Machine learning model for nutrient release from biopolymers coated controlled-release fertilizer

Recent developments in the controlled-release fertilizer (CRF) have led to the new modern agriculture industry, also known as precision farming. Biopolymers as encapsulating agents for the production of controlled-release fertilizers have helped to overcome many challenging problems such as nutrient...

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Main Authors: Irfan, S.A., Azeem, B., Irshad, K., Algarni, S., Kushaari, K., Islam, S., Abdelmohimen, M.A.H.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.29795 /
Published: MDPI AG 2020
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095985856&doi=10.3390%2fagriculture10110538&partnerID=40&md5=74064f191e90339f824ffd617826905d
http://eprints.utp.edu.my/29795/
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spelling utp-eprints.297952022-03-25T02:56:30Z Machine learning model for nutrient release from biopolymers coated controlled-release fertilizer Irfan, S.A. Azeem, B. Irshad, K. Algarni, S. Kushaari, K. Islam, S. Abdelmohimen, M.A.H. Recent developments in the controlled-release fertilizer (CRF) have led to the new modern agriculture industry, also known as precision farming. Biopolymers as encapsulating agents for the production of controlled-release fertilizers have helped to overcome many challenging problems such as nutrients� leaching, soil degradation, soil debris, and hefty production cost. Mechanistic modeling of biopolymers coated CRF makes it challenging due to the complicated phenomenon of biodegradation. In this study, a machine learning model is developed utilizing Gaussian process regression to predict the nutrient release time from biopolymer coated CRF with the input parameters consisting of diffusion coefficient, coefficient of-variance of coating thickness, coating mass thickness, coefficient of variance of size distribution and surface hardness from biopolymer coated controlled-release fertilizer. The developed model has shown greater prediction capabilities measured with R2 equalling 1 and a Root Mean Square Error (RMSE) equalling 0.003. The developed model can be utilized to study the nutrient release profile of different biopolymers�-coated controlled-release fertilizers. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. MDPI AG 2020 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095985856&doi=10.3390%2fagriculture10110538&partnerID=40&md5=74064f191e90339f824ffd617826905d Irfan, S.A. and Azeem, B. and Irshad, K. and Algarni, S. and Kushaari, K. and Islam, S. and Abdelmohimen, M.A.H. (2020) Machine learning model for nutrient release from biopolymers coated controlled-release fertilizer. Agriculture (Switzerland), 10 (11). pp. 1-13. http://eprints.utp.edu.my/29795/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Recent developments in the controlled-release fertilizer (CRF) have led to the new modern agriculture industry, also known as precision farming. Biopolymers as encapsulating agents for the production of controlled-release fertilizers have helped to overcome many challenging problems such as nutrients� leaching, soil degradation, soil debris, and hefty production cost. Mechanistic modeling of biopolymers coated CRF makes it challenging due to the complicated phenomenon of biodegradation. In this study, a machine learning model is developed utilizing Gaussian process regression to predict the nutrient release time from biopolymer coated CRF with the input parameters consisting of diffusion coefficient, coefficient of-variance of coating thickness, coating mass thickness, coefficient of variance of size distribution and surface hardness from biopolymer coated controlled-release fertilizer. The developed model has shown greater prediction capabilities measured with R2 equalling 1 and a Root Mean Square Error (RMSE) equalling 0.003. The developed model can be utilized to study the nutrient release profile of different biopolymers�-coated controlled-release fertilizers. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
format Article
author Irfan, S.A.
Azeem, B.
Irshad, K.
Algarni, S.
Kushaari, K.
Islam, S.
Abdelmohimen, M.A.H.
spellingShingle Irfan, S.A.
Azeem, B.
Irshad, K.
Algarni, S.
Kushaari, K.
Islam, S.
Abdelmohimen, M.A.H.
Machine learning model for nutrient release from biopolymers coated controlled-release fertilizer
author_sort Irfan, S.A.
title Machine learning model for nutrient release from biopolymers coated controlled-release fertilizer
title_short Machine learning model for nutrient release from biopolymers coated controlled-release fertilizer
title_full Machine learning model for nutrient release from biopolymers coated controlled-release fertilizer
title_fullStr Machine learning model for nutrient release from biopolymers coated controlled-release fertilizer
title_full_unstemmed Machine learning model for nutrient release from biopolymers coated controlled-release fertilizer
title_sort machine learning model for nutrient release from biopolymers coated controlled-release fertilizer
publisher MDPI AG
publishDate 2020
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095985856&doi=10.3390%2fagriculture10110538&partnerID=40&md5=74064f191e90339f824ffd617826905d
http://eprints.utp.edu.my/29795/
_version_ 1741197300763459584
score 11.62408

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