2. Shantappa Duttarganvi
M.Sc. (Agri) Dept of Agronomy, 2009

3.  Introduction
 Need of Real-time N management
 Tools
 Basic approaches in Real-time N management
 Challenges of Real-time N management
 Strategies of N management
 Variable rate N application
 Conclusion

5. Continued improvement in cropping system management
Better prediction of soil N mineralization
Improved timing of N application
Improved manure management
Improved fertilizers

6. .
“Match the agricultural inputs and practices to localized
conditions within field to do the right thing, in the right
place, at right time and in right way”.
(Pierce et al., 1994)
The precision agriculture concept wheel based on GPS

7. .
Real-time N
management
Diagrammatic representation of the relationships between various terms related to Precision Agriculture

9. SSNM provides two equally effective
options
 Real-time N management
 Fixed time N management

10. Site-specific nutrient management (SSNM)
1. Establish a
yield target –
the crop’s
total needs
2. Effectively
use existing
nutrients
Feeding
crop
needs!
3. Fill deficit
between total
needs and
indigenous
supply

11. What is Real-time N
management ?

12. Nitrogen is the nutrient that most often limits crop
production.
(Pathak et al., 2005)
 Crop use nitrogen inefficiently, generally more than 50% of
N applied is not assimilated by plants.
(Dobermann and cassman, 2004)


Leaching, runoff and denitrification are the processes that
result in loss of N from soil-plant system creating the
potential for N deficiency in crop.
(Nowak et al., 1998)

13. 
Worldwide nitrogen use efficiency for cereal grains and
row crops estimated at only 33 %.

Unaccounted 67 % represents a $ 28 billion annual
loss of fertilizer N.
FAO., 2006

14. 
To apply nutrients at optimal rates

To achieve high yield and high efficiency of nutrient
use by the rice crop

Estimating the total fertilizer N required for rice in
a typical season

Formulating the dynamic N management to
distribute fertilizer N to best match the crop need
for nitrogen

15. 
LCC

SPAD

Optical sensor or crop canopy spectral
reflectance

GIS

16.  To develop Site-specific N Management based on crop N
status monitoring
- Canopy reflectance of light
- Chlorophyll content

17. 

IRRI- 1996
The leaf color chart (LCC) is an easy-to-use and inexpensive
diagnostic tool for monitoring the relative greenness of a rice leaf
as an indicator of the plant N status.
Alam et al., 2005

18. How to use the LCC

Select at least 10 disease-free rice plants

Select the topmost fully expanded leaf and compare the leaf
color with the color panels of the LCC and do not detach or
destroy the leaf

Measure the leaf color under the shade of your body

Determine the average LCC reading for the selected leaves

19. Year
7
Mean
Range
Mean
120 kg N ha-1
11.2 - 30.4
20.8
15.0 - 48.2
30.9
10.2 – 42.7
27.4
29.3 – 53.6 42.7
9.8 – 51.5
28.1
21.1 – 51.1 42.1
120 kg N ha-1
7.0 – 25.4
15.4
18.2 – 50.8 29.1
9.2 – 31.2
19.8
18.9 – 58.3 38.9
LCC 4
(20 kg N ha-1
as basal)
25
Range
LCC 4 (no
basal N)
2002
Treatments
7
RE (%)
LCC 4
(20 kg N ha-1
as basal)
2001
AE (kg grain/kg N)
LCC 4 (no
basal N)
2000
No. of
sites
8.5 – 41.8
21.6
18.2 – 56.3 45.4
120 kg N ha-1
3.8 – 22.5
11.3
16.7 – 61.7 39.8
LCC 4
(20 kg N ha-1
as basal)
8.3 - 33. 8
19.2
26.3 – 88.8 58.3
Yadvinder Singh et al., 2004

20. Treatments
Grain yield
(kg ha-1)
2000
Straw yield
(kg ha-1)
2001
Net income
(RS ha-1)
Benefit cost
ratio
2000
2001
2000
2001
2000
2001
Nitrogen management
Control N0
N
3008
2617
4793
4440
4001
3428
1.32
1.28
LCC value 3
4557
3151
6624
4518
10646
4702
1.79
1.35
LCC value 4
5769
4297
7702
6315
16152
11164
2.17
1.81
LCC value 5
5456
3802
7592
5508
14489
7898
2.02
1.56
Recommend
ed N
4342
2917
6608
4466
9123
3394
1.66
1.25
CD (P=0.05)
336
572
879
820
NA
NA
NA
NA
Budhar (2005)

