physical properties of synbiotic yogurts as affected by
TRANSCRIPT
1
Physical properties of synbiotic yogurts as affected by the 1
acidification rate 2
3
4
Paloma Delgado-Fernández1,2
, F. Javier Moreno 1, Nieves Corzo
1, Stefan Nöbel
2,3* 5
6
1Autonomous University of Madrid, Institute of Food Science Research CIAL, (CSIC-UAM) 7
CEI (UAM + CSIC), ES-28049 Madrid, Spain 8
2University of Hohenheim, Institute of Food Science and Biotechnology, DE-70593 Stuttgart, 9
Germany 10
11
*Corresponding author: Tel.: +49 431 609 2264; Fax: +49 431 609 2300. 12
Email address: [email protected] (Stefan Nöbel) 13
3Present address: Max Rubner-Institut, Department of Safety and Quality of Milk and Fish 14
Products, DE-24103 Kiel, Germany 15
2
ABSTRACT 16
Synbiotic yogurts are fermented using a probiotic starter culture and prebiotics, which are 17
claimed to promote health benefits. In previous studies, we have shown that new prebiotic 18
oligosaccharides derived from lactulose (OsLu) are chemically stable during fermentation and 19
cold storage. This study aims to test how physical properties are affected while adding OsLu 20
and lactulose at concentrations reasonable for fermented milks’ consumption (2% and 4%). 66 21
stirred yogurts were produced from skimmed milk (<0.1% fat), as high-heated (95ºC, 256 s) 22
after prebiotic supplementation. Protein content was standardized (4.5 – 5.2%) by skim milk 23
powder (SMP) or total milk protein (TMP). Lactose and maltodextrin served as inert 24
carbohydrate controls. Fermentation was significantly slowed down by OsLu or lactulose, 25
regardless of the concentration, indicating a substrate inhibition. Such gels were softer and 26
resulted in less viscous yogurt. Multivariate analysis revealed a clustering into samples 27
containing either OsLu, lactulose, or the inert carbohydrates with acidification rate being the 28
most prominent feature. 29
30
31
Keywords: stirred synbiotic yogurts, microgel suspension, OsLu, fermentation, rheology 32
3
1 Introduction 33
Functional foods are part of the human diet and are demonstrated to provide health benefits by 34
reducing the risk of chronic diseases (Granato, Branco, Nazzaro, Cruz & Faria, 2010). There 35
is an increasing demand for functional foods related to the modulation of colonic microbiota, 36
being the dairy industry one of the most important sectors. Fermented dairy products, like 37
yogurt and fresh cheese, are frequently consumed because of their high nutritional value, good 38
compatibility and sensorial properties, but also by their ability to exert positive effects on the 39
consumer's health (Das, Choudhary & Thompson-Witrick, 2019). Yogurt is manufactured by 40
microbial acidification of milk using thermophilic lactic acid bacteria (LAB). In the course of 41
fermentation to pH 4.5, the electrostatic repulsion between the casein micelles decreases, 42
causing their aggregation into a homogeneous gel network (Lee & Lucey, 2010). Set-style 43
yogurt is fermented in the retail package while stirred yogurt is subsequently broken into a 44
microgel suspension by mechanical post-processing (Jørgensen et al., 2019; Mokoonlall, 45
Nöbel & Hinrichs, 2016). 46
Synbiotic yogurts constitute an important class of functional foods as combining pro- and 47
prebiotics: probiotics are living microorganisms, which when administered in adequate 48
amounts, confer a health benefit to its host. Lactobacillus delbrueckii ssp. bulgaricus and 49
Streptococcus thermophilus are the most common starters in yogurt production 50
(Papadimitriou et al., 2016), although other probiotics are also used for this purpose, e.g. 51
Lactobacillus acidophilus and Bifidobacterium animalis ssp. lactis, because of their ability to 52
promote functional properties and benefits to the health (da Silva et al., 2017). 53
Prebiotics are non-digestible ingredients that could selectively stimulate the growth or activity 54
of probiotic bacteria in the colon (synergistic effect). The most recent definition includes non-55
carbohydrate substances and other categories rather than food (Gibson et al. 2017). Different 56
types of prebiotics such as galactooligosaccharides (GOS) (Delgado-Fernández, Corzo, 57
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Olano, Hernández-Hernández & Moreno, 2019a; Vénica, Bergamini, Rebechi & Perotti, 58
2015) and lactulose (Delgado-Fernández et al., 2019a; Delgado-Fernández, Corzo, Lizasoain, 59
Olano & Moreno, 2019b; de Souza Oliveira, Rodrigues Florence, Perego, de Oliveira & 60
Converti, 2011) have already been applied in manufacture yogurt and other fermented milks. 61
Lactulose is a disaccharide composed of fructose and galactose, e.g., formed by isomerization 62
of lactose, and it is widely used in food products because of the bifidogenic (prebiotic) effect 63
(Ruszkowski & Witkowski, 2019). In the case of lactic acid fermentation, the effect of 64
lactulose was previously studied by several authors who demonstrated a stimulating effect on 65
the growth of Lactobacillus delbrueckii ssp. bulgaricus (Delgado-Fernández et al., 2019a; 66
Delgado-Fernández, Hernández-Hernández, Olano, Moreno & Corzo, 2019c), bifidobacteria 67
and Lactobacillus acidophilus (de Souza Oliveira et al., 2011; Özer, Akin & Özer, 2005). 68
However, by considering that lactulose could not reach the descendant colon, new lactulose-69
derived oligosaccharides (OsLu) were requested to reach this distal region and modulate the 70
gut microbiota (López-Sanz, Montilla, Moreno & Villamiel, 2015). OsLu are synthetized 71
similarly to GOS using lactulose as the precursor substrate, and their structure are composed 72
for galactoses linked by a variety of glycosidic linkages, such as β(1→6), β(1→1) and/or 73
β(1→4) and a terminal fructose with a degree of polymerization DP ≥ 3 (Diez-Municio et al., 74
2014). . Various in vitro assays using rats demonstrated their resistance to gut digestion 75
because of the presence of terminal fructose in the oligosaccharides composition, as compared 76
to commercial GOS (Ferreira-Lazarte et al., 2017, 2019). In addition, the effect of the 77
potential prebiotic trisaccharides from OsLu on fermentations using pure cultures 78
(Lactobacillus acidophilus LA-5, Streptococcus salivarius ZL50-7 and Bifidobacterium lactis 79
BB12, among other microorganisms) demonstrated that all strains are able to metabolize them 80
at 24 or 48 hours when the saccharides from OsLu are the sole carbon source (Cardelle-Cobas 81
et al. 2012). Besides, their low ileal digestibility was studied in vivo, showing a full resistant 82
to the extreme environment of the upper digestive tract in rats (Hernández-Hernández et al., 83
5
2012). Thus, OsLu could be fermented by gut microbiota slowly than lactulose, without any 84
alteration in their structure, reaching the distal colon where many chronic diseases occurred, 85
such as colorectal cancer. Indeed, Fernández et al. (2018) demonstrated the chemoprotective 86
effect of OsLu, reducing significantly the number of colon tumors in rats. Therefore, oral 87
administration of OsLu could be an interesting strategy for preventing colorectal diseases, as 88
