Geoinformatics and Precision Agriculture.pdf

Overviews-
1. Precision agriculture; concepts and techniques
2. Geoinformatics- definition, concepts, tool and techniques and their used in agriculture
3. Crop discrimination and yield monitoring, soil mapping, fertilizer recommendation using geospatial
technologies
4. Spatial data and their management in GIS
5. Remote sensing concepts and application in agriculture
6. Image processing and interpretation; GPS, components and its function
7. Introduction to crop simulation models and their uses for optimization of agriculture inputs
8. STCR approach for precision agriculture
9. Nanotechnology, definition, concepts and techniques, brief introduction about nanoscale effects, nano
particles, nano fertilizers, nano-sensors
10. Use of nano technology in seed, water, fertilizer and plant protection for scaling up farm productivity

Lecture- 1
Precision agriculture- concepts,
techniques, their issues and concerns for
Indian agriculture

Objectives of precision farming-
• Precision agriculture refers to the precise application of
agricultural inputs with respect to soil, weather and crop
need in order to improve productivity, quality, and
profitability in agriculture.
• It is a modern agriculture practice involving the use of
technology in agriculture like remote sensing, GPS and
Geographical Information System (GIS) for improving
productivity and profitability.
• It enables farmers to use crop inputs more efficiently
including pesticides, fertilizers, tillage and irrigation water.
• More effective utilization of inputs will bring in more crop
yield and quality without polluting the environment and will
result in sustainable agriculture and sustainable
development.
• Hence precision agriculture is about doing the right thing, in
the right place, in the right way, at the right time.

Need of precision farming –
1. To increase production efficiency
2. To improve product quality
3. Use of chemicals more efficiently
4. Energy conservation
5. To increase input use efficiency
6. Soil and ground water protection
7. Improve soil structure
8. Prevent land degradation
9. Prevent resource depletion
10. Prevent environmental degradation
11. Improving livelihood

Components of precision farming
1. Information or data base-
➢ Soil: Soil texture, structure, physical condition, soil moisture, soil nutrients, etc.
➢ Crop: Plant Population; Crop Tissue Nutrient Status, Crop Stress, Weed patches (weed type and intensity);
Insect or fungal infestation (species and intensity), Crop Yield; Harvest Swath Width etc.
➢ Climate: Temperature, humidity, rainfall, solar radiation, wind velocity, etc. In-fields variability, spatially or
temporally, in soil-related properties, crop characteristics, weed and insect-pest population and harvest data are
important databases that need to be developed to realize the potential of precision farming.
2. Technology: Technologies include a vast array of tools of hardware, software and equipments.
1) Global Positioning System (GPS) receivers
2) Differential Global Positioning System (DGPS)
3) Geographical information systems (GIS)
4) Remote sensing
5) Variable Rate Applicator: The variable rate applicator has three components: Control computer, Locator
and Actuator. The application map is loaded into a computer mounted on a variable-rate applicator. The
computer uses the application map and a GPS receiver to direct a product-delivery controller that changes
the amount and kind of product, according to the application map.
6) Combine harvesters with yield monitors
3. Management: 1) Information management 2) Decision support system (DSS) 3) Identifying a precision
agriculture service provider

Global Positioning System Differential Global Positioning System
Combine harvesters with yield monitor

Steps in precision farming -
1.Identification and assessment of variability
Grid soil sampling Crop scouting VRT
• Use of precision technologies for assessing variability
2. Management of variability
a) Variable rate application- Variable rate application (VRA) in precision agriculture is an area of technology that
focuses on the automated application of materials to a given landscape. The way in which the materials are applied is
based on data that is collected by sensors, maps, and GPS. These materials include things like fertilizers, chemicals,
and seeds, and they all help optimize one’s crop production. The technologies used for VRT are drones and satellites,
to artificial intelligence (AI) and hyperspectral imaging.
1. Savings on fertilizers and chemicals.
2. Potential yield increase due to more efficient fertilization and spraying based on actual crop needs and variability
of fields.
3. Environmental protection from excess fertilization or spraying of chemicals.

b) Yield monitoring and mapping-
• To enable decision makers and planners to predict the amount of crop import and export yield estimation well
before harvest is imperative
• But conventional methods are expensive, time consuming and are prone to large errors due to incomplete and
inaccurate ground observations
• Data captured through remote sensing has the prospective, capacity and the potential to exhibit spatial information
at global scale
Components-
Aerial photography- This is used for optimized use of resources for agriculture and crop inventory. Black and white
photography has been used for crop identification, primarily based on ground appearance and the equivalent aerial
photographic form of selected fields at nine intervals during growing season
Multispectral Scanners-It uses pattern recognition techniques using a computer format to differentiate specific crop
from other agricultural crops. It also helps in species identification
Radar- It helps in monitoring the yield concentrating on seasonal change between the crops and numerous variables
which are considered in making simplest determinations
Satellite Data- Remote sensing has proved effective in predicting crop yield and provide representative and spatially
exhaustive information on the development of the model. Yield estimates through remote sensing is indirect in
nature. Recently, researchers are using course resolution data as a sampling tool to estimate the yield through
remote sensing for increased precision

Soil Mapping- Soil maps are required on different scales varying from 1:1 million to 1:4,000 to meet the requirements of planning
at various levels. As the scale of a soil map has direct correlation with the information content and field investigations that are
carried out, small scale soil maps of 1:1 million are needed for macro-level planning at national level. Applications of soil mapping
through remote sensing-
1. Remote sensing for soil and
land degradation mapping
2. Soil mapping methods
3. Visual image interpretation
4. Computer aided approach
Soil mapping Yield monitoring
c) Quantifying on farm variability-
d) Flexibility-
• Long leave
• Right to reduce
hours
• Flexible working
hours
• Shift work
• Over time
• No risk

Scope of precision farming in India
1. The concept of precision farming is not new for India. Farmers try their best to do the things for getting maximum
possible yield with information and technologies available to them but unless & until total information about his field
and advanced technologies are available, they cannot do precision farming in perfect sense.
2. In India, major problem is the small field size. More than 58 percent of operational holdings in the country have
size less than 1ha.
3. Only in the states of Punjab, Rajasthan, Haryana and Gujarat more than 20 per cent of agricultural lands have
operational holding size of more than four hectare.
4. When contiguous fields with the same crop are considered, it is possible to obtain fields of over 15 ha extent in
which similar crop management are followed. Such fields can be considered for the purpose of initiating the
implementation of precision farming. Similar implementation can also be carried out on the state farms.
5. There is a scope of implementing precision agriculture for crops like, rice and wheat especially in the states of
Punjab and Haryana. Commercial as well as horticultural crops also show a wider scope for precision agriculture in
the cooperative farms. Nearly two-third arable land in India is rain-fed. The crop yields are very low (≈1t ha-1) and
very good potential exists for increasing productivity of rain-fed Cropping systems.

Advantages of precision farming
✓ Overall yield increase
✓ Efficiency improvement
✓ Reduced production costs
✓ Better decision making in Agricultural management
✓ Reduced environmental impact
✓ Accumulation of farmer’s knowledge for better management with time
✓ It will minimize the risk to the environment particularly with respect to the nitrate leaching and groundwater
contamination by means of the optimization of Argo-chemical products.
✓ It will reduce excessive chemical usage in crop production.
✓ Water resources will be utilized efficiently under the precision farming.
✓ Non-uniform fields can be sub-divided into smaller plots based on their unique requirements
Drawbacks/Disadvantages of Precision Farming
o High costs
o Lack of technical expertise knowledge and technology
o Not applicable or difficult/costly for small land holdings
o Heterogeneity of cropping systems and market imperfections
o It is an extremely difficult task particularly the collection and analysis of data.
o Precision agriculture techniques are still under development and requires expert advice before actual
implementation

Lecture- 2
Geo-informatics- definition, concepts,
tool, techniques and their used in
precision agriculture

Geo-informatic definitions
✓ Geoinformatics is defined as the combination of technology and science dealing by means of the spatial
information, its acquisition, its qualification and classification, its processing, storage and dissemination.
✓ It is an integral tool to collect process and generate information from spatial and non spatial data.
✓ Geoinformatics is an appropriate blending of modules like remote sensing, global positioning system,
geographical information system and relational database management system
Tools and techniques in Geoinformatics
1. Global positioning system
1. The Global Positioning System (GPS) is a satellite-based navigation system that can be used to locate positions
anywhere on the earth.
2. GPS provides continuous (24 hours/day), real-time, 3-dimensional positioning, navigation and timing worldwide
in any weather condition.
3. As a tool of precision agriculture, Global Positioning System satellites broadcast signals that allow GPS receivers
to calculate their position. This information is provided in real time, meaning that continuous position information
is provided while in motion. Having precise location information at any time allows crop, soil and water
measurements to be mapped
4. GPS makes use of a series of satellites that identify the location of farm equipment within a 3 meter of an actual
site in the field.
5. The most common use of GPS in agriculture is for yield mapping and variable rate fertilizer/pesticide applicator.

6. GPS are important to find out the exact location in the field to assess the spatial variability and site-specific application of the
inputs
7. The positional (horizontal) accuracy of the GPS can be of the order of 20 m.
8. In order to achieve the required accuracies, especially needed for precision agriculture, the GPS has to be operated in a
differentially corrected positioning mode, i.e. DGPS
2. Remote Sensing technique
➢ Remote sensing (RS) is the science of making inferences about material objects from measurements, made at distance, without
coming into physical contact with the objects under study
➢ A remote sensing system consists of a sensor to collect the radiation and a platform – an aircraft, balloon, rocket, satellite or
even a ground-based sensor-supporting stand - on which a sensor can be mounted
➢ Currently a number of aircraft and spacecraft imaging systems are operating using remote sensing sensors. Some of the current
image systems from spacecraft platform include Indian Remote Sensing Satellites (IRS), French National Earth Observation
Satellite (SPOT), IKONOS etc.
➢ Detection, identification, measurement and monitoring of agricultural phenomena are predicted on assumption that agricultural
landscape features have consistently identifiable signatures on the type of remote sensing data.
➢ These identifiable signatures are reflection of crop type, state of maturity, crop density, crop geometry, crop vigour, crop
moisture etc.
➢ The detection of features to a large extent depends on the type of sensor used and the portion of the electromagnetic spectrum
used in sensing.

