synthetic Nitrogen Fertilizers Deplete Soil Nitrogen: A Global Dilemma for Sustainable Cereal Production

Phillips: 17. Seasonal and long-term changes in nitrate-nitrogen content of well water in Oklahoma.  1997.  J. Environmental Quality, 26:1632-1637.

Mulvaney 18. Need for a Soil-Based Approach in Managing Nitrogen Fertilizers for Profitable Corn Production

19. Westerman, NH4 and NO3 Accumulation

20. Soil Plant Inorganic N Buffering, 1995

(SOIL 5112, SAS Programs)

21. Concepts and Rationale for Regional Nitrogen Rate Guidelines for Corn (Sawyer, Nafziger, Randall, Bundy, Rehm, Joern)

22.  Post-anthesis nitrogen loss from corn. Agron. J. 85:659-663.

23.  Increased plant N loss with increasing nitrogen applied in winter wheat observed with 15N.  J. Plant Nutr. 23:219-230. (pdf)

24.  Effect of nitrogen rate on plant nitrogen loss in winter wheat varieties. J. of Plant Nutr. 20 (2&3):389-404.

25. Freeze mitigation

26.  What to expect, CV, NDVI, and Yield (Mexico Trip, OSU Students)

GMO's
-------------------------------
27.  GM crops, world statistics

28.  Consumers afraid of Biotech?


 "I have heard it said that the average person is lucky to have only a handful of true friends in their lifetime.  Well, I sincerely feel I've got millions.  John Wooden once told me "I would rather believe in people and be disappointed some of the time than never believe and be disapppointed all of the time."  JN




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Nitrogen Uptake Exercise

N Uptake Excel File


Homework #2 Due Friday Feb 19, 2016
  Experiment 406
  Experiment 407

Homework #3.

Compute the number of days from planting to sensing, where growth was possible (40°F Threshhold) for a planting date of October 1, 2015, Sensing Date of February 21, 2016 (Locations, all 4-Payne County, Altus, Woodward)

Homework #4 (included in the excel sheet)

 

    

READING
_________________________________________________
____________________________________________



1. Becoming a Nitrogen Cycle Ninja (Bloomington, IL, Feb 3, 2015) 

2. Nitrogen Cycle Ninja (Manuscript)

3. N Deposits in Rainfall

4. Equations for Estimating the Amount of Nitrogen Mineralized from Crop Residues Vigil and Kissel, 1991


5. Independence of YP0 and RI

6. Independence of YPO and RI2

(reviewer response 1)
(reviewer response 2)
7. Improving Nitrogen Use Efficiency, 1999, AJ
(excel file 2010)

8. Global Population and Nitrogen Cycle (V. Smil)



HOMEWORK 1

9.  Bray Mobility Concept (A Nutrient Mobility Concept of Soil-Palnt Relationships)

10. Investment in By-Plant Technology

MISSION II

Presentation, November 5, 2012, Dr. Bobby Stewart

Multilingual Crop Nutrient Removal Calculator

http://ipni.info/calculator

 Feeding our World (link)

2 lbs N/bu of wheat (recommendation)

Article

 on Kernza, Univ. Minnesota


LIMUS Nitrogen Management, BASF

 BAE Article, Dr. Borlaug