Measurement and analysis of fluorescent whitening agent content in soybean milk based on image techniques |
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| Affiliation: | 1. School of Electronics and Information, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212003, China;2. Automation School, Harbin Engineering University, Harbin, Heilongjiang 150001, China;1. Dept. of Information Technology and Electrical Engineering, University of Naples “Federico II”, via Claudio 21, 80125 Naples, Italy;2. Dept. of Electrical and Information Engineering, University of Cassino and Southern Lazio, via G. Di Biasio, 43, 03043 Cassino, Italy;1. National Metrology Institute of Japan, National Institute of Industrial Science and Technology (AIST), 1-1-1 Umezono, Tsukuba, Ibaraki 305-8563, Japan;2. The Graduate School for the Creation of New Photonics Industries, Hamamatsu, Shizuoka 431-1202, Japan;3. Graduate School of Mechanical Engineering, Pusan National University 2, Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan 46241, Repubilc of Korea |
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| Abstract: | This paper presents a method for measuring and quantitatively analyzing the fluorescent whitening agent in soybean milk based on image techniques. After collecting the fluorescent images of the soybean milk samples, the top seven wavelet moment invariants are selected according to the sample training and experimental comparison. Then calculate the standard templates of the 49 classes of calibration samples with different fluorescent whitening agent content ranging from 0.02 mg/ml to 0.5 mg/ml. The minimum distance method is carried out to match the testing sample with the calibration template, which realizes the quantitative analysis. To verify the effectiveness of the presented method, the prediction experiment is carried out. Results show that the absolute errors are within 0.005 mg/ml and the relative errors are within 5%, which means this method can measure the fluorescent whitening agent in soybean milk. This research presents a new approach for detecting the illegal fluorescence additive in food production. |
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| Keywords: | Quantitative analysis Wavelet moment invariant Image techniques |
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