Optics and Lasers in Engineering, 28 (1997) 443456 0 1997 Elsevier Science Limited

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All rights reserved. Printed in Northern Ireland 0143-8166197 $17.00 + 0.00

PII: SO143-8166(97)00056-O

Point-wise and Whole-field Laser Speckle Intensity Fluctuation Measurements Applied to Botanical

Specimens

Yang Zhao”, Junlan Wang”, Xiaoping Wua*, Fred W. Williams’ & Richard J. Schmidt’

” Department of Mechanics and Mechanical Engineering, University of Science and Technology of China, Hefei, Anhui 230027, People’s Republic of China

’ Cardiff School of Engineering, UWC, PO Box 686, Cardiff CF2 3TB, UK ‘ Welsh School of Pharmacy, UWC, Redwood Building, King Edward VII Avenue, Cardiff

CFl3XF, UK

(Received 5 December 1996: accepted 21 July 1997)

ABSTRACT

Based on multi-scattering speckle theory, the speckle fields generated by plant specimens irradiated by laser light have been studied using a point- wise method. In addition, a whole-field method has been developed with which entire botanical specimens may be studied. Results are reported from measurements made on tomato and apple fruits, orange peel, leaves of tobacco seedlings, leaves of shihu seedlings (a Chinese medicinal herb), soy-bean sprouts, and leaves from an unidentified trailing houseplant. Although differences where observed in the temporal fluctuations of speckles that could be ascribed to differences in age and vitality, the growing tip of the bean sprout and the shihu seedling both generated virtually stationary speckles such as were observed from boiled orange peel and from localised heat-damaged regions on apple ,fruit. Our results suggest that both the identity of the botanical specimen and the site at which measurements are taken are likely to critically affect the observation or otherwise of temporal fluctuations of laser speckles. 0 1997 Elsevier Science Ltd.

Keywords: Biospeckle; botanical; laser speckle; non-destructive testing.

1. INTRODUCTION

When a laser illuminates a rough surface, the diffused reflected laser light exhibits mutual interference and so forms random bright and dark spots,

* Currently Visiting Professor at the University of Wales Cardiff (UWC).

443

444 Y. Zhao et al.

called laser speckle, in space’. When it impinges on the surface of biological material, laser light will pass through one or more surfaces (air interface; epidermal and other cell walls), each of which will act as a stationary diffuser. Particles within the material are thus illuminated by a laser speckle field and will scatter the laser light back out through the air interface. Hence the laser light is diffused many times before finally a speckle field is formed in space; this is called “speckled speckle”‘. If the particles within the biological material are in motion, the speckle field exhibits temporal fluctuations and is said to “boi1”3 or “twinkle”4. This phenomenon has been referred to as “bio-speckle”‘.

The biospeckle phenomenon has been used extensively for measuring blood flow in the retina and other tissues+“. Motion of particles within botanical samples has also been studied’&i4. Oulamara et al.“, for example, reported differences in the temporal evolution of speckle in a tomato, an orange and an apple, but deliberately avoided presenting any hypothesis regarding the biological significance of their quantitative results. More recently, Xu et ~1.‘~ described the possible use of the biospeckle phenomenon to sense the age of a botanical sample which, in turn, would be an indicator of shelf life, on the basis that temporal fluctuations of speckle appeared to decrease with the age of the sample.

Whilst biospeckle arising from blood flow is clearly a function of the rate of movement of red blood cells, the identity of the moving particles responsible for biospeckle from botanical specimens is less obvious. Briers4 noted that the speckle fluctuation was greatest when the colour of the biological sample corresponded closely to the wavelength of the laser radiation. The assumption has been made that speckle fluctuation is a function of the cyclical motion of intracellular organelles such as chloroplasts and amyloplasts, or of the Brownian motion of mineral particles in cell vacuoles. The speed of movement is between 1 pm and 1 mm/min and is a function of temperature, illuminating light intensity, and wavelength”. It is reasonable to suppose, therefore, that a higher rate of metabolic activity in a given plant specimen will lead to increased “twinkle” of speckles, i.e. increased particle motion.

