Korean Journal of Agricultural Science (농업과학연구)

Institute of Agricultural Science, CNU (충남대학교 농업과학연구소)
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Non-destructive identification of fake eggs using fluorescence spectral analysis and hyperspectral imaging

  • Geonwoo, Kim (Department of Bio-industrial Machinery Engineering, College of Agriculture and Life Science, Gyeongsang National University) ;
  • Ritu, Joshi (Department of Biosystems Machinery Engineering, Chungnam National University) ;
  • Rahul, Joshi (Department of Biosystems Machinery Engineering, Chungnam National University) ;
  • Moon S., Kim (Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture) ;
  • Insuck, Baek (Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture) ;
  • Juntae, Kim (Department of Biosystems Machinery Engineering, Chungnam National University) ;
  • Eun-Sung, Park (Department of Biosystems Machinery Engineering, Chungnam National University) ;
  • Hoonsoo, Lee (Department of Biosystems Engineering, College of Agriculture, Life & Environment Science, Chungbuk National University) ;
  • Changyeun, Mo (Department of Biosystems Engineering, College of Agriculture and Life Sciences, Kangwon National University) ;
  • Byoung-Kwan, Cho (Department of Biosystems Machinery Engineering, Chungnam National University)
  • Received : 2022.06.10
  • Accepted : 2022.07.13
  • Published : 2022.09.01
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Abstract

In this study, fluorescence hyperspectral imaging (FHSI) was used for the rapid, non-destructive detection of fake, manmade eggs from real eggs. To identify fake eggs, protoporphyrin IX (PpIX)-a natural pigment present in real eggshells-was utilized as the main indicator due to its strong fluorescence emission effect. The fluorescence images of real and fake eggs were acquired using a line-scan-based FHSI system, and their fluorescence features were analyzed based on spectroscopic techniques. To improve the detection performance and accuracy, an optimal waveband combination was investigated with analysis of variance (ANOVA), and its fluorescence ratio images (588/645 nm) were created for visualization of the real eggs between two different egg groups. In addition, real and fake eggs were scanned using a one-waveband (645 nm) handheld fluorescence imager that can perform real-time scanning for on-site applications. Then, the results of the two methods were compared with one another. The outcome clearly shows that the newly developed FHSI system and the fluorescence handheld imager were both able to distinguish real eggs from fake eggs. Consequently, FHSI showed a better performance (clearer images) compared to the fluorescence handheld imager, and the outcome provided valuable information about the feasibility of using FHSI imaging with ANOVA for the discrimination of real and fake eggs.

Keywords

Acknowledgement

This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry (IPET) through Advanced Agricultural Machinery Industrialization Technology Development Program, funded by Ministry for Agriculture, Food and Rural Affairs (MAFRA) (120104-03).

