Accepted Manuscript

Towards the development of a predictive model of the formulation-dependent

mechanical behaviour of edible oil-based ethylcellulose oleogels

Andrew J. Gravelle, Shai Barbut, Margaret Quinton, Alejandro G. Marangoni

PII: S0260-8774(14)00285-4

DOI: http://dx.doi.org/10.1016/j.jfoodeng.2014.06.036

Reference: JFOE 7852

To appear in: Journal of Food Engineering

Received Date: 6 March 2014

Revised Date: 26 June 2014

Accepted Date: 28 June 2014

Please cite this article as: Gravelle, A.J., Barbut, S., Quinton, M., Marangoni, A.G., Towards the development of a

predictive model of the formulation-dependent mechanical behaviour of edible oil-based ethylcellulose oleogels,

Journal of Food Engineering (2014), doi: http://dx.doi.org/10.1016/j.jfoodeng.2014.06.036

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Towards the development of a predictive model of the formulation-dependent

mechanical behaviour of edible oil-based ethylcellulose oleogels

Andrew J. Gravelle a, Shai Barbut

a, Margaret Quinton

b, Alejandro G. Marangoni

a,*

aDepartment of Food Science, University of Guelph, Guelph, ON, N1G 2W1, Canada

bDepartment of Animal Science, University of Guelph, Guelph, ON, N1G 2W1, Canada

*Corresponding author. Tel. +1-519-824-4120 ext. 54340 Email address: amarango@uoguelph.ca (A.G.

Marangoni)

Abstract

The functionality of the recently discovered ethylcellulose (EC) oleogel systems are highly dependent on

the mechanical strength of these gels. This mechanical strength depends strongly on a variety of

different compositional parameters. Here we report on a predicative model relating the mechanical

strength of EC oleogels as a function of both gelator and surfactant concentration for a variety of oils,

surfactants, and EC molecular weights. Predictive modelling was based on a goodness-of-fit approach

achieved in a step-wise fashion. Two-dimensional fits were performed on the experimental data for gel

strength as a function of both mass fraction ethylcellulose (0.07 – 0.15) and surfactant (fixed to three

EC/surfactant ratios) to obtain candidate equations for the eventual three-dimensional model. It was

discovered that gel strength increases with mass fraction of EC in a power law fashion for all conditions

tested. Comparison of mechanical strength determined by back extrusion and texture profile analysis

(TPA) showed similar trends in scaling behaviour. In addition, the behaviour of the elastic constant

extracted from TPA was also found to follow a power law with increasing gelator concentration. Finally,

the validity of the predictive model was investigated through interpolation.

Keywords: Ethylcellulose, Oleogels, Response surface, Back extrusion, Texture Profile Analysis

Abbreviations: ethylcellulose (EC); glycerol monooleate (GMO); molecular weight (MW) sorbitan

monostearate (SMS) texture profile analysis (TPA)

1. Introduction

The physical, mechanical, and organoleptic characteristics of many food products are largely influenced

by the functional properties of their solid fat component. Traditionally, fats contain a liquid oil phase

stabilized by a hierarchal network of structures composed of crystalline triglyceride nanoplatelets

(Acevedo and Marangoni, 2010; Marangoni, 2012; Marangoni et al., 2012). These platelets, which

contain a large proportion of saturated and trans-fatty acids, aggregate to form fractal structures which

assemble into a 3-dimensional network which immobilizes the liquid oil component (Marangoni et al.,

2012; Peyronel et al., 2013). However, excessive consumption of saturated fats has been identified as a

significant contributor to the globally rising rates of obesity, as well as associated detrimental health

effects such as cardiovascular disease, metabolic syndrome, and diabetes (American Heart Association

Statistics Committee and Stroke Statistics Subcommittee, 2012; Mensink et al., 2003; W.H.O., 2002).

Unfortunately, direct replacement of hard fats with liquid oil often has detrimental effects on final

product quality, which can lead to consumer rejection. As a result, the non-triglyceride structuring of

edible oils has become an active area of research, with much progress seen in recent years in regards to

the identification and characterization of such structuring agents (Bot et al., 2009; Co and Marangoni,

2012; Marangoni and Garti, 2011; Pernetti et al., 2007). Several different mechanisms of gelation have

been identified in oleogel systems having potential for food applications, and although the mechanisms

of gelation can differ substantially, these gelators can generally be grouped into three categories. These

include self-assembled fibrillar networks (SAFiNs) of low molecular weight (MW) organogelators, the

formation of a network of crystalline particles, or via polymer gelation. However, although many of

these organogelators can in principal be incorporated into a food matrix, few yet have approval as food

additives.

