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Can potato fiber efficiently substitute xanthan gum in modulating chemical properties of tomato products?
Journal Pre-proof Can potato fiber efficiently substitute xanthan gum in modulating chemical properties of tomato products? Agoura Diantom, Fatma Boukid, Eleonora Carini, Elena Curti, Elena Vittadini PII:
S0268-005X(19)30204-8
DOI:
https://doi.org/10.1016/j.foodhyd.2019.105508
Reference:
FOOHYD 105508
To appear in:
Food Hydrocolloids
Received Date: 28 January 2019 Revised Date:
18 October 2019
Accepted Date: 11 November 2019
Please cite this article as: Diantom, A., Boukid, F., Carini, E., Curti, E., Vittadini, E., Can potato fiber efficiently substitute xanthan gum in modulating chemical properties of tomato products?, Food Hydrocolloids (2019), doi: https://doi.org/10.1016/j.foodhyd.2019.105508. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.
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Can potato fiber efficiently substitute xanthan gum in modulating chemical properties of tomato
2
products?
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Agoura Diantom1, Fatma Boukid1,2, Eleonora Carini1,2, Elena Curti1, Elena Vittadini1,3*
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1
Department of Food and Drug, University of Parma, Parco Area delle Scienze 47/a, 43124 Parma, Italy
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2
Siteia.Parma Interdepartmental Centre, University of Parma, Parco Area delle Scienze 181/a, Italy
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3
School of Biosciences and Veterinary Medicine, University of Camerino, via Gentile da Varano III, 62032
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Camerino (MC), Italy (current address)
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* Corresponding author: Elena Vittadini. Address: School of Biosciences and Veterinary Medicine,
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University of Camerino, via Gentile da Varano III, 62032 Camerino (MC), Italy. Email:
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[email protected].
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Abstract 1
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In the frame of clean labelling, potato fiber (F) was tested as a potential texturizing agent to substitute
30
xanthan (X) in the tomato industry. For this purpose, a physico-chemical evaluation was performed on three
31
different tomato products [(tomato pulp (TP), double (DC) and triple tomato concentrate (TC)] that were
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processed under different thermal treatments (cold and hot) and added with different levels (1, 1.5 and 2 %
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(g ingredient / 100 g tomato product) of texturing agents (F and X). For physical features, a higher redness
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was obtained at 2% of F in DC and TC, while TP color remained unvaried. Furthermore, F showed a
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stronger effect on apparent viscosity than X in the case of TP. Concerning chemical features, moisture
36
content, water activity and pH significantly varied among samples, but no clear trend was observed as a
37
function of amount/type of additive. At a molecular level, F reduced proton molecular mobility, in contrast
38
with X. Summarizing, F can be considered a potential “clean label” substitute for X in tomato-based
39
products.
40 41
Keywords: tomato, multivariate statistics, clean label, NMR, consistency, color
42 43 44 45 46 47 48 49 50 51 52 53 54 55 56
1. Introduction 2
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Clean labeling has been and is still among the trendiest concern in the food industry, where the term “clean
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label” is a sort of reflection of transparency and better health and authenticity, but the conception is still not
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fully deciphered (Nascimento, De Oliveira Do Nascimento, Do, Dias Paes, & Augusta, 2018; Weinrich &
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Spiller, 2016). Product developers still need more information about the list of clean label ingredients and
61
particularly the reasons behind their inclusion, to embrace more of a clean label philosophy, rather than rigid
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rules (Alting & van de Velde, 2012; Asioli et al., 2017; Osborn, 2015). Consumers are also asking for clean
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label products, given their increasing consciousness toward natural ingredients and their association to
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healthiness and wellbeing (Aschemann-Witzel, Varela, & Peschel, 2019; Asioli et al., 2017; Hartmann,
65
Hieke, Taper, & Siegrist, 2018). As a result, manufacturers are encountering serious challenges when
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considering moving to clean label products in terms of processing and formulation (Osborn, 2015). The
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substitution of a “non-clean” ingredient with a “clean” one should assure the same functionality and
68
performance, so that the product they are included in will be equally accepted by consumers.
69
Tomato is one of the most important vegetables used for human nutrition, which can be consumed either
70
fresh or, more frequently, processed due its perishable nature. A wide spectrum of tomato products is
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available in the market, tomato pulp, concentrates, dippings (e.g. Mexican salsa), condiments (e.g. ketchup,
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tomato sauce or pulp), complex foods (e.g. eggplants parmigiana), and beverages (e.g. gazpacho). To reach
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the suitable consistency and water activity, these products are generally subjected to different processing and
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additives can be included in the formulation. Hydrocolloids (e.g. native starch, xanthan, guar, carboxy
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methyl cellulose, tragacanth and locust bean gums) are commonly added as additives in tomato industry
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(Diantom, Curti, Carini, & Vittadini, 2017; Koocheki, Ghandi, Razavi, Mortazavi, & Vasiljevic, 2009; Sahin
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& Ozdemir, 2004), as they are able to modulate the rheological features of tomato-based products, according
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to their intended use, by increasing viscosity, interact with water and improve physical stability. Among
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hydrocolloids, xanthan gum is intensively used as a stabilizer, thickener or emulsifier in tomato products
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(Diantom et al., 2017; Torbica et al., 2016). However, xanthan gum is considered a food additive (identified
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as E415) by FDA (Code of Federal Regulations Title 21 21CFR172.695, 2018) and the European Union
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(McArdle & Hamill, 2011), and hence, does not fit in within the clean label category.
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In the frame of these challenges, the present study aims to test the feasibility of potato fiber to substitute
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xanthan in different tomatoes products. Potato fiber has been already recognized with specific physico3
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chemical and functional properties (e.g. high water-holding capacity and emulsifying) (Dhingra, Michael,
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Rajput, & Patil, 2012; Dobrowolski et al., 2012; Olatunde, Henshaw, Idowu, & Tomlins, 2016). In previous
87
work, very interesting structural and functional properties (i.e. water and oil-holding capacity, foaming and
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emulsion properties) of potato fiber extracted from potato peel waste were reported,which were ascribable to
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the presence of CO, CH and OH functional groups. (Jeddou et al., 2016). Commercial potato fiber (used in
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the present work, which extracted from potato peel) was reported to retard staling in bread thanks to its
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ability to interact with water at mesoscopic (throughout DSC analysis) and molecular (throughout 1H NMR
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Relaxometry) levels (Curti, Carini, Diantom, & Vittadini, 2016).
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A full factorial design was set up with 4 factors: tomato product [with different total solids: tomato pulp,
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double and triple concentrates, thermal treatment and different levels of addition of potato fiber and xanthan
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[1, 1.5 and 2 % (g ingredient / 100 g tomato product)]. Accordingly, the effect of the substitution was
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assessed in terms of physical (color and rheology) and chemical properties [(water activity, moisture content,
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pH and proton molecular mobility NMR indicators (1H FID, 1H T2 and 1H D)].
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2. Materials and methods
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2.1. Tomato products’ preparation
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Tomato products [tomato pulp (TP), double (DC) and triple concentrates (TC); Mutti S.p.a., Parma, Italy]
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with the same expiration date were purchased from a local supermarket. Xanthan (X) gum [humidity: max
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13% (g / 100 g); ashes: max 13%; proteins (Nx6.5) max 5%; fat: max 1%] was provided from Chimab S.p.a
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(Campodaresego, Italy), and potato fiber (F) [HI-FIBRE 115; < 6.0% moisture, protein < 1.0 %, fat < 1.0%,
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non-dietary fiber carbohydrates < 1.0 %, dietary fiber ~ 92.0 % (soluble fiber ~ 73.0 %; insoluble fiber ~
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19.0 %), ashes ~ 2.0 %] from HI-FOOD S.p.a (Parma, Italy).
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Tomato pulp with no added ingredients (0%) was used as a control, and it was added with X or F at different
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levels [1, 1.5 and 2 % (g ingredient / 100 g tomato)] and mixed (Bimby® Vorwerk, Sunbeam, USA) at 25°C
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for 2 min at 500 rpm to prepare the functionalized samples. After mixing, 200 g aliquots of the control and
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the added products were placed in glass jars and sealed and stored at room temperature (cold samples). The
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remaining products were subjected to continuous mixing (80°C, 20 min) and placed into glass jars (200 g
4
112
aliquots). Afterward, the heated jars were sealed and stored at room temperature (hot samples). All jars were
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stored at room temperature for 12 hours before analysis.
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2.2. Tomato products’ physico-chemical characterization
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2.2.1. Color
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Color indicators L* (lightness), and degree of redness (a*/b* ratio, where a* red-green and b* yellow-blue,
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Barreiro, Milano, & Sandoval, 1997; Batu, 2004) were measured with a Colorimeter (D65, 10° position,
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standard observer, CIE, 1978; CM 2600d, Minolta Co., Osaka, Japan). At least twelve measurements were
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taken for each sample.
