28/11/2014
Adding sustainability to productivity
Seminar on Smart Fertilization
Bemesting in de 21e eeuw : Smart Fertilization
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Prof. Martin Kropff click in programme on 14.00-14.10 Rector Wageningen University
28/11/2014
Seminar on Smart Fertilization
Welcome: The commitment of WUR to Smart Fertilization
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28/11/2014
Prof. Rudy Rabbinge Wageningen University
Seminar on Smart Fertilization
C.T. de Wit revisited; from fertilizer placement to smart fertilization
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Smart nutrient use according to de Wit from theory in the fifties to adoption today Prof. dr ir Rudy Rabbinge Emeritus university professor Sustainable Development & Food Security ‘De Wit revisited’, Wageningen Nov. 28th 2014
Outline
1
Global food security
2
Contributions C.T. de Wit
3
Principles of Production Ecology
4
4 R’s
5
Conclusions
6
Food Security: currently plenty but skewed distribution
Future: increase production
agricultural production in next 40 years, as much as in the past 8,000 years
-6,000 BC
2050 AC
Demand
=
Population
Population
x
Diet
Grain equivalents per year
(billions)
(billion tonnes)
15
15
10 10
5
5
0 1700
1800
1900
2000
2100
diets in 2050 (medium population)
0
4 pillars of the food system
food system
10
Two times…
more
less
healthier
C.T. de Wit (1924-1993)
A physical theory on placement of fertilizers (1953)
On competition (1960)
Photosynthesis of leaf canopies (1965)
Theorie en model (1968)
Ionic balance and growth of plants (1963)
Resource use efficiency in agriculture (1992)
12
A physical theory on placement of fertilizers (1953) Ub
Ur
Xb
Xr
Broad fertilization
Row fertilization
Ur = Ub (Xr/Xb)a
On competition (1960) 150
O 100
O2
O1=k1(2e)Z1{[k1(2e)-1]z1+1}-1 M1
O1
O2= k2(1e)Z2{[k2(1e)-1]Z2+1}-1 M2
50
0
0
Z2
0.5
Z1
1
Ionic balance and growth of plants (1963) external alkaline effect
C+
external acidic effect
A-
C+ plant
soil solution decreasing [H+] + H
C+
A-
C+ A- increasing [H+] C+ H+ OH-
soil complex
H+
Photosynthesis of leaf canopies (1965)
Resource use efficiency in agriculture (1992)
to serve both agriculture and its environment
Costs ($)
minimum external costs per unit product added point of marginalization
costs of external inputs costs of internal resources
0
45°
0
Productivity goal : Yield ($)
marginal return
focus not on marginal returns of variable resources,
but towards the minimum of each production resource that is needed to allow maximum utilization of all other resources
Production-ecological principles & practice Limiting factors •water •nutrients (N,P,K)
yield increasing measures
Reducing factors •weeds •pests •diseases •pollutants yield protecting measures
Post-harvest losses •microbial •insects •rodents •waste
yield gap
Defining factors •CO2 •radiation •temperature •crop genetics
yield level
bio techno logy
postharvesttechnology
• storage • packing
potential production
attainable production
actual production
PRODUCTION SITUATION
available production
18
Production-ecological principles & practice Limiting factors •energy •proteins •minerals •water yield increasing measures
Reducing factors •stress •pests •diseases •pollutants yield protecting measures
Post-harvest losses •microbial •waste
yield gap
Defining factors •temperature •genetics
yield level
bio techno logy
postharvesttechnology
• storage • packing
potential production
attainable production
actual production
PRODUCTION SITUATION
available production
19
Production-ecological principles & practice Limiting factors •O2 •proteins •minerals •vitamins yield increasing measures
Reducing factors •stress •pests •diseases •pollutants yield protecting measures
Post-harvest losses •microbial •waste
yield gap
Defining factors •temperature •genetics
yield level
bio techno logy
postharvesttechnology • storage • packing
potential production
attainable production
actual production
PRODUCTION SITUATION
available production
20
Defining factors techno- •infrastructure logy •land rights innovations
Limiting factors •price ratios •credit use •skills & knowledge
market education extension
potential
attainable
Reducing factors •conflicts •labour use •governance
health policy ethics contracts insurance
institutional gap
performance level
Socio-economic principles & practice
actual
PRODUCTION ENABLING ENVIRONMENT after: R. Ruben 2014
21
Interventions & issues at different levels
socio-economic factors
crop
farm
region
bio-physical factors
continent
globe
Flow diagram: potential production Defining factors bio
Limiting factors
Reducing factors
techno logy
yield increasing measures
potential production
attainable production
yield protecting measures
actual production
Flow diagram: water limited production Defining factors bio
Limiting factors
Reducing factors
techno logy
yield increasing measures
potential production
attainable production
yield protecting measures
actual production
Flow diagram: water&nutrient lim. production Defining factors bio
Limiting factors
Reducing factors
techno logy
yield increasing measures
potential production
attainable production
yield protecting measures
actual production
Flow diagram: actual production Defining factors bio
Limiting factors
Reducing factors
techno logy
yield increasing measures
potential production
attainable production
weed: - water competition
weed: - nutrient competition
yield protecting measures
actual production
Terrestrial production
2%
0.25%
98%
Global Food Potential
146 billion people (de Wit, 1966)
120 billion people (MOIRA, 1977) 44 billion people (WRR, 1992)
Wheat yield EU (water limited)
non-suitable soil
3 5
ton grain/ha
7
(dry matter)
>9
WRR, 1992
Production situation & resource input yield level (kg output ha-1) potential attainable actual
resource use efficiency (kg output kg-1 input)
30
To share and to spare
agriculture
production ecology • •
high productivity efficient resource use
integration
resource ecology • •
multifunctional secure local resources
nature
evolution ecology • •
ecological integrity biodiversity
Discontinuities wheat yields (NL) ton grain ha-1 10
Green revolution
8 6 4 2 0 1875
1900
1925
1950
1975
2000
2025
courtesy: B.Rijk (with data from Wit et al 1988, Knibbe 1993) 32
Expanding green revolutions ton grain ha-1 6
Rice
Maize
start African discontinuities ?