To date, the only known polymer relevant to food applications which is able to structure edible oils is

ethylcellulose (EC). This cellulose derivative is included in the list of food additives approved by the Joint

Food and Agriculture Organization of the United Nations / World Health Organization (FAO/WHO)

Expert Committee on Food Additives (J.E.C.F.A., 2005) and has been approved for GRAS (generally

regarded as safe) status as a food additive by the US FDA. The commercially available products are

synthesized to have an ethoxy content of approximately 48–49.5 %, (Dow Cellulosics, 2005) which

translates to roughly 2.5/3 ethoxy substitutions per glucose monomer and corresponds to a minimum in

the thermoreversible glass transition temperature of the polymer (approximately 140 °C). When heated

above this rubber plateau, EC softens and can be dispersed in vegetable oil, and upon cooling the

polymer returns to a rigid state (Laredo et al., 2011). During the cooling process, the dispersed EC

molecules become stabilized through the formation of intermolecular interactions, producing an

entangled polymer network which entraps the oil phase and provides mechanical support. It has

reported that the resulting a physical gel is supported by hydrogen bonds formed between the

unsubstituted hydroxyl groups of the ethoxylated glucose units (Laredo et al., 2011).

Several recent studies have investigated the nature of the internal structure of these gels and their

physical characteristics at the molecular level (Gravelle et al., 2012; Gravelle et al., 2013; Laredo et al.,

2011; Zetzl et al., 2012). Through these studies, it has also come to light that there are several factors in

formulating an EC oleogel which have a significant effect on the mechanical strength. These include

changes in the oil type and/or polarity of the oil phase, the MW and concentration of the polymer, and

whether or not a surfactant is incorporated into the system. Despite these factors having been identified

as a means to manipulate gel strength, only specific examples of their formulation-dependent influence

on the mechanical behaviour have been demonstrated. In terms of applications in food systems, these

gels show great potential as fat replacers, and their use has been documented in several food systems,

including cream fillings, chocolate, cookies, and frankfurters (Stortz and Marangoni, 2011; Stortz et al.,

2012; Zetzl et al., 2012). However, adaptation of these oleogels to new food systems may require

drastically different mechanical properties of the fat phase to achieve the desired organoleptic

properties. It was therefore the goal of the present work to provide a comprehensive analysis of how

each of the formulation-dependent parameters noted above effect the mechanical strength of EC

oleogels.

2. Materials and methods

2.1. Materials

Canola oil and soybean oil were purchased from Caldic Canada Inc. (Mississauga, ON, Canada). The

surfactants sorbitan monostearate (SMS) and glycerol monooleate (GMO) were purchased from Danisco

A/S (Scarborough, ON, Canada) and HallStar (Bedford Park, IL, USA), respectively. The antioxidant 2,6-Di-

tert-butyl-p-cresol (BHT) was purchased from Spectrum Chemical Manufacturing Corporation (New

Brunswick, NJ, USA) through Fisher Scientific. ETHOCELTM

std. 10, 20, and 45 (10 cP, 20 cP, and 45 cP,

respectively) were obtained from Dow Wolff Cellulosics through Colorcon Inc. (St. Laurent, QC, Canada).

These polymers are all produced to have an ethoxyl content of 48.0 – 49.5 % (degree of substitution of

~2.5) and have been found to have molecular weights of 28.6 ± 6.2, 51.9 ± 10, and 72.8 ± 15 kDa,

respectively (Davidovich-Pinhas et al.). The associated numbers indicate the viscosity of the polymer

when measured in an 80:20 solution of toluene/ethanol with 5 wt% EC solids.

2.2. Preparation of EC oleogels

EC oleogels were prepared following a protocol developed previously in our laboratory (Gravelle et al.,

2012). The EC-oil-surfactant mixture was heated in a bench-top gravity convection oven (Fisher

Scientific) set to approximately 170 °C. Throughout the heating process, the solution was mixed with an

overhead mechanical stirrer (model L1U10F Ligntnin LabMaster, Wytheville, VA, USA) and a long shafted

stirring rod with a high shear radial flow impeller, which was fed through a hole in the roof of the oven.

Temperature was monitored with a thermocouple unit (model 800024, Sper Scientific, Scottsdale, AZ,

USA) to note the onset of the glass transition temperature (Tg) of EC (~140 °C). After the Tg was reached,

the solution was left for an additional 10 min to facilitate complete softening of the polymer. The entire

heating process took 45-50 min, and the final temperature of the molten gel was approximately 150 °C.

After heating, the sample was removed and split into five aliquots of ~35 ml each in 50 ml polypropylene

centrifuge tubes (Fisher Scientific). The remainder of the gel was poured into a cylindrical glass tube

(height: 14.5 cm, inside diameter: 1.9 cm) lined with aluminum foil and plugged at one end with a #3

rubber stopper (Fisher Scientific) (Gravelle et al., 2013). The molten gels were then moved to an

incubator and kept at 20 °C for a minimum of 2 hr, and subsequently transferred to a 4 °C incubator for

overnight storage.

2.3. Evaluation of oleogel mechanical strength

The mechanical properties of EC oleogels were evaluated using two large deformation techniques; back

extrusion and Texture Profile Analysis (TPA). Both tests were performed using a texture analyzer (model

TA.XT2, Stable Micro Systems, Texture Technologies Corp., Scarsdale, NY, USA). For the back extrusion

test, after storage, a stainless steel cylindrical probe (height: 9.8 cm, inside diameter: 1.8 cm) with a

truncated spherical tip (height: 1.3 cm, inside diameter: 2.0 cm) was used to penetrate 30 mm into the

gel at a rate of 1.5 mm/s (extrusion cell inside diameter: 2.7 mm). The resulting response force was

digitally recorded using a 30 kg load cell which has a maximum measurable force of ~370 N, and any

samples which exceeded this threshold were discarded. The reported gel strength was taken as the

average force over the final 25 % of the penetration (see Fig. 1a). This procedure minimizes the

relatively large signal noise in the back extrusion force-deformation curve. Five back extrusion tests

were performed per replicate, and each formulation was repeated using three independently prepared

replicates.

