Assessment of physiological state of Betula pendula and Carpinus betulus through leaf reflectance measurements

Abstract In this study, the evidence of a relationship between the physiological state and leaf optical properties led us to investigate the behaviour of two species – Betula pendula Roth and Carpinus betulus L. – in order to determine if the vegetation is affected by the heavy metal load of the soil from a former mining area, Rosia Montana, Romania (46°18′47″N, 23°10′15″E). Two non-destructive techniques (leaf transmittance and reflectance) were compared to assess the physiological state of the plants, and 27 vegetation indices for estimating foliar pigment content were tested. For chlorophyll assessment, the reflectance ratios RNIR/R550 and RNIR/R700 were the most reliable for an accurate estimation of the pigment content of the leaves. The light use efficiency (LUE) indices were within normal values, except the Red Green Ratio, indicating that the overall reactions of photosynthesis are not impaired by the specific conditions of the habitat. Differences in leaf optical properties are minimal between the two studied species and the values of the vegetation indices are showing similar trends. Both techniques performed consistently well and yielded accurate estimations of pigment content, supporting their interoperability.

[1]  Dai Lp,et al.  Antioxidative and Chelating Properties of Anthocyanins in Azolla imbricata Induced by Cadmium , 2012 .

[2]  Wenjiang Huang,et al.  Reflectance Variation within the In-Chlorophyll Centre Waveband for Robust Retrieval of Leaf Chlorophyll Content , 2014, PloS one.

[3]  R. Bharagava,et al.  Accumulation and distribution of toxic metals in wheat (Triticum aestivum L.) and Indian mustard (Brassica campestris L.) irrigated with distillery and tannery effluents. , 2009, Journal of hazardous materials.

[4]  Qunhui Wang,et al.  Effects of copper and cadmium on heavy metal polluted waterbody restoration by duckweed (Lemna minor). , 2007, Plant physiology and biochemistry : PPB.

[5]  D. Sims,et al.  Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages , 2002 .

[6]  Josep Peñuelas,et al.  Visible and near-infrared reflectance techniques for diagnosing plant physiological status , 1998 .

[7]  Vijaya Gopal Kakani,et al.  Nitrogen deficiency effects on plant growth, leaf photosynthesis, and hyperspectral reflectance properties of sorghum , 2005 .

[8]  John A. Gamon,et al.  Assessing leaf pigment content and activity with a reflectometer , 1999 .

[9]  M. Cho,et al.  An investigation into robust spectral indices for leaf chlorophyll estimation , 2011 .

[10]  C. Dobrotă,et al.  Impact of the past mining activity in Roşia Montană (Romania) on soil and vegetation , 2014, Environmental Earth Sciences.

[11]  K. Takeda.  Blue metal complex pigments involved in blue flower color , 2006, Proceedings of the Japan Academy. Series B, Physical and biological sciences.

[12]  G. A. Blackburn,et al.  Spectral indices for estimating photosynthetic pigment concentrations: A test using senescent tree leaves , 1998 .

[13]  J. Dungan,et al.  The effect of a red leaf pigment on the relationship between red edge and chlorophyll concentration , 1991 .

[14]  A. Gitelson,et al.  Signature Analysis of Leaf Reflectance Spectra: Algorithm Development for Remote Sensing of Chlorophyll , 1996 .

[15]  F. Loreto,et al.  Associated changes in physiological parameters and spectral reflectance indices in olive (Olea europaea L.) leaves in response to different levels of water stress , 2008 .

[16]  A. Gitelson,et al.  Three‐band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves , 2006 .

[17]  John R. Miller,et al.  Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data , 2001, IEEE Trans. Geosci. Remote. Sens..

[18]  J. Cortina,et al.  Response to drought of Zn-stressed Quercus suber L. seedlings , 2011 .

[19]  A. Gitelson,et al.  Detection of Red Edge Position and Chlorophyll Content by Reflectance Measurements Near 700 nm , 1996 .

[20]  E. Cholewa,et al.  Effects of combined drought and heavy metal stresses on xylem structure and hydraulic conductivity in red maple (Acer rubrum L.). , 2012, Journal of experimental botany.

