Authors: Mänd P1
Reviewers: Porcar Castell A2, Linder S3
Measurement unit: mg cm-2, mg g-1; Measurement scale: leaf-level; Equipment costs: €–€€; Running costs: €; Installation effort: medium; Maintenance effort: low; Knowledge: medium; Measurement mode: manual
Chlorophylls and carotenoids are plant pigments which absorb light energy for use in photosynthesis. There are two main chlorophyll (Chl) pigments in higher plants (Chl a and Chl b) and several hundred different carotenoids (Car). However, only six carotenoids are ubiquitous among higher plants (Esteban et al., 2015). The pigment content of plants is species-specific and changes with season and leaf age (Linder, 1972), but also depends on environmental parameters, mainly light conditions (Demmig-Adams & Adams, 1992; Niinemets & Valladares, 2004). Shade plants usually have higher chlorophyll concentrations per unit leaf mass and a lower ratio of Car:Chl and Chl a:b (Niinemets et al., 1998). Light-harvesting protein complexes in plant photosystems (mainly LHCII) are rich in Chl b, in contrast to the core reaction centre complexes of plant photosystems that consist only of Chl a. Thus, an increase in antenna (LHC) size will be reflected as a decrease in the Chl a:b ratio. Under low light there is no need to invest so much on reaction centres and electron transport chain constituents and resources are invested instead in building larger antennae (Eichelmann et al., 2005). The chlorophyll content of leaves and ratio of Chl a:b are furthermore known to change as a response to climate- and global-change drivers, such as air pollution (Tripathi & Gautam, 2007), drought (Anjum et al., 2011), salt stress (Santos, 2004), and iron deficiency (Belkhodja et al., 1998). In addition to light harvesting, the carotenoids play an important role in the photoprotection of the photosystems, which is why the Car:Chl ratio depends mainly on light conditions (Demmig-Adams, 1990).
The conversion of a carotenoid violaxanthin to zeaxanthin is the main pathway in the regulation of heat dissipation of photosystem II (PSII) energy, when PSII encounters excess energy that exceeds the photosynthetic capacity of the photosystem (Young, 1991). In fact, most plants experience excess light on a daily basis, although in the case of stressed plants, photosynthetic capacity declines even more and excess light needs to be redirected to avoid photodamage (Ort, 2001). Thus, the content of photoprotective pigments tends to increase in stressed environments, as has been observed in cases of nitrogen starvation (Jalal et al., 2013) or drought (Colom & Vazzana, 2003). Chlorophyll content is used also as an indicator of the nitrogen (N) status of leaves while N is needed for chlorophyll production (Linder, 1980; Muñoz-Huerta et al., 2013). Pigment content also affects the optical properties of leaves including their spectral reflectance (Vogelmann, 1993; Gitelson et al., 2003; Atherton et al., 2017). A large number of indices, mostly based on reflectance (see section 5.2.2) (Peñuelas et al., 1995; Sims & Gamon, 2002; Gamon et al., 2016) but also on fluorescence ratios (e.g. Gitelson et al., 1998), has been developed in order to link changes in plant pigment concentrations to optical measurements. The advantage of these indices is that they can be used to track changes in leaf pigment concentrations on a non-destructive basis (when applied at the leaf level), or to track vegetation greenness and pigment dynamics (when applied at the canopy and landscape scales via remote sensing) (Sims & Gamon, 2002; Inoue et al., 2016). As such, the more effective and less-laborious remote quantification of the content of pigments could give us an opportunity to detect early on severe changes in pigment content, indicating stress in plants and/or whole canopies.
