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Empirical based irrigation model using predicted soil moisture for durian plantation

It is vital to the agricultural activities to have sufficient water supply for its operation and maintenance mainly for cultivation to keep it in good condition Therefore, it is important to determine the soil moisture levels existing while designing a precise irrigation system. Installing soil mois...

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Main Authors:	Ramli, Muhammad Shahrul Azwan, Zainal Abidin, Mohamad Shukri, Pui, Boon Hean, Abd. Rahman, Mohd. Amiruddin, Perumal, Thinagaran, Md. Reba, Mohd. Nadzri
Format:	Book Section
Published:	Springer Science and Business Media Deutschland GmbH 2022
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/100730/ http://dx.doi.org/10.1007/978-981-19-3923-5_23
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id	my.utm.100730
record_format	eprints
spelling	my.utm.1007302023-04-30T10:20:59Z http://eprints.utm.my/id/eprint/100730/ Empirical based irrigation model using predicted soil moisture for durian plantation Ramli, Muhammad Shahrul Azwan Zainal Abidin, Mohamad Shukri Pui, Boon Hean Abd. Rahman, Mohd. Amiruddin Perumal, Thinagaran Md. Reba, Mohd. Nadzri TK Electrical engineering. Electronics Nuclear engineering It is vital to the agricultural activities to have sufficient water supply for its operation and maintenance mainly for cultivation to keep it in good condition Therefore, it is important to determine the soil moisture levels existing while designing a precise irrigation system. Installing soil moisture sensors in each tree is complicated or excessively expensive. Forecasting the value using climate data is a viable solution in this scenario. Climate data are used to forecast soil moisture and then utilized in this irrigation model. This study uses an Artificial Neural Network (ANN) to forecast soil moisture values. The statistical method is used to determine the predicted values’ correctness. After the process, the irrigation volume and schedule are calculated based on the most accurate prediction findings. Springer Science and Business Media Deutschland GmbH 2022 Book Section PeerReviewed Ramli, Muhammad Shahrul Azwan and Zainal Abidin, Mohamad Shukri and Pui, Boon Hean and Abd. Rahman, Mohd. Amiruddin and Perumal, Thinagaran and Md. Reba, Mohd. Nadzri (2022) Empirical based irrigation model using predicted soil moisture for durian plantation. In: Control, Instrumentation and Mechatronics: Theory and Practice. Lecture Notes in Electrical Engineering, 921 (NA). Springer Science and Business Media Deutschland GmbH, Singapore, pp. 261-272. ISBN 978-981193922-8 http://dx.doi.org/10.1007/978-981-19-3923-5_23 DOI:10.1007/978-981-19-3923-5_23
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Ramli, Muhammad Shahrul Azwan Zainal Abidin, Mohamad Shukri Pui, Boon Hean Abd. Rahman, Mohd. Amiruddin Perumal, Thinagaran Md. Reba, Mohd. Nadzri Empirical based irrigation model using predicted soil moisture for durian plantation
description	It is vital to the agricultural activities to have sufficient water supply for its operation and maintenance mainly for cultivation to keep it in good condition Therefore, it is important to determine the soil moisture levels existing while designing a precise irrigation system. Installing soil moisture sensors in each tree is complicated or excessively expensive. Forecasting the value using climate data is a viable solution in this scenario. Climate data are used to forecast soil moisture and then utilized in this irrigation model. This study uses an Artificial Neural Network (ANN) to forecast soil moisture values. The statistical method is used to determine the predicted values’ correctness. After the process, the irrigation volume and schedule are calculated based on the most accurate prediction findings.
format	Book Section
author	Ramli, Muhammad Shahrul Azwan Zainal Abidin, Mohamad Shukri Pui, Boon Hean Abd. Rahman, Mohd. Amiruddin Perumal, Thinagaran Md. Reba, Mohd. Nadzri
author_facet	Ramli, Muhammad Shahrul Azwan Zainal Abidin, Mohamad Shukri Pui, Boon Hean Abd. Rahman, Mohd. Amiruddin Perumal, Thinagaran Md. Reba, Mohd. Nadzri
author_sort	Ramli, Muhammad Shahrul Azwan
title	Empirical based irrigation model using predicted soil moisture for durian plantation
title_short	Empirical based irrigation model using predicted soil moisture for durian plantation
title_full	Empirical based irrigation model using predicted soil moisture for durian plantation
title_fullStr	Empirical based irrigation model using predicted soil moisture for durian plantation
title_full_unstemmed	Empirical based irrigation model using predicted soil moisture for durian plantation
title_sort	empirical based irrigation model using predicted soil moisture for durian plantation
publisher	Springer Science and Business Media Deutschland GmbH
publishDate	2022
url	http://eprints.utm.my/id/eprint/100730/ http://dx.doi.org/10.1007/978-981-19-3923-5_23
_version_	1765296695019569152
score	13.211869

Empirical based irrigation model using predicted soil moisture for durian plantation

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