A Web Based Sweet Orange Crop Expert
System using Rule Based System and
Artificial Bee Colony Optimization
Algorithm
1.Prof.M.S.Prasad Babu 2. Mrs.J.Anitha 3.K.Hari Krishna
1. Professor, Department of CS & SE, Andhra University, Visakhapatnam, Andhra Pradesh, India. [email protected]
2. Asst.Professor, Dept. of IT, GITAM University, Visakhapatnam, Andhra Pradesh, India [email protected]
2. Asst.Professor, M.V.G.R.College of Engg., Visakhapatnam, Andhra Pradesh, India [email protected]
ABSTRACT
Citrus fruits have a prominent place among popular and exclusively grown tropical and sub-tropical fruits. Their nature ,multifold nutritional and medicinal values have made them so important. Sweet Orange Crop expert advisory system is aimed at a collaborative venture with eminent Agriculture Scientist and Experts in the area of Sweet Orange Plantation with an excellent team of computer Engineers, Programmers and designers. This Expert System contains two main parts one is Sweet Orange Information System and the other is Sweet Orange Crop Expert System where information system, the user can get all the static information about different species, Diseases, Symptoms, chemical controls, Preventions, Pests, Virus of Sweet Orange fruits and plants. In Advisory System , the user is having an interaction with the expert system online; the user has to answer the questions asked by the Expert System. Depends on the response by the user the expert system decides the disease and displays its control measure of disease. This Sweet Orange Crop Information Expert System deals with different varieties of Sweet Crop, Identification of various diseases generally occurs to Sweet Orange crop based on the symptoms.
KEYWORDS:
Expert Advisory System – Information System – Rule Based – ABC Algorithm-Optimization Algorithms – Web Based – JSP – SQL
1.Introduction
Expert systems are computer applications, which embody some non-algorithmic expertise for solving certain types of problems. For example, expert systems are used in diagnostic applications servicing both people and machinery. Machine learning is a set of tools that allow us to “teach” computers how to perform tasks by providing examples of how they should be done.
and viruses .Citrus fruits have a prominent place among popular and exclusively grown tropical and sub-tropical fruits. Their wholesome nature, multifold nutritional and medicinal values have made them so important. Citrus fruits possess greater adaptability to different climatic conditions successfully in tropical, subtropical and even in some favorable parts f the temperate regions of the world. They are available through out the yea ,not only delicious and refreshing to eat but also provide vitamins, minerals and many other essential elements which are required for human health. Sweet Orange is main source of vitamin ’C’ They are consumed as fresh and used in preparing delicious and refreshing drinks.
1.1 Origin and Spread
Himalayan region and South China are places of origin for most citrus fruits. In India citron is found under wild
conditions particularly in Niagara’s, Assam and lower Himalayas. Sweet Orange was introduced into India during
13th century from South-East Asian countries. Later Portuguese and Paris travelers took citrus to South America.
1.2 Soil
Citrus trees grow in almost any soil that is well-drained, sufficiently aerated and allows tap root to penetrate to the
desired depth. The Decline of Batavian orange plantations in Palacol area, the reduction in area under cultivation of
Vadlapudi orange in parts of Guntur, Krishna and Godavari districts. The hard pan restricts the root system and
creates stagnant moisture conditions within the root zone for prolonged periods, causing root rot and early decline of
trees.
1.3 Disease Management
Describe symptoms of each disease in sufficient detail to enable identification, indicate the casual organisms and their
mode of action and recommend remedial measures. Diseases caused by viruses are dreaded, since there is no cure.
The only way to avoid such diseases is to use virus-free(nuclear)certified saplings or budlings for planting. Some of
the diseases are
Algal Spot(Symptoms):
o Greyis-green, Velvety algal colonies 1 cm in diameter from on the trunk, limbs, branches and leaves.
o Thickening and cracking of the affected bark into small, irregular –shaped platelets or shreds is
common.
o In severe cases of infection, terminal growth of branches is restricted and the leaves become chlorotic
and drop off.
Black Mould Rot(or) Aspergillus Rot(Symptoms):
o This rot develops as a light –colored soft spot that can be punctured easily.
o It gradually turns pale yellow and orange in colour with the tissue becoming wrinkled.
o As the tot develops further, the decayed area sinks and mycelium and fruiting bodies of the fungus
appear.
2.Proposed System
1) Information System 2) Advisory System
In Information system, the user can get all the static information about different species, Diseases, Symptoms, chemical controls, Preventions, Pests, Virus of Sweet Orange fruits and plants. In Advisory System, the user is having an interaction with the expert system online; the user has to answer the questions asked by the Expert System. Depends on the response by the user the expert system decides the disease and displays its control measure of disease.
This web application is expected to have the following features:
1) This web application provides time-to-time updates of Sweet Orange information to the users at their doorsteps regarding diseases, virus and its control measure, which leads to good yields.
2) This site contains four major sections named Information Systems of Sweet Orange crop, Sweet Orange Advisory System, other services related to web application and an additional feature is links to other agriculture systems
3) The web directory service, articles and the discussion forum service provided in the website will help the Sweet Orange fraternity in a greater way to interact each other to produce better findings in the area of Sweet Orange field.
2.1 Functional Requirements for Sweet Orange Expert System:
2.1.1 Inputs – The system needs the information about the symptoms from the user to produce the output. 2.1.2 Outputs-
The outputs of the system will be: 1) Information Diseases
2) Small Description about the disease 3) Chemical controls
4) Preventions 2.1.3 Store-
The information collected through experts is stored as a database (Knowledge Base) that serves as a repository for quick processing and future retrieval. The system stores the information in html files.
