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 CHEMICAL ENGINEERING TRANSACTIONS  
 

VOL. 58, 2017 

A publication of 

 
The Italian Association 

of Chemical Engineering 
Online at www.aidic.it/cet 

Guest Editors: Remigio Berruto, Pietro Catania, Mariangela Vallone
Copyright © 2017, AIDIC Servizi S.r.l. 
ISBN 978-88-95608-52-5; ISSN 2283-9216 

Challenges to Apply the Biospeckle Laser Technique in the 
Field 

Roberto A. Braga 
Federal University of Lavras, CP 3037 Lavras 37200-000 MG Brazil 
robertobraga@deg.ufla.br 

Biospeckle laser, or dynamic laser speckle, is used as a technique when its outcomes are useful to monitor 
activity of the illuminated sample. The term “bio” means the relation of the activity with biological material, and 
the adoption of the dynamic laser speckle has been reported since 1970s, initially in blood flow monitoring. 
The range of applications improved along the years from medicine to agriculture, food and other areas. 
However, despite the increase of applications, there are some limits or challenges that are necessary to 
overcome in order to make this technique useful far from the optical laboratories. The instability of the solid-
state lasers, used to reduce the size of the setup, as well as the influence of the external light and vibration 
can compromise the results and are some examples of the limits found. The standardization of the procedures 
to maintain the repeatability is another issue that must be faced, associated to the portability and accessibility 
of the devices. This work presents the state of the art in the area of biospeckle laser application and discuss 
the efforts that have to be taken to make it accessible, robust and reliable. A proposal of a free library in M 
code (Matlab and Octave) with its tutorial is presented and shared as a way to start the standardization of the 
image analysis. The library has a collection of numerical and graphical codes, as well as frequency filters to 
isolate phenomena. A list of applications is presented associated to the advances regarding the new born 
experimental configurations, mainly related to the digital devices used to acquire and to analyze the data. 

1. Introduction 

The Biospeckle Laser (BSL) is a dynamic interferometric phenomenon (Rabal & Braga 2008), which has been 
adapted as a sensitive tool to monitor changes in biological samples, and thus it has been applied in many 
areas, from medicine (Briers 1975, Asakura 1988) to agriculture (Xu et al. 1995, Zdunek et al. 2014), since the 
fact that it is a Non-Destructive Technique (NDT) is relevant in biological applications. 
The multitude of applications is associated to a range of methods to illuminate, to assemble the images and to 
provide their analysis. The applications in agriculture offer the potential monitoring of alive phenomena by a 
NDT approach, in a sensitive way, overcoming the time consuming and the human dependence of judgement. 
The identification of activity in seed analysis (Braga et al. 2003), the study of the growing process in roots 
(Braga et al. 2009) or even the monitoring of maturity of bruising in fruits (Xu et al. 1995, Pajuelo et al. 2003, 
Kurenda et al. 2012) are some examples of feasible applications. 
The static appearance of a speckle pattern is expressed by an image with clear and dark grains distributed 
over all the illuminated material as presented in Figure 1, where a tissue of a root growing in a gel, in this 
case, magnified in one portion of the root to be possible to observe the grains. Since it is a dynamic 
phenomenon, the speckle pattern expresses the boiling effect with the grains changing their shape and level 
of lightness related to the level of movement of the scatterers of the coherent light. The scatterers in an inert 
material, for example, do not change, so much so, the boiling effect isn’t observed, whilst the boiling is 
observed in the tissue of the root, and its intensity is linked to the level of activity.  
One outcome of the BSL is the map of activity, as observed in Figure 2, where the Generalized Difference 
method (Arizaga et al. 2002) was applied. Thus, the map of activity that can be displayed in pseudo-colour 
located in the areas where one has more activity of the scatterers in time, in red, and where one has low 
activity, in blue. From blue to red it is possible to tag the level of activity and with it classify the biological 
phenomena that caused the boiling effect. Since a biological material is very complex with a multitude of 

                               
 
 

 

 
   