References

  1. Baiano A. 2017. Applications of hyperspectral imaging for quality assessment of liquid based and semi-liquid food products: A review. Journal of Food Engineering 214:10-15. https://doi.org/10.1016/j.jfoodeng.2017.06.012
  2. Behbahani M, Keisham B, Rosinski CL, Berry V, Mehta AI. 2021. Intraoperative imaging device for glioblastoma multiforme surgery: Review of Raman-based intraoperative imaging and introduction of a novel handheld probe technology. Journal of Raman Spectroscopy 52:1228-1236. https://doi.org/10.1002/jrs.6101
  3. Bravo JJ, Olson JD, Davis SC, Roberts DW, Paulsen KD, Kanick SC. 2017. Hyperspectral data processing improves PpIX contrast during fluorescence guided surgery of human brain tumors. Scientific Reports 7:1-13. https://doi.org/10.1038/s41598-016-0028-x
  4. Cho B, Baek I, Lee N, Mo CY. 2011. Study on bruise detection of "Fuji" apple using hyperspectral reflectance imagery. Journal of Biosystems Engineering 36:484-490. https://doi.org/10.5307/JBE.2011.36.6.484
  5. Cho B, Kim MS, Baek I, Kim DY, Lee WH, Kim J, Bae H, Kim YS. 2013. Detection of cuticle defects on cherry tomatoes using hyperspectral fluorescence imagery. Postharvest Biology and Technology 76:40-49. https://doi.org/10.1016/j.postharvbio.2012.09.002
  6. Dean ML, Miller TA, Bruckner C. 2011. Egg-citing! Isolation of protoporphyrin IX from brown eggshells and its detection by optical spectroscopy and chemiluminescence. Journal of Chemical Education 88:788-792. https://doi.org/10.1021/ed100093h
  7. ElMasry G, Kamruzzaman M, Sun DW, Allen P. 2012. Principles and applications of hyperspectral imaging in quality evaluation of agro-food products: A review. Critical Reviews in Food Science and Nutrition 52:999-1023. https://doi.org/10.1080/10408398.2010.543495
  8. Fearnley L. 2021. Fake eggs: From counter-qualification to popular certification in China's food safety crisis. BioSocieties 17:253-275. https://doi.org/10.1057/s41292-020-00211-7
  9. Feng YZ, Sun DW. 2012. Application of hyperspectral imaging in food safety inspection and control: A review. Critical Reviews in Food Science and Nutrition 52:1039-1058.
  10. Fung F, Wang HS, Menon S. 2018. Food safety in the 21st century. Biomedical Journal 41:88-95. https://doi.org/10.1016/j.bj.2018.03.003
  11. Gautam SP, Chakraborty S, Narjary A, Deka J, Hazarika MK. 2021. Application of instant decompression-assisted steam curing for improving turmeric (Curcuma longa L.) powder quality. Journal of Biosystems Engineering 46:305-315. DOI:10.1007/s42853-021-00108-8.
  12. Huang H, Liu L, Ngadi MO. 2014. Recent developments in hyperspectral imaging for assessment of food quality and safety. Sensors 14:7248-7276. https://doi.org/10.3390/s140407248
  13. Idrish Miah M. 2001. Fluorescence spectroscopy study of protoporphyrin IX metabolism level in cells. Biopolymers-Biospectroscopy Section 62:237-240. https://doi.org/10.1002/bip.1018
  14. Joshi R, Joshi R, Faqeerzada MA, Park E, Bae H, Lee J, Kim HT, Cho BK. 2019. Effects of the storage environment on the quality attributes of eggs with a washing treatment. Korean Journal of Agricultural Science 46:689-703. https://doi.org/10.7744/KJOAS.20190056
  15. Joshi R, Lohumi S, Joshi R, Kim MS, Qin J, Baek I, Cho BK. 2020. Raman spectral analysis for non-invasive detection of external and internal parameters of fake eggs. Sensors and Actuators B:Chemical 303:127243.
  16. Kim G, Baek I, Stocker MD, Smith JE, Van Tassell AL, Qin J, Chan DE, Pachepsky Y, Kim MS. 2020a. Hyperspectral imaging from a multipurpose floating platform to estimate chlorophyll-a concentrations in irrigation pond water. Remote Sensing 12:2070.
  17. Kim G, Lee H, Baek I, Cho BK, Kim MS. 2022. Quantitative detection of benzoyl peroxide in wheat flour using line-scan short-wave infrared hyperspectral imaging. Sensors and Actuators B: Chemical 352:130997.
  18. Kim G, Lee H, Cho BK, Baek I, Kim MS. 2021a. Quantitative evaluation of food-waste components in organic fertilizer using visible-near-infrared hyperspectral imaging. Applied Sciences 11:17.
  19. Kim MJ, Mo C, Kim HT, Cho B, Hong SJ, Lee D, Shin C, Jang K, Kim YH, Baek I. 2021b. Research and technology trend analysis by big data-based smart livestock technology: A review. Journal of Biosystems Engineering 46:386-398. DOI:10.1007/s42853-021-00115-9.
  20. Kim MS, Chen YR, Mehl PM. 2001. Hyperspectral reflectance and fluorescence imaging system for food quality and safety. Transactions of the American Society of Agricultural Engineers 44:721-729.