For gels which were firm enough to be evaluated by TPA, 10 mm tall discs (or pucks) were sectioned

from the middle region of the cylindrical gel prepared in the glass moulds. Five pucks were cut from the

center region of each sample using a metal die designed in-house, and a tool with a thin, taught metal

wire. Samples were subjected to a two-cycle compression to 50 % of the original puck height between

two parallel plates. Sample hardness evaluated by TPA is defined as the force exerted by the sample on

the probe (resistance force) at the maximum point of deformation during the first cycle. The elastic

constant (K) can also be calculated from TPA data by taking the ratio of stress vs. strain at the initial

stages of compression. The elastic constant is a component of the Young’s modulus (E), which is defined

mathematically as the ratio of tensile stress to extensional strain εσ /=E . The elastic constant can

therefore be determined by taking the gradient of the force vs. distance curve in the linear region at the

onset of deformation, i.e. within the first 5 % of sample deformation, relative to the initial sample height

(See Fig. 1b, Inset). All treatments were carried out in three independent trials, and mechanical testing

was performed at 4 °C.

2.4. Experimental design and data modelling

It was decided that the mechanical strength would be evaluated as a function of mass fraction EC and

mass fraction surfactant, and the remaining three parameters (oil type, surfactant type, and variety of

EC) were fixed for each data set. Samples were prepared with 0.07 – 0.15 mass fraction EC in increments

of 0.02. Three different molar ratios of EC/surfactant were prepared for each level of EC; 1:0 (no

surfactant), 6:1, and 3:1. After mechanical testing, it was found that with the exception of oleogels

prepared with 45 cP EC in soybean oil, all gels prepared with 0.07 mass fraction EC were too soft to be

considered true gels, and were therefore discarded for the fitting procedure.

Data fitting was performed using TableCurve3D®, version 4.0 (Systat Software Inc., San Jose, CA, USA).

For fitting purposes, all data points were normalized to the maximum measurable force, taken here to

be 350 N. Two-dimensional fits were first performed independently to identify functions best suited to

model the data as a function of mass fraction EC and of mass fraction surfactant. A select set of

equations were then used to fit the data to a three-dimensional model to determine the most

appropriate equation form. Once selected, parameter estimates and Pearson correlation coefficients

(R2) were obtained from the fitting software.

3. Results and discussion

3.1. Versatility of EC oleogel formulations

The versatility of EC oleogels in terms of their mechanical and textural properties is due in part to the

large variety of adjustable parameters in their formulation. These include the type of oil used, MW

(viscosity) of the polymer, type of surfactant used (if any), and the concentration of both the gelator and

surfactant. For example, the type of oil dictates the fatty acid profile, a parameter which has been

shown to have a large effect on the strength of these gels (Gravelle et al., 2013; Laredo et al., 2011; Zetzl

et al., 2012). It has previously been shown that changes in the fatty acid profile of the oil phase has an

effect on the oil density and was thus hypothesized that more efficient packing of unsaturated lipids

would result in a more dense network of oil droplets entrapped in a scaffolding of EC, producing a firmer

gel (Laredo et al., 2011). However, more recent work in our laboratory suggests there are additional

contributing factors which may influence the strength of the final product. For example, altering the

polarity of the oil component through partial supplementation with castor oil or mineral oil has been

shown to have a dramatic effect on the mechanical behaviour of EC oleogels (Gravelle et al., 2013). It

has also recently been discovered that the lipid profile has an effect on the size of the entrapped oil

droplets which may contribute to the macroscopic behaviour of the oleogel (Zetzl et al., 2014). The MW

of EC selected as the gelling agent has also been found to have a profound effect on the gel strength, as

determined by back extrusion. Zetzl et al. (2012) reported a significant increase in mechanical strength

with increasing MW (10, 45, and 100 cP EC), regardless of the fatty acid composition of the oil used

(Zetzl et al., 2012). In addition, the incorporation of certain surfactants such as SMS and GMO have been

found to have a plasticizing effect on EC oleogels (Dey et al., 2011) and increase gel firmness (Gravelle et

al., 2013). Therefore, due to the complexity of these systems, it was decided to approach the

characterization of a broad range of oleogel formulations in a step-wise manner, in an attempt to take a

more guided approach to modelling the mechanical behaviour.

3.2. Evaluation of mechanical strength via large deformation

Fig. 1. Sample data of force response curves of an EC oleogel evaluated using a) back extrusion and b)

TPA. Dashed lines in a) highlight final quarter of test which is averaged to reduce noise in the reported

mechanical strength. Inset in b) shows the first second of the TPA test from which the gradient of the

curve in the linear region can be used to extract the elastic constant, K. The oleogel tested was

formulated with canola oil, 13 wt% 45 cP EC and a 6:1 EC/SMS ratio. Note that distance and time are

interchangeable, as the cross-head velocity was constant at 1.5 mm/s.