Wheat
4 3
1900
1925
1950
1975
Africa
SE Asia
0 1875
SE Asia
1
Indonesia
2
UK USA
yield (ton/ha)
5
2000
2025
33
Global production, acreage, N-use
tons ton/ha
300
50
200 ha
100 0 1950
Source: FAOstat
100
fertilizer N (billion kg)
Index value
400
1960
1970
1980 1990 year
2000
2010
2020
34
4
R’s in fertilizer use
35
Other R’s in fertilizer use
Reduce emissions& spillage
Resource Use Efficiently
Recover
Recycle
36
Precision in time, place and amount
Farming bots N - application Imaging result with high resultion Agro drone monitoring crop growth
Rowbot, 2014 unibots.com
Weeding EUROP: European Roborics technology Platform
Land cleared for crops [Gha]
N use and global acreage
60 80 100
120 140
100
150 200 250 Global N use in 2050 [Mtonnes]
160
300
after: Tilman et al., 2011
Conclusions
Technical sciences offer opportunities Sufficient food of good quality possible Sustainable systems may cause win-win-win-win situations Ecoliteracy is the basis
de Wit applied on Mars ..? Thanks for your attention
Marsian soil for growing food crops Wamelink (WageningenUR)
28/11/2014
Dr. Joachim Lammel Vice-president Research &
Development YARA Oslo, Norway
Seminar on Smart Fertilization
Profit from placement
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Yara N Fertilization Strategy To strive for better yields and higher N use efficiency Joachim Lammel , Yara International ASA
Target: Highest grower profitability at optimum fertilizer rate Optimum fertilizer rate: best practice manure application as base dressing
Mineral N fertilizer to adjust N demand within growing season Challenge: Optimum N fertilizer rate changes from field to field, year to year and even within fields
Date: 2014-11-25 - Page: 44
maximum profit
optimum fertilizer rate
The optimum fertilizer rate can only be measured in N-response trials Grain yield (t/ha)
10 9 8 7 6 5 4 3 2 1
Economic optimum N rate at 213 kg N /ha
0
50
100
150
200
N Fertilizer Rate (kg N/ha)
Date: 2014-11-25 - Page: 45
250
300
In different fields the same yield was achieved at different N fertilizer rates
110 100
Optimum N rate:
144
180
225 kg N/ha
Yield, dt/ha
90 80 70
60 50 40 30
0
50
100
150
200
250
300
350
N Fertilization, kg N/ha
Yield response curve from trials with winter wheat at 3 fields
Date: 2014-11-25 - Page: 46
The grain yield does not indicate the required fertilizer rate 16 15 14 13 12 11 10 9 8 7 6 5
Yield t ha-1
50
100
150
200
250
300
350
400
Nopt Fertilizer Rate kg N ha-1 Yield data and optimum N fertilizer rates from 248 field trials with cereals 1996-2013
Annual variability in crop growth and N supply from organic soil N influence N fertilizer demand 250
kg N/ha Year D, Field 4
200
Year C, Field 3
N uptake crop
150
Fertilizer demand
100
Year B, Field 2 50
Year A, Field 1 0 Feb
March
Date: 2014-11-25 - Page: 48
April
May
June
July
Aug
N supply from soil & organic
Annual changes of the optimum N fertilizer rate in the same field with the same crop rotation Crop: Winter wheat, pre-crop Potatoes, Longterm trial Rothamsted, UK Optimum N Fertilizer Rate (kg/ha)
Maximum
240 225 210 195
Average = 199 kg N 180
9,4
8,4
9,5
Date: 2014-11-25 - Page: 49
8,8
8,3
8,1
8,9
9,8
Mimimum
20 01
20 00
19 99
19 98
19 97
19 96
19 95
19 94
19 93
19 92
19 91
19 90
165
9,7
9,8
9,0
6,3
Yield t/ha
Yara crop nutrition approach: “from mass-balance to flexible N management” Principle
The nutritional status of the crop determines the fertilizer application rate and timing
Benefits
fertilizer to the crop
Higher nutrient use efficiency because nutrients applied when needed
Prerequisites
efficient fertilizer products balanced nutrition and crop focus Foliar fertilizers, Fertigation diagnostic tools
Date: 2014-11-25 - Page: 50
Fertilizer application in several N rates reduce the risk of N losses • Better synchronisation of N fertilizer application to crop N uptake increases the nitrogen fertilizer use efficiency kg N ha-1 250
One N application several N applications
200
N uptake 150
100 50
0 J
Date: 2014-11-25 - Page: 51
F
M
A
M
J
J
A
S