[21]  D. Horler,et al.  The red edge of plant leaf reflectance , 1983 .

[22]  B. Datt.  Remote Sensing of Chlorophyll a, Chlorophyll b, Chlorophyll a+b, and Total Carotenoid Content in Eucalyptus Leaves , 1998 .

[23]  R. Tewari,et al.  Modulation of oxidative stress responsive enzymes by excess cobalt , 2002 .

[24]  Jan G. P. W. Clevers,et al.  Using Hyperspectral Remote Sensing Data for Retrieving Canopy Chlorophyll and Nitrogen Content , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[25]  G. Carter.  Ratios of leaf reflectances in narrow wavebands as indicators of plant stress , 1994 .

[26]  S. Tarantola,et al.  Detecting vegetation leaf water content using reflectance in the optical domain , 2001 .

[27]  G. Agati,et al.  New vegetation indices for remote measurement of chlorophylls based on leaf directional reflectance spectra. , 2001, Journal of photochemistry and photobiology. B, Biology.

[28]  J. Jones,et al.  The handbook of trace elements , 1997 .

[29]  Chaoyang Wu,et al.  Estimating chlorophyll content from hyperspectral vegetation indices : Modeling and validation , 2008 .

[30]  A. Kabata-Pendias.  Trace elements in soils and plants , 1984 .

[31]  Andrew D. Richardson,et al.  An evaluation of noninvasive methods to estimate foliar chlorophyll content , 2002 .

[32]  A. N. Misra,et al.  The xanthophyll cycle activity in kidney bean and cabbage leaves under salinity stress , 2006, Russian Journal of Plant Physiology.

[33]  K. Barry,et al.  Optimizing spectral indices and chemometric analysis of leaf chemical properties using radiative transfer modeling , 2011 .

[34]  Gustavo A. Lobos,et al.  Chlorophyll, anthocyanin, and gas exchange changes assessed by spectroradiometry in Fragaria chiloensis under salt stress. , 2014, Journal of integrative plant biology.

[35]  A. Fargašová.  Phytotoxic Effects of Cd, Zn, Pb, Cu and Fe on Sinapis Alba L. Seedlings and their Accumulation in Roots and Shoots , 2001, Biologia Plantarum.

[36]  P. Das,et al.  Aluminium toxicity in plants: a review , 2001 .

[37]  R. Saxena,et al.  Interactive Metal Accumulation and Its Toxic Effects under Repeated Exposure in Submerged Plant Najas indica Cham , 2003, Bulletin of environmental contamination and toxicology.

[38]  Govindjee,et al.  Chlorophyll a Fluorescence: A Bit of Basics and History , 2004 .

[39]  S. Brantley,et al.  Application of hyperspectral vegetation indices to detect variations in high leaf area index temperate shrub thicket canopies , 2011 .

[40]  Claus Buschmann,et al.  In vivo spectroscopy and internal optics of leaves as basis for remote sensing of vegetation , 1993 .

[41]  Yuri A. Gritz,et al.  Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. , 2003, Journal of plant physiology.

[42]  C. Field,et al.  A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency , 1992 .

[43]  Anatoly A. Gitelson,et al.  Remote estimation of nitrogen and chlorophyll contents in maize at leaf and canopy levels , 2013, Int. J. Appl. Earth Obs. Geoinformation.

[44]  P. Ryser,et al.  Influence of heavy-metal contamination on plant response to water availability in white birch, Betula papyrifera. , 2009 .

[45]  Moon S. Kim,et al.  Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance , 2000 .

[46]  O. Björkman,et al.  Photon yield of O2 evolution and chlorophyll fluorescence characteristics at 77 K among vascular plants of diverse origins , 1987, Planta.

[47]  A. Gitelson,et al.  Spectral reflectance changes associated with autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectral features and relation to chlorophyll estimation , 1994 .

[48]  S. Ahn,et al.  Effects of Heavy Metals on Plant Growths and Pigment Contents in Arabidopsis thaliana , 2012 .