1 INTRODUCTION
Optical methods present considerable advantages for in vivo and in vitro assessment of the physiological condition of live tissues as compared to chemical and physicochemical methods, because they are much faster, noninvasive and nondestructive (see, for example, BerberanSantos et al. [1–3] and references therein). Laser induced fluorescence (LIF) analysis is particularly interesting for this application because the measurements can be carried out remotely, allowing, for example, difficulttoaccess canopies to be inspected. Large plantations and woods can also be efficiently inspected, by scanning an instrument placed at a high viewpoint or by mounting the LIF LIDAR instrument in an aircraft.
Early research [4, 5] showed that the LIF spectra of plant leaves present two maxima—a local maximum at 685 nm ( ) and an absolute maximum at 740 nm ( )—the relative intensities of these maxima changing with the physiological condition of the plant photosynthetic system. LIF was applied for estimating the maturity of lettuce [6], differentiating plant species [7–9], assessing potassium deficiency related stress [10], estimating the overall metabolic activity of plants during a defined period of time [5, 11], and studying
1The article is published in the original.
I685
I740
the influence of ambient light [8], intense UV radia tion [4], atmospheric [12] and soil pollutants [12, 13], and excess of ammonium nitrate [14] on plant physi ology.
Presently, the most important optical methods for evaluating the plants physiological condition are based on the Kautsky effect (also known as fluorescence induction). In 1931, Kautsky and Hirsh [15] discov ered that the intensity of fluorescent radiation emitted by leaves suddenly illuminated after a period of dark ness increases from an initial level (usually mea sured ~20 µs after excitation) to a maximum value , observed about 1 s later. Kitajima and Butler [16]
showed that the maximum potential quantum yield of PS II photosynthesis system is characterised by the
dimensionless parameter = . A
value of of 0.832 ± 0.004 was found for healthy leaves of a very wide variety of species [17], while stress due to disease or environmental conditions is indi cated by lower values. also depends on the chloro phyll concentration in the leaves [18], which, in turn, depends on the physiological condition of the photo synthetic system, but severe stress may change the basal fluorescence yield, affecting the relation between and chlorophyll concentration. A significant increase of due to heat stress, independent of the
F0
Fm
/ m
Fv F
(
Fm−F0)
/Fm/ m Fv F
F0
F0
F0
Water Stress Assessment of Cork Oak Leaves and Maritime Pine Needles Based on LIF Spectra
1A. Lavrova, b, A. B. Utkina, b, J. Marques da Silvac, Rui Vilarb, d, N. M. Santosa, and B. Alvesa
a INOVInescInovação, Lisbon 1000029, Portugal
b Institute of Material and Surface Science and Engineering, Lisbon, 1049001, Portugal
c University of Lisbon, Faculty of Science, Department of Plant Biology and BioFIG, Lisbon, 1749016, Portugal
d Instituto Superior Técnico, Department of Chemical and Biological Engineering, Lisbon, 1049001, Portugal
email: andrei.utkin@inov.pt
Received July 13, 2011; in final form, September 15, 2011
Abstract—The aim of the present work was to develop a method for the remote assessment of the impact of fire and drought stress on Mediterranean forest species such as the cork oak (Quercus suber) and maritime pine (Pinus pinaster). The proposed method is based on laser induced fluorescence (LIF): chlorophyll fluo rescence is remotely excited by frequencydoubled YAG:Nd laser radiation pulses and collected and analyzed using a telescope and a gated high sensitivity spectrometer. The plant health criterion used is based on the I685/I740 ratio value, calculated from the fluorescence spectra. The method was benchmarked by comparing the results achieved with those obtained by conventional, continuous excitation fluorometric method and water loss gravimetric measurements. The results obtained with both methods show a strong correlation between them and with the weightloss measurements, showing that the proposed method is suitable for fire and drought impact assessment on these two species.
DOI: 10.1134/S0030400X12020166
NONLINEAR AND QUANTUM OPTICS
chlorophyll concentration, was reported by Havaux and Strasser [19]. The increase of the basal fluores cence intensity probably reflects a disturbance on the organization of thylakoid membranes [20].
In vivo chloroplast fluorescence analysis is cur rently a key tool in photosynthesis research [21]. The Kautsky effect is on the basis of the pulse amplitude modulation method (PAM) [22], which is nowadays the most common plant fluorescence analysis method.
