A Novel Variable Selection Method Based on Ordered Predictors Selection and Successive Projections Algorithm for Predicting Gastrodin Content in Fresh <i>Gastrodia elata</i> Using Fourier Transform Near-Infrared Spectroscopy and Chemometrics
Gastrodin is one of the most important biologically active components of <i>Gastrodia elata</i>, which has many health benefits as a dietary and health food supplement. However, gastrodin measurement traditionally relies on laboratory and sophisticated instruments. This research was aime...
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MDPI AG
2023-12-01
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| Series: | Foods |
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| Online Access: | https://www.mdpi.com/2304-8158/12/24/4435 |
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| author | Zhenjie Wang Changzhou Zuo Min Chen Jin Song Kang Tu Weijie Lan Chunyang Li Leiqing Pan |
| author_facet | Zhenjie Wang Changzhou Zuo Min Chen Jin Song Kang Tu Weijie Lan Chunyang Li Leiqing Pan |
| author_sort | Zhenjie Wang |
| collection | DOAJ |
| description | Gastrodin is one of the most important biologically active components of <i>Gastrodia elata</i>, which has many health benefits as a dietary and health food supplement. However, gastrodin measurement traditionally relies on laboratory and sophisticated instruments. This research was aimed at developing a rapid and non-destructive method based on Fourier transform near infrared (FT-NIR) to predict gastrodin content in fresh <i>Gastrodia elata</i>. Auto-ordered predictors selection (autoOPS) and successive projections algorithm (SPA) were applied to select the most informative variables related to gastrodin content. Based on that, partial least squares regression (PLSR) and multiple linear regression (MLR) models were compared. The autoOPS-SPA-MLR model showed the best prediction performances, with the determination coefficient of prediction (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi mathvariant="normal">R</mi></mrow><mrow><mi mathvariant="normal">p</mi></mrow><mrow><mn>2</mn></mrow></msubsup></mrow></semantics></math></inline-formula>), ratio performance deviation (RPD) and range error ratio (RER) values of 0.9712, 5.83 and 27.65, respectively. Consequently, these results indicated that FT-NIRS technique combined with chemometrics could be an efficient tool to rapidly quantify gastrodin in <i>Gastrodia elata</i> and thus facilitate quality control of <i>Gastrodia elata</i>. |
| first_indexed | 2024-03-08T20:46:48Z |
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| id | doaj.art-6fad2fbc03794312a642b3fcf57360e6 |
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| issn | 2304-8158 |
| language | English |
| last_indexed | 2024-03-08T20:46:48Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj.art-6fad2fbc03794312a642b3fcf57360e62023-12-22T14:08:43ZengMDPI AGFoods2304-81582023-12-011224443510.3390/foods12244435A Novel Variable Selection Method Based on Ordered Predictors Selection and Successive Projections Algorithm for Predicting Gastrodin Content in Fresh <i>Gastrodia elata</i> Using Fourier Transform Near-Infrared Spectroscopy and ChemometricsZhenjie Wang0Changzhou Zuo1Min Chen2Jin Song3Kang Tu4Weijie Lan5Chunyang Li6Leiqing Pan7College of Food Science and Technology, Nanjing Agricultural University, No. 1 Weigang Road, Nanjing 210095, ChinaCollege of Food Science and Technology, Nanjing Agricultural University, No. 1 Weigang Road, Nanjing 210095, ChinaCollege of Food Science and Technology, Nanjing Agricultural University, No. 1 Weigang Road, Nanjing 210095, ChinaCollege of Artificial Intelligence, Nanjing Agricultural University, No. 40 Dianjiangtai Road, Nanjing 210095, ChinaCollege of Food Science and Technology, Nanjing Agricultural University, No. 1 Weigang Road, Nanjing 210095, ChinaCollege of Food Science and Technology, Nanjing Agricultural University, No. 1 Weigang Road, Nanjing 210095, ChinaInstitute of Agro-Products Processing, Jiangsu