Inspection of maleic anhydride in starch powder using line-scan hyperspectral Raman chemical imaging technique
Keywords:
Raman spectroscopy, chemical imaging, starch, adulteration, food authenticationAbstract
Excessive use of maleic anhydride (MAN) in starch production is potentially harmful for consumers’ health. This study presents a macro-scale Raman chemical imaging method for detection and quantification of MAN particles mixed in starch powder. MAN was mixed into corn starch at eight concentration levels from 50 ppm to 6400 ppm (w/w). Each mixture was put in a sample holder with a 150 mm×100 mm area and a 2 mm depth to create a large surface and a thin layer of the powdery sample for inspection. A 30 W 785 nm line laser was projected on the sample surface, from which hyperspectral images were obtained by a line-scan Raman imaging system with a spatial resolution of 0.2 mm. Fluorescence signals generated by laser-sample interactions were eliminated by a mathematical baseline correction method. A unique Raman peak was selected at 1839 cm−1 for the MAN detection, at which single-band fluorescence-corrected images were extracted from the mixture of each concentration and used to generate chemical images for MAN detection and mapping. The MAN detection limit was estimated at 100 ppm based on the Raman imaging measurement results. Pixel concentrations of the MAN in the chemical images were found linearly correlated with mass concentrations of the MAN particles in the starch powder, suggesting the Raman chemical imaging method has the potential for quantitative detection of the MAN in the starch-MAN mixtures. Keywords: Raman spectroscopy, chemical imaging, starch, adulteration, food authentication DOI: 10.25165/j.ijabe.20181106.4339 Citation: Qin J W, Kim M S, Chao K L, Bellato L, Schmidt W F, Cho B-K, et al. Inspection of maleic anhydride in starch powder using line-scan hyperspectral Raman chemical imaging technique. Int J Agric & Biol Eng, 2018; 11(6): 120–125.References
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[11] Chao K, Dhakal S, Qin J, Kim M S, Peng Y. A 1064 nm dispersive Raman spectral imaging system for food safety and quality evaluation. Appl. Sci., 2018; 8(3): 431.
[12] Dhakal S, Chao K, Qin J, Kim M S, Chan D. Raman spectral imaging for quantitative contaminant evaluation in skim milk powder. J. Food. Meas. Charact., 2016; 10: 374–386.
[13] Qin J, Chao K, Cho B, Peng Y, Kim M S. High-throughput Raman chemical imaging for rapid evaluation of food safety and quality. Trans. ASABE 2014; 57: 1783–1792.
[14] Qin J, Chao K, Kim M S, Cho B. Line-scan macro-scale Raman chemical imaging for authentication of powdered foods and ingredients. Food Bioprocess Technol., 2016; 9: 113–123.
[15] Qin J, Kim M S, Chao K, Dhakal S, Lee H, Cho B, et al. Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique. Food Addit. Contam. Part A, 2017; 34(2): 152–161.
[16] Qin J, Kim M S, Chao K, Gonzalez M, Cho B. Quantitative detection of benzoyl peroxide in wheat flour by line-scan macro-scale Raman chemical imaging. Appl. Spectrosc., 2017; 71(11): 2469–2476.
[17] Qin J, Kim M S, Chao K, Bellato L. Detecting maleic anhydride in starch using line-scan hyperspectral Raman chemical imaging. ASABE Annual International Meeting, Spokane, WA. USA. 2017; ASABE Paper, No. 1700398.
[18] Zhang Z, Chen S, Liang Y. Baseline correction using adaptive iteratively reweighted penalized least squares. Analyst, 2010; 135(5): 1138–1146.
[19] Mirone P, Chiorboli P. Infrared and Raman spectra and vibrational assignment of maleic anhydride. Spectrochim. Acta, 1962; 18: 1425–1432.
[2] Chen H, Wu C, Wu K. Determination of the maleic acid in rat urine and serum samples by isotope dilution-liquid chromatography-tandem mass spectrometry with on-line solid phase extraction. Talanta, 2015; 136: 9–14.
[3] Xu D, Chen Y, Zhou S, Lian Y, Chen L, Lin L, et al. Determination of the total amount of maleic acid and maleic anhydride in starch and its products by high performance liquid chromatography-tandem mass spectrometry. Chin. J. Chromatogr, 2013; 31(12): 1224–1227.
