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Large-Scale Screening of Intact Castor Seeds by Viscosity Using Time-Domain NMR and Chemometrics

  • Original Paper
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Journal of the American Oil Chemists' Society

Abstract

Castor is one of the most promising non-edible oil crops, due to its high oil content and since it can be grown on marginal lands and in a semi-arid climate. However, the high content of ricinoleic acid results in an extremely high viscosity of castor-based biodiesel. In this study, we report on the development of a rapid and non-destructive method for large-scale screening of intact castor seeds according to their viscosity by time domain NMR and chemometrics. A qualitative principal component analysis model was constructed, where each observation was assigned to a different viscosity group. This model straightforwardly detects desirable outliers, and can also be applied for detection of other transgenic oilseeds, especially those containing small levels of hydroxylated fatty acid.

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References

  1. Gui MM, Lee KT, Bhatia S (2008) Feasibility of edible oil vs. non-edible oil vs. waste edible oil as biodiesel feedstock. Energy 33:1646–1653

    Article  CAS  Google Scholar 

  2. Sailaja M, Tarakeswari M, Sujatha M (2008) Stable genetic transformation of castor (Ricinus communis L.) via particle gun-mediated gene transfer using embryo axes from mature seeds. Plant Cell Rep 27:1509–1519

    Article  CAS  Google Scholar 

  3. Scholz V, da Silva JN (2008) Prospects and risks of the use of castor oil as a fuel. Biomass Bioenergy 32:95–100

    Article  CAS  Google Scholar 

  4. Kinney AJ, Clemente TE (2005) Modifying soybean oil for enhanced performance in biodiesel blends. Fuel Process Technol 86:1137–1147

    Article  CAS  Google Scholar 

  5. Knothe G, Steidley KR (2005) Kinematic viscosity of biodiesel fuel components and related compounds. Influence of compound structure and comparison to petrodiesel fuel components. Fuel 84:1059–1065

    Article  CAS  Google Scholar 

  6. Rojas-Barros P, De Haro A, Muñoz J, Fernández-Martínez JM (2004) Isolation of a natural mutant in castor (Ricinus communis L.) with high oleic/low ricinoleic acid content in the oil. Crop Sci 44:76–80

    CAS  Google Scholar 

  7. Carr HY, Purcell EM (1954) Effects of diffusion on free precession in nuclear magnetic resonance experiments. Phys Rev 94:630–638

    Article  CAS  Google Scholar 

  8. Meiboom S, Gill D (1958) Modified spin-echo method for measuring nuclear relaxation times. Rev Sci Instrum 29:688–691

    Article  CAS  Google Scholar 

  9. Prestes RA, Colnago LA, Forato LA, Vizzotto L, Novotny EH, Carrilho E (2007) A rapid and automated low resolution NMR method to analyze oil quality in intact oilseeds. Anal Chim Acta 596:325–329

    Article  CAS  Google Scholar 

  10. Pedersen HT, Munck L, Engelsen SB (2000) Low-field 1H nuclear magnetic resonance and chemometrics combined for simultaneous determination of water, oil, and protein contents in oilseeds. J Am Oil Chem Soc 77:1069–1077

    Article  CAS  Google Scholar 

  11. Wold S, Berglund A, Kettaneh N (2002) New and old trends in chemometrics. How to deal with the increasing data volumes in R&D&P (research, development and production): with examples from pharmaceutical research and process modeling. J Chemometrics 16:377–386

    Article  CAS  Google Scholar 

  12. Likas A, Vlassis N, Verbeek J (2003) The global k-means clustering algorithm. Pattern Recogn 36:451–461

    Article  Google Scholar 

  13. Allen CAW, Watts KC, Ackman RG, Pegg MJ (1999) Predicting the viscosity of biodiesel fuels from their fatty acid ester composition. Fuel 78:1319–1326

    Article  CAS  Google Scholar 

  14. Knothe G (2005) Dependence of biodiesel fuel properties on the structure of fatty acid alkyl esters. Fuel Process Technol 86:1059–1070

    Article  CAS  Google Scholar 

  15. Dorado MP, Ballesteros E, López FJ, Mittelbach M (2004) Optimization of alkali-catalyzed transesterification of Brassica Carinata oil for biodiesel production. Energy Fuels 18:77–83

    Article  CAS  Google Scholar 

  16. Meneghetti SMP, Meneghetti MR, Wolf CR, Silva EC, Lima GES, Silva LL, Serra TM, Cauduro F, Oliveira LG (2006) Biodiesel from castor oil: a comparison of ethanolysis versus methanolysis. Energy Fuels 20:2262–2265

    Article  Google Scholar 

  17. Bechmann IE, Pedersen HT, Nørgaard L, Engelsen SB (1999) Comparative chemometric analysis of transverse low-field 1H NMR relaxation data. In: Belton PS, Hills BP, Webb G (eds) Advances in magnetic resonance in food science. Royal Society of Chemistry, London

    Google Scholar 

  18. Rubel G (1994) Simultaneous determination of oil and water contents in different oilseeds by pulsed nuclear magnetic resonance. J Am Oil Chem Soc 71:1057–1062

    Article  CAS  Google Scholar 

  19. Hickey H, MacMillan B, Newling B, Ramesh M, Eijck PV, Balcom B (2006) Magnetic resonance relaxation measurements to determine oil and water content in fried foods. Food Res Int 39:612–618

    Article  CAS  Google Scholar 

  20. Povlsen VT, Rinnan A, van den Berg F, Andersen HJ, Thybo AK (2003) Direct decomposition of NMR relaxation profiles and prediction of sensory attributes of potato samples. Lebensmittel-Wissenschaft und-Technologie 36:423–432

    Article  CAS  Google Scholar 

  21. Grushcow J, Smith M (2006) Engineering high-performance biolubricants in crop plants. Ind Biotechnol 2:48–50

    Article  CAS  Google Scholar 

  22. Seland JG, Sørland GH, Anthonsen HW, Krane J (2003) Combining PFG and CPMG NMR measurements for separate characterization of oil and water simultaneously present in heterogeneous system. Appl Magn Reson 24:41–53

    Article  CAS  Google Scholar 

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Acknowledgments

This work was partially supported by Evogene Ltd. The authors would like to thank Ormat Industries for the donation of the LR-NMR System. Special thanks are extended to Mrs. Edna Oxman for her scientific editing work.

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Authors and Affiliations

  1. The Phyto-Lipid Biotechnology Lab, Department of Biotechnology Engineering, The Institutes for Applied Research, Ben-Gurion University of the Negev, P.O. Box 653, 84105, Beersheba, Israel

    Paula Berman, Shahar Nizri & Zeev Wiesman

  2. Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, P.O. Box 653, 84105, Beersheba, Israel

    Yisrael Parmet

Authors
  1. Paula Berman
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  2. Shahar Nizri
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  3. Yisrael Parmet
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  4. Zeev Wiesman
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Correspondence to Zeev Wiesman.

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Berman, P., Nizri, S., Parmet, Y. et al. Large-Scale Screening of Intact Castor Seeds by Viscosity Using Time-Domain NMR and Chemometrics. J Am Oil Chem Soc 87, 1247–1254 (2010). https://doi.org/10.1007/s11746-010-1612-z

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  • DOI: https://doi.org/10.1007/s11746-010-1612-z

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