Use of handheld mid-infrared spectroscopy and partial least-squares regression for the prediction of the phosphorus buffering index in Australian soils
Sean T. Forrester A , Les J. Janik A , José M. Soriano-Disla A B C G , Sean Mason C , Lucy Burkitt D , Phil Moody E , Cameron J. P. Gourley F and Michael J. McLaughlin A C
+ Author Affiliations
- Author Affiliations
A Contaminant Biogeochemistry and Environmental Toxicology Group, CSIRO Land and Water, Waite Campus, Waite Road, Urrbrae, SA 5064, Australia.
B Department of Agrochemistry and Environment, University Miguel Hernández of Elche. Avenuenida de la Universidad S/N, 03202. Elche, Spain.
C University of Adelaide, PMB 2, Glen Osmond, SA 5064, Australia.
D Fertiliser and Lime Research Centre, Massey University, Private Bag 11222, Palmerston North, 4442, New Zealand.
E Science Division, DSITIA, 41 Boggo Road, Dutton Park, Qld 4102, Australia.
F Victorian Department of Environment and Primary Industries, RMB 2460, Ellinbank, Vic. 3821, Australia.
G Corresponding author. Email: jose.sorianodisla@csiro.au
Soil Research 53(1) 67-80 https://doi.org/10.1071/SR14126
Submitted: 9 May 2014 Accepted: 14 September 2014 Published: 12 January 2015
Abstract
The development of techniques for the rapid, inexpensive and accurate determination of the phosphorus (P) buffer index (PBI) in soils is important in terms of increasing the efficiency of P application for optimum crop requirements and preventing environmental pollution due to excessive use of P fertilisers. This paper describes the successful implementation of partial least-squares regression (PLSR) from spectra obtained with bench-top and handheld mid-infrared (MIR) spectrometers for the prediction of PBI on 601 representative Australian agricultural soils. By contrast, poor predictions were obtained for available (Colwell) P. Regression models were successfully derived for PBI ranges of 0–800 and 0–150, the latter range resulting in the optimum model considering the dominance of low PBI soils in the sample set. Concentrations of some major soil minerals (mainly kaolinite and gibbsite content for high PBI, and smectites or illites for low PBI), quartz (representative of low surface area of soils) and, to a lesser extent, carbonate and soil organic matter were identified as the main drivers of the PBI models. Models developed with soils sieved to <2 mm presented an accuracy similar to those developed using fine-ground material. The accuracy of the PLSR for the prediction of PBI by using bench-top and handheld instruments was also similar. Our results confirm the possibility of using MIR spectroscopy for the onsite prediction of PBI.
Additional keywords: Al and Fe oxyhydroxides, available phosphorus, particle size, phosphorus buffering capacity, phosphorus sorption, portable MIR.
References
Bainbridge SH, Miles N, Praan R, Johnston MA (1995) Phosphorus sorption in Natal soils. South African Journal of Plant and Soil 12, 59–64.| Phosphorus sorption in Natal soils.Crossref | GoogleScholarGoogle Scholar |
Baldock JA, Hawke B, Sanderman J, MacDonald LM (2013) Predicting contents of carbon and its component fractions in Australian soils from diffuse reflectance mid-infrared spectra. Soil Research 51, 577–595.
| Predicting contents of carbon and its component fractions in Australian soils from diffuse reflectance mid-infrared spectra.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhvF2ktbjF&md5=2a6c39456d630d51199f3e3996673613CAS |
Barnes RJ, Dhanoa MS, Lister SJ (1993) Correction of the description of Standard Normal Variate (SNV) and De-Trend Transformations in Practical spectroscopy with applications in food and beverage analysis, 2nd edn. Journal of Near Infrared Spectroscopy 1, 185–186.
Barrow NJ (1978) The description of phosphate adsorption curves. Journal of Soil Science 29, 447–462.
| The description of phosphate adsorption curves.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaE1MXhtlKlsb8%3D&md5=f1694c9046a110020d9eea03b6337ca7CAS |
Bertrand I, Holloway RE, Armstrong RD, McLaughlin MJ (2003) Chemical characteristics of phosphorus in alkaline soils from southern Australia. Australian Journal of Soil Research 41, 61–76.
| Chemical characteristics of phosphorus in alkaline soils from southern Australia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXitVygsrg%3D&md5=aaa29848a91c66142715782e9368f5b9CAS |
Bolland MD, Gilkes RJ, Brennan RF, Allen DG (1996) Comparison of seven phosphorus sorption indices. Australian Journal of Soil Research 34, 81–89.