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2.2.2. Apparent viscosity
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Tomato products’ apparent viscosity was measured with an ARES Rheometer (TA Instruments, New Castle,
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DE, USA), using a Couette geometry (34 mm cup diameter, 32 mm bob diameter and 33 mm height). About
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8 mL of tomato product were transferred into the cup and subjected to a rate sweep test (1-600 s-1, 25°C,
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points for decade 10) to obtain shear stress (τ) and viscosity. Shear rate (γ) and viscosity were then fitted
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with a non-Newtonian model (Cross equation, Khalili Garakani, et al., 2011) to extrapolate y0 (yield stress),
127
flow index (n), and the consistency coefficient (K). Y = a + ((
128
− a))/(1 +
∗
)
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2.2.3. Moisture content
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Moisture content (MC, % g water / 100 g product) of tomato products was determined by weight loss by
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drying in a forced-air oven (ISCO NSV 9035, ISCO, Milan, Italy) at 80°C to constant weight. At least
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triplicate tomato products samples were analyzed.
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2.2.4. Water activity
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Water activity of tomato products were measured at 25°C (Aqualab 4TE, Decagon Devices, Inc. WA, USA).
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At least triplicate measurements were taken for each tomato product.
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2.2.5. pH
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The pH of all tomato products was measured at 25°C (JENWAY 3510 pH meter, Bibby Scientific Ltd,
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Stone, Staff, UK). pH meter was calibrated with two buffer solutions (pH 7 and pH 4). At least triplicate
139
measurements were obtained for each tomato product. 5
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2.2.6. 1H Molecular Mobility (1H Low Resolution Nuclear Magnetic Resonance)
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A low resolution (20 MHz) 1H Nuclear Magnetic Resonance (NMR) spectrometer (the MiniSpec, Bruker
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Biospin, Milano, Italy) operating at 25.0 ± 0.1 °C was used. About 4 grams of tomato product (10 mm high)
143
were placed into a 10 mm (diameter) NMR tube that was then sealed with Parafilm® to prevent moisture
144
loss during the NMR experiment. 1H FIDs were acquired using a single 90° pulse, followed by a dwell time
145
of 7 µs, a recycle delay of 5 s and a 0.5 ms acquisition window and 900 data points. The curves were fitted
146
with a two components model [exponential and Gaussian, Le Grand, Cambert, & Mariette, 2007; Sigmaplot,
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v6, Systat Software Inc., USA] ( )= 0+
×
+
×
(
)
148
where y0 is the FID decay offset, A and B are the intensities of each relaxation component, TA and TB are
149
the apparent relaxation times.
150
T2 spin-spin relaxation time was measured with a Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence with a
151
recycle delay of 3 s (≥5 1H T1), an interpulse spacing of 0.04 ms and 26000 data points. 1H T2 curves were
152
analyzed as quasi-continuous distributions of relaxation times using an UPENWin software (Alma Mater
153
Studiorum, Bologna, Italy). Default values for all UPEN settings parameters were used with the exception of
154
the LoXtrap parameter that was set to 1 to avoid extrapolation of relaxation times shorter than the first
155
experimental point. 1H T2 CPMG relaxation decays were also fitted with a discrete exponential model
156
(Sigmaplot, v.6, Systat Software Inc., USA).
157
Proton self-diffusion coefficient (1H D) was measured at 25°C with a pulsed-field gradient spin echo
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(PFGSE) sequence and a 30 % gradient. The instrument was calibrated with water at 25°C (D = 2.29*10-9 m2
159
/s).
160 161
2.4. Statistical analysis
162
Considering that the studied data set was a full factorial design, multivariate analysis of variance
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(MANOVA) was used to determine the contribution of each factor to the physico-chemical properties
164
changes in tomato products. Two MANOVA were performed based on fixed factors at a significance level of
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α=0.05: 1st MANOVA was a 4ways-ANOVA taking into consideration 4 factors [P: product, T: thermal
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treatment (cold/hot) levels addition of potato fiber (F) and xanthan (X) (1, 1.5 and 2 %, g ingredient / 100 g 6
167
tomato) and 2nd MANOVA was 3 ways-ANOVA considering 3 factors (T, X and F) for each tomato product.
168
In both cases, the percentages of total variations were computed to explain the variance of each parameter, as
169
a function of the main and interaction effects to evaluate the contribution of each factor on its variability.
170
Significant differences among the mean values were calculated using Duncan’s test. All experimental data
171
were statistically analyzed using SPSS version 19.0 (SPSS Inc., Chicago, IL, USA).
172 173
3. Results and Discussion
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All the formulated tomato products using X or F resulted in differently thickened products that were found to
175
be stable during storage at a macroscopic observation. No syneresis was observed in all samples at all
176
storage times, indicating good stability of all products.
177
3.1. Overall evaluation of the experimental design through multivariate statistics
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The obtained dataset of physico-chemical properties was subjected to a 4 ways-ANOVA, and the partition of
179
sum squares of the studied factors and their interactions are summarized in Table 1. From the Pillai's trace
180
test, all the physico-chemical properties were significantly affected by the 4 studied factors [1: P (pulp,
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double and triple concentrate); 2: F (1, 1.5 and 2 %); 3: X (1, 1.5 and 2 %); 4: T, thermal treatments (cold
182
and hot)]. P mainly contributed to the changes of most parameters, except for some 1H NMR indicators that
183
were more controlled by T. Overall, T had a highly significant (p ≤ 0.001) effect on all parameters, except
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for one 1H NMR parameter. Likewise, thickening agents had a highly significant (p ≤ 0.001) effect but less
185
relevant than the above-mentioned factors. The interactions among factors were in most cases significant but
186
barely relevant as compared to the studied factors. Such a result can be likely attributed to a higher influence
187
of P on the studied parameters, which probably masked the effect of the remaining factors. To highlight the
188
single effect of T, F and X on physico-chemical properties, 3 ways-ANOVA was carried out on each
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category of tomato product and it will be discussed throughout this investigation.
190 191
3.2. Potato fiber vs xanthan gum usefulness in modulating physical properties of tomato products
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3.1.1. Color
193
The presence of added ingredients (F and X) drastically changed the color of tomato products, especially if
194
associated with a thermal treatment (T). In most cases, the interactions T×F and T×X significantly modified 7
195
color parameters indicating that the effect of the substitution was dependent on temperature (hot or cold)
196
(Table 2). This result can be explained by the degradation of lycopene upon prolonged heating treatments
197
(Manzo, Santini, Pizzolongo, Aiello, & Romano, 2018).
198
For TP, L* significantly decreased with F and X, following the same trend independently on T (Table S1). In
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DC, F was the leading factor on L* (an increase), with a 2% for cold processed and 1% for hot-processed
200
products. The (a*/b*) ratio is often used as an indicator to describe tomato sauces redness, which strictly
201
relates to consumers’ perception of the products (Barreiro et al., 1997; Batu, 2004). A tomato formulation is
202
considered having a desirable color for potential application when a*/b* = 2 (Wang, Sun, Li, Adhikari, & Li,
203
2018). For TP, a*/b* was quite low (1.1-1.4) and did not significantly changed as function of thermal
204
treatment but it was affected by the addition of additives particularly X (Table 2). In DC and TC, 2% of F
205
significantly increased a*/b* giving the highest value (a*/b*≥ 1.8) for cold-treated product, making them
206
top-quality products in terms of color (Donegà, Marchetti, Pedrini, Costa, & Tamburini, 2015; Wang et al.,
207
2018). F impact on DC color was more pronounced than X contrarily to TC. X resulted in lower values
208
(a*/b* <1.8) independently from the type of product and thermal treatment, indicating a potential decrease of
209
consumer acceptability in comparison to F based-products (Donegà et al., 2015).
210 211
3.1.2. Apparent viscosity
212
As illustrated in Table S1, the flow index “n” of TP and DC were lower than 1, confirming their pseudo-
213
plastic nature (n < 1). However, the n values of TC were close to 1, suggesting a Newtonian behavior. In
214
most cases, n decreased with increasing levels of ingredients (X and F), independently of product type. Table
215
1 reported the results of MANOVA performed on the data of TP and DC and excluding the data of TC,
216
which were not feasible to be discussed, possibly due to an heterogeneity of the matrix. The results showed
217
that the changes in n were mainly controlled by P, X and F, while T did not have relevant effect on n. In
218
Table 2, the contribution of the studied factors in this variability was closely related to product type. Indeed,
219
for TP, n was significantly controlled by F (74.56%), X (15.11%), T×F (7.37%), while T and T×X did not
220
show relevant impact. For DC, n was exclusively controlled by X (76.09%) and T×X (23.9%). This
221
variability can be likely attributed to different interaction established by the two additives with water and
8
222
other components of the matrix. Notably, F had a more pronounced effect on water retention than X in
223
products with low solid contents (TP).