                                                  
DOI: 10.3303/CET1758097

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Please cite this article as: Braga R., 2017, Challenge to apply the biospeckle laser technique in the field, Chemical Engineering Transactions, 
58, 577-582  DOI: 10.3303/CET1758097 

577



phenomena occurring at the same time, in most cases it is impossible to isolate directly the main cause of the 
dynamic effect. Despite the feasible application in seeds, fruits, roots, as well as in animal sperm (Carvalho et 
al. 2009), parasites (Pomarico & DiRocco 2004), and many others in agriculture, the main limitation so far is 
the restriction to optical laboratories. The main aim of this work is to identify the challenges to use the 
biospeckle phenomenon in the field facing all sort of interferences suggesting some alternatives to overcome 
the limits. 

 

Figure 1: Outcome of an illumination of a sample using the laser, with the grains representing the speckle, 
amplified to magnify the grains. Raw data of root of coffee from Centre for Development of Applied 
Instrumentation in Agriculture (CEDIA) 
 

 

Figure 2: Outcome of the dynamic image of speckle in time after graphical processing with the map of activity. 
Raw data of root of coffee from Centre for Development of Applied Instrumentation in Agriculture (CEDIA) 

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2. Electing the limits 

The absence of a standard, and even of a commercial equipment dedicated to agriculture to create some 
common approaches can be considered the main limit to the biospeckle accessibility as a technology to 
measure biological activity. 
However, the development of digital electronics and laser sources opened new doors regarding the biospeckle 
laser phenomenon and certainly the possibilities to build reliable equipment. New cameras, computers and 
lasers did a revolution in the applications as well as in the field of image and signal analysis. The migration to 
the usage of biospeckle phenomenon in the field, such as measuring water activity in leaves without tear 
them, or the presence of biological material in a soil must overcome the limits regarding placed by the use 
outside doors with light and noise interference. 
The light interference can be circumvented using dark environment around the laser and the digital camera. 
While the noise can be circumvented by the adoption of fast measurement techniques, such as the ones 
adopted in blood flow monitoring in alive human beings (Briers & Webster 1996, Godinho et al. 2012). Fast 
measurement means the measure using only one image or a short collection of image faster enough to avoid 
the mechanical noise interference. 
In Figure 3, it is possible to gather some challenges that can be addressed to enhance the hardware and 
software allowing the portability and robustness needed. 

 
Figure 3: Scheme of the challenges driven by the limits to use the dynamic laser speckle regarding hardware 
and software 

3. Discussing the limits 

During many years, the applications of the dynamic laser speckle phenomenon, particularly, in biological 
material, became familiar (Zdunek et al. 2014, Rabal and Braga 1998) as well as the limits of its usage. In 
Figure 2, the limits were divided in hardware and software and the discussion about those limits are 
addressed in the next subsections. 

3.1 Laser stability 

Traditionally, the laser most used in this sort of interferometric measurements is the HeNe laser, however 
there is a great limitation to move it away from the optical laboratories. In addition, the variety of wavelengths 
offered by diode lasers is high. The adoption of diode laser has been useful in many applications, since its 

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reduced costs and size, however the stability of the laser can be compromised by, for example, the low quality 
of the power source or non-stable operation of the laser set (Ahmed et al. 2001, Ahmed 2003). Therefore, the 
use of diode lasers must be carried out after tests of stability of the laser. 

3.2 Camera adjustments 

There are many options of cameras in the market, however the user must have in mind that the parameters of 
the camera, such as the zoom, the ISO, the white (light) balance as well as the speed can be in automated set 
point as a factory default, which means that the camera will continuously bias those parameters in accordance 
with the changes in the illuminated objects and that can compromise the result of dynamic phenomenon such 
as the speckle laser (Braga et al., 2016). Thus, a mandatory step before the assembling of the data is the 
setup of the camera disabling the automated adjustments. In doing so, the user will be able to apply cheap 
cameras. Additionally, the adjustment of the ratio of the system’s focal lens to the diameter of the entrance 
pupil (iris) named f-number. (González-Peña and Braga, 2016)  

3.3 Portability 

The use of dynamic laser speckle out of laboratories dedicated to optics can be seen as the next step of its 
use, however it is necessary to circumvent the limits presented by mechanical noise, by external light and by 
the needed robustness of the apparatus. For example, the power supply must be independent and therefore 
must be designed to have long live and avoid ripples. The system proposed to measure parasites can be an 
example of portable equipment using the forward scattering approach (Pomarico & DiRocco 2004). 

