Literature DB >> 19691675

Prediction of delta(13)C and delta(15)N in plant tissues with near-infrared reflectance spectroscopy.

Till Kleinebecker1, Sebastian R Schmidt1, Christian Fritz2, Alfons J P Smolders2, Norbert Hölzel1.   

Abstract

Isotope measurements associated with critical plant resources, such as carbon and nitrogen, have helped deepen the ecological understanding of plant resource acquisition and plant interactions. In this study, we tested the appropriateness of near-infrared reflectance spectroscopy for the estimation of stable isotope ratios for nitrogen and carbon of plant tissues. delta(13)C and delta(15)N, as well as total carbon (Ct) and nitrogen (Nt), in leaf tissues of a heterogeneous set of 72 samples of seven bog species from southern Patagonia were determined. Near-infrared reflectance spectroscopy calibrations were developed using partial least-squares regressions and tested by a cross-validation procedure. For each variable, three calibrations were calculated: one with nontransformed data and two with transformations (first and second derivative). Ct and Nt, as well as delta(13)C and delta(15)N, were well predicted by our calibration models. The correlation coefficients of predicted vs actual values of the best calibration models were as follows: 0.95 (Ct), 0.99 (Nt), 0.89 (delta(13)C) and 0.99 (delta(15)N). The cross-validation procedure confirmed the high estimation quality of the calibrations. The results obtained underpin the great potential of the near-infrared reflectance spectroscopy technique in ecological studies as an alternative to more expensive and time-consuming standard methods.

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Year:  2009        PMID: 19691675     DOI: 10.1111/j.1469-8137.2009.02995.x

Source DB:  PubMed          Journal:  New Phytol        ISSN: 0028-646X            Impact factor:   10.151


  7 in total

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Journal:  Molecules       Date:  2022-06-20       Impact factor: 4.927

2.  Landscape-scale assessments of stable carbon isotopes in soil under diverse vegetation classes in East Africa: application of near-infrared spectroscopy.

Authors:  Leigh Ann Winowiecki; Tor-Gunnar Vågen; Pascal Boeckx; Jennifer A J Dungait
Journal:  Plant Soil       Date:  2017-10-16       Impact factor: 4.192

3.  A Perspective on Plant Phenomics: Coupling Deep Learning and Near-Infrared Spectroscopy.

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Journal:  Front Plant Sci       Date:  2022-05-20       Impact factor: 6.627

4.  Leaf optical properties reflect variation in photosynthetic metabolism and its sensitivity to temperature.

Authors:  Shawn P Serbin; Dylan N Dillaway; Eric L Kruger; Philip A Townsend
Journal:  J Exp Bot       Date:  2011-10-06       Impact factor: 6.992

5.  Fast and inexpensive detection of total and extractable element concentrations in aquatic sediments using near-infrared reflectance spectroscopy (NIRS).

Authors:  Till Kleinebecker; Moni D M Poelen; Alfons J P Smolders; Leon P M Lamers; Norbert Hölzel
Journal:  PLoS One       Date:  2013-07-29       Impact factor: 3.240

6.  Retrieving nitrogen isotopic signatures from fresh leaf reflectance spectra: disentangling δ(15)N from biochemical and structural leaf properties.

Authors:  Christine Hellmann; André Große-Stoltenberg; Verena Lauströ; Jens Oldeland; Christiane Werner
Journal:  Front Plant Sci       Date:  2015-05-01       Impact factor: 6.627

7.  Bryophytes and Organic layers Control Uptake of Airborne Nitrogen in Low-N Environments.

Authors:  Alexandra Bähring; Andreas Fichtner; Uta Friedrich; Goddert von Oheimb; Werner Härdtle
Journal:  Front Plant Sci       Date:  2017-12-04       Impact factor: 5.753

  7 in total

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