224
The consistency coefficient K was significantly affected by P and F and their interaction, but T and X had no
225
effect (Table 1). For TP, K was significantly (p ≤ 0.001) influenced exclusively by F (97.35%, Table 2). For
226
DC, all the studied factors did not affected K and remained stable regardless of the treatment and the
227
type/dose of added additives (Table 2).
228 229
3.2. Potato fiber vs xanthan gum usefulness in modulating chemical properties of tomato products
230
3.2.1. Moisture content
231
As illustrated in Table 3, moisture contents (MC) of TP were significantly (p ≤ 0.001) controlled by F (55%)
232
and X (39%), but the effect of T was limited (∼ 5%). Noteworthy, the interactions T×F and T×X did not
233
have a significant effect indicating a stability of the thermal treatment in association with the addition of both
234
F and X. In DC, F and X resulted in similar MC, but T was the major factor (55%) followed by T×F (20%).
235
In TC, no changes were observed. Overall, MC slightly decreased in the presence of added ingredients
236
(Table S2), as expected.
237
3.2.1. Water activity
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Regarding water activity, slight changes were observed, where T did not show any relevant effect (Table 3).
239
For TP, a significant effect of F was observed, but no trend was observed. For DT, T×F significantly
240
contributed (53%) to water activity changes, yet additives addition was irrelevant. However, both added
241
ingredients slightly reduced water activity in TC. Overall, water activity did not show relevant changes
242
regardless of the amount/type of additive (Table S2).
243
3.2.3. pH
244
For all tomato products, pH ranged between 4.2 and 4.3 (Table S2), in agreement with previous works
245
(Busch, Savage, & Searle, 2008; Donegà et al., 2015). Based on Table 4, T did not significantly affect pH of
246
tomato products, except for DC, where its effect was significant (p ≤ 0.05) but minor (1.6%) (Table 3).
247
Besides, pH of TP was modified by X and F (p ≤ 0.001, 46%). In DC, F was more relevant (78.4%) over X
248
(14.7%), while that of TC was only influenced by X (53%). Such results indicated that pH mainly depended
9
249
on product’s solid concentration, with the added ingredients having a less important influence and no
250
particular trends was observed in the products separately considered.
251
3.2.4. Proton Nuclear Magnetic Resonance (1H NMR)
252
1
253
as population A (pop A) and B (pop B). The second population (pop B) described the same protons observed
254
in the first population of the T2 relaxation time distribution and, therefore, was not considered in the
255
discussion. As shown in Table S3, the more rigid protons, pop A generally reflected the presence of more
256
solids in all the products (increasing pop A with increasing amount of added ingredients). TA was
257
comparable in all products. Pop A was not affected by T, T×F and T×X in the case of TP (Table 3). In DC, it
258
was modulated by X (pop A: 33.4%); the effect of F was more relevant on pop A (48.6%) (Table 3).
259
Proton T2 distributions for all tomato products exhibited complex relaxations with the presence of pools of
260
protons with different mobility according to the product type. TP and DC showed three unresolved
261
populations (C, D and E, Figure 1 a and Figure 1 b), with the exception of X (three unresolved populations,
262
C, D, E and F, Figure 1c). TC indicated the presence of four populations in all formulations (Figure 1d), with
263
populations C and E represented by shoulders of the main peak. However, only two unresolved populations
264
were reported in tomato sauces in previous studies (Diantom et al., 2017). These findings might be
265
associated with the heterogeneity of canned products.
266
In the case of TP, 1H T2 populations (pop C, D, E and F, Table S3) and their corresponding relaxation time
267
(T2C, T2D, T2E and T2F, respectively) were significantly influenced in most cases by all factors (Table 3).
268
Considering the more abundant population (i.e. pop D), X showed a higher impact (61.5%) than F (28.9%),
269
while T effect was more relevant (34.9%) on its corresponding relaxation time (T2D) (Table 3). More mobile
270
protons (i.e. pop E) were strongly influenced by T, F and their interaction, while their corresponding
271
relaxation time was significantly affected by X (60.0%). In DC, all proton molecular mobility parameters
272
were in most cases significantly influenced by all factors, where X was the more relevant factor. As for TC,
273
T effect was more pronounced on pop D, pop E and pop C; while pop F was equally controlled by F and
274
T×F. Furthermore, F showed higher impact on pop C and pop F, while X was more relevant only on pop E.
275
Overall, the addition of F significantly induced an increase of rigidity with consequent limited mobility of
276
the protons. However, X significantly increased proton molecular mobility (Diantom et al., 2017).
H FIDs were fitted with a two components model and two proton populations were obtained and identified
10
277
The proton self-diffusion coefficient (1H D) (Table S3) was not significantly affected in TP by the studied
278
factors, while it was significantly decreased by T in DC and TC. Added ingredients reduced proton
279
translational mobility depending on the amount and the nature of tomato by product, where F was less
280
effective than X in both products, DC and TC. These changes might be related to the interactions among
281
added ingredient and tomato products’ components with a consequent establishment of gel-like structure,
282
which affected proton mobility (Carini et al., 2015).
283 284
4. Conclusion
285
In the light of the obtained results, integrating physical and chemical features enabled relevant insights on the
286
substitution of X by F (different concentration) in different tomato products (solid concentration) under
287
different thermal treatments (hot or cold): i) MANOVA showed that the full factorial design was efficient in
288
detecting differences between additives, when each product was treated separately; ii) for physical features:
289
a*/b* indicator showed that the addition of 2% of F enabled desirable color in DC and TC, while a*/b* of TP
290
was quite low regardless of the amount/type of additive. Moreover, F showed a stronger effect on apparent
291
viscosity than X particularly in the case of TP (the product with the lowest solid concentration); and iii)
292
chemical features: MC, water activity and pH significantly varied without showing a particular trend.
293
Noteworthy, 1H NMR revealed that F and X behaved different at a molecular scale, where F increased proton
294
molecular rigidity and X increased proton molecular mobility. Concluding, F can be a valid alternative for X
295
in tomato products formulations thereby avoiding the declaration of additives into product label. This might
296
suggest that F (2%) had a strong capacity to create a consistent structure of the product, and accordingly, F
297
can be used as substitute for X in tomato products applications.
298 299
Acknowledgments
300
The authors would like to thank Alessandro Grolli for carrying out part of the experimental work.
301 302
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388 389
Table 1: F significance level and sum square percent of the studied parameters and their interactions effects on physical and chemical features.
P T F X P* T P*F P*X T*F T*X P*T*F P*T*X
a*/b* ss (%) 37.72 1.09 4.16 10.19 2.99 12.85 7.07 7.39 0.34 14.03 2.15
P
ss (%) 99.51
T
0.12
F
0.04
sig *** *** *** *** *** *** *** *** *** *** ***
∆E ss (%) 17.88 2.53 2.44 2.03 1.24 16.66 22.43 2.96 1.30 28.99 1.54
Sig *** *** *** *** *** *** *** *** *** *** ***
K ss (%) 12.70 0.57 42.24 0.30 0.18 42.22 0.06 0.63 0.03 0.63 0.44
Sig *** ns *** ns ns *** ns ns ns ns ns
D
X
0.24
P* T
0.02
P*F
0.03
P *X
0.02
T*F
0.00
T *X
0.01
P*T*F
0.01
P*T*X
P T F X P* T P*F P *X T*F T *X P*T*F P*T*X
390
ss (%)
0.00 Pop D ss (%) 0.02 55.77 3.68 16.94 1.45 0.00 1.62 10.52 1.96 0.00 8.04
*** *** *** *** *** *** *** * *** *** ns sig ns *** *** *** ** ns * *** * ns ***
Pop E ss (%) sig 0.30 ns 55.96 *** 5.26 *** 14.57 *** 1.30 ** 0.00 ns 1.66 ** 11.83 *** 1.68 * 0.00 ns 7.44 ***
Pop F ss (%) sig 63.28 *** 6.62 *** 12.91 *** 2.22 *** 0.00 ns 0.00 ns 0.55 *** 14.05 *** 0.21 ns 0.00 ns 0.13 ns
n ss (%) 42.76 0.22 17.54 14.25 0.66 17.54 0.44 1.75 1.10 1.75 1.97 PopA ss (%) 80.38
sig *** ns *** *** ns *** ns * ns * * sig ***
MC ss (%) 99.15 0.12 0.09 0.20 0.05 0.24 0.04 0.03 0.01 0.04 0.03 TA ss (%) 28.72
sig *** *** *** *** ** *** ns ns ns ns ns Sig ***
ss (%) 39.36 0.11 20.37 1.03 0.88 17.08 15.38 2.45 0.20 1.31 1.85 TB ss (%) 99.99
pH ss (%) *** ns *** * * *** *** *** ns ns * sig ***
aw ss (%) sig 97.61 *** 0.00 *** 0.51 *** 0.29 *** 0.08 ** 0.91 *** 0.28 ns 0.02 ns 0.04 ns 0.12 ns 0.14 ns Pop C ss (%) sig 0.53 ns
0.20
***
0.06
ns
0.00
ns
49.44
***
11.91
***
7.54
***
0.00
ns
26.18
***
5.20
***
41.00
***
0.00
ns
10.21
***
0.77
***
2.31
*
0.00
ns
0.30
ns
0.41
***
2.48
ns
0.00
ns
0
ns
0.37
***
4.38
**
0.00
ns
0.90
ns
0.02
ns
0.61
ns
0.00
ns
8.07
***
0.15
***
1.02
ns
0.00
ns
0.84
ns
0.38
***
0.58
ns
0.00
ns
0.00
ns
***
0.00
ns
0.21 T2C ss (%) 19.79 37.92 3.24 24.07 1.17 0.00 2.86 5.90 1.59 0.00 3.47
*** sig *** *** ** *** * ns ** * ns ns ***
11.29 T2D ss (%) 37.55 26.53 3.13 25.69 0.35 0.00 1.22 3.05 0.29 0.00 2.18
sig *** *** *** *** * ns *** *** ns ns ***
ns= not significant; *: p ≤ 0.05; **: p ≤ 0.01; ***: p≤ 0.001; SS: sum of squares
15
T2E ss (%) 20.30 44.56 1.56 23.49 0.43 0.00 0.55 8.19 0.32 0.00 0.61
sig *** *** *** *** *** ns *** *** * ns ***
3.52 T2F ss (%) 74.08 11.86 6.61 6.51 0.00 0.00 0.32 0.37 0.05 0.00 0.20
*** sig *** *** *** *** Ns Ns Ns Ns ns ns ns
391
Table 2: F significance level and sum square percent of the studied parameters and their interactions effects
392
on physical features of each tomato product.