5.2.1 What and how to measure?
Extraction of chlorophyll from plant materials requires organic solvents that diffuse through plant tissue, increasing the permeability of chloroplast membranes and disrupting the chlorophyll-protein complexes (Hosikian et al., 2010). After solubilising the pigments, the pigment content of the extracts is quantified by spectrophotometric (Lichtenthaler, 1987; Porra et al., 1989) or high-performance liquid chromatography (HPLC) measurements (Wright et al., 1991; Dunn et al., 2004). In general, HPLC measurements are more time-consuming, labour-intensive, and costly than spectrometric analysis of pigments. But when individual carotenoid concentrations are required, HPLC measurements must be done (Dunn et al., 2004). Most often, plant photosynthetic pigments are extracted using 80% acetone for chlorophyll and pure acetone for polar carotenoids (Dunn et al., 2004; Vicas et al., 2010). The buffering of aqueous acetone (80% acetone) at pH 7.8 (e.g. acetone/Tris buffer solution, 80:20 vol:vol, pH = 7.8) is recommended to avoid the pheophytin formation by loss of the Mg atom in the presence of extracted metabolic acids (Porra, 2002). Most often Tris or sodium phosphate buffers have been used (e.g. Porra et al., 1989; Sims & Gamon, 2002). Other solvents, such as methanol, ethanol, N,N – dimethylformamide (DMF)can be used as well.
Extinction coefficients have been provided for a number of different solutes (Lichtenthaler, 1987; Wellburn, 1994; Porra, 2002; Vicas et al., 2010) and need to be used when calculating the pigment contents. The choice of solvent often depends on the type of plant material (Wellburn, 1994; Dunn et al., 2004). In most solutes, the leaf tissue needs to be homogenised first (adding solvent to the sample when grinding) and centrifuged or filtered after pigments have been solubilised. For pigment calculations, the total volume of solute added to the sample during different stages of grinding and washing the mortar from sample-residuals must be collected, recorded, and taken into account during the quantification. Some solutes, such as DMF can be used for determining Chl content in intact tissues if chlorophyll content is low enough (Inskeep & Bloom, 1985). Many solvents require precautionary measures because of their toxicity.
The incubation time of tissues in solvents for extraction depends on the solvent and on the size of the material and also on the species (Minocha et al., 2009). A thumb-rule is that if the leaflet or pellet of leaf residuals look greenish after the extraction then not all chlorophylls have been solubilised, if the leaf material looks yellowish some carotenoids have not solubilised, and when the leaf material is white (or any other colour but not green or yellowish) then the incubation time is long enough. The extraction process can be repeated if the plant material still contains pigments, the total volume of solute needs to be taken into account. During incubation in solute the intact tissues must be stored in dark probes with corks to avoid vaporising of the solvent.
As traditional measurements of plant pigments are destructive, there is a less laborious and non-destructive method for estimating leaf Chl content using optical chlorophyll meters, which are portable and easy to use (e.g. Netto et al., 2005). In addition, new devices are being developed for simultaneous estimation of more than one plant pigment, such as content of Chl, nitrogen, flavonols, and anthocyanins of the leaf. The Chl content in most of the chlorophyll meters is estimated by measuring the ratio of transmission of near-infrared (NIR) to red wavelengths. It is assumed that transmission of red light is affected both by Chl and other cell structures, while transmission of NIR is not affected by Chl. However, in order to quantify the readings of an optical chlorophyll meter, a correlative dataset of non-destructively gained Chl estimations v. Chl contents from destructive measurements is required. This is because at the near-infrared region, leaf thickness, structure, and consequent internal light scattering affect the light transmission (Parry et al., 2014). The correlative dataset must be done separately for every species. Also one must be aware that optical estimations of Chl content appear to be less accurate if Chl content increases (Richardson et al., 2002). As Chl in leaves is distributed unevenly, it is recommended that a few optical measurements be made from one leaf and take an average for the whole leaf Chl estimation.
Installation, field operation, maintenance, and interpretation of the data
Leaf samples (e.g. using a cork drill) or whole leaves for pigment content measurements should be collected under comparable light conditions (Demmig-Adams & Adams, 1992) and age (Linder, 1972). Pigments in leaves are not distributed evenly, so in order to get results that can be readily compared, all leaf discs should be taken from same leaf region. Leaves or leaf discs (of known area) must preferentially be frozen as soon as possible (e.g. transported in liquid nitrogen) and stored at -80 °C in the dark to sustain the plant material until pigment analysis. If leaf samples are collected from very moist or wet conditions and/or stored for longer periods or transported in unstable conditions before extraction, it is recommended to lyophilise the samples. Such samples can be stored at room temperatures for days allowing easy transportation if kept away from moisture (Tausz et al., 2003). In the field, it is not always possible to freeze or freeze-dry pigment samples, in which case alternative (less recommended) methods for sampling and preserving plant pigments are available (Esteban et al., 2009). It is also recommended to collect parallel samples (e.g. nearby leaf) for determination of total area and fresh and dry weights. This will enable the quantification of leaf pigments on a mass or area basis. The mass of lyophilised samples (for estimation of dry mass) can be measured for calculations of pigment concentrations. Pigments should be extracted in dim light. Common problems that can be encountered during plant pigment analysis are errors in sample collection, preservation, labelling, biomass, and leaf area measurements, as well as incomplete extraction, instruments not working correctly, false compound identification, pipetting errors, confusion in units, etc. (Fernández-Marín et al., 2015).
