http://www.fao.org/globalsoilpartnership This presentation was made during the GSP/E-SOTER Global Soil Information workshop that took place at the FAO HQ, Rome , Italy from 20-23 March 2012. This presentation was made on the first day by Terry Roberts, and it presents The Value of Global Soil Information to the International Plant Nutrition Institute. ©FAO: http://www.fao.org

1. The Value of Global Soil Information to the
International Plant Nutrition Institute
GSP/e-SOTER workshop
March 20, 2012, Rome, Italy
Terry Roberts, PhD
President, IPNI
Better Crops, Better Environment … through Science

2. • IPNI is a not-for-profit, scientific
organization supported by leading
fertilizer manufacturers and industry
associations
• Our mission is to develop and
promote scientific information
about the responsible management
of plant nutrition
Better Crops,Better Environment … through Science

3. Eastern Europe
and Central Asia
Australia/New
Zealand
Middle
East
North
America
Northern
Latin America Brazil
China
South
Asia
SE Asia
Latin America
Southern Cone
IPNI … 30 scientists working 12 Program Areas
Africa
Mexico &
Central America

4. Multipleissues/benefitsof soils
• Degraded soils, soil
protection, sustainable soil
management … impact food
security, water resources,
biodiversity, carbon
sequestration
• Of most concern to IPNI are
those related to soil-plant
relationships … soil fertility

5. Soil-plant relationships
• Soil physical, chemical, and
biological characteristics …
support or limit productivity
• Soil characteristics in
relation to parent material
affect soil nutrient supply
and other factors impacting
crop production
• Accurate information about the distribution and variability
of soil properties, at the proper scale is needed to
optimize inputs

6. IPNI uses global soil information to facilitate
the management of plant nutrients
• To make better general and site-specific nutrient
management decisions
• To identify areas of poor or excessive soil fertility
• To better understand and manage soil variability
• To link soil information to decision support tools

7. Appliedsoil fertility … soil testing, calibration
and fertilizer recommendations

8. Median soil test K levels in 2010.

9. Percent of samples testing below critical levels for K
for major crops in 2010.

10. Relationship between soil test K and relative soybean
yield and soil test K and K2O rate (Arkansas)
What happens when soil testing and calibration trials
are not available?

11. Supply of nutrients from the soil can estimated using
omission plot techniques.
• Small plots where each of
the nutrients being
evaluated is omitted,
while all the other
nutrients are adequately
supplied
• Use the agronomic efficiency (AE) from omission plots
to determine fertilizer rates in similar soils
• AE= Y-Y0/F

12. Example:calculating fertilizer rates from
omission plots in winter wheat from India
Treatment Yield, kg/ha
1. Ample rates of N, P, and K 5,556
2. N omitted; ample rates of P and K 1,667
N rate= 150 kg/ha
AE = (5,556 – 1,667)/150 = 26 kg of grain/kg of N
If the target yield was 4,500 kg/ha:
Calculated N rate = (4,500 – 1,667)/26 = 109 kg/ha
IPNI unpublished data, 2011

13. Site-specificnutrient management (SSNM)
• Set of nutrient management principles used to make
field-specific decisions on N, P, and K management
tailored to a specific field or growing environment. It
aims to:
– account for indigenous nutrient sources, including crop
residues and manures
– apply fertilizer at optimum rates and at critical growth
stages to meet the deficit between nutrient need and
indigenous supply
• Originally developed for rice in Asia by IRRI and now
successfully adapted for maize and wheat

14. Generic principles of SSNM for calculating
fertilizerrequirements

15. Challengewith SSNM …
• Mainly a research tool … little adoption by farmers
beyond on-farm trials. Farmers rely on extension for
nutrient management guidance
• Extension agents lack confidence in using the
methodology and many perceive SSNM as too
complicated
• Decision support tools make
the use of SSNM easy … e.g.
IRRI’s Nutrient Manager for
Rice
Source:http://webapps.irri.org/nm/nmtutorial/

16. Decision support tools help advisers develop
fertilizerrecommendations for a specific field
or growing environment
• IPNI has developed
simple software based
on the principles of
SSNM to help advisers
develop fertilizer
recommendations for a
specific field or growing
environment Source: http://seap.ipni.net/articles/SEAP0059-EN

17. Nutrient Expert follows principles of the QUEFTS model
in using the relationship between the uptake of nutrients
at harvest and grain yield to develop NPK requirements
http://seap.ipni.net/articles/SEAP0059-EN

19. Nutrient Expert for Hybrid Maize: SSNM Rates
• In the absence of data from nutrient omission plots, NE
estimates attainable yield and yield responses to N, P, and K
based on climate and soil properties, i.e. soil fertility indicators

20. NE decision rules for use of proxy information to
estimate SSNM parameters
SSNM parameter Proxy information
Attainable yield • Characteristics of the growing environment
(water availability, risk of flood/drought, soil
depth, problem soils)
• Maximum attainable yield (Ymax) – based on
experts’ experience or crop modelling
• Farmers’ actual yield
Yield response • Soil fertility indicators: soil texture, soil
color/OM content, historical use of organics,
soil test for P/K (if any; not required)
• Nutrient balance (P and K) from previous crop
(affected by nutrient inputs, crop residue
management, irrigation water for K)

