Classification of oil palm fresh fruit maturity based on carotene content from Raman spectra

Abstract The oil yield, measured in oil extraction rate per hectare in the palm oil industry, is directly affected by the ripening levels of the oil palm fresh fruit bunches at the point of harvesting. A rapid, non-invasive and reliable method in assessing the maturity level of oil palm harvests wil...

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Autores principales:	Thinal Raj, Fazida Hanim Hashim, Aqilah Baseri Huddin, Aini Hussain, Mohd Faisal Ibrahim, Peer Mohamed Abdul
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ac6d2f9ce6dc405a8b3cd611c632b415
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spelling	oai:doaj.org-article:ac6d2f9ce6dc405a8b3cd611c632b4152021-12-02T18:02:22ZClassification of oil palm fresh fruit maturity based on carotene content from Raman spectra10.1038/s41598-021-97857-52045-2322https://doaj.org/article/ac6d2f9ce6dc405a8b3cd611c632b4152021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-97857-5https://doaj.org/toc/2045-2322Abstract The oil yield, measured in oil extraction rate per hectare in the palm oil industry, is directly affected by the ripening levels of the oil palm fresh fruit bunches at the point of harvesting. A rapid, non-invasive and reliable method in assessing the maturity level of oil palm harvests will enable harvesting at an optimum time to increase oil yield. This study shows the potential of using Raman spectroscopy to assess the ripeness level of oil palm fruitlets. By characterizing the carotene components as useful ripeness features, an automated ripeness classification model has been created using machine learning. A total of 46 oil palm fruit spectra consisting of 3 ripeness categories; under ripe, ripe, and over ripe, were analyzed in this work. The extracted features were tested with 19 classification techniques to classify the oil palm fruits into the three ripeness categories. The Raman peak averaging at 1515 cm−1 is shown to be a significant molecular fingerprint for carotene levels, which can serve as a ripeness indicator in oil palm fruits. Further signal analysis on the Raman peak reveals 4 significant sub bands found to be lycopene (ν1a), β-carotene (ν1b), lutein (ν1c) and neoxanthin (ν1d) which originate from the C=C stretching vibration of carotenoid molecules found in the peel of the oil palm fruit. The fine KNN classifier is found to provide the highest overall accuracy of 100%. The classifier employs 6 features: peak intensities of bands ν1a to ν1d and peak positions of bands ν1c and ν1d as predictors. In conclusion, the Raman spectroscopy method has the potential to provide an accurate and effective way in determining the ripeness of oil palm fresh fruits.Thinal RajFazida Hanim HashimAqilah Baseri HuddinAini HussainMohd Faisal IbrahimPeer Mohamed AbdulNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Thinal Raj Fazida Hanim Hashim Aqilah Baseri Huddin Aini Hussain Mohd Faisal Ibrahim Peer Mohamed Abdul Classification of oil palm fresh fruit maturity based on carotene content from Raman spectra
description	Abstract The oil yield, measured in oil extraction rate per hectare in the palm oil industry, is directly affected by the ripening levels of the oil palm fresh fruit bunches at the point of harvesting. A rapid, non-invasive and reliable method in assessing the maturity level of oil palm harvests will enable harvesting at an optimum time to increase oil yield. This study shows the potential of using Raman spectroscopy to assess the ripeness level of oil palm fruitlets. By characterizing the carotene components as useful ripeness features, an automated ripeness classification model has been created using machine learning. A total of 46 oil palm fruit spectra consisting of 3 ripeness categories; under ripe, ripe, and over ripe, were analyzed in this work. The extracted features were tested with 19 classification techniques to classify the oil palm fruits into the three ripeness categories. The Raman peak averaging at 1515 cm−1 is shown to be a significant molecular fingerprint for carotene levels, which can serve as a ripeness indicator in oil palm fruits. Further signal analysis on the Raman peak reveals 4 significant sub bands found to be lycopene (ν1a), β-carotene (ν1b), lutein (ν1c) and neoxanthin (ν1d) which originate from the C=C stretching vibration of carotenoid molecules found in the peel of the oil palm fruit. The fine KNN classifier is found to provide the highest overall accuracy of 100%. The classifier employs 6 features: peak intensities of bands ν1a to ν1d and peak positions of bands ν1c and ν1d as predictors. In conclusion, the Raman spectroscopy method has the potential to provide an accurate and effective way in determining the ripeness of oil palm fresh fruits.
format	article
author	Thinal Raj Fazida Hanim Hashim Aqilah Baseri Huddin Aini Hussain Mohd Faisal Ibrahim Peer Mohamed Abdul
author_facet	Thinal Raj Fazida Hanim Hashim Aqilah Baseri Huddin Aini Hussain Mohd Faisal Ibrahim Peer Mohamed Abdul
author_sort	Thinal Raj
title	Classification of oil palm fresh fruit maturity based on carotene content from Raman spectra
title_short	Classification of oil palm fresh fruit maturity based on carotene content from Raman spectra
title_full	Classification of oil palm fresh fruit maturity based on carotene content from Raman spectra
title_fullStr	Classification of oil palm fresh fruit maturity based on carotene content from Raman spectra
title_full_unstemmed	Classification of oil palm fresh fruit maturity based on carotene content from Raman spectra
title_sort	classification of oil palm fresh fruit maturity based on carotene content from raman spectra
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/ac6d2f9ce6dc405a8b3cd611c632b415
work_keys_str_mv	AT thinalraj classificationofoilpalmfreshfruitmaturitybasedoncarotenecontentfromramanspectra AT fazidahanimhashim classificationofoilpalmfreshfruitmaturitybasedoncarotenecontentfromramanspectra AT aqilahbaserihuddin classificationofoilpalmfreshfruitmaturitybasedoncarotenecontentfromramanspectra AT ainihussain classificationofoilpalmfreshfruitmaturitybasedoncarotenecontentfromramanspectra AT mohdfaisalibrahim classificationofoilpalmfreshfruitmaturitybasedoncarotenecontentfromramanspectra AT peermohamedabdul classificationofoilpalmfreshfruitmaturitybasedoncarotenecontentfromramanspectra
_version_	1718378948000219136

Classification of oil palm fresh fruit maturity based on carotene content from Raman spectra

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