This document describes a proposed expert system for agricultural extension in India. It provides details on the institutions and researchers involved, rationale for the system, selected crops and regions, requirement analysis, development of the knowledge base including expert groups for different crops, linkages with other organizations, and design of the system including its architecture, components, and user interface. The system is intended to help farmers make appropriate decisions by providing up-to-date information and recommendations tailored to their specific resources and needs.

1. Presenter: Dr. Ram Bahal
rb_agex@yahoo.com
Division of Agricultural Extension
I.A.R.I, New Delhi-12
Expert System of Extension

2. Institutes Involved
• Lead Center: Division of Agricultural
Extension, IARI, New Delhi-12
• Co-operating Center: Division of
Computer Science, IASRI, New Delhi-12

3. Research Team
• Dr.Ram Bahal (PI), IARI
• Dr. (Mrs.)Monika Wason (Co- PI), IARI
• Sh. Sudeep (CCPI), IASRI

4. Rationale:
Expert System
of
Extension

5. Introduction of Extension
• 1866 Great Famine of Bengal & Orissa
• 1861-1941 Rabindranath Tagore-Self help and
Mutual help
• 1869-1948 Mahatma Gandhi-Improvement in their
inner man
• 1880 Famine Commission
• 1901 Famine Commission
• 1928 Royal Commission
• 1947 Grow More Food Campaign
• 1952 Community Development Programme
To Meat the Food Need
(Quantity)
Quality and Precision
Rationale 1

6. Medical
AirwaysRailways
Communication
Industries
Financial
Institutions
Agriculture &
Farmer ?
Rationale 2

7. Poor
ratio of SMS
to agents
Lower level of
education of
extension agents
Short supply
of extension
agents
More number of
farmer per extension
worker
More area to
be covered by
agents
Less number
of female
extension
agents
Human Resource
of Extension
Rationale 3

8. Poor
transportation
facility to agents
Lower pay to
extension agents
Less avialability
of
programme cost
Poor housing
to extension
workers
Poor
communication
facility to agents
Very little
expenditure
per farmer
Financial Resource
of Extension
Rationale 4

9. Personal & Group Contact in 19th Century
Rationale-5

10. Use of Print media in 20th Century
Rationale-6

11. Use of Electronic media in 21st Century
Rationale-7

12. Difference between Conventional Extension System
and Expert System of Extension
Conventional Extension System
1. Limited possibility to disseminate the
same information to all farmers at the
same time.
2. The farmers need, resources,
infrastructure, market facilities etc. are
rarely considered while recommending
the information.
3. Information given by agents depends
on its availability.
4. Cost benefit analysis is not well
calculated
5. The farmer can get the information
only if extension agent is available.
6. The information may not necessary be
helpful in decision-making in choosing
any crop or enterprise.
7. The information may not be up-dated.
8. The extension agents are generally less
educated and non technical.
9. The working is fragmented, as it is
totally manual.
10. This system is now getting out dated.
Expert System of Extension
1. Disseminate the same information to all
the farmers at the same time.
2. The farmer’s needs, resources, etc. are
considered while recommending the
information
3. Information is chosen by farmers
based on needs and suitability.
4. Recommendations depend on well
calculated cost benefit analysis.
5. The farmer can get the information
from any Cyber Cafe at any place at
any time.
6. The information provided essentially
helps in decision-making.
7. The information generally up-dated on
day to-day basis.
8. The experts are highly knowledgeable
and high-tech.
9. The working is through networking and
interconnected with a number of
electronic systems
10. This system is a recent advancement.

13. What should I do?
Extension Client

14. Market
5 km
Land
2 acres
Labour
5 members
Capital
Rs. 5000
Power
Pair of bullock
Source of
Irrigation
Pump set
My resources

15. Which choice
is best?
Which choice
is income
generating?
Which choice
requires less
labour?
Which choice
requires less
land area ?
Which choice
is not much
affected by
season?
Which choice
requires less
input?
Fisheries
Crops
Fruits
Piggerey
Flowers
Poultry
Dairy
Bee
keeping

16. Magazine
Television
Extension
worker
Neighbour
News paperFriend
Who will help me
in appropriate
decision making?
The answer of all these questions is:
EXPERT
SYSTEM OF
EXTENSION