As noted above, the mechanical strength of the oleogels were evaluated using both back extrusion and

TPA. A sample data set of each mechanical test is presented in Fig. 1. The use of TPA is well established

for the evaluation of the textural attributes of food products and is commonly used as a standardized

method to evaluate sensory properties of foods as an alternative to relying on the subjective opinions of

human panelists (Bourne, 1978). The challenge of using this technique for the present study was that it

imposed a lower limit to the firmness of the gels which could be evaluated. This is due to the fact that

they must be firm enough to retain their shape; however, some potentially useful formulations of EC

oleogels may fall below this threshold. In addition, soft samples can be easily deformed or damaged

when being handled during preparation for testing, which can introduce errors in the measured

parameters. In contrast, the back extrusion technique is particularly advantageous for softer samples

that may not be firm enough to be tested by TPA, however there is an upper limit to this test in the case

that the oleogel is too firm for the probe to penetrate. In considering the limitations of each of these

techniques, it was determined that the back extrusion method would be applicable to a wider range of

formulations, in particular, those which produce gels with mechanical strength relevant to applications

in food systems. For this reason, data collected using back extrusion was used to model the formulation-

dependent behaviour of EC oleogel mechanical strength. A comparison of the two techniques is further

discussed in section 3.7.

3.3. Effect of EC molecular weight on gel strength

Previous work has suggested that the mechanical strength of certain EC oleogels as a function of mass

fraction gelator behave according to a power law function. These gels were prepared with soybean or

canola oil and without surfactant, across a range of 0.04 to 0.10 mass fraction 45 cP EC (Zetzl et al.,

2012). This information was used as a starting point for modelling the mechanical strength of a large

variety of oleogel formulations. The previously reported formulations represent the lower range of

firmness for these oleogels, as it has been reported that a 0.04 mass fraction 45 cP EC oleogel is the

threshold concentration for gel formation of this particular MW. In the present work, all oleogels were

formulated using 0.07, 0.09, 0.11, 0.13, and 0.15 mass fraction EC, regardless of MW used, as gels

formulated in this range more accurately mimic commercially available fats.

Fig. 2. EC molecular weight dependence on the scaling behaviour of oleogels as a function of mass

fraction EC (ΦEC), as measured by back extrusion. The figures show the log of the mean force over the

last 25% of the back extrusion test as a function of the log of mass fraction EC. Oleogels were prepared

using a) canola oil and b) soybean oil. Reported values are normalized in percentage format to the limit

of the load cell used, 350 N. Error bars indicate the standard error of the mean, and those which cannot

be seen are smaller than the data symbols.

Additionally, the previously reported mechanical behaviour of EC oleogels was restricted to a single

MW, whereas here we expand on this work to model the behaviour of several different commercially

available versions; 10 cP, 20 cP, and 45 cP. This range was selected due to the fact that the Tg increases

with increasing MW; as a result, varieties of EC greater than 45 cP can be difficult to solubilize in a

reasonable timeframe, which may pose problems when adapting formulations for fat replacement in

food products. Fig. 2 depicts the trends in mechanical strength observed for all three varieties of EC used

in this study, prepared using both canola and soybean oils. In all cases, the data fit very well to a power

law model, regardless of oil type or polymer viscosity. However, it is immediately apparent that within

each oil type the scaling behaviour of the different varieties of EC are quite dissimilar.

The difference in viscosity between varieties of EC arises due to differences in the average MW (or chain

length) of the polymer. These values have previously been estimated by extrapolation of data reported

by Rowe (Rowe, 1986), and were reasonably close to values determined recently in our laboratory of the

products used in the present study. The peak MW values determined for the 10, 20, and 45 cP varieties

of EC available from DOW® Wolff Cellulosics were 28.6 ± 6.2, 51.9 ± 10, and 72.8 ± 15 kDa, respectively

(Davidovich-Pinhas et al.). It is interesting to note that regardless of either oil type or variety of EC, the

mechanical properties of all these gels behave according to a power law model. The fact that the

tendency of gel strength is consistent across all MWs makes sense intuitively when considering their

structural make-up. Cryo-SEM micrographs of partially de-oiled gels show that the internal structure

consists of oil droplets entrapped within a network of interconnected strands or bundles of EC, which

form a scaffolding to support the gel (Zetzl et al., 2014; Zetzl et al., 2012). Therefore, reducing the MW

of the gelator would be expected to produce a less entangled network with shorter strands/bundles,

having fewer interconnections per structural unit. This difference would not alter the type of

interactions supporting the gel, so a consistent behaviour in the mechanical strength with increasing EC

concentration, regardless of MW, seems a reasonable prediction.

It is also worth noting that the results in Fig. 2 are in contrast to previous finding reported by Zetzl et al.