PAM was successfully applied to a wide range of plants, including the olive tree, rosemary and lavender [23], Paspalum dilatatum [24], Phillyrea angustifolia [25], the grass Setaria sphacelata [26] and other C4 turfgrasses [27], maize [28, 29], and Arabidopsis thaliana [30], among others. Plant Efficiency Analysis (PEA), which is also based on Kautsky effect, employs
continuous wave excitation and measures the rapid rise of fluorescence intensity after a darklight transi tion [31]. It provides useful complementary informa tion to the PAM method [32]. Both methods present, however, a major drawback: they require contact with the biological material, making measurements time and labour consuming when large numbers of plants must be evaluated or when the plants are in difficult to access areas. PEA also requires a darkness adaptation period for measuring the minimal fluorescence inten sity, making the tests slow.
One of the most important problems in Mediterra nean forest management is the exact evaluation of the impact of forest fires and extended drought periods on plants health. The accurate assessment of water scar city related stress is also of utmost importance for irri gation optimization, particularly taking into consider ation the increasing global water deficit [23]. A fast, remote and contactless method of plant stress evalua tion would greatly facilitate the effective inspection of large woods and plantations. The aim of the present work was to develop a method for the remote assess ment of plants drought and fire stress based on laser induced fluorescence analysis (LIFLIDAR). The method was applied to two species of paramount importance in Mediterranean forestry, namely cork oak (Quercus suber) and maritime pine (Pinus pinas ter). The proposed method was benchmarked against PEA and water loss measurements.
EXPERIMENTAL SETUP
The experiments were carried out using the LIF LIDAR setup represented schematically in Fig. 1.
Fluorescence is excited by the second harmonic of a pulsed YAG:Nd laser (λ = 532 nm) with a pulse dura tion of 5 ns, maximum energy per pulse 20 mJ and pulse repetition rate 10 Hz. The fluorescent radiation
Sample
Fluorescence radiation Longpass filter
Light gathering optics Optical fiber
Control and data acquisition Synch
Ocean optics spectrometer Nd:YAG laser, 532 nm
Fig. 1. Layout of the LIFLIDAR system.
Start of the
800 750
700
650 λ, nm
1.0
0 0.5
Normalized signal
2 days 1 day
experiments
Fig. 2. Fluorescence spectra of cork oak leaves.
is collected by a 20 mm diameter telescope. To prevent backscattered laser radiation from entering the tele scope and saturating or damaging the spectrometer CCD, a long pass filter with a cutoff wavelength of 550 nm was introduced in the optical path, in front of the telescope. The collected radiation is transferred to a lownoise computercontrolled CCD spectrometer (Ocean Optics USB4000) by an optical fibre. In order to reduce the influence of background radiation on the measurements, the spectrometer was operated in the external triggered mode, using short time intervals (about 10 μs) synchronized with the laser pulse emis sion for data acquisition. To increase the signalnoise ratio, each spectrum results from averaging radiation collected during 10 laser pulses. The distance between the LIFLIDAR instrument and the samples was 1 m.
Analysis of the accuracy of the fluorescence inten sity measurements indicated that the main sources of errors are the instability of the laserpulse energy and the nonuniformity of the CCDdetector response.
For the equipment involved in the experiments, the total relative error of the measurements did not exceed 10% for the LIF intensities and 7% for the integral fluorescence parameter .
SAMPLES AND EXPERIMENTAL PROCEDURE
Ten leaves of mature cork oak and 40 maritime pine needles were used for each series of experiments. The leaves were collected immediately before the experi ments and stored at 22°C and 50% humidity until complete drying. Maritime pine needles required about 11 days for complete drying, while the cork oak leaves loose water much faster, in about 2.5 days. Dur ing the drying period the leaves were periodically removed from the controlled humidity oven and sub mitted to the following tests: weight measurement using an analytical balance with a precision of 0.1 mg;
evaluation of and ratio using a Handy PEA fluorometer; fluorescence spectral analysis using the instrument represented in Fig. 1. The measurements were performed once a day on the maritime pine nee dles and twice a day on the oak tree leaves. The first experiments showed that pine tree needles do not loose water uniformly, water loss being slower near the needle sheath than near its tip. To take this into con sideration, measurements were performed in two dif ferent positions along the needle length: near the sheath and at midlength. In general the values pre sented are the average of 10 measurements. The water loss was characterized by the relative water content (RWC), given by [33]:
, (1)
where DW, TW, and FWi are the sample’s dry weight, fully turgid weight, and fresh weight at , respec
/ m Fv F
F0 Fv/Fm
( )
RWCi FWi DW 100%
TW DW
= − ×
−
t =ti
tively. TW was measured at the end of each series of experiments, by weighting the samples after floating them in water until saturation. The samples were then dried in an oven at 80°C during three days and weighted to find the DW value.