21. Year
Different
methods
LCC(4) based N
management
AE (%)
RE (%)
Grain
Total N
yield(t/ha) applied
(kg N/ha)
2000
86
20.8
0.31
6.63
95
27.4
0.43
FFP
6.53
120
28.1
0.43
-B, LCC
6.89
79
15.4
0.29
+B,LCC
7.20
91
19.8
0.39
FFP
2002
6.59
+B,LCC
2001
-B, LCC
6.84
120
21.6
0.45
-B, LCC
6.76
71
11.3
0.40
+B,LCC
7.01
91
19.2
0.58
FFP
6.69
127
16.4
0.53
Singh

22. 
The LCC is a cheap

Farmers can easily use the LCC to qualitatively assess foliar N status
and adjust N topdressing accordingly

It helps to manage N for large area leading to improved fertilizer N
use efficiency

It reduces the risks associated with fertilizer N application

It saves nearly 26% fertilizer N

It helps to synchronize N supply and crop demand

23. It is a simple, quick and non
destructive in situ tool for
measuring relative content
of chlorophyll in leaf that is
directly proportional to leaf
N content.

24. 1.
2.
3.
4.
5.
SPAD readings are taken at 9-15 day intervals, starting from
14 DAT for transplanted rice and 21DAS for wet direct
seeded rice, Periodic readings continue up to the first (10%)
flowering.
The youngest fully expanded leaf of a plant is used for SPAD
measurement.
Readings are taken on one side of the midrib of the leaf
blade.
A mean of 10-15 readings per field or plot is taken as the
measured SPAD value.
Whenever SPAD values fall below the critical values, N
fertilizer should be applied immediately to avoid yield loss.

25.  Nitrogen fertilizer efficiency
 Rice cultivar
 Position of leaf on plant
 Deficiencies of P, Zn, Mn and Fe

26. N
Management
Grain
yield(Mg/ha)
Total N
uptake(kg/ha)
Recovery
efficiency(%)
Agronomic
efficiency(%)
Well fertilized
plot
5.05
131.4
35.7
9.1
SPAD based
5.05
106.4
61.6
22.7
Fixed timing
5.17
120.1
57.6
18.0
Control
3.0
51.0
-
-
Hussain et al. (2000)

27. Rice grain yield, N uptake, total fertilizer N applied, and
recovery and agronomic efficiency using different need
based fertilizer N management criteria
N management
treatment
Grain
yield
Mg/ha
Total N
uptake
Kg/ha
0
4.4
60
-
-
T2- Recommended
splits
120
6.1
111
42
14.3
T3- N30 at SPAD <35,
N30 basal
60
4.9
86
43
8.2
T4- N30 at SPAD<35, no
basal
30
5.1
75
50
22.4
T5- N30 at SPAD
< 37.5, N30 basal
90
5.8
88
31
15.4
T6- N30 at SPAD<37.5,
no basal
90
6.4
93
37
21.8
T1- Zero N (control)
Total N
applied
Kg/ha
RE (%)
AE (%)
Singh et al. (2002)

28. Treatment
N used (kg ha-1)
Grain yield
(t ha-1)
AEN
FP-N
Philippines
Control
0
3.7
-
-
Farmer’s practice
126
6.0
18.2
41.0
SPAD-35
150
6.7
19.7
44.7
0
5.3
-
-
Farmer’s practice
125
6.4
8.8
51.6
SPAD-35
60
7.1
51.0
118.4
0
2.8
-
-
Farmer’s practice
120
4.0
9.8
33.0
SPAD-35
70
4.0
17.8
57.5
India
Control
Vietnam
Control
Balasubramanian (2000)

29. Treatment
Biometric observations
1000-grain weight
Harvest index
Filled grain (%)
T1 –control
20.40
71.66
0.34
T2 -NPK
recommended
22.13
99.70
0.26
T3 –LCC 2
21.80
90.86
0.37
T4 -LCC 3
21.70
89.30
0.34
T5 -LCC 4
22.80
99.73
0.33
T6 -LCC 5
22.23
98.93
0.29
T7 -CM 35
21.80
88.96
0.27
T8 –CM 37
21.66
89.94
0.30
T9 -CM 40
22.23
96.50
0.29
Balaji and Jawahar (2007)

30. Total N
applied
(kg ha-1)
Grain yield
(t ha-1)
Total N
uptake
(kg ha-1)
AEN
REN
0
5.2
59
-
-
120
9.1
132
32
61
180
9.6
170
25
62
115 (SPAD 35)
9.7
142
39
72
135 (SPAD 37)
9.5
143
32
60
Peng et al.(1996)

31. 
The chlorophyll meter is faster than tissue testing for N.

Samples can be taken often and can be repeated if results
are questionable.