(2012) in which no significant difference was found in the scaling factor for oleogels prepared using 45

cP EC in both canola and soybean oil (Zetzl et al., 2012). However, these samples were prepared on a

hotplate with poor temperature control, and the molten gels were allowed to cool 20 °C below the Tg

under mixing, before being transferred to storage vials and allowed to set. Considering that heating

time, oil oxidation, and gelation conditions have been seen to have a dramatic effect on the physical

characteristics of EC oleogels (Gravelle et al., 2012; Gravelle et al., 2013), the observed differences in

scaling behaviour reported here, as compared to the previous study, are likely due to differences in the

oleogel preparation procedures.

3.4. Effect of surfactant addition on gel strength

It is well known that the physical characteristics of the fat component of food products have a direct

effect on both their physical and organoleptic properties. When developing a formulation for an oleogel

intended for use as a fat substitute, it may be necessary to alter the physical characteristic of the gel to

more accurately mimic the original fat source. In this respect, the incorporation of surfactants can be

used as plasticizing agents to provide an additional method of manipulating the mechanical and textural

properties of the oleogel. To explore what effect plasticizers may have on the gel strength, two

surfactants commonly used in food products were selected; GMO and SMS. Both of these surfactants

have previously been incorporated into EC oleogels with notable effects (Dey et al., 2011; Gravelle et al.,

2013), however, once again only select formulations were considered. It is also worth noting that these

surfactants have different effects on the physical properties of the resulting oleogel and can affect

properties such as gel strength and consistency.

In this work we have investigated the effects of surfactant incorporation at three different EC/surfactant

ratios, 1:0 (no surfactant), 6:1, and 3:1, and considered each across a range of EC concentrations. Fig. 3

demonstrates how the EC/surfactant ratio can alter the mechanical behaviour of the oleogel. It is

interesting to note that despite the addition of a plasticizer, in all cases the strength of the oleogels

continue to behave according to a power law model, albeit the scaling behaviour is not affected in the

same way for different MWs. This same behaviour was observed regardless of surfactant type, oil type,

or MW. However, to characterize how these surfactants affect the scaling behaviour would require an

in-depth analysis into the role these molecules play within the context of an EC oleogel. Such an analysis

was beyond the scope of the present study, in which the aim was to characterize the macroscopic

behaviour of the gels through large deformation techniques.

Fig. 3. Effect of EC/surfactant ratio on the scaling behaviour of oleogels for different MWs of gelator.

The figure shows the log of the mean force measured over the final 25% of the back extrusion test as a

function of the log mass fraction EC (ΦEC). Oleogels were prepared using soybean oil and a) 10cP EC with

SMS, b) 10 cP EC with GMO, and c) 45cP EC with GMO. Legends indicate ratio of EC:surfactant used in

the formulation. Reported values are normalized in percentage format to the limit of the load cell used,

350 N. Error bars indicate the standard error of the mean, and those which cannot be seen are smaller

than the data symbols.

3.5. Response surface fitting: Modelling 3-dimensional data sets

Due to the large number of adjustable parameters, for the purposes of modelling the oleogel

mechanical strength, only two of these parameters were kept variable; mass fraction EC and the

EC/surfactant ratio used. The remaining three parameters (oil type, surfactant type, and MW of EC)

were fixed for a given data set. In all, this amounted to a total of 12 3-dimensional data sets for which

the mechanical strength was evaluated to provide an individual response surface for each. In contrast to

the uniform behaviour seen in the gel strength as a function of mass fraction EC, no such consistent

trend was apparent when considering the effect of increasing surfactant level.

Noting the results presented in the previous section, a guided approach was taken to fitting the

experimental data, restricting the dimension described by EC mass fraction to power law and power

law-like fits. Somewhat surprisingly, it was discovered that a single equation form could be used to

describe every one of the 12 data sets, regardless of surfactant type, MW of EC, or oil type selected for

the formulation. This equation took the form

( )2cYbYaXZ ++= μ (1)

where Z denotes the normalized gel strength and X and Y respectively represent the mass fraction EC

and surfactant used in formulating the gel. The scaling factor μ and the coefficients a, b, and c were

obtained from the fitting procedure for each independent response surface. This equation not only

incorporates the power law dependence of the gelator used, but also demonstrates a synergistic effect

of the surfactant on gel strength which can be described by a second order polynomial. The relative

simplicity of the equation was also somewhat surprising, however multiple fits were performed to

confirm that no additional independent terms were necessary to improve the goodness of fit. The

Pearson correlation coefficients (R2) and fitted parameter estimates for all characterized formulations

are displayed in Tables 1 and 2 for canola oil and soybean oil oleogels, respectively.

Table 1 Pearson correlation coefficients (R2 value) and parameter estimates corresponding to Equation 1

fitted to back extrusion hardness data from oleogels prepared with canola oil. The remaining fixed

parameters (polymer viscosity and surfactant type) are listed in the formulation column. For each

experimental data set, the mass fraction EC was varied from 0.07 to 0.15 in 0.02 increments and three

EC/surfactant ratios were prepared for each level of EC used; 1:0, 6:1, and 3:1.