3. Geographical Information System
1. GIS is a computerized data storage and retrieval system,
which can be used to manage and analyse spatial data
relating crop productivity and agronomic factors
2. GIS can display analysed information in maps that allow
better understanding of interactions among yield, fertility,
pests, weeds and other factors, and decision-making based
on such spatial relationships
3. Many farm information systems (FIS) are available, which
use simple programmes to create a farm level database. One
example of such FIS is LORIS. LORIS (Local Resources
Information System) consists of several modules, which
enable the data import; generation of raster files by different
gridding methods; the storage of raster information in a
database; the generation of digital Agro-resource maps; the
creation of operational maps etc.
4. A comprehensive farm GIS contains base maps such as
topography, soil type, N, P, K and other nutrient levels, soil
moisture, pH, etc. Data on crop rotations, tillage, nutrient
and pesticide applications, yields, etc. can also be stored.
5. GIS is useful to create fertility, weed and pest intensity
maps, which can then be used for making maps that show
recommended application rates of nutrients or pesticides

Application of Geoinformatics in precision Agriculture
1) Precision farming employs a system engineering approach to crop production where inputs are made on an "as
needed basis," and was made possible by recent innovation in information and technology such as
microcomputers, geographic information systems, remote sensing, positioning technologies (Global
Positioning System), and automatic control of farm machinery.
2) It is a holistic approach to manage spatial and temporal variability in agricultural lands at micro level based on
integrated soil, plant, information, and engineering management technologies as well as economics.
3) It is well known that soil resources and weather vary across space and over time. Given this inherent
variability, management decisions should be specific to time and place rather than rigidly scheduled and uniform.
4) Precision agriculture provides tools for tailoring production inputs to specific plots within a field, thus
potentially reducing input costs, increasing yields, and reducing environmental impacts by better matching inputs
applied to crop needs.
5) Modern technologies used in precision agriculture cover three aspects of production:
(a) data collection or information input,
(b) analysis or processing of the precision information, and
(c) recommendations or application of the information.

6) Data collection for soil is done basically to understand inherent variability factors controlling crop growth
and yield.
7) Conventional approach for soil variability mapping is commonly done through manual grid sampling and
interpolation through geostatistical techniques for whole agricultural landscape.
8) The inherent variability can be correlated with the variability map of yield to develop cause and effect
relationships. This may help to develop relatively homogenous management zones. Such samplings are costly
and time consuming.
9) The scope of remote sensing data has been widely studied and looking more closely at how the spectral
response of soil can be linked to various soil properties and characteristics.
10) As an alternate to conventional laboratory soil analysis, hyperspectral remote sensing which is non-
destructive, cost effective and capable of spatial prediction has been investigated for surface soil
characterization.
11) Hyperspectral image data or imaging spectrometry technique, which many narrow and contiguous bands,
provides near-laboratory-quality reflectance information, has the capability to obtain non-visible information
over a spatial view in large scales.

Lecture- 3
Crop discrimination and spectral features for crop
classification, yield monitoring and soil mapping, site specific
nutrient management (SSNM)

INTRODUCTION
• Currently computers are being used automation and to expand decision support system (DSS)
for the agricultural research. Recently, geographic information systems (GIS) and remote
sensing technology has Come up with a capable role in agricultural research predominantly in
crop. yield prediction in addition to crop suitability studies and site specific resource allocation.
• Remote Sensing is an efficient technology and worthy source of earth surface information. as it
can capture images of reasonably large area on the earth. With the use of these imaging and
non-imaging data, we can easily characterise the different species
• Different crops show distinct phonological characteristics and timings according to their
nature of germination, tillering, flowering, boll formation (cotton), ripening etc. Even for the
same crop and growing season, the duration and magnitude of each phonological stage can
differ between the varieties, which introduce data variability for crop type discrimination with
imaging systems.
• Agricultural crops arc significantly better characterised, classified, modelled and mapped using
hyperspectral data.Crop Discrimination (differentiation/classification) Crop discrimination is a
necessary step for most agricultural monitoring systems in which differentiate/classification of
crops as per season, phonological stages, pigmentation, spatial arrangement/architecture as well
as spectral features.

Feature Extraction
Feature extraction refers to the process of transforming raw data
into numerical features that can be processed while preserving
the information in the original data set. It yields better results
than applying machine learning directly to the raw data.
Feature extraction is the process of defining image characteristics
or features which effectively provides meaningful information
for image interpretation or classification. The ultimate goals of
feature extraction are:
a. Effectiveness and efficiency in classification.
b. Avoiding redundancy of data.
c. Identifying useful spatial as well as spectral features.
d. Maximizing the pattern discrimination.
e. For crop type discrimination, spatial features are useful.
Crops are planted in rows. either multiple or single rows, as
per the crop types for convenience and to maximize yields
f. Different spatial arrangement of the crops gives better spatial
information, but it requires high spatial resolution images.
g. In spatial image classification, spatial image elements are
combined with spectral properties in reaching a classification
decision. Most commonly’ used elements are texture,
contexture and geometry (shape).

Role of texture in classification
- As it is possible to distinguish between regular textures manifested by man-made objects hence, this texture
characteristic is used to discriminate between divergent objects
- Grey value relationship is obtained from segmentation both by conventional texture analysis and grey level co-
occurence matrix (GLCM)
- GLCM method analyses within GLCM space not from original grey values
Grey Level Co-occurence Matrix (GLCM)
- The GLCM can be viewed as two dimensional histogram of the frequency with which pairs of grey level pixels
occur in a given spatial relationship, defined by specific inter-pixel distance and a given pixel orientation
- Hence this segmentation of urban objects , texture analysis are usually performed by GLCM
Local Binary Pattern (LBP)
It is a simple yet very efficient texture operator which labels the pixels of an image by thresholding the
neighbourhood of each pixel and considers the result as a binary number.
Due to its discriminative power and computational plainness, LBP texture operator become a popular approach
Spatial feature extraction for crop type discrimination works well if we have high spatial resolution satellite
imagery. Rather than this spatial information is also useful in spectral based classification for visual interpretation in
supervised learning
Spectral Features for Crop Classification
Band selection
Narrow band vegetation indices

Band Selection
Band selection is one of the important steps in hyperspectral remote sensing.
There are to conceptually different approaches of band selection like
Unsupervised and supervised
Due to a availability of hundreds of spectral bands, there may be same values in several bands which increase the
data redundancy,
To avoid the data redundancy and to get distinct features from available hundreds of bands, we have to choose the
specific band by studying the reflectance behavior of crops.
Narrow Band Vegetation Indices
Spectral indices assume that the combined interaction between a small numbers of wavelengths is adequate to
describe the biochemical or bio-physical interaction between light and matter.
The simplest form of index is a simple ratio (SR). a potentially greater contribution of hyperspectral systems is
their ability to create new indices that integrate not sampled by any broadband system and to quantify absorptions that
are Specific to important biochemical and biophysical quantities of vegetation.
Vegetation properties measured with hyperspectral vegetation indices (HVIs) can be divided into three main
categories. (1) Structure, (2) biochemistry and (3) plant physiology/stress.
Importance of Hyperspectral Remote Sensing
Spectrum allows us to study very specific characteristics of agricultural crops
Non-imaging sensors gave spectral signatures with approximate 1-10 nm sampling rate which is very effective for
distinct feature identification
Narrow band vegetation indices play an important role for mapping plant biophysical and biochemical properties of
agricultural crops
It gives detailed information about crops but it is necessary to select appropriate bands

Introduction on Yield Monitoring
• To enable decision makers and planners to predict the amount of crop import and export yield estimation well
before harvest is imperative
• But conventional methods are expensive, time consuming and are prone to large errors due to incomplete and
inaccurate ground observations
• Data captured through remote sensing has the prospective, capacity and the potential to exhibit spatial information
at global scale
• Different approaches include=>
• Aerial photography
• Multispectral scanners
• Radar
• Satellite Data
Aerial Photography
❖ This is used for optimized use of
resources for agriculture and crop
inventory
❖ Black and white photography has been
used for crop identification, primarily
based on ground appearance and the
equivalent aerial photographic form of
selected fields at nine intervals during
growing season

Multispectral Scanners- It uses pattern recognition techniques using a computer format to differentiate specific crop
from other agricultural crops. It also helps in species identification
Radar- It helps in monitoring the yield concentrating on seasonal change between the crops and numerous variables
which are considered in making simplest determinations
Satellite Data- Predicting crop yields with conventional models proved to be unsuccessful in
present day World
➢ Remote sensing has proved effective in predicting crop yield and provide representative and spatially exhaustive
information on the development of the model
➢ India’s marked the beginning of remote sensing with the launch of IRS satellite in 1988.
➢ Yield estimates through remote sensing is indirect in nature
➢ Recently, researchers are using course resolution data as a sampling tool to estimate the yield through remote
sensing for increased precision

SOIL MAPPING
✓ Soil maps are required on different scales varying from 1:1 million to 1:4,000 to meet the requirements of
planning at various levels.
✓ As the scale of a soil map has direct correlation with the information content and field investigations that are
carried out, small scale soil maps of 1:1 million are needed for macro-level planning at national level.
✓ Soil maps at 1:250,000 scale provide information for planning at regional or state level with generalised
interpretation of soil information for determining the suitability and limitations for several agricultural uses and
requires less intensity of soil observations and time.
✓ Soil maps at 1:50,000 scale where association of soil series are depicted, serve the purpose for planning resources
conservation and optimum land use at district level and require moderate intensity of observations in the field.
✓ Large scale soil maps at 1:8,000 or 1:4,000 scale are specific purpose maps which can be generated through high
intensity of field observations based on maps at 1:50,000 scale of large scale aerial photographs or very high
resolution satellite data.
✓ Similarly, information on degraded lands like salt affected soils, eroded soils, waterlogged areas, jhum lands
(shifting cultivation) etc is required at different scales for planning strategies for reclamation and conservation of
degraded lands.

