Skip to main content
SpringerLink
Log in

Assessing Metal-Induced Changes in the Visible and Near-Infrared Spectral Reflectance of Leaves: A Pot Study with Sunflower (Helianthus annuus L.)

  • Research Article
  • Published:
Journal of the Indian Society of Remote Sensing Aims and scope Submit manuscript

Abstract

The aim of this study was to monitor changes in leaf spectral reflectance due to phytoaccumulation of trace elements (Cd, Pb, and As) in sunflower mutant (M5 mutant line 38/R4-R6/15-35-190-04-M5) grown in spiked and in situ metal-contaminated potted soils. Reflectance spectra (350–2500 nm) of leaves were collected using portable ASD spectroradiometer, and respective leaves sample were analyzed for total metal contents. The spectral changes were quite noticeable and showed increased visible and decreased NIR reflectance for sunflower grown in soil spiked with 900 mg As kg−1, and in in situ metal-contaminated soils. These changes also involved a blue-shift feature of red-edge position in the first derivatives spectra, studied vegetation indices and continuum removed absorption features at 495, 680, 970, 1165, 1435, 1780, and 1925 nm wavelength. Correlograms of leaf-metal concentration and reflectance values show highest degrees of overall correlation for visible, near-infrared, and water-sensitive wavelengths. Partial least square and multiple linear regression statistical models (cross-validated), respectively, based on Savitzky–Golay filter first-order derivative spectra and combination of spectral feature such as vegetation indices and band depths yielded good prediction of leaf-metal concentrations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Abdi, H. (2003). Partial least square regression (PLS regression). In Lewis-Beck, T. F. Liao, & A. Bryman (Eds.), The SAGE encyclopedia of social science research methods (Vol. 1, pp. 792–795). Thousand Oaks: Sage.

    Google Scholar 

  • Adesodun, J., Atayese, M., Agbaje, T. A., Osadiaye, B., Mafe, O. F., & Soretire, A. (2010). Phytoremediation potentials of sunflowers (Tithonia diversifolia and Helianthus annuus) for metals in soils contaminated with zinc and lead nitrates. Water, Air, and Soil Pollution, 207(1–4), 195–201. https://doi.org/10.1007/s11270-009-0128-3.

    Article  Google Scholar 

  • Bandaru, V., Hansen, D. J., Codling, E. E., Daughtry, C. S., White-Hansen, S., & Green, C. E. (2010). Quantifying arsenic-induced morphological changes in spinach leaves: Implications for remote sensing. International Journal of Remote Sensing, 31(15), 4163–4177. https://doi.org/10.1080/01431161.2010.498453.

    Article  Google Scholar 

  • Blackburn, G. (2007). Hyperspectral remote sensing of plant pigments. Journal of Experimental Botany, 58(4), 855–867. https://doi.org/10.1093/jxb/erl123.

    Article  Google Scholar 

  • Boyd, D., Entwistle, J., Flowers, A., Armitage, R., & Goldsmith, P. (2006). Remote sensing the radionuclide contaminated Belarusian landscape: A potential for imaging spectrometry? International Journal of Remote Sensing, 27(10), 1865–1874. https://doi.org/10.1080/01431160500328355.

    Article  Google Scholar 

  • Buschmann, C., & Nagel, E. (1993). In vivo spectroscopy and internal optics of leaves as basis for remote sensing of vegetation. International Journal of Remote Sensing, 14(4), 711–722. https://doi.org/10.1080/01431169308904370.

    Article  Google Scholar 

  • Clark, R. N., & Roush, T. L. (1984). Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications. Journal of Geophysical Research: Solid Earth, 89(B7), 6329–6340. https://doi.org/10.1029/JB089iB07p06329.

    Article  Google Scholar 

  • Cundy, A., Bardos, R. P., Puschenreiter, M., Mench, M., Bert, V., Friesl-Hanl, W., et al. (2016). Brownfields to green fields: Realising wider benefits from practical contaminant phytomanagement strategies. Journal of Environmental Management, 184(1), 67–77. https://doi.org/10.1016/j.jenvman.2016.03.028.