| Comparison of seven phosphorus sorption indices.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK28Xhs1yhs70%3D&md5=40494986df303c5fbcf1013aae242d04CAS |
Bomans E, Fransen K, Gobin A, Mertens J, Michiels P, Vandendriessche H, Vogels N (2005) Addressing phosphorus related problems in farm practice. Final Report to the European Commission. Available at: http://ec.europa.eu/environment/natres/pdf/phosphorus/AgriPhosphorusReport%20final.pdf
Brunet D, Barthès BG, Chotte JL, Feller C (2007) Determination of carbon and nitrogen contents in Alfisols, Oxisols and Ultisols from Africa and Brazil using NIRS analysis: Effects of sample grinding and set heterogeneity. Geoderma 139, 106–117.
| Determination of carbon and nitrogen contents in Alfisols, Oxisols and Ultisols from Africa and Brazil using NIRS analysis: Effects of sample grinding and set heterogeneity.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXjvVagtb4%3D&md5=8be13279219135e0101211d7576cf493CAS |
Burkitt LL, Moody PW, Gourley CJP, Hannah MC (2002) A simple phosphorus buffering index for Australian soils. Australian Journal of Soil Research 40, 497–513.
| A simple phosphorus buffering index for Australian soils.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38Xks1eksL0%3D&md5=3da2294973ef1cb71f6a10be9c80e6b6CAS |
Burkitt LL, Gourley CJP, Hannah MC, Sale PWG (2006) Assessing alternative approaches to predicting soil phosphorus sorption. Soil Use and Management 22, 325–333.
| Assessing alternative approaches to predicting soil phosphorus sorption.Crossref | GoogleScholarGoogle Scholar |
Burkitt LL, Sale PWG, Gourley CJP (2008) Soil phosphorus buffering measures should not be adjusted for current phosphorus fertility. Australian Journal of Soil Research 46, 676–685.
| Soil phosphorus buffering measures should not be adjusted for current phosphorus fertility.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXhsVCms7%2FF&md5=b50bf1ada0b4d18720d0283461620662CAS |
Burkitt LL, Dougherty WJ, Carlson SM, Donaghy DJ (2010) Effect of variable soil phosphorus on phosphorus concentrations in simulated surface runoff under intensive dairy pastures. Australian Journal of Soil Research 48, 231–237.
| Effect of variable soil phosphorus on phosphorus concentrations in simulated surface runoff under intensive dairy pastures.Crossref | GoogleScholarGoogle Scholar |
Cohen MJ, Paris J, Clark MW (2007) P-sorption capacity estimation in southeastern USA wetland soils using visible/near infrared (VNIR) reflectance spectroscopy. Wetlands 27, 1098–1111.
| P-sorption capacity estimation in southeastern USA wetland soils using visible/near infrared (VNIR) reflectance spectroscopy.Crossref | GoogleScholarGoogle Scholar |
Colwell JD (1963) The estimation of the phosphorus fertiliser requirements of wheat in southern New South Wales by soil analysis. Australian Journal of Experimental Agriculture and Animal Husbandry 6, 105–120.
Cox FR (1994) Predicting increases in extractable phosphorus from fertilizing soils of varying clay content. Soil Science Society of America Journal 58, 1249–1253.
| Predicting increases in extractable phosphorus from fertilizing soils of varying clay content.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK2cXlsFKnur4%3D&md5=c98908967b648fdfc03fa5b025d4cbe2CAS |
Crawley MJ (2007) ‘The R Book.’ (John Wiley & Sons: Chichester, UK)
Forrester S, Janik L, Beech A, Merry R, McLaughlin M, Burkitt L, Gourley C (2003) Prediction of a range of phosphorus buffering techniques using mid-infrared spectroscopy. In ‘Tools for nutrient and pollutant management: Applications to agriculture and environmental quality’. Occasional Report No. 17. (Eds LD Currie, JA Hanly) (Fertiliser and Lime Research Centre, Massey University: Palmerston North, New Zealand)
Forrester S, Janik L, McLaughlin M (2010a) Mid-infrared spectroscopic analysis of soils—from the laboratory to the field. In ‘The environment—the future’. Australasian Soil & Plant Analysis Council Inc. (ASPAC) Conference, Canberra. (ASPAC: Carapook, Vic.)