  21. Kim MS, Lefcourt AM, Chen YR. 2003. Optimal fluorescence excitation and emission bands for detection of fecal contamination. Journal of Food Protection 66:1198-1207. https://doi.org/10.4315/0362-028X-66.7.1198
  22. Kim WS, Lee WS, Kim YJ. 2020b. A review of the applications of the internet of things (IoT) for agricultural automation. Journal of Biosystems Engineering 45:385-400. DOI:10.1007/s42853-020-00078-3.
  23. Lee H, Kim MS, Chao K, Lefcourt AM, Chan DE. 2013. Development of fluorescence based handheld imaging devices for food safety inspection. Sensing for Agriculture and Food Quality and Safety V 2013:45-52. DOI:10.1117/12.2018154.
  24. Lee H, Kim MS, Lee WH, Cho BK. 2018. Determination of the total volatile basic nitrogen (TVB-N) content in pork meat using hyperspectral fluorescence imaging. Sensors and Actuators B: Chemical 259:532-539. https://doi.org/10.1016/j.snb.2017.12.102
  25. Lee H, Kim MS, Qin J, Park E, Song YR, Oh CS, Cho BK. 2017. Raman hyperspectral imaging for detection of watermelon seeds infected with Acidovorax citrulli. Sensors 17:1-11. https://doi.org/10.3390/s17010001
  26. Lee HS, Shin BS. 2020. Potato detection and segmentation based on mask R-CNN. Journal of Biosystems Engineering 45:233-238. DOI:10.1007/s42853-020-00063-w.
  27. Li G, Chen S, Duan Z, Qu L, Xu G, Yang N. 2013. Comparison of protoporphyrin IX content and related gene expression in the tissues of chickens laying brown-shelled eggs. Poultry Science 92:3120-3124. https://doi.org/10.3382/ps.2013-03484
  28. Lohumi S, Lee S, Lee H, Kim MS, Lee WH, Cho BK. 2016. Application of hyperspectral imaging for characterization of intramuscular fat distribution in beef. Infrared Physics and Technology 74:1-10. https://doi.org/10.1016/j.infrared.2015.11.004
  29. MedlinePlus. 2021. Paraffin poisoning. Accessed in https://medlineplus.gov/ency/article/002731.htm on 9 Jun 2022.
  30. Mo C, Kim G, Kim MS, Lim J, Cho H, Barnaby JY, Cho BK. 2017. Fluorescence hyperspectral imaging technique for foreign substance detection on fresh-cut lettuce. Journal of the Science of Food and Agriculture 97:3985-3993. https://doi.org/10.1002/jsfa.8262
  31. More D. 2020. The potential risks of tartrazine. Accessed in https://www.verywellhealth.com/tartrazine-free-diet-83227 on 9 Jun 2022.
  32. Ostertag E, Scholz M, Klein J, Rebner K, Oelkrug D. 2019. Pigmentation of white, brown, and green chicken eggshells analyzed by reflectance, transmittance, and fluorescence spectroscopy. ChemistryOpen 8:1084-1093. https://doi.org/10.1002/open.201900154
  33. Pu H, Lin L, Sun DW. 2019. Principles of hyperspectral microscope imaging techniques and their applications in food quality and safety detection: A review. Comprehensive Reviews in Food Science and Food Safety 18:853-866. https://doi.org/10.1111/1541-4337.12432
  34. Qin J, Chao K, Kim MS, Lee H, Peng Y. 2014. Development of a Raman chemical imaging detection method for authenticating skim milk powder. Journal of Food Measurement and Characterization 8:122-131. https://doi.org/10.1007/s11694-014-9172-9
  35. Qin J, Kim MS, Chao K, Chan DE, Delwiche SR, Cho BK. 2017. Line-scan hyperspectral imaging techniques for food safety and quality applications. Applied Sciences 7:125. https://doi.org/10.3390/app7020125
  36. Seo Y, Mo C, Lim J, Lee A, Kim B, Jang J, Kim G. 2021. Detection of spinach juice residues on stainless steel surfaces using VNIR hyperspectral images. Journal of Biosystems Engineering 46:173-181. https://doi.org/10.1007/s42853-021-00097-8
  37. Seo YW, Lee H, Mo C, Kim MS, Baek I, Lee J, Cho BK. 2019. Multispectral fluorescence imaging technique for on-line inspection of fecal residues on poultry carcasses. Sensors 19:3483. https://doi.org/10.3390/s19163483
  38. Soon JM. 2020. Consumers' awareness and trust toward food safety news on social media in Malaysia. Journal of Food Protection 83:452-459. https://doi.org/10.4315/0362-028X.JFP-19-415
  39. Yang Q, Niu B, Gu S, Ma J, Zhao C, Chen Q, Guo D, Deng X, Yu Y, Zhang F. 2022. Rapid detection of nonprotein nitrogen adulterants in milk powder using point-scan Raman hyperspectral imaging technology. ACS Omega 7:2064-2073. https://doi.org/10.1021/acsomega.1c05533
  40. Zahid HSM, Swati P, Dibyajyoti S. 2013. Artificial and fake eggs: Dance of death. Advances in Pharmacology and Pharmacy 1:13-17. https://doi.org/10.13189/app.2013.010103
  41. Zhuang Q, Peng Y, Yang D, Wang Y, Zhao R, Chao K, Guo Q. 2022. Detection of frozen pork freshness by fluorescence hyperspectral image. Journal of Food Engineering 316:110840. https://doi.org/10.1016/j.jfoodeng.2021.110840