Academy of Agricultural Sciences, No. 50 Zhongling Road, Nanjing 210014, ChinaCollege of Food Science and Technology, Nanjing Agricultural University, No. 1 Weigang Road, Nanjing 210095, ChinaGastrodin is one of the most important biologically active components of <i>Gastrodia elata</i>, which has many health benefits as a dietary and health food supplement. However, gastrodin measurement traditionally relies on laboratory and sophisticated instruments. This research was aimed at developing a rapid and non-destructive method based on Fourier transform near infrared (FT-NIR) to predict gastrodin content in fresh <i>Gastrodia elata</i>. Auto-ordered predictors selection (autoOPS) and successive projections algorithm (SPA) were applied to select the most informative variables related to gastrodin content. Based on that, partial least squares regression (PLSR) and multiple linear regression (MLR) models were compared. The autoOPS-SPA-MLR model showed the best prediction performances, with the determination coefficient of prediction (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi mathvariant="normal">R</mi></mrow><mrow><mi mathvariant="normal">p</mi></mrow><mrow><mn>2</mn></mrow></msubsup></mrow></semantics></math></inline-formula>), ratio performance deviation (RPD) and range error ratio (RER) values of 0.9712, 5.83 and 27.65, respectively. Consequently, these results indicated that FT-NIRS technique combined with chemometrics could be an efficient tool to rapidly quantify gastrodin in <i>Gastrodia elata</i> and thus facilitate quality control of <i>Gastrodia elata</i>.https://www.mdpi.com/2304-8158/12/24/4435<i>Gastrodia elata</i>gastrodinnear-infrared spectroscopy (NIRS)partial least squares (PLS)multiple linear regression (MLR) |
| spellingShingle | Zhenjie Wang Changzhou Zuo Min Chen Jin Song Kang Tu Weijie Lan Chunyang Li Leiqing Pan A Novel Variable Selection Method Based on Ordered Predictors Selection and Successive Projections Algorithm for Predicting Gastrodin Content in Fresh <i>Gastrodia elata</i> Using Fourier Transform Near-Infrared Spectroscopy and Chemometrics Foods <i>Gastrodia elata</i> gastrodin near-infrared spectroscopy (NIRS) partial least squares (PLS) multiple linear regression (MLR) |
| title | A Novel Variable Selection Method Based on Ordered Predictors Selection and Successive Projections Algorithm for Predicting Gastrodin Content in Fresh <i>Gastrodia elata</i> Using Fourier Transform Near-Infrared Spectroscopy and Chemometrics |
| title_full | A Novel Variable Selection Method Based on Ordered Predictors Selection and Successive Projections Algorithm for Predicting Gastrodin Content in Fresh <i>Gastrodia elata</i> Using Fourier Transform Near-Infrared Spectroscopy and Chemometrics |
| title_fullStr | A Novel Variable Selection Method Based on Ordered Predictors Selection and Successive Projections Algorithm for Predicting Gastrodin Content in Fresh <i>Gastrodia elata</i> Using Fourier Transform Near-Infrared Spectroscopy and Chemometrics |
| title_full_unstemmed | A Novel Variable Selection Method Based on Ordered Predictors Selection and Successive Projections Algorithm for Predicting Gastrodin Content in Fresh <i>Gastrodia elata</i> Using Fourier Transform Near-Infrared Spectroscopy and Chemometrics |
| title_short | A Novel Variable Selection Method Based on Ordered Predictors Selection and Successive Projections Algorithm for Predicting Gastrodin Content in Fresh <i>Gastrodia elata</i> Using Fourier Transform Near-Infrared Spectroscopy and Chemometrics |
| title_sort | novel variable selection method based on ordered predictors selection and successive projections algorithm for predicting gastrodin content in fresh i gastrodia elata i using fourier transform near infrared spectroscopy and chemometrics |
| topic | <i>Gastrodia elata</i> gastrodin near-infrared spectroscopy (NIRS) partial least squares (PLS) multiple linear regression (MLR) |
| url | https://www.mdpi.com/2304-8158/12/24/4435 |
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