Application of near‐infrared spectroscopy in analysis of soil mineral nutrients

Malley, D. F.; Yesmin, Laila; Wray, David S.; Edwards, Scott

doi:10.1080/00103629909370263

Cited by 95 publications

(63 citation statements)

References 8 publications

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“…In recent years, attempts have been made to relate NIR-spectra to N-uptake in crops within single fields, with promising results (Börjesson et al, 1999;Dunn et al, 2000). NIR-spectra have been related to several soil properties that can be expected to have influence on plant available N, such as amount and quality of organic matter (Chang and Laird, 2002;Fystro, 2002;Palmborg and Nordgren, 1993), soil texture (Chang et al, 2001;Stenberg et al, 1995) and nutrient status (Malley et al, 1999). Börjesson et al (1999) compared the performance of NIR-models with potential net N-mineralization, organic matter content and initial mineral N present in the soil profile at the beginning of the cropping season in order to predict N-uptake by the crop, and found NIR and initial mineral N to have the best predictive ability and to be equally good.…”

Section: Introductionmentioning

confidence: 99%

Use of near infrared reflectance spectroscopy to predict nitrogen uptake by winter wheat within fields with high variability in organic matter

Stenberg¹,

Jönsson²,

Börjesson³

2005

Plant Soil

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. (2005) Use of near infrared reflectance spectroscopy to predict nitrogen uptake by winter wheat within fields with high variability in organic matter. Plant and Soil. Volume: 269, pp 251-258. http://dx.doi.org/10.1007/s11104-004-0556-1.Access to the published version may require journal subscription. Published with permission from: Springer.Standard set statement from the publisher: "An author may self-archive an author-created version of his/her article on his/her own website and or in his/her institutional repository. He/she may also deposit this version on his/her funder's or funder's designated repository at the funder's request or as a result of a legal obligation, provided it is not made publicly available until 12 months after official publication. He/ she may not use the publisher's PDF version, which is posted on www.springerlink.com, for the purpose of self-archiving or deposit. Furthermore, the author may only post his/her version provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at www.springerlink.com".Prior versions of the article published on non-commercial preprint servers like arXiv.org can remain on these servers and/or can be updated with the author's accepted version. The final published version (in PDF or HTML/XML format) cannot be used for this purpose. Acknowledgement needs to be given to the final publication and a link should be inserted to the published article on Springer's website, accompanied by the text "The final publication is available at www.springerlink.com". AbstractIn this study, the ability to predict N-uptake in winter wheat crops using NIR-spectroscopy on soil samples was evaluated. Soil samples were taken in unfertilized plots in one winter wheat field during three years (1997)(1998)(1999) and in another winter wheat field nearby in one year (2000). Soil samples were analyzed for organic C content and their NIR-spectra. N-uptake was measured as total N-content in aboveground plant materials at harvest. Models calibrated to predict N-uptake were internally cross validated and validated across years and across fields. Cross-validated calibrations predicted N-uptake with an average error of 12.1 to 15.4 kg N ha -1 . The standard deviation divided by this error (RPD) ranged between 1.9 and 2.5. In comparison, the corresponding calibrations based on organic C alone had an error from 11.7 to 28.2 kg N ha -1 and RPDs from 1.3 to 2.5. In three of four annual calibrations within a field, the NIR-based calibrations worked better than the organic C based calibrations. The prediction of N-uptake across years, but within a field, worked slightly better with an organic C based calibration than with a NIR based one, RPD = 1.9 and 1.7 respectively. Across fields, the corresponding difference was large in favour of the NIR-calibration, RPD = 2.5 for the NIR-calibration and 1.5 for the organic C calibration. ...

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Section: Introductionmentioning

confidence: 99%

Use of near infrared reflectance spectroscopy to predict nitrogen uptake by winter wheat within fields with high variability in organic matter

Stenberg¹,

Jönsson²,

Börjesson³

2005

Plant Soil

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“…literature, sodium (Na ex ) and potassium (K ex ) are among the most difficult properties to be measured with the NIR spectroscopy (Malley et al, 1999;Chang et al, 2001;Zornoza et al, 2008;Pirie et al, 2005;Dunn et al, 2002;Shepherd & Walsh, 2002;Islam et al, 2003;Volkan et al, 2010;. For the same soil property, laboratory vis-NIR methods achieved higher accuracy as compared to measurement under field soil conditions, particularly with on-line vis-NIR sensors Kuang et al, 2012).…”

mentioning

confidence: 99%

On-line measurement of soil properties without direct spectral response in near infrared spectral range

Marín-González

Kuang

Quraishi

et al. 2013

Soil and Tillage Research

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This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues.Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited.

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“…Furthermore, their results revealed the feasibility to predict heavy metals in contaminated soils using the rapid and cost-effective NIRS. Other applications are reported by Malley et al [40] and Choe et al [41].…”

Section: Applications Of Nirs-multi-linear Regression Determination Tmentioning

confidence: 89%

“…To overcome these challenges, some chemometric tools have been used to be applied to the quantitative analysis of the spectroscopic data [38]. These chemometric tools include multiple linear regression (MLR) [39], principal component regression (PCR) [40,41], and partial least squares (PLS) regression [42]. These chemometric tools have been used to characterize soil spectra and build models for estimating the trace metal concentrations in soil or sediments and other matrices [25].…”

Section: Application Of Near-infrared Spectroscopy (Nirs) For Analysimentioning

confidence: 99%

Near-Infrared Spectroscopy Combined with Multivariate Tools for Analysis of Trace Metals in Environmental Matrices

Nomngongo¹,

Munonde²,

Mpupa³

et al. 2017

Developments in Near-Infrared Spectroscopy

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Environmental contamination by trace elements is becoming increasingly important problem worldwide. Trace metals such as cadmium, copper, lead, chromium, and mercury are major environmental pollutants that are predominantly found in areas with high anthropogenic activities. Therefore, there is a need for rapid and reliable tools to assess and monitor the concentration of heavy metal in environmental matrices. A nondestructive, cost-effective, and environmentally friendly procedure based on near-infrared reflectance spectroscopy (NIRS) and chemometric tools has been used as alternative technique for the simultaneous estimation of various heavy metal concentrations in environmental sample. The metal content is estimated by assigning the absorption features of metals associated with molecular vibrations of organic and inorganic functional groups in organic matter, silicates, carbonates, and water at 780-2500 nm in the near-infrared region.This chapter, reviewed the application of NIRS combined with chemometric tools such as multiple linear regression (MLR), principal component regression (PCR), and partial least squares (PLS) regression. The disadvantages and advantages of each chemometric tool are discussed briefly.

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Application of near‐infrared spectroscopy in analysis of soil mineral nutrients

Cited by 95 publications

References 8 publications

Use of near infrared reflectance spectroscopy to predict nitrogen uptake by winter wheat within fields with high variability in organic matter

Use of near infrared reflectance spectroscopy to predict nitrogen uptake by winter wheat within fields with high variability in organic matter

On-line measurement of soil properties without direct spectral response in near infrared spectral range

Near-Infrared Spectroscopy Combined with Multivariate Tools for Analysis of Trace Metals in Environmental Matrices

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