well as, their potential prebiotic effect. In this sense, metagenomics sequencing revealed 89
significant reductions in colon microbiota populations of pro-inflammatory bacteria families 90
and species, and significant increases in interesting beneficial populations, such as 91
Bifidobacterium. These findings are in line with previous reports that showed OsLu to be 92
selective for bifidobacteria and lactic-acid bacteria following several in vitro fermentation 93
studies (Cardelle-Cobas et al., 2008, 2009, 2011, 2012). This bifidogenic effect was also 94
found in growing rats fed 1% (w/w) of OsLu (Hernández-Hernández et al., 2012), together 95
with a significant and selective increase of Bifidobacterium animalis found in the caecum and 96
colon sections (Marín-Manzano et al., 2013). These beneficial properties have sparked the 97
interest, for instance, in the continuous and long term production of OsLu through the 98
efficient immobilization of a commercial enzymatic preparation that exhibited a high stability 99
and performance in reusability (Nguyen et al., 2018).Apart from the oral toxicological studies 100
using OsLu in rats (Anadón et al.,2013), in terms of food applications, OsLu syrup was 101
successfully used in milk and processed apple juice (López-Sanz et al., 2015) as well as in 102
synbiotic yogurts during 28 days of storage (Delgado-Fernández et al., 2019c) and in kefirs 103
(Delgado-Fernández et al., 2019b), showing an excellent stability. However, a deeper 104
understanding into the fermentation rate and physical properties were not considered even 105
though the quality of fermented dairy products is primarily determined by texture perception 106
(Krzeminski et al., 2013). 107
Regarding the strength of the milk protein network, the addition of dairy ingredients, 108
including skim milk powder (SMP) or total milk protein (TMP), was used to enhance the 109
6
functional and textural properties of yogurts (Karam, Gaiani, Hosri, Burgain & Scher, 2013). 110
Apart from these fortified powders, prebiotic supplementation of milks (typically 1 – 5 % 111
(w/w)) prior to fermentation increases solids and potentially affects the acidification rate and 112
the proteolytic activity of LAB because of the increased phase volume and water binding 113
capacity (Mensink et al. 2015). The effect of the prebiotics oligofructose and inulin were 114
extensively investigated with positive (Guggisberg, Cuthbert-Steven, Piccinali, Bütikofer & 115
Eberhard, 2009; Villegas & Costell, 2007) or negative effects (de Castro,Cunha, Barreto, 116
Amboni & Prudêncio, 2009; Cruz et al. 2013; Guven, Yasar, Karaca & Hayaloglu, 2005; 117
Paseephol, Small & Sherkat, 2008) on the microgel structure of yogurts. These studies have 118
mainly focused on the effect on rheological properties of the final products, missing 119
accompanying information related to physico-chemical parameters (dry matter, protein, 120
osmotic pressure) and acidification (lag-phase, rate). Solely for lactulose, de Souza Oliveira et 121
al. (2011) reported the fermentation of LAB, and our group has recently studied its effect on 122
the production of organic acids, microbial composition, lactose, monosaccharides, and 123
prebiotics during fermentation and subsequent refrigerated storage (Delgado-Fernández et al., 124
2019c). 125
In our previous studies, probiotic strains were found to metabolize lactulose along with 126
lactose during fermentation and acidification, respectively (Delgado-Fernández et al., 127
2019a,c). A traditional starter (Lactobacillus delbrueckii ssp. bulgaricus and Streptococcus 128
thermophilus) in co-culture with probiotics (Lactobacillus acidophilus and Bifidobacteria 129
animalis ssp. lactis) was applied in the present work. Synbiotic yogurts were manufactured by 130
adding two levels (2% and 4% (w/w)) of prebiotics (lactulose, OsLu) to study the physical 131
properties of the set gels and the stirred products as influenced by acidification rate. At the 132
same levels, lactose and maltodextrin, and yogurt without added carbohydrates served as 133
controls. Here, the mixtures of carbohydrates along with monosaccharides were expected to 134
specifically affect the fermentation via the starter culture, which cannot be tailored by other 135
7
superimposed measures, i.e. temperature or inoculation level. Furthermore, the effects of 136
prebiotics and compositional changes were discriminated using multiple factor analysis 137
(MFA) in order to identify the key structural parameters in synbiotic yogurts. 138
2 Materials and methods 139
2.1 Composition of milk powders and prebiotics (ing) 140
The milk base was fortified either by low-heat skim milk powder (SMP) (Milchwerke 141
Schwaben eG, Ulm, Germany), with a protein content of 34% and a lactose content of 50 –142
55%, or by total milk protein (TMP) (MILEI Protein GmbH & Co. KG, Leutkirch, 143
Germany), with a protein content of 83.6% and a lactose content of 7.3% according to the 144
manufacturers’ specifications. During the ultrafiltration process in TMP production, the major 145
milk proteins are separated from the serum phase keeping the native casein-to-whey protein 146
ratio of 80:20 constant. The mandatory milk pasteurization and final spray drying step cause 147
the denaturation of approx. 30% of the whey proteins in the same way as for low-heat SMP 148
[eventually, DOI: 10.1080/07373930701370175]. In both cases, the powders’ fat content was 149
below 1.25%. Owing to a large number of experimental parameters and for clarity, 150
abbreviations in the scheme ‘group.parameter’ will be used in the following. As an example, 151
the type of powder used for fortification will be coded as ing.powd = SMP or ing.powd = 152
TMP. 153
As prebiotics (ing.sug), lactulose, trade name ‘Duphalac’ (Abbott Biologicals B.V, Olst, The 154
Netherlands) is composed of 66.7 g lactulose, 11 g galactose, 6 g lactose, and 7.7 g epilactose, 155
tagatose and fructose per 100g of total carbohydrates. Carbohydrate analyses were performed 156
using GC-FID, as described by Montilla, van de Lagemaat, Olano & del Castillo (2006). 157
Oligosaccharides derived from lactulose (OsLu) were synthesized in our research group with 158
Aspergillus Oryzae by transglycosylation of lactulose with a fraction of carbohydrates of 159
8
26.0 g fructose, 15.0 g galactose, 2.4 g glucose, 12.1 g lactulose, 3.4 g lactose and 41.3 g 160
oligosaccharides with different degree of polymerization (18.8 g disaccharides, 16.2 g 161
trisaccharides and 6.3 g tetrasaccharides as synthesized) per 100 g of total carbohydrates. The 162
maltodextrin powder Agenamalt 20.224 (dextrose equivalent DE 12; Agrana Beteiligungs-163
AG, Vienna, Austria) and α-lactose monohydrate (Carl Roth GmbH & Co. KG, Karlsruhe, 164
Germany) served as control carbohydrates. 165
2.2 Sample preparation 166
Milk standardization and pretreatment 2.2.1167
Fresh bovine raw milk was provided from the research station Meiereihof (University 168
Hohenheim, Stuttgart, Germany). In the Dairy for Research and Training (University 169
Hohenheim), the raw milk was pasteurized (74°C, 30 s) and standardized using SMP or TMP 170
