Photosynthesis Research 25: 309-316, 1990. © 1990 Kluwer Academic Publishers. Printed in the Netherlands.

Technical communication

Computer-controlled pulse modulation system for analysis of photoacoustic signals in the time domain J6rg Kolbowski, Heinz Reising & Ulrich Schreiber Lehrstuhl Botanik I, Universitiit Wiirzburg, Mittlerer Dallenbergweg 64, D-8700 Wiirzburg, FRG Received 6 October 1989; accepted 8 May 1990

Key words: photoacoustics, photosynthesis, O2-evolution, gas-exchange, heat evolution, chlorophyll fluorescence Abstract

A newly developed photoacoustic system for measurement of photosynthetic reactions in intact leaves is described. The system is based on pulsed light-emitting diodes, the pulse program and pulse response analysis being computer controlled. Separation of various components in the overall photoacoustic signal is achieved by curve fitting analysis of the responses following individual measuring light pulses in the millisecond time domain. This procedure is in distinction to the conventionally used analysis in the frequency domain, with the advantage that various signal components are obtained by on-line deconvolution, yielding simultaneous recordings of photothermal (complement of energy storage) and photobaric (evolution and uptake) signals. The basic components of the new system are described by block diagrams and the principal steps for deconvolution of the overall photoacoustic response are outlined. An example of application with simultaneous recording of chlorophyll fluorescence is given. It is apparent that the photobaric uptake component represents a significant part of the overall signal, particularly during induction of photosynthesis after dark-adaptation. This component probably contains not only O2-uptake but uptake of CO 2 as well.

Abbreviations: P A - photoacoustic, L E D - light-emitting-diode; R A M - random access memory

Introduction

Since the introduction of the photoacoustic method (PA-method) to photosynthesis research (Malkin and Cahen 1979, Bults et al. 1982) this non-destructive method has proven to yield important information on various aspects of photosynthetic energy conversion in intact leaves (see e.g., Buschmann and Prehn 1983, Poulet et al. 1983, Canaani and Malkin 1984, Havaux et al. 1986, Malkin 1987). The PA-signal is composed of photobaric and photothermal components, originating from the pressure changes caused by light-induced, photosynthetic gas exchange and heat release (Bults et al. 1982). These two main

components can be distinguished experimentally by their frequency dependency and their response to saturating non-modulated background light. The photobaric signal is predominantly suppressed at modulation frequencies above about 200Hz (Poulet et al. 1983) and upon application of saturating background light the photobaric component is suppressed, while the photothermal component becomes maximal (Bults et al. 1982, Poulet et al. 1983). In most previous PA-studies with leaves, conventional lock-in amplifier technology has been applied for signal analysis: modulated excitation light is produced by means of a mechanical chopper, and separation of various PA-signal

310 components is achieved by proper choice of modulation frequency and phase angle. To obtain selective information of photobaric and photothermal components with this commonly used method, normally consecutive experiments are done at two different modulation frequencies, a procedure which relies on full reproducibility of measurements. Here we describe a newly developed, computer-controlled PA-measuring system based on pulsed light-emitting diodes (LED), with which it is possible to separate photobaric and photothermal signal components on-line by analysis of the PA-response in the millisecond time domain. It will be shown that under certain conditions the photobaric signal contains a large negative component, presumably reflecting light-induced uptake of 0 2 and of CO 2. The new PA-measuring system

In Fig. 1 the essential parts of the overall measuring system are shown in a block-diagram. Polyfurcated fiberoptics (101 F, Walz) link the PA-cell with various light-sources and the emitter-detector unit of a modulated chlorophyll fluorometer (PAM fluorometer, Walz). Pulsed PA-measuring light is produced by two LEDs (Stanley H-3000, peak wavelength 650 nm). Con-