21. NE decision rule: estimate attainable yield
1. Determine the maximum attainable yield (Ymax) for the
region, province, or domain
• what can be attained with BMPs, considering climate and soil
constraints
• from local experts’ experience or crop modeling of yield potential
2. Estimateattainable yield (Ya) for a location depending on
the growing environment and the current yield of the
farmer (Y)
• Growing environment: low-risk, medium-risk, and high-risk —
depending on presence or lack of risks (i.e. drought, flooding,
problem soils, etc)

22. NE decision rule: estimate yield response to fertilizer
Soil fertility class Characteristics
low
sandysoil regardless of soil color, or
clayey or loamy and reddish/yellowish
medium clayey or loamy and grayish/brownish
high
clayey or loamy and very dark soil with high OM
and high fertility
Assessment of soil fertility class

23. NE decision rule: estimate yield response to fertilizer
Observations and assumptions
• The nutrient-limited yield (i.e. Y0N, Y0P, Y0K) is a fraction of the
attainable yield (Ya).
• For a specific field or location, nutrient-limited yield follows the
same trend as Ya, which depends on the climate.
• Under the same climatic condition, the indigenous nutrient
supply (soil fertility) will determine the nutrient-limited yield.
The indigenous nutrient supply (INS, IPS, IKS) will determine the
ratio of nutrient-limited yield to attainable yield (i.e. Y0N/Ya,
Y0P/Ya, Y0K/Ya).

24. NE decision rule: estimate yield response to fertilizer
• For a given attainable yield (Ya) and soil
fertility class, NE estimates N-limited
yield (Y0N) from ‘Y0N/Ya’. It assumes
that:
– the median represents soils with
average fertility or indigenous N supply
(INS)
– the 25th percentile represents low INS
– the 75th percentile represents high INS
• N response = Ya * N response factor
N response factor = 1– ‘Y0N/Ya’ (for the
INS level)
Grain yield with NPK (t/ha)
0 2 4 6 8 10 12 14
GrainyieldwithoutfertilizerN(t/ha) 0
2
4
6
8
10
12
14
China
S. Asia
25th
median
75th
L
M
H
• NE determines the indigenous N supply class (low, medium, high) from
soil characteristics (texture, soil color and/or organic matter content)
Source: IPNI data (unpublished)
N response based on INS class

25. Spatially variable soil fertility in North Vietnam and its
implications for fertilizer needs
• Soil survey on more than 100,000
ha of degraded soil with intensive
rice and maize cultivation in
North Vietnam revealed potential
large-scale nutrient stresses
– Area of small farms (0.3 ha) with
large field-to-field variability in
terms of crops, cropping practices,
fertilizer use, and soil fertility status
• Permanent variability in soil properties in relation to parent
material affecting soil nutrient supply and factors relevant to
crop production
Source: Wittet al. 2007

26. Objective of survey: Assess spatial variability of soil
properties that (i) affect general soil fertility for rice
and maize and (ii) soil indigenous supply of nutrients
Location of degraded
soils (blue) and study
sites (red)
• Red River Delta in Vietnam has
about 132,000 ha of degraded
soils of light or gray color
- characterized as low fertility
because of parent material and
nutrient losses from leaching and
intensive cropping
• Base samples on 1 x 1 km grid
(100 ha) with additional transects
giving spatial support of 100 x 100
m (1 ha) to model short-distance
spatial variability

27. Survey results …
• Correlation analysis indicated weak relationships between
easily measured soil parameters (e.g. elevation and texture)
and those related to nutrient status like organic matter or
exchangeable bases … mapped soil parameters individually
Soil pH in degraded soil of North Vietnam. Interpolation by kriging.

28. Spatially variable soil fertility in North Vietnam
and its implications for fertilizer needs
• More systematic research on
spatial variability is needed in
small-scale rice, wheat, and maize
in Asia is needed to improve
SSNMrecommendations.
• Reliance on old soil maps to help
delineation of borderlines for
fertilizer recommendationsare
problematic, because they were
not developed for agronomic
purposes.

29. Would global soil information facilitate the transfer
nutrient management information from one location
in the world to another?
Example:
• IPNI’s SE Asia program has successfullydeveloped a system of
sustainable agronomic BMPs at commercial oil palm
plantations in degraded land environments in South Asia that
have increased yields by 25%
• We are developing an Alliance for Ecological Oil Palm
Intensification to try an adapt BMPs developed in Southeast
Asia to elsewhere in the world.

30. Global soil information would aid the transfer of
nutrient management information from one location
in the world to another.
Homologue Evaluation of Environments (climate)
Oil Palm in SE-Asia
This data is based on climate only, and would benefit from a soils overlay.

31. Global soil information … often outdated and
inadequate
• Better linkage of global soil information to decision
support tools …
• Need to extrapolate soil information to:
– yield gap analysis and target yields: assess nutrient limited
yields and develop target from soil information
– Integrate risk from soil degradation, soil acidity, salinity,
nutrient depletion, excessive nutrient loading, etc.
– Incorporate spatial soil information’s impact on nutrients
and nutrient supply

32. www.ipni.net
Better Crops, Better Environment … through Science