Applications of soil mapping through RS-
-Remote Sensing for Soil and Land Degradation
Mapping
-Conventional surveys are subjective, time consuming
and laborious
-Remote sensing speeded up the conventional soil
survey programmes
-Aerial photography and satellite data reduced the field
work with respect to locating soil types and boundaries
owing to synoptic view
-Soil Mapping methods
-Topographic variations as the base for depicting soil
variability
-Multispectral satellite data is being used for mapping
soil up to family association level (1:50000)
-Visual Image Interpretation
-It is based on shape, size, tone, shadow, texture, pattern,
site and association
-This is relatively simple and inexpensive
-Several workers have concluded that remote sensing
technology provides better efficiency at 1:50000 and
detailed at 1:10000 scale of mapping

Computer Aided Approach
Numerical analysis of remote sensing data utilising the Computers has been developed because of requirement to
analyse faster and extract information from the large quantities of data
Computer aided techniques utilize the spectral variations for classification
Pattern recognition in remote sensing assists in identification of homogeneous areas, which can be used as a base
for carrying out detailed field investigations and generating models between remote sensing and field parameters
Major problem with conventional soil survey and soil cartography is accurate delineation of boundary. Field
observations based on conventional soil survey are tedious and time consuming.
Remote sensing data in conjunction with ancillary data provide the best alternative, with a better delineation of soil
mapping units. Introduction SSNM
Site specific nutrient management (SSNM) approach, relatively new approach of
nutrient recommendations, is mainly based on the indigenous nutrient supply from the soil and nutrient demand of the
crop for achieving targeted yield. The SSNM recommendations could be evolved on the basis of solely plant analysis
or soil cum plant analysis
The SSNM helps in improving NUE as it provides an approach for feeding crops like rice, maize, wheat, etc. with
nutrients as and when needed.
The major benefit for farmers from improved nutrient management strategy is an increase in the profitability.

The SSNM eliminates the wastage of fertilizers by preventing excessive rates of fertilization and
by avoiding fertilizer application when the crop does not require nutrient inputs.
Importance of SSNM
1. Optimal use of existing indigenous nutrient sources such as crop residues and measures.
2. Application of N, P and K fertilizers is adjusted to the location and season-specific needs of
the crop.
3. Use of the leaf colour chart ensures that nitrogen is applied at the right time and in the amount
needed by the crop which prevents wastage of fertilizer.
4. Use of nitrogen omission plots to determine the P & K fertilizers required to meet the crop
needs. This ensures that P and K are applied in the ratio required by the rice crop.
5. Local randomization for application of Zn, S and micronutrients are followed.
6. Selection of most economic combination of available fertilizer sources.
7. Integration with other integrated crop management (ICM) practices such as the use of quality
seeds, optimum plant density, integrated pest management and good water management.
8. Local randomization for application of Zn, S and micronutrients are followed.
9. Selection of most economic combination of available fertilizer sources.
10. Integration with other integrated crop management (ICM) practices such as the use of quality
seeds, optimum plant density, integrated pest management and good water management.

SSNM approaches- The relatively new approach of nutrient recommendations is mainly based on
the indigenous nutrient supply from the soil and nutrient demand of the crop for achieving
targeted yield. The SSNM recommendations could be evolved on the basis of solely plant analysis
or soil cum plant analysis

Lecture- 4
Spatial data and their management in GIS

Introduction
❖ Geospatial data has significantly different structure and function. It includes structure data about objects in the
spatial universe- their identity, location, shape and orientation and other things we may know about them
❖ In geographical data all the objects are described in terms of points, lines, tables and polygons constituting the
tabular portion of geospatial data
❖ GIS technology accommodates some kinds of unstructured data (usually raster imagery) that can be tagged and
geocoded and integrated by GIS software the other kinds of map data
❖ Raw GIS data is generally meaning less for human eye until converted into a map. This is what GIS software does.
What is a GIS
a) A geographic information system (GIS) is a computer-based tool for mapping and analyzing things that exist and
events that happen on earth.
b) GIS technology integrates common database operations such as query and statistical analysis with the unique
visualization and geographic analysis benefits offered by maps
c) These abilities distinguish GIS from other information systems and make it valuable to a wide range of public
and private enterprises for explaining events, predicting outcomes and planning strategies.
d) Mapmaking and geographic analysis are not new, but a GIS performs these tasks better and faster than do the old
manual methods.
Importance of GIS
Perform Geographic Queries and Analysis
Improve Organizational Integration
Make Better Decisions
Making Maps much more

How GIS works-A GIS stores information about the world as a collection of thematic layers that can be linked
together by geography. This simple but extremely powerful and versatile concept has proven valuable for solving
many real-world problems from tracking delivery vehicles, to recording details of planning applications, to modelling
global atmospheric circulation
Geographic References - Geographic information contains either an explicit geographic reference, such as a latitude
and longitude or national grid coordinate or an implicit reference such as an address, postal code, census tract name,
forest stand identifier or road name.
• An automated process called geo-coding is used to create explicit geographic references (multiple locations) from
implicit references (descriptions such as addresses).
• These geographic references allow location of features, such as a business or forest stand and events, such as an
earthquake, on the earth’s surface for analysis.
Vector and Raster Models
o Geographic information systems work with two fundamentally different types of geographic models - the “vector”
model and the “raster” model. In the vector model, information about points, lines and polygons is encoded and
stored as a collection of x, y coordinates. The location of a point feature, such as a bore-hole, can be described by
a single collection of point x, y coordinate. Linear features, such as roads and rivers, can be stored as a be stored
Coordinates. Polygonal features, such as sales territories and river catchment as a closed loop of coordinates.
o The vector model is extremely useful for describing discrete features, but less useful for describing Continuously
varying features such as soil type or accessibility costs for hospitals.
o The raster model has evolved to model such continuous features. A raster image comprises a collection of grid
cells rather like a scanned map or picture. Both the vector and raster for storing geographic data have unique
advantages and disadvantages

Geospatial data contains coordinate information (e.g.,
latitude and longitude), which allows features to be
drawn on a map. Geospatial data can be used to
create maps and analyze data in GIS. There are two
primary geospatial data models: vector and raster.
Raster Data
•Typically used to represent continuous data (e.g.,
temperature, elevation). Rasters can also be used to
represent discrete data (e.g., land cover type).
•Uses equal-sized pixels (cells) arranged in a grid to
represent geographic data.
•Examples of raster data include aerial photographs,
satellite imagery, digital elevation models (DEMs),
etc.
Vector Data
•Works best when used to represent geographic
features with discrete boundaries (e.g., streets, land
parcels, administrative boundaries, etc.)
•Coordinate-based model where geographic locations
are represented as points, lines, or polygon features.
•Each geographic feature has associated
tabular/spreadsheet data (i.e., attribute information).

Attribute (Tabular) Data
Many geospatial data sets include an attribute table
that provides additional information about the data set.
Attribute (tabular) data can be used to perform queries
and analyses, join data sets, visualize specific variables
on a map, etc. Additional variables and calculations
can be added to attribute tables using editing sessions,
field calculator, etc. Attribute (tabular) data can also be
uploaded to GIS software as standalone table and/or
converted into spatial data using location information
within the attribute table (e.g., geographic coordinates,
street addresses, etc.)
Some common file formats that work with GIS
applications include:
shapefiles (.shp),file geodatabases (.gdb), Keyhole
Markup Language (.kml or .kmz),GeoTIFF
(.tiff),comma-separated values(.csv), GeoJSON
(.json), GPS Exchange Format (.gpx),LiDAR point
cloud data (.las)
Convert File Formats- Many GIS software programs
(e.g., ArcGIS, QGIS) include data conversion tools if
you need to convert data into a different file format.
Some important GIS, GPS and RS software
S.N GIS GPS RS
1 ArcGIS Traccar ERDAS IMAGINE
2 QGIS OpenGTS ENVI
3 GRASS GIS Trackit by Flespi PCI Geomatica
4 Esri Track My Ride RemoteView
5 SAGA GIS Navit TNTmips
6 gvSIG GPS Trace ILWIS
7 MapWindow GIS Trackme eCognition
8 GeoServer ClearPath GPS Geomatica

Components of GIS –
A working GIS integrates five key components; Hardware, software, data, people and methods.
Hardware- It is the computer on which a GIS operates. Today, GIS software runs a wide range of hardware types,
from centralized computer servers to desktop computers used in stand alone or networked configurations.
Software- The GIS software provides the functions and tools needed to store, analyze and display geographic
information. Key software components are:
➢ Tools for the input and manipulation of geographic information.
➢ A database management system (DBMS).
➢ Tools that support geographic query, analysis and visualization.
➢ A graphical user interface (GUI) for easy access to tools.
Data- Possibly, the most important component of a GIS is the data. Geographic data and related tabular data cm be
collected in-house or purchased from a commercial data provider. A GIS will integrate spatial data with other data
resources and can even use a DBMS, used by most organizations to organize and maintain their data, to manage
spatial data.
People- The GIS technology is of limited value without the people who manage the system and develop plans for
applying it to real-world problems The GIS users range from technical specialists who design and maintain the
System to those who use it to help them perform the everyday work.
Methods- A successful GIS operates according to a well-designed plan and business rules, are the models and
operating practices Unique to each organization

Lecture- 5
Remote sensing concepts
and Application in
agriculture

Remote Sensing-
- Remote sensing is the science (and to some extent, art) of acquiring information about the Earth's surface without
actually being in contact with it.
- This is done by sensing and recording reflected or emitted energy and processing, analyzing, and applying that
information. In much of remote sensing, the process involves an interaction between incident radiation and the targets
of interest.
Components of Remote Sensing-
(a). Energy Source or Illumination (A) – the first requirement for remote sensing is to have an energy source which
illuminates or provides electromagnetic energy to the target of interest.
(b). Radiation and the Atmosphere (B) – as the energy travels from its source to the target, it will come in contact with
and interact with the atmosphere it passes through. This interaction may take place a second time as the energy travels
from the target to the sensor.
(c). Interaction with the Target (C) - once the energy makes its way to the target through the atmosphere, it interacts
with the target depending on the properties of both the target and the radiation.
(d). Recording of Energy by the Sensor (D) - after the energy has been scattered by, or emitted from the target, we
require a sensor (remote - not in contact with the target) to collect and record the electromagnetic radiation
(e). Transmission, Reception, and Processing (E) - the energy recorded by the sensor has to be transmitted, often in
electronic form, to a receiving and processing station where the data are processed into an image (hardcopy and/or
digital).
(f). Interpretation and Analysis (F) - the processed image is interpreted, visually and/or digitally or electronically, to
extract information about the target which was illuminated.

