Non-Destructive Quantitative Analysis of Azodicarbonamide Additives in Wheat Flour by High-Throughput Raman Imaging
Azodicarbonamide (ADA) additives are limited or prohibited from being added to wheat flour by various countries because they may produce carcinogenic semicarbazide in humid and hot conditions. This study aimed to realize the non-destructive detection of ADA additives in wheat flour using high-throug...
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| Format: | Article |
| Language: | English |
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Institute of Animal Reproduction and Food Research
2021-10-01
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| Series: | Polish Journal of Food and Nutrition Sciences |
| Subjects: | |
| Online Access: | http://journal.pan.olsztyn.pl/Non-Destructive-Quantitative-Analysis-of-Azodicarbonamide-Additives-in-Wheat-Flour,142879,0,2.html |
| _version_ | 1819172936062337024 |
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| author | Xiaobin Wang Chunjiang Zhao |
| author_facet | Xiaobin Wang Chunjiang Zhao |
| author_sort | Xiaobin Wang |
| collection | DOAJ |
| description | Azodicarbonamide (ADA) additives are limited or prohibited from being added to wheat flour by various countries because they may produce carcinogenic semicarbazide in humid and hot conditions. This study aimed to realize the non-destructive detection of ADA additives in wheat flour using high-throughput Raman imaging and establish a quantitative analysis model. Raman images of pure wheat flour, pure ADA, and wheat flour-ADA mixed samples were collected respectively, and the average Raman spectra of each sample were calculated. A partial least squares (PLS) model was established by using the linear combination spectra of pure wheat flour and pure ADA and the average Raman spectra of mixed samples. The regression coefficients of the PLS model were used to reconstruct the 3D Raman images of mixed samples into 2D grayscale images. Threshold segmentation was used to classify wheat flour pixels and ADA pixels in grayscale images, and a quantitative analysis model was established based on the number of ADA pixels. The results showed that the minimum detectable content of ADA in wheat flour was 100 mg/kg. There was a good linear relationship between the ADA content in the mixed sample and the number of pixels classified as ADA in the grayscale image in the range of 100 – 10,000 mg/kg, and the correlation coefficient was 0.9858. This study indicated that the combination of PLS regression coefficients with threshold segmentation had provided a non-destructive method for quantitative detection of ADA in Raman images of wheat flour-ADA mixed samples. |
| first_indexed | 2024-12-22T20:15:06Z |
| format | Article |
| id | doaj.art-67fd9ca1a83b4e0c8ccdcccc04159879 |
| institution | Directory Open Access Journal |
| issn | 2083-6007 |
| language | English |
| last_indexed | 2024-12-22T20:15:06Z |
| publishDate | 2021-10-01 |
| publisher | Institute of Animal Reproduction and Food Research |
| record_format | Article |
| series | Polish Journal of Food and Nutrition Sciences |
| spelling | doaj.art-67fd9ca1a83b4e0c8ccdcccc041598792022-12-21T18:13:59ZengInstitute of Animal Reproduction and Food ResearchPolish Journal of Food and Nutrition Sciences2083-60072021-10-0171440341010.31883/pjfns/142879142879Non-Destructive Quantitative Analysis of Azodicarbonamide Additives in Wheat Flour by High-Throughput Raman ImagingXiaobin Wang0https://orcid.org/0000-0002-0402-6895Chunjiang Zhao1https://orcid.org/0000-0002-8641-2254School of Physics and Electronic Information, Nanchang Normal University, Nanchang 330032, ChinaBeijing Research Center of Intelligent Equipment for Agriculture, Beijing 100097, ChinaAzodicarbonamide (ADA) additives are limited or prohibited from being added to wheat flour by various countries because they may produce carcinogenic semicarbazide in humid and hot conditions. This study aimed to realize the non-destructive detection of ADA additives in wheat flour using high-throughput Raman imaging and establish a quantitative analysis model. Raman images of pure wheat flour, pure ADA, and wheat flour-ADA mixed samples were collected respectively, and the average Raman spectra of each sample were calculated. A partial least squares (PLS) model was established by using the linear combination spectra of pure wheat flour and pure ADA and the average Raman spectra of mixed samples. The regression coefficients of the PLS model were used to reconstruct the 3D Raman images of mixed samples into 2D grayscale images. Threshold segmentation was used to classify wheat flour pixels and ADA pixels in grayscale images, and a quantitative analysis model was established based on the number of ADA pixels. The results showed that the minimum detectable content of ADA in wheat flour was 100 mg/kg. There was a good linear relationship between the ADA content in the mixed sample and the number of pixels classified as ADA in the grayscale image in the range of 100 – 10,000 mg/kg, and the correlation coefficient was 0.9858. This study indicated that the combination of PLS regression coefficients with threshold segmentation had provided a non-destructive method for quantitative detection of ADA in Raman images of wheat flour-ADA mixed samples.http://journal.pan.olsztyn.pl/Non-Destructive-Quantitative-Analysis-of-Azodicarbonamide-Additives-in-Wheat-Flour,142879,0,2.htmlazodicarbonamidewheat flourraman imagingimage classificationquantitative model |
| spellingShingle | Xiaobin Wang Chunjiang Zhao Non-Destructive Quantitative Analysis of Azodicarbonamide Additives in Wheat Flour by High-Throughput Raman Imaging Polish Journal of Food and Nutrition Sciences azodicarbonamide wheat flour raman imaging image classification quantitative model |
| title | Non-Destructive Quantitative Analysis of Azodicarbonamide Additives in Wheat Flour by High-Throughput Raman Imaging |
| title_full | Non-Destructive Quantitative Analysis of Azodicarbonamide Additives in Wheat Flour by High-Throughput Raman Imaging |
| title_fullStr | Non-Destructive Quantitative Analysis of Azodicarbonamide Additives in Wheat Flour by High-Throughput Raman Imaging |
| title_full_unstemmed | Non-Destructive Quantitative Analysis of Azodicarbonamide Additives in Wheat Flour by High-Throughput Raman Imaging |
| title_short | Non-Destructive Quantitative Analysis of Azodicarbonamide Additives in Wheat Flour by High-Throughput Raman Imaging |
| title_sort | non destructive quantitative analysis of azodicarbonamide additives in wheat flour by high throughput raman imaging |
| topic | azodicarbonamide wheat flour raman imaging image classification quantitative model |
| url | http://journal.pan.olsztyn.pl/Non-Destructive-Quantitative-Analysis-of-Azodicarbonamide-Additives-in-Wheat-Flour,142879,0,2.html |
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