Hyperspectral Reflectance Imaging Technique for Visualization of Moisture Distribution in Cooked Chicken Breast
Spectroscopy has proven to be an efficient tool for measuring the properties of meat. In this article, hyperspectral imaging (HSI) techniques are used to determine the moisture content in cooked chicken breast over the VIS/NIR (400–1,000 nm) spectral range. Moisture measurements were performed using...
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2013-09-01
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Online Access: | http://www.mdpi.com/1424-8220/13/10/13289 |
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doaj-c30cb447ed7e4deb87f52e0dc229db332020-11-25T00:45:26ZengMDPI AGSensors1424-82202013-09-011310132891330010.3390/s131013289Hyperspectral Reflectance Imaging Technique for Visualization of Moisture Distribution in Cooked Chicken BreastByoung-Kwan ChoChangyeun MoMoon S. KimHoonsoo LeeLalit Mohan KandpalSpectroscopy has proven to be an efficient tool for measuring the properties of meat. In this article, hyperspectral imaging (HSI) techniques are used to determine the moisture content in cooked chicken breast over the VIS/NIR (400–1,000 nm) spectral range. Moisture measurements were performed using an oven drying method. A partial least squares regression (PLSR) model was developed to extract a relationship between the HSI spectra and the moisture content. In the full wavelength range, the PLSR model possessed a maximum of 0.90 and an SEP of 0.74%. For the NIR range, the PLSR model yielded an of 0.94 and an SEP of 0.71%. The majority of the absorption peaks occurred around 760 and 970 nm, representing the water content in the samples. Finally, PLSR images were constructed to visualize the dehydration and water distribution within different sample regions. The high correlation coefficient and low prediction error from the PLSR analysis validates that HSI is an effective tool for visualizing the chemical properties of meat.http://www.mdpi.com/1424-8220/13/10/13289hyperspectral imagingchicken breastmoisture contentcooking ovenPLSR |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Byoung-Kwan Cho Changyeun Mo Moon S. Kim Hoonsoo Lee Lalit Mohan Kandpal |
spellingShingle |
Byoung-Kwan Cho Changyeun Mo Moon S. Kim Hoonsoo Lee Lalit Mohan Kandpal Hyperspectral Reflectance Imaging Technique for Visualization of Moisture Distribution in Cooked Chicken Breast Sensors hyperspectral imaging chicken breast moisture content cooking oven PLSR |
author_facet |
Byoung-Kwan Cho Changyeun Mo Moon S. Kim Hoonsoo Lee Lalit Mohan Kandpal |
author_sort |
Byoung-Kwan Cho |
title |
Hyperspectral Reflectance Imaging Technique for Visualization of Moisture Distribution in Cooked Chicken Breast |
title_short |
Hyperspectral Reflectance Imaging Technique for Visualization of Moisture Distribution in Cooked Chicken Breast |
title_full |
Hyperspectral Reflectance Imaging Technique for Visualization of Moisture Distribution in Cooked Chicken Breast |
title_fullStr |
Hyperspectral Reflectance Imaging Technique for Visualization of Moisture Distribution in Cooked Chicken Breast |
title_full_unstemmed |
Hyperspectral Reflectance Imaging Technique for Visualization of Moisture Distribution in Cooked Chicken Breast |
title_sort |
hyperspectral reflectance imaging technique for visualization of moisture distribution in cooked chicken breast |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2013-09-01 |
description |
Spectroscopy has proven to be an efficient tool for measuring the properties of meat. In this article, hyperspectral imaging (HSI) techniques are used to determine the moisture content in cooked chicken breast over the VIS/NIR (400–1,000 nm) spectral range. Moisture measurements were performed using an oven drying method. A partial least squares regression (PLSR) model was developed to extract a relationship between the HSI spectra and the moisture content. In the full wavelength range, the PLSR model possessed a maximum of 0.90 and an SEP of 0.74%. For the NIR range, the PLSR model yielded an of 0.94 and an SEP of 0.71%. The majority of the absorption peaks occurred around 760 and 970 nm, representing the water content in the samples. Finally, PLSR images were constructed to visualize the dehydration and water distribution within different sample regions. The high correlation coefficient and low prediction error from the PLSR analysis validates that HSI is an effective tool for visualizing the chemical properties of meat. |
topic |
hyperspectral imaging chicken breast moisture content cooking oven PLSR |
url |
http://www.mdpi.com/1424-8220/13/10/13289 |
work_keys_str_mv |
AT byoungkwancho hyperspectralreflectanceimagingtechniqueforvisualizationofmoisturedistributionincookedchickenbreast AT changyeunmo hyperspectralreflectanceimagingtechniqueforvisualizationofmoisturedistributionincookedchickenbreast AT moonskim hyperspectralreflectanceimagingtechniqueforvisualizationofmoisturedistributionincookedchickenbreast AT hoonsoolee hyperspectralreflectanceimagingtechniqueforvisualizationofmoisturedistributionincookedchickenbreast AT lalitmohankandpal hyperspectralreflectanceimagingtechniqueforvisualizationofmoisturedistributionincookedchickenbreast |
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1725270157000966144 |