(g). Application (G) - the final element of the remote sensing process is achieved when we apply the information we
have been able to extract from the imagery about the target in order to better understand it, reveal some new
information, or assist in solving a particular problem.
Types of Remote Sensing-
1. Active Remote Sensing: when remote sensing work is carried out with a man made source of radiations which is
used to illuminate a body and to detect the signal reflected form. eg. Radar and Lidar remote sensing
2. Passive Remote Sensing: when remote sensing work is carried out with the help of electromagnetic radiations
(signals) reflected by a natural body (sun and earth). eg visible, NIR and Microwave remote sensing.
Application of Remote Sensing in Agriculture
Satellite and airborne images are used as mapping tools to classify crops, examine their health and viability and
monitor farming practices.
Agricultural applications of remote sensing includes-
1. Soil properties sensing- soil texture, soil structure, physical condition and soil moisture and soil nutrients.
2. Crop sensing- plant population, crop stress and nutrient status.
3. Yield monitoring systems- crop yield, harvest swath width and moisture content of grain
4. Variable rate technology systems- fertilizer flow, weed detection etc.
Crop Identification-
-It is very important for a national government to know what crops the country is going to produce in the current
growing season
-This knowledge has financial benefits for the country, as it allows the budget planning for importing and exporting
of food products

o To identify the crop we need to know in advance, how the crops reflect the near-
infrared at each of their various growth stages. Using the different near infrared
reflectance is one of the tools we have to discriminate between two crops.
o Having the knowledge of when each crop is planted and harvested, we can
estimate the percentage of vegetation cover through the growth period, assuming
no external factors (stress, disease, etc.) affect its growth.
Detection, diagnosis and control of plant diseases-
o Remote sensing assist in protecting the plants from potential attacks of pests,
fungi or bacteria
o By combining agricultural knowledge with remotely sensed data, it is possible to
have early warning and prevent a pest or a disease from affecting the crops, by
taking appropriate action at an early stage.
Yield estimation- Remote sensing has been used to forecast crop yields based
primarily upon statistical–empirical relationships between yield and vegetation
indices
Yield maps - Yield maps created on the basis of satellite images acquired in many
seasons represent the spatial variability in crops yield regardless of plant species
Soil Analysis - A major breakthrough in these studies has been the use of visible-near
infrared spectroscopy to develop quantitative calibrations for rapid characterization of
soil nutrients and various physical properties of soils. The coupling of this technology
with remote sensing data, geo-referenced ground surveys, and new spatial statistical
methods has resulted in the improved capability for large area soil assessments.

Soil Mapping –
Soil maps are another type of maps
developed using remote sensing data. These
maps can be compiled on the basis of airborne
or satellite images acquired when the degree of
soil coverage by plants is less than 30-50%.
Soil maps present homogeneous soil zones
with similar properties and conditions for plant
growth. These maps are useful in determining
soil sampling locations for detailed studies of
soil, soil moisture sensors location or
developing irrigation plans
Land cover mapping –
It is one of the most important and typical
applications of remote sensing data. Land
cover corresponds to the physical condition of
the ground surface, for example, forest,
grassland, concrete pavement etc., while land
use reflects human activities such as the use of
the land, for example, industrial zones,
residential zones, agricultural fields etc.

Lecture- 6
Image processing and
interpretation, global positioning
system, components and its
functions

Image Processing and Interpretation
Image Processing and Interpretation can be defined as act of examining images for the
purpose of identifying objects and judging their significance. Common image processing
functions;
Pre-Processing
➢ Prior to data analysis, initial processing on the raw data is usually carried out to
correct for any distortion due to the characteristics of the imaging system and imaging
conditions.
➢ Depending on the user's requirement, some standard correction procedures may be
carried out by the ground station operators before the data is delivered to the end-user.
➢ These procedures include radiometric correction to correct for uneven sensor
response over the whole image and geometric correction to correct for geometric
distortion due to Earth's rotation and other imaging conditions (such as oblique
viewing).
➢ The image may also be transformed to conform to a specific map projection system.
➢ Furthermore, if accurate geographical location of an area on the image needs to be
known, ground control points (GCP's) are used to register the image to a precise map
(geo-referencing).
Image Enhancement- It is to improve the appearance of the imagery to assist in visual
interpretation and analysis. Examples of enhancement functions include contrast
stretching to increase the tonal distinction between various features in a scene, and
spatial filtering to enhance (or suppress) specific spatial patterns in an image

Image Classification
1. Different landcover types in an image can be discriminated using some image classification algorithms using
spectral features, i.e. the brightness and "colour" information contained in each pixel. The classification
procedures can be "supervised" or "unsupervised".
2. In supervised classification, the spectral features of some areas of known landcover types are extracted from the
image. These areas are known as the "training areas". Every pixel in the whole image is then classified as
belonging to one of the classes depending on how close its spectral features are to the spectral features of the
training areas.
3. In unsupervised classification, the computer program automatically groups the pixels in the image into separate
clusters, depending on their spectral features. Each cluster will then be assigned a landcover type by the analyst.
4. Each class of landcover is referred to as a "theme“ and the product of classification is known as a "thematicmap".
Spatial Feature Extraction
o In high spatial resolution imagery, details such as buildings and roads can be seen.
o The amount of details depend on the image resolution.
o In very high resolution imagery, even road markings, vehicles, individual tree crowns, and aggregates of people
can be seen clearly. Pixel-based methods of image analysis will not work successfully in such imagery.
o In order to fully exploit the spatial information contained in the imagery, image processing and analysis algorithms
utilizing the textural, contextual and geometrical properties are required.
o Such algorithms make use of the relationship between neigh bouring pixels for information extraction.
o Incorporation of a-priori information is sometimes required.
o A multi-resolutional approach (i.e. analysis at different spatial scales and combining the resoluts) is also a useful
strategy when dealing with very high resolution imagery.

o In this case, pixel-based method can be used in the lower resolution mode and merged with the contextual and textural method
at higher resolutions.
Measurement of Bio-geophysical Parameters
• Specific instruments carried on-board the satellites can be used to make measurements of the bio-geophysical
parameters of the earth.
• Some of the examples are: atmospheric water vapour content, stratospheric ozone, land and sea surface
temperature, sea water chlorophyll concentration, forest biomass, sea surface wind field, tropospheric aerosol,
etc.
• Specific satellite missions have been launched to continuously monitor the global variations of these
environmental parameters that may show the causes or the effects of global climate change and the impacts of
human activities on the environment.
Geographical Information System (GIS)
o Different forms of imagery such as optical and radar images provide complementary information about the
landcover.
o More detailed information can be derived by combining several different types of images.
o For example, radar image can form one of the layers in combination with the visible and near infrared layers
when performing classification.
o The thematic information derived from the remote sensing images are often combined with other auxiliary
data to form the basis for a Geographic Information System (GIS).
o A GIS is a database of different layers, where each layer contains information about a specific aspect of the
same area which is used for analysis by the resource scientists.

Global Positioning System (GPS) is a satellite based navigation system consisting of more than 20 satellites and
several supporting ground facilities, which provide accurate, three dimensional position, velocity and time, 24 hours a
day, everywhere in the world and in all weather conditions 10.2 Components of GPS
GPS Ground control stations
✓ The ground control component stations send control signals to the GPS satellites, The GPS satellites transmit radio
signals and the GPS receivers, receive these signals and use it to calculate its position.
✓ The control segment uses measurements collected by the monitor stations to predict the behavior of each satellite's
orbit and atomic clocks.
✓ The prediction data is linked up to the satellites for transmission to users.
✓ The control segment also ensures that GPS satellite orbits remain within limits and that the satellites do not drift
too far from nominal orbits.
GPS satellites
• GPS satellites orbit in circular orbits at 17,440 km altitude, each orbit lasting 12 hours.
• The orbits are tilted to the equator by 55o to ensure coverage in polar regions. The satellites are powered by solar
cells to continually orientate themselves to point the solar panels towards the Sun and the antennas towards the
Earth.
• Each satellite contains four atomic clocks which measure time to a high degree of accuracy.
• The time information is placed in the codes broadcast by the satellite so that a receiver can continuously determine
the time the signal was broadcast.
• The signal contains data that a receiver uses to compute the locations of the satellites and to make other
adjustments needed for accurate positioning. The receiver uses the time difference between the time of signal
reception and the broadcast time to compute the range to the satellite

GPS receivers
-When you buy a GPS, you are actually buying only the GPS receiver and get free use of the other two main
components.
-GPS receivers are smaller to carry, easier to handle, much more versatile and updateable.
-Personal navigation with a GPS also means you can customize maps as you go along - plotting points of interest and
marking all those wonderful
places in an easy, neat and ordered manner.
Functions of GPS
Giving a location:
Its ability to accurately triangulate your position based on the data transmissions from multiple satellites.
It will give your location in coordinates, either latitude and longitude or Universal Transverse Mercators (UTMs).
Point to point navigation:
This GPS navigation feature allows you to add waypoints to your trips. By using a map, the coordinates of a trailhead
or road or the point where you're standing, you can create a point-to point route to the place where you're headed.
Route navigation:
By combining multiple waypoints on a trail, you can move point-to-point with intermediate bearing and distance
guides. Once you reach the first predetermined waypoint, the GPS receiver can automatically point you to the next
one or you can manually do this.
Keep a Track: Tracks are some of the most useful functions of navigation systems. You can map where you've
already been. This virtual map is called a track, and you can program the GPS system to automatically drop track-
points as you travel, either over intervals of time or distance. This can be done on land or in a nautical setting and
allows you to retrace your steps

GPS Applications- The GPS applications include;
Guidance- (a) Point guidance, (b) Swath guidance
Control- (a) Variable rate application, (b) Variable tillage depth and
(c) Variable irrigation
Mapping-
Soil properties
Chemical application
Chemical prescriptions
Tillage maps
Yield mapping
Pest mapping
Topographic maps
Planting maps

Lecture- 7
Introduction to crop simulation models and their uses for
optimization of agricultural inputs

When Simulation Is the Appropriate Tool, When Simulation Is Not Appropriate, Advantages and Disadvantages of
Simulation, Areas of Application, Systems and System Environment, Components of a System, Discrete and
Continuous Systems, Model of a System, Types of Models, Discrete-Event System Simulation, Steps in a Simulation
Study
Definition-
◼ A simulation is the imitation of the operation of real-world process or system over time.
 Generation of artificial history and observation of that observation history
◼ A model construct a conceptual framework that describes a system
◼ The behavior of a system that evolves over time is studied by developing a simulation model.
◼ The model takes a set of expressed assumptions:
 Mathematical, logical
 Symbolic relationship between the entities
Goal of modeling and simulation
◼ A model can be used to investigate a wide verity of “what if” questions about real-world system.
 Potential changes to the system can be simulated and predicate their impact on the system.
 Find adequate parameters before implementation
◼ So simulation can be used as
 Analysis tool for predicating the effect of changes
 Design tool to predicate the performance of new system
◼ It is better to do simulation before Implementation.

