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Food Analytical Methods

, Volume 12, Issue 12, pp 2886–2894 | Cite as

Simplified Quantification of Representative Bioactives in Food Through TLC Image Analysis

  • Lujing Xu
  • Tong Shu
  • Songbai LiuEmail author
Article
  • 116 Downloads

Abstract

In this work, simplified quantification of representative bioactives through thin-layer chromatography (TLC) image was established employing state-of-the-art quantitative image analysis technology. A general protocol including developing system, visualization condition, and image analysis procedure was developed for representative bioactives such as polyphenols, flavonoids, anthocyanins, phytosterols, and carotenoids. Applicability of this method including linearity, repeatability, and accuracy was validated by comparison with the conventional UV-Vis spectrophotometry methods. Application in actual food samples including carrot and green tea demonstrated this method was accurate and selective. The high-throughput potential of this method was also demonstrated. This method is free from special instrument, is efficient, and would be a fantastic substitute for the conventional UV-Vis spectrophotometry methods. This work has unveiled the power of quantitative image analysis in bioactive analysis and would encourage further application in food industry.

Keywords

Thin-layer chromatography Image analysis ImageJ Bioactive Quantitative analysis 

Notes

Funding information

This study was funded by the National Key R&D Program of China (2017YFF0207800, 2016YFD0400805), the Zhejiang Public Welfare Technology Research Program (LGN18C200009), the Qinghai Science and Technology Program (2017-ZJ-Y06, 2016-NK-C22, 2015-NK-502), and the Foundation of Fuli Institute of Food Science at Zhejiang University, Zhejiang Science and Technology Program (2017C26004).

Compliance with Ethical Standards

Conflict of Interest

Lujing Xu declares that she has no conflict of interest. Tong Shu declares that he has no conflict of interest. Songbai Liu declares that he has no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed Consent

Not applicable.