Gourley CJP, Melland AM, Waller RA, Awty IM, Smith AP, Peverill KI, Hannah MC (2006) Making better fertiliser decisions for grazed pastures in Australia. Australian Soil Resource Information System. Available at: www.asris.csiro.au/themes/nutrient.html (accessed 12 August 2014)
Hart M, Cornish P (2012) Available soil phosphorus, phosphorus buffering and soil cover determine most variation in phosphorus concentration in runoff from pastoral sites. Nutrient Cycling in Agroecosystems 93, 227–244.
| Available soil phosphorus, phosphorus buffering and soil cover determine most variation in phosphorus concentration in runoff from pastoral sites.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38XpvVyqtbY%3D&md5=6aaf97c539e4a9a5612a5c46b80bf925CAS |
Isbell RF (1996) ‘The Australian Soil Classification.’ (CSIRO Publishing: Melbourne)
Janik LJ, Skjemstad JO (1995) Characterization and analysis of soils using mid-infrared partial least-squares. II. Correlations with some laboratory data. Australian Journal of Soil Research 33, 637–650.
| Characterization and analysis of soils using mid-infrared partial least-squares. II. Correlations with some laboratory data.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK2MXotlygtbw%3D&md5=7859efc46a0ee1ec0a75aa309afe053aCAS |
Janik LJ, Merry RH, Skjemstad JO (1998) Can mid infrared diffuse reflectance analysis replace soil extractions? Australian Journal of Experimental Agriculture 38, 681–696.
| Can mid infrared diffuse reflectance analysis replace soil extractions?Crossref | GoogleScholarGoogle Scholar |
Janik LJ, Forrester ST, Rawson A (2009) The prediction of soil chemical and physical properties from mid-infrared spectroscopy and combined partial least-squares regression and neural networks (PLS-NN) analysis. Chemometrics and Intelligent Laboratory Systems 97, 179–188.
| The prediction of soil chemical and physical properties from mid-infrared spectroscopy and combined partial least-squares regression and neural networks (PLS-NN) analysis.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXmtlWmtLY%3D&md5=4d3345722205c8a48f43f0200356aa53CAS |
Kuang B, Mahmood HS, Quraishi MZ, Hoogmoed WB, Mouazen AM, van Henten EJ (2012) Sensing soil properties in the laboratory, in situ, and on-line. A review. Advances in Agronomy 114, 155–223.
| Sensing soil properties in the laboratory, in situ, and on-line. A review.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38Xhs12lsr%2FI&md5=15817ae2ddc4717cc8dce9ba078cce6cCAS |
Kudeyarova AY, Davydkina LV, Kvartskheliya MZ, Korbacheva II (1991) Ability of phosphate to replace organic compounds in soil organomineral complexes. USSR Academy of Sciences, Translated from Pochvovedeniye 2, 31–44.
Lins IDG, Cox FR (1989) Effect of extractant and selected soil properties on predicting the optimum phosphorus fertiliser rate for growing soybeans under field conditions. Communications in Soil Science and Plant Analysis 20, 319–333.
| Effect of extractant and selected soil properties on predicting the optimum phosphorus fertiliser rate for growing soybeans under field conditions.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaL1MXptl2hug%3D%3D&md5=1727930c7db0fb59de458a0e4e2b4d89CAS |
Maindonald J, Braun J (2010) ‘Data analysis and graphics using R: An example-based approach.’ (Cambridge University Press: Cambridge, UK)
McKeague JA, Day JH (1966) Dithionite and oxalate extractable Fe and Al as aids in differentiating various classes of soils. Canadian Journal of Soil Science 46, 13–22.
| Dithionite and oxalate extractable Fe and Al as aids in differentiating various classes of soils.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaF28XktVeit78%3D&md5=5a82a7358f4318de1964c6018804ea0dCAS |
McLaughlin JR, Ryden JC, Syers JK (1981) Sorption of inorganic phosphate by iron- and aluminium- containing components. Journal of Soil Science 32, 365–378.
| Sorption of inorganic phosphate by iron- and aluminium- containing components.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaL3MXlvFSgtbg%3D&md5=af496065b6f34dd4c26a5c198881a7d1CAS |
McLaughlin MJ, McBeath TM, Smernik R, Stacey SP, Ajiboye B, Guppy C (2011) The chemical nature of P accumulation in agricultural soils-implications for fertiliser management and design: An Australian perspective. Plant and Soil 349, 69–87.
