Fourier Transform Infrared—Attenuated Total Reflection Nitrate Determination of Soil Pastes Using Principal Component Regression,Partial Least Squares,and Cross-Correlation

Abstract

This paper investigates the use of Fourier transform infrared (FT-IR) attenuated total reflectance (ATR) spectroscopy as a fast and simple way for direct determination of nitrate concentration in soil pastes, which would assist precision fertilizer placement and reduce nitrate pollution. Eight types of soils are investigated, with nitrate concentrations ranging from 0 to 1000 ppm-N. The spectral region around the nitrate band (1300–1550 cm⁻¹) is analyzed by (1) principal component regression (PCR), (2) partial least squares (PLS), and (3) cross-correlation with reference libraries that include spectra of pure ions and/or soils. The main obstacle to accurate nitrate measurement appears to be an interfering band present in calcareous soils. This band, which may be due to carbonate, is located around 1450 cm⁻¹ and overlaps with the nitrate band centered around 1370 cm⁻¹. For non-calcareous soils, and in particular for light sandy agricultural soils, PLS and cross-correlation with a reference library containing only spectra of ions in water give similar results (about 8 ppm-N on dry soil basis), while PCR leads to slightly poorer results. When calcareous soils are included in the analysis, the prediction errors are about twice as large. In this case, the best results are obtained using PLS, followed by PCR, while cross-correlation with reference libraries leads to poorer results.

Keywords

Chemometrics Mid-infrared Calcareous soil Precision fertilizer placement

References

Forman

Al-Dabbagh

and Doll

, Nature (London) 313, 620 (1985).

Addiscott

T. M.

Whitmore

A. P.

and Powlson

D. S

, Farming, Fertilizers and the Nitrate Problem (C.A.B. International, Wallingford, UK, 1991).

Castelnuovo

, “Environment concerns driving site-specific management in agriculture”, in Proceedings of the Second International Conference on Site-Specific Management for Agricultural Systems, Robert

P. C.

Rush

R. H.

and Larson

W. E

, Eds. (ASA-CSSA-SSSA, Madison, Wisconsin, 1995), p. 867.

Smil

, Global Biogeochem. Cycles 13, 647 (1999).

Robert

P. C.

, Plant Soil 247, 143 (2002).

Roblin

and Barrow

D. A

, J. Environ. Monitor. 2, 385 (2000).

Adsett

J. F.

and Zoerb

J. C

, “Automated field monitoring of soil nitrate levels”, in Automated Agriculture for the 21st Century, Proceeding of the 1991 Symposium (ASAE, St. Joseph, Michigan, 1991), p. 326.

Price

R. R.

Hummel

J. W.

Birrell

S. J.

and Ahmad

I. S

, Trans. ASAE 46, No. 3, 601 (2003).

Ehsani

M. R.

Upadhyaya

S. K.

Slaughter

Protsailo

L. V.

and Fawcett

W. R

, Trans. ASAE 44, No. 6, 1931 (2001).

10.

Shibusawa

Anom

S. W. Imade

Sato

Sasao

and Hirako

, “Soil mapping using the real-time soil spectrophotometer”, in Proceedings of the Third European Conference on Precision Agriculture (Agro Montpellier, Montpellier, France, 2001), p. 485.

11.

Shaviv

Kenny

Shmulevitz

Singher

Reichlin

and Katzir

, Environ. Sci. Technol. 37, 2807 (2003).

12.

Messica

Greenstein

and Katzir

, Appl. Opt. 35, 2274 (1996).

13.

Linker

Shmulevitz

Kenny

and Shaviv

, “Data processing of FTIR/ATR measurements of nitrate concentration in soils”, Trans. ASAE, paper submitted (2003).

14.

Page

A. L.

Miller

R. H.

and Keeney

D. R

, Methods of soil analysis—Part 2 (Madison, Wisconsin, 1982), 2nd ed., p. 167.

15.

Rahmelow

and Hübner

, Appl. Opt. 51, 160 (1997).

16.

Jolliffe

I. T.

, Principal Component Analysis (Springer-Verlag, New York, 1986).

17.

Haaland

D. M.

and Thomas

E. V

, Anal. Chem. 60, 1193 (1988).

18.

Smith

S. W.

, The Scientist and Engineer's Guide to Digital Signal Processing (California Technical Publishing, San Diego, California, 1997).