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tinuous actinic white and far-red light is obtained from fiber illuminators (KL 1500, Schott), equipped with a short-pass filter (A ~ A t>700 nm (RG 710, Schott; NIR, Balzers), respectively. Saturation pulses of white light (5000 ~ E m -2 S - I ) are produced by a FL 103 lamp (Walz) controlled by the PAM fluorometer. A twin-type PA-cell is used (laboratory-built), with two condenser microphones (BL 1785, Knowles) in separate, identical leaf chambers, only one of which is illuminated. A differential amplifier eliminates non-specific signals not caused by the modulated measuring light. The construction of the single chambers is very similar to that developed at the Weizmann Institute (Cahen 1981), which has become commercially available (Applied Photophysics). The synchronized production of LED measuring pulses and PA-signal analysis is achieved by the combination of a laboratory-built 'control unit', details of which are presented in Fig. 2, and a Macintosh II data acquisition system. Via the computer, LED measuring pulses and triggering of the various actinic light sources are programmed. Furthermore, with the aid of the computer, the data processed by the 'control unit' are stored and analysed with respect to the various signal com-

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Fig. 1. Block diagram of overall set-up incorporating pulse modulation system for measurements of photoacoustic, fluorescence

and P700 absorbance signals. For further description, see text.

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ponents. The resulting graphs, together with the fluorescence signal, are registered via a printer (Image Writer II, Apple). Details on signal processing in the 'control unit' are presented in Fig. 2. In this unit all electronic components for the generation of pulsed measuring light and for synchronous analog processing of the PA-signals are incorporated. A central role is played by a programmable read & write memory (Pulse RAM) with 1 Kbyte storage capacity (8 bit times 1024 points). By cyclic addressing, at the output of the Pulse RAM, eight independent control pulses are provided, two of which serve to control the LED driver (current pulses), while the remaining six control the sample & hold switches of the Synchronous Amplifier (sample pulses) (see also Fig. 3). Cyclic addressing is in 1024 steps via the outputs of an Address-Counter which is driven by a quartz-stabilized frequency-generator. Analog processing of the pre-amplified signal occurs in the Synchronous Amplifier, with each of three measuring channels involving two sample & hold units and a differential amplifier with variable gain and damping, controlled by a Parameter RAM. The three channels correspond to

three selected time windows, at which the amplitude of the PA-signal is sampled (see also Fig. 3). The resulting three analog signals are further processed in the Data Acquisition System. The Parameter R A M serves as a buffer memory to store the system parameters, i.e., measuring frequency, gain, damping and light-intensity. It is programmed by the computer, together with the Pulse RAM, via a 24-channel digital I / O interface. Transfer of the relevant information to the two RAM-units is via an internal bus system, consisting of Data-, Control- and Address-Bus. By use of the RAM-units for control of the pulsed measuring light and of synchronous amplification, a high degree of flexibility is achieved at low expenditure of hardware components. The flexibility, for example, also extends to measurements using the conventional lock-in measuring principle.

PA-pulse responses Figure 3 shows a typical individual PA-pulse response as obtained with the new measuring system, in relation to the timing of the LEDpulses and the measurement of three different

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Fig. 3. Pulse program in relation to an individual photoacoustic pulse response in the time domain between two consecutive

pulses. The 'time windows' tl, t2 and t3 correspond to the sampling periods for photothermal, evolution and uptake signals, respectively, used with on-line measurements. Tobacco leaf, 2 h dark adapted. See text for further discussion. signal components during selected time windows (t 1, t 2 and t3) by the synchronous amplifier. The positioning of these windows is based on information on the pulse responses of the three main PA-components separated by a curve fitting procedure described below (see Figs. 4-8). In the given example the two L E D s are triggered simultaneously at time zero, to give a light pulse of 720/~s length. Two sample & hold units each serve for measuring the three different signal components by comparison of the signal amplitudes shortly before the LED-pulse and at the times tl, t2 and t 3. I~ED-pulses are repeated every 22.5 ms. In practice, pulse width and frequency, as well as the position of the sampling time windows are variable with a resolution of 1024 time addresses. This feature provides for a high degree of flexibility of the measuring system. The 'selective time window method' is the basis for on-line deconvolution of the overall PA-response into three different components (see following section). The PA-pulse response depicted in Fig. 3 displays positive and negative components. De-

pending on the physiological conditions of the leaf and, in particular on the state of preillumination, individual pulse responses can vary significantly. This is shown in Fig. 4, which displays four different PA-pulse responses of a tobacco leaf, in dependence of the time of preillumination by the measuring light. It is apparent, that 600 •~