3.4 Standardization 

The presence of many approaches to analyse the phenomenon and provide a reliable outcome need to be 
gathered and the alternatives compared, in the same way, they should be classified and organized. One can 
see that there are online and offline approaches, where the online are restricted to two methods: Laser 
Speckle Contrast Analysis (LASCA) (Briers & Webster 1996) and the Motion History Image (MHI) (Godinho et 
al. 2012) and the main outcome is graphic. 
In turn, offline procedures to analyse the dynamic laser speckle data can be divided in time and frequency 
domain, and in both cases the possible outcomes can be numerical or graphical. All these known methods, so 
far, were gathered in an open library (Braga et al. 2016) to encourage the standardization of the procedures. 
The library was constructed in M Code related to MATLAB and Octave platforms, with free access of raw data 
of dynamic laser speckle (http://www.nongnu.org/bsltl/).  

3.5 Light reference 

The influence of the light during the dynamic laser speckle must be considered appropriately since the change 
of the level of the light can cause variations in the final outcomes (Reis et al. 2016). The methods adopted to 
analyse the raw data can be adapted to circumvent the light variation, however if the amount of light is 
insufficient to bring the needed information from the biological material, there is no way to circumvent this lack 
of light. The user must have in mind that the level of light plays a key role in the dynamic laser speckle as can 
be seen in Figure 4, where the same seed was lit by the same laser with distinct intensity. The histogram of 
the distribution of the grey level intensity can be seen in Figure 5, clearly showing in bold the distribution of 
grey in a seed with sub-illumination. 

 

  
 

(a) (b) 
 

Figure 4: Level of illumination using the laser in a coffee seed with (a) high level of light and with (b) low level 
of light. Raw data of coffee beam seed from Centre for Development of Applied Instrumentation in Agriculture 
(CEDIA) 

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Figure 5: Histograms of the two images of a coffee seed with (a) high level of light in continuous line and with 
(b) low level of light in continuous bold line 

The result of the sub-illumination of the seed can be observed in Figure 6, after the processing using the 
standard deviation analysis (Cardoso & Braga 2014), where the map of activity, presented in pseudo-colours 
(from blue representing low activity to red representing high activity), is shown with areas of high activity in the 
seed with more light (Figure 6a). Thus, many questions rise from the level of illumination and the most critical 
question is if the intensity of the laser wasn’t enough to bring all the information we needed from the inner 
layers of a seed, that is a complex organism with many structures. If the light could not get through the desired 
layer, we will not be able to analyse the information of the scattered light from its elements. 

 

  
 

(a) (b) 

Figure 6: Standard deviation processing of illuminated coffee seed with (a) high level of light and with (b) low 
level of light (from blue representing low activity to red representing high activity). Raw data of coffee beam 
seed from Centre for Development of Applied Instrumentation in Agriculture (CEDIA) 

4. Conclusions 

This work presented the adoption of the phenomenon provided by dynamic laser speckle as a reliable tool to 
monitor the biological activity and the main challenges to its usage in the field. The challenges were divided in 
hardware and software, with the limits presented and commented. The presentation of a standardization 
project to circumvent the lack of a known protocol was done, and there was also presented the results of the 
influence of the level of the light in the experiments. The domain of the phenomenon and the knowledge of its 
limitation are relevant to help new users to avoid drawbacks in their applications. The standardization of the 
analysis helps the development of the technique and its usage by those who is not so keen to deal with 
software. This is a key step in the help the industry/academy to create equipment to the multitude of 
applications in agriculture, providing more instruments to enhance the economic sustainability of the 
agricultural processes. 

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Acknowledgments  

This work was partially funded by CAPES, FAPEMIG, FINEP, CNPq and UFLA.  

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