to a protein content of 4.92± 0.04% (n = 18) or 5.01 ± 0.15% (n = 21), respectively. After 171
high heating the milk (95ºC, 256 s), it was cooled to 10ºC by using a pilot plant (150L h-1
; 172
Asepto GmbH, Dinkelscherben, Germany) and stored overnight (6°C) at maximum for 3 173
days. 174
Starter culture and fermentation 2.2.2175
For producing synbiotic yogurts a commercial lyophilized starter culture named Lyoflora 176
SYAB 1 (Sacco s.r.l., Cadorago, Italy) composed of Lactobacillus acidophilus, 177
Bifidobacterium animalis ssp. lactis, Streptococcus thermophilus, and Lactobacillus 178
delbrueckii ssp. bulgaricus was used as constitutive microflora at a concentration of 179
1 UC mL-1
. 180
Before fermentation, OsLu, lactulose, maltodextrin, or lactose was added to achieve a final 181
mass fraction (ing.add) of 2% or 4% (w/w) in 450 g of each type of standardized milk 182
(Table 1). A control (ing.add = 0) without adding prebiotics or carbohydrates (ing.sug = 183
9
control) was prepared. These fortified milks were stirred using a lab dispenser (Robomix AU-184
L60; La Nuovagel s.r.l., San Vendemiano, Italy) and preheated to 42ºC. A stock solution of 185
starter culture at 20% (w/v) was prepared by thawing 1.7 g of frozen starter culture in 8.5 mL 186
from the same milk (10ºC). Milks were inoculated with 0.05% starter culture and split in 187
100 mL-glass jars, which were immersed in a water bath (K25-MPC; Huber Kältemaschinen 188
GmbH, Offenburg, Germany) at 42ºC. Temperature and pH were monitored continuously 189
(DAQ Factory Express v16.3; AzeoTech Inc., Ashland, USA) with pH sensors (SE555X/2-190
NMSN; Knick Elektronische Messgeräte GmbH & Co. KG, Berlin, Germany or CPS31; 191
Endress+Hausser GmbH & Co. KG, Gerlingen, Germany) which were previously calibrated. 192
Fermentations were stopped at pH 4.55 (pH.raw.455) by immersing the glass jars during 193
30 min on ice. Samples were stored overnight at 10 °C for mechanical post-processing. All 194
fortified yogurts and accompanying controls were produced at least three times (i ≥ 3) per 195
type of standardization (SMP or TMP). 196
Stirred yogurt production 2.2.3197
Fermented milks in each glass jar of 100 mL were slightly broken with a spoon and the 198
content of three was sheared with a large syringe/piston pump through a nozzle (D = 3 mm, 199
L = 25 mm) at 10ºC. The piston was moved by a universal testing machine (type 5944; 200
Instron, Norwood, USA; load cell: 2 kN) to ensure a constant flow rate of 1200 mL min-1
, 201
which correspond to a shear rate of 7550 s-1
during a 5 s-pass per glass jar (Körzendörfer, 202
Nöbel & Hinrichs, 2017). Stirred yogurts were filled in fresh glass jars and stored at 10°C 203
until further analyses. 204
2.3 Compositional analyses (ing) 205
The total protein content of milk samples (ing.prot) was determined based on the method of 206
Dumas (Anonymous, 2002; IDF 185) using a nitrogen analyzer (Dumatherm DT; C. Gerhardt 207
GmbH & Co. KG, Königswinter, Germany) and with a mid-infrared spectrometer 208
10
(Lactoscope FTIR Advanced; Delta Instruments B.V., Drachten, The Netherlands). The dry 209
matter content (ing.dm) was determined with a gravimetric method by drying at 102ºC 210
(Anonymous, 2010; C 35.3) and, for the osmotic pressure (ing.osmo), the freezing point was 211
measured (milk cryoscope 4250; Advanced Instruments Inc., Norwood, USA). Compositional 212
analyses were performed for raw milk and milk with added powders (SMP and TMP) at least 213
in duplicate. Table 1 summarizes the average composition of all yogurt samples. 214
2.4 Physical characterization 215
Firmness of set gels (pen) 2.4.1216
Penetration tests of all set-style yogurts were carried out with the universal testing machine 217
(Instron; load cell: 50 N) prior to mechanical post-processing, as described in section 2.2.3. A 218
stress-deformation curve was recorded from breaking the middle of the set gel in the glass jar 219
(at 10ºC) with a cylindrical probe (d = 5 mm). The test speed was set to 20 mm min-1
for 45 s. 220
The first maximum force (pen.fMAX) and the initial slope for each type of set-style yogurt 221
(pen.slope) were calculated. The measurement was repeated three times with fresh glass jars. 222
Particle size analysis (lds) 2.4.2223
Particle size distributions of microgel particles (d < 0.5 mm) were determined through static 224
light scattering (LS13320; Beckman Coulter Inc., Miami, USA) as described by Hahn, 225
Sramek, Nöbel & Hinrichs (2012). Briefly, yogurt samples were diluted with demineralized 226
water (6% w/w) and stirred 15 min at 150 rpm. Approximately 1 mL of the sample was added 227
by adjusting the obscuration to 8 – 10% in the instrument dispersion unit. The protein and 228
water refractive index were 1.57 and 1.33, respectively. Data was acquired with LS32 v3.19 229
software. Three successive runs were performed for each sample. The particle size 230
measurement was repeated three times per yogurt, and the parameters arithmetic mean 231
11
(lds.mean), d10,3, d25,3, d50,3, d75,3, d90,3 (lower 10 – 90th percentiles of the volume-weighted 232
distribution; lds.d10 – lds.d90) and its span ((d90,3 − d10,3)/d50,3; lds.span) were calculated. 233
Rheological characterization of stirred yogurt (rheo) 2.4.3234
Oscillatory and rotational measurements were carried out following the optimized conditions 235
of Fysun, Nöbel, Loewen & Hinrichs (2018) and using two stress-controlled rheometers, an 236
AR2000ex (TA Instruments, New Castle, USA) with a concentric cylinder system 237
(di = 28 mm, do = 30 mm, l = 42 mm) and a MCR 301 (Anton Paar GmbH, Ostfildern, 238
Germany) with a similar geometry (di = 25 mm, do = 27 mm, l = 40 mm). The chilled sample 239
(10°C) was gently stirred with a plastic spoon and 16 – 19 g of the sample was loaded to the 240
cup of the concentric cylinder geometry. After the bob was lowered, the sample was 241
equilibrated for 7 min at 10°C. From a time sweep at a constant angular frequency of ω = 10 242
rad s-1
and strain of γ = 0.0025, the storage modulus (G´) was averaged in a 30 s steady-state 243
period (rheo.modulus). After finishing the small deformation test, the flow curve of the same 244
sample was determined by logarithmically increasing the share rate from �̇� = 0.01 to 1000 s-1
245
in 8 min (ten points per decade). Viscosities at low, intermediate and high shear rates of 246
�̇� = 0.1, 50, 631 s-1
(rheo.eta01, rheo.eta50, rheo.eta631), respectively, were extracted as well 247
as the yield stress (rheo.yield), which was taken from a constant shear stress region at low 248
rates (7 data points). Intermediate shear rates, i.e. �̇� = 50 s-1
, correlate with the oral perception 249
of viscosity in fermented milk products (Krzeminski et al., 2013). Each microgel suspension 250
was prepared and analyzed per triplicate. 251
2.5 Statistical analysis 252
At least three productions (i ≥ 3) per formulation were carried out within 11 consecutive 253
weeks using a randomized full factorial design (ing.powd (2 levels) × ing.sug (4 levels) × 254
ing.add (2 levels) and control; Table 1). The date of production (smpl.date) might serve as a 255