Chlorophyll content can be measured at any time to
determine the crop N status.

The chlorophyll meter allows “fine tuning” of N
management to field condition.

The Chlorophyll Meter would also help people who are
not highly trained to make N recommendations.

32. Variations in reflectance are employed on a variable rate
applicator

34. Crop that needs N is
- lighter in color
- smaller in size and
- reflects light differently
than a crop that has sufficient N

35. Optical sensor
 Optical sensor used rapidly through measurement of
visible and near infrared spectral response from plant
canopies to detect the nitrogen stress.
 It can not work properly when the crop is too young
 It can not work in transplanted rice in early stages

36.  Grid soil sampling
 Residual Soil-nitrate N values
 N availability maps
 N fertilizer recommendation maps

37. Paul and Subramanian (2006)

38. Based on Remote sensing
 Develop Site-specific optional N rate recommendations
based on condition of specific N response curves
 Aerial or satellite photos or digital images

40. Major challenges
 To retain the success of approach
 To build on what has been already achieved using this approach
while reducing the complexity of the technology as it is
disseminated to the farmers
 The nutrient needs of rice are highly variable
 Differ from field to field
 Differ year to year

41. OPPORTUNITIES
 Supply nutrients to optimally match the location specific
needs of the crop for an achievable yield goal
 Provides basis for plant based approach to nutrient
management

42.  Assessing variability
One cannot manage what one does not know
 Spatial variability (high degree is needed)
 Temporal variability (difficult to manage)
 Management of maps
Condition maps
 Prescription maps
 Performance maps


43. Soil supply and plant demand vary in space and time
Higher the spatial dependence, higher the potential for
precision
Field variability should be accurately identified and reliably
interpreted

44.  Economics
Whether the documented agronomic benefits – translated
into value through market mechanism.
 Environment
Whether precision management can improve soil, water, and
ecological sustainability of our agriculture system?.
 Technology transfer
Whether bundle of enabling technologies and agronomic
principles will work on individual farm?.

45.  Prevention strategies
Application of N inputs prior to or early in the N uptake phase
of plant growth to avoid nutrient deficiencies.
 Intervention strategies
N inputs are applied to meet N requirements as determined by
the nutrient status of soil or plants during the rapid N uptake
phase of growing plants.
 Hybrid strategies
Combination of both strategies.

46. Feeding the plant need for
nitrogen
Nitrogen
Plant demand is
related to growth
stage
Split apply N fertilizer
to match plant
demand

47. Variable rate N fertilizer demand is a function of year to year
climate differences (Rainfall & Temp).
Point - to - point soil differences
 Nutrient content of manure
 Soil tests and crop needs
 Water quality concerns

49. 
Uniform N rates

Variable N rates
N use Efficiency,
kg grain/kg N
28-39
39-50
52-62
62-73
Murrell and Murrell (2002)

50. 40 ha field divided into 9 zones
Frequency of zones
9
Whole field year 1, 47 kg grain/kg N
8
8
Variable rate year 3, 53 kg grain/kg N
7
13% increase in
fertilizer N efficiency
6
5
4
4
3
2
2
2
1
2
1
1
0
0
28-39
39-50
50-62
N use efficiency, kg grain/kg
applied N
62-73
Murrell and Murrell (2002)

51. General guidelines for determining the early
application of N before 14 DAT or 21 DAS of rice
 Typically apply 20 to 30 kg N ha−1 in seasons with yield response
between 1 and 3 t ha-1 Apply about 25 to 30% of the total N in
seasons with yield response >3 t ha−1 .
 Increase the N application up to 30 to 50% of the total N when old
seedlings (>24 days old) and short-duration varieties are used.
 Reduce or eliminate early N application when high-quality organic
materials and composts are applied.
 Eliminate early application when yield response is ≤1 t ha−1 .
 Do not use the LCC with the early N application.
www.irri.org/irrc/ssnm

