This document discusses real-time nitrogen management for rice crops. It begins with an introduction and outlines the need for real-time N management. It then describes the basic approaches and tools used in real-time N management including leaf color charts, SPAD chlorophyll meters, and optical sensors. The document also discusses challenges and strategies for N management. It concludes that tools like leaf color charts and SPAD meters allow farmers to adjust N applications based on the crop's real-time nitrogen needs, improving fertilizer use efficiency.
Definition and introduction of fertilizer use efficiency , Causes for Low and Declining Crop Response to Fertilizers and FUE.Methods to increase fertilizer use efficiency.
Diagnosis and Recommendation Integrated System is a new approach to interpreting leaf or plant analysis and a comprehensive system which identifies all the nutritional factors limiting crop production and increases the chances of obtaining high crop yields by improving fertilizer recommendations.
Conservation agriculture useful for meeting future food demands and also contributing to sustainable agriculture.
Conservation agriculture helps to minimizing the negative environmental effect and equally important to increased income to help the livelihood of those employed in agril. Production.
Introduction of conservation technologies (CT) was an important break through for sustaining productivity, It seeks to conserve, improve and make more efficient use of natural resources through integrated management of soil, water, crops and other biological resources in combination with selected external inputs.
Definition and introduction of fertilizer use efficiency , Causes for Low and Declining Crop Response to Fertilizers and FUE.Methods to increase fertilizer use efficiency.
Diagnosis and Recommendation Integrated System is a new approach to interpreting leaf or plant analysis and a comprehensive system which identifies all the nutritional factors limiting crop production and increases the chances of obtaining high crop yields by improving fertilizer recommendations.
Conservation agriculture useful for meeting future food demands and also contributing to sustainable agriculture.
Conservation agriculture helps to minimizing the negative environmental effect and equally important to increased income to help the livelihood of those employed in agril. Production.
Introduction of conservation technologies (CT) was an important break through for sustaining productivity, It seeks to conserve, improve and make more efficient use of natural resources through integrated management of soil, water, crops and other biological resources in combination with selected external inputs.
The portion of a plant left in the field after harvest of the crop that is (straw, stalks, stems, leaves, roots) not used domestically or sold commercially”. The non – economical plant parts that are left in the field after harvest and remains that are generated from packing sheds or that are discarded during crop processing. Organic recycling has to play a key role in achieving sustainability in agricultural production. Multipurpose uses of crop residue include, but are not limited to, animal feeding, soil mulching, bio-manure, thatching of rural homes and fuel for domestic and industrial use. Thus, crop residues are of tremendous value to the farmers. Crop residue benefit the soil physically, chemically as well as biologically.
The portion of a plant left in the field after harvest of the crop that is (straw, stalks, stems, leaves, roots) not used domestically or sold commercially”. The non – economical plant parts that are left in the field after harvest and remains that are generated from packing sheds or that are discarded during crop processing. Organic recycling has to play a key role in achieving sustainability in agricultural production. Multipurpose uses of crop residue include, but are not limited to, animal feeding, soil mulching, bio-manure, thatching of rural homes and fuel for domestic and industrial use. Thus, crop residues are of tremendous value to the farmers. Crop residue benefit the soil physically, chemically as well as biologically.
Directrice adjointe de l'Institut Jean-Pierre Bourgin (Institut de recherche végétale, INRA de Versailles) Françoise Vedèle fait un focus sur la génétique et les effets de l'azote dans la nutrition des plantes.
Rice Root physiology work at CIAT: Identification of ideal root system to imp...CIAT
Water and Nitrogen are quantitatively the most essential resources for plant growth. Active root systems that can take up water and nutrients more efficiently are essential for enhancing grain yield. However, it is difficult to find the ideal root system to improve water and Nitrogen uptake because the root growth was sensitive and affected by environment such as drought and nutrient deficiency conditions. However, there were several reported that some constitutive root traits and root controlling genes (QTLs) to improve water and nitrogen uptake (Uga et al. 2013; Arai-Sanoh et al. ; Ogawa et al. 2016) .
Here, we examined with root modified breeding lines using both marker assisted selection and transgenic technology under stress conditions. Using 48 chromosome segment substitution lines (CSSLs) between Curinga; commercial upland rice in Brazil and Oryza rufipogon (IRGC105491); a non-sativa species, we found total 15 QTLs including a QTL for nitrogen-deficiency tolerance in grain yield on chromosomes 1. In addition to QTLs identification, we observed that the dimorphic roots system (that has both shallow and deep roots system) from Oryza rufipogon trait correlated to Nitrogen deficiency tolerance in grain yield under field conditions. Using DEEPER ROOTING 1 (DRO1) inserting transgenic lines, we found higher expression of DRO1 increases the root growth angle, whereby roots grow in a more downward direction. Introducing DRO1 into IR64; a shallow-rooting rice cultivar enabled the resulting line to maintained high yield performance under both water and Nitrogen deficient conditions relative to the recipient cultivar. The result showed us the deeper rooting traits is useful to absorb water and Nitrogen from the deeper layer under both water and nitrogen deficiency conditions.