T F
TP
X T*F T *X
a*/b*
∆E
K
n
0.15 ns 18.73 *** 69.29 *** 9.80 *** 2.02 **
0.01 ns 3.28 *** 63.04 *** 31.44 *** 2.23 **
0.81 ns 97.35 *** 0.13 ns 1.45 ns 0.26 ns
1.79 ns 74.56 *** 15.11 *** 7.37 *** 1.17 ns
sig
23.07 *** 59.57 *** 3.90 *** 12.40 *** 1.06 *
10.43 *** 71.11 *** 2.50 *** 15.71 *** 0.26 ns
9.63 ns 0.00 ns 45.07 ns 0.00 ns 45.29 ns
0.00 ns 0.00 ns 76.09 *** 0.00 ns 23.91 ***
ss (%) sig ss (%) sig ss (%) sig ss (%) sig ss (%) sig
0.01 ns 9.93 *** 19.66 *** 63.92 *** 6.47 ***
3.70 *** 9.02 *** 24.55 *** 57.56 *** 5.17 ***
-
-
ss (%) sig ss (%) sig ss (%) sig ss (%) sig ss (%) sig
T
ss (%)
F
ss (%)
X
ss (%)
T*F
ss (%)
T*X
ss (%)
sig sig
DC
sig sig
T F
TC
X T*F T*X
393 394
ns= not significant; *: p ≤ 0.05; **: p ≤ 0.01; ***: p≤ 0.001; SS: sum of squares
395 396
16
Table 3: F significance level and sum square percent of the studied parameters and their interactions effects on chemical features of each tomato product.1
T F TP
X T*F T *X T F
DC
X T*F T*X
T F TC
X T*F T*X
1
MC 5.2 *** 55.2 *** 38.9 *** 0.3 ns 0.4 ns
aw 4.3 ns 81.3 *** 3.4 ns 1.1 ns 10.0 ns
pH 0.6 ns 40.6 *** 40.1 *** 4.5 * 2.5 ns
D 4.7 ns 24.1 ns 17.0 ns 25.5 ns 28.7 ns
PopA 0.0 ns 66.3 *** 33.3 *** 0.1 ns 0.3 ns
TA 0.4 ns 20.2 ** 74.3 *** 1.1 ns 4.0 ns
TB 15.2 ns 22.8 ns 54.5 ** 3.9 ns 3.7 ns
Pop C 34.5 *** 8.2 *** 43.7 *** 1.7 ** 11.9 ***
Pop D 6.1 *** 28.9 ** 61.5 *** 2.2 *** 1.3 **
Pop E 49.2 *** 16.6 *** 4.3 *** 24.0 *** 5.9 ***
Pop F -
T2C 0.5 *** 21.7 *** 76.9 *** 0.5 *** 0.4 ***
T2D 34.9 *** 14.5 *** 18.7 *** 29.8 *** 2.1 ***
T2E 1.5 ns 10.7 *** 60.0 *** 18.0 *** 9.8 ***
T2F -
55.2 *** 8.7 ns 12.2 ns 20.1 * 3.7 ns
5.3 ns 2.9 ns 11.9 ns 53.1 *** 26.8 ns
1.69 * 78.4 *** 14.78 *** 3.9 * 1.4 ns
22.4 *** 9.8 *** 64.6 *** 0.1 ns 3.2 ***
12.3 *** 48.9 *** 33.4 *** 2.0 *** 3.4 ***
5.9 ** 11.9 *** 41.9 *** 1.3 ns 38.9 ***
5.3 ns 27.9 ** 55.9 *** 4.3 ns 6.8 ns
12.3 *** 2.5 *** 78.4 *** 6.8 *** 0.0 ns
2.7 *** 2.3 *** 94.6 *** 0.3 *** 0.0 ns
0.6 * 4.2 *** 70.9 *** 11.0 *** 13.3 ***
-
4.1 *** 3.0 *** 92.2 *** 0.3 *** 0.3 ***
2.1 *** 1.0 * 89.3 *** 0.8 * 6.7 ***
0.2 ** 2.9 *** 93.8 *** 2.3 *** 0.9 ***
-
5.0 ns 14.5 ns 43.8 ns 17.1 ns 19.6 ns
2.0 ns 42.5 *** 44.5 *** 7.0 ns 4.0 ns
3.7 ns 8.5 ns 53. *** 20.1 ns 14.77 ns
51.8 *** 8.3 *** 38.1 *** 0.83 ns 0.90 *
0.5 * 77.6 *** 16.5 *** 4.0 *** 1.42 ***
5.6 ** 7.3 * 66.4 *** 3.0 ns 17.71 ***
0.5 * 77.6 *** 16.5 *** 4.0 *** 1.42 ***
44.5 *** 33.0 *** 7.9 *** 10.1 *** 4.5 **
53.6 *** 5.8 *** 15.4 *** 16.5 *** 8.7 ***
51.4 *** 2.6 *** 31.7 *** 13.7 *** 0.6 ***
21.6 *** 33.7 *** 7.1 *** 36.7 *** 0.9 *
44.3 *** 6.6 *** 27.9 *** 12.1 *** 9.1 ***
41.8 *** 7.8 *** 40.4 *** 7.6 *** 2.4 ***
53.7 *** 8.0 *** 12.6 *** 17.9 *** 7.8 **
39.5 *** 31.6 *** 26.4 *** 1.8 ns 0.7 ns
ns= not significant; *: p ≤ 0.05; **: p ≤ 0.01; ***: p≤ 0.001; SS: sum of squares
17
Figure 1: Characteristic 1H T2 NMR distributions of relaxation times for (a) tomato pulp STD, F, and X, (b1) double concentrate STD and F, (b2) double concentrate X, (c) triple concentrate STD, F, and X.
Highlights:
•
Potato fiber was tested as a clean label ingredient in different tomato products.
•
Potato fiber performance was compared to xanthan by multivariate statistics.
•
Potato fiber showed a stronger effect on apparent viscosity than xanthan.
•
Potato fiber reduced proton molecular mobility, in contrast with xanthan.
Conflict of Interest and Authorship Conformation Form Please check the following as appropriate:
o
All authors have participated in (a) conception and design, or analysis and interpretation of the data; (b) drafting the article or revising it critically for important intellectual content; and (c) approval of the final version.
o
This manuscript has not been submitted to, nor is under review at, another journal or other publishing venue.
o
The authors have no affiliation with any organization with a direct or indirect financial interest in the subject matter discussed in the manuscript
o
The following authors have affiliations with organizations with direct or indirect financial interest in the subject matter discussed in the manuscript:
Author’s name
Agoura Diantom
Affiliation
Department of Food and Drug, University of Parma &
Ecole Supérieure des Techniques Biologiques et Alimentaires, University of Lomé Fatma Boukid
Department of Food and Drug, University of Parma
Elena Curti
Department of Food and Drug, University of Parma
Eleonora Carini
Department of Food and Drug, University of Parma
Elena Vittadini
Department of Food and Drug, University of Parma & School of Biosciences and Veterinary Medicine, University of Camerino
S0268-005X(19)30204-8
DOI:
https://doi.org/10.1016/j.foodhyd.2019.105508
Reference:
FOOHYD 105508
To appear in:
Food Hydrocolloids
Received Date: 28 January 2019 Revised Date:
18 October 2019
Accepted Date: 11 November 2019
Please cite this article as: Diantom, A., Boukid, F., Carini, E., Curti, E., Vittadini, E., Can potato fiber efficiently substitute xanthan gum in modulating chemical properties of tomato products?, Food Hydrocolloids (2019), doi: https://doi.org/10.1016/j.foodhyd.2019.105508. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.