    Article  Google Scholar 

  • Cundy, A., Bardos, P., Puschenreiter, M., Witters, N., Mench, M., Bert, V., et al. (2015). Developing effective decision support for the application of “gentle” remediation options: The GREENLAND project. Remediation Journal, 25(3), 101–114. https://doi.org/10.1002/rem.21435.

    Article  Google Scholar 

  • Curran, P. J. (1989). Remote sensing of foliar chemistry. Remote Sensing of Environment, 30(3), 271–278. https://doi.org/10.1016/0034-4257(89)90069-2.

    Article  Google Scholar 

  • Curran, P. J., Dungan, J. L., Macler, B. A., Plummer, S. E., & Peterson, D. L. (1992). Reflectance spectroscopy of fresh whole leaves for the estimation of chemical concentration. Remote Sensing of Environment, 39(2), 153–166. https://doi.org/10.1016/0034-4257(92)90133-5.

    Article  Google Scholar 

  • Curran, P. J., Dungan, J. L., & Peterson, D. L. (2001). Estimating the foliar biochemical concentration of leaves with reflectance spectrometry: Testing the Kokaly and Clark methodologies. Remote Sensing of Environment, 76(3), 349–359. https://doi.org/10.1016/S0034-4257(01)00182-1.

    Article  Google Scholar 

  • Cuypers, A., Smeets, K., & Vangronsveld, J. (2009). Heavy metal stress in plants. In H. Hirt (Ed.), Plant Stress Biology: From Genomics to Systems Biology (pp. 161–178). KGaA, Weinheim: Wiley-VCH. https://doi.org/10.1002/9783527628964.ch8.

    Chapter  Google Scholar 

  • de Gandy, Y. P. P. (2010). Spectral reflectance as an indicator of foliar concentrations of arsenic in common sunflower (Helianthus Annuus). M.S. dissertation No. 1488735. Department of Chemistry, University of Texas-Pan American.

  • Dorigo, W., Bachmann, M., & Heldens, W. (2006). AS toolbox and processing of field spectra: Use’s manual, Version 1.13. Wessling: German Aerospace Center (DLR), German Remote Sensing Data Center, Institute for Environment and Geo-information Team Imaging Spectroscopy.

    Google Scholar 

  • Font, R., del Río-Celestino, M., & de Haro-Bailón, A. (2007). Near-infrared reflectance spectroscopy: Methodology and potential for predicting trace elements in plants. In N. Willey (Ed.), Phytoremediation, methods and reviews (Vol. 23). Totowa, NJ: Humana Press Inc.

    Google Scholar 

  • Gallego, S. M., Benavides, M. P., & Tomaro, M. L. (1996). Effect of heavy metal ion excess on sunflower leaves: Evidence for involvement of oxidative stress. Plant Science, 121, 151–159. https://doi.org/10.1016/S0168-9452(96)04528-1.

    Article  Google Scholar 

  • Garg, N., & Singla, P. (2011). Arsenic toxicity in crop plants: Physiological effects and tolerance mechanisms. Environmental Chemistry Letters, 9(3), 303–321. https://doi.org/10.1007/s10311-011-0313-7.

    Article  Google Scholar 

  • Gitelson, A. A., & Merzlyak, M. N. (1996). Signature analysis of leaf reflectance spectra: Algorithm development for remote sensing of chlorophyll. Journal of Plant Physiology, 148(3), 494–500. https://doi.org/10.1016/S0176-1617(96)80284-7.

    Article  Google Scholar 

  • Götze, C., Jung, A., Merbach, I., Wennrich, R., & Gläßer, C. (2010). Spectrometric analyses in comparison to the physiological condition of heavy metal stressed floodplain vegetation in a standardised experiment. Open Gioscience (Formerly Central European Journal of Geosciences), 2(2), 132–137. https://doi.org/10.2478/v10085-010-0002-y.

    Article  Google Scholar 

  • Herzig, R., Nehnevajova, E., Pfistner, C., Schwitzguebel, J.-P., Ricci, A., & Keller, C. (2014). Feasibility of labile Zn phytoextraction using enhanced tobacco and sunflower: Results of five-and one-year field-scale experiments in Switzerland. International Journal of Phytoremediation, 16, 735–754. https://doi.org/10.1080/15226514.2013.856846.