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Fig. 4. Variety of individual PA-pulse responses resulting from different states of pre-fllumination. A 2 h dark-adapted tobacco leaf was pre-illuminated for the indicated times with the pulsed measuring light (integrated intensity 20/~E m -2 s-l; peak wavelength 650 nm).

the negative signal is most pronounced with a dark-adapted leaf, and disappearing with prolonged illumination. The overall PA-signal is composed of a rapid positive component peaking around 840/~s, a slow positive and an even slower negative component with peaks at 4.5 and 7 ms, respectively, the amplitudes of which are highly variable. While the rapid positive component can be assumed to represent the photothermal signal (including some unavoidable nonphotosynthetic contribution from cuvette walls and windows), the slower positive and negative components reflect O2-evolution and uptake of 0 2 or CO 2, respectively. As will be shown in the following section, it is possible to deconvolute the overall PA-signal by on-line computer-aided analysis, such that continuous, parallel information on heat dissipation, O2-evolution and the uptake signal is obtained.

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Fig. 5. Determination of photothermal component in the overall PA-signal. The saturated thermal component is obtained upon application of saturating non-modulated background light. The actual contribution to the overall signal is calculated by normalization of the initial rise. Tobacco leaf, steady-state illumination at 20/~E m -2 s -1.

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Deconvolution of the overall PA-signal into the three main components (photothermal, 0 2evolution and uptake signal) is achieved in two steps: 1. By application of saturating non-modulated background light the photobaric responses are selectively suppressed, such that the pure photothermal signal remains. Assuming that the curve shape of the thermal response is independent of background illumination, its contribution to the overall PA-pulse response in absence of saturating background light can be calculated by normalization of the initial rise (see Fig. 5). Subtraction of this normalized thermal component from the overall signal leads to the total photobaric signal, depicted in Fig. 6. 2. Deconvolution of the photobaric signal into evolution and uptake components, as shown in Fig. 6, is accomplished via a curve fitting procedure on the basis of 'model responses' for pure evolution and uptake signals, stored in computer memory (see Fig. 7). These 'model responses' were obtained with very similar leaf material under conditions leading to maximal suppression of the respective other component: O2-evolution is largely suppressed following over-night dark-adaptation,

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Fig. 6. Deconvolution of evolution and uptake components from total photobaric PA-signal, which was obtained by subtraction of normalized photothermal component from overall PA-signal. Deconvolution involves a fitting procedure based on computer-stored pure evolution and uptake pulse responses (see Fig. 7). Condition as for Fig. 5.

while the uptake signal is negligible after pre-illumination with saturating light. The 'model responses' are corrected for the photothermal component, as described above (see Fig. 5). The fitting procedure is based on the assumption that any measured photobaric PAresponse (i.e., the signal after subtraction of the photothermal component) can be described by a linear superposition of O2-evolution and uptake 'model responses' multiplied by appropriate amplitude factors. As shown in Fig. 8, this assumption has proven correct for a variety of different PA-pulse responses: In all cases a close fit between the measured

314 what different 'model responses', on which deconvolution has to be based. In this way, at any time during leaf illumination with pulsed measuring light, the newly developed PA-system can provide simultaneous information on the relative extent of heat formation, O2-evolution and of the uptake signal. To obtain complete traces of separated PA-pulse responses with a high signal/noise ratio, as in the examples of Figs. 4-8, about 125 individual pulse responses must be averaged and submitted to the curve fitting procedure described above. With the present speed of data acquisition and calculation this procedure yields about one set of separated responses per 30 s. For on-line recording of the three signal components, a more rapid fitting procedure is used, which is based on signals sampled during three 'selected time windows' (see Fig. 3). In this case not the complete pulse responses, but only data points for the selected window periods are calculated. As with the complete responses, first the photothermal contribution is subtracted, and then the relative contributions of evolution and uptake signals are determined by solving two equations with the two unknown amplitude factors, (a) and (b) (see Fig.