1
Can potato fiber efficiently substitute xanthan gum in modulating chemical properties of tomato
2
products?
3 4
Agoura Diantom1, Fatma Boukid1,2, Eleonora Carini1,2, Elena Curti1, Elena Vittadini1,3*
5 6 7
1
Department of Food and Drug, University of Parma, Parco Area delle Scienze 47/a, 43124 Parma, Italy
8
2
Siteia.Parma Interdepartmental Centre, University of Parma, Parco Area delle Scienze 181/a, Italy
9
3
School of Biosciences and Veterinary Medicine, University of Camerino, via Gentile da Varano III, 62032
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Camerino (MC), Italy (current address)
11 12
* Corresponding author: Elena Vittadini. Address: School of Biosciences and Veterinary Medicine,
13
University of Camerino, via Gentile da Varano III, 62032 Camerino (MC), Italy. Email:
14
[email protected].
15 16 17 18 19 20 21 22 23 24 25 26 27 28
Abstract 1
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In the frame of clean labelling, potato fiber (F) was tested as a potential texturizing agent to substitute
30
xanthan (X) in the tomato industry. For this purpose, a physico-chemical evaluation was performed on three
31
different tomato products [(tomato pulp (TP), double (DC) and triple tomato concentrate (TC)] that were
32
processed under different thermal treatments (cold and hot) and added with different levels (1, 1.5 and 2 %
33
(g ingredient / 100 g tomato product) of texturing agents (F and X). For physical features, a higher redness
34
was obtained at 2% of F in DC and TC, while TP color remained unvaried. Furthermore, F showed a
35
stronger effect on apparent viscosity than X in the case of TP. Concerning chemical features, moisture
36
content, water activity and pH significantly varied among samples, but no clear trend was observed as a
37
function of amount/type of additive. At a molecular level, F reduced proton molecular mobility, in contrast
38
with X. Summarizing, F can be considered a potential “clean label” substitute for X in tomato-based
39
products.
40 41
Keywords: tomato, multivariate statistics, clean label, NMR, consistency, color
42 43 44 45 46 47 48 49 50 51 52 53 54 55 56
1. Introduction 2
57
Clean labeling has been and is still among the trendiest concern in the food industry, where the term “clean
58
label” is a sort of reflection of transparency and better health and authenticity, but the conception is still not
59
fully deciphered (Nascimento, De Oliveira Do Nascimento, Do, Dias Paes, & Augusta, 2018; Weinrich &
60
Spiller, 2016). Product developers still need more information about the list of clean label ingredients and
61
particularly the reasons behind their inclusion, to embrace more of a clean label philosophy, rather than rigid
62
rules (Alting & van de Velde, 2012; Asioli et al., 2017; Osborn, 2015). Consumers are also asking for clean
63
label products, given their increasing consciousness toward natural ingredients and their association to
64
healthiness and wellbeing (Aschemann-Witzel, Varela, & Peschel, 2019; Asioli et al., 2017; Hartmann,
65
Hieke, Taper, & Siegrist, 2018). As a result, manufacturers are encountering serious challenges when
66
considering moving to clean label products in terms of processing and formulation (Osborn, 2015). The
67
substitution of a “non-clean” ingredient with a “clean” one should assure the same functionality and
68
performance, so that the product they are included in will be equally accepted by consumers.
69
Tomato is one of the most important vegetables used for human nutrition, which can be consumed either
70
fresh or, more frequently, processed due its perishable nature. A wide spectrum of tomato products is
71
available in the market, tomato pulp, concentrates, dippings (e.g. Mexican salsa), condiments (e.g. ketchup,
72
tomato sauce or pulp), complex foods (e.g. eggplants parmigiana), and beverages (e.g. gazpacho). To reach
73
the suitable consistency and water activity, these products are generally subjected to different processing and
74
additives can be included in the formulation. Hydrocolloids (e.g. native starch, xanthan, guar, carboxy
75
methyl cellulose, tragacanth and locust bean gums) are commonly added as additives in tomato industry
76
(Diantom, Curti, Carini, & Vittadini, 2017; Koocheki, Ghandi, Razavi, Mortazavi, & Vasiljevic, 2009; Sahin
77
& Ozdemir, 2004), as they are able to modulate the rheological features of tomato-based products, according
78
to their intended use, by increasing viscosity, interact with water and improve physical stability. Among
79
hydrocolloids, xanthan gum is intensively used as a stabilizer, thickener or emulsifier in tomato products
80
(Diantom et al., 2017; Torbica et al., 2016). However, xanthan gum is considered a food additive (identified
81
as E415) by FDA (Code of Federal Regulations Title 21 21CFR172.695, 2018) and the European Union
82
(McArdle & Hamill, 2011), and hence, does not fit in within the clean label category.
83
In the frame of these challenges, the present study aims to test the feasibility of potato fiber to substitute
84
xanthan in different tomatoes products. Potato fiber has been already recognized with specific physico3
85
chemical and functional properties (e.g. high water-holding capacity and emulsifying) (Dhingra, Michael,
86
Rajput, & Patil, 2012; Dobrowolski et al., 2012; Olatunde, Henshaw, Idowu, & Tomlins, 2016). In previous
87
work, very interesting structural and functional properties (i.e. water and oil-holding capacity, foaming and
88
emulsion properties) of potato fiber extracted from potato peel waste were reported,which were ascribable to
89
the presence of CO, CH and OH functional groups. (Jeddou et al., 2016). Commercial potato fiber (used in
90
the present work, which extracted from potato peel) was reported to retard staling in bread thanks to its
91
ability to interact with water at mesoscopic (throughout DSC analysis) and molecular (throughout 1H NMR
92
Relaxometry) levels (Curti, Carini, Diantom, & Vittadini, 2016).
93
A full factorial design was set up with 4 factors: tomato product [with different total solids: tomato pulp,
94
double and triple concentrates, thermal treatment and different levels of addition of potato fiber and xanthan
95
[1, 1.5 and 2 % (g ingredient / 100 g tomato product)]. Accordingly, the effect of the substitution was
96
assessed in terms of physical (color and rheology) and chemical properties [(water activity, moisture content,
97
pH and proton molecular mobility NMR indicators (1H FID, 1H T2 and 1H D)].
98 99
2. Materials and methods
100
2.1. Tomato products’ preparation
101
Tomato products [tomato pulp (TP), double (DC) and triple concentrates (TC); Mutti S.p.a., Parma, Italy]
102
with the same expiration date were purchased from a local supermarket. Xanthan (X) gum [humidity: max
103
13% (g / 100 g); ashes: max 13%; proteins (Nx6.5) max 5%; fat: max 1%] was provided from Chimab S.p.a
104
(Campodaresego, Italy), and potato fiber (F) [HI-FIBRE 115; < 6.0% moisture, protein < 1.0 %, fat < 1.0%,
105
non-dietary fiber carbohydrates < 1.0 %, dietary fiber ~ 92.0 % (soluble fiber ~ 73.0 %; insoluble fiber ~
106
19.0 %), ashes ~ 2.0 %] from HI-FOOD S.p.a (Parma, Italy).
107
Tomato pulp with no added ingredients (0%) was used as a control, and it was added with X or F at different
108
levels [1, 1.5 and 2 % (g ingredient / 100 g tomato)] and mixed (Bimby® Vorwerk, Sunbeam, USA) at 25°C
109
for 2 min at 500 rpm to prepare the functionalized samples. After mixing, 200 g aliquots of the control and
110
the added products were placed in glass jars and sealed and stored at room temperature (cold samples). The
111
remaining products were subjected to continuous mixing (80°C, 20 min) and placed into glass jars (200 g
4
112
aliquots). Afterward, the heated jars were sealed and stored at room temperature (hot samples). All jars were
113
stored at room temperature for 12 hours before analysis.
114 115
2.2. Tomato products’ physico-chemical characterization
116
2.2.1. Color
117
Color indicators L* (lightness), and degree of redness (a*/b* ratio, where a* red-green and b* yellow-blue,
118
Barreiro, Milano, & Sandoval, 1997; Batu, 2004) were measured with a Colorimeter (D65, 10° position,
119
standard observer, CIE, 1978; CM 2600d, Minolta Co., Osaka, Japan). At least twelve measurements were
120
taken for each sample.
