Non-invasive measurement of shear force in chicken meat using near infrared spectroscopy supported by neural network analysis.
The aim of the present work was to evaluate the ability of a portable near-infrared (NIR) spectroscopy integrated with machine learning methods to predict the shear force in chicken meat. Considering the benefits of dimension reduction from Principal Component Regression (PCR) and the ability to han...
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Malaysian Society for Computed Tomography & Imaging Technology (MyCT)
2022
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my.utm.1042632024-01-22T08:38:44Z http://eprints.utm.my/104263/ Non-invasive measurement of shear force in chicken meat using near infrared spectroscopy supported by neural network analysis. Abdul Rahim, Herlina Zulkifli, Syahidah Nurani Ghazali, Rashidah Abd. Rahim, Intan Maisarah T Technology (General) TK Electrical engineering. Electronics Nuclear engineering The aim of the present work was to evaluate the ability of a portable near-infrared (NIR) spectroscopy integrated with machine learning methods to predict the shear force in chicken meat. Considering the benefits of dimension reduction from Principal Component Regression (PCR) and the ability to handle non-linearity from Artificial Neural Network (ANN), these two algorithms were combined. Through the augmentation, the Principal Component Neural Network (PCNN) is developed. The results show that PCNN successfully surpassed the respective versions of PCR and ANN with higher shear force prediction performances. The PCNN proved to achieve the best prediction in breast meat with root mean square error of prediction (RMSEP) of 0.0815 kg and coefficient of determination, (Rp2) of 0.7977. NIRS technology integrated with machine learning yield a promising non-invasive technique in predicting the shear force of intact raw chicken meat. Malaysian Society for Computed Tomography & Imaging Technology (MyCT) 2022-12-29 Article PeerReviewed application/pdf en http://eprints.utm.my/104263/1/RashidahGhazaliHerlinaAbdulRahimSyahidahNuraniZulkifli2022_NonInvasiveMeasurementofShearForce.pdf Abdul Rahim, Herlina and Zulkifli, Syahidah Nurani and Ghazali, Rashidah and Abd. Rahim, Intan Maisarah (2022) Non-invasive measurement of shear force in chicken meat using near infrared spectroscopy supported by neural network analysis. Journal Of Tomography System & Sensors Application, 5 (2). pp. 24-31. ISSN 2636-9133 https://tssa.my/index.php/jtssa/article/view/202/90 NA |
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T Technology (General) TK Electrical engineering. Electronics Nuclear engineering Abdul Rahim, Herlina Zulkifli, Syahidah Nurani Ghazali, Rashidah Abd. Rahim, Intan Maisarah Non-invasive measurement of shear force in chicken meat using near infrared spectroscopy supported by neural network analysis. |
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The aim of the present work was to evaluate the ability of a portable near-infrared (NIR) spectroscopy integrated with machine learning methods to predict the shear force in chicken meat. Considering the benefits of dimension reduction from Principal Component Regression (PCR) and the ability to handle non-linearity from Artificial Neural Network (ANN), these two algorithms were combined. Through the augmentation, the Principal Component Neural Network (PCNN) is developed. The results show that PCNN successfully surpassed the respective versions of PCR and ANN with higher shear force prediction performances. The PCNN proved to achieve the best prediction in breast meat with root mean square error of prediction (RMSEP) of 0.0815 kg and coefficient of determination, (Rp2) of 0.7977. NIRS technology integrated with machine learning yield a promising non-invasive technique in predicting the shear force of intact raw chicken meat. |
format |
Article |
author |
Abdul Rahim, Herlina Zulkifli, Syahidah Nurani Ghazali, Rashidah Abd. Rahim, Intan Maisarah |
author_facet |
Abdul Rahim, Herlina Zulkifli, Syahidah Nurani Ghazali, Rashidah Abd. Rahim, Intan Maisarah |
author_sort |
Abdul Rahim, Herlina |
title |
Non-invasive measurement of shear force in chicken meat using near infrared spectroscopy supported by neural network analysis. |
title_short |
Non-invasive measurement of shear force in chicken meat using near infrared spectroscopy supported by neural network analysis. |
title_full |
Non-invasive measurement of shear force in chicken meat using near infrared spectroscopy supported by neural network analysis. |
title_fullStr |
Non-invasive measurement of shear force in chicken meat using near infrared spectroscopy supported by neural network analysis. |
title_full_unstemmed |
Non-invasive measurement of shear force in chicken meat using near infrared spectroscopy supported by neural network analysis. |
title_sort |
non-invasive measurement of shear force in chicken meat using near infrared spectroscopy supported by neural network analysis. |
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Malaysian Society for Computed Tomography & Imaging Technology (MyCT) |
publishDate |
2022 |
url |
http://eprints.utm.my/104263/1/RashidahGhazaliHerlinaAbdulRahimSyahidahNuraniZulkifli2022_NonInvasiveMeasurementofShearForce.pdf http://eprints.utm.my/104263/ https://tssa.my/index.php/jtssa/article/view/202/90 |
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