2.0 1.0
1.0
0.5
0 Fv/Fm
(a)
2.0 1.0
0 600
200 F0, a.u.
(b)
400
2.0 1.0
0 1.0 I685/I740
(c)
0.5
Time, days
Fig. 3. (a), (b), and (c) vs. time for cork oak leaves. The error bars denote the standard devia tion.
Fv/Fv F0 I685/I740
800 750
700
650 λ, nm
1.0
0.5
0
Normalized signal
10 days 9 days
8 days 7 days
3 days 2 days
Start of the experiments 11 days
Fig. 4. Fluorescence spectra of pine tree needles near the sheaths.
800 750
700
650 λ, nm
1.0
0.5
0
Normalized signal
10 days 9 days
8 days 7 days
3 days 2 days
Start of the experiments
Fig. 5. Fluorescence spectra of pine tree needles at mid length.
EXPERIMENTAL RESULTS AND DISCUSSION
The evolution of the fluorescence spectra of cork oak leaves is presented in Fig. 2. In the green leaves the maximum intensity occurs at 737 nm, but, as the water deficit increases, the maximum is shifted to shorter wavelengths, reaching about 722 nm after twoday drying time. Simultaneously, a new local maximum develops at 685 nm. The corresponding variations of , , and are presented in Fig. 3. This figure shows that both the LIFLIDAR and PEA methods present good sensitivity to drought stress and show a similar evolution with the drying time.
In order to assess quantitatively the reliability of the LIFLIDAR method [34], the correlation coefficients
λmax ≈
/ m
Fv F F0 I685/I740
between = , calculated from the LIF
measurements and = and = ,
measured at the same instants , was cal culated using the equation:
(2) Λi 685/ 740
t ti
I I =
Φi 0 t ti
F = Φi /
m t ti
Fv F =
1, , ...,2 n
t =t t t
( ) ( )
( ) ( )
1
2 2
1 1
1 1
,
1 , 1 .
n
i i
i
n n
i i
i i
n n
i i
i i
R
n n
=
= =
= =
Λ − Λ Φ − Φ
=
Λ − Λ Φ − Φ
Λ = Λ Φ = Φ
∑
∑ ∑
∑ ∑
10 5
0 1.0
0.5 Fv/Fm
(a)
10 5
0 1.0
0.5 Fv/Fm
(b)
10 5
0 1000 F0, a.u.
(d)
600
200 10
5 0
1000 F0, a.u.
(c)
600
200
10 5
0 1.6 I685/I740
(e)
0.8
Time, days
10 5
0 1.6 I685/I740
(f)
0.8
Time, days
Fig. 6. Averaged values of (a, b), (c, d), and (e, f) vs. time for pine needles. Averaging is made over 10 needle bundles. The error bars denote the standard deviation of , or , or from their averaged values. Results for needle sheath are presented in Figs. 6a, 6c, 6e. Results for midlength are presented in Figs. 6b, 6d, 6f.
Fv/Fv F0 I685/I740
Fv/Fv F0 I685/I740
For cork oak the correlation coefficients are –0.93 for = and –0.99 for = , showing a strong correlation between the three datasets. This result shows that the parameter obtained by the LIFLIDAR technique is as reliable for evaluation of drought stress as the parameters obtained by the PEA method.
The evolution of the fluorescence spectra of mari time pine needles over a period of 11 days is depicted in Figs. 4 and 5. The fresh needles present a maximum of fluorescent radiation intensity at 736 nm, indepen dently of the measurement position. As the needles loose water, the maximum is shifted towards shorter wavelengths, reaching 730 nm after 11 days, while a new peak appears at 685 nm. The evolution is slower than for the cork oak, due to the lower water loss rate.
The relative fluorescence intensity at 685 nm is larger for maritime pine than for oak tree, due to differences between the photosynthetic systems of two species.
The time variation of , , and for the two measurement positions is presented in Fig. 6. The correlation coefficients of – near the nee dle sheath and at halflength are –0.88 and –0.96, respectively. For – –0.91 and –0.99 were found. The large values of the correlation coeffi cient show that the ratio can be reliably
Φi F0t t=i Φi /
m ti
Fv F
Λi
/ m
Fv F F0 I685/I740
F0 I685/I740 / m
Fv F I685/I740
685/ 740
I I
applied for monitoring drought stress in maritime pine.