52. Principles of N management
When is fertilizer N needed?
Match early application of N with low
initial demand of the crop for N
Apply only a moderate amount of
fertilizer N to young rice
Ensure sufficient supply of N to the
crop at active tillering and panicle
initiation
Use the LCC to assess leaf N status
and adjust applications to match crop
needs for N
A standardized leaf color chart
(LCC)

53. Example of a real-time N
recommendation for rice
Active
tillering
Transplanting
-20
-10
0
10
20
30
Panicle
initiation (PI)
40
50
Harvest
Heading
60
70
80
90
100 DAT
Take LCC readings
every 7 days
Early
Within 14 DAT
30 kg N/ha
0 to 20 kg N/ha *
21–50 DAT
If LCC < 3.5 **
45 kg N/ha
High-yielding season
If LCC < 3.5 **
23 kg N/ha
Low-yielding season
Yield target = 7 t/ha
Yield target = 5 t/ha
* Early N is not essential but up to 20 kg N/ha can be applied when NPK fertilizers are used to supply P and K.
** Leaf color is nearer to LCC reading 3 than 4 with standardized IRRI LCC
23 kg N/ha = 1 bag urea/ha; 45 kg N/ha = 2 bags urea/ha.
www.irri.org/irrc/ssnm

54. Dobermann et al. (1998)

55. Effect of Nitrogen regimes on grain yield, straw yield
and dry matter production of rice
Treatment
N consumed
(kg/ha)
T1 - Control
Output ( t/ha)
Grain yield Straw yield Dry matter yield
3.77
7.34
10.45
T2 -NPK
recommended
125
4.68
14.92
17.47
T3 - LCC 2
80
5.18
9.02
13.73
T4 -LCC 3
80
5.16
10.04
14.70
T5 -LCC 4
110
6.36
14.33
19.65
T6 -LCC 5
130
5.78
16.36
21.26
T7 -CM 35
80
5.26
13.41
17.77
T8 -CM 37
80
5.48
12.07
17.82
T9 -CM 40
130
5.64
14.37
19.34
Balaji and Jawahar (2007)

56. Nitrogen use efficiency as influenced by
different LCC and SPAD values
Treatment
Nitrogen use efficiency
Agronomic
(%)
Physiological
(%)
Economic (%)
-
-
0.44
T2 -NPK
recommended
7.32
17.49
0.43
T3 -LCC 2
17.69
23.55
0.49
T4 -LCC 3
17.37
22.82
0.48
T5 -LCC 4
23.54
31.75
0.54
T6 -LCC 5
15.50
25.81
0.48
T7 -SPAD 35
18.69
24.58
0.50
T8 -SPAD 37
21.44
27.83
0.52
T9 -SPAD 40
14.42
24.57
0.47
T1 -control
Balaji and Jawahar (2007)

57. Where and when Real-time N management will pay off in
terms of either profitability or environmental benefits?
Where N inputs are high
(Fiez et al., 1994)
Where residual N is temporally stable and /or high residual N is
predictable
(Cattanach et al., 1996)
Where crop quality is affected by excess N in soil
(Lenz et al., 1996)
Where crop yield spatial variability is high and predictable
(Long et al., 1996)

58. Contd….
 Where net mineralization is high and consistently
related to soil and landscape properties
(Pan et al., 1997)
 Where N application is not restricted in time
(Evan et al., 1996)
 Where leaching potential is very high during the crop N
uptake period of the plant growth
(Malzer et al., 1995)

59. Tool / Tactics
Benefit :
cost
Limitations
Site specific N management
High
Has to developed for every site
Chlorophyll meter
High
Initial high cost
Leaf color chart
Very high
Minimum limitations
Plant analysis
High
Facilities need to be developed
Controlled- released fertilizer
Low
Nitrification inhibitor
Low
Low profitability and lack of interest
by industry
Fertilizer placement
High
Lack of equipment, labour intensive
Foliar N application
High
Lack of equipment, risk involved
Breeding strategy
Very high
Varieties yet to be developed
N – fixation in non legumes
High
Technology yet to be developed for
field scale
Models and decision support
system
Medium
Tools are not available
Remote sensing tools
Low
Geographic information
system
Low
Resource-conserving
technology
High
Integrated crop management
high
Technology need to be fine-tuned
Technology needs to be evaluated for
long- term impacts
Ladha et al. (2005)