Formulation R2 µ a b c

10 cP, GMO 0.99 11.53 ± 0.61 (9.25 ± 10.74) x 109 (-4.70 ± 5.45) x 10

11 (3.77 ± 4.34) x 10

13

20 cP, GMO 0.99 13.80 ± 0.91 (7.43 ± 12.87) x 1012

(7.21 ± 14.17) x 1014

(6.01 ± 10.46) x 1015

45 cP, GMO 0.95 8.75 ± 0.69 (1.07 ± 1.41) x 109 (-3.99 ± 5.96) x 10

10 (1.63 ± 2.42) x 10

12

10 cP, SMS 0.98 7.75 ± 0.50 (6.73 ± 6.82) x 106 (2.01 ± 3.27) x 10

8 (4.09 ± 3.87) x 10

10

20 cP, SMS 0.99 11.38 ± 0.71 (7.55 ± 10.14) x 1010

(1.29 ± 1.93) x 1013

(3.05 ± 4.75) x 1013

45 cP, SMS 0.98 12.07 ± 0.91 (6.00 ± 10.41) x 1011

(2.35 ± 5.07) x 1013

(1.24 ± 2.24) x 1015

Table 2 Pearson correlation coefficients (R2 value) and parameter estimates corresponding to Equation 1

fitted to back extrusion hardness data from oleogels prepared with soybean oil. The remaining fixed

parameters (polymer viscosity and surfactant type) are listed in the formulation column. For each

experimental data set, EC mass fraction was varied from 0.07 to 0.15 in 0.02 increments and three

EC/surfactant ratios were prepared for each level of EC used; 1:0, 6:1, and 3:1.

Formulation R2 µ a b C

10 cP, GMO 0.98 11.30 ± 0.67 (3.72 ± 4.72) x 1010

(1.46 ± 1.88) x 1012

(-3.29 ± 6.43) x 1012

20 cP, GMO 0.97 10.76 ± 0.86 (7.15 ± 12.53) x 1010

(5.37 ± 9.45) x 1012

(-8.37 ± 14.79) x 1013

45 cP, GMO 0.97 4.74 ± 0.28 (9.52 ± 5.52) x 105 (-3.17 ± 1.82) x 10

7 (7.45 ± 4.24) x 10

8

10 cP, SMS 0.98 5.58 ± 0.26 (6.28 ± 3.19) x 105 (3.85 ± 2.09) x 10

7 (7.30 ± 10.50) x 10

7

20 cP, SMS 0.98 7.42 ± 0.42 (7.51 ± 6.57) x 107 (1.08 ± 0.95) x 10

10 (-1.30 ± 1.17) x 10

11

45 cP, SMS 0.99 6.65 ± 0.27 (4.91 ± 2.71) x 107 (-1.48 ± 26.07) x 10

7 (1.96 ± 1.79) x 10

10

The finding that a single equation form is able to describe the mechanical behaviour of all the oleogels,

regardless of fatty acid profile, MW of EC, or the type of plasticizer used, is quite interesting. In

particular, despite the differences in the chemical nature of the two surfactants under investigation,

their influence on gel strength can both be described by a second-order polynomial. Additionally, the

fact that this contribution appears as a cross-term suggests there is some type of interplay between the

polymer network and the surfactant molecules. Several of the response surfaces are depicted in Fig. 4 to

illustrate some notable differences between the three fixable parameters mentioned previously.

Fig. 4a and Fig. 4b represent gels prepared with the same variety of EC and surfactant (10 cP and SMS,

respectively), and contrast the differences in the behaviour of gel strength when the oil type is altered. It

was found that for a given formulation, oleogels prepared with soybean oil were consistently firmer

than their canola oil counterparts. This trend was consistent across all varieties of EC and surfactant, at

all incorporation levels. The findings presented here are in agreement with those of previous studies,

which have proposed a greater amount of unsaturations in the oil component (higher iodine value)

produce a firmer oleogel (Laredo et al., 2011; Zetzl et al., 2012). Although the findings presented here do

not contradict this hypothesis, the manipulation of gel strength through the addition of other lipids such

as castor oil and mineral oil (Gravelle et al., 2013) suggest additional factors may be at play. Regardless

of this fact, it is clear that solvent composition is a significant contributing factor in determining EC

oleogel strength, and must be considered when formulating a gel with tailored mechanical properties.

Attempts have previously been made to quantify differences attributed to solvent composition;

however it is apparent here that such a comparison using individual formulations would be difficult due

to the observed differences in scaling behaviour (see parameters listed in Table 1 and Table 2), as well as

the interplay between EC and the type of surfactant employed. Therefore, the model presented here is

an important step forward in understanding how the mechanical properties of EC oleogels are affected

by a variety of different compositional parameters, over a broad range of formulations.

Fig. 4. Comparison of response surfaces developed for the prediction of EC oleogel strength, as

evaluated by back extrusion. Axis ΦEC and Φsurf correspond to the volume fraction EC and surfactant used

in the formulation, respectively. The formulations of the oleogels in each panel were as follows: a)

Canola oil, 10 cP EC, SMS; b) Soybean oil, 10 cP EC, SMS; c) Canola oil, 10 cP EC, GMO; d) Canola oil, 45

cP EC, GMO; e) Soybean oil, 45 cP EC, SMS; f) Soybean oil, 45 cP EC, GMO. Note that there are

differences in the Z-axis scale.