blocking factor covering the variability of the natural source milk. n refers to the overall 256
12
number of examined samples and i to the number of independent repetitions of the 257
experiments. 258
All statistical calculations were performed with the R statistic language v3.5.2 (R Foundation 259
for Statistical Computing, Vienna, Austria). Significance levels were set to α = 0.05 or given 260
where appropriate. Nonparametric Mann–Whitney U-tests between two particular groups 261
(control and fortified milks), the univariate analysis of variance (ANOVA), univariate 262
Shapiro–Wilk and multivariate Royston test of normality, and the correlation matrix were 263
covered by R's basic version. Multivariate analyses involving all independent parameters of 264
the experimental design and all physico-chemical properties were conducted by multiple 265
factor analysis (MFA) with R's package FactoMineR v1.41 (Lé, Josse & Husson, 2008). A 266
suitable number of factors was predetermined using R's package nFactors v2.3.3. The 267
complete data set consisting of 66 experiments (rows), 6 independent, and 21 dependent 268
variables (columns) can be accessed as supplementary material. Samples were sorted 269
ascending by the type (ing.sug) and the amount of added carbohydrate (ing.add), and were 270
labeled consecutively. The abbreviations in the supplemented table are identical to the 271
scheme ‘group.parameter’ given in this section. 272
3 Results and discussion 273
3.1 Acidification kinetics of fortified milks 274
All yogurts were manufactured from a standardized milk base (SMP or TMP) with an 275
increased protein content of about 5% as being commonly used for plain and blended yogurt 276
production. Table 1 summarizes the composition of the samples with added carbohydrates. 277
Keeping the protein content constant, the dry matter content was raised from 10.8% and 278
13.1% in the TMP and SMP control, respectively, to a maximum of 15.8% and 17.8% by 279
adding 4% oligosaccharides derived from lactulose (OsLu). Added carbohydrates mainly 280
13
affected the osmotic pressure of the milk base ranging from 0.721 (TMP, control) to 281
1.89 MPa (SMP, 4% OsLu). Samples with maltodextrin served as blanks, which contain the 282
same amount of added carbohydrates but acting (microbiologically) inert for the starter 283
culture. Owing to its high carbohydrate molar mass (dextrose equivalent DE 12), those 284
samples showed osmotic pressures similar to the corresponding controls (Table 1). Additional 285
yogurts were produced from a milk base with lactose at the same levels of added 286
carbohydrates as the oligosaccharide samples (lactulose and OsLu). Thus, the osmotic 287
pressure was in the same range as well (Table 1). 288
Figure 1 shows the acidification kinetics as an example of milks with either an added inert 289
carbohydrates or the oligosaccharides, both in SMP and TMP. Although the same starter 290
culture (Lyoflora SYAB 1) and inoculation ratio were used, a significant shift in the 291
characteristic sigmoid profile was observed. Regardless of the type of standardization, SMP 292
or TMP, the total fermentation time until pH 4.55 (pH.raw.455, supplementary material) 293
was significantly delayed from 245 min (average of all control, maltodextrin, and lactose 294
samples) to 314 and 375 min by adding the oligosaccharides lactulose and OsLu, respectively 295
(Figure 1a and 1c). Previous studies of Delgado-Fernández et al. (2019a) also showed a 296
longer fermentation time (360 min) of yogurt with 4% (w/w) of added lactulose as compared 297
to control (300 min) who used a two strain, S. thermophilus and L. delbrueckii ssp. 298
bulgaricus, starter. However, de Souza Oliveira et al. (2011) observed a higher rate and 299
shorter acidification time in yogurts by adding 4% (w/w) of lactulose (purity of 98%) and 300
using different co-cultures. Different starter cultures or the addition of a commercial mixture 301
of carbohydrates with 67% of lactulose (Duphalac), also containing residual mono- and 302
disaccharides instead of pure lactulose, could explain the different acidification profiles due to 303
highly strain-dependent preferences regarding the carbon source (Kárnyáczki & Csanádi, 304
2017; Schmidt, Mende, Jaros & Rohm, 2016). 305
14
Fermentation in milk with lactulose and OsLu took longer, mainly because of a moderate 306
peak acidification rate (dpH/dt) as calculated by numerical approximation of the first-order 307
derivative of the pH-profile (Figure 1b and 1d). Acidification rate and duration within the 308
lag-phase (pH > 6.2) were not affected (pH.raw.620) by the type of carbohydrate. Two 309
distinct groups of acidification kinetics were identified: control, maltodextrin, and lactose 310
samples showed a steep decline after pH < 6.0 and, in turn, lactulose and OsLu samples 311
without further acceleration of the fermentation. In the following, the acidification rate will be 312
regarded as a major factor that might influence the physical properties of the final yogurts. 313
Since the numerical first-order derivative was sensitive to measurement instabilities and noisy 314
pH-time signals, the data was also modeled using the mathematical Logistic function 315
(sigmoid shape, 4 parameters) for further feature extraction. Fitting the measured pH by such 316
a model equation results in an inherent smoothing of the data and gives the (acidification) rate 317
at the inflection point (pH.log.rate) among other model parameters (pH.log.0, pH.log.inf, 318
pH.log.lag; supplementary material). Figure 1 additionally includes the acidification rates 319
as extracted from the Logistic function. pH.log.rate is attributed to an average acidification 320
rate during the steepest drop in the entire range pH 5.0 – 6.0 as being the critical part of the 321
gel structure formation (Nöbel, Protte, Körzendörfer, Hitzmann & Hinrichs, 2016). Therefore, 322
the absolute values differed from the peak acidification rate during fermentation at around pH 323
5.5, if applicable. 324
3.2 Effect of prebiotics on single physical properties 325
Firmness of acidified gels (pen) 3.2.1326
The firmness all set-type gels was measured post-fermentation by a penetration test, and 327
maximum forces were listed in Table 2. Mann–Whitney U-test at a significance level of 5% 328
was used for comparing samples with different carbohydrates (maltodextrin, lactose, 329
lactulose, and OsLu) to control and, additionally, by subgrouping the data by the type of 330
15
fortification (SMP or TMP) and amount of carbohydrate (2% or 4%). For the same protein 331
content, it can be observed that gels from SMP are softer than those from TMP (P < 0.05), 332
which is in line with previous studies (Karam et al., 2013; Remeuf, Mohammed, Sodini & 333
Tissier, 2003; Sodini, Lucas, Tissier & Corrieu, 2004). In the case of using SMP, the control 334
showed a maximum force of 233 mN, being significantly firmer than gels with OsLu at 4% 335
(134 mN). Acidified gels with OsLu at 4% (194 mN) and lactose at 4% (230 mN) fortified 336
with TMP were significantly softer as compared to control (312 mM) (Table 2). Meletharayil, 337