| The chemical nature of P accumulation in agricultural soils-implications for fertiliser management and design: An Australian perspective.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXhsFKntbzP&md5=1bb1f16510cc3e8270adeca83f7f3096CAS |
Minasny B, Tranter G, McBratney AB, Brough DM, Murphy BW (2009) Regional transferability of mid-infrared diffuse reflectance spectroscopic prediction for soil chemical properties. Geoderma 153, 155–162.
| Regional transferability of mid-infrared diffuse reflectance spectroscopic prediction for soil chemical properties.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXht1SktL%2FP&md5=a6d115ffa1ac7ae18c83ee29296cc8a0CAS |
Moody PW (2007) Interpretation of a single-point P buffering index for adjusting critical levels of the Colwell soil P test. Australian Journal of Soil Research 45, 55–62.
| Interpretation of a single-point P buffering index for adjusting critical levels of the Colwell soil P test.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXhs1yqsL0%3D&md5=013d10d20d81ace42ab414993aa53486CAS |
Moody PW, Speirs S, Scott BJ, Mason SD (2013) Soil phosphorus tests I: What soil phosphorus pools and processes do they measure? Crop & Pasture Science 64, 461–468.
| Soil phosphorus tests I: What soil phosphorus pools and processes do they measure?Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhtlakt7zF&md5=33dda298b8c289a6522839938c0f4a49CAS |
Nduwamungu C, Ziadi N, Tremblay GF, Parent LÉ, Tremblay GF, Thuriès B (2009) Near-infrared reflectance spectroscopy prediction of soil properties: Effects of sample cups and preparation. Soil Science Society of America Journal 73, 1896–1903.
| Near-infrared reflectance spectroscopy prediction of soil properties: Effects of sample cups and preparation.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhsVSku7vM&md5=7a8e009e99fd631bc7b7688a53ed07c0CAS |
Nguyen TT, Janik LJ, Raupach M (1991) Diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy in soil studies. Australian Journal of Soil Research 29, 49–67.
| Diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy in soil studies.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK3MXhvV2nsbk%3D&md5=da4bd750dee0fc8ffe4da79c08bf7486CAS |
Ozanne PG (1980) Phosphate nutrition of plants—A general treatise. In ‘The role of phosphorus in agriculture’. pp. 559–589. (American Society of Agronomy/Crop Science Society of America/Soil Science Society of America: Madison, WI, USA)
Reeves JB (2010) Near- versus mid-infrared diffuse reflectance spectroscopy for soil analysis emphasizing carbon and laboratory versus on-site analysis: Where are we and what needs to be done? Geoderma 158, 3–14.
| Near- versus mid-infrared diffuse reflectance spectroscopy for soil analysis emphasizing carbon and laboratory versus on-site analysis: Where are we and what needs to be done?Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXnvFWhsr0%3D&md5=5b81b7590eff94a07358016e2a21ae9cCAS |
Reeves JB, McCarty GW, Reeves VB (2001) Mid-infrared diffuse reflectance spectroscopy for the quantitative analysis of agricultural soils. Journal of Agricultural and Food Chemistry 49, 766–772.
| Mid-infrared diffuse reflectance spectroscopy for the quantitative analysis of agricultural soils.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3MXmsVeltA%3D%3D&md5=70d221bf6e20feef2d6641f610097483CAS | 11262026PubMed |
Reeves JB, McCarty GW, Hively WD (2010) Mid- versus near-infrared spectroscopy for on-site analysis of soil. In ‘Proximal soil sensing’. (Eds RA Viscarra-Rossel, AB McBratney, B Minasny) pp. 133–142. (Springer Science+Business Media: New York)
Ryan J, Curtin D, Cheema MA (1984) Significance of iron oxides and calcium carbonate particle size in phosphate sorption by calcareous soils. Soil Science Society of America Journal 48, 74–76.