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Fig. 7. 'Model responses' for pure evolution and uptake pulse signals, which are stored in computer memory and used for deconvolution of evolution and uptake components in overall photobaric PA-signals. To obtain the selective uptakecurve, a tobacco leaf was dark-adapted over-night, illuminated with pulsed measuring light (40 ~ E m -2 s -x) for 30s and the then measured signal averaged over 30 s. For the selective evolution-curve a tobacco leaf was preilluminated for 10rain at saturating light intensity (2000/~Em-2s -1 white light).

pulse responses and the fitted curves calculated from the 'model responses' was achieved. Due to differences in leaf morphology, which has an influence on diffusion parameters, different leaf material yields some-

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Fig. 8. Comparison of four different photobaric PA-signals, after correction for photothermal component, with the corresponding curves calculated by the computer fitting routine on the basis of stored 'model responses' for evolution and uptake pulse signals. Assumed amplitude factors for evolution (a) and uptake (b) are indicated. The lines show the measured responses, whereas the dots correspond to the calculated signals (not all data points shown). Tobacco leaf, with different PA-responses produced by different states of preillumination (see also Fig. 4).

315 8). The time window chosen to characterize a particular component is positioned such that the relative contribution of the two other components is minimal. The relevant information for the time windows is obtained from a full deconvolution of the three pulse responses carried out for a particular leaf material. The 'selected time window' method for on-line measurements presently allows a deconvolution rate of two points/ sec. Two examples for on-line measurements are presented in Fig. 9. In parallel with the PAsignals, also modulated chlorophyll fluorescence is recorded. Instead of heat release, the percentage of 'energy storage' in photosynthesis is depicted (previously also called 'photochemical loss'; Malkin and Cahen 1979, Bults et al. 1982), which is equivalent to the increase of the ob-

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served heat release induced by application of saturating background light relative to the heat release observed in the presence of saturating background light. In the given examples, changes in energy storage are rather small, particularly in the experiment with longer dark adaptation of the leaf. In part this probably is due to a non-photosynthetic contribution (from cuvette walls and windows) to the photothermal signal. For better comparison, the uptake signal is displayed as a positive trace, as is O2-evolution. Both photobaric signals reflect quantum yields of the corresponding photochemical reactions, as the applied measuring light intensity is rather low. It is apparent that the uptake signal overlapping O2-evolution is quite large, in particular following a longer period of dark-adaptation. In the 45 min dark-adapted sample 0 2evolution transiently reaches zero, about 45s following onset of illumination. In the 10 min dark-adapted sample, where significant changes in energy storage are observed, these changes are closely related to changes of the uptake signal, an observation which has been reproduced in a number of other experiments (not shown). A discussion of the mechanistic causes of this correlation and of other phenomenological properties is beyond the scope of the present communication. At present it is not clear to what extent the uptake signal is caused by uptake of 0 2 or CO 2. Preliminary experiments suggest, that at least part of it may reflect rapid CO2-solubilisation (Laisk et al. 1989).

Conclusions

Fig. 9. Simultaneous recordings of photosynthetic energy storage, oxygen evolution, gas uptake and chlorophyll fluorescence using the newly developed measuring system. Deconvolution of the three different PA-signal components is achieved by on-line computer analysis using the 'selected time window method' (see Fig. 3). Induction kinetics of a tobacco leaf dark-adapted for 10 rain (A) and 45 rain (B) are presented. Actinic light (AL) is identical to pulsed PAmeasuring light (integrated intensity 40 p E m - 2 s - 1 ; peak wavelength 650 nm).