Patel, Metzger, & Huppertz, (2016) found considerable differences in the firmness of acid 338
milk gels when different protein–lactose ratios were adjusted. Soft and coarse gels were 339
attributed to altered water binding and volume exclusion effects. For prebiotic yogurts, lower 340
firmness was reported by adding 1% of pineapple peel powder and 4% of short 341
(oligofructose), medium, or long-chain inulins (Paseephol et al., 2008; Sah, Vasiljevic, 342
McKechnie & Donkor, 2016). 343
Microgel particles in stirred yogurt (lds) 3.2.2344
Changes of the 10th- to 90th-percentiles and the arithmetic mean from the volume-weighted 345
particle size distribution are shown in Table 2. 3 In the presence of OsLu, microgel particles 346
were always smaller with a narrow distribution, and less pronounced for lactulose at the 347
highest level of 4% (P ≤ 0.05). Figure 2 illustrates the percentiles of small (d10,3), median 348
(d50,3), and large particles (d90,3) as normalized to the corresponding controls. In the case of 349
SMP, a clear difference in particle size was observed between yogurts with OsLu and 350
lactulose, at the one side, and maltodextrin and lactose, on the other side (all at 4%) (Figure 351
2a). For TMP, containing already less lactose in control, a decrease in particle size (P ≤ 0.05) 352
also occurred by adding 4% lactose (Figure 2b). Thus, a weak gel structure was achieved by 353
the addition of OsLu and lactulose, which enhanced the breakdown of the microgel particles 354
16
(Table 2) and, as a consequence, promoted the formation of smaller particles as compared to 355
control. 356
Rheological characterization of stirred yogurt (rheo) 3.2.3357
Small amplitude oscillatory tests were carried out to establish the viscoelastic properties of the 358
stirred yogurt samples. In yogurts with SMP, the storage modulus (G´) ranged from 116 to 359
266 Pa, being significantly lower in the case of yogurts with added lactulose and OsLu at 4% 360
(Table 3). Although lower storage moduli were observed for OsLu and lactulose at 4% again, 361
no significant influence was detected in the case of TMP, mainly due to an overall increase of 362
the measurement variation. A decrease of the storage modulus by the use of the prebiotics at 363
high doses should be noticed, which is a characteristic of weak gels as corroborated by the 364
set-gel firmness (Table 2). Cruz et al. (2013) and Paseephol et al. (2008) also reported on low 365
moduli of yogurts with oligofructose and inulin, respectively. 366
Figure 3 presents the flow curves of control and selected yogurts with OsLu and lactulose in 367
SMP (Figure 3a) and TMP milk base (Figure 3b). All yogurts showed yielding and shear-368
thinning flow behavior regardless of the fortification or the oligosaccharide used. In general, 369
the addition of prebiotics resulted in lower shear stresses at low shear rates (<10 s-1
) or, in the 370
case of 4% OsLu, shifted the entire flow curve towards lower shear stress as being equal to a 371
reduced overall viscosity. Besides, the transition region from linear viscoelastic to non-linear 372
behavior was characterized precisely by the yield point where the rupture of microgel 373
particles and their continuous break-down due to shear was expected (Fysun et al., 2018; 374
Mokoonlall et al., 2016). The yield point and several low- and high-shear apparent viscosities 375
were extracted for all yogurt samples (Table 3). Lowest yield points were observed in yogurts 376
with OsLu and lactulose at 4% fortified with SMP. In the case of TMP, lactose and lactulose 377
at 4% were different from control. The effect of OsLu at 4% was not significant despite a 378
marked decrease. Hence, significant differences were observed in yogurts with SMP and TMP 379
17
at lowest viscosities (0.1 s-1
) as well (Table 3). Apparent viscosities decreased in all yogurts 380
with an increase in shear rate. Soft particles’ internal structure is mainly affecting low shear 381
viscosities, where relaxation times are dominant (Deborah number). Regarding all shear rates, 382
OsLu at 4% showed lower viscosities as compared to control. These results are in contrast to 383
TMP, in which the addition of OsLu did not significantly affect any apparent viscosity 384
(p = 0.0571 vs. p = 0.0201 in Mann–Whitney U-test and two-sample t-test, respectively). Test 385
differences were attributed to the robustness of the U-test which was applied since parametric 386
tests’ requirements for normality were not met a priori. Cruz et al. (2013) and Villegas & 387
Costell, (2007) reported a general increase in the apparent viscosity at shear rates of 10, 50, 388
and 100 s-1
by adding oligofructose (2 – 8%) and inulin (2 – 10%) without further heating. 389
Contrastingly, de Castro et al. (2009) found a decrease in the viscosity (50 s-1
) in yogurts with 390
added oligofructose at 2% and 5%. According to Villegas & Costell, (2007), the viscosity 391
increased with oligosaccharide content when long-chain prebiotics (degree of polymerization 392
DP > 10) were used. Further effects, i.e. on the bulk viscosity in comparison with the strength 393
of the gel network, were not discussed in the literature. Thus, OsLu (DP = 6) and other 394
carbohydrates are considered as short-chain prebiotics, which could explain the reduced 395
apparent viscosities obtained in this study. In summary, the rheological properties of the 396
stirred milk gel are slightly affected by the type and amount of carbohydrates, generally 397
forming softer particles during fermentation. No clear trend was observed except for the 398
dominant impact of OsLu resulting in softer acidified gels, smaller microgel particles, and low 399
viscous stirred yogurts. Therefore, correlation and multivariate analyses will be described in 400
the following sections in order to investigate possible links between the multiple parameters 401
and composition. 402
18
3.3 Multivariate analysis of structural parameters 403
Correlation of all physical properties 3.3.1404
Structural parameters were extracted and grouped according to pH measurement and 405
modeling (pH), penetration test (pen), laser diffraction spectroscopy (lds), and rheology (rheo) 406
in order to identify correlations between all dependent variables (supplementary material). 407
Figure S1 shows the Pearson correlation coefficients and their significances (P < 0.05) as 408
presented as correlation matrix for all stirred yogurts regardless of added carbohydrates and 409
standardization, as those from an altered composition were considered as non-continuous and 410
independent variables. High correlations were found within groups with similar physical 411
meaning (intra-group), i.e., lds.d10 – lds.d90 (absolute particle sizes, r ≥ 0.976) and 412
rheo.eta01 – rheo.eta631 (apparent viscosities, r ≥ 0.611). Beyond their group (inter-group), 413
pH.raw.455 (fermentation duration) was moderately negative correlated (r ≤ -0.438) with 414
almost all other parameters, and, in turn, pH.log.rate (acidification rate) always showed 415
moderate positive relations (r ≥ 0.252) except for lds.span (r = 0.153, p = 0.221). As an 416
