**2.2 Chlorophyll fluorescence**

In recent years, chlorophyll fluorescence (ChlF) analysis has become one of the widely used techniques available to plant physiologists and has participated increasingly in plant ecology and physiology studies (Rolando & Little, 2003; Chaerle et al., 2004; Gielen et al., 2006). This analysis has been used more extensively to provide considerable information on the organization and function of the photosynthetic apparatus (Campbell et al., 2007). The chlorophyll molecule has the ability to absorb light energy and transfer it into the photosynthetic apparatus. Excess energy can be dissipated as heat or re-emitted as light at longer wavelength, i.e. chlorophyll fluorescence. The increase in efficiency of one of these three processes (absorption, fluorescence and thermal emission) will result in a decrease in yield of the other two. As such, the relative intensities of ChlF are strongly related to the efficiency of photochemistry and heat dissipation (Papageorgiou & Govindjee, 2004; Lichtenthaler et al., 2007; Delalieux et al. 2009b) and may provide additional data to detect plant stress in an early stage. Generally, fluorescence yield is highest when photochemistry and heat dissipation are lowest.

Chlorophyll a (Chl a) is contributing largely to plant fluorescence emission. Excitation energy for this fluorescence is delivered from accessory antenna chlorophylls (Chl a and Chl b), absorbing light of blue and red wavelengths, and from carotenoids, absorbing photons of blue wavelengths. At room temperature, Chl a emits fluorescence in the red and NIR spectral regions between 650–800 nm, in two broad bands with peaks at λmax1 (684–695 nm) and λmax2 (730–740 nm) (Franck et al., 2002). The shorter wavelength emission is attributed to Chl a

characterize natural canopies and agricultural crops has been demonstrated in numerous studies aimed at seasonal phenology (Carter, 1998; Qi et al., 2000), biomass prediction (Broge and Leblanc, 2001; Haboudane et al., 2004), mapping chlorophyll content (Haboudane et al., 2002). Numerous studies have documented the use of vegetation indices such as ratio vegetation index (RVI) and normalized difference vegetation index (NDVI) in the detection of crop stress (Kobayashi et al., 2001; Vigier et al., 2004; Yang et al., 2009). Combining individual spectral reflectance bands as simple ratio vegetation indices (SRVI) has been a common approach in remote sensing because it generally reduces the effects of spectral noise and allows for better temporal comparisons due to minimization of atmospheric effects (Carter & Miller, 1994). Commonly, SRVIs have consisted of the ratio of blue to red wavebands in an effort to detect responses due to changes in chlorophyll a and b concentrations. Gitelson et al. (2003, 2006) suggested the use of empirical vegetation indices, calculated from the reflectance of three wavelengths that were highly correlated with chlorophyll (Chl), carotenoid, and anthocyanin concentrations to estimate the content of foliar pigments in single leaves. Furthermore, various statistical and artificial intelligence methods have been used to analyze the remotely sensed data in agricultural crops. Among many, popular approaches include cluster analysis (Holden & LeDrew, 1998), principal component analysis (Zhang et al., 2002; 2003), partial-least square regression (Huang &

With the advent of hyperspectral remote sensing technology, more detailed data are potentially available. Therefore the extracting meaningful relationships of the overwhelming quantity of data are necessary. Currently, a variety of techniques have been used including a number of different vegetation indices, band absorption analysis, spectral mixture analysis, "red edge" position, statistical analysis, wavelet transform and neural networks (Thenkabail

