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Prediction of Heavy Metal Content in Compost Using Near-infrared Reflectance Spectroscopy

  • Ko, H.J. (Incheon Regional Campus, Korea National Open University) ;
  • Choi, H.L. (School of Agricultural Biotechnology, Seoul National University) ;
  • Park, H.S. (School of Agricultural Biotechnology, Seoul National University) ;
  • Lee, H.W. (Department of Agronomy, Korea National Open University)
  • Received : 2004.03.10
  • Accepted : 2004.07.28
  • Published : 2004.12.01

Abstract

Since the application of relatively high levels of heavy metals in the compost poses a potential hazard to plants and animals, the content of heavy metals in the compost with animal manure is important to know if it is as a fertilizer. Measurement of heavy metals content in the compost by chemical methods usually requires numerous reagents, skilled labor and expensive analytical equipment. The objective of this study, therefore, was to explore the application of near-infrared reflectance spectroscopy (NIRS), a nondestructive, cost-effective and rapid method, for the prediction of heavy metals contents in compost. One hundred and seventy two diverse compost samples were collected from forty-seven compost facilities located along the Han river in Korea, and were analyzed for Cr, As, Cd, Cu, Zn and Pb levels using inductively coupled plasma spectrometry. The samples were scanned using a Foss NIRSystem Model 6500 scanning monochromator from 400 to 2,500 nm at 2 nm intervals. The modified partial least squares (MPLS), the partial least squares (PLS) and the principal component regression (PCR) analysis were applied to develop the most reliable calibration model, between the NIR spectral data and the sample sets for calibration. The best fit calibration model for measurement of heavy metals content in compost, MPLS, was used to validate calibration equations with a similar sample set (n=30). Coefficient of simple correlation (r) and standard error of prediction (SEP) were Cr (0.82, 3.13 ppm), As (0.71, 3.74 ppm), Cd (0.76, 0.26 ppm), Cu (0.88, 26.47 ppm), Zn (0.84, 52.84 ppm) and Pb (0.60, 2.85 ppm), respectively. This study showed that NIRS is a feasible analytical method for prediction of heavy metals contents in compost.

Keywords

Compost Quality;NIRS;Calibration Equation;Coefficient of Multiple Determination;Standard Error of Prediction

References

  1. Blanco, M. and I. Villarroya. 2002. NIR spectroscopy: a rapidresponse analytical tool. Trends Anal. Chem. 21(4):240-250.
  2. Burns, D. A. and E. W. Ciurczak. 1992. Handbook of Near-Infrared Analysis. Marcel Dekker, Inc., NY.
  3. Nicholson, F. A., B. J. Chambers, J. R. Williams and R. J. Unwin. 1999. Heavy metal contents of livestock feeds and animal manures in England and Wales. Bioresour. Technol. 70:23-31.
  4. Petruzzelli, G., G. Guidi and L. Lubrano. 1986. Chemicals in the environment. In: (Ed. J. N. Lester, N. Perry and R. M. Kester). Proceedings of International Conference: 772-776.
  5. Reeves III, J. B. and G. W. McCarty. 2001. Quantitative analysis of agricultural soils using near infrared reflectance spectroscopy and a fibre-optic probe. J. Near Infrared Spectrosc 9(1):25-34.
  6. Shi, W., J. M. Norton, B. E. Miller and M. G. Pace. 1999. Effects of aeration and moisture during windrow composting on the nitrogen fertilizer values of dairy waste composts. Appl. Soil Ecol. 11:17-28.
  7. Ben-Dor, E. and A. Banin. 1995. Near Infrared analysis (NIRA) as a method to simultaneously evaluate spectral featureless constituents in soils. Soil Sci. 159:259-270.
  8. Kabata-Pendias, A. and H. Pendias. 1992. Trace elements in soils and plants. $2^{nd}$ Ed. CRC Press Inc., Boca Raton, FL, USA.
  9. Gay, S. W., D. R. Schmidt, C. J. Clanton, K. A. Janni, L. D. Jacobson and Weisberg, S. 2003. Odor, total reduced sulfur, and ammonia emissions from animal housing facilities and manure storage units in Minnesota. Appl. Eng. Agri. 19(3):347-360.
  10. Chen, B., X. Fu and D. Lu. 2002. Improvement of predicting precision of oil content in instant noodles by using wavelet transforms to treat near-infrared spectroscopy. J. Food Eng. 53:373-376.
  11. Osborne, B. G., T. Fearn and P. H. Hindle. 1993. Practical NIR Spectroscopy with Applications in Food and Beverage Analysis; Longman Scientific and Technical: Burnt Mill, Harlow, Essex, England.
  12. L'Herroux, L., S. Le Roux, P. Appriou and J. Martinez. 1997. Behaviour of Metals following intensive pig slurry applications to a natural field treatment process in Brittany (France). Environ. Pollut. 97 (1-2):119-130.
  13. Malley, D. F. and P. C. Williams. 1997. Use of Near-Infrared Reflectance Spectroscopy in Prediction of Heavy Metals in Freshwater Sediment by Their Association with Organic Matter. Environ. Sci. Technol. 31:3461-3467.
  14. George, W. O. and D. Steele. 1995. Computing applications in molecular spectroscopy. Hartnolls Ltd., Bodmin, Cornwall, UK. pp. 217-235.
  15. Sims, J. T. and D. C. Wolf. 1994. Poultry waste management : Agricultural and Environmental issues. Adv. Agron. 52:2-72.
  16. He, X. T., T. J. Logan and S. J. Traina. 1995. Physical and chemical Characteristics of selected U. S. Municipal solid waste composts. J. Environ. Qual. 24:1177-1183.
  17. Shenk, J. S. and M. O. Westerhaus. 1991. Population definition, sample selection, and calibration procedures for near infrared reflectance spectroscopy. Crop Sci. 31:469-474.
  18. Ru, Y. J. and P. C. Glatz. 2000. Application of Near Infrared Spectroscopy (NIR) for Monitoring the Quality of Milk, Cheese, Meat and Fish. Asian-Aust. J. Anim. Sci. 13(7):1017-1025.
  19. Garcia, G., T. Hernanderz and F. Costa. 1992. Composted vs. Uncomposted organics. Biocycle. 33:70-72.
  20. Williams, P. C. and K. H. Norris. 1987. Near-Infrared Technology in the Agricultural and Food Industries; American Association of Cereal Chemists Inc. : St. Paul, MN. p. 330.
  21. Windham, W. R., J. A. Robertson and R. G. Leffler. 1987. A comparison among methods of moisture determination of forages for NIRS calibration and validation. Crop Sci. 27:777-783.
  22. FOSS NIRSystems/TECATOR. 1999. ISI Windows Near-Infrared Software: WinISI. II Ver. 1.02. Infrasoft International, LLC. Silver Spring, MD.
  23. Petruzzelli, G. 1989. Recycling wastes in agriculture: Heavy metals bioavailability. Agric. Ecosyst. Environ. 17:493-503.
  24. Geladi, P., D. MacDougall and H. Martens. 1985. Linearization and scatter-correction for near-infrared reflectance spectra of meat. Appl. Spectros. 39:491-500.
  25. Greenway, G. M. and Q. J. Song. 2002. Heavy metal speciation in the composting process. J. Environ. Monit. 4:300-305.
  26. Hunt, G. R. and J. W. Salisbury. 1970. Visible and near infrared spectra of mineral and rocks: I. Silicate minerals. Mod. Geol. 1(4):283-300.
  27. Fleming, G. A. and A. Mordenti. 1991. The Production of Animal Wastes. European Conference on Environment and Agriculture, Stock Farming in Europe, Mantua, Italy.
  28. Menzi, H. and J. Kessler. 1998. Heavy metal content of manures in Switzerland. In: Proceedings of the Eighth International Conference of the FAO Network on Recycling of Agricultural. Municipal and Industrial Residues in Agriculture.
  29. Veeken, A. and B. Hamelers. 2002. Sources of Cd, Cu, Pb and Zn in biowaste. Sci. Total Environ. 300(1-3):87-98.
  30. Davies, A. M. C. and A. Grant. 1987. Review: near infrared analysis of food. Int. J. Food Sci. Technol. 22:191-207.
  31. King, L. D., J. C. Burns and P. W. Westerman. 1990. Long-term swine lagoon effluent applications on ‘coastal’ bermudagrass : Ⅰ. Effect on nutrient accumulation in soil. J. Environ. Qual. 19:756-760.
  32. Payne, G. G., D. C. Martens, C. Winarko and N. F. Perera. 1988. Availability and form of copper in three soils following eight annual applications of copper enriched swine manure. J. Environ. Qual. 17:740-746. https://doi.org/10.2134/jeq1988.00472425001700040038x
  33. Golueke, C. G. 1973. Composting-A study of the process and its principles. Rodale Press, Emmaus, PA.
  34. CAST (Council for Agricultural Science and Technology). 1996. Integrated Animal Waste Management. Task Force Report, No. 128. Wisconsin.

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