121
2.2.2. Apparent viscosity
122
Tomato products’ apparent viscosity was measured with an ARES Rheometer (TA Instruments, New Castle,
123
DE, USA), using a Couette geometry (34 mm cup diameter, 32 mm bob diameter and 33 mm height). About
124
8 mL of tomato product were transferred into the cup and subjected to a rate sweep test (1-600 s-1, 25°C,
125
points for decade 10) to obtain shear stress (τ) and viscosity. Shear rate (γ) and viscosity were then fitted
126
with a non-Newtonian model (Cross equation, Khalili Garakani, et al., 2011) to extrapolate y0 (yield stress),
127
flow index (n), and the consistency coefficient (K). Y = a + ((
128
− a))/(1 +
∗
)
129
2.2.3. Moisture content
130
Moisture content (MC, % g water / 100 g product) of tomato products was determined by weight loss by
131
drying in a forced-air oven (ISCO NSV 9035, ISCO, Milan, Italy) at 80°C to constant weight. At least
132
triplicate tomato products samples were analyzed.
133
2.2.4. Water activity
134
Water activity of tomato products were measured at 25°C (Aqualab 4TE, Decagon Devices, Inc. WA, USA).
135
At least triplicate measurements were taken for each tomato product.
136
2.2.5. pH
137
The pH of all tomato products was measured at 25°C (JENWAY 3510 pH meter, Bibby Scientific Ltd,
138
Stone, Staff, UK). pH meter was calibrated with two buffer solutions (pH 7 and pH 4). At least triplicate
139
measurements were obtained for each tomato product. 5
140
2.2.6. 1H Molecular Mobility (1H Low Resolution Nuclear Magnetic Resonance)
141
A low resolution (20 MHz) 1H Nuclear Magnetic Resonance (NMR) spectrometer (the MiniSpec, Bruker
142
Biospin, Milano, Italy) operating at 25.0 ± 0.1 °C was used. About 4 grams of tomato product (10 mm high)
143
were placed into a 10 mm (diameter) NMR tube that was then sealed with Parafilm® to prevent moisture
144
loss during the NMR experiment. 1H FIDs were acquired using a single 90° pulse, followed by a dwell time
145
of 7 µs, a recycle delay of 5 s and a 0.5 ms acquisition window and 900 data points. The curves were fitted
146
with a two components model [exponential and Gaussian, Le Grand, Cambert, & Mariette, 2007; Sigmaplot,
147
v6, Systat Software Inc., USA] ( )= 0+
×
+
×
(
)
148
where y0 is the FID decay offset, A and B are the intensities of each relaxation component, TA and TB are
149
the apparent relaxation times.
150
T2 spin-spin relaxation time was measured with a Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence with a
151
recycle delay of 3 s (≥5 1H T1), an interpulse spacing of 0.04 ms and 26000 data points. 1H T2 curves were
152
analyzed as quasi-continuous distributions of relaxation times using an UPENWin software (Alma Mater
153
Studiorum, Bologna, Italy). Default values for all UPEN settings parameters were used with the exception of
154
the LoXtrap parameter that was set to 1 to avoid extrapolation of relaxation times shorter than the first
155
experimental point. 1H T2 CPMG relaxation decays were also fitted with a discrete exponential model
156
(Sigmaplot, v.6, Systat Software Inc., USA).
157
Proton self-diffusion coefficient (1H D) was measured at 25°C with a pulsed-field gradient spin echo
158
(PFGSE) sequence and a 30 % gradient. The instrument was calibrated with water at 25°C (D = 2.29*10-9 m2
159
/s).
160 161
2.4. Statistical analysis
162
Considering that the studied data set was a full factorial design, multivariate analysis of variance
163
(MANOVA) was used to determine the contribution of each factor to the physico-chemical properties
164
changes in tomato products. Two MANOVA were performed based on fixed factors at a significance level of
165
α=0.05: 1st MANOVA was a 4ways-ANOVA taking into consideration 4 factors [P: product, T: thermal
166
treatment (cold/hot) levels addition of potato fiber (F) and xanthan (X) (1, 1.5 and 2 %, g ingredient / 100 g 6
167
tomato) and 2nd MANOVA was 3 ways-ANOVA considering 3 factors (T, X and F) for each tomato product.
168
In both cases, the percentages of total variations were computed to explain the variance of each parameter, as
169
a function of the main and interaction effects to evaluate the contribution of each factor on its variability.
170
Significant differences among the mean values were calculated using Duncan’s test. All experimental data
171
were statistically analyzed using SPSS version 19.0 (SPSS Inc., Chicago, IL, USA).
172 173
3. Results and Discussion
174
All the formulated tomato products using X or F resulted in differently thickened products that were found to
175
be stable during storage at a macroscopic observation. No syneresis was observed in all samples at all
176
storage times, indicating good stability of all products.
177
3.1. Overall evaluation of the experimental design through multivariate statistics
178
The obtained dataset of physico-chemical properties was subjected to a 4 ways-ANOVA, and the partition of
179
sum squares of the studied factors and their interactions are summarized in Table 1. From the Pillai's trace
180
test, all the physico-chemical properties were significantly affected by the 4 studied factors [1: P (pulp,
181
double and triple concentrate); 2: F (1, 1.5 and 2 %); 3: X (1, 1.5 and 2 %); 4: T, thermal treatments (cold
182
and hot)]. P mainly contributed to the changes of most parameters, except for some 1H NMR indicators that
183
were more controlled by T. Overall, T had a highly significant (p ≤ 0.001) effect on all parameters, except
184
for one 1H NMR parameter. Likewise, thickening agents had a highly significant (p ≤ 0.001) effect but less
185
relevant than the above-mentioned factors. The interactions among factors were in most cases significant but
186
barely relevant as compared to the studied factors. Such a result can be likely attributed to a higher influence
187
of P on the studied parameters, which probably masked the effect of the remaining factors. To highlight the
188
single effect of T, F and X on physico-chemical properties, 3 ways-ANOVA was carried out on each
189
category of tomato product and it will be discussed throughout this investigation.
190 191
3.2. Potato fiber vs xanthan gum usefulness in modulating physical properties of tomato products
192
3.1.1. Color
193
The presence of added ingredients (F and X) drastically changed the color of tomato products, especially if
194
associated with a thermal treatment (T). In most cases, the interactions T×F and T×X significantly modified 7
195
color parameters indicating that the effect of the substitution was dependent on temperature (hot or cold)
196
(Table 2). This result can be explained by the degradation of lycopene upon prolonged heating treatments
197
(Manzo, Santini, Pizzolongo, Aiello, & Romano, 2018).
198
For TP, L* significantly decreased with F and X, following the same trend independently on T (Table S1). In
199
DC, F was the leading factor on L* (an increase), with a 2% for cold processed and 1% for hot-processed
200
products. The (a*/b*) ratio is often used as an indicator to describe tomato sauces redness, which strictly
201
relates to consumers’ perception of the products (Barreiro et al., 1997; Batu, 2004). A tomato formulation is
202
considered having a desirable color for potential application when a*/b* = 2 (Wang, Sun, Li, Adhikari, & Li,
203
2018). For TP, a*/b* was quite low (1.1-1.4) and did not significantly changed as function of thermal
204
treatment but it was affected by the addition of additives particularly X (Table 2). In DC and TC, 2% of F
205
significantly increased a*/b* giving the highest value (a*/b*≥ 1.8) for cold-treated product, making them
206
top-quality products in terms of color (Donegà, Marchetti, Pedrini, Costa, & Tamburini, 2015; Wang et al.,
207
2018). F impact on DC color was more pronounced than X contrarily to TC. X resulted in lower values
208
(a*/b* <1.8) independently from the type of product and thermal treatment, indicating a potential decrease of
209
consumer acceptability in comparison to F based-products (Donegà et al., 2015).
210 211
3.1.2. Apparent viscosity
212
As illustrated in Table S1, the flow index “n” of TP and DC were lower than 1, confirming their pseudo-
213
plastic nature (n < 1). However, the n values of TC were close to 1, suggesting a Newtonian behavior. In
214
most cases, n decreased with increasing levels of ingredients (X and F), independently of product type. Table
215
1 reported the results of MANOVA performed on the data of TP and DC and excluding the data of TC,
216
which were not feasible to be discussed, possibly due to an heterogeneity of the matrix. The results showed
217
that the changes in n were mainly controlled by P, X and F, while T did not have relevant effect on n. In
218
Table 2, the contribution of the studied factors in this variability was closely related to product type. Indeed,
219
for TP, n was significantly controlled by F (74.56%), X (15.11%), T×F (7.37%), while T and T×X did not
220
show relevant impact. For DC, n was exclusively controlled by X (76.09%) and T×X (23.9%). This
221
variability can be likely attributed to different interaction established by the two additives with water and
8
222
other components of the matrix. Notably, F had a more pronounced effect on water retention than X in
223
products with low solid contents (TP).