A complete theoretical analysis is very difficult. However, various useful experimental techniques have been developed to show the states of motion of particles by using the statistical properties of the dynamic speckle intensity fluctuation given as (l)-(4) below. These valuable properties have been deduced from experiments for a range of velocities which covers velocities measured in this paper, and are as follows:

1. the velocity is inversely proportional to the time correlation length; 2. the velocity is proportional to the auto-correlation coefficient r(t),

see eqn (9) later;

Point-wise and whole-field laser speckle intensity fluctuation measurements 445

3. the average deviation u is linearly related to the diffuser velocity; and

4. the contrast of the integral spatial speckle intensity is inversely proportional to the diffuser velocity.

Several applicable techniques, such as power spectral density and correlation, have been used in the literature for measuring and analysing temporal speckle intensity variations. They have been shown to provide information about the ageing of some botanical specimens.

In 1993, Briers presented a overview of published biospeckle papers4. He pointed out that the biospeckle intensity fluctuations obey the same statistics as the spatial variation of a stationary speckle pattern. These statistics can be used to measure movement of scattering particles, which is a technique of particular value in biomedical science. In cooperative experiments in 199412,13 both subjective and objective biospeckles were measured and the cut-off frequency fc of the biospeckle temporal spectrum was adopted as a parameter, in addition to al(Z) and r(t) when describing activity in botanical specimens (for (I), see eqn (10) later). Xu’” investigated techniques for measuring the time-varying biospeckle of botanical specimens. Xu’s space-time speckle pattern effectively combines the spatial and temporal features of the time-varying speckle pattern in a single two-dimensional image14.

The experimental methods for investigating blood flow and activity in botanical specimens are similar and for both cases the characteristics of the speckle field depend on the area of the detector and on the analytical method used. Quantitative measurements of blood flow velocity have been achieved, but whilst quantitative comparisons of activity in botanical samples can be made, only qualitative interpretations are as yet possible. The reasons why interpreting what may loosely be called botanical activity is harder than measuring blood velocity include the following. First, although biologists accept that particle velocities are related to such botanical activity the nature of this relationship is complex and not yet understood. Second, the flow is almost uniform and of known direction for blood vessels, whereas in botanical applications the particles at any chosen location move in essentially random directions and with a very wide range of velocities.

This paper gives experimental results obtained from a variety of botanical samples employing a point-wise method utilising three statistical parameters. Further, it reports the development of a whole-field method for acquiring speckle data from botanical specimens. Measurements have been made on tomatoes, apples, oranges, tobacco seedlings, shihu seedlings (a Chinese medicinal herb), leaves from an unidentified trailing plant, and from soy-bean sprouts. The objective was to investigate further the

446 Y. Zhao et al.

possibility that measurements of biospeckle could be used to sense ageing of botanical specimens.

2. THEORETICAL BACKGROUND AND DYNAMIC LASER SPECKLE

When a diffusing surface is illuminated by a laser, a speckle field is formed in space because of random diffusion from the surface. As the surface motion changes the speckle field will be changed, by translating or boiling, as a function of time. In the former case the speckle fields before and after are correlated, but in the latter case there is decorrelation.

The dynamic speckle field formed by a single surface is studied first, e.g. reflection by an opaque diffuser such as a metal plate, or transmission by a transparent diffuser such as a ground glass. The two main conclusions obtained are as follows: If the speckle field retains its correlation, the speckle velocity is directly proportional to the surface velocity. In this case the speckle can move a distance larger than the speckle size’. Additionally, if the speckle movement is smaller than the speckle size then at any point in space the variance of the light intensity is linearly related to the surface velocity15. If there is decorrelation of the speckle field, the temporal auto- correlation length is inversely proportional to the velocity of the surface. This kind of speckle field is a boiling rather than a translating one’.

The speckle statistics of doubly-scattered light have been analysed in several papers16s17. In this case the laser light illuminates a diffuser then the resulting diffused laser light, i.e. the laser speckle, impinges on a second diffuser. Hence a doubly-scattered speckle pattern is formed in the space behind the second diffuser. When the first diffuser moves in its plane, this doubly-scattered speckle pattern is a boiling one. In a certain velocity range, the reciprocal value of the time correlation length of the speckle is a linear function of the velocity of the first diffuser. The analysis assumes that the individual scatterings each give rise to a Gaussian speckle, but in general the doubly-scattered speckle field has a larger intensity fluctuation than does this Gaussian speckle.