    Article  Google Scholar 

  • Hong, H., Feng-jie, Y., Guang-zhu, Z., & Yin-ming, L. (2010). Spectral features and regression model of mine vegetation in the press of heavy metal. In Second International Workshop on Education Technology and Computer Science (pp. 57–59). IEEE. https://doi.org/10.1109/etcs.2010.398.

  • Horler, D. N. H., Barber, J., & Barringer, A. R. (1980). Effects of heavy metals on the absorbance and reflectance spectra of plants. International Journal of Remote Sensing, 1, 121–136. https://doi.org/10.1080/01431168008547550.

    Article  Google Scholar 

  • Horler, D. N. H., Dockray, M., & Barber, J. (1983). The red edge of plant leaf reflectance. International Journal of Remote Sensing, 4(2), 273–288. https://doi.org/10.1080/01431168308948546.

    Article  Google Scholar 

  • Huber, S., Kneubuhler, M., Psomas, A., Itten, K., & Zimmermann, N. E. (2008). Estimating foliar biochemistry from hyperspectral data in mixed forest canopy. Forest Ecology and Management, 256, 491–501. https://doi.org/10.1016/j.foreco.2008.05.011.

    Article  Google Scholar 

  • Imran, M. A., Sajid, Z. A., & Chaudhary, M. N. (2015). Arsenic (As) toxicity to germination and vegetative growth of sunflower (Helianthus annuus L.). Poland Journal of Environment Studies, 24(5), 1993–2002. https://doi.org/10.15244/pjoes/39553.

    Article  Google Scholar 

  • Kabata-Pendias, A., & Pendias, H. (2001). Trace elements in soils and plants (3rd ed.). Boca Raton: CRC Press LLC.

    Google Scholar 

  • Kancheva, R., & Borisova, D. (2010). Spectral data for plant chlorophyll assessment. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 7(3), 239–245.

    Google Scholar 

  • Kidd, P., Mench, M., Álvarez-López, V., Bert, V., Dimitriou, I., Friesl-Hanl, W., et al. (2015). Agronomic practices for improving gentle remediation of trace element-contaminated soils. International Journal of Phytoremediation, 17(11), 1005–1037. https://doi.org/10.1080/15226514.2014.1003788.

    Article  Google Scholar 

  • Li, X., Liu, X., Liu, M., Wang, C., & Xia, X. (2015). A hyperspectral index sensitive to subtle changes in the canopy chlorophyll content under arsenic stress. International Journal of Applied Earth Observation and Geoinformation, 36, 41–53. https://doi.org/10.1016/j.jag.2014.10.017.

    Article  Google Scholar 

  • Maria, S. D., Puschenreiter, M., & Rivelli, A. R. (2013). Cadmium accumulation and physiological response of sunflower plants to Cd during the vegetative growing cycle. Plant Soil Environment, 59(6), 254–261.

    Article  Google Scholar 

  • Mariotti, M., Ercoli, L., & Masoni, A. (1996). Spectral properties of iron-deficient corn and sunflower leaves. Remote Sensing of Environment, 58(3), 282–288. https://doi.org/10.1016/S0034-4257(96)00070-3.

    Article  Google Scholar 

  • Mench, M., Lepp, N., Bert, V., Schwitzguébel, J.-P., Gawronski, S. W., Schröder, P., et al. (2010). Successes and limitations of phytotechnologies at field scale: Outcomes, assessment and outlook from COST Action 859. Journal of Soils and Sediments, 10(6), 1039–1070. https://doi.org/10.1007/s11368-010-0190-x.

    Article  Google Scholar 

  • Milton, N. M., Ager, C. M., Eiswerth, B. A., & Power, M. S. (1989). Arsenic-and selenium-induced changes in spectral reflectance and morphology of soybean plants. Remote Sensing of Environment, 30(3), 263–269. https://doi.org/10.1016/0034-4257(89)90068-0.

    Article  Google Scholar 

  • Nehnevajova, E., Herzig, R., Bourigault, C., Bangerter, S., & Schwitzguébel, J.-P. (2009a). Stability of enhanced yield and metal uptake by sunflower mutants for improved phytoremediation. International Journal of Phytoremediation, 11(4), 329–346. https://doi.org/10.1080/15226510802565394.