Where to start
Dunn et al. (2004), Esteban et al. (2009), Hosikian et al. (2010), Minocha et al. (2009), Porra (2002)
5.2.2 Special cases, emerging issues, and challenges
Estimating canopy-pigment contents remotely enables the monitoring of plant parameters over much larger spatial and temporal scales. Reflectance indices (see Table 5.2.1) and fluorescence indices (e.g. Gitelson et al., 1998) have been developed enabling remote estimations of chlorophyll and carotenoid contents. For instance, in global carbon budget models, PRI (Table 5.2.1) is used, as this index correlates with changes in pigment pools of plant canopies (Gamon et al., 1992; Gitelson et al., 2017). Recently, an index tracking Chl:Car ratios and photosynthetic activity of evergreen trees was introduced (Gamon et al., 2016). There has even been an attempt to use the reflectance spectra of the regions of different tree biochemical constituents that change seasonally (e.g. pigments) to classify trees remotely (Kozhoridze et al., 2016). However, one must always be aware of the effect of canopy structure and overlapping wavelength regions on reflectance while using remote estimations of plant parameters (Mänd et al., 2010).
Table 5.2.1 Vegetation indices for estimations of leaf pigment content (most-cited or recently developed and repeatedly cited indices). Table modified and provided with permission from COST Action ES0903. Rx means the reflectance (R) at wavelength x. Dx shows the first derivative (D) of reflectance at the respective wavelength x.
|Simple Ratios (SR)||SR=RNIR/RRED||Greenness||Jordan, 1969|
|Chlorophyll Index (CI)||CI=(R750-R705)/(R750+R705)||Chlorophyll content||Gitelson & Merzlyak, 1994|
|Canopy Chlorophyll Index (CCI)||CCI=D720/D700||Canopy chlorophyll content||Sims et al., 2006|
|Normalized Difference Vegetation Index (NDVI)||NDVI=(RNIR-RRED)/(RNIR+RRED)||Greenness||Myneni et al., 1997|
|Structural Insensitive Pigment Index (SIPI)||SIPI=(R800-R445)/(R800-R680)||Carotenoid:Chlorophyll ratio||Peñuelas et al., 1995|
|Modified Chlorophyll Absorption in Reflectance Index (MCARI)||MCARI=[(R700-R670)-0.2(R700-R550)] (R700/R670)||Canopy Chlorophyll content||Daughtry et al., 2000|
|Transformed Chlorophyll Absorption in Reflectance Index (TCARI)||TCARI=3[(R700-R670)-0.2(R700-R550) (R700/R670)]||Canopy Chlorophyll content||Haboudane et al., 2002|
|Photochemical Reflectance Index (PRI)||PRI=(R531-R570)/(R531 –R570)||Photosynthetic light use efficiency and leaf pigment contents||Gamon et al., 1992|
Theory, significance, and large datasets
Demmig-Adams & Adams (1992), Fernández-Marín (2015), Niinemets et al. (1998), Ort (2001), Richardson et al. (2002)
More on methods and existing protocols
Lichtenthaler (1987), Porra et al. (1989), Vicas et al. (2010), Wellburn (1994), Wright et al. (1991)
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Authors: Mänd P1
Reviewers: Porcar Castell A2; Linder S3
1 Institute of Ecology and Earth Sciences, University of Tartu, Tartu, Estonia
2 Optics of Photosynthesis Laboratory, Institute for Atmospheric and Earth System Research/Forest Sciences, University of Helsinki, Helsinki, Finland
3 Southern Swedish Forest Research Centre, Alnarp, Sweden