In the biospeckle case, moving particles exist intracellularly behind a stationary transparent diffuser formed by the cell membrane. The illuminating laser light is first scattered by the stationary diffuser and then by these moving particles. The doubly-scattered light is diffused again by the static diffuser, i.e. the cell membrane, and so a triply-scattered speckle pattern is formed in space’1,18. Generally, doubly-, triply-, and multiply- scattered speckles are called cascade speckles or speckled speckles.

The simplest type of triply-scattered speckle pattern is illustrated by Fig. 1. This shows two parallel ground glasses D1 and D2, where D1 is a

Point-wise and whole-jield laser speckle intensity fluctuation measurements 447

Fig. 1. Triply-scattered speckle pattern.

static diffuser and D, is a moving one. D, is illuminated by a laser that has been expanded by passing through a lens and the triply-scattered speckle pattern is detected by a detector as either an objective speckle in space, or a subjective speckle in the image plane if an image lens is used. Obviously, when a botanical surface is illuminated by a laser beam the multiply- scattered speckle pattern is more complex than this. For example, boiling speckles are caused by particles inside cells moving with different speeds and in different directions. Therefore. it is reasonable to measure dynamic speckle information to learn about such activity where the word dynamic is used to imply boiling specimen and translation elsewhere.

in botanical samples, for some parts of the

The following analysis starts with those particles inside the cell that are illuminated by a speckle field diffused by the cell membrane, see Fig. 2. The particles exist in a space described by coordinates (x, y, z) and the cell membrane is in the plane (5,~). The botanical speckle field is observed in

PLANE

Krl

Fig. 2. Multiply-scattered speckle pattern from a botanical sample.

448 Y. Zhao et al.

the space (X, Y 2). Suppose there is a particle at point (xi, yi, zJ, where zi is its distance from the plane (5, q), and that its scattered light field at

plane (6,~) is

f( 5277 I xi9Yi9Zi) = aiej+i jhz eXp (jkZJ eXp

I ( $ [( 5 - xi)’ + (7 - YJ’I ) Cl)

1 where A is the wavelength of the laser, k= 27rlA and ai and $i are the original amplitude and phase angle.

Actually, f( 5,~ I Xi,Yi,Zi) is a spherical wave. The time that the particle remains within the finite brightly illuminated area of the “point” (x, y, z) is described as P(x, y, z). Of course, P(x, y, z) is a probability density, is inversely proportional to the particle velocity at each point, and is a function of time because of the movement of the particle.

The optical field just inside the membrane plane (5, 7) is

&(5,.17) = I

fYx,~,z>~ f (01) x,y,z)dxdydz (2)

while just outside the plane (5, 7) it is

B2(5>rl) =d5>rl)%m7) (3) where g([, 7) is the random spatial phase delay caused by the cell membrane. This optical wave propagates into the space (X, Y, 2). From physical optics, the optical field A(X, Y, Z) is the Fourier transform of B,(5, 7) evaluated at frequencies (X/AZ, Y/AZ), giving

A(X.Y>Z) = 3V2(5~7)1= 9 g~5,rlF’(~~y,z)f(5~1~ x,y,zWdydz

= I P(x,y,z)G(X,Y;Z) 0 F(X,Y;Z ) x,y,z) dxdy d z (4)

where 9 denotes Fourier-transformation, G(X, Y; Z) = %{g(l, v)), and

F(X,Y;Z I &Y,Z) = q(f(s,77 I q,z) Then letting

&(X,Y,Z ( x,.Y,z) = WW;Z) 0 F(X.Y;Z I x,y,z), where @ is the symbol for convolution enables eqn (4) to be written as

A(X,Y,Z) = I

P(x,y,z)*A,(X,Y;Z 1 x,v,z)dxdydz (5)

Here the function A0 (X,Y;Z 1 x,y,z) is the amplitude of the speckle field and has a much higher spatial frequency than does g(,$, 7).

