A Predictive Fuzzy Expert System for Diagnosis of Cassava Plant Diseases

A Predictive Fuzzy Expert System for Diagnosis of Cassava Plant Diseases

Awoyelu, I.O.

Contact

Awoyelu

Contact

I.O.

Contact

Adebisi

Contact

R.O.

Contact

Obafemi Awolowo University

A Predictive Fuzzy Expert System for Diagnosis of Cassava Plant Diseases

Article Fingerprint

ReserarchID

B2DUN

A Predictive Fuzzy Expert System for Diagnosis of Cassava Plant Diseases Banner

AI TAKEAWAY

Connecting with the Eternal Ground

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.

References

18 Cites in Article

Reference Format

N Otim,T Alicai,J Thresh (2005). Changes in the Incidence and Severity of Cassava Mosaic Virus Disease, Varietal Diversity and Cassava Production in Uganda.
S Khan,S Razzaq,K Irfan,F Maqbool,Farid,I Illahi,Tauqeerulamin (2008). A Web-based Expert System for Diagnosis of Diseases and Pests in Pakistani Wheat.
Puja Shrivastava,Susanta Satpathy,Kapil Nagwanshi (2010). Development of an Expert System as Spiritual Guru.
Rajkishore Prasad,Kumar Ranjan,A Sinha (2006). AMRAPALIKA: An expert system for the diagnosis of pests, diseases, and disorders in Indian mango.
S Saini,R Kamal,A Sharma (2002). Web Based Fuzzy Expert System for Integrated Pest Management in Soybean.
El-Sayed El-Azhary,Hesham Hassan,A Rafea (2000). Pest Control Expert System for Tomato (PCEST).
D Li,Z Fu,Y Duan (2002). Fish-expert: A Web-Based Expert System for Fish Disease Diagnosis.
John Quinn,Kevin Leyton-Brown,Ernest Mwebaze (2011). Modeling and Monitoring Crop Disease in Developing Countries.
Patricia Muñoz-Escalona,Paul Maropoulos (2009). Artificial Neural Networks for Surface Roughness Prediction when Face Milling Al 7075-T7351.
L Zhanjie,Y Bing,T Meili (2007). Prediction of Surface Roughness of Diffi cult-to-Cut Material by HSM Based on RBF Neural Network.
Chen Lu,Jean Costes (2008). Surface profile prediction and analysis applied to turning process.
Christian Brecher,Guillem Quintana,Thomas Rudolf,Joaquim Ciurana (2011). Use of NC kernel data for surface roughness monitoring in milling operations.
S Hossain,N Ahmad (2012). Adaptive Neuro-fuzzy Inference System (ANFIS) Based Surface Roughness Prediction Model for Ball end Milling Operation.
G Aderounmu,E Omidiora,B Adegoke,T Taiwo (2013). Neuro-fuzzy System for Livestock Feed Formulation (Africa Poultry).
P Benardos,G-C Vosniakos (2003). Predicting surface roughness in machining: a review.
R Rai,A Kumar,S Rao,S Shriram (2010). Development of a Surface Roughness Prediction System for Machining of Hot Chromium Steel (Aisi H11) Based on Artificial Neural Network.
C Bruni,L Apolito,A Forcellese,F Gabrielli,M Simoncini (2008). Surface Roughness Modeling in Finish Face Milling Under MQL and Dry Cutting Conditions.
M Yazdi,A Khorram (2010). Modeling and Optimization of Milling Process by Using RSM and ANN Methods.

Download References

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.. 2015. \u201cA Predictive Fuzzy Expert System for Diagnosis of Cassava Plant Diseases\u201d. Global Journal of Science Frontier Research - C: Biological Science GJSFR-C Volume 15 (GJSFR Volume 15 Issue C5).

More Citation Formats

Select Citation Style:

Download Citation

GJSFR Volume 15 Issue C5

Explore Journals Explore Volume Read This Issue

Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

Keywords

Not Found

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

Experiance in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

View in VR

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

View in 3D

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): 154

Total Views (Real + Logic): 4005

Total Downloads (simulated): 2018

Publish Date: 2015 08, Fri

Monthly Totals (Real + Logic):

Month 1: 56 views
Month 2: 51 views
Month 3: 27 views
Month 4: 55 views
Month 5: 32 views
Month 6: 33 views
Month 7: 32 views
Month 8: 47 views
Month 9: 51 views
Month 10: 36 views
Month 11: 46 views
Month 12: 11 views
Month 13: 15 views
Month 14: 37 views
Month 15: 19 views
Month 16: 23 views
Month 17: 25 views
Month 18: 29 views
Month 19: 33 views
Month 20: 46 views
Month 21: 49 views
Month 22: 29 views
Month 23: 40 views
Month 24: 16 views
Month 25: 29 views
Month 26: 15 views
Month 27: 20 views
Month 28: 30 views
Month 29: 32 views
Month 30: 22 views
Month 31: 23 views
Month 32: 39 views
Month 33: 23 views
Month 34: 24 views
Month 35: 27 views
Month 36: 30 views
Month 37: 17 views
Month 38: 23 views
Month 39: 35 views
Month 40: 28 views
Month 41: 37 views
Month 42: 31 views
Month 43: 35 views
Month 44: 29 views
Month 45: 25 views
Month 46: 18 views
Month 47: 27 views
Month 48: 32 views
Month 49: 25 views
Month 50: 35 views
Month 51: 21 views
Month 52: 32 views
Month 53: 21 views
Month 54: 46 views
Month 55: 40 views
Month 56: 21 views
Month 57: 33 views
Month 58: 40 views
Month 59: 39 views
Month 60: 19 views
Month 61: 37 views
Month 62: 12 views
Month 63: 22 views
Month 64: 19 views
Month 65: 33 views
Month 66: 21 views
Month 67: 32 views
Month 68: 29 views
Month 69: 25 views
Month 70: 35 views
Month 71: 19 views
Month 72: 19 views
Month 73: 32 views
Month 74: 39 views
Month 75: 24 views
Month 76: 13 views
Month 77: 39 views
Month 78: 16 views
Month 79: 29 views
Month 80: 41 views
Month 81: 45 views
Month 82: 47 views
Month 83: 30 views
Month 84: 28 views
Month 85: 22 views
Month 86: 32 views
Month 87: 45 views
Month 88: 23 views
Month 89: 35 views
Month 90: 32 views
Month 91: 24 views
Month 92: 26 views
Month 93: 33 views
Month 94: 31 views
Month 95: 29 views
Month 96: 22 views
Month 97: 36 views
Month 98: 20 views
Month 99: 37 views
Month 100: 37 views
Month 101: 46 views
Month 102: 28 views
Month 103: 47 views
Month 104: 16 views
Month 105: 29 views
Month 106: 24 views
Month 107: 28 views
Month 108: 23 views
Month 109: 39 views
Month 110: 40 views
Month 111: 13 views
Month 112: 22 views
Month 113: 39 views
Month 114: 37 views
Month 115: 24 views
Month 116: 38 views
Month 117: 32 views
Month 118: 41 views
Month 119: 25 views
Month 120: 29 views
Month 121: 23 views
Month 122: 25 views
Month 123: 16 views
Month 124: 28 views
Month 125: 31 views
Month 126: 28 views
Month 127: 35 views
Month 128: 31 views
Month 129: 32 views

Total Views: 4005

Total Downloads: 2018

2026 Trends

Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]