Influence of a split application of N fertilizer on yield of winter cereals (1 N dressing vs 3 N dressings)
Average of 43 field trials (38 x wheat, 3 x barley, 2 x rye) Same N fertilizer rate in both treatments, average 186 kg N ha-1
Yield (t ha-1) 9,5 9,27 9,0
9,00
8,5
8,0 1 x CAN CAN = Calcium Ammonium Nitrate
Date: 2014-11-25 - Page: 52
3 x CAN
Nitrogen fertilizers that contain nitrate have a better nitrogen use efficiency
NUE (%)
100
No nitrate
25 % nitrate
50% nitrate
100% nitrate 93
90
89 85
85
Urea
UAN
80
70
CAN
CN
Avg. of 15 field trials in UK with winter wheat at a N supply of (160 kg/ha)
Date: 2014-11-25 - Page: 53
Flexible N management with crop analysis help to adjust the N rate during growing season 250
Plant analysis + N application
kg N/ha
200
Plant analysis + N-application
150
100
50
1. Base dressing
0 Feb
March
April
May
June
July
Aug
The optimum N rate is not known at the start of the growing season Date: 2014-11-25 - Page: 54
The N-Tester
A reliable tool to determine crop nitrogen demand
Easy to handle, prompt results
Applicable to a wide range of crops
It enable:
Date: 2014-11-25 - Page: 55
decision about optimum N fertilizer rate
decision about optimum N application time
Approved in several European countries
High variation in soil characteristics can be observed on large fields • large fields can even been seen as a consolidation of several single fields
~ 1 km
diagram of different soil types, field size 36 ha, Golzow farm
Date: 2014-11-25 - Page: 56
Mineral N content in spring can variy a lot within large fields
Mineral N content (0-60 cm soil depth), Golzow farm, WW, 36 ha,
Date: 2014-11-25 - Page: 57
How can the N content of crops as a result of different soil N supply be measure?
• • • •
=> Analysis of many plants => fast identification of spatial variability, => measurement just before or during N fertilization => measuring process shall not slow down N application
Conclusion: optical, remote sensing crop analysis
Date: 2014-11-25 - Page: 58
Yara N-Sensor® - variable rate N fertilization
Date: 2014-11-25 - Page: 59
Yield response to increasing N fertilizer rates show a large difference at 3 spots in a field 12
Yield* (t ha-1)
11,5 11 10,5 10 9,5 9 8,5 0
50
100
150
200
250
N fertilizer rate (2. + 3. N rate), kg ha-1
Area 1
Area 2
Area 3
1st N rate uniform 70 kg N ha-1 Map of relative crop biomass in spring 0m
50 m
100 m
150 m
Date: 2014-11-25 - Page: 60
200 m
*costs for N fertilization considered
N-Sensor detects areas of different organic N supply and adjusts mineral N fertilizer rates Spectral Index
Sensor Map
High
Without organic Cattle slurry Pig slurry 0m
100 m 200 m 300 m 400 m
Low
N [kg N/ha]
N-Application-Map
100 90 80
Winter Barley, N-Sensor-measurement and N-application on the 25th of May Source: AgriCon, Germany
0m
100 m 200 m 300 m 400 m
70 60 50 40
Date: 2014-11-25 - Page: 61
Example how such tools like the N-Sensor can improve yield and nitrogen use efficiency 10% + 6%
5%
grain yield
0%
Farmer practice
-5% -10%
N application rate
-15%
- 14% Yield and N application average of 23 trials with winter wheat in Germany
Date: 2014-11-25 - Page: 62
Summary:
A yield target is not a good indicator for the required N fertilizer rate
The Nitrogen fertilizer rate depend on growth conditions and on N supply from the organic N pool.
Plant analysis is a good tool to determine N fertilizer demand
Several tools exist to conduct in field plant analysis and to adjust the N rate within the growing season
Precision farming technologies help to adjust the N fertilizer rate even within a field to optimize crop yield and nitrogen use efficiency
Date: 2014-11-25 - Page: 63
Click in programme 14.50-15.10 uur Wageningen University Alterra
28/11/2014
Seminar on Smart Fertilization
Technology and information management of precision fertilization
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28/11/2014
Bemesting in de 21e eeuw : Smart Fertilization Adding sustainability to productivity
Seminar on Smart Fertilization
And Information market!
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