Point-wise and whole-field laser speckle intensity fluctuation measurements 449

The above analysis is for static particles. Dynamic speckles are now considered. The function P(x, y, z) has a distribution which varies with time because particles move in and out of the bright speckle and 2 is measured to a fixed detector plane. Then eqn (5) can be rewritten as

A(X,Y;t) = P(x,y,z;t)A,(X,Y;x,y,z)dxdydz J (6)

The intensity Z(X, Y, t) is the product of amplitude A(X, Y; t) and its complex conjugate A*(X, Y, t) and the intensity autocorrelation function R, is important and is given by1

&(XJGX&) = (Z(X,,WZ(X,,Y,)) + 1 .WW%Xz,Yz) / * (7)

where ( ) is the ensemble average and .ZA is the amplitude auto-correlation function

J, = A(X,W,)*A(XJ’;t,) = (A(XJ,)A*(X,&)) (8) where * is correlation and the asterisk denotes complex conjugate.

High activity in botanical samples signifies particles moving with faster random speeds and with large velocity standard deviations CT,,. Then the amplitude autocorrelation function JA should be a narrow function and so from eqn (7) R, should be narrow too. Hence the narrower JA is, the greater is the fluctuation of I. If activity in the botanical sample is high. then the following qualitative results can be obtained:

1. 2.

3.

4.

The

R, is narrow and the intensity auto-correlation length is shorter; the power spectrum of intensity is wide, i.e. the cut-off frequency is higher; the temporal integrated intensity jA(X, Y; t)dt will give a blue speckle; and the speckle contrast decreases as the integral duration time increases.

speckle intensity Z(t) is a function of time t. It can be written in discrete form as Z(i), i = 1,2 ,..., N and its temporal variation can be analysed by any of the following three methods12-‘4:

1. The temporal intensity auto-correlation method uses a random discrete sample set I(i), i= 1, 2,..., N and the unifying auto- correlation coefficient

N/? ..- c Z(i)Z(i + t)

r(t) = i=l

Max [( ~~20). (?12(i=O)] (9)

450

2.

3.

Y. Zhao et al.

where r(t) I 1, r(0) = 1 and r(t) decreases if the intensity of boiling is fast. In the al@ ratio method, the standard deviation of the intensity fluctuation is u and the average of the intensities, from 1 to N, is

(I), giving

(1) = + $ z(i), u = d 5 [Z(i) - (Z)12/N (10) 1=1 i=l

So as far as random fluctuation is concerned, faster fluctuation corresponds to a higher value of o/(Z). For the temporal frequency spectrum or power spectrum analysis method, if the intensity is measured N times at time intervals of T then the sample function Z, and frequency density function of the spectrum Fs(y) can be represented by

N-l

I, = T 2 Z(nT)S(t - nT) n=O

N-l N-l

F,(Y) = s{Z,(t)) = c [In] X 9(S(t - nT)J = c Z,exp[ - j27rT] n=O n=O

where Y is frequency. When Y = m/NT, F,(Y) can be expressed as N-l

F,(mINT) = 2 Z,exp ( - j2 rrnrn/N) (11) n=O

The cut-off frequency of this spectrum is an important parameter and the higher the intensity of boiling, i.e. for faster boiling, the higher the cut-off frequency must be.

3. EXPERIMENTS

For the point-wise method, the set up is as shown on Fig. 3, i.e. the specimen is observed point by point. The illuminated area (the “point”), is about 1 mm in diameter and the diffused reflected light forms a speckle field in space. The speckle intensity can be recorded by either of two methods. In the first method the speckle falls directly onto the charge coupled device (CCD) chip without passing through the lens of a CCD camera, i.e. the objective speckle field is recorded. In the second method, a CCD camera with a lens is used and so the subjective speckle field is recorded.

Point-wise and whole-field laser speckle intensity fluctuation measurements 451

I IMAGE PROCESSING SYSTEM

Fig. 3. Point-wise measuring.

