Comparative Quantitative and Discriminant Analysis of Wheat Flour with Different Levels of Chemical Azodicarbonamide Using NIR Spectroscopy and Hyperspectral Imaging
This study investigated and comprehensively compared the performance of spectra (950–1660 nm) acquired respectively from NIR and HSI in the rapid and non-destructive quantification of azodicarbonamide (ADA) content (0–100 mg/kg) in WF and simultaneously identified WF containing excessive ADA (>45...
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MDPI AG
2024-11-01
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| author | Hongju He Yuling Wang Shengqi Jiang Jie Zhang Jicai Bi Hong Qiao Leiqing Pan Xingqi Ou |
| author_facet | Hongju He Yuling Wang Shengqi Jiang Jie Zhang Jicai Bi Hong Qiao Leiqing Pan Xingqi Ou |
| author_sort | Hongju He |
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| description | This study investigated and comprehensively compared the performance of spectra (950–1660 nm) acquired respectively from NIR and HSI in the rapid and non-destructive quantification of azodicarbonamide (ADA) content (0–100 mg/kg) in WF and simultaneously identified WF containing excessive ADA (>45 mg/kg). The raw spectra were preprocessed using 14 methods and then mined by the partial least squares (PLS) algorithm to fit ADA levels using different numbers of WF samples for training and validation in five datasets (N<sub>Training</sub>/<sub>Validation</sub> = 189/21, 168/42, 147/63, 126/84, 105/105), yielding better abilities of NIR Savitzky–Golay 1st derivative (SG1D) spectra-based PLS models and raw HSI spectra-based PLS models in quantifying ADA with higher determination coefficients and lower root-mean-square errors in validation (R<sup>2</sup><sub>V</sub> & RMSEV), as well as establishing 100% accuracy in PLS discriminant analysis (PLS-DA) models for identifying excessive ADA-contained WF in each dataset. Twenty-four wavelengths selected from a NIR SG1D spectra in a 168/42 dataset and 23 from a raw HSI spectra in a 147/63 dataset allowed for the better performance of quantitative models in ADA determination with higher R<sup>2</sup><sub>V</sub> and RMSE<sub>V</sub> in validation (R<sup>2</sup><sub>V</sub> > 0.98, RMSE<sub>V</sub> < 3.87 mg/kg) and for discriminant models in WF classification with 100% accuracy. In summary, NIR technology may be sufficient if visualization is not required. |
| format | Article |
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| issn | 2304-8158 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Foods |
| spelling | doaj-art-88286d5f95c74b71bf68a72fb99b62dd2025-08-20T02:05:02ZengMDPI AGFoods2304-81582024-11-011322366710.3390/foods13223667Comparative Quantitative and Discriminant Analysis of Wheat Flour with Different Levels of Chemical Azodicarbonamide Using NIR Spectroscopy and Hyperspectral ImagingHongju He0Yuling Wang1Shengqi Jiang2Jie Zhang3Jicai Bi4Hong Qiao5Leiqing Pan6Xingqi Ou7School of Food Science, Henan Institute of Science and Technology, Xinxiang 453003, ChinaSchool of Life Science & Technology, Henan Institute of Science and Technology, Xinxiang 453003, ChinaCollege of Food Science and Engineering, Northwest A&F University, Yangling 712100, ChinaHenan Xinlianxin Chemical Industry Co., Ltd., Xinxiang 453003, ChinaSchool of Food Science, Henan Institute of Science and Technology, Xinxiang 453003, ChinaHenan Shudiyi Seed Industry Co., Ltd., Xinxiang 453003, ChinaCollege of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, ChinaSchool of Life Science & Technology, Henan Institute of Science and Technology, Xinxiang 453003, ChinaThis study investigated and comprehensively compared the performance of spectra (950–1660 nm) acquired respectively from NIR and HSI in the rapid and non-destructive quantification of azodicarbonamide (ADA) content (0–100 mg/kg) in WF and simultaneously identified WF containing excessive ADA (>45 mg/kg). The raw spectra were preprocessed using 14 methods and then mined by the partial least squares (PLS) algorithm to fit ADA levels using different numbers of WF samples for training and validation in five datasets (N<sub>Training</sub>/<sub>Validation</sub> = 189/21, 168/42, 147/63, 126/84, 105/105), yielding better abilities of NIR Savitzky–Golay 1st derivative (SG1D) spectra-based PLS models and raw HSI spectra-based PLS models in quantifying ADA with higher determination coefficients and lower root-mean-square errors in validation (R<sup>2</sup><sub>V</sub> & RMSEV), as well as establishing 100% accuracy in PLS discriminant analysis (PLS-DA) models for identifying excessive ADA-contained WF in each dataset. Twenty-four wavelengths selected from a NIR SG1D spectra in a 168/42 dataset and 23 from a raw HSI spectra in a 147/63 dataset allowed for the better performance of quantitative models in ADA determination with higher R<sup>2</sup><sub>V</sub> and RMSE<sub>V</sub> in validation (R<sup>2</sup><sub>V</sub> > 0.98, RMSE<sub>V</sub> < 3.87 mg/kg) and for discriminant models in WF classification with 100% accuracy. In summary, NIR technology may be sufficient if visualization is not required.https://www.mdpi.com/2304-8158/13/22/3667comparative analysiswheat flourazodicarbonamideNIRhyperspectral imaging |
| spellingShingle | Hongju He Yuling Wang Shengqi Jiang Jie Zhang Jicai Bi Hong Qiao Leiqing Pan Xingqi Ou Comparative Quantitative and Discriminant Analysis of Wheat Flour with Different Levels of Chemical Azodicarbonamide Using NIR Spectroscopy and Hyperspectral Imaging Foods comparative analysis wheat flour azodicarbonamide NIR hyperspectral imaging |
| title | Comparative Quantitative and Discriminant Analysis of Wheat Flour with Different Levels of Chemical Azodicarbonamide Using NIR Spectroscopy and Hyperspectral Imaging |
| title_full | Comparative Quantitative and Discriminant Analysis of Wheat Flour with Different Levels of Chemical Azodicarbonamide Using NIR Spectroscopy and Hyperspectral Imaging |
| title_fullStr | Comparative Quantitative and Discriminant Analysis of Wheat Flour with Different Levels of Chemical Azodicarbonamide Using NIR Spectroscopy and Hyperspectral Imaging |
| title_full_unstemmed | Comparative Quantitative and Discriminant Analysis of Wheat Flour with Different Levels of Chemical Azodicarbonamide Using NIR Spectroscopy and Hyperspectral Imaging |
| title_short | Comparative Quantitative and Discriminant Analysis of Wheat Flour with Different Levels of Chemical Azodicarbonamide Using NIR Spectroscopy and Hyperspectral Imaging |
| title_sort | comparative quantitative and discriminant analysis of wheat flour with different levels of chemical azodicarbonamide using nir spectroscopy and hyperspectral imaging |
| topic | comparative analysis wheat flour azodicarbonamide NIR hyperspectral imaging |
| url | https://www.mdpi.com/2304-8158/13/22/3667 |
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