Data mining on climatic factors for Harumanis mango yield prediction

Rohani S. Mohamed Farook; Abdul Hallis Abdul Aziz; Azizi Harun; Zulkifli Husin; Ali Yeon Md Shakaff; Mahmad Nor Jaafar; D. L. Ndzi; Ammar Zakaria; Latifah Munirah Kamarudin

doi:10.1109/ISMS.2012.51

Data mining on climatic factors for Harumanis mango yield prediction

Rohani S. Mohamed Farook^*, Abdul Hallis Abdul Aziz, Azizi Harun, Zulkifli Husin, Ali Yeon Md Shakaff, Mahmad Nor Jaafar, D. L. Ndzi, Ammar Zakaria, Latifah Munirah Kamarudin

^*Corresponding author for this work

Faculty of Technology

Universiti Malaysia Perlis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Yield Prediction is an essential task to be achieved in order to implement effective forward marketing. Forward marketing is a contract that will be signed between supplier and client based on the amount of delivery and the price of delivery in future. To be able to sign such a contract the supplier should be very confident that the yield could be achieved. The yield sustainability is a challenging process in agriculture. Mango cultivar Harumanis is one of the best table tropical fruit due to its aroma and sweetness. Despite its overwhelming local demand in Malaysia and also internationally, the fruit supply never meets the demand. The flowering phase is identified as an important stage as plant reproductive physiology. Currently, Harumanis mango flowering only happens once a year that restricts the yield. In this paper, data mining is used to quantify the climatic effects on Harumanis mango yield to enable yield prediction.

Original language	English
Title of host publication	2012 Third International Conference on Intelligent Systems Modelling and Simulation
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	115-119
Number of pages	5
ISBN (Electronic)	9780769546681
ISBN (Print)	9781467308861
DOIs	https://doi.org/10.1109/ISMS.2012.51
Publication status	Published - 8 Feb 2012
Event	3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012 - Kota Kinabalu, Malaysia Duration: 8 Feb 2012 → 10 Feb 2012

Publication series

Name	Proceedings - 3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012
Publisher	IEEE
ISSN (Print)	2166-0662
ISSN (Electronic)	2166-0670

Conference

Conference	3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012
Country/Territory	Malaysia
City	Kota Kinabalu
Period	8/02/12 → 10/02/12

Keywords

data mining
Mango yield prediction model
regression
soft computing

Access to Document

10.1109/ISMS.2012.51

Cite this

Farook, R. S. M., Aziz, A. H. A., Harun, A., Husin, Z., Md Shakaff, A. Y., Jaafar, M. N., Ndzi, D. L., Zakaria, A., & Kamarudin, L. M. (2012). Data mining on climatic factors for Harumanis mango yield prediction. In 2012 Third International Conference on Intelligent Systems Modelling and Simulation (pp. 115-119). Article 6169685 (Proceedings - 3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISMS.2012.51

Farook, Rohani S. Mohamed ; Aziz, Abdul Hallis Abdul ; Harun, Azizi et al. / Data mining on climatic factors for Harumanis mango yield prediction. 2012 Third International Conference on Intelligent Systems Modelling and Simulation. Institute of Electrical and Electronics Engineers Inc., 2012. pp. 115-119 (Proceedings - 3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012).

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abstract = "Yield Prediction is an essential task to be achieved in order to implement effective forward marketing. Forward marketing is a contract that will be signed between supplier and client based on the amount of delivery and the price of delivery in future. To be able to sign such a contract the supplier should be very confident that the yield could be achieved. The yield sustainability is a challenging process in agriculture. Mango cultivar Harumanis is one of the best table tropical fruit due to its aroma and sweetness. Despite its overwhelming local demand in Malaysia and also internationally, the fruit supply never meets the demand. The flowering phase is identified as an important stage as plant reproductive physiology. Currently, Harumanis mango flowering only happens once a year that restricts the yield. In this paper, data mining is used to quantify the climatic effects on Harumanis mango yield to enable yield prediction.",

keywords = "data mining, Mango yield prediction model, regression, soft computing",

author = "Farook, {Rohani S. Mohamed} and Aziz, {Abdul Hallis Abdul} and Azizi Harun and Zulkifli Husin and {Md Shakaff}, {Ali Yeon} and Jaafar, {Mahmad Nor} and Ndzi, {D. L.} and Ammar Zakaria and Kamarudin, {Latifah Munirah}",

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Farook, RSM, Aziz, AHA, Harun, A, Husin, Z, Md Shakaff, AY, Jaafar, MN, Ndzi, DL, Zakaria, A & Kamarudin, LM 2012, Data mining on climatic factors for Harumanis mango yield prediction. in 2012 Third International Conference on Intelligent Systems Modelling and Simulation., 6169685, Proceedings - 3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012, Institute of Electrical and Electronics Engineers Inc., pp. 115-119, 3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012, Kota Kinabalu, Malaysia, 8/02/12. https://doi.org/10.1109/ISMS.2012.51

Data mining on climatic factors for Harumanis mango yield prediction. / Farook, Rohani S. Mohamed; Aziz, Abdul Hallis Abdul; Harun, Azizi et al.
2012 Third International Conference on Intelligent Systems Modelling and Simulation. Institute of Electrical and Electronics Engineers Inc., 2012. p. 115-119 6169685 (Proceedings - 3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Aziz, Abdul Hallis Abdul

AU - Harun, Azizi

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AU - Md Shakaff, Ali Yeon

AU - Jaafar, Mahmad Nor

AU - Ndzi, D. L.

AU - Zakaria, Ammar

AU - Kamarudin, Latifah Munirah

PY - 2012/2/8

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AB - Yield Prediction is an essential task to be achieved in order to implement effective forward marketing. Forward marketing is a contract that will be signed between supplier and client based on the amount of delivery and the price of delivery in future. To be able to sign such a contract the supplier should be very confident that the yield could be achieved. The yield sustainability is a challenging process in agriculture. Mango cultivar Harumanis is one of the best table tropical fruit due to its aroma and sweetness. Despite its overwhelming local demand in Malaysia and also internationally, the fruit supply never meets the demand. The flowering phase is identified as an important stage as plant reproductive physiology. Currently, Harumanis mango flowering only happens once a year that restricts the yield. In this paper, data mining is used to quantify the climatic effects on Harumanis mango yield to enable yield prediction.

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T3 - Proceedings - 3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012

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BT - 2012 Third International Conference on Intelligent Systems Modelling and Simulation

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012

Y2 - 8 February 2012 through 10 February 2012

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Farook RSM, Aziz AHA, Harun A, Husin Z, Md Shakaff AY, Jaafar MN et al. Data mining on climatic factors for Harumanis mango yield prediction. In 2012 Third International Conference on Intelligent Systems Modelling and Simulation. Institute of Electrical and Electronics Engineers Inc. 2012. p. 115-119. 6169685. (Proceedings - 3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012). doi: 10.1109/ISMS.2012.51