Previously described methods have all used the point-wise method and have detected subjective speckles. The results which follow are for the objective speckle as recorded both by the point-wise and whole-field methods. These experimental results are compared by using a variety of methods.

The set up for the whole-field method is shown in Fig. 4, which is very similar to Fig. 3. The expanded laser beam illuminates the specimen so that its image is recorded by the CCD chip and appears as a distinct image on

I IMAGE PROCESSING SYSTEM

Fig. 4. Whole-field measuring.

452 Y. Zhao et al.

the monitor screen. The monitor screen also shows speckles on the specimen image. This method has not been reported before.

However, in any recording method the speckle size should be larger than the detector element, here the pixel of the CCD chip, and in general the size must be larger than four pixels. The speckle size can be controlled by adjusting the distance between the specimen and the CCD chip if no lens is used and otherwise the lens aperture can be changed. The laser is an He-Ne laser with wavelength 0.633 pm and power 5 mW. At each measured area, the speckle intensity was recorded as a function of time at three arbitrary pixels and the collecting frequency was 50 Hz. The results, r(t), a@) and fc, are the averages of those calculated parameters which come from over 10 measurements over a period of several minutes at each selected pixel.

3.1. Whole-field method

As shown in Fig. 4, an enlarged and distinct image of the whole specimen is seen on the monitor screen. Because the speckle size is greater than the pixel size, several suitable pixels can be chosen in each measured part. Hence the speckle intensity fluctuation can be recorded by an image processing system and the statistical parameters of intensity fluctuation can be analysed by computer, using any one of the above three formulae in Section 2, see eqns (9)-(11). Th e results given by such computations were similar to those reported below for the point-wise method.

The first specimen examined was a leaf from an unidentified trailing house-plant. The leaf image and associated twinkling speckles could be seen on the monitor screen. At an area near to the main vein speckles twinkled rapidly, whereas at the leaf margin the speckles twinkled more slowly.

The second specimen was a soy-bean sprout which was growing in water. It was about 80-90 mm long and 4 mm in diameter. The whole-field experiment showed that the most active part was a small section very near the bean, while at other positions the activity levels were lower. Actually, on the various parts of the sprout, the different rates of twinkling could be distinguished easily by eye.

The statistical properties of the speckle intensity fluctuation of the leaf and bean sprout are similar to those from point-wise measurement, shown later as Figs 5 and 6.

These results demonstrate that the whole-field method is able to generate useful comparative data that could possibly be used in non- destructive testing of the vitality of botanical samples.

Point-wise and whole-field laser speckle intensity fluctuation measurements 453

08-

06-

04.

0 52

02. oldest middle youngest

0 123401234012345

TIME t (200 ms)

Auto-correlation curves of leaves of different ages, i.e. oldest, middle and youngest. - vem, . . . . . margin, showing the value (T/(I) by each curve.

3.2. Point-wise method

The angle between the illuminating and receiving directions is lo”-20” (Fig. 3). The detector is put at some distance from the illuminated surface and, for comparisons between different plants, this distance should not be changed again, either for objective or subjective speckle measurements.

The seven specimens tested experimentally and the reasons for the experiments are as follows:

An inanimate object, actually a metal plate, was tested to show a static speckle. The reliability of the measuring system and of the data processing program could thus be confirmed. Three leaves from an unidentified trailing house-plant were tested. They were obtained from near the top, middle and bottom of a single trailing stem. These three leaves were of different ages. A soy-bean sprout was tested to examine the nature of variation observed qualitatively by the whole-field method.

:

tip

I

near bean II

I

middle

t I I I AL I 1

12340123401234

FREQUENCY (Hz)

the

Fig. 6. Temporal frequency spectrum of soy-bean sprout near the bean, in the middle and at the tip.

4.54

4.

5.

6.

7.