In recent years, chlorophyll fluorescence (ChlF) analysis has become one of the widely used techniques available to plant physiologists and has participated increasingly in plant ecology and physiology studies (Rolando & Little, 2003; Chaerle et al., 2004; Gielen et al., 2006). This analysis has been used more extensively to provide considerable information on the organization and function of the photosynthetic apparatus (Campbell et al., 2007). The chlorophyll molecule has the ability to absorb light energy and transfer it into the photosynthetic apparatus. Excess energy can be dissipated as heat or re-emitted as light at longer wavelength, i.e. chlorophyll fluorescence. The increase in efficiency of one of these three processes (absorption, fluorescence and thermal emission) will result in a decrease in yield of the other two. As such, the relative intensities of ChlF are strongly related to the efficiency of photochemistry and heat dissipation (Papageorgiou & Govindjee, 2004; Lichtenthaler et al., 2007; Delalieux et al. 2009b) and may provide additional data to detect plant stress in an early stage. Generally, fluorescence yield is highest when photochemistry

Chlorophyll a (Chl a) is contributing largely to plant fluorescence emission. Excitation energy for this fluorescence is delivered from accessory antenna chlorophylls (Chl a and Chl b), absorbing light of blue and red wavelengths, and from carotenoids, absorbing photons of blue wavelengths. At room temperature, Chl a emits fluorescence in the red and NIR spectral regions between 650–800 nm, in two broad bands with peaks at λmax1 (684–695 nm) and λmax2 (730–740 nm) (Franck et al., 2002). The shorter wavelength emission is attributed to Chl a

Apan, 2006), artificial neural networks (Liu et al., 2008).

et al., 2004; Delalieux et al., 2007; Steele et al., 2008b).

**2.2 Chlorophyll fluorescence** 

and heat dissipation are lowest.

mostly associated to PSII (Dekker et al., 1995), whereas the longer wavelength emission originates from antenna chlorophyll of both PSI and PSII (Agati et al., 2000; Buschmann, 2007). Several environmental factors, including water, salinity, light and nutrients, affect the process of photosynthesis and may lead to plant stress. Changes in chlorophyll function take place before changes in chlorophyll content, before any physical signs of tissue or chlorophyll deterioration are manifested in the plant, and therefore alterations in the fluorescence signal occur before any visible signs are apparent (Cambpell et al., 2007; Li et al., 2010). Under conditions of stress, some plant mechanisms for disposing of excess energy do not work efficiently, thus causing changes in the competing reactions of photochemistry, heat loss and fluorescence. Although the total amount of chlorophyll fluorescence is very small (only 2 or 3% of total light absorbed), measurement is quite easy. The spectrum of fluorescence is different to that of absorbed light with the peek of fluorescence emission being at longer wavelength than that of absorption. Therefore, fluorescence yield can be quantified by exposing a leaf to light of defined wavelength and measuring the amount of light re-emitted at longer wavelengths (Maxwell & Johnson, 2000).

Various fluorescence intensity ratios, combining the emissions at blue (F440), green (F520), red (F690), and NIR (F740) wavelengths, were proposed for probing the vegetation vitality status and stress responses (Buschmann et al., 2000; Mishra & Gopal, 2008). The red ChlF emission between 684-695 nm is strongly reabsorbed by the Chl pigments in the upper layer leaf cells (Agati et al., 1993; Dau, 1994), while the NIR ChlF between 730–740 nm is reabsorbed to a much smaller extent. Consequently, the ratio between the red and far-red ChlF bands (e.g. F690/F740) decreases with increasing leaf Chl content in a curvilinear relationship, which can be used as a good inverse indicator of Chl content changes due to plant growth or stress events (Buschmann, 2007). Finally, the UV excited blue-to-red/NIR fluorescence intensity ratios (F440/F690 and F440/F740) were proposed as indicators of the leaf physiological development (Stober et al., 1994; Meyer et al., 2003), but also as marker of the nutrition availability and stress occurrence (Heisel et al., 1996).