17. What is Expert System ?
“Expert System” is an intelligent computer
programme that uses knowledge and
inference procedures to solve problems that
are difficult enough to require human
expertise for their solution. The knowledge
necessary to perform at such a level plus the
inference procedures used can be thought of
as a model of the expertise of the best
practitioners in the field.
(Daniel Hunt, 1986)

18. Cyber Extension
Cyber extension means “using the power
of online networks, computer
communications and digital interactive
multimedia to facilitate dissemination of
agricultural technology” (Sharma)

19. 1. Area
1. Gujarat
2. Rajasthan
3. Madhya Pradesh
4. Punjab
5. Haryana
6. Uttar Pradesh
7. Delhi

20. 2. Sub-Domains of Agriculture
1. Agriculture
• Cereal Production
• Vegetable Production
• Pulse Production
• Fruit Production
• Oil Seed Production
• Flower production
• Fodder Production
• Fiber Production
• Spices Production
• Aromatic plant Production
• Wood plant Production
• Medicinal Plant Production
• Commercial crop production
2. Animal Husbandry
• Milk Production
• Meat Production
• Wool Production
• Poultry Production
3. Fishery
4. Agri Business

21. 3. Selected States, Districts and
Crops
Sl. No. State Districts Crops
1. Punjab Ludhiyana Paddy, Mustard,
Pea
2. Haryana
Karnal
Gurgaon
Hisar
Paddy
Mustard
Tomato
3. Delhi Delhi Gladiolus, Tomato,
Mushroom, Pea
4. Rajsthan Bharatpur Mustard
5. Gujarat Anand Mustard
6. M.P. Datia Musatrd
7. U.P.
Kanpur
Lucknow
Varansi
Tomato, Gladiolus
Mango
Pea and Tomato

22. Districts selecting criteria was as follow:
1.Should cover maximum states of selected agro
ecological region.
2. Should have ICAR/KVK/SAU centre near it.
3. Should have sufficient area under the crops covered
in this system.
4.Should have maximum climatic & socio economic
diversity within the same agro-ecological region.
5.Should give higher priority to those districts where the
selected crops are taken on commercial basis.
Requirement Analysis

23. 1. Mustard

24. 1.Mustard

25. 1.Mustard
2. Paddy

26. 1. Mustard
2. Paddy
3. Pea
4. Tomato

27. 1. Mustard
2. Paddy
3. Pea
4. Tomato
5. Gladiolus

28. Kanpur
Lucknow
Varanasi
1. Mustard
2. Paddy
3. Pea
4. Tomato
5. Gladiolus
6. Mango

29. Map of Delhi
1. Mushroom
2. Pea
3. Tomato
4. Gladiolus

30. 4. Selected Crops by sub-area and seasons
Sl.
No.
Sub
Area
Seasons
Rabi Kharif Zayad
1. Cereals - Paddy -
2. Pulses Pea - -
3. Oilseed Mustard - -
4. Vegetables Tomato - -
5. Flowers Gladiolus - -
6. Agribusiness Mushroom - -
7. Post Harvest
Technology
- - Mango

31. 5. Inauguration of Workshop
Workshop on Expert System of Extension
To Design Document
March 26-27, 2002

32. 6. Core group of Paddy
Experts from IARI:
Genetics: Dr. F. U. Zaman and Dr. V. P. Singh
BGA: Dr. (Mrs.) Dolly Dhar
Physics: Dr. N.V. K. Ckhkrabarty
P. Pathology: Dr. (Mrs.) Janki Kandhari
Chemicals: Dr. R. L. Gupta
Nematology: Dr. Pankaj
Microbiology: Sh. R. D.S. Malik

33. 7. Core group of Mustard
Experts from IARI:
Biotechnology:Dr. R. K. Katiyar
Genetics: Dr. R. S. Malik
Soil Science: Dr. R. N. Panday
Physics: Dr. N.V. K. Chakrabarty
Nematology: Dr. Pankaj
Microbiology: Sh. R. D. S. Malik
Agr. Enrg.: Dr. S. K. Adalakha
Seed Science: Dr. Surender prakash
NBPGR: Miss. Madhu Bala

34. 8. Core group of Pea
Experts from IARI:
Genetics: Dr. S. K. Mishra
Vegetables: Dr. R. R. Sharma
Genetics: Dr. R. S. Malik
Soil Science: Dr. R.N. Panday
P. Pathology: Dr. Pratibha Sharma
Nematology: Dr. Pankaj
NBPGR: Miss. Madhu Bala
Microbiology: Sh. R.D. S. Malik