TYPES OF MODELS-
Depending upon the purpose for which it is designed the models are classified into different groups or types. Of them
a few are:
a. Statistical models: These models express the relationship between yield or yield components and weather
parameters. In these models relationships are measured in a system using statistical techniques. Example: Step
down regressions, correlation, etc.
b. Mechanistic models: These models explain not only the relationship between weather parameters and yield, but
also the mechanism of these models (explains the relationship of influencing dependent variables). These models
are based on physical selection.
c. Deterministic models: These models estimate the exact value of the yield or dependent variable. These models
also have defined coefficients.
d. Stochastic models: A probability element is attached to each output. For each set of inputs different outputs are
given along with probabilities. These models define yield or state of dependent variable at a given rate.
e. Dynamic models: Time is included as a variable. Both dependent and independent variables are having values
which remain constant over a given period of time.
f. Static: Time is not included as a variable. Dependent and independent variables having values remain constant
over a given period of time.
g. Simulation models: Computer models, in general, are a mathematical representation of a real world system. One
of the main goals of crop simulation models is to estimate agricultural production as a function of weather and soil
conditions as well as crop management. These models use one or more sets of differential equations, and calculate
both rate and state variables over time, normally from planting until harvest maturity or final harvest.

h. Descriptive model: A descriptive model defines the behavior of a system in a simple manner. The model reflects
little or none of the mechanisms that are the causes of phenomena. But, consists of one or more mathematical
equations. An example of such an equation is the one derived from successively measured 48 weights of a crop. The
equation is helpful to determine quickly the weight of the crop where no observation was made.
i. Explanatory model: This consists of quantitative description of the mechanisms and processes that cause the
behavior of the system. To create this model, a system is analyzed and its processes and mechanisms are quantified
separately. The model is built by integrating these descriptions for the entire system. It contains descriptions of
distinct processes such as leaf area expansion, tiller production, etc. Crop growth is a consequence of these processes.
Model Development
Model Calibration: Calibration is the adjustment of the system parameters so that simulation results reach a pre-
determined level, usually that of an observation. In many instances, even if a model is based on observed data,
simulated values do not exactly comply with the observed data and minor adjustments have to be made for some
parameters
Model Validation: The model validation stage involves the confirmation that the calibrated model closely
represents the real situation. The procedure consists of a comparison of simulated output and observed data. Ideally,
all mechanistic models should be validated. However, validation of all the components is not possible due to lack of
detailed datasets and the option of validating only the determinant ones is adopted.

How a model can be developed?
◼ Mathematical Methods
 Probability theory, algebraic method,.
 Their results are accurate
 They have a few Number of parameters
 It is impossible for complex systems
◼ Numerical computer-based simulation
 It is simple
 It is useful for complex system
When simulation is appropriate
◼ Simulation enable the study of internal interaction of a subsystem with complex system
◼ Informational, organizational and environmental changes can be simulated and find
their effects
◼ A simulation model help us to gain knowledge about improvement of system
◼ Finding important input parameters with changing simulation inputs
◼ Simulation can be used with new design and policies before implementation
◼ Simulating different capabilities for a machine can help determine the requirement
◼ Simulation models designed for training make learning possible without the cost
disruption
◼ A plan can be visualized with animated simulation
◼ The modern system (factory, wafer fabrication plant, service organization) is too
complex that its internal interaction can be treated only by simulation
When simulation is not appropriate-
When the problem can be solved by common sense.
When the problem can be solved analytically.
If it is easier to perform direct experiments.
If cost exceed savings.
If resource or time are not available.
If system behavior is too complex.
Like human behavior

Advantages and disadvantages of simulation-
In contrast to optimization models, simulation models are “run” rather than solved. Given as a set of inputs and model
characteristics the model is run and the simulated behavior is observed
1. Advantages of simulation-
New policies, operating procedures, information flows and son on can be explored without disrupting ongoing operation of the
real system. New hardware designs, physical layouts, transportation systems and can be tested without committing resources for
their acquisition.
• Time can be compressed or expanded to allow for a speed-up or slow-down of the phenomenon (clock is self-control).
• Insight can be obtained about interaction of variables and important variables to the performance.
• Bottleneck analysis can be performed to discover where work in process, the system is delayed. A simulation study can help
in understanding how the system operates. “What if” questions can be answered.
2. Disadvantages of simulation-
• Model building requires special training. Vendors of simulation software have been actively developing packages that
contain models that only need input (templates).
• Simulation results can be difficult to interpret. Simulation modeling and analysis can be time consuming and expensive.
• Many simulation software have output-analysis.

Areas of application-
Manufacturing applications, semiconductor manufacturing
Construction engineering and project management
military application
logistics, supply chain and distribution application
transportation modes and traffic
business process simulation
health care, automated material handling system (amhs)
test beds for functional testing of control-system software
risk analysis
insurance, portfolio, computer simulation
CPU, Memory,
Network simulation
Internet backbone, LAN (Switch/Router), Wireless, PSTN (call
center)
Types of models

Systems and System Environment-
A system is defined as a groups of objects that are joined together in some regular interaction toward the
accomplishment of some purpose.
An automobile factory: Machines, components parts and workers operate jointly along assembly line
A system is often affected by changes occurring outside the system: system environment.
Factory : Arrival orders
Effect of supply on demand: relationship between factory output and arrival (activity of system)
Banks : arrival of customers
Components of system
◼ Entity- An object of interest in the system : Machines in factory
◼ Attribute- The property of an entity : speed, capacity
◼ Activity- A time period of specified length :welding, stamping
◼ State- A collection of variables that describe the system in any time : status of machine (busy, idle, down,)
◼ Event- A instantaneous occurrence that might change the state of the system: breakdown
◼ Endogenous- Activities and events occurring with the system
◼ Exogenous- Activities and events occurring with the environment

Discrete and Continues Systems
A discrete system is one in which the state variables change only at a discrete set of points in time : Bank example
A continues system is one in which the state variables change continuously over time: Head of water behind the dam
Model of a System
◼ To study the system
- It is sometimes possible to experiments with system
◼ This is not always possible (bank, factory,…)
◼ A new system may not yet exist
◼ Model: construct a conceptual framework that describes a system
- It is necessary to consider those accepts of systems that affect the problem under investigation (unnecessary
details must remove)

Characterizing a Simulation Model
◼ Deterministic or Stochastic
-Does the model contain stochastic components?
-Randomness is easy to add to a DES
◼ Static or Dynamic
-Is time a significant variable?
◼ Continuous or Discrete
-Does the system state evolve continuously or only at discrete points
in time?
-Continuous: classical mechanics
-Discrete: queuing, inventory, machine shop models
Discrete-Event Simulation Model
➢ Stochastic: some state variables are random
➢ Dynamic: time evolution is important
➢ Discrete-Event: significant changes occur at discrete time
instances
Model Taxonomy

DES Model Development;How to develop a model:
➢ Determine the goals and objectives
➢ Build a conceptual model
➢ Convert into a specification model
➢ Convert into a computational model
➢ Verify
➢ Validate, Typically an iterative process
Three model levels
Conceptual
- Very high level
- How comprehensive should the model
be?
- What are the state variables, which
are dynamic, and which are important?
Specification
- On paper
- May involve equations, pseudocode,
etc.
- How will the model receive input?
Computational
- A computer program
- General-purpose PL or simulation
language?
Verification vs. Validation
Verification
-Computational model should be consistent with specification model
-Did we build the model right?
Validation
-Computational model should be consistent with the system being
analyzed
-Did we build the right model?
-Can an expert distinguish simulation output from system output?
Interactive graphics can prove valuable

Steps in Simulation-
1. Analyze the problem
2. Formulate a model- (a) Gather data, (b) Make simplifying assumptions
and document them
3. Model abstraction
4. Determine variables and units- (a) establish relationships among
variables and sub-models, (b) determine equation and functions
5. Solve the model
6. Model implementation
7. Verify and interpret the models solution
8. Execution
9. Output analysis
10. Report on the model-
(a) analysis of the problem, (b) model design
(c) model solution, (d) result and conclusions
11. Recommendation

Lecture- 8
STCR approach for precision agriculture
Soil test crop response (STCR) study based on soil test based fertilizer recommendation should be carried out to
develop quantitative basis for calculating the profit maximizing dose of fertilizers based on soil test for any crop.
STCR approach is based on soil contribution and yield level is used for recommending fertilizer dose. STCR concept
is more quantitative, precise and meaningful. Among various methods of fertilizer recommendation such as general
recommended dose (GRD), soil test based recommendation, critical value approach, etc.,
STCR-
1. Soil testing is a rapid chemical analysis to access available nutrient status of the soil and includes interpretation,
evaluation and fertilizer recommendation based on the result of chemical analysis and other considerations.
2. A chemical method for estimating the nutrient supplying capacity of a soil. It can determine soil’s nutrient status
before a crop (field, vegetable, ornamental) is planted.
Objectives and motto –
a. To study the relationship between soil test values for available N, P, K and yield response to important crops.
b. To derive yield targeting equations for important crops for making fertilizer recommendations.
c. To evaluate various soil test method for their suitability under field conditions.
d. To evaluate the extent to which fertilizer needs of crop can be reduced in relation with conjunctive use of organic
manure