[4] Tsai C, Wu G, Kuo C, Lin Y, Chang C, Tseng S, et al. Effective extraction method through alkaline hydrolysis for the detection of starch maleate in foods. J. Food Drug Anal., 2015; 23(3): 442–446.
[5] Su W, Sun D. Fourier transform infrared and Raman and hyperspectral imaging techniques for quality determinations of powdery foods: a review. Compr. Rev. Food Sci. Food Saf., 2018; 17(1): 104–122.
[6] Xu L, Shi W, Cai C, Zhong W, Tu K. Rapid and nondestructive detection of multiple adulterants in kudzu starch by near infrared (NIR) spectroscopy and chemometrics. LWT Food Sci. Technol., 2015; 61(2): 590–595.
[7] Fu H, Li H, Xu L, Yin Q, Yan T, Ni C, et al. Detection of unexpected frauds: Screening and quantification of maleic acid in cassava starch by Fourier transform near-infrared spectroscopy. Food Chem, 2017; 227: 322–328.
[8] Almeida M R, Alves R S, Nascimbem L B L R, Stephani R, Poppi R J, de Oliveira L F C. Determination of amylose content in starch using Raman spectroscopy and multivariate calibration analysis. Anal. Bioanal. Chem., 2010; 397: 2693–2701.
[9] Liu Y, Xu Y, Yan Y, Hu D, Yang L, Shen R. Application of Raman spectroscopy in structure analysis and crystallinity calculation of corn starch. Starch – Stärke, 2015; 67(7–8): 612–619.
[10] Qin J, Chao K, Kim M S. Raman chemical imaging system for food safety and quality inspection. Trans. ASABE, 2010; 53(6): 1873–1882.
[11] Chao K, Dhakal S, Qin J, Kim M S, Peng Y. A 1064 nm dispersive Raman spectral imaging system for food safety and quality evaluation. Appl. Sci., 2018; 8(3): 431.
[12] Dhakal S, Chao K, Qin J, Kim M S, Chan D. Raman spectral imaging for quantitative contaminant evaluation in skim milk powder. J. Food. Meas. Charact., 2016; 10: 374–386.
[13] Qin J, Chao K, Cho B, Peng Y, Kim M S. High-throughput Raman chemical imaging for rapid evaluation of food safety and quality. Trans. ASABE 2014; 57: 1783–1792.
[14] Qin J, Chao K, Kim M S, Cho B. Line-scan macro-scale Raman chemical imaging for authentication of powdered foods and ingredients. Food Bioprocess Technol., 2016; 9: 113–123.
[15] Qin J, Kim M S, Chao K, Dhakal S, Lee H, Cho B, et al. Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique. Food Addit. Contam. Part A, 2017; 34(2): 152–161.
[16] Qin J, Kim M S, Chao K, Gonzalez M, Cho B. Quantitative detection of benzoyl peroxide in wheat flour by line-scan macro-scale Raman chemical imaging. Appl. Spectrosc., 2017; 71(11): 2469–2476.
[17] Qin J, Kim M S, Chao K, Bellato L. Detecting maleic anhydride in starch using line-scan hyperspectral Raman chemical imaging. ASABE Annual International Meeting, Spokane, WA. USA. 2017; ASABE Paper, No. 1700398.
[18] Zhang Z, Chen S, Liang Y. Baseline correction using adaptive iteratively reweighted penalized least squares. Analyst, 2010; 135(5): 1138–1146.
[19] Mirone P, Chiorboli P. Infrared and Raman spectra and vibrational assignment of maleic anhydride. Spectrochim. Acta, 1962; 18: 1425–1432.
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Published
2018-12-08
How to Cite
Qin, J., Kim, M. S., Chao, K., Bellato, L., Schmidt, W. F., Cho, B.-K., & Huang, M. (2018). Inspection of maleic anhydride in starch powder using line-scan hyperspectral Raman chemical imaging technique. International Journal of Agricultural and Biological Engineering, 11(6), 120–125. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/4339
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Information Technology, Sensors and Control Systems
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