Y. Zhao et al.

A tomato was tested when first purchased and then three days later, in order to study the relationship between speckle statistical properties and time since picking. Tests were performed on fresh and heat-damaged surfaces of an apple. Heat-induced damage was produced by branding the apple by bringing a hot soldering iron into contact with its surface. Results were also obtained for a heated surface obtained by placing a light bulb about 0.3 m from it for 1 h. Tests were performed on fresh and boiled (for 20 min) orange peel. The results are not presented in detail, but were totally different from each other, because one specimen was alive and the other was dead and had extremely low biospeckle activity. Fresh leaves from tobacco and shihu seedlings growing in culture flasks were tested. Both seedlings were of about the same size, shape and green colour. Again, the results are not presented in detail, but were totally different from each other, with the shihu showing extremely low biospeckle activity, whereas the tobacco showed high laser speckle activity. (Shihu is a Chinese medicinal herb. Botanically, it is derived from orchid species of the genus Dendrobium.)

Figures 5 and 6 give the statistical properties of speckle intensity slow fluctuations of the leaves and bean sprout, respectively. Table 1 shows that, for tomato and apple, respectively, the lowering or loss of vitality has an obvious relationship with dynamic speckle statistical properties. The fresh fruit has small r(t), large u/(I) and high fc. However, when activity at different sites of a soy-bean sprout was measured, activity progressively

TABLE 1 The statistical parameters of temporal intensity fluctuation

Specimen Age VI@ f&W

SOY-BEAN SPROUT

TOMATO

APPLE

LEAF margin/vein

near bean 0.26 2.9 middle 0.17 1.4 tip 0.13 1.1 fresh 0.48 2.3 three days later 0.44 1.3 fresh 0.45 1.6 one night later 1.5 heated surface 0.8 branded surface 0.12 0.15 oldest 0.2710.29 0.3911.2 middle 0.3410.48 0~58l1.5 youngest 0.461052 l.Wl.7

Point-wise and whole-field laser speckle intensity fluctuation measurements 45s

decreased towards the growing tip of the sprout. Also, measurements on two different seedlings revealed that whilst high activity was present in tobacco seedlings, virtually no activity was observed in shihu seedlings.

4. CONCLUSIONS

1. From the statistical analysis and experimental data it is concluded that both the pointwise method and whole-field method are effective techniques and that laser biospeckle statistical properties can be used to measure activity in botanical samples.

2. The whole-field technique allows the experimental conditions to be controlled easily, because there is no need to move anything in order to measure each part of a plant during the course of an experiment. Hence, experimental results can readily be compared with each other.

3. Measurements of laser biospeckle activity from botanical samples appear to provide a means of sensing ageing and vitality.

4. Low biospeckle activity may, but does not necessarily, signify a dying or dead tissue; rather, it would appear to be a measure of low metabolic rate. Shihu seedlings, as do orchids generally, grow only very slowly (= 3 mm per year for shihu) and showed extremely low laser biospeckle activity, whereas tobacco seedlings grow very quickly (order of 0.2 m per month) and showed high laser biospeckle activity.

5. Higher biospeckle activity indicates higher flow rates in the veins of botanical specimens and hence conceivably could be useful in nutrient transportation system studies.

ACKNOWLEDGEMENTS

Financial support from the National Science Foundation of China and from the Cardiff Advanced Chinese Engineering Centre of the University of Wales Cardiff is gratefully acknowledged.

REFERENCES

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and speckled-speckle statistics. Journal of Optical Society of America, 71 (1981) 914-916.

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11. Oulamara, A., Tribillon, G. and Duvernoy, J., Biological activity measurement on botanical specimen surfaces using a temporal decorrelation effect of laser speckle. Journal of Modern Optics, 36 (1989) 165-179.

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13. Wang, J., The relationship between the biospeckle statistical properties and botany activity. B.Sc. thesis. University of Science and Technology of China, Hefei, China, 1994.

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15. Zhang, Q., Wu, X. and Zhang, P., Noncontact measurement for random vibration by laser speckle correlation technique. Journal of Experimental Mechanics, 5 (1990) 190-195. (in Chinese)

16. O’Donnell, K. A., Speckle statistics of doubly scattered light. Journal of the Optical Society ofAmerica, 72 (1982) 1459-1463.

17. Okamoto, T. and Asakura, T., Velocity dependence of image speckle produced by a moving diffuser under dynamic speckle illumination. Optical Communication, 77 (1990) 113-120.

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