1) About Sweet Orange system 2) About Sweet Orange Varieties 3) Climate and Soil
4) Nutrients
The System Stores the information related to expert design in knowledge base in the following ways.
2.1.4 Rules: A set of rules, which constitute the program, stored in a rule memory of production memory and on an inference engine required to execute the rules.
2.1.5 Dataset: The monitoring data is in Sweet Orange Crop Advisory System the MySQL database. It can be used
as any other data stored in a database. This greatly increases the opportunity with which you can conduct post-analysis of the monitoring data.
3. MACHINE LEARNING ARCHITECTURE OF SWEET ORANGE CROP ADVISORY EXPERT SYSTEM
Fig: SWEET ORANGE CROP ADVISORY EXPERT SYSTEM 3.1 Rule Based System –I
Fig :Architecture of SubSystem-1(RULE Based System)
3.2 Rule Based Algorithm
:
Repeat
Collect the rules whose conditions match facts in working Memory. If more than one rule matches
o Use Conflict resolution strategy to eliminate all but one.
o Do Actions indicated by the rules( add facts to WM or delete facts from WM) Until problem is solved or no condition match.
If the system 1 (Rule Based System) unable to produce the exact disease then the system 2 (Optimization Algorithm) explained below starts performing its work.
3.3 Optimization Algorithm (System –II)
Artificial Bee Colony Algorithm (ABC) is an optimization algorithm based on the intelligent foraging behavior of
Fig.Architecture of SubSystem -2(ABC Algorithm)
Detailed Pseudo code of the ABC Algorithm 1.Initilaize the population of solutions xi,j
2.Evaluate the population 3.Cycle=1
4.Repeat
5.Produce new solutions (food Source positions) Õi,j= xi,j +Öij(xi,j-xk,j) ( K is a solution in the neighborhood of i, Ö is a
random number in the range [-1,1]) and evaluate them . 6.Apply the greedy selection process between xi and Õi..
7.Calculate the probability values Pi for the solutions xi by means of their fitness values using the equation (1).
8.Produce the new solutions ( new Positions ) Õi..for the onlookers from the solutions xi. selected depending on Pi
and evaluate them.
10.Determine the abandoned solution (source),if exists, and replace it with a new randomly produced solution xi.
for the scout using the equation (3) xi,=minj+rand(0,1) * (maxj-minj) (3)
11.Memorize the best food source position (solution) achieved so far 12.cycle=cycle+1
13.until cycle =Maxi
3.3.1 Cure Database Table
id Disease S1 S2 S3 S4 S5 S6 S7 S8 S9
1 Algal Spot 1 1 0 0 0 0 0 0 0
2 Alternaria Rot 0 1 0 0 0 0 0 0 0
3 Anthracnose Rot 0 0 1 0 0 0 0 0 0
4 Black Mould Rot 0 0 0 1 0 0 0 0 0
5 Bacterial Canker 0 0 0 0 1 0 0 0 0
6 Bark eruption 0 0 0 0 0 0 0 0 1
0 indicates that the symptom is not present for that particular disease and 1 indicates that the symptom will present for that particular disease.
3.3.2 Symptoms Database table:
Id Disease_id cure
1. Algol Spot Spraying 0.3% copper oxychloride(3 g of copper oxychloride/litre of water) at monthly intervals during every rainy season contains the disease.
2. Alternaria Rot Sandovit or Teepol should be mixed with the spray fluid 10 ml. per litre. 3. Anthracnose Rot Spraying 0.3 percent malathion. Apply recommended doses of
Nitrogenous fertilizers.
4.Results & Discussions:
Fig: Sweet Orange Expert System
Fig:Sweet Orange Expert Advisory System
5.Future Work
In this SWEET ORANGE Expert System two algorithms are implemented, which are 1) RULE Based Algorithm
2) ABC Algorithm
The 2 algorithms were to identify the Diseases and Viruses of the orange plants and the future enhancement will be in such a way using training data from the farmers collect from overall India, to check whether the disease is correct or not from the all subset of diseases.
6.Conclusion
This is a web-enabled application developed using java server pages (jsp) and MySql database is used as backend. So as to ensure the quality of the software, all software engineering concepts, including test cases are implemented. Its main emphasis is to have a well designed interface for giving Horticulture related advices and suggestions in the area of Sweet Orange crop field by providing facilities like dynamic interaction between expert system and the user without the need of expert (Sweet crop) at all times. By the thorough interaction with the users and beneficiaries the functionality of the System can be extended further to many more areas in and around the world.
7.References
[1] TIMOTHY C. LETHBRIDGE ROBERT LAGANIERE: Object-Oriented Software Engineering, TMH Publications [2] BERND BRUEGGE ALLEN H. DUTOIT: Object-Oriented Software Engineering, PEARSON Education
[3] ANN NAVARRO TODD STAUFFER: HTML by Example, PHI Publications
[4] ROGER S. PRESSMAN: Software Engineering - A practitioners Approach, Mc Graw Hill [5] TIMOTHY BRIGGS, SAMEER TYAGI: Professional JSP - Wrox Press, Shroff Publishers [6] C.J. DATE: An Introduction to Database Systems
[7] Sweet Orange crop Manual books, Published by Acharya. N.G.Ranga Agricultural University [8] www.aphorticulture.com