224
The consistency coefficient K was significantly affected by P and F and their interaction, but T and X had no
225
effect (Table 1). For TP, K was significantly (p ≤ 0.001) influenced exclusively by F (97.35%, Table 2). For
226
DC, all the studied factors did not affected K and remained stable regardless of the treatment and the
227
type/dose of added additives (Table 2).
228 229
3.2. Potato fiber vs xanthan gum usefulness in modulating chemical properties of tomato products
230
3.2.1. Moisture content
231
As illustrated in Table 3, moisture contents (MC) of TP were significantly (p ≤ 0.001) controlled by F (55%)
232
and X (39%), but the effect of T was limited (∼ 5%). Noteworthy, the interactions T×F and T×X did not
233
have a significant effect indicating a stability of the thermal treatment in association with the addition of both
234
F and X. In DC, F and X resulted in similar MC, but T was the major factor (55%) followed by T×F (20%).
235
In TC, no changes were observed. Overall, MC slightly decreased in the presence of added ingredients
236
(Table S2), as expected.
237
3.2.1. Water activity
238
Regarding water activity, slight changes were observed, where T did not show any relevant effect (Table 3).
239
For TP, a significant effect of F was observed, but no trend was observed. For DT, T×F significantly
240
contributed (53%) to water activity changes, yet additives addition was irrelevant. However, both added
241
ingredients slightly reduced water activity in TC. Overall, water activity did not show relevant changes
242
regardless of the amount/type of additive (Table S2).
243
3.2.3. pH
244
For all tomato products, pH ranged between 4.2 and 4.3 (Table S2), in agreement with previous works
245
(Busch, Savage, & Searle, 2008; Donegà et al., 2015). Based on Table 4, T did not significantly affect pH of
246
tomato products, except for DC, where its effect was significant (p ≤ 0.05) but minor (1.6%) (Table 3).
247
Besides, pH of TP was modified by X and F (p ≤ 0.001, 46%). In DC, F was more relevant (78.4%) over X
248
(14.7%), while that of TC was only influenced by X (53%). Such results indicated that pH mainly depended
9
249
on product’s solid concentration, with the added ingredients having a less important influence and no
250
particular trends was observed in the products separately considered.
251
3.2.4. Proton Nuclear Magnetic Resonance (1H NMR)
252
1
253
as population A (pop A) and B (pop B). The second population (pop B) described the same protons observed
254
in the first population of the T2 relaxation time distribution and, therefore, was not considered in the
255
discussion. As shown in Table S3, the more rigid protons, pop A generally reflected the presence of more
256
solids in all the products (increasing pop A with increasing amount of added ingredients). TA was
257
comparable in all products. Pop A was not affected by T, T×F and T×X in the case of TP (Table 3). In DC, it
258
was modulated by X (pop A: 33.4%); the effect of F was more relevant on pop A (48.6%) (Table 3).
259
Proton T2 distributions for all tomato products exhibited complex relaxations with the presence of pools of
260
protons with different mobility according to the product type. TP and DC showed three unresolved
261
populations (C, D and E, Figure 1 a and Figure 1 b), with the exception of X (three unresolved populations,
262
C, D, E and F, Figure 1c). TC indicated the presence of four populations in all formulations (Figure 1d), with
263
populations C and E represented by shoulders of the main peak. However, only two unresolved populations
264
were reported in tomato sauces in previous studies (Diantom et al., 2017). These findings might be
265
associated with the heterogeneity of canned products.
266
In the case of TP, 1H T2 populations (pop C, D, E and F, Table S3) and their corresponding relaxation time
267
(T2C, T2D, T2E and T2F, respectively) were significantly influenced in most cases by all factors (Table 3).
268
Considering the more abundant population (i.e. pop D), X showed a higher impact (61.5%) than F (28.9%),
269
while T effect was more relevant (34.9%) on its corresponding relaxation time (T2D) (Table 3). More mobile
270
protons (i.e. pop E) were strongly influenced by T, F and their interaction, while their corresponding
271
relaxation time was significantly affected by X (60.0%). In DC, all proton molecular mobility parameters
272
were in most cases significantly influenced by all factors, where X was the more relevant factor. As for TC,
273
T effect was more pronounced on pop D, pop E and pop C; while pop F was equally controlled by F and
274
T×F. Furthermore, F showed higher impact on pop C and pop F, while X was more relevant only on pop E.
275
Overall, the addition of F significantly induced an increase of rigidity with consequent limited mobility of
276
the protons. However, X significantly increased proton molecular mobility (Diantom et al., 2017).
H FIDs were fitted with a two components model and two proton populations were obtained and identified
10
277
The proton self-diffusion coefficient (1H D) (Table S3) was not significantly affected in TP by the studied
278
factors, while it was significantly decreased by T in DC and TC. Added ingredients reduced proton
279
translational mobility depending on the amount and the nature of tomato by product, where F was less
280
effective than X in both products, DC and TC. These changes might be related to the interactions among
281
added ingredient and tomato products’ components with a consequent establishment of gel-like structure,
282
which affected proton mobility (Carini et al., 2015).
283 284
4. Conclusion
285
In the light of the obtained results, integrating physical and chemical features enabled relevant insights on the
286
substitution of X by F (different concentration) in different tomato products (solid concentration) under
287
different thermal treatments (hot or cold): i) MANOVA showed that the full factorial design was efficient in
288
detecting differences between additives, when each product was treated separately; ii) for physical features:
289
a*/b* indicator showed that the addition of 2% of F enabled desirable color in DC and TC, while a*/b* of TP
290
was quite low regardless of the amount/type of additive. Moreover, F showed a stronger effect on apparent
291
viscosity than X particularly in the case of TP (the product with the lowest solid concentration); and iii)
292
chemical features: MC, water activity and pH significantly varied without showing a particular trend.
293
Noteworthy, 1H NMR revealed that F and X behaved different at a molecular scale, where F increased proton
294
molecular rigidity and X increased proton molecular mobility. Concluding, F can be a valid alternative for X
295
in tomato products formulations thereby avoiding the declaration of additives into product label. This might
296
suggest that F (2%) had a strong capacity to create a consistent structure of the product, and accordingly, F
297
can be used as substitute for X in tomato products applications.
298 299
Acknowledgments
300
The authors would like to thank Alessandro Grolli for carrying out part of the experimental work.
301 302
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Table 1: F significance level and sum square percent of the studied parameters and their interactions effects on physical and chemical features.
P T F X P* T P*F P*X T*F T*X P*T*F P*T*X
a*/b* ss (%) 37.72 1.09 4.16 10.19 2.99 12.85 7.07 7.39 0.34 14.03 2.15
P
ss (%) 99.51
T
0.12
F
0.04
sig *** *** *** *** *** *** *** *** *** *** ***
∆E ss (%) 17.88 2.53 2.44 2.03 1.24 16.66 22.43 2.96 1.30 28.99 1.54
Sig *** *** *** *** *** *** *** *** *** *** ***
K ss (%) 12.70 0.57 42.24 0.30 0.18 42.22 0.06 0.63 0.03 0.63 0.44
Sig *** ns *** ns ns *** ns ns ns ns ns
D
X
0.24
P* T
0.02
P*F
0.03
P *X
0.02
T*F
0.00
T *X
0.01
P*T*F
0.01
P*T*X
P T F X P* T P*F P *X T*F T *X P*T*F P*T*X
390
ss (%)
0.00 Pop D ss (%) 0.02 55.77 3.68 16.94 1.45 0.00 1.62 10.52 1.96 0.00 8.04
*** *** *** *** *** *** *** * *** *** ns sig ns *** *** *** ** ns * *** * ns ***
Pop E ss (%) sig 0.30 ns 55.96 *** 5.26 *** 14.57 *** 1.30 ** 0.00 ns 1.66 ** 11.83 *** 1.68 * 0.00 ns 7.44 ***
Pop F ss (%) sig 63.28 *** 6.62 *** 12.91 *** 2.22 *** 0.00 ns 0.00 ns 0.55 *** 14.05 *** 0.21 ns 0.00 ns 0.13 ns
n ss (%) 42.76 0.22 17.54 14.25 0.66 17.54 0.44 1.75 1.10 1.75 1.97 PopA ss (%) 80.38
sig *** ns *** *** ns *** ns * ns * * sig ***
MC ss (%) 99.15 0.12 0.09 0.20 0.05 0.24 0.04 0.03 0.01 0.04 0.03 TA ss (%) 28.72
sig *** *** *** *** ** *** ns ns ns ns ns Sig ***
ss (%) 39.36 0.11 20.37 1.03 0.88 17.08 15.38 2.45 0.20 1.31 1.85 TB ss (%) 99.99
pH ss (%) *** ns *** * * *** *** *** ns ns * sig ***
aw ss (%) sig 97.61 *** 0.00 *** 0.51 *** 0.29 *** 0.08 ** 0.91 *** 0.28 ns 0.02 ns 0.04 ns 0.12 ns 0.14 ns Pop C ss (%) sig 0.53 ns
0.20
***
0.06
ns
0.00
ns
49.44
***
11.91
***
7.54
***
0.00
ns
26.18
***
5.20
***
41.00
***
0.00
ns
10.21
***
0.77
***
2.31
*
0.00
ns
0.30
ns
0.41
***
2.48
ns
0.00
ns
0
ns
0.37
***
4.38
**
0.00
ns
0.90
ns
0.02
ns
0.61
ns
0.00
ns
8.07
***
0.15
***
1.02
ns
0.00
ns
0.84
ns
0.38
***
0.58
ns
0.00
ns
0.00
ns
***
0.00
ns
0.21 T2C ss (%) 19.79 37.92 3.24 24.07 1.17 0.00 2.86 5.90 1.59 0.00 3.47
*** sig *** *** ** *** * ns ** * ns ns ***
11.29 T2D ss (%) 37.55 26.53 3.13 25.69 0.35 0.00 1.22 3.05 0.29 0.00 2.18
sig *** *** *** *** * ns *** *** ns ns ***
ns= not significant; *: p ≤ 0.05; **: p ≤ 0.01; ***: p≤ 0.001; SS: sum of squares
15
T2E ss (%) 20.30 44.56 1.56 23.49 0.43 0.00 0.55 8.19 0.32 0.00 0.61
sig *** *** *** *** *** ns *** *** * ns ***
3.52 T2F ss (%) 74.08 11.86 6.61 6.51 0.00 0.00 0.32 0.37 0.05 0.00 0.20
*** sig *** *** *** *** Ns Ns Ns Ns ns ns ns
391
Table 2: F significance level and sum square percent of the studied parameters and their interactions effects
392
on physical features of each tomato product.