    Article  Google Scholar 

  • Nehnevajova, E., Herzig, R., Federer, G., Erismann, K.-H., & Schwitzguébel, J.-P. (2005). Screening of sunflower cultivars for metal phytoextraction in a contaminated field prior to mutagenesis. International Journal of Phytoremediation, 7(4), 337–349. https://doi.org/10.1080/16226510500327210.

    Article  Google Scholar 

  • Nehnevajova, E., Herzig, R., Schwitzguébel, J. P., & Schmülling, T. (2009b). Sunflower mutants with improved growth and metal accumulation traits show a potential for soil decontamination. In Q. Y. Shu (Ed.), Induced plant mutations in the genomics era (pp. 83–86). Rome: Food and Agriculture Organization of the United Nations.

    Google Scholar 

  • Noomen, M. F. (2007). Hyperspectral reflectance of vegetation affected by underground hydrocarbon gas seepage. Ph.D. Thesis. Faculty of Geoscience and Earth Observation, University of Twente, The Netherlands. https://webapps.itc.utwente.nl/librarywww/papers_2007/phd/noomen.pdf.

  • Onwubuya, K., Cundy, A., Puschenreiter, M., Kumpiene, J., Bone, B., Greaves, J., et al. (2009). Developing decision support tools for the selection of “gentle” remediation approaches. Science of the Total Environment, 407(24), 6132–6142. https://doi.org/10.1016/j.scitotenv.2009.08.017.

    Article  Google Scholar 

  • Peñuelas, J., & Filella, I. (1998). Visible and near-infrared reflectance techniques for diagnosing plant physiological status. Trends in Plant Science, 3(4), 151–156. https://doi.org/10.1016/S1360-1385(98)01213-8.

    Article  Google Scholar 

  • Peñuelas, J., Gamon, J. A., Fredeen, A. L., Merino, J., & Field, C. B. (1994). Reflectance indices associated with physiological changes in nitrogen- and water-limited sunflower leaves. Remote Sensing of Environment, 48, 135–146. https://doi.org/10.1016/0034-4257(94)90136-8.

    Article  Google Scholar 

  • Pilon-Smits, E. (2005). Phytoremediation. Annual Review of Plant Biology, 56, 15–39. https://doi.org/10.1146/annurev.arplant.56.032604.144214.

    Article  Google Scholar 

  • Prasad, M. N. V. (2004). Heavy metal stress in plants: From molecules to ecosystems (2nd ed.). New Delhi: Springer and Jointly published with Narosa Publishing House.

    Book  Google Scholar 

  • Prasad, M. N. V., & de Oliveira Freitas, H. M. (2003). Metal hyperaccumulation in plants: Biodiversity prospecting for phytoremediation technology. Electronic Journal of Biotechnology, 6(3), 285–321. https://doi.org/10.2225/vol6-issue3-fulltext-6.

    Article  Google Scholar 

  • Raba, A., Henk, S., Meharg, A. A., & Feldmann, J. (2005). Uptake, translocation, and transformation of arsenate and arsenite in sunflower (Helianthus annuus): Formation of arsenic-phytochelatin complexes during exposure to high arsenic concentration. New Phytologist, 168, 551. https://doi.org/10.1111/j.1469-8137.2005.01519.x.

    Article  Google Scholar 

  • Rathod, P. H., Brackhage, C., Van der Meer, F. D., Müller, I., Noomen, M. F., Rossiter, D. G., et al. (2015). Spectral changes in the leaves of barley plant due to phytoremediation of metals-results from a pot study. European Journal of Remote Sensing, 48, 283–302. https://doi.org/10.5721/EuJRS20154816.

    Article  Google Scholar 

  • Rathod, P. H., Rossiter, D. G., Noomen, M. F., & Van der Meer, F. D. (2013). Proximal spectral sensing to monitor phytoremediation of metal-contaminated soils. International Journal of Phytoremediation, 15(5), 405–426. https://doi.org/10.1080/15226514.2012.702805.

