Skip to main content
SpringerLink
Log in

Simplified Quantification of Representative Bioactives in Food Through TLC Image Analysis

  • Published:
Food Analytical Methods Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • 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):736–742

    Google Scholar 

  • Baviskar SN (2011) A Quick & Automated Method for Measuring Cell Area Using ImageJ. Am Biol Teach 73(9):554–556

    Article  Google Scholar 

  • 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):649–656

    Article  CAS  Google Scholar 

  • 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

  • Chen X, Lin X (2014) Big Data Deep Learning: Challenges and Perspectives. 2:514–525 IEEE Access

    Article  Google Scholar 

  • 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):271–284

    Article  CAS  Google Scholar 

  • Dini I, Tenore GC, Dini A (2009) Saponins in Ipomoea batatas tubers: Isolation, characterization, quantification and antioxidant properties. Food Chem 113(2):411–419

    Article  CAS  Google Scholar 

  • 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):305–311

    Article  CAS  Google Scholar 

  • 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):194–218

    Article  Google Scholar 

  • Marinova D, Ribarova F, Atanassova M (2005) Total phenolics and total flavonoids in Bulgarian fruits and vegetables. J Univ Chem Technol Metall 40(40):255–260

  • 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 268:287–291

    Article  CAS  Google Scholar 

  • 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

  • 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):188–197

    Article  CAS  Google Scholar 

  • 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):491–508

    Article  Google Scholar 

  • Segler MHS, Preuss M, Waller MP (2018) Planning chemical syntheses with deep neural networks and symbolic AI. Nature 555(7698):604–610

    Article  CAS  Google Scholar 

  • 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):215–222

    CAS  Google Scholar 

  • Thilakarathna SH, Rupasinghe HPV (2013) Flavonoid Bioavailability and Attempts for Bioavailability Enhancement. Nutrients 5(9):3367–3387

    Article  Google Scholar 

  • Tsuda T (2012) Dietary anthocyanin-rich plants: Biochemical basis and recent progress in health benefits studies. Mol Nutr Food Res 56(1):159–170

    Article  CAS  Google Scholar 

  • 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):431–439

    Article  Google Scholar 

  • 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):1740–1746

    Article  CAS  Google Scholar 

  • 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):113–122

    Article  CAS  Google Scholar 

  • 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):284–294

    Article  CAS  Google Scholar 

Download references

Funding

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).

Author information

Authors and Affiliations

  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 Equipment, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China

    Lujing Xu & Songbai Liu

  2. Qinghai Food Inspection and Testing Institute, 12 Beidajie, Xining, 810000, China

    Tong Shu & Songbai Liu

Authors
  1. Lujing Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tong Shu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Songbai Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Songbai Liu.

Ethics declarations

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.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xu, L., Shu, T. & Liu, S. Simplified Quantification of Representative Bioactives in Food Through TLC Image Analysis. Food Anal. Methods 12, 2886–2894 (2019). https://doi.org/10.1007/s12161-019-01645-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12161-019-01645-x

Keywords

Search

Navigation