In the future, these identified root system and genes (QTLs) will shed light on root architecture systems in rice breeding to improve agronomic performance under stress conditions.
The presentation is by P Kumar, IARI and P K Joshi, IFPRI from the one day workshop on ‘Pulses for Nutrition in India: Changing Patterns from Farm-to-Fork’ organized on Jan 14, 2014. The workshop is based on a few studies conducted by the International Food Policy Research Institute under the CGIAR’s Research Program on Agriculture for Nutrition and Health. These studies covered the entire domain of pulse sector in India from production to consumption, prices to trade, processing to value addition, and from innovations to the role of private sector in strengthening the entire pulse value chain. These studies were designed to better understand the drivers of changing dynamics of pulses in the value chain from farm-to-fork, and explore opportunities for meeting their availability through increased production, enhanced trade and improved efficiency.
Liquid organic fertilizers: Nutrient rich material is soaked in water for several days or weeks to undergo fermentation. Frequent stirring encourages microbial activity in liquid manures. The resulting liquid can either be used as a foliar fertilizer or applied to the soil.
PRECISION FARMING
It is an approach where inputs are utilized in precise amounts to get increased average yields, compared to traditional cultivation techniques. It is also known as precision Agriculture, A science of improving crop yield and assisting management decisions using high technology sensor and analysis tools. It is an approach to farm management that uses information technology (IT).
Pros and cons of VRT in Indian Agriculture as compared to Developed countries PragyaNaithani
Variable-rate technology (VRT) allows fertilizer,
chemicals, lime, gypsum, irrigation water and other farm
inputs to be applied at different rates across a field,
without manually changing rate settings on equipment
or having to make multiple passes over an area.
Variable-rate application (VRA) can range from the
simple control of flow rate to the more complex
management of rate, chemical mix and application
pattern. VRA can match changes in crop yield potential
with specific input rates resulting in a more efficient
system and minimising potential environmental impacts.
VRT can be used to deal with spatial variability between
paddocks or between management zones/classes. There
are two types of VRT:
1. Map-based control: a map of application rates is
produced for the field prior to the operation.
2. Real-time control: decisions about what rates
to apply in different locations are made using
information gathered during the operation. This
requires sensors to detect necessary information
‘on-the-go’ and is usually designed for a specific
job such as herbicide application.
Conservation agriculture (CA) refers to a set of agricultural practices encompassing minimum mechanical soil disturbance, diversified crop rotation and permanent soil cover with crop residues to mitigate soil erosion and improve soil fertility besides soil functions. The CA aims to conserve, improve and make more efficient use of resources through CA-based technologies. It has many tangible and intangible benefits in terms of reduced cost of production, saving of time, increased yield through timely planting, improved water productivity, adaptation to climate variability, reduced disease and pest incidence through stimulation of biological diversity, reduced environmental footprints and ultimately improvements in soil health. However, weeds are a major biotic interference in CA, posing big defy towards its success unless all the principles are completely followed. Development of post-emergence herbicide and growing herbicide-tolerant crops and also the retention of crop residues as a mulch help in managing weed problems and also improve soil moisture retention. Furthermore, this practice of agriculture improves soil organic carbon content which ultimately leads to an increase in input use efficiency.
The need to move from fallow-based to legume-based systems.Legume-based cropping system that combines suboptimum inorganic fertilizer rate can enhance nutrient-use efficiency and increase productivity
Modern approaches of nitrogen management in rice.pptxPankajLochanPanda
Among plant nutrients, Nitrogen plays a crucial role in growth and yield of the crops. Owing to its importance it is subjected to indiscriminate application which inturn gives rise to several ill effects such as environmental and water pollution. Therefore it is of paramount importance to manage Nitrogen in an efficient way.
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Advantage of SRI over Conventionally Transplanted Rice are discussed on the following Parameters: Yield and Yield Attributing Characters, Water Productivity, Soil Properties, Nitrogen Use Efficiency ,Phosphorus and Potassium use efficiency, Ammonia Loss and Microbiological Properties.
Presented by Yohannes Regassa May 9, 2019, as part of the first CCAFS & GRA CLIFF-GRADS Webinar Series. See the Introduction for more details: 2019 CLIFF-GRADS Webinar Series - Using modeling, life cycle assessment, and trade-off analysis to understand low emissions development options.
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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
4.
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
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
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
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)
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
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)
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.
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
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
39.
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
48.
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
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)