References

  1. Araújo LBDC, Silva SL, Galvão MAM, Ferreira MRA, Araújo EL, Randau KP, Soares LAL (2013) Total phytosterol content in drug materials and extracts from roots of Acanthospermum hispidum by UV-VIS spectrophotometry. Rev Bras 23(5):736–742Google Scholar
  2. Baviskar SN (2011) A Quick & Automated Method for Measuring Cell Area Using ImageJ. Am Biol Teach 73(9):554–556CrossRefGoogle Scholar
  3. Bunea A, Andjelkovic M, Socaciu C, Bobis O, Neacsu M, Verhé R, Camp JV (2008) Total and individual carotenoids and phenolic acids content in fresh, refrigerated and processed spinach (Spinacia oleracea L.). Food Chem 108(2):649–656CrossRefGoogle Scholar
  4. Butnariu M, Coradini CZ (2012) Evaluation of Biologically Active Compounds from Calendula officinalis Flowers using Spectrophotometry. Chem Cent J.  https://doi.org/10.1186/-153X-6-35
  5. Chen X, Lin X (2014) Big Data Deep Learning: Challenges and Perspectives. 2:514–525 IEEE AccessCrossRefGoogle Scholar
  6. Demonty I, Ras RT, van der Knaap HCM, Duchateau GS, Meijer L, Zock PL, Geleijnse JM, Trautwein EA (2009) Continuous Dose-Response Relationship of the LDL-Cholesterol-Lowering Effect of Phytosterol Intake. J Nutr 139(2):271–284CrossRefGoogle Scholar
  7. Dini I, Tenore GC, Dini A (2009) Saponins in Ipomoea batatas tubers: Isolation, characterization, quantification and antioxidant properties. Food Chem 113(2):411–419CrossRefGoogle Scholar
  8. Helaly FM, Soliman HSM, Soheir AD, Ahmed AA (2001) Controlled release of migration of molluscicidal saponin from different types of polymers containing Calendula officinalis. Adv Polym Technol 20(4):305–311CrossRefGoogle Scholar
  9. Maiani G, Castón MJ, Catasta G, Toti E, Cambrodón IG, Bysted A, Granado-Lorencio F, Olmedilla-Alonso B, Knuthsen P, Valoti M, Böhm V, Mayer-Miebach E, Behsnilian D, Schlemmer U (2009) Carotenoids: Actual knowledge on food sources, intakes, stability and bioavailability and their protective role in humans. Mol Nutr Food Res 53(S2):194–218CrossRefGoogle Scholar
  10. Marinova D, Ribarova F, Atanassova M (2005) Total phenolics and total flavonoids in Bulgarian fruits and vegetables. J Univ Chem Technol Metall 40(40):255–260Google Scholar
  11. Minnaar P, Nyobo L, Jolly N, Ntushelo N, Meiring S (2018) Anthocyanins and polyphenols in Cabernet Franc wines produced with Saccharomyces cerevisiae and Torulaspora delbrueckii yeast strains: Spectrophotometric analysis and effect on selected sensory attributes. Food Chem 268:287–291CrossRefGoogle Scholar
  12. Müller M, Öller VM, Hennig S, Hübner W, Huser T (2016) Open-source image reconstruction of super-resolution structured illumination microscopy data in ImageJ. Nat Commun.  https://doi.org/10.1038/ncomms10980
  13. Murray M, Walchuk C, Suh M, Jones PJ (2015) Green tea catechins and cardiovascular disease risk factors: Should a health claim be made by the United States Food and Drug Administration. Trends Food Sci Technol 41(2):188–197CrossRefGoogle Scholar
  14. Peterson JJ, Dwyer JT, Jacques PF, McCullough ML (2012) Associations between flavonoids and cardiovascular disease incidence or mortality in European and US populations. Nutr Rev 70(9):491–508CrossRefGoogle Scholar
  15. Segler MHS, Preuss M, Waller MP (2018) Planning chemical syntheses with deep neural networks and symbolic AI. Nature 555(7698):604–610CrossRefGoogle Scholar
  16. Sripakdee T, Mahachai R, Chanthai S (2017) Direct analysis of anthocyanins-rich Mao fruit juice using sample dilution method based on chromophores/fluorophores of both cyanidin-3-glucoside and pelargonidin-3-glucoside. Int Food Res J 24(1):215–222Google Scholar
  17. Thilakarathna SH, Rupasinghe HPV (2013) Flavonoid Bioavailability and Attempts for Bioavailability Enhancement. Nutrients 5(9):3367–3387CrossRefGoogle Scholar
  18. Tsuda T (2012) Dietary anthocyanin-rich plants: Biochemical basis and recent progress in health benefits studies. Mol Nutr Food Res 56(1):159–170CrossRefGoogle Scholar
  19. Wang P, Chen Y, Xu X, Hellmann B, Huang C, Bai Y, Jin Z (2019) HPTLC Screening of Folic Acid in Food: In Situ Derivatization with Ozone-Induced Fluorescence. Food Anal Methods 12(2):431–439CrossRefGoogle Scholar
  20. Waramboi JG, Gidley MJ, Sopade PA (2013) Carotenoid contents of extruded and non-extruded sweetpotato flours from Papua New Guinea and Australia. Food Chem 141(3):1740–1746CrossRefGoogle Scholar
  21. Yang C, Wang H, Li G, Yang Z, Guan F, Jin H (2011) Cancer prevention by tea: Evidence from laboratory studies. Pharmacol Res 64(2):113–122CrossRefGoogle Scholar
  22. Zhang Y, Yang P, Sun T, Li D, Xu X, Rui Y, Li C, Chong M, Ibrahim T, Mercatali L, Amadori D, Lu X, Xie D, Li Q, Wang X (2013) miR-126 and miR-126* repress recruitment of mesenchymal stem cells and inflammatory monocytes to inhibit breast cancer metastasis. Nat Cell Biol 15(3):284–294CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Food Science and Nutrition, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang R & D Center for Food Technology and EquipmentZhejiang UniversityHangzhouChina
  2. 2.Qinghai Food Inspection and Testing InstituteXiningChina

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