Targeted Yield Approach
✓ Targeted yield concept is an approach comes under STCR.
✓ For obtaining a given yield a definite quantity of the nutrients must be taken up by the crop.
✓ Once this requirement is known for a given yield, the requirement of fertilizer can be estimated by taking into
account efficiency of the soil available nutrient pool and that of fertilizer requirement.
Concept of STCR
➢ ICAR established the AICRP on STCR in 1967 and the STCR concept was developed by Ramamoorthy in 1987.
➢ STCR approach is aiming at obtaining a basis for precise quantitative adjustment of fertilizer doses under varying
soil test values and response for targeted levels of crop production.
➢ STCR provides the relationship between a soil test value and crop yield. These are tested in follow up verification
by field trials to back up soil testing laboratories for their advisory purpose under specific soil, crop, and agro-
climatic condition
Methods of STCR
Gradient experiment: in this phase artificial soil fertility gradient is created at experiment site by- Divided the
experiment field into 3 or 4 equal strips according to size of field.
1. In 1st strip – no fertilization, 2nd strip -single fertilization, 3rd strip – double fertilization likely increasing
fertilizer dose with increase in number of strips
2. Grow exhaustive crop like maize, sorghum fodder crops.
3. Pre sowing and post harvest soil samples were collected from each strips and analysis. Plant analysis after
harvest of exhaustive crop

Test crop experiment: after confirming the establishment of fertility gradients in the experiment field this phase of
field experiment conducted with the following procedure:
1. Each strip is divided in number of plots which is equal to treatments
2. Initial soil sample is collected from each plot and analyzed
3. The experiment is layout as per statistical design
4. Test crop experiment is taken with different level of fertilizers
5. After maturity of crop to calculated yield from each plot
6. Soil and plant sample is collected from each plot and analyzed
7. Using the yield and nutrient uptake data, soil test values and applied fertilizer doses of treated and control plots,
the basic data viz. nutrient requirement (kg/q), soil, fertilizer and organic manure efficiencies (%) for making
fertilizer recommendation can be worked out.
Target Yield Equation
• Liebig’s law of minimum is the basis of this concept.
• First advocated by Truog (1960), Ramamoorthy and coworkers in 1967 established the theoretical basis and
experimental proof for the fact that Liebig’s law of the minimum operates equally well for N, P and K
• Among the various methods of fertilizer recommendation, the one based on yield targeting is unique in the sense
that this method not only indicates soil test based fertilizer dose but also the level of yield.
• Targeted yield concept is a balance between applied nutrients and the available nutrients in the soil.
𝑭𝒆𝒓𝒕𝒊𝒍𝒊𝒛𝒆𝒓 𝒅𝒐𝒔𝒆(𝑵, 𝑷𝟐𝑶𝟐, 𝑲𝟐𝑶 =
𝑵𝑹 𝒙 𝑻 𝒙 𝟏𝟎𝟎
% 𝑪𝑭
−
%𝑪𝑺
%𝑪𝑭
𝒙 𝒔𝒐𝒊𝒍 𝒕𝒆𝒔𝒕 𝒗𝒂𝒍𝒖𝒆
Expression for NR, CS and CF are presented below as;

Soil test crop response (STCR)
STCR approach is aiming at obtaining a basis for precise quantitative adjustment of fertilizer doses under varying soil
test values and response conditions of the farmers and for targeted levels of crop production. These are tested in
follow up verification by field trials to back up soil testing laboratories for their advisory purpose under specific soil,
crop, and agro-climatic conditions. STCR methodology takes in to account the three factors;
➢ Nutrient requirement (NR) in kg/ quintal of the produce
➢ Percentage contribution from soil available nutrients (SE)
➢ Percentage contribution from added fertilizers towards making effective fertilizer prescriptions for specific yields.
The adjustment equation derived from these parameters take the form;
F(NPK)=a(NPK)xT-b(NPK)xS(NPK)
Where,
F= Fertilizers nutrient (kg/ha), S= Soil available nutrients (kg/ha), T= Target yield (q/ha)
Nutrient requirement (NR), Fertilizer efficiency (FE) and Soil efficiency (SE) can be calculated from the
experimental data as
𝑎 (𝑁𝑃𝐾) =
𝑁𝑅
𝐹𝐸/100
, 𝑏 (𝑁𝑃𝐾) =
𝑆𝐸
𝐹𝐸
1. Nutrient requirement (NR) for one quintal (q) of grain;
𝑁𝑅 =
𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑡𝑟𝑖𝑒𝑛𝑡 𝑢𝑝𝑡𝑎𝑘𝑒 𝑏𝑦 𝑔𝑟𝑎𝑖𝑛 𝑎𝑛𝑑 𝑠𝑡𝑟𝑎𝑤 (𝑘𝑔/ℎ𝑎)
𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑 (𝑞/ℎ𝑎)
2. Fertilizer efficiency (FE per cent); [CF]=
FE=
Total nutrient uptake (kg/ha) – (Soil test value in treated plot (kg/ha)x Soil nutrient efficiency (%)
Fertilizer dose (kg/ha)
𝑥 100

3.Soil efficiency (SE)% [CS] =
Total nutrient uptake in control (kg/ha)
Soil test value in control (kg/ha)
x100
Using the above parameters, adjustment equation have been developed for different crops in different
agroclimatic regions on various soils as indicated
Ex. - For Rice crop.
a. Fertilizer N = 4.39 T -0.6723 Soil N
b. Fertilizer P2O5 = 2.83 T – 6.110 Soil P
c. Fertilizer K2O = 1.41 T – 0.329 Soil K
Where T= Targeted yield of rice Advantages
1) Efficient and profitable site specific fertilizer recommendation for increased crop production and for maintenance
of soil fertility.
2) Aims to provide balanced, efficient and profitable nutrient application rates for pre- set yield targets giving due
consideration to basic fertility status of soi
3) Efficient crop fertilization programme to meet the crop nutrient requirements is key to sustainable agriculture, it
means optimizing crop yields, minimizing nutrient losses to the environment, which is important economically
and environmentally.
STCR approach for precision farming; Agricultural production system is an outcome of complex interaction of
seed, soil, water, fertilizers and other agrochemicals. Therefore, judicious management of all the inputs is essential for
sustainability of such a complex system. Under normal conditions, recommended soil sampling procedure is to take
samples from portions of fields are no more than 20 acres in area

Grid soil sampling – it uses the same principles of soil sampling but increases the intensity of sampling
Ex. For example, a 20 acre sampling area would have 10 samples using a 2grid sampling system (samples are spaced
300 feet from each other) compared to one sample in the traditional recommendation. Soil samples collected in a
systematic grid also have location information that allows the data to be mapped. The goal of grid soil sampling is to
generate a map of nutrient requirement called an application map
1. Application map is loaded into the computer mounted on variable rate fertilizer spreader
2. Computer uses the application map and GPS receiver to direct a product delivery controller that changes the
amount and kind of fertilizer product according to application map

Lecture - 9
Nanotechnology, definition, concepts and techniques, brief introduction about nanoscale
effects, nano-particles, nano-pesticides, nano fertilizers and nano sensors etc.

- The word “nano” comes from a Greek word that means “Dwarf”
- 1nm = 10−9 m
Definition
Nano-science – it is the study of phenomena and manipulation of materials at atomic, molecular and macro-molecular
scale, where properties differ significantly from those at larger scale.
Nano-technologies- These are the design, characterization, production and application of structures, devices and
systems by controlling shape and size at nanometer.
Nanotechnology- is a process that builds controls and restructures that are the size of atoms and molecules.
Nano-particle- is defined as the small object that acts as a whole unit in terms of transport and properties.
Concept
The idea of nanotechnology was for the first time introduced in 1959 by the physicist Richard Feynman. The term
nanotechnology was first used in 1974 by Norio Taniguchi. Nano-particle is ultrafine unit with dimensions measured
in nanometers. Nanoparticle exists in the nature and can be created artificially. Nano-particles are having the
following properties
They are highly mobile in free state
They have enormous surface areas
They may exhibit the quantum effects
Nano-technology is based on two main approaches
1) Bottom up approach: Materials and devises are built from molecular components and which assemble themselves
chemically by molecular recognition
2) Top down approach: Nano objects are constructed from large entities without atomic level control

Type of Nano-sensors
Optical Nano-sensor
Ambient Light Nano-
sensor
Proximity Nano-
sensor
Enzymatic
Interaction
DNA Interaction
Antibody/Antigen
Interaction
Physical Nano-sensor
Chemical Nano-sensor
Biological Nano-sensor
Molecular
Concentration
Chemical
Composition
Displacement
Mass
Force
Pressure

Nano scale effects
Two principal factors cause the properties of nano-material to differ significantly from other materials
1) Increased relative surface area
2) Quantum effects
1) Increase relative surface area:
-Nano-scale materials have far larger surface areas than similar masses of larger area
-As surface area per mass of material increases, greater amount of material can come into contact with surrounding materials, thus
affecting reactivity.
Quantum size effect = Electronic properties of solids are altered with reduction in particle size
1. When particle sizes of solid matter in visible scale are compared to what can be seen in a regular optical micro-scope, there is a
little difference in the properties of the particle.
2. When the particles are created with nano dimensions the material properties change significantly from those at larger scales
3. Melting point, fluorescence, electrical conductivity, magnetic permeability and chemical reactivity change as a function of size
of the particle
4. Materials reduced to nano-scale can show different properties compared to that they exhibit in macro-scale enabling unique
application.
Example:
-Opaque substances become transparent (copper)
-Stable materials turn combustible (aluminium)
-Solids turn into liquids at room temperature (gold)
-Insulators become conductors (silicon)
Size of the cube Number of cubes Collective surface area
1m 1 6 𝑚2
0.1m 1000 60 𝑚2
0.01m 10−6
600 𝑚2
0.001m 10−9 6000 𝑚2
0. 0−9m=1nm 1027 6×10−9𝑚2

Nanotechnology can increase agricultural production, and its applications include:
(1) Nano-formulations of agrochemicals for applying pesticides and fertilizers for crop improvement;
(2) The application of Nano-sensors in crop protection for the identification of diseases and residues of
agrochemicals;
(3) Nanodevices for the genetic engineering of plants;
(4) Plant disease diagnostics;
(5) Animal health, animal breeding, poultry production; and
(6) Postharvest management. Precision farming techniques might be used to further improve the crop yields but not
damage soil and water.
NANO-PESTICIDES
1. Nano-pesticides are defined as any formulation that includes elements of nm size range and/or claims novel
properties associated with these small size range
2. Nano-pesticides are plant protection chemicals, in which either the active ingredient or the carrier molecule is
developed through nanotechnology
3. The major aim in the development of nano-pesticides is to lessen the environmental hazards of a pesticide active
ingredient through improving the efficacy of a chemical
4. The size of a nano-particle generally ranges 1-100 nanometer and a nanometer is one billionth of a meter. When the
size gets this small, particles reach a very large surface area and thus more volume of pesticides get contact with the
pests.