T F
TP
X T*F T *X
a*/b*
∆E
K
n
0.15 ns 18.73 *** 69.29 *** 9.80 *** 2.02 **
0.01 ns 3.28 *** 63.04 *** 31.44 *** 2.23 **
0.81 ns 97.35 *** 0.13 ns 1.45 ns 0.26 ns
1.79 ns 74.56 *** 15.11 *** 7.37 *** 1.17 ns
sig
23.07 *** 59.57 *** 3.90 *** 12.40 *** 1.06 *
10.43 *** 71.11 *** 2.50 *** 15.71 *** 0.26 ns
9.63 ns 0.00 ns 45.07 ns 0.00 ns 45.29 ns
0.00 ns 0.00 ns 76.09 *** 0.00 ns 23.91 ***
ss (%) sig ss (%) sig ss (%) sig ss (%) sig ss (%) sig
0.01 ns 9.93 *** 19.66 *** 63.92 *** 6.47 ***
3.70 *** 9.02 *** 24.55 *** 57.56 *** 5.17 ***
-
-
ss (%) sig ss (%) sig ss (%) sig ss (%) sig ss (%) sig
T
ss (%)
F
ss (%)
X
ss (%)
T*F
ss (%)
T*X
ss (%)
sig sig
DC
sig sig
T F
TC
X T*F T*X
393 394
ns= not significant; *: p ≤ 0.05; **: p ≤ 0.01; ***: p≤ 0.001; SS: sum of squares
395 396
16
Table 3: F significance level and sum square percent of the studied parameters and their interactions effects on chemical features of each tomato product.1
T F TP
X T*F T *X T F
DC
X T*F T*X
T F TC
X T*F T*X
1
MC 5.2 *** 55.2 *** 38.9 *** 0.3 ns 0.4 ns
aw 4.3 ns 81.3 *** 3.4 ns 1.1 ns 10.0 ns
pH 0.6 ns 40.6 *** 40.1 *** 4.5 * 2.5 ns
D 4.7 ns 24.1 ns 17.0 ns 25.5 ns 28.7 ns
PopA 0.0 ns 66.3 *** 33.3 *** 0.1 ns 0.3 ns
TA 0.4 ns 20.2 ** 74.3 *** 1.1 ns 4.0 ns
TB 15.2 ns 22.8 ns 54.5 ** 3.9 ns 3.7 ns
Pop C 34.5 *** 8.2 *** 43.7 *** 1.7 ** 11.9 ***
Pop D 6.1 *** 28.9 ** 61.5 *** 2.2 *** 1.3 **
Pop E 49.2 *** 16.6 *** 4.3 *** 24.0 *** 5.9 ***
Pop F -
T2C 0.5 *** 21.7 *** 76.9 *** 0.5 *** 0.4 ***
T2D 34.9 *** 14.5 *** 18.7 *** 29.8 *** 2.1 ***
T2E 1.5 ns 10.7 *** 60.0 *** 18.0 *** 9.8 ***
T2F -
55.2 *** 8.7 ns 12.2 ns 20.1 * 3.7 ns
5.3 ns 2.9 ns 11.9 ns 53.1 *** 26.8 ns
1.69 * 78.4 *** 14.78 *** 3.9 * 1.4 ns
22.4 *** 9.8 *** 64.6 *** 0.1 ns 3.2 ***
12.3 *** 48.9 *** 33.4 *** 2.0 *** 3.4 ***
5.9 ** 11.9 *** 41.9 *** 1.3 ns 38.9 ***
5.3 ns 27.9 ** 55.9 *** 4.3 ns 6.8 ns
12.3 *** 2.5 *** 78.4 *** 6.8 *** 0.0 ns
2.7 *** 2.3 *** 94.6 *** 0.3 *** 0.0 ns
0.6 * 4.2 *** 70.9 *** 11.0 *** 13.3 ***
-
4.1 *** 3.0 *** 92.2 *** 0.3 *** 0.3 ***
2.1 *** 1.0 * 89.3 *** 0.8 * 6.7 ***
0.2 ** 2.9 *** 93.8 *** 2.3 *** 0.9 ***
-
5.0 ns 14.5 ns 43.8 ns 17.1 ns 19.6 ns
2.0 ns 42.5 *** 44.5 *** 7.0 ns 4.0 ns
3.7 ns 8.5 ns 53. *** 20.1 ns 14.77 ns
51.8 *** 8.3 *** 38.1 *** 0.83 ns 0.90 *
0.5 * 77.6 *** 16.5 *** 4.0 *** 1.42 ***
5.6 ** 7.3 * 66.4 *** 3.0 ns 17.71 ***
0.5 * 77.6 *** 16.5 *** 4.0 *** 1.42 ***
44.5 *** 33.0 *** 7.9 *** 10.1 *** 4.5 **
53.6 *** 5.8 *** 15.4 *** 16.5 *** 8.7 ***
51.4 *** 2.6 *** 31.7 *** 13.7 *** 0.6 ***
21.6 *** 33.7 *** 7.1 *** 36.7 *** 0.9 *
44.3 *** 6.6 *** 27.9 *** 12.1 *** 9.1 ***
41.8 *** 7.8 *** 40.4 *** 7.6 *** 2.4 ***
53.7 *** 8.0 *** 12.6 *** 17.9 *** 7.8 **
39.5 *** 31.6 *** 26.4 *** 1.8 ns 0.7 ns
ns= not significant; *: p ≤ 0.05; **: p ≤ 0.01; ***: p≤ 0.001; SS: sum of squares
17
Figure 1: Characteristic 1H T2 NMR distributions of relaxation times for (a) tomato pulp STD, F, and X, (b1) double concentrate STD and F, (b2) double concentrate X, (c) triple concentrate STD, F, and X.
Highlights:
•
Potato fiber was tested as a clean label ingredient in different tomato products.
•
Potato fiber performance was compared to xanthan by multivariate statistics.
•
Potato fiber showed a stronger effect on apparent viscosity than xanthan.
•
Potato fiber reduced proton molecular mobility, in contrast with xanthan.
Conflict of Interest and Authorship Conformation Form Please check the following as appropriate:
o
All authors have participated in (a) conception and design, or analysis and interpretation of the data; (b) drafting the article or revising it critically for important intellectual content; and (c) approval of the final version.
o
This manuscript has not been submitted to, nor is under review at, another journal or other publishing venue.
o
The authors have no affiliation with any organization with a direct or indirect financial interest in the subject matter discussed in the manuscript
o
The following authors have affiliations with organizations with direct or indirect financial interest in the subject matter discussed in the manuscript:
Author’s name
Agoura Diantom
Affiliation
Department of Food and Drug, University of Parma &
Ecole Supérieure des Techniques Biologiques et Alimentaires, University of Lomé Fatma Boukid
Department of Food and Drug, University of Parma
Elena Curti
Department of Food and Drug, University of Parma
Eleonora Carini
Department of Food and Drug, University of Parma
Elena Vittadini
Department of Food and Drug, University of Parma & School of Biosciences and Veterinary Medicine, University of Camerino