Non-Destructive Near-Infrared Moisture Detection of Dried Goji (<i>Lycium barbarum</i> L.) Berry
To detect the moisture of dried Goji (<i>Lycium barbarum</i> L.) berries nondestructively, a near-infrared (NIR) hyperspectral imager was used for experiments. NIR hyperspectral data were obtained and processed by standard normal variate (SNV) calculation using the MATLAB software v.R201...
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MDPI AG
2024-03-01
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| Series: | Horticulturae |
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| Online Access: | https://www.mdpi.com/2311-7524/10/3/302 |
| _version_ | 1797240734468800512 |
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| author | Rui Kang Te Ma Satoru Tsuchikawa Tetsuya Inagaki Jun Chen Jian Zhao Dongdong Li Gongpei Cui |
| author_facet | Rui Kang Te Ma Satoru Tsuchikawa Tetsuya Inagaki Jun Chen Jian Zhao Dongdong Li Gongpei Cui |
| author_sort | Rui Kang |
| collection | DOAJ |
| description | To detect the moisture of dried Goji (<i>Lycium barbarum</i> L.) berries nondestructively, a near-infrared (NIR) hyperspectral imager was used for experiments. NIR hyperspectral data were obtained and processed by standard normal variate (SNV) calculation using the MATLAB software v.R2016a. On the basis of the actual moisture of dried Goji berries, the predicted moisture was obtained based on the partial least squares (PLS) algorithm and a prediction model for the moisture of dried goji berries was established. It was found that the moisture of dried Goji berries was responsive to the NIR hyperspectral imager. The established prediction model could accurately predict the moisture of dried goji berries, and its <i>R</i><sup>2</sup>-value was 0.9981. The results provide a theoretical basis for the design of non-destructive moisture-detecting equipment for dried Goji berries. |
| first_indexed | 2024-04-24T18:12:08Z |
| format | Article |
| id | doaj.art-317737f01f3742508a8afab42313cd88 |
| institution | Directory Open Access Journal |
| issn | 2311-7524 |
| language | English |
| last_indexed | 2024-04-24T18:12:08Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Horticulturae |
| spelling | doaj.art-317737f01f3742508a8afab42313cd882024-03-27T13:44:33ZengMDPI AGHorticulturae2311-75242024-03-0110330210.3390/horticulturae10030302Non-Destructive Near-Infrared Moisture Detection of Dried Goji (<i>Lycium barbarum</i> L.) BerryRui Kang0Te Ma1Satoru Tsuchikawa2Tetsuya Inagaki3Jun Chen4Jian Zhao5Dongdong Li6Gongpei Cui7College of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, ChinaGraduate 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, JapanCollege of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Xianyang 712100, ChinaCollege of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Xianyang 712100, ChinaCollege of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, ChinaCollege of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, ChinaTo detect the moisture of dried Goji (<i>Lycium barbarum</i> L.) berries nondestructively, a near-infrared (NIR) hyperspectral imager was used for experiments. NIR hyperspectral data were obtained and processed by standard normal variate (SNV) calculation using the MATLAB software v.R2016a. On the basis of the actual moisture of dried Goji berries, the predicted moisture was obtained based on the partial least squares (PLS) algorithm and a prediction model for the moisture of dried goji berries was established. It was found that the moisture of dried Goji berries was responsive to the NIR hyperspectral imager. The established prediction model could accurately predict the moisture of dried goji berries, and its <i>R</i><sup>2</sup>-value was 0.9981. The results provide a theoretical basis for the design of non-destructive moisture-detecting equipment for dried Goji berries.https://www.mdpi.com/2311-7524/10/3/302non-destructive detectionmoisturegoji berry<i>L. barbarum</i> polysaccharidesNIR hyperspectral imagingSNV |
| spellingShingle | Rui Kang Te Ma Satoru Tsuchikawa Tetsuya Inagaki Jun Chen Jian Zhao Dongdong Li Gongpei Cui Non-Destructive Near-Infrared Moisture Detection of Dried Goji (<i>Lycium barbarum</i> L.) Berry Horticulturae non-destructive detection moisture goji berry <i>L. barbarum</i> polysaccharides NIR hyperspectral imaging SNV |
| title | Non-Destructive Near-Infrared Moisture Detection of Dried Goji (<i>Lycium barbarum</i> L.) Berry |
| title_full | Non-Destructive Near-Infrared Moisture Detection of Dried Goji (<i>Lycium barbarum</i> L.) Berry |
| title_fullStr | Non-Destructive Near-Infrared Moisture Detection of Dried Goji (<i>Lycium barbarum</i> L.) Berry |
| title_full_unstemmed | Non-Destructive Near-Infrared Moisture Detection of Dried Goji (<i>Lycium barbarum</i> L.) Berry |
| title_short | Non-Destructive Near-Infrared Moisture Detection of Dried Goji (<i>Lycium barbarum</i> L.) Berry |
| title_sort | non destructive near infrared moisture detection of dried goji i lycium barbarum i l berry |
| topic | non-destructive detection moisture goji berry <i>L. barbarum</i> polysaccharides NIR hyperspectral imaging SNV |
| url | https://www.mdpi.com/2311-7524/10/3/302 |
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