35. 9. Core group of Tomato
Experts from IARI:
Vegetables: Dr. R. R. Sharma
Vegetables: Dr. D. C. Pachauri
Soil Science: Dr. R. N. Pandey
P. Pathology: Dr. Pratibha Sharma
Nematology: Dr. Pankaj
Microbiology: Sh. R. D. S. Malik
PHT: Dr. (Mrs.) Vijay. Sethi
Entomology: Dr. O. P. Lal
NBPGR: Miss. Madhu Bala

36. 10.Core group of Gladiolus
Experts from IARI:
Floriculture: Dr. R. L. Mishra
Floriculture: Dr. R. S. Panwar
Floriculture: Dr. K. P. Singh
P. Pathology: Dr. Pratibha Sharma
Nematology: Dr. Pankaj
Soil Science: Dr. R. N. Panday
Physiology: Dr. Madan Pal
NBPGR: Miss. Madhu Bala

37. 11.Core group of Mushroom
Experts from IARI:
P. Pathology: Dr. R. K. Sharmara
Nematology: Dr. Pankaj
PHT: Dr. R. K. PAl
NBPGR: Miss. Madhu Bala
PHT: Dr. (Mrs.) Vijay Sethi

38. 12. Core group of Mango
Experts from IARI:
Horticulture: Dr. S. N. Panday
Horticulture: Dr. R. R. Sharma
P. Pathology: Dr. Pratibha Sharma
Nematology: Dr. Pankaj
Entomology: Dr. O. P. Lal
PHT: Dr. R. K. Pal
PHT: Dr. (Mrs.) Vijay Sethi
NBPGR: Miss. Madhu Bala

39. 13. Linkages Developed
Sl. No. Institutes/Organizations
1. CCS Haryana Agricultural University
2. IIVR& BHU Varansi
3. NRCRM, Bharatpur
4. CIAE Bhopal
5. Gurgaon & Bawal Centers
6. Central institute of Sub-Tropical Horticulture, Lucknow
7. C. S. Azad University of Agril and Technology, Kanpur
8. IIPR, Kalyanpur, Kanpur
9. PAU, Ludhiyana
10. NDRI, Karnal, Haryana

40. 14. Design of Expert System of xtension
The system was designed in four components
1. The Knowledge Base
2. The Inference Engine
3. The Knowledge – Acquisition Module
4. The Explanatory Interface

41. Components
Kernel
Or
Core of
Expert
System
Explanatory Interface
Acquisition module
Knowledge
base
Inference Engine
Representation of
Knowledge
Dat
abas
e
Expert
Machine
learning
(Induction
Strategies)
Methods of
Plausible
reasoning
The Human
Window
User

42. Explanatory Interface
(Html, JavaScript)
Application Logic Layer
(Java Server Pages)
Inference Engine Layer
( Java Expert System Shell )
Database Layer
(SQL Server)
Architecture of Expert System of Extension
N-Tier Architecture

43. Architecture of Expert System of Extension
• The inference engine layer was implemented using
the Java Expert System Shell built by the Sandia
National Laboratories, Livermore, CA, USA.
• IASRI has acquired R&D license for the JESS under
this project.
• Jess's rule engine uses an improved form of a well-
known algorithm called Rete (latin for "net") to match
rules against the knowledge base. Jess is actually
faster than some popular expert system shells written
in C.

44. 15. Home page of Website

45. Technology Developed

46. Web Page of Paddy

47. Insect Control in Paddy

48. Gandhi Bug

49. Gandhi Bug on Paddy Ear Head

50. Paddy Blast

51. Home page of Irrigated Mustard

52. Aphid Attack on Mustard

53. Home page of Pea

54. Home page of Tomato

55. Home Page of Gladiolus

56. Home page of Mushroom

57. Home page of Mango

58. Selection of Variety Attributes

60. Knowledge Retrieval about Plant Protection

61. Search Queries

62. Benefits to farmers
•Maximization of benefit
•Efficient use of available resources and infrastructure
•Awareness of cost benefit ratio before actual adoption
•Appropriate Decision making
•Encouraging for diversification
•Encouraging for quality production
Benefits to Private Agencies
*Creating scope for developing infrastructure
* Generating Rural Employment