The red and NIR fluorescence emissions by Chl a are highly dynamic, being modulated by photochemical and non-photochemical quenching. These dynamic phenomena yielded important insights into the molecular processes of photosynthesis that occur within time-scales ranging from femtoseconds to minutes depending on the power of an actively applied actinic light (Govindjee, 1995; Nedbal & Koblizek, 2006; Baker, 2008). Most widely used field observations are active, using devices exciting the photosynthetic machinery with a measuring light and recording the induced fluorescence. Introduction of the pulsed amplitude modulation (PAM) fluorometer allowed non-imaging outdoor measurements in broad daylight (Schreiber et al., 1986). Fluorescence imaging was introduced in the laboratory by Omasa et al. (1987) and modified for field surveys in the mid-1990s by Nedbal et al. (2000). The laser pulses of actinic light, which can be discriminated from static and panchromatic background light, are applied to elicit fluorescent transients when measuring fluorescence from a distance (Cecchi et al., 1994; Corp et al., 2006). The footprint of such a light detection and ranging (LIDAR) laser beam can be expanded from several centimetres up to metres to cover larger observation areas or to decrease the power of the excitation source (Saito et al., 2005). The first field laser-induced vegetation fluorescence was observed by Measures et al., (1973). Lately, an eye-safe outdoor laser-induced fluorescence transient (LIFT) fluorometer has been constructed. This device is able to measure the fluorescence parameters and nonphotochemical quenching or electron transport rate from a distance of about 30-50 m (Ananyev et al., 2005; Kolber et al., 2005). A new generation active field fluorescence

Spectral Remote Sensing of the Responses of Soybean Plants to Environmental Stresses 225

The second part of the experiments was focused on studying of the effect of the salinity on nitrogen fixing soybean plants. Three day's seedlings were inoculated with adding of 108 cells ml-1 suspension of Bradyrhizobium japonicum strain 273. After that they were transferred into plastic vessels with Helrigel nutrient solution. The nitrogen in the nutrient solution was equal to ¼ of the full dose until the growth stage of fully expanded 2nd trifoliate leaf, i.e. up to nodule forming and beginning of effective nitrogen fixation. The plants were salinity treated during the vegetative stage of growth from 2nd to 4th trifoliate expanded leaf for 14 days. Salinity was performed by means of adding in nutrient solution NaCl at two concentrations (40 mM and 80 mM). The control plants were kept only in nutrient solution. Figs. 4, 5, and 6 show the roots and nodules of nitrogen fixing control and treated with two NaCl concentrations plants on 14th day after

The third part of experiments was aimed to investigate the effect of salinity stress and two consecutive stress factors (salinity and UV-B radiation) on young nitrogen fixing soybean plants. They were grown, nitrogen fixing, and salinity treated in the same way as the plants

The investigated plants were divided into six groups. The first group consisted of untreated (control) plants. The second and third groups were only salinity treated by two NaCl concentrations. The plants of the fourth group were control (not salinized). The plants of fifth and sixth groups were treated for 14 days with 40 mM and 80 mM NaCl, respectively. Together with the control group they were irradiated with UV-B light for two hours. As a light source a lamp HPQ type with intensity 64.4 μmol m-2 s-1 was used at a distance of 25 cm. Fig. 7 a), b) shows some of investigated leaves from first (control for salinity treatment) and forth (control for treatment with UV-B radiation) groups. Fig. 8 a), b) and Fig. 9 a), b) show some leaves from plants treated with 40 mM NaCl and (40 mM NaCl + UV-B), and 80

a b

Fig. 4. Control nitrogen fixing soybean plants: a) leaves; b) roots.

mM NaCl and (80 mM NaCl + UV-B), respectively.

the salinity.

of the previous experiments.

instrument, developed by Raimondi et al. (2007), was successfully employed in summer 2007 during the joint CarboEurope, FLEX, and Sentinel-2 ESA mission campaign. These groundbased active fluorescence-sensing techniques can be used whenever temporal monitoring of fluorescence transients is required regardless of the appearance of cloud cover.

Lately, chlorophyll fluorescence techniques proved to be a non-intrusive, fast and reliable attractive tool in ecophysiological studies, and have extensively been used in assessing plant responses to environmental stress.
