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NEAR INFRARED REFLECTANCE SPECTROSCOPY (NIRS) FOR LARGE SCALE SCREENING OF FATTY ACID PROFILE IN PEANUT (ARACHIS HYPOGAEA L.)

DOI: 10.5958/j.0976-0571.37.3.041    | Article Id: LR-2992 | Page : 272-280
Citation :- NEAR INFRARED REFLECTANCE SPECTROSCOPY (NIRS) FOR LARGE SCALE SCREENING OF FATTY ACID PROFILE IN PEANUT (ARACHIS HYPOGAEA L.).Legume Research.2014.(37):272-280
Kavera*, H.L. Nadaf and R.R. Hanchinal kaveri_pnut@rediffmail.com
Address : National Seed Project, Seed Unit, University of Agricultural Sciences, Dharwad 580 005, India

Abstract

Breeding programmes dealing with the modifications of the fatty acid profile in oilseed crops require large number of chromatographic analysis. This study was conducted to characterize the potential of near infrared reflectance spectroscopy (NIRS) for the fatty acid analysis of intact single seeds of peanut. The material consisted of 1000 mutant entries of M4 with varying fatty acid profile determined by gas chromatography (GC). Spectra from intact single seeds of the  mutant entries were collected with a specially designed adapter using standard monochromator instrument. Calibration equations were developed for the calibration set of 800 mutant entries and were further validated with cross-validation and external-validation set consisting each of 100 mutant entries. Among the three regression models, the spectra with modified partial least square regression model (mPLS) after second derivative pretreatment with SNV and detrend scatter correction had the best calibration and satisfactory prediction abilities. The r2 between NIRS and GC was 0.79 (palmitic acid), 0.91 (oleic acid) and 0.89 (linoleic acid) in cross validation, demonstrating the high reliability of NIRS in determining these fatty acid concentrations in intact single seeds. NIRS permitted analysis of about 40 samples per hour as against 1-2 samples in GC. Research clearly indicated that NIRS prediction of fatty acid profile using intact seeds was non-destructive, accurate, rapid and should be especially useful for early generation selection.

Keywords

Chemometrics Coefficient of determination Fatty acids NIR spectroscopy Peanut   Regression models.

References

  1. Braddock, J. C., Sims, C. A. and O’Keefe, S. K. (1995). Flavor and oxidative stability of roasted high oleic acid peanuts. J. Food Sci. 60: 489-493.
  2. Brown, D. F., Carter, C. M., Mattil, K. F. and Darroch, J. G. (1975). Effect of variety, growing location and their interaction on fatty acid composition of peanuts. J. Food Sci., 40: 1055-1060.
  3. Cogdill, R. P. and Anderson, C. A. (2005). J. Near Infrared Spectrosc. 13: 119.
  4. Giese, A. T. and French, C. S. (2007). Appl.Spectrosc. 82: 395-398.
  5. Golebiowski, T., Fillip, M. L., Harman, C. F. and Pallot, T. (1995). Routine analysis of fatty acids in whole seed of canola by NIR. 10th Australian Research Assembly on Brassicas, September, pp. 87.
  6. Hesise, H. M. and Winzen, R. (2002). Fundamental Chemometric Methods. In: Near Infrared Spectroscopy: Principals, Instruments, Applications. [Siesler H. W., Ozaki Y., Kawata S., Heise H. M. (Ed.], Wiely-VCH Verlag GmbH, Weinheim, p. 125.
  7. Knauft, D. A., Moore, K. M. and Gorbet, D. W. (1993). Further studies on the inheritance of fatty acid composition in peanut. Peanut Sci. 20: 74-76.
  8. Murphy D.J. (1999). Plants lipids: Their metabolism, function and utilization. In: Plant Chemistry and Molecular Biology. [Lea P.J. and Leegood R.C. (Ed.] John Wiley & Sons Ltd., Chichester, England, pp. 119.
  9. Murray, I. (1987). NIR spectra of homologous series of original compounds. In: NIR/NIT Spectroscopy, [Hollo J. et al. (Ed.], Akademiai Kiado, Budapest, pp. 13.
  10. Ozaki, Y., Morita, S. and Du, Y. (2007). Near Infrared Spectroscopy, In: Christy Food Science and Technology, Y. Ozaki, W. Fred Mc Culture, A. A., (Ed.), Wiley-Interscience, Hoboken, NJ, pp. 43.
  11. Pallot, T. N., Leong, A. S., Allen, J. A., Golder, T. M., Greenwood, C. F. and Golebiowski, T. (1999). Precision of fatty acid analysis using near infrared spectroscopy of whole seed brassicas. Proc. 10 th In: Rapeseed Congress,Canberra, Australia, 8.
  12. Panford, J. A. and deMan, J. M. (1990). Amer. Oil Chemists Soc, 67: 473.
  13. Pazdernik, D. L., Killam, A. S. and Orf, J. H. (1997). Analysis of amino and fatty acid composition in soybean seed, using near infrared reflectance spectroscopy. Agron. J. 9: 679-685.
  14. Reinhardt, T. C., Paul, C. and Robbelen, G. (1991). Making Light Work in Near Infrared Spectroscopy, In: Quantitative Analysis of Fatty Acids in Intact Rapeseed by NIRS, [Murray, I. Cowe, I (Ed.)], VCH, London, pp.323.
  15. Robbelen, G. (1990). Mutation breeding for quality improvement- a case study for oilseed crops. Mutat. Breed. Rev. 6: 1-44.
  16. Roberts, C. A., Joost, R. E. and Rottinghaus, G. E. (1997). Crop. Sci. 37: 281.
  17. Sato, T. S., Kawano and Iwamoto (1991). Near infra-red spectral patterns of fatty acid analysis from fats and oils. J. Amer. Oil Chem. Soc. 68: 827-833.
  18. Velasco, L., Fernandez- Martinez, J. M. and De Haro, A. (1995). The applicability of NIRS for estimating Multiple Seed Quality Components in Ethiopian Mustard, Rapeseed: today and tomorrow. 9th International Rapeseed Congress, July, pp. 867.
  19. Velasco, L., Fernandez-Martinez, J. M. and De Haro, A. (1997). Use of near infrared reflectance spectroscopy to screen Ethiopian mustard for seed weight. Agron. J. 89: 150-153.
  20. Velasco, L., Perez-Vich, B. and Fernandez-Martinez, J. M. (1999). Nondestructive screening for oleic and linoleic acid in single sunflower achenes by near infrared reflectance spectroscopy. Crop Sci. 39: 219-222.
  21. Windham, W. R., Mertens, D. R., Barton, F. E. (1989). Protocol for NIRS calibration: Sample selection and equation development and validation. In: Near infrared reflectance spectroscopy (NIRS): Analysis of forage quality. Agric. Handb. [Martin, G. C. et al. (Ed.)] USDA-ARS, Washington DC, pp. 643.
  22. Xie, L., Ying, Y. and Ying, J. (2007). Food Eng. 82: 395.

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