The effect of altering the EC MW is highlighted in Fig. 4c and Fig. 4d which depict the response surfaces

prepared with 10 cP and 45 cP EC, respectively, in canola oil with GMO used as the plasticizing agent. As

was previously discussed, an increase in MW (polymer chain length) would be expected to produce a

more interconnected gel network with a greater number of junction zones per EC fibre/bundle. In

accordance with this, it can be seen that although the overall behaviour is quite similar, the higher MW

version of EC produces firmer gels at lower incorporation levels. Interestingly, the scaling factor for the

45 cP EC surface is lower than that of the 10 cP (11.5 and 9.2, respectively). A similar result is seen when

comparing the scaling factors of the corresponding soybean oil response surfaces (12.0 and 5.0,

respectively). As the same phenomenon is not observed for gels prepared with SMS, it is anticipated

that the surfactant plays some role in mediating this effect.

Finally, the difference in mechanical behaviour resulting from the use of different surfactants is

contrasted in Fig. 4e and Fig. 4f. What can be seen here is that gels prepared with GMO remain softer

until higher incorporation levels are used (note the concave nature of the surface) whereas those

prepared with SMS begin to influence gel strength at lower concentrations, producing only a slight

concavity in the surface. These differences in behaviour likely arise due to the differences in chemical

nature of the two surfactants. GMO is very similar in structure to a triglyceride and therefore likely

interacts quite favourably with the oil phase. SMS on the other hand has a large, rigid head-group and is

known for having oleogellation properties at sufficiently high concentrations (Peyronel and Marangoni,

2014). This fact indicates that under certain conditions it is more favourable for SMS to aggregate and

precipitate out of solution, and therefore does not likely act as favourably with the oil component as

does GMO. Although the mechanism of interaction of these molecules within an EC oleogel is not yet

known, it has been demonstrated that the addition of surfactants provides a useful way to manipulate

the mechanical properties of these gels.

3.6. Comparison of large deformation techniques

It was previously noted that although the use of TPA is well established for analyzing the textural

properties of food products, in the present work a greater range of oleogel formulations could be

evaluated through the use of back extrusion. However, one particular advantage of TPA is that only a

single test is required to characterize a variety of textural parameters which may be useful when

formulating an oleogel for a particular food application. In addition, one can obtain information about

the elastic constant of the material under investigation, which is given by the gradient of the TPA curve

at the initial stages of deformation. Here we report the behaviour of both oleogel mechanical strength

(TPA hardness) and elastic constant with increasing gelator concentration, and consider the

comparability of the results obtained using back extrusion and TPA for oleogels prepared with 45 cP EC

in soybean oil.

Fig. 5. Comparison of TPA hardness, or force measured at 50% compression (a, b) and elastic constant, k,

extracted from the TPA profile (c, d) as a function of mass fraction EC (ΦEC) for three different

EC/surfactant ratios. Oleogels were prepared with soybean oil, 45 cP EC, and the surfactants GMO (a, c),

and SMS (b, d). As above, all force values were normalized to the maximum detectible force of the load

cell used (350 N) and are reported as relative % force. Units of the elastic constant are therefore m-1

.

Error bars indicate the standard error of the mean, and those which cannot be seen are smaller than the

data symbols.

Fig. 5a and Fig. 5b demonstrate that irrespective of either the surfactant type or the level of surfactant

employed, the log-log plot of gel strength (as measured by TPA hardness at 50% compression) vs. mass

fraction EC increases in a linear fashion. This demonstrates that the same trend in the mechanical

behaviour is observed in both large deformation techniques (back extrusion and TPA hardness). It is also

interesting to note that the scaling behaviour of the gels containing GMO are not significantly different

across surfactant incorporation levels for either back extrusion (presented in Fig. 3c, P=0.532) or TPA

(Presented in Fig. 5a, P=0.694). In fact, the pooled scaling factors were found to be quite similar; 5.54

when evaluated by back extrusion and 5.84 as determined by TPA. When SMS was used as the

plasticizing agent the same trend was not seen; however it was found that the scaling factors of the 6:1

and 3:1 incorporation levels did not differ significantly within each of the two large deformation

techniques. Comparing the pooled scaling factors of the 6:1 and 3:1 EC/SMS formulations to that of the

corresponding surfactant-free oleogels, a relative increase of 1.20 and 1.36 was found by back extrusion

and TPA, respectively. These findings suggest there is a good agreement between the two large

deformation techniques used when evaluating the behaviour of the mechanical strength of such

materials. It also justifies their use as complementary techniques for the characterization of such soft

materials, and thus, could be taken advantage of in other systems in the future.

In addition to gel strength, the elastic constant was also extracted from the TPA results for the soybean

oleogels prepared with 45 cP EC. These results are depicted in Fig. 5c and Fig. 5d, and exhibit similar

trends to those seen in the gel strength evaluated by both back extrusion and TPA. Once again, the

tendency of the mechanical behaviour with increasing mass fraction EC can be accurately described by a

power law model, regardless of either the type of surfactant used, or the EC-surfactant ratio. This type

of mechanical behaviour has also been observed for the storage modulus of other gel systems, including

both colloidal gels produced from boehmite alumina (Shih et al., 1990), and xanthan gum in the

presence of aluminum ions (Rodd et al., 2001), as well as polymer gels such as chromium (III)-crosslinked

polyacrylamide gels (Grattoni et al., 2001), and acid-induced soy protein isolate gels (Bi et al., 2013).

