Visualization of Sugar Content Distribution of White Strawberry by Near-Infrared Hyperspectral Imaging
In this study, an approach to visualize the spatial distribution of sugar content in white strawberry fruit flesh using near-infrared hyperspectral imaging (NIR-HSI; 913–2166 nm) is developed. NIR-HSI data collected from 180 samples of “Tochigi iW1 go” white strawberries are investigated. In order t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Foods |
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| Online Access: | https://www.mdpi.com/2304-8158/12/5/931 |
| _version_ | 1797615364763287552 |
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| author | Hayato Seki Te Ma Haruko Murakami Satoru Tsuchikawa Tetsuya Inagaki |
| author_facet | Hayato Seki Te Ma Haruko Murakami Satoru Tsuchikawa Tetsuya Inagaki |
| author_sort | Hayato Seki |
| collection | DOAJ |
| description | In this study, an approach to visualize the spatial distribution of sugar content in white strawberry fruit flesh using near-infrared hyperspectral imaging (NIR-HSI; 913–2166 nm) is developed. NIR-HSI data collected from 180 samples of “Tochigi iW1 go” white strawberries are investigated. In order to recognize the pixels corresponding to the flesh and achene on the surface of the strawberries, principal component analysis (PCA) and image processing are conducted after smoothing and standard normal variate (SNV) pretreatment of the data. Explanatory partial least squares regression (PLSR) analysis is performed to develop an appropriate model to predict Brix reference values. The PLSR model constructed from the raw spectra extracted from the flesh region of interest yields high prediction accuracy with an RMSEP and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mi>R</mi><mn>2</mn></msup><msub><mrow></mrow><mi>p</mi></msub></mrow></semantics></math></inline-formula> values of 0.576 and 0.841, respectively, and with a relatively low number of PLS factors. The Brix heatmap images and violin plots for each sample exhibit characteristics feature of sugar content distribution in the flesh of the strawberries. These findings offer insights into the feasibility of designing a noncontact system to monitor the quality of white strawberries. |
| first_indexed | 2024-03-11T07:25:14Z |
| format | Article |
| id | doaj.art-23215b213da04deda6b1fc332c687752 |
| institution | Directory Open Access Journal |
| issn | 2304-8158 |
| language | English |
| last_indexed | 2024-03-11T07:25:14Z |
| publishDate | 2023-02-01 |
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| series | Foods |
| spelling | doaj.art-23215b213da04deda6b1fc332c6877522023-11-17T07:39:54ZengMDPI AGFoods2304-81582023-02-0112593110.3390/foods12050931Visualization of Sugar Content Distribution of White Strawberry by Near-Infrared Hyperspectral ImagingHayato Seki0Te Ma1Haruko Murakami2Satoru Tsuchikawa3Tetsuya Inagaki4Institute of Agricultural Machinery, National Agricultural and Food Research Organization, 1-40-2, Nisshin-Cho, Kita-Ku, Saitama City 331-8537, JapanGraduate School of Bioagricultural Sciences, Nagoya University, Furo-Cho, Chikusa, Nagoya 464-8601, JapanGraduate School of Bioagricultural Sciences, Nagoya University, Furo-Cho, Chikusa, Nagoya 464-8601, JapanGraduate School of Bioagricultural Sciences, Nagoya University, Furo-Cho, Chikusa, Nagoya 464-8601, JapanGraduate School of Bioagricultural Sciences, Nagoya University, Furo-Cho, Chikusa, Nagoya 464-8601, JapanIn this study, an approach to visualize the spatial distribution of sugar content in white strawberry fruit flesh using near-infrared hyperspectral imaging (NIR-HSI; 913–2166 nm) is developed. NIR-HSI data collected from 180 samples of “Tochigi iW1 go” white strawberries are investigated. In order to recognize the pixels corresponding to the flesh and achene on the surface of the strawberries, principal component analysis (PCA) and image processing are conducted after smoothing and standard normal variate (SNV) pretreatment of the data. Explanatory partial least squares regression (PLSR) analysis is performed to develop an appropriate model to predict Brix reference values. The PLSR model constructed from the raw spectra extracted from the flesh region of interest yields high prediction accuracy with an RMSEP and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mi>R</mi><mn>2</mn></msup><msub><mrow></mrow><mi>p</mi></msub></mrow></semantics></math></inline-formula> values of 0.576 and 0.841, respectively, and with a relatively low number of PLS factors. The Brix heatmap images and violin plots for each sample exhibit characteristics feature of sugar content distribution in the flesh of the strawberries. These findings offer insights into the feasibility of designing a noncontact system to monitor the quality of white strawberries.https://www.mdpi.com/2304-8158/12/5/931white strawberryhyperspectral imagingprincipal component analysisimage processingpartial least squares regressionsugar content distribution |
| spellingShingle | Hayato Seki Te Ma Haruko Murakami Satoru Tsuchikawa Tetsuya Inagaki Visualization of Sugar Content Distribution of White Strawberry by Near-Infrared Hyperspectral Imaging Foods white strawberry hyperspectral imaging principal component analysis image processing partial least squares regression sugar content distribution |
| title | Visualization of Sugar Content Distribution of White Strawberry by Near-Infrared Hyperspectral Imaging |
| title_full | Visualization of Sugar Content Distribution of White Strawberry by Near-Infrared Hyperspectral Imaging |
| title_fullStr | Visualization of Sugar Content Distribution of White Strawberry by Near-Infrared Hyperspectral Imaging |
| title_full_unstemmed | Visualization of Sugar Content Distribution of White Strawberry by Near-Infrared Hyperspectral Imaging |
| title_short | Visualization of Sugar Content Distribution of White Strawberry by Near-Infrared Hyperspectral Imaging |
| title_sort | visualization of sugar content distribution of white strawberry by near infrared hyperspectral imaging |
| topic | white strawberry hyperspectral imaging principal component analysis image processing partial least squares regression sugar content distribution |
| url | https://www.mdpi.com/2304-8158/12/5/931 |
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