example, a prolonged fermentation and slow acidification were linked to lower gel firmness 417
(pen.fMAX, P < 0.001), softer particles (lds.d10 – lds.d90, P < 0.001) and lower viscosities 418
(rheo.eta01 – rheo.eta631, P < 0.05) of the yogurt samples (section 3.2.3). Additional 419
correlations of about r ≥ 0.660 and r ≥ 0.534 were calculated between pen.fMAX and the 420
particle sizes (lds) or the rheological parameters (rheo), respectively, as not necessarily being 421
related from a microstructural point of view, like pen.fMAX with lds.span. Besides, 422
pH.raw.start and pH.log.inf were considered random and might be omitted for further 423
analyses without losing information. The correlation matrix is consistent with and 424
corroborates the results obtained in previous sections. Although no clear assignment between 425
dependent measurement parameters and the use of different prebiotics, dose, and type of 426
fortification can be established. 427
19
Multiple factor analysis 3.3.2428
Factorial analysis was applied to distinguish the most relevant physical and fermentation 429
properties and the related ingredients parameters out of multiple variables (Figure S1) and 430
map them to a significantly lower number of dimensions. Those dimensions, factors, or so-431
called principal components in the case of PCA contain the most important information but 432
can be reliably interpreted (Pagés, 2015). Several antagonistic criteria were proposed to 433
determine the appropriate number of factors: Figure S2 shows the scree plot from all 434
dependent parameters for all yogurt samples, where additionally Horn's (parallel analysis of 435
random data, n = 3) and Kaiser's criterion (eigenvalue λ > 1, n = 4) were marked. Horn's 436
criterion was further used in this study and retained the first three dimensions (n = 3). 437
Multiple factor analysis (MFA) was applied subsequently to correlate structural parameters 438
(pH, pen, lds, rheo) and the yogurt composition (ing), especially with the type and amount of 439
carbohydrates. Here, MFA was used because of its mixed design including quantitative and 440
qualitative parameters structured into groups (Lé et al., 2008; Pagés, 2015). An alternate 441
linear discriminant analysis (LDA) was discarded as the basic clusters were unknown a priori. 442
For instance, the added carbohydrate content (ing.add) was not necessarily the sole and main 443
driving effect on all physical parameters of the yogurt samples as demonstrated in the case of 444
fortification with SMP and TMP (Table 2 and 3, section 3.2). The pH profiles (Figure 1) and 445
the correlation matrix (Figure S1) already indicated that parameters are interrelated, and some 446
arise via fermentation (pH.log.rate, pH.raw.455) from multiple factors such as type (ing.sug) 447
and amount of carbohydrates (ing.add). 448
Table 4 lists the correlation coefficient and contribution of all 21 dependent and 6 449
independent parameters, from which 4 were of qualitative nature, in constructing the three 450
factors by multiple factor analysis. The first factor was capable to explain 56.6% of the 451
variance, 17.8% by the second, and 14.9% by the third factor (89.2% in total). Higher 452
20
dimensions were rejected by the Horn criterion (Figure S2). Focusing on the most 453
contributing parameters, the particle sizes lds.d10 − lds.d75 were positively loaded on the first 454
factor (r ≥ 0.904), and the parameters lds.span and pH.log.0 and pH.log.inf on the second 455
factor. From pH modeling features, the second dimension was also negatively correlated to 456
the parameter pH.log.lag, whereas the third factor was so to pH.raw.start. Interestingly, the 457
acidification rate (pH.log.rate) was positively and strongly correlated to the third factor 458
(r = 0.979), which was also positively correlated to the type of added carbohydrates (ing.sug). 459
pH.log.rate and ing.sug also contributed to the first and second factor but to a smaller extent. 460
Some physical parameters with a similar meaning showed the same correlation but a different 461
contribution to the construction of the factors (Table 4). Hence, at least one parameter of each 462
measurement subgroup was chosen for further processing. These parameters in the reduced 463
data set should be either unique or highly contributing to the construction of the factors. 464
Namely, pH.raw.455, pH.raw.620, pH.log.lag, pH.log.rate, pen.fMAX, lds.mean, lds.span, 465
rheo.modulus, rheo.yield remained from pH, firmness, particle size, and rheological 466
measurements, respectively, as well as all independent compositional parameters (ing), which 467
were not used in the construction of the factorial analysis. Additionally, lds.span was 468
transformed by logarithmic scaling (lds.span.LN) to reduce asymmetry and avoid outliers 469
(box plot not shown) without eliminating individual observations. Subsequently, the reduced 470
and standardized data set complies with the assumption of univariate normality for each 471
parameter (Shapiro–Wilk test, P > 0.01) and multivariate normality (Royston test, p = 0.052). 472
Results from the MFA of the reduced data set revealed that the factors explained 84.8% of the 473
total variance, with the proportions 51.3%, 19.2%, and 14.3% dedicated to first, second, and 474
third dimension, respectively (Figure 4). The total explained inertia was slightly decreased 475
compared to the analysis of the full data set (Table 4). A renewed determination of the 476
appropriate number of factors using Horn’s criterion confirmed that three factors were still 477
21
adequate (data not shown). All parameters remaining were well represented with this 478
(correlation coefficients r > 0.6). 479
Interpreting the first factor in terms of the dependent measures, mainly the parameters which 480
are involved in microgel break-up during shearing were highly correlated, e.g., lds.mean 481
(r1 = 0.921, P < 0.001), rheo.yield (r1 = 0.898, P < 0.001) and pen.fMAX (r1 = 0.842, 482
P < 0.001): stiff gels (pen.fMAX) were hard to disrupt and resulted in coarse microgel 483
suspensions with large fragments (lds.mean). Such rough particles showed an increased initial 484
resistance to flow (rheo.yield). The supplemented compositional parameters were (negatively) 485
correlated to the first factor with osmotic pressure (ing.osmo) being the most representative 486
(r1 = -0.840, P < 0.001) from this group. Consequently, the first factor is referred to as the gel 487
firmness dimension. The direction and extent of the effects of pen.fMAX, rheo.modulus, 488
rheo.yield, and lds.mean were superimposed on slight changes in protein content (ing.prot; 489
Figure 4a, quadrant I) as well as the type of added carbohydrate (ing.sug) and the 490
acidification rate (pH.log.rate). All of them might affect the physical properties separately or 491
by a cause-and-effect chain. 492
The second factor was constructed from the duration of the initial lag-phase during 493
fermentation and the heterogeneity of the microgel particle size distribution as attributed to 494
pH.log.lag (r2 = -0.745, P <0.001) and lds.span.LN (r2 = 0.614, P < 0.001), respectively; more 495