Formulations of Nano-pesticides
Nano-pesticides are formulated according to their intended purpose as formulations improving solubility, slow release
of active ingredients, prevent degradation etc. Some foremost nano-formulations are:
Nano-emulsions: In this formulation active ingredient of the chemical is dispersed as nanosized droplets in water,
with surfactant molecules confined at the pesticide-water interface
Nano-suspension: Nano-suspensions, also termed as nano-dispersions, are formulated by dispersing the pesticide as
solid nanosized particles in aqueous media
Polymer based nano-particles: Polymer-based pesticide nanocarriers are majorly deployed in the slow and
controlled release of active ingredients to the target site
Nano-encapsulation: This confines the hydrophobic or hydrophilic active ingredient, surrounded by a polymer
coating or membrane.
Nanospheres: These are homogeneous vesicular structures, in which the bioactive ingredient is uniformly dispersed
throughout the polymer matrix.
Nanogels: These are also known also hydrogel nano-particles. These are formulated by cross linking of polymeric
particles having hydrophilic groups
Nano-fibres: Nano-fibres are developed through electrospinning, thermal induced phase separation

Advantages of Nano-pesticides
▪ Improved solubility of active ingredients
▪ Better stability of formulation
▪ Slow release of active ingredient
▪ Improved mobility
▪ Higher surface area
▪ Uniform leaf coverage
▪ Improve pesticide utilization
▪ Nano-formulations improve adhesion of droplets to plant surface
▪ Eco-friendly approach

NANO-FERTILIZERS
Nano-fertilizers are nutrient carries of nano-dimensions ranging from 30-40 nm (10−9
or one billionth of a meter) capable of holding
bountiful of nutrient ions due to their high surface area and release it slowly and steadily that commensurate with crop demand. These
fertilizers can be used to improve nutrient use efficiency. As per literature, it appears that nano fertilizers are more beneficial as compared
to chemical fertilizers.
i. Three times increase in nutrient use efficiency (NUE)
ii. 80-100 times less requirement to chemical fertilizers
iii. 10 times more stress tolerant by the crops
iv. Complete bio-source, so eco-friendly
v. More nutrient mobilization by the plants
vi. 17-54 percent improvement in the crop yield
vii. Improvement in soil aggregation, moisture retention and carbon build up.
Nano-fertilizers are nutrient carriers of Nano-dimensions capable of holding bountiful of nutrient ions due to their high surface area and
release it slowly and steadily that commensurate with crop demand. Nutrient use efficiencies of conventional fertilizers hardly exceed 30-
35 %, 18-20 % and 35-40 % for N, P and K respectively. The data remain constant for the past several decade. Nano particles have
extensive surface area and capable of holding abundance of nutrients and release it slowly and steadily such that it facilitates uptake of
nutrients matching the crop requirement without any associated ill effects of customized fertilizer inputs.
Encapsulation of fertilizers within a nano particle is one of these new facilities which are done in three ways :
The nutrient can be encapsulated inside nano-porous materials
Coated with thin polymer film
Delivered as particle or emulsions of nano scales dimensions
In addition, nano-fertilizers will combine nano devices in order to synchronize the release of fertilizer nutrient losses to soil, water and
air via direct internalization by crops, and avoiding the interaction of nutrients with soil, microorganisms, water, and air.
Types of nano devices available are:
Nano-porous zeolites
Controlled release nano fertilizer

They are very soluble in a variety of solvents, including water.
Nano-fertilizers have particles that are less than 100 nm in size,
allowing for greater penetration of the plant from the applied
surface, such as soil or leaves.
In comparison to conventional fertilizers, nano fertilizers have a
number of benefits, including improved crop quality parameters
and soil fertility yield, nontoxicity and reduced risk to people and
the environment, lower cost, and higher profitability.
There have been three categories of nano fertilizers proposed:
1. Nanoscale fertilizer (nutrient-containing nanoparticles)
2. Nanoscale additives
3.Nanoscale coating: conventional fertilizers coated with or loaded
with nanoparticles.

NANO-SENSORS
Sensors are any biological, chemical or surgical sensory points used to convey information about nanoparticles to the
macroscopic world. Their use mainly includes various medicinal purposes and as gateways to building other
nanoproducts, such as computer chips that work at the nanoscale and nanorobots. Nano-sensors in agriculture
are used to detect the humidity of soil, pesticide residue, nutrient requirement and crop pest identification.

Different types include
✓ Sensors using semi-conductor nanowire detection elements- these sensors are capable of detecting a range of chemical
vapours. When molecules bond to nanowires made from semiconducting materials such as zinc oxide, the conductance of the
wire change. The amount that the conductance changes and in which direction depends on the molecule bonded to the
nanowire.
✓ Semi-conducting carbon nano tubes – to detect chemical vapours, you can first functionalize carbon nanotubes by bonding
them with molecules of a metal, such as gold. Molecules of chemicals then bond to the metal, changing the conductance of the
carbon nanotubes.
✓ Carbon nanotubes and nanowires detect bacteria and viruses- these also utilize changes in electrical conductivity, in this
case that of carbon nanotubes to which an antibody is bonded. When a matching bacteria or virus attaches to the antibody a
change in conductivity can be measured. In this process you attach nano-tubes to metal contacts in the detector and apply a
voltage across the nanotube. When a bacteria or virus bonds to the nanotube, the current changes and generates a detection
signals.
✓ Nanocantilevers-these devices are being used to develop sensors that can detect single molecules. These sensors take
advantage of the fact that the nano-cantilever oscillates at a resonance frequency that change if a molecule lands on the
cantilever, changing its weight. Coating a cantilever with molecule, such as antibodies, that bond to a particular bacteria or
virus determines what bacteria or virus will bond to the cantilever.
Nano Materials- whether of natural or manufactured origin, possess external dimensions in the range of 1-100nm. An extremely
small device capable of detecting and responding to physical stimuli with dimension in the order of one billion of a meter
Nanomaterials -
Fertilizer,
Plant protection things – pesticides, fungicides, weedicides
Plant pathogen detection tools

NANO-BIOSENSORS
1. Nano-biosensor is a modified version of a biosensor which may be defined as a compact analytical device/ unit incorporating a
biological or biologically derived sensitized element linked to a physico-chemical transducer
2. Nano-sensors with immobilized bioreceptor probes that are selective for target analyte molecules are called nano-biosensors.
3. A nano-biosensor is usually built on the nanoscale to obtain process and analyze the data at the level of atomic scale
4. Their applications include detection of analytes like urea, glucose, pesticides etc., monitoring of metabolites and detection of
various microorganisms/pathogens.
Characteristics of ideal biosensor
• Highly specific for the purpose of the analyses i.e. a sensor must be able to distinguish between analyte and any ‘other’
material. Stable under normal storage conditions.
• Specific interaction between analytes should be independent of any physical parameters such as stirring, pH and temperature.
• Reaction time should be minimal.
• The responses obtained should be accurate, precise, reproducible and linear over the useful analytical range and also be free
from electrical noise.
• The nano-biosensor must be tiny, biocompatible, nontoxic and nonantigenic. Should be cheap, portable and capable of being
used by semi-skilled operators Constituents of Nano-biosensors
1) The biologically sensitized elements (probe) including receptors, enzymes, antibodies, nucleic acids, molecular imprints,
lectins, tissue, microorganisms, organelles etc., which are either a biologically derived material or bio-mimic component that
receives signals from the analytes (sample) of interest and transmits it to transducer. And such nano-receptor may play a vital
role in the development of future nano-biosensors.
2) The transducer acts as an interface, measuring the physical change that occurs with the reaction at the bioreceptor/sensitive
biological element then transforming that energy into measurable electrical output.
3) The detector element traps the signals from the transducer, which are then passed to a microprocessor where they are amplified
and analyzed; the data is then transferred to user friendly output and displayed/stored

Types of Nano-biosensors
1. Mechanical Nano-biosensors: Nanoscale mechanical forces between biomolecules provide an exciting ground
to measure the biomolecular interaction. This helps in the development of minute, sensitive and label free
biosensors
2. Optical Nano-biosensors: Optical biosensors are based on the arrangement of optics where beam of light is
circulated in a closed path and the change is recorded in resonant frequency when the analyte binds to the
resonator
3. Nanowire Biosensors: Nanowire biosensor is a hybrid of two molecules that are extremely sensitive to outside
signals: single stranded DNA, (serving as the ‘detector’) and a carbon nanotube, (serving as the transmitter).
4. Ion Channel Switch Biosensor Technologies: The Ion Channel Switch (ICS) is based on a synthetic self-
assembling membrane that acts as a biological switch for detecting the signals i.e. the presence of specific
molecules by triggering an electrical current
5. Electronic Nano-biosensors: Electronic nano-biosensors work by electronically detecting the binding of a target
DNA that actually forms a bridge between two electrically separated wires on a microchip
6. Viral nano-biosensors: Virus particles are essentially biological nanoparticles. Herpes simplex virus (HSV) and
adenovirus have been used to trigger the assembly of magnetic nanobeads as a nano-sensor for clinically relevant
viruses
7. Nano-shell Biosensors: Positioning gold nano-shells are used in a rapid immunoassay for detecting analytes
within complex biological media without any sample preparation
8. PEBBLE Nano-biosensors: Probes Encapsulated by Biologically Localized Embedding (PEBBLE) nano-
biosensors consist of sensor molecules entrapped in a chemically inert matrix by a microemulsion polymerization
process that produces spherical sensors in the size range of 20 to 200 nm.