Additionally, as discussed above, the scaling factor for the oleogels prepared with GMO are not

significantly different (P=0.34), although the pooled value of 7.07 is higher than that seen in the

hardness tests. The effect of the surfactant SMS also had a similar effect on the elastic constant to that

seen on the mechanical strength. Although the addition of SMS significantly altered the scaling

behaviour, the results from the two incorporation levels (6:1 and 3:1 EC/SMS) were not significantly

different, and their pooled scaling factor exhibits a relative increase of 1.16, as compared to the

surfactant-free samples. These findings demonstrate that the tendency of the gel strength and elastic

constant of vegetable oil-based EC oleogels are affected in a similar manner by changes in the content of

both gelator and surfactant.

3.7. Validation of the predictive model

To confirm the validity of the proposed predictive model, a series of oleogels were prepared using oils

obtained from alternative suppliers (local supermarket brands). A set of formulations were selected for

interpolation and the observed gel strength is presented in Table 3. At first glance, there appear to be

large discrepancies between the experimental observations and empirical predictions of gel strength.

However, a back calculation to determine the EC concentration required as input for the predictive

model to match the experimentally observed gel strength reveals a clear trend. It was found that for all

gels prepared with 10 cP EC, the empirical model could more accurately predict the gel strength by

increasing the gelator concentration by approximately 0.65 wt%, regardless of EC concentration or

surfactant used. A similar adjustment could be made for gels prepared using 45 cP EC, by reducing the

concentration by roughly 1.33 wt% for either oil type. This suggests that although there seems to be

significant variability in gel strength when changing ingredients, the overall predictive behaviour as a

function of mass fraction EC and surfactant does not change. Therefore, the proposed model can still

accurately describe the formulation-dependent behaviour of EC oleogel strength, but may require the

use of an experimentally determined adjustment factor for a given batch of ingredients.

Table 3 Validation of predictions for EC oleogel mechanical strength. Empirically predicted hardness

values were generated from Equation 1 using the appropriate parameter estimates taken from either

Table 1 or 2. Experimentally observed hardness was taken as the mean force over the final 25 % of the

back extrusion test, normalized to maximum of load cell (presented in relative % ± standard error of the

mean). The column denoted as Adjusted EC Concentration represents the EC concentration required as

input for the predictive model to match the experimentally observed oleogel strength.

Formulation Predicted

hardness (rel%)

Observed

hardness

(rel%)

Adjusted EC

Concentration (wt%)

14% 10 cP, 3:1 GMO in Canola 9.63 14.98 ± 0.41 14.46

14% 10 cP, 3:1 SMS in Canola 25.27 38.28 ± 1.10 14.62

12.45% 10 cP, 3:1 SMS in Canola 8.42 15.62 ± 1.14 13.31

14% 45 cP, 1:0 in Canola 1.62 6.35 ± 1.18 12.60

12% 45 cP, 1:0 in Soy 40.68 23.10 ± 0.51 10.74

4. Conclusion

The mechanical behaviour of vegetable oil-based EC oleogels have been characterized as a function of

both the mass fraction EC and mass fraction surfactant. A broad range of formulations were explored to

develop an array response surfaces characterizing the effects of several fixable parameters. A

comparative analysis was performed using a pool of targeted candidate functions. In all cases, regardless

of EC MW, oil type, surfactant type, or EC/surfactant ratio, the gel strength as a function of mass

fraction EC was successfully fitted using a power law relation. Response surfaces were presented for a

total of 12 data sets exploring the effect of three fixable parameters; two varieties of oil, two

surfactants, and three MW versions of EC. It was found that for data sets, the mechanical strength could

be described using a single universal equation.

The behaviour of the gel strength with increasing gelator was evaluated using two complementary large

deformation techniques; back extrusion and TPA. For both testing methods, a power law dependence in

gel strength was observed with increasing mass fraction EC. Such agreement not only adds support to

the validity of the presented response surface analysis, but also suggests that coupling these two

techniques may provide an opportunity to extend the range of physical characteristics which can be

characterized by either method alone. In addition, the elastic constant extracted from TPA data of

soybean oil oleogels prepared with 45cP EC was also found to exhibit a power law dependence. Finally,

the reproducibility of the proposed empirical model was tested through interpolation and it was found

that the same trends in mechanical strength were observed, however an experimentally-determined

adjustment factor may be required to appropriately adjust the polymer concentration to accurately

predict gel strength for a given set of ingredients.

Acknowledgements

The authors would like to acknowledge the Ontario Ministry of Agriculture, Food and Rural Affairs for

the financial support of this research.

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Highlights of the submitted manuscript entitled “Towards the development of a predictive model of the

formulation-dependent mechanical behaviour of edible oil-based ethylcellulose oleogels”

-Single equation form identified describing mechanical behaviour of all oleogels

-Gel strength universally increases as a power law with ethylcellulose concentration

-Similar behaviour in gel strength identified by both back extrusion and TPA

-Synergistic effect between gelator and surfactant identified by the empirical model