63. Cost Benefit Page

64. Farmers viewing web site

65. Address
• http://www.iasri.res.in:8081/krishisamad
han/index.html
• IP No. of IARI=172.16.0.200
(Intranet)

66. OilseedPulse
Fruits
Vegetable
Flowers
Fodder
Fiber
Grain
Spices
Wood
Aromatic
Plant
Medicinal
Plant
commercial

68. Grains
1. Paddy
2. Wheat
3. Barley
4. Oat
5. Maize
6. Jowar
7. Bajra

69. Oilseeds
1. Mustard
2. Castor
3. Coconut
4. Groundnut
5. Linseed
6. Indian rape
7. Soybean
8. Sunflower

70. Vegetables
1. Tomato
2. Potato
3. Cauliflower
4. Cabbage
5. Onion
6. Spinach
7. Brinjal
8. Carrot
9. Radish
10.Cucumber
11. Beans
12. Cowpea

71. Fruits
1. Mango
2. Banana
3. Apple
4. Grapes
5. Pine apple
6. Papaya
7. Lemon
8. Peach
9. Pear
10. Cherry
11. Cashew
12. Guava

72. Pulses
1. Pea
2. Gram
3. Black gram
4. Bengal gram
5. Horse gram
6. Lentil
7. Pigeon pea
8. Chickling vetch
9. Cowpea
10. Kidney gram

73. Flowers
1. Gladiolus
2. Rose
3.Chrysenthemum
4. Marigold

74. Commercial
1. Mushroom
2. Rubber
3. Sugarcane
4. Tobacco
5. Coffee
6. Tea
7. Betel

75. Paddy
Back
-Better the plant population higher the yield.
-Longer the duration of crop more the yield.
-Using Gaze wheel for land preparation yields
more.
-Changing crop rotation controls weed and
enhances soil fertility.

76. Tomato
Back
Decision Rules
Plant population per acre should be 9600 to 9700 (9680).
-Suitable temperature ranging from 18-28 degree centigrade.
-The best soil is loam and sandy loam.
-350-400 gm seed sufficient for one hectare.
-The nursery beds should be 65-cm width.
-15 cm long seedlings should be transplanted.
-First crop should be grown in June-July and transplanted in July-August
-Second crop should be grown in November-December and transplanted in January-
February.

77. Gladiolus
Back
-Corms are most productive during first six years.
-Loam or Sandy loam soil best suits it.
-Fertility condition of soil to be assertained after soil testing.
-The time from planting to bloom varies from 70 to 90 or more days.
-Plant large bulbs 4 to 6 inch deep, medium 3 to 4 inch deep and small
bulbs 2 to 3 inch deep.
-Rows should be spaced from 20 to 36 inches apart.
-Corms may be spaced only 2 to 3 inches apart in the row.

78. Mushroom
Back
-Mushroom do not contain chlorophyll, therefore, depend upon other plant
material for their food.
-Picking is done by twisting the mushroom gently so that it is pulled out
without leaving any stub.
-Mushroom should be harvested when the cap begins to fold and has
attained a diameter of 8-10 cm.
-It is possible to get 800 gm to a kilogram per kg of the dry substrate.
-The packed bags are incubated in well-ventilated room where uniform
temperature of 25 degree centigrade is maintained.

79. Mango
Back
--Firm ripe mangoes that are just developing colour are picked and
ripened in straw.
-Ripen fruits are selected daily from the lot.
-The slices are placed in 2 per cent common salt solution to prevent their
enzymic browning.
-Plain cans should be used.

80. Mustard
Back
-Sowing is to be done within10-20 Oct. as pure crop
to control aphids.
-There is risk of Aphid attach if sown after 20 Oct.
-Thinning is one most required intercultural operation.
-Better the pant population higher the yield.
-Paleva before sowing enhances germination and yield.
-Mustard cultivation controls weeds in the field for the next crop.
-Requires less input and labour.
-It suits best in less irrigated water and labour areas.

81. Pea
Back
-Early varieties take 55-60 days.
-Mid-season varieties take 57-90 days.
-Late season varieties take 100-110 days.
-70-75 kg seed per hectare for late varieties.
-100kg seed per hectare early varieties