Role of Nano-Biosensors in Agriculture
1. Presently, nanomaterial-based biosensors exhibit fascinating prospects over traditional biosensors.
2. Nano-biosensors have marked advantages such as enhanced detection sensitivity/ specificity and possess great
potential for its applications in different fields including environmental and bioprocess control, quality control of
food, agriculture, bio defense, and, particularly, medical applications.
3. But here we are concerned with the role of nano biosensor in agriculture and agro-products.
4. Some of the potential applications of nano-biosensors are listed below:
▪ As diagnostic tool for soil quality and disease assessment
▪ As an agent to promote sustainable agriculture
▪ As a device to detect contaminants and other molecule
▪ As tool for effective detection of DNA and protein

Lecture - 10
Use of nanotechnology in seed, water, fertilizer, plant protection for scaling up farm productivity

1. Agriculture has always been the backbone of the developing countries
2. Nanotechnology is now emerging and fast growing field of science which is being exploited over a wide range of
scientific disciplines including Agriculture
3. A smarter way for sustainable agriculture appears to be nanotechnology
Potential applications of Nanotechnology in Agriculture
I. Increase the productivity using nano-pesticides and nano-fertilizers
II. Improve the soil quality using nano-zeolites and hydrogels
III. Stimulate crop growth using nanomaterials
IV. Provide smart monitoring using nano-sensors by wireless communication devises
NANOTECHNOLOGY IN TILLAGE
1) Mechanical tillage practices improve soil structure and increase porosity leading to better distribution of soil
aggregates and eventually modify the physical properties of soil.
2) Nanomaterials usage increase soil pH and soil structure
3) It also reduces mobility, availability and toxicity of heavy metals besides reducing soil erosion
4) Nanoparticles in soil reduce cohesion and internal friction besides reducing the shear strength of the soil.
Reduction in adhesion of soil particles allows easy crushing of lumps with less energy
NANOTECHNOLOGY IN SEED SCIENCE
a) Seed is nature’s nano-gift to man. It is self perpetuating biological entity that is able to survive in harsh
environment on its own.
b) Nanotechnology can be used to harness the full potential of seed.
c) Seed production is a tedious process especially in wind pollinated crops.
d) Detecting pollen load that will cause contamination is a sure method to ensure genetic purity.

1. Pollen flight is determined by air temperature, humidity, wind velocity and pollen production of the crop.
2. Use of nano-biosensors specific to contaminating pollen can help alert the possible contamination and thus
reduces contamination.
3. The same method can also be used to prevent pollen from Genetically, modified crop from contaminating field
crops.
4. Novel genes are being incorporated into /seeds and sold in the market.
5. Tracking of sold seeds could be done with the help of nano-barcodes that are encodable, machine - readable,
durable and sub-micron sized taggants.
6. Disease spread through seeds and many times stored seeds are killed by pathogens.
7. Nano-coating of seeds using elemental forms of Zn, Mn, Pa, Pt, Au, Ag will not only protect seeds but used in far
less quantities than done today.
8. Technologies such as encapsulation and controlled release methods have revolutionized the use of pesticides and
herbicides. Seeds can also be imbibed with nanoencapsulations with specific bacterial strain termed as Smart
seed.
9. It will thus reduce seed rate, ensure right field stand and improved crop performance.
10. A smart seed can be programmed to germinate when adequate moisture is available.
11. Coating seeds with nanomembrane, which senses the availability of water and allow seeds to imbibe only when
time is right for germination, aerial broadcasting of seeds embedded with magnetic particle, detecting the
moisture content during storage to take appropriate measure to reduce the damage and use of bioanalytical nano-
sensors to determine ageing of seeds are some possible thrust areas of research.
12. Carbon nanotubes (CNTs) can also be used as new pores for water permeation by penetration of seed coat and act
as a passage to channelize the water from the substrate into the seeds.

NANOTECHNOLOGY IN WATER USE
I. Water purification using nanotechnology exploits nanoscopic materials such as carbon nanotubes and alumina filters for
nanofiltration
II. It utilizes the existence of nanoscopic pores in zeolite filtration membranes, nano-catalysts and magnetic nanoparticles
III. Carbon nanotube membranes and Nanofibrous alumina filters can remove almost all kinds of water contaminants including
turbidity, oil bacteria, viruses and organic contaminants
NANOTECHNOLOGY IN FERTILIZERS
• Fertilizers have played a pivotal role in enhancing the food grain production in India
• Despite the resounding success in grain yield, it has been observed that yields of many crops have begun to stagnate as a
consequence of imbalanced fertilization and decline in organic matter content of soils.
• Excessive use of nitrogenous fertilizer affects the groundwater and also causes eutrophication in aquatic ecosystems.
• A disturbing fact is that the fertilizer use efficiency is 20-50 per cent for nitrogen and 10-25 per cent for phosphorus.
• Elimination of eutrophication and drinking water with possible build up of nutrients in soil is possible only by adopting nano
fertilizers an emerging alternative to conventional fertilizers
• Additionally, nano-technology has improved nutrient use efficiency, and minimize costs of environmental protection.
• Slow-release of nano-fertilizers and nanocomposites are excellent alternatives to soluble fertilizers. Nutrients are released at a
slower rate throughout the crop growth; plants are able to take up most of the nutrients without any waste.
• Slow release of nutrients in the environments could be achieved by using zeolites that are a group of naturally occurring
minerals having a honeycomb-like layered crystal structure. Its network of interconnected tunnels and cages can be loaded with
nitrogen and potassium, combined with other slowly dissolving ingredients containing phosphorous, calcium and a complete
suite of minor and trace nutrients. Zeolite acts as a reservoir for nutrients that are slowly released “on demand.”
• Fertilizer particles can be coated with nanomembranes that facilitate slow and steady release of nutrients.
• The Nano-composites being contemplated to supply all the nutrients in right proportions through the “Smart” delivery systems
also needs to be examined closely.

NANOTECHNOLOGY IN PLANT PROTECTION
i. Persistence of pesticides in the initial stage of crop growth helps in bringing down the pest population below the economic
threshold level and to have an effective control for a longer period. Hence, the use of active ingredients in the applied surface
remains one of the most cost-effective and versatile means of controlling insect pests.
ii. To protect the active ingredient from the adverse environmental conditions and to promote persistence, a nanotechnology
approach, namely “nano-encapsulation” can be used to improve the insecticidal value.
iii. Nanoencapsulation comprises nano-sized particles of the active ingredients being sealed by a thin-walled sac or shell
(protective coating).
iv. Nanoencapsulation of insecticides, fungicides or nematicides will help in producing a formulation which offers effective
control of pests while preventing accumulation of residues in soil.
v. In order to protect the active ingredient from degradation and to increase persistence, a nanotechnology approach of
“controlled release of the active ingredient” may be used to improve effectiveness of the formulation that may greatly decrease
amount of pesticide input and associated environmental hazards.
vi. Nano-pesticides will reduce the rate of application because the quantity of product actually being effective is at least 10-15
times smaller than that applied with classical formulations, hence a much smaller than the normal amount could be required to
have much better and prolonged management.
vii. Recently, clay nanotubes (halloysite) have been developed as carriers of pesticides at low cost, for extended release and better
contact with plants, and they will reduce the amount of pesticides by 70-80%, thereby reducing the cost of pesticide with
minimum impact on water streams.
Currently, the nutrient use efficiency is low due to the loss of 50-70% of the nitrogen supplied in conventional fertilizers.
Encapsulation of fertilizers within a nanoparticle is one of these new facilities which are done in three ways
a) The nutrient can be encapsulated inside nano-porous materials,
b) Coated with thin polymer film
c) Delivered as particle or emulsions of nanoscales dimensions

NANOTECHNOLOGY IN WEED MANAGEMENT
a. Multi-species approach with single herbicide in the cropped environment resulted in poor control and herbicide
resistance
b. Continuous exposure of plant community having mild susceptibility to herbicide in one season and different
herbicide in other season develops resistance in due course and become uncontrollable through chemicals
c. Developing a target specific herbicide molecule encapsulated with nanoparticle is aimed at specific receptor in
the roots of target weeds, which enter into roots system and translocated to parts that inhibit glycolysis of food
reserve in the root system. This will make the specific weed plant to starve for food and gets killed
d. In rainfed areas, application of herbicides with insufficient soil moisture may lead to loss as vapour so controlled
release of encapsulated herbicides is expected to take care of the competing weeds with crops.
e. Now a days, adjuvants for herbicide application are currently available that claim to include nanomaterials.
f. Excessive use of herbicides leave residue in the soil and cause damage to the succeeding crops. continuous use of
single herbicide leads to evolution of herbicide resistant weed species and shift in weed flora.
g. For example, Atrazine, an s-triazine-ring herbicide, is used globally for the control of pre-and postemergence
broadleaf and grassy weeds, which has high persistence (half life-125 days) and mobility in some types of soils.
Residual problems due to the application of atrazine herbicide pose a threat towards widespread use of herbicide
and limit the choice of crops in rotation.
h. To remediate the atrazine residue from soil within a short span of time, application of silver modified with
nanoparticles of magnetite stabilized with Carboxy Methyl Cellulose (CMC) nanoparticles recorded 88%
degradation of herbicide atrazine residue under controlled environment found to be a potential remedy

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