    Article  Google Scholar 

  • Schwitzguébel, J. P., Nehnevajova, E., & Herzig, R. (2008). Sustainable approach to remove metals from contaminated soils: Improved phytoextraction by sunflower mutants. ID 291. In N. Kalogerakis, F. Fava & S. A. Banwart (Eds.), E-book of abstract of the fourth European Bioremediaton conference, Crete, Greece, September 3–6, 2008.

  • Slonecker, T., Haack, B., & Price, S. (2009). Spectroscopic analysis of arsenic uptake in Pteris ferns. Remote Sensing, 1, 644–675. https://doi.org/10.3390/rs1040644.

    Article  Google Scholar 

  • Sridhar, B. B., Han, F. X., Diehl, S. V., Monts, D. L., & Su, Y. (2007a). Monitoring the effects of arsenic and chromium accumulation in Chinese brake fern (Pteris vittata). International Journal of Remote Sensing, 28(5), 1055–1067. https://doi.org/10.1080/01431160600868466.

    Article  Google Scholar 

  • Sridhar, B. B., Han, F. X., Diehl, S. V., Monts, D. L., & Su, Y. (2007b). Spectral reflectance and leaf internal structure changes of barley plants due to phytoextraction of zinc and cadmium. International Journal of Remote Sensing, 28(5), 1041–1054. https://doi.org/10.1080/01431160500075832.

    Article  Google Scholar 

  • Sridhar, B. B., Witter, J. D., Wu, C., Spongberg, A. L., & Vincent, R. K. (2014). Effect of biosolids amendments on the metal and nutrient uptake and spectral characteristics of five vegetables plants. Water, Air, and Soil Pollution, 225(2092), 1–14. https://doi.org/10.1007/s110270-014-2092-9.

    Article  Google Scholar 

  • Vangronsveld, J., Herzig, R., Weyens, N., Boulet, J., Adriaensen, K., Ruttens, A., et al. (2009). Phytoremediation of contaminated soils and groundwater: Lessons from the field. Environmental Science and Pollution Research, 16(7), 765–794. https://doi.org/10.1007/s11356-009-0213-6.

    Article  Google Scholar 

  • Westad, F., & Marten, H. (2000). Variable selection in near infrared spectroscopy based on significance testing in partial least squares regression. Journal of Near Infrared Spectroscopy, 8(2), 117–124. https://doi.org/10.1255/jnirs.271.

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to acknowledge the European Commission Higher Education Program for Granting Erasmus Mundus External Cooperation Window Scholarship to support this research. Special thanks to faculties at Department of Earth System Analysis, ITC, University of Twente; at Institute of General Ecology and Conservation, Tharandt, TU Dresden; and at Saxon State Office for Environment, Agriculture and Geology, Freiberg, for their invaluable technical assistance. The authors are specially thankful to Dr. Rolf Herzig, Phytotech Foundation, Bern, Switzerland, for providing with the seeds of sunflower M5 mutant lines – M5/R4-R6/15-35-190-04-M5.

Author information

Author notes

  1. Paresh H. Rathod

    Present address: Anand Agricultural University, Anand, Gujarat State, India

Authors and Affiliations

  1. Department of Earth Systems Analysis, Faculty of Geo-information Science and Earth Observation, University of Twente, 7514AE, Enschede, The Netherlands

    Paresh H. Rathod, Freek D. Van der Meer & Marleen F. Noomen

  2. Institute for General Ecology and Environmental Protection, Technical University, TU Dresden, 01737, Tharandt, Germany

    Carsten Brackhage

  3. Saxon State Office for Environment, Agriculture and Geology, 09599, Freiberg, Germany

    Ingo Müller

Authors
  1. Paresh H. Rathod
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Carsten Brackhage
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ingo Müller
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Freek D. Van der Meer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Marleen F. Noomen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Paresh H. Rathod.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rathod, P.H., Brackhage, C., Müller, I. et al. Assessing Metal-Induced Changes in the Visible and Near-Infrared Spectral Reflectance of Leaves: A Pot Study with Sunflower (Helianthus annuus L.). J Indian Soc Remote Sens 46, 1925–1937 (2018). https://doi.org/10.1007/s12524-018-0846-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12524-018-0846-3

Keywords

Search

Navigation