prominent than their contributions to the first factor. From supplemented and qualitative 496
parameters the type of protein standardization (ing.powd) was moderately correlated 497
(r2 = 0.300, P < 0.001). Both, either SMP or TMP fortification, were poles of the second 498
dimension’s axis (Figure 4b). Although other parameters were also related, the second factor 499
predominately discriminated against the protein standardization, within samples of similar gel 500
firmness (as grouped by the first factor), by their delayed lag-phase. 501
The third factor exclusively represented the acidification rate (pH.log.rate; r3 = 0.992, 502
P < 0.001) and the type of added carbohydrate (ing.sug; r3 = 0.656, P < 0.001). No further 503
22
parameter contributed to the construction of this factor that, hence, is referred to as the 504
acidification rate dimension (Figure 4b). Regarding the supplemented compositional 505
parameters, the third dimension also distinguished between lactulose and all samples from 506
other carbohydrates, including OsLu. Hence, the acidification rate was affected by each 507
oligosaccharide whereby lactulose resulted in medium rates and, additionally, OsLu in a 508
longer overall fermentation time (section 3.1). 509
In summary, a high osmotic pressure (ing.osmo) relates to slower acidification (pH.log.rate), a 510
prolonged lag phase (pH.raw.620), and, to a minor extent, to a longer overall fermentation 511
time (pH.raw.455). Osmotic pressure was raised either by an overall increase in dry matter 512
content or, specifically, by adding OsLu as a prebiotic owing to its residual monosaccharides 513
(Table 1). The lag phase, as extracted by Logistic function modeling (pH.log.lag), was 514
unrelated to most of the other parameters, also pH.raw.620. Thus, pH.raw.620 is regarded as 515
arbitrarily chosen, with pH 6.00 or pH 6.10 being other candidates (Figure 1b and 1d), which 516
was not a universal and reliable indicator or feature in order to characterize the lagging of the 517
starter culture during fermentation. pH.log.lag from the Logistic model does suitably fit the 518
sigmoidal shape and gives a better impression of the steep decline’s onset in pH profile. 519
It should be noted that the amount of added carbohydrates (ing.add; levels 2% and 4% (w/w)) 520
had a minor effect on all dimensions (Figure 4; r ≤ 0.296). Adding carbohydrates induced 521
like an on-off effect for most of the parameters studied corroborating an indirect influence of 522
the oligosaccharides via the starter culture that altered the acidification rate and, finally, 523
resulted in different physical properties of the gel network. A direct effect of the 524
carbohydrates on serum viscosity (outer phase of the microgel suspension) would be more 525
dose-dependent. In contrast, a high osmotic pressure (ing.osmo) at high dry matter content 526
(ing.dm) interpreted as non-protein dry matter content, also resulted in reduced physical 527
properties (Figure 4a, quadrant III). 528
23
Hierarchical clustering by acidification rate 3.3.3529
From MFA, the synbiotic yogurts can be discriminated by their gel firmness (dimension 1), 530
lag-phase at the beginning of fermentation (dimension 2), or acidification rate at pH < 6.0 531
(dimension 3). Subsequently, hierarchical clustering (Ward's method; Pagés, 2015) according 532
to those features was applied to map all individual samples regardless of the added 533
carbohydrates or standardization, and to take the variability of independent repetitions into 534
account. Figure 5 shows three clusters as clearly defined by a steep decrease of the inertia 535
from the first to the second branch (2.68), and from the second to third branch (1.29). 536
Distinguishing between more branches resulted in a poor inertia gain (<0.5). Two major 537
density clusters were already obvious by mapping the individual samples to the first and 538
second factor of the MFA (Figure 5, inset subfigure) whereas an additional cluster was 539
accounted for the third dimension. Drawing on this classification, the effect of the 540
carbohydrates was divided into two major influences concerning the acidification rate and the 541
lag-phase of fermentation: (a) adding OsLu particularly delayed the fermentation at a 542
shortened lag-phase (cluster 1 vs. 2 + 3), and (b) lactulose resembles the control 543
carbohydrates with minor differences in the acidification rate (cluster 2 vs. 3). 544
Cluster 1 and cluster 2 discriminated between samples with added oligosaccharides and 545
samples in cluster 3 (control, lactose, maltodextrin), which served as references (Figure 5). 546
Yogurt samples with OsLu were exclusively represented in cluster 1, while lactulose was 547
overrepresented in cluster 2 (14 of 15 experiments). The most typical experiment (center) of 548
cluster 1 was sample OsLu.2 with added OsLu at 2% and fortified with SMP (supplementary 549
material). Samples in cluster 1 had smaller particles (lds.mean) and lower gel firmness 550
(pen.fMAX, rheo.modulus, rheo.yield), at least significantly lower than the overall average 551
(P < 0.001). The sample Lactulose.2 (SMP, 2% lactulose) was the center of cluster 2, which 552
had no significant differences in all physical parameters as compared to overall averages 553
24
(P > 0.05) expect of the intermediate acidification rate (factor 3). Cluster 3 pooled all 554
remaining samples with Lactose.3, Maltodextrin.1, and Control.1 being the most typical 555
experiments. This cluster was composed of samples that have the highest parameters of 556
lds.mean, rheo.yield, and rheo.modulus (P < 0.001) regardless of the dry matter content or 557
type of fortification (P > 0.05). 558
A general gain of rheological parameters was usually reported owing to increased dry matter 559
or protein content as often associated with negatively perceived textural attributes, i.e., 560
graininess and lumpiness (Jørgensen et al., 2019; Karam et al., 2013). In our study, the gel 561
structure was mainly affected via the acidification rate, which has not been investigated by 562
most of the authors in the context of prebiotic yogurts (Cruz et al., 2013; Paseephol et al., 563
2008). Applying the same starter culture or chemical agent, i.e. glucono-δ-lactone (GDL), 564
acidification rate was increased by raised temperature or inoculation rate/concentration, and 565
source of milk with a varying buffering capacity (Jacob, Nöbel, Jaros & Rohm, 2011; Kristo, 566
Biliaderis & Tzanetakis, 2003; Lee & Lucey, 2004; Medeiros, Souza & Correia, 2015). Most 567
factors superimpose the rate-driven acidification mechanism, e.g., due to altered hydrophobic 568
and electrostatic interactions (Lee & Lucey, 2010), or exopolysaccharide production (EPS) 569
(Schmidt et al., 2016). For microbiological acidification, two effects which cannot be 570
distinguished at the moment might be responsible for the slow fermentation and soft gels: (a) 571
too much substrate (any carbohydrate) slowed down the lactic acid synthesis and milk 572
acidification (Figure 1) because of increasing osmotic stress (Chandan & Kilara, 2013; 573