It was the aim of this work to develop a new type of PA-measuring system with which it is possible to obtain simultaneous information on heat dissipation, O2-evolution and gas-uptake in intact leaves. This aim has been reached by introducing modern solid state electronics and data acquisition methods to the analysis of PA-responses in the millisecond time domain following individual LED measuring pulses. With this achievement, the PA-method has become an even more powerful tool in the study of photosynthetic reactions in leaves. In particular, it appears important that the new method allows separation of an uptake

316 component from the O2-evolution signal. Future work must reveal how much of this uptake signal is due to 0 2- or CO2-uptake. To clarify this point it will be essential to modify the PA-cell in such a way that the gas composition can be controlled without significant loss in signal/noise ratio. A major field of research, where the described PA-measuring system should yield new insights, concerns the interpretation of photochemical and non-photochemical chlorophyll fluorescence quenching. The lay-out of the system makes it fully compatible with a recently developed modulation fluorometer (Schreiber 1986, Schreiber et al. 1986) which allows quenching analysis by application of saturating light pulses. It will be an important aim of future work to find out which components of non-photochemical fluorescence quenching are correlated with rapid heat dissipation reflected in the photothermal PAsignal.

Acknowledgements Ulrich Schliwa is thanked for help in electronic engineering. Shmuel Malkin, Ulrich Heber, Christof Klughammer and Jan Snel are thanked for helpful discussions and suggestions. This work was supported by the Deutsche Forschungsgemeinschaft (SFB 251). References BuRs G, Horwitz BA, Malkin S and Cahen D (1982) Photoacoustic measurements of photosynthetic activities in

whole leaves. Photochemistry and gas exchange. Biochim Biophys Acta 679:452-465 Buschmann C and Prehn H (1983) In vivo photoacoustic spectra of Raphanus and Tradescantia leaves taken at different chopping frequencies of the excitation light. Photobiochem Photobiophys 5 : 6 3 - 6 9 Cahen D (1981) Photoacoustic cell for reflection and transmission measurements. Rev Sci Instr 52:1306-1310 Canaani O and Malkin S (1984) Distribution of light excitation i n ' a n intact leaf between the two photosystems of photosynthesis. Changes in absorption cross-sections following state 1-state 2 transitions. Biochim Biophys Acta 766:513-524 Havaux M, Canaani O and Malkin S (1986) Photosynthetic responses of leaves to water stress, expressed by photoacoustic and related methods. I. Probing the photoacoustic method as an indicator for water stress in vivo. Plant Physiol 82:827-833 Laisk A, Oja V, Kiirats O, Raschke K and Heber U (1989) The state of the photosynthetic apparatus in leaves as analysed by rapid gas exchange and optical methods: the pH of the chloroplast stroma and activation of enzymes in vivo. Planta 177:350-358 Malkin S (1987) Fast photoacoustic transients from darkadapted intact leaves: oxygen evolution and uptake pulses during photosynthetic induction- a phenomenology record. Planta 171:65-72 Malkin S and Cahen D (1979) Photoacoustic spectroscopy and radiant energy conversion: Theory of the effect with special emphasis on photosynthesis. Photochem Photobiol 29:803-813 Poulet P, Cahen D and Malkin S (1983) Photoacoustic detection of photosynthetic oxygen evolution from leaves Quantitative analysis by phase and amplitude measurements. Biochim Biophys Acta 724:433-446 Schreiber U (1986) Detection of rapid induction kinetics with a new type of high-frequency modulated chlorophyll fluorometer. Photosynth Res 9:261-272 Schreiber U, Schliwa U and Bilger W (1986) Continuous recording of photochemical and non-photochemical chlorophyll fluorescence quenching with a new type of modulation fluorometer. Photosynth Res 10:51-62