A Predictive Fuzzy Expert System for Diagnosis of Cassava Plant Diseases

Awoyelu, I.O.; Adebisi, R.O.

A Predictive Fuzzy Expert System for Diagnosis of Cassava Plant Diseases

Awoyelu, I.O. * §

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Adebisi, R.O. §

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§ Obafemi Awolowo Unversity

A Predictive Fuzzy Expert System for Diagnosis of Cassava Plant Diseases

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Abstract

Cassava is an important tropical root cropwidely grown in many part of the world in a range of agro-ecological environments. The crop can be used for food and non-foods products. Cassava is capable of providing starch for use in drug industries, it is a stable source of dietary energy for more than 500 million. Nonetheless, despite the nutritional and economic significance of the cassava crop, the diseases incidence on cassava plantations is fast becoming a constraint in farmers’ quest for a bountiful harvest. The efforts of agricultural extension agents seem not to be sufficient in tackling this menace since there is always a limit to how far the human capacity can be stretched in the face of highly demanding situations. Hence, this paper proposed the development of fuzzy expert system for predicting cassava plant disease. The system was developed with the help of fuzzy tool in MATLAB vs. 9. It employed 18 rules for the Cassava Mosaic, 27 rules for the cassava brown streak and 27 rules for cassava bacteria blightfor the classification and prediction of cassava plant diseases. This would provide immediate and instant information to the possible disease.

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18 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Awoyelu, I.O., Adebisi, R.O.. 2015. "A Predictive Fuzzy Expert System for Diagnosis of Cassava Plant Diseases". Global Journal of Science Frontier Research - C: Biological Science GJSFR-C Volume 15 (GJSFR Volume 15 Issue C5).

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GJSFR Volume 15 Issue C5

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Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

Keywords

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Classification

GJSFR-C Classification FOR Code: 069999

Submission ReceivedAugust 1, 2015
Peer Review Double Blind
Handling Editor
Accepted August 24, 2015
Published September 5, 2015

Version of record

v1.2

Issue date

August 21, 2015

Language

English

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Article Matrices

Total Score: 104

Country: Nigeria

Subject: Global Journal of Science Frontier Research - C: Biological Science

Authors: Awoyelu, I.O., Adebisi, R.O. (PhD/Dr. count: 0)

View Count (all-time): 357

Total Views (Real + Logic): 1389

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Publish Date: 2015 09, Sat

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