The dependencies of , , and on RWC for cork oak and maritime pine are presented in Figs. 7 and 8, respectively. The results present a fairly large scatter, as expected taking into consideration the large standard deviation of the experimental data.
Even for the present conditions of uniform stress, a biunique correspondence between , , and on one hand and RWC on the other hand is observed for RWC values between 20 and 60%. When RWC > 60%, and remain approximately constant, demonstrating the resilience of the core PSII to water stress [19].
Scatterplots illustrating the joint distributions of vs. and vs. for oak tree and maritime pine are presented in Figs. 9a to 9f. The cor relation coefficients for the data presented in Figs. 9a, 9b, 9d, 9e, and 9f are –0.99, 0.93, 0.88, –0.98, and 0.96, respectively. The experimental points are situ ated approximately in a straight line, showing that the least square fitting coefficients are reliable predictors of and on the basis of , measure ments and vice versa. The correlation for the data plot ted in Fig. 9c, corresponding to the maritime pine needles near the sheaths, is also very good, but the dependence is not linear, leading to a lower correlation
/ m
Fv F F0 I685/I740
/ m Fv F F0
685/ 740
I I
/ m
Fv F F0
685/ 740
I I Fv/Fm I685/I740 F0
/ m
Fv F F0 I685/I740
100 50
0 1.0
0.5 Fv/Fm
Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Sample 6 Sample 7 Sample 8 Sample 9 Sample 10
100 50
0 700 F0, au
200 600 500 400 300
RWC, %
100 50
0 1.0
0.5 I685/I740
RWC, %
Fig. 7. Fv/Fm, F0, and I685/I740 vs. RWC for cork oak. Experimental data for all 10 cork oak leaves are presented in the figure.
coefficient (–0.91). The value of can be derived from LIF data with the same accuracy as before using methods (for example, ones based on essentially non linear artificial neural networks [35]) that do not imply linear mutual relationship between and
.
The range of the instrument used in the present work is about one meter, due to the relatively low sen sitivity of the spectrometer and the small diameter of the light gathering telescope used. Estimations based on a previously developed LIDAR model [36, 37]
show that a range of about 100 m is achievable with the same laser pulse energy if an intensified CCD detector spectrometer [38] and a 150 mm diameter telescope are used.
/ m Fv F
/ m Fv F
685/ 740
I I
CONCLUSIONS
The present results show that LIFLIDAR can be reliably used for the remote evaluation of water stress due to drought or fire in cork oak (Quercus suber) and maritime pine (Pinus pinaster). The method demon strates the same sensitivity to the changes induced by water deficit on the plants photosynthetic system as the standard in situ methods based on the Kautsky effect, and has a great potential in facilitating the inspection of large areas, because it is fast, contactless, and the measurements can be carried out remotely.
The equipment can be used in the field in order to inspect distant canopies, isolated trees and groups of trees as well as small plantations. It can also be installed in an airplane to inspect larger areas, making surveillance faster and less labourintensive.
100 80
60 40 20 0.8
0.4
0 Fv/Fm
Sample 1 Sample 2 Sample 3 Sample 4 Sample 5
Sample 6 Sample 7 Sample 8 Sample 9 Sample 10
100 50
0.8
0.4
0 Fv/Fm
(a) (b)
100 50
1000
0 F0, a.u.
(d)
500
100 50
600
0 F0, a.u.
(c)
400
200
100 50
2.4
0 I685/I740
(e)
1.2
100 50
2.4
0 I685/I740
(f)
1.2
RWC, % RWC, %
Fig. 8. (a, b), (c, d), and (e, f) vs. RWC for pine needle. Experimental data for all 10 bundles of needles are presented in the figure. Results for needle sheath are presented in Figs. 8a, 8c, 8e. Results for midlength are presented in Figs. 8b, 8d, 8f. 䊏 Sample 1, 䊐 Sample 2, 䊉 Sample 3, 䊊 Sample 4, 䉱 Sample 5, 䉭 Sample 6, 䉲 Sample 7, 䉮 Sample 8, 䉬 Sample 9,
䉫 Sample 10.
/ m
Fv F F0 I685/I740
ACKNOWLEDGMENTS
The authors wish to thank Ricardo Cruz de Car valho for assistance in the determination of RWC. This research was partially supported by project no. 2005 09 002227.7 of the Portuguese Ministry of Agriculture
“Desenvolvimento de uma técnica inovadora de avali ação do impacto dos incêndios no coberto florestal baseada em LIFLIDAR”.
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