A Portable in-situ near-infrared LEDs-based soil nitrogen sensor using artificial neural network
Monitoring soil Nitrogen content for palm oil cultivation is paramount to produce high-quality palm oil. This study aims to investigate the feasibility of a proposed portable near-infrared (NIR) light emitting diodes (LEDs)-based soil Nitrogen sensor in predicting the soil Nitrogen content using ar...
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| Format: | Article |
| Language: | English |
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Penerbit UTHM
2018
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| Online Access: | http://umpir.ump.edu.my/id/eprint/29825/ http://umpir.ump.edu.my/id/eprint/29825/1/A%20portable%20in-situ%20near-infrared%20LEDs-based%20soil.pdf |
| _version_ | 1848823372632293376 |
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| author | Nur Aisyah Syafinaz, Suarin Chia, Kim Seng Siti Fatimah Zaharah, Mohd Fuzi |
| author_facet | Nur Aisyah Syafinaz, Suarin Chia, Kim Seng Siti Fatimah Zaharah, Mohd Fuzi |
| author_sort | Nur Aisyah Syafinaz, Suarin |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Monitoring soil Nitrogen content for palm oil cultivation is paramount to produce high-quality palm oil. This study aims to investigate the feasibility of a proposed portable near-infrared (NIR) light emitting diodes (LEDs)-based soil Nitrogen sensor in predicting the soil Nitrogen content using artificial neural network (ANN). First, soil samples that collected from a local oil palm plantation were scanned using the developed sensor and then followed by a conventional method, i.e. Kjeldahl analysis to measure the actual soil Nitrogen content. ANN was used for C hemometric analysis to develop a predictive model to in-situ predict the soil Nitrogen content using the near infrared light . The performance of ANN was validated using leave one out cross-validation. Results indicate that ANN with one hundred hidden neurons achieved the best accuracy with a root mean square error of cross-validation of 0.031%. This finding suggests that the proposed portable sensor coupled with ANN is promising to satisfactorily predict soil Nitrogen content. |
| first_indexed | 2025-11-15T02:56:05Z |
| format | Article |
| id | ump-29825 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:56:05Z |
| publishDate | 2018 |
| publisher | Penerbit UTHM |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-298252020-11-13T02:57:04Z http://umpir.ump.edu.my/id/eprint/29825/ A Portable in-situ near-infrared LEDs-based soil nitrogen sensor using artificial neural network Nur Aisyah Syafinaz, Suarin Chia, Kim Seng Siti Fatimah Zaharah, Mohd Fuzi QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering Monitoring soil Nitrogen content for palm oil cultivation is paramount to produce high-quality palm oil. This study aims to investigate the feasibility of a proposed portable near-infrared (NIR) light emitting diodes (LEDs)-based soil Nitrogen sensor in predicting the soil Nitrogen content using artificial neural network (ANN). First, soil samples that collected from a local oil palm plantation were scanned using the developed sensor and then followed by a conventional method, i.e. Kjeldahl analysis to measure the actual soil Nitrogen content. ANN was used for C hemometric analysis to develop a predictive model to in-situ predict the soil Nitrogen content using the near infrared light . The performance of ANN was validated using leave one out cross-validation. Results indicate that ANN with one hundred hidden neurons achieved the best accuracy with a root mean square error of cross-validation of 0.031%. This finding suggests that the proposed portable sensor coupled with ANN is promising to satisfactorily predict soil Nitrogen content. Penerbit UTHM 2018-09-03 Article PeerReviewed pdf en cc_by_nc_sa_4 http://umpir.ump.edu.my/id/eprint/29825/1/A%20portable%20in-situ%20near-infrared%20LEDs-based%20soil.pdf Nur Aisyah Syafinaz, Suarin and Chia, Kim Seng and Siti Fatimah Zaharah, Mohd Fuzi (2018) A Portable in-situ near-infrared LEDs-based soil nitrogen sensor using artificial neural network. International Journal of Integrated Engineering, 10 (4). pp. 81-87. ISSN 2229-838X (Print); 2600-7916 (Online). (Published) https://doi.org/10.30880/ijie.2018.10.04.013 https://doi.org/10.30880/ijie.2018.10.04.013 |
| spellingShingle | QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering Nur Aisyah Syafinaz, Suarin Chia, Kim Seng Siti Fatimah Zaharah, Mohd Fuzi A Portable in-situ near-infrared LEDs-based soil nitrogen sensor using artificial neural network |
| title | A Portable in-situ near-infrared LEDs-based soil nitrogen sensor using artificial neural network |
| title_full | A Portable in-situ near-infrared LEDs-based soil nitrogen sensor using artificial neural network |
| title_fullStr | A Portable in-situ near-infrared LEDs-based soil nitrogen sensor using artificial neural network |
| title_full_unstemmed | A Portable in-situ near-infrared LEDs-based soil nitrogen sensor using artificial neural network |
| title_short | A Portable in-situ near-infrared LEDs-based soil nitrogen sensor using artificial neural network |
| title_sort | portable in-situ near-infrared leds-based soil nitrogen sensor using artificial neural network |
| topic | QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/29825/ http://umpir.ump.edu.my/id/eprint/29825/ http://umpir.ump.edu.my/id/eprint/29825/ http://umpir.ump.edu.my/id/eprint/29825/1/A%20portable%20in-situ%20near-infrared%20LEDs-based%20soil.pdf |