Full Project – Expert system for the diagnosis of farm disease in cassava plant
The significant roles of artificial intelligence system in agricultural science domain cannot be relegated to the background, due to efficient techniques in Artificial Intelligence adopted by many system developers in building expert system for solving pest and disease affecting crops. The optimal advantage of expert systems is its capacity to minimize the amount of information that users need to process and thereby increase output with little personnel cost (Kaur, 2016).
The advancement in internet technology has contributed to the architectural system globally. Nowadays, both mobile technologies have framework for knowledge domain experts in various fields to build robust mobile and web-based expert systems for end-users to solve problems. Application of Expert System in the area of agriculture would take the form of Integrated Crop management, decision aids and would encompass irrigation, nutritional disorders and fertilization, weed control, cultivation and herbicidal application, insect control and pest control prototypes. Decision support systems (Expert system) for the identification of pest, disease and nutritional disorder management of crops, namely Banana, Cashew, Coconut, Rice, Pepper, with control measures have been developed successfully.
In farming, expert systems are found to be helpful for unprofessional farmers in the rural areas who need professional knowledge on how to diagnose crop diseases and control pests. Although, for effective use of expert system by farmers, there is a strong need for farmers to understand the abnormal symptoms observed on diseased crops in order to find appropriate expert system that could be used for diagnosis.
1.1 Background of the Study
Cassava is the third largest source of carbohydrates for human consumption worldwide, providing more food calories per cultivated acre than any other staple crop. It is an extremely robust plant which tolerates drought and low quality soil. The foremost cause of yield loss for this crop is viral disease (Otim, Thresh and Alicai, 2005). The plant grows in a bushy form, up to 2.4 meters high, with greenish-yellow flowers. The roots are up to 8 centimeters thick and 91 centimeters long. Two varieties of the cassava are of economic value: the bitter, or poisonous; and the sweet, or non-poisonous. Both varieties yield a wholesome food because the volatile poison can be destroyed by heat in the process of preparation.
Expert systems are intelligent computer programs designed to simulate the problem-solving behaviour of a human being who is an expert in a narrow domain or discipline. Knowledge-based expert systems, or simply expert systems, use human knowledge to solve problems that normally would require human intelligence. These expert systems represent the expertise knowledge as data or rules within the computer. Agricultural production has evolved into a complex business requiring the accumulation and integration of knowledge and information from many diverse sources. Unfortunately, agricultural specialist assistance is not always available when the farmer needs it. In order to alleviate this problem, expert systems were identified as a powerful tool with extensive potential in agriculture.
Cassava is the chief source of tapioca, and in South America a sauce and an intoxicating beverage are prepared from the juice. The root in powder form is used to prepare farinha, a meal used to make thin cakes sometimes called cassava bread. The starch of cassava yields a product called Brazilian arrowroot. In Florida, where sweet cassava is grown, the roots are eaten as food, fed to stock, or used in the manufacture of starch and glucose.
The economies of many developing countries are dominated by an agricultural sector in which small-scale and subsistence farmers are responsible for most production, utilizing relatively low levels of agricultural technology. As a result, disease among staple crops presents a serious risk, with the potential for devastating consequences. It is therefore critical to monitor the spread of crop disease, allowing targeted interventions and foreknowledge of famine risk.
1.2 Statement of the Problem
An expert system is a system that could keep knowledge in its knowledge base as the system knowledge resources and manipulate that knowledge, so it could prepare the high level decision tool to the user that is called inference engine as the brain of the system. On the other hand, expert system could help people in many cases in order to get decision in solving a problem. A number of cassava diseases are responsible for reducing the overall production of cassava to a great extent. A disease is an alteration of one or more ordered series of physiological processes as caused by irritation from some factors or agents resulting into loss of co-ordination in plants.
In Nigeria, there is a knowledge gap between the expert that know the diseases of cassava and the local farmer. As a result of this, the diseases have been killing the cassava plants being planted by the farmers. So this research is to bridge this knowledge gap by designing an expert system model to diagnose the disease of cassava. If this project is implemented, local farmer does not need to go to a human expert: all they need to do is to consult the expert system to solve his/her problem.
1.3 Aim and Objectives of the study
The aim of this work is to design an expert system for the diagnosis of farm disease in cassava plant.
The objectives of the study are:
- to develop an enhanced knowledge base decision support system to aid farmers in diagnosis of cassava disease.
- to implement the model with PHP and MySQL server by developing a robust system with friendly interface for users to capture relevant input parameters that will be processed by the system in order to generate output for users in making an appropriate decision on the basis of the given diseases affecting the crops.
- to give accurate treatment procedures for the different diseases of cassava.
- to efficiently guide the farmer in preventing/maintaining of his/her cassava plant from diseases.
1.4 Significance of the Study
Nowadays, the uses of expert systems are rapidly becoming a means of decision making not only in industries but also in agriculture. This research work will make contribution in terms of providing an expert system model that will be used to diagnose and treat diseases of cassava, which some of the local farmers are ignorant of. Furthermore, it will be adequately beneficial to stakeholders in agriculture and the government as it tends to be a better and effective method of dispensing diagnosis information of cassava plant diseases, hence increasing National GDP (Gross Domestic Product).
1.5 Scope of the Study
This work covers the development of a farm disease diagnosis system with particular reference to cassava plant. It does not tend to implement other plant-like features or description of the plant.
1.6 Definition of terms
- Model: A computer-based model is a computer program that is designed to simulate what might or what did happen in a situation.
- Diagnosis: The identification of the nature of an illness or other problem by examination of the symptoms.
- Disease: A disease is any condition which results in the disorder of a structure or function in a living organism that is not due to any external injury. The study of disease is called pathology, which includes the study of cause.
- Knowledge-base: A knowledge base is a technology used to store complex structured and unstructured information used by a computer system. The initial use of the term was in connection with expert systems which were the first knowledge-based systems
- Artificial intelligence: Artificial intelligence is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals.
- Interface: In computing, an interface is a shared boundary across which two or more separate components of computer system exchange information. The exchange can be between software, computer hardware, peripheral devices, humans and combinations of these.
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Full Project – Expert system for the diagnosis of farm disease in cassava plant