Papadimitriou et al. 2016). The starter culture appeared to be progressively inhibited by 574
substrate, particularly due to some (low molecular) carbohydrates from OsLu (cluster 1) and, 575
to a minor extent, from lactulose (cluster 2). These oligosaccharide samples always showed 576
the lowest acidification rates (Figure 5) regardless of the osmotic pressure, as adjusted by 577
SMP and TMP (section 3.2.1). Applying GDL, higher rates controversially resulted in stiffer 578
(Moussier, Huc-Mathis, Michon & Bosc, 2019) as well as softer acidified milk gels (Jacob et 579
25
al., 2011) depending on the absolute GDL mass fraction range of 0.5 – 1.5% and 3 – 7%, 580
respectively. Moussier et al. (2019) also found that at medium acidification rates and final pH 581
of around 4.5, as close to lactic acid fermentation, additional GDL increased the initial 582
firmness of brittle gels, which tend to collapse subsequently. Thus, low gel firmness, small 583
microgel particles and low apparent viscosity of our yogurt samples prepared from OsLu and 584
lactulose could result from lower acidification rates (Horne, 1999) as caused by an inhibited 585
fermentation. Although no significant shift in the two strain ratio was observed right after 586
fermentation in a previous study (Delgado-Fernández et al., 2019a); or (b) any carbohydrate 587
as solved in the serum phase of milk increased the bulk viscosity (section 3.2.3). Hence, 588
energy transport during shearing, especially stirring the yogurt, will be enhanced and 589
produces smaller particles (Mokoonlall et al., 2016). The theoretic viscosity increment of milk 590
serum at 42°C is a maximum of 7.9% by adding 4% (w/w) of OsLu (13.3% total 591
carbohydrates; Table 1) as slightly depending on its molar mass and conformation 592
(Longinotti & Corti, 2008). Körzendörfer et al. (2017) measured the viscosity of yogurt in the 593
course of fermentation as influence by EPS segregation of the starter culture. Despite distinct 594
differences in the bulk viscosity (>25% at pH 4.6), the serum viscosity was raised only about 595
4.3% by a high-EPS starter. A further increase in serums’ carbohydrate content might 596
improve the firmness of acidified milk gels by hydration effects, which counteracts the 597
enhanced shear-induced break down (Schorsch, Wilkins, Jones & Norton, 2001). Thus, lower 598
rheological parameters of OsLu and lactulose samples were physically driven and not 599
necessarily linked to the acidification rate. 600
4 Conclusion 601
This work firstly describes both the production of synbiotic yogurts with prebiotics and the 602
possible impact on their microgel structure. Our findings revealed the successful 603
incorporation of a new prebiotic (OsLu) but showed slower acidification and reduced physical 604
26
properties of this stirred yogurt. Acidification rate was the most prominent fermentation 605
parameter and clustered samples with oligosaccharides (lactulose, OsLu), on the one hand, 606
and with inert carbohydrates (lactose, maltodextrin), on the other hand. Oligosaccharides are 607
most likely proposed to inhibit the lactic acid fermentation regardless of the concentration. 608
Adding 2% (w/w) OsLu resulted in an average loss of 25% and 15% in set gel firmness and 609
yogurt viscosity, respectively, accompanied by a 37% decrease of the largest microgel 610
particles’ size. Both effects will compensate each other and virtually increase the creaminess 611
perception by about 14% as predicted according to Krzeminski et al. (2013). Above 2% (w/w) 612
the viscosity was further decreased and, thus, creaminess gets lower again. Hence, 613
oligosaccharides addition has to be balanced between a reasonable impact on yogurt texture 614
and its nutritional recommendation, most probably in the range of 2 – 4% (w/w). 615
Since marked differences of the rheological properties occurred with OsLu, further studies 616
regarding the bacterial cell counts of traditional cultures (Lactobacillus delbrueckii ssp. 617
bulgaricus and Streptococcus thermophilus) and probiotics along with the production of 618
exopolysaccharides (EPS) during fermentation process are needed. The analysis of the serum 619
phase after fermentation should be considered to discard an increase in the bulk viscosity due 620
to the carbohydrates. Besides, the sensory quality of yogurts with added new prebiotic should 621
be assessed. Factors such as color, sweetness, viscosity, aroma, and creaminess need to be 622
evaluated to observe possible differences in the mouth-feel of the costumers. 623
Acknowledgments 624
This work was supported by the Spanish Danone Institute and Spanish Ministry of Economy, 625
Industry and Competitiveness (project AGL2017-84614-C2-1-R). Paloma Delgado-Fernández 626
thanks her contract from Spanish Danone, as well as the scholarship from German Academic 627
Exchange Device (DAAD). Oligosaccharides derived from lactulose (OsLu) and Lyoflora 628
SYAB 1 yogurt starter cultures were kindly provided by L. C. Julio-González from Institute 629
27
of Food Science Research (CIAL, Madrid, Spain) and optiferm GmbH (Oy-Mittelberg, 630
Germany), respectively. 631
28
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776–781. https://doi.org/10.1016/j.idairyj.2006.09.007 816
36
Table captions 817
Table 1: Compositional analysis of milk fortified with skim milk powder (SMP) and total 818
milk protein (TMP) for producing yogurt; averages and standard errors calculated from i ≥ 3, 819
n ≥ 9 820
821
Table 2: Gel firmness and microgel particle size of yogurts fortified with skim milk powder 822
(SMP) and total milk protein (TMP); averages and standard errors calculated from i ≥ 3, n ≥ 6 823
824
Table 3: Rheological parameters of synbiotic yogurts fortified with skim milk powder (SMP) 825
and total milk powder (TMP) at 𝜗 = 10ºC; averages and standard errors calculated from i ≥ 3, 826
n ≥ 9 827
828
Table 4: Correlation of the first, second and third factor from multiple factor analysis (MFA) 829
of all dependent parameters (n = 66) 830
831
832
Figure captions 833
Figure 1: pH value (left) and acidification rate (right) during fermentation of yogurts fortified 834
with skim milk powder (SMP; top) and total milk protein (TMP; bottom) at 42°C; open 835
diamond: control without added carbohydrates; circle: added maltodextrin, square: added 836
lactulose, triangle: added OsLu at a mass fraction of 4%; average points and standard errors 837
calculated from i ≥ 3, n ≥ 3; dashed lines: acidification rate parameter as estimated from 838
Logistic pH model (supplementary material) 839
840
37
Figure 2: Normalized percentiles from laser diffraction of yogurts fortified with skim milk 841
powder (SMP) and total milk protein (TMP) and added carbohydrates lactose, maltodextrin 842
(MD), lactulose and OsLu at mass fractions of 2% and 4%; * samples differ significantly 843
from control (P < 0.05); average bars and standard errors calculated from i ≥ 3, n ≥ 6 844
845
Figure 3: Shear stress of stirred yogurts fortified with skim milk powder (SMP) and total 846
milk protein (TMP) as a function of shear rate at 10°C; open diamond: control without added 847
carbