Biology and Fertility of Soils

, Volume 44, Issue 1, pp 171–180 | Cite as

Near-infrared spectroscopy for analysis of chemical and microbiological properties of forest soil organic horizons in a heavy-metal-polluted area

  • Marcin ChodakEmail author
  • Maria Niklińska
  • Friedrich Beese
Original Paper


In industrial areas, heavy metals may accumulate in forest soil organic horizons, affecting soil microorganisms and causing changes in the chemical composition of the accumulated organic matter. The objectives of this study were to test the ability of near-infrared spectroscopy (NIRS) to detect heavy metal effects on the chemical composition of forest soil O horizons and to test whether NIRS may be used to quantitatively determine total and exchangeable concentrations of Zn and Pb (Znt, Pbt, Znex, Pbex) and other chemical and microbial properties in forest soil O horizons polluted with heavy metals. The samples of O horizons (n = 79) were analyzed for organic C (Corg), total N and S (Nt, St), Znt, Pbt, Znex, Pbex, basal respiration (BR), microbial biomass (Cmic) and Cmic-to-Corg ratio. Spectra of the samples were recorded in the Vis-NIR range (400–2,500 nm). To detect heavy-metal-induced changes in the chemical composition of O horizons principal components (PC1–PC7) based on the spectral data were regressed against Znt + Pbt values. A modified partial least squares method was used to develop calibration models for prediction of various chemical and microbial properties of the samples from their spectra. Regression analysis revealed a significant relationship between PC3 and PC5 (r = −0.27 and −0.34, respectively) and Znt + Pbt values, indicating an effect of heavy metal pollution on the spectral properties of the O horizons and thus on their chemical composition. For quantitative estimations, the best calibration model was obtained for Corg-to-Nt ratio (r = 0.98). The models for Corg, Nt, and microbial properties were satisfactory but less accurate. NIRS failed to accurately predict St, Corg-to-St, Znt, Pbt, Znex, and Pbex.


Forest soil organic horizons Soil microbial biomass Basal respiration NIR spectroscopy Heavy metal pollution 



The study was financed by the IBAES European Community Centre of Excellence at the Institute of Environmental Sciences, Jagiellonian University. Marcin Chodak acknowledges the financial support of the European Science Foundation, The Role of Soils in the Terrestrial Carbon Balance (RSTCB) Program, Grant No. 670.


  1. Anderson JPE, Domsch KH (1978) A physiological method for the quantitative measurement of microbial biomass in soils. Soil Biol Biochem 10:215–221CrossRefGoogle Scholar
  2. Bååth E (1989) Effects of heavy metals in soil on microbial processes and populations (a review). Water Air Soil Pollut 47:335–379CrossRefGoogle Scholar
  3. Beck T, Öhlinger R, Baumgarten A (1996) Substrate-Induced Respiration. In: Schinner F, Öhlinger R, Kandeler E, Margesin R (eds) Methods in Soil Biology. Springer, Berlin Heidelberg New York, pp 95–98Google Scholar
  4. Berg B, Ekbohm G, Söderstöm B, Staaf H (1991) Reduction of decomposition rates of Scots pine needle litter due to heavy-metal pollution. Water Air Soil Pollut 59:165–177CrossRefGoogle Scholar
  5. Brown DJ, Bricklemyer RS, Miller PR (2005) Validation requirements for diffuse reflectance soil characterization models with case study of VNIR soil C prediction in Montana. Geoderma 129:251–267CrossRefGoogle Scholar
  6. Brūmelis G, Lapina L, Nikodemus O, Tabors G (2002) Use of the O horizon of forest soils in monitoring metal deposition in Latvia. Water Air Soil Pollut 135:291–309CrossRefGoogle Scholar
  7. Chang CW, Laird DA (2002) Near-infrared reflectance spectroscopic analysis of soil C and N. Soil Sci 167:110–116CrossRefGoogle Scholar
  8. Chang CW, Laird DA, Mausbach MJ, Hurburgh CR (2001) Near infrared reflectance spectroscopy—principal components regression analyses of soil properties. Soil Sci Soc Am J 65:480–490CrossRefGoogle Scholar
  9. Chodak M, Ludwig B, Khanna P, Beese F (2001) Use of near infrared spectroscopy to determine biological and chemical characteristics of organic layers under spruce and beech stands. J Plant Nutr Soil Sci 165:27–33CrossRefGoogle Scholar
  10. Chodak M, Khanna P, Beese F (2003) Hot water extractable C and N in relation to microbiological properties of soils under beech forests. Biol Fertil Soils 39:123–130CrossRefGoogle Scholar
  11. Chodak M, Khanna P, Horvath B, Beese F (2004) Near infrared spectroscopy for determination of total and exchangeable cations in geologically heterogenous forest soils. J Near Infrared Spectrosc 12:315–324Google Scholar
  12. Coûteaux MM, Berg B, Rovira P (2003) Near infrared reflectance spectroscopy for determination of organic matter fractions including microbial biomass in coniferous forest soils. Soil Biol Biochem 35:1587–1600CrossRefGoogle Scholar
  13. Cozzolino D, Moron A (2004) Exploring the use of near infrared reflectance spectroscopy (NIRS) to predict trace minerals in legumes. Anim Feed Sci Technol 111:161–173CrossRefGoogle Scholar
  14. Cozzolino D, Moron A (2006) Potential of near-infrared reflectance spectroscopy and chemometrics to predict soil organic carbon fractions. Soil Tillage Res 85:78–85CrossRefGoogle Scholar
  15. Foley WJ, McIlwee A, Lawler I, Aragones L, Woolnough AP, Berding N (1998) Ecological applications of near infrared reflectance spectroscopy—a tool for rapid, cost-effective prediction of the composition of plant and animal tissues and aspects of animal performance. Oecologia 116:293–305CrossRefGoogle Scholar
  16. Friedland AJ, Johnson AH, Siccama TG, Mader DL (1984) Trace metal profiles in the forest floor of New England. Soil Sci Soc Am J 48:422–425CrossRefGoogle Scholar
  17. Gans J, Wolinsky M, Dunbar J (2005) Computational improvements reveal great bacterial diversity and high metal toxicity in soil. Science 309:1387–1390PubMedCrossRefGoogle Scholar
  18. Gong P, Siciliano SD, Srivastava S, Greer CW, Sunahara GI (2002) Assessment of pollution induced community tolerance to heavy metals in soils using ammonia-oxidizing bacteria and Biolog assay. Hum Ecol Risk Assess 8:1067–1081CrossRefGoogle Scholar
  19. Hernandez L, Probst A, Probst JL, Ulrich E (2003) Heavy metal distribution in some French forest soils: evidence for atmospheric contamination. Sci Total Environ 312:195–219PubMedCrossRefGoogle Scholar
  20. Kabata-Pendias A, Pendias H (2001) Trace elements in soils and plants, 3rd edition. CRC, Boca Raton, FloridaGoogle Scholar
  21. Kemper T, Somers S (2002) Estimate of heavy metal contamination in soils after a mining accident using reflectance spectroscopy. Environ Sci Technol 36:2742–2747PubMedCrossRefGoogle Scholar
  22. Knight BR, McGrath SP, Chaudri AM (1997) Biomass carbon measurements and substrate utilization patterns of microbial populations from soils amended with cadmium, copper or zinc. Appl Environ Microbiol 63:39–43PubMedGoogle Scholar
  23. Kooistra L, Wehrens R, Leuven RSEW, Buydens LMC (2001) Possibilities of visible-near-infrared spectroscopy for the assessment of soil contamination in river floodplains. Anal Chim Acta 446:97–105CrossRefGoogle Scholar
  24. Laskowski R, Maryański M, Niklińska M (1994) Effect of heavy metals and mineral nutrients on forest litter respiration rate. Environ Pollut 84:97–102PubMedCrossRefGoogle Scholar
  25. Ludwig B, Khanna PK (2001) Use of near infrared spectroscopy to determine inorganic and organic carbon fractions in soil and litter. In: Lal R, Kimble JM, Follett RF, Stewart BA (eds) Assessment methods for soil carbon. CRC/Lewis Publishers, Boca Raton, FL, pp 361–370Google Scholar
  26. Ludwig B, Khanna PK, Bauhus J, Hopmans P (2002) Near infrared spectroscopy of forest soils to determine chemical and biological properties related to soil sustainability. For Ecol Manag 171:121–132CrossRefGoogle Scholar
  27. Malley DF (1998) Near-infrared spectroscopy as a potential method for routine sediment analysis to improve rapidity and efficiency. Water Sci Technol 37:181–188CrossRefGoogle Scholar
  28. Malley DF, Williams PC (1997) Use of near-infrared spectroscopy in prediction of heavy metals in freshwater sediment by their association with organic matter. Environ Sci Technol 31:3461–3467CrossRefGoogle Scholar
  29. Moron A, Cozzolino D (2003) Exploring the use of near infrared reflectance spectroscopy to study physical properties and microelements in soils. J Near Infrared Spectrosc 11:145–154Google Scholar
  30. Niklińska M, Chodak M, Laskowski R (2005) Characterization of the forest humus microbial community in a heavy metal polluted area. Soil Biol Biochem 37:2185–2194CrossRefGoogle Scholar
  31. Nordgren A, Kauri T, Bååth E, Söderström B (1986) Soil microbial activity, mycelial lengths and physiological groups of bacteria in heavy metal polluted area. Environ Pollut A 41:89–100CrossRefGoogle Scholar
  32. Odlare M, Svensson K, Pell M (2005) Near infrared reflectance spectroscopy for assessment of spatial soil variation in an agricultural field. Geoderma 126:193–202CrossRefGoogle Scholar
  33. Öhlinger R (1996) Soil respiration by titration. In: Schinner F, Öhlinger R, Kandeler E, Margesin R (eds) Methods in soil biology. Springer, Berlin Heidelberg New York, pp 95–98Google Scholar
  34. Osborne BG, Fearn T (1986) Near infrared spectroscopy in food analysis. Longman Scientific and Technical, EssexGoogle Scholar
  35. Palmborg C, Nordgren A (1996) Partitioning the variation of microbial measurements in forest soil into heavy metal and substrate quality dependent parts by use of near infrared spectroscopy and multivariate statistics. Soil Biol Biochem 28:711–720CrossRefGoogle Scholar
  36. Pennanen T, Frostegård Å, Fritze H, Bååth E (1996) Phospholipid fatty acids and heavy metal tolerance of soil microbial communities along two heavy metal-polluted gradients in coniferous forests. Appl Environ Microbiol 62:420–428PubMedGoogle Scholar
  37. Shenk JS, Westerhaus MO (1991) Population definition, sample selection, and calibration procedure for near infrared reflectance spectroscopy. Crop Sci 31:469–474CrossRefGoogle Scholar
  38. Shenk JS, Westerhaus MO (1993) Analysis of agriculture and food products by near infrared reflectance spectroscopy. Infrasoft, Port MatildaGoogle Scholar
  39. Shenk JS, Workman Jr JJ, Westerhaus MO (1992) Application of NIR spectroscopy to agricultural products. In: Burns DA, Ciurczak EW (eds) Handbook of near-infrared analysis. Marcel Dekker, New York, pp 383–431Google Scholar
  40. Siebielec G, McCarty GW, Stuczynski TI, Reeves III JB (2004) Near- and Mid-infrared diffuse reflectance spectroscopy for measuring soil metal content. J Environ Qual 33:2056–2069PubMedCrossRefGoogle Scholar
  41. Simonsson M, Kaiser K, Danielsson R, Andreux F, Ranger J (2005) Estimating nitrate, dissolved organic carbon and DOC fractions in forest floor leachates using ultraviolet absorbance spectra and multivariate analysis. Geoderma 124:157–168CrossRefGoogle Scholar
  42. Terhoeven-Urselmans T, Kerstin M, Helfrich M, Flessa H, Ludwig B (2006) Near-infrared spectroscopy can predict the composition of organic matter in soil and litter. J Plant Nutr Soil Sci 169:168–174CrossRefGoogle Scholar
  43. Timm NH (2002) Applied multivariate statistics. Springer, Berlin Heidelberg New York, pp 720Google Scholar
  44. Viscarra Rossel RA, Walvoort DJJ, McBratney AB, Janik LJ, Skjemstad JO (2006) Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties. Geoderma 131:59–75CrossRefGoogle Scholar
  45. Weyer L, Lo S-C (2002) Spectra-structure correlations in the near-infrared. In: Handbook of vibrational spectroscopy, vol 3. Wiley, UK, pp 1817–1837Google Scholar
  46. Workman Jr JJ (1993) A brief review of the near infrared measurement technique. NIR news 4:8–16Google Scholar
  47. Workman J (2000) Handbook of organic compounds: NIR, IR, Raman, and UV–vis spectra featuring polymers and surfactants, vol 1. Academic, pp 77–197Google Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Marcin Chodak
    • 1
    Email author
  • Maria Niklińska
    • 2
  • Friedrich Beese
    • 3
  1. 1.Department of Open-strip MiningAGH University of Science and TechnologyKrakówPoland
  2. 2.Institute of Environmental SciencesJagiellonian UniversityKrakówPoland
  3. 3.Institute of Soil Science and Forest NutritionUniversity of GöttingenGöttingenGermany

Personalised recommendations