Samadi A, Gilkes RJ (1998) Forms of phosphorus in virgin and fertilized calcareous soils of Western Australia. Australian Journal of Soil Research 36, 585–601.
| Forms of phosphorus in virgin and fertilized calcareous soils of Western Australia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK1cXks1Kitrw%3D&md5=63a1f780c547c3aa4b445d3663af779cCAS |
Scheinost AC, Schwertmann U (1995) Predicting phosphate adsorption–desorption in a soilscape. Soil Science Society of America Journal 59, 1575–1580.
| Predicting phosphate adsorption–desorption in a soilscape.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK2MXpvVSru7o%3D&md5=978460b9a3b881a0b817f0c361f49d55CAS |
Sibanda HM, Young SD (1986) Competitive adsorption of humus acids and phosphate on goethite, gibbsite and two tropical soils. Journal of Soil Science 37, 197–204.
| Competitive adsorption of humus acids and phosphate on goethite, gibbsite and two tropical soils.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaL28XltFChs74%3D&md5=fb4f661769ad5bbdfe6cc1eed134553bCAS |
Smith RJ (1993) Logarithmic transformation bias in allometry. American Journal of Physical Anthropology 90, 215–228.
| Logarithmic transformation bias in allometry.Crossref | GoogleScholarGoogle Scholar |
Soriano-Disla JM, Janik L, Viscarra Rossel RA, McDonald LM, McLaughlin MJ (2014) The performance of visible, near and mid-infrared spectroscopy for prediction of soil physical, chemical and biological properties. Applied Spectroscopy Reviews 49, 139–186.
| The performance of visible, near and mid-infrared spectroscopy for prediction of soil physical, chemical and biological properties.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhtVCrtLfF&md5=2c2bf807227ac09e06390b60819a56d3CAS |
Speirs SD, Scott BJ, Moody PW, Mason SD (2013) Soil phosphorus tests II: A comparison of soil test-crop response relationships for different soil tests and wheat. Crop & Pasture Science 64, 469–479.
| Soil phosphorus tests II: A comparison of soil test-crop response relationships for different soil tests and wheat.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhtlakt7%2FJ&md5=014020b140f1ff1b1fd7eecc27a378e5CAS |
Stenberg B, Viscarra-Rossel RA (2010) Diffuse reflectance spectroscopy for high-resolution soil sensing. In ‘Proximal soil sensing. Progress in soil science 1’. (Ed. RA Viscarra-Rossel) pp. 29–47. (Springer Science+Business Media: New York)
Stenberg B, Viscarra-Rossel RA, Mouazen AM, Wetterling J (2010) Visible and near-infrared spectroscopy in soil science. Advances in Agronomy 107, 163–215.
| Visible and near-infrared spectroscopy in soil science.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXht1yht7bE&md5=abae79ada2e77ec45cdd3d649f7e34fcCAS |
Stumpe B, Weihermüller L, Marschner B (2011) Sample preparation and selection for qualitative and quantitative analyses of soil organic carbon with mid-infrared reflectance spectroscopy. European Journal of Soil Science 62, 849–862.
| Sample preparation and selection for qualitative and quantitative analyses of soil organic carbon with mid-infrared reflectance spectroscopy.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38Xmt1answ%3D%3D&md5=a27d24f83d3dffc3c366ca5005c9a18dCAS |
Sudduth KA, Hummel JW (1996) Geographic operating range evaluation of a NIR soil sensor. Transactions of the American Society of Agricultural Engineers 39, 1599–1604.
| Geographic operating range evaluation of a NIR soil sensor.Crossref | GoogleScholarGoogle Scholar |
Uehara G, Gillman G (1981) ‘The mineralogy, chemistry, and physics of tropical soils with variable charge clays.’ pp. 31–95. (Westview Press: Boulder, CO, USA)
Van der Marel HW, Beutelspacher H (1976) Clay and related minerals. In ‘Atlas of infrared spectroscopy of clay minerals and their admixtures’. (Eds HW Van der Marel, H Beutelspacher) (Elsevier Scientific: Amsterdam, The Netherlands)
Varmuza K, Filmoser P (2009) ‘Introduction to multivariate statistical analysis in chemometrics.’ (Taylor & Francis Group: Boca Raton, FL, USA)
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, 59–75.
| Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28XhtFyhsLg%3D&md5=2a0cca6f01847a9e287cba4fe7a79278CAS |
Whitehead DC (2000) Phosphorus. In ‘Nutrient elements in grassland: Soil-plant-animal relationships’. (Ed. DC Whitehead) pp. 126–153. (CAB International: Wallingford, UK)
Williams PC (1987) Variables affecting near-infrared reflectance spectroscopy. In ‘Near-infrared technology in the agricultural and food industries’. (Eds PC Williams, KH Norris) pp. 143–167. (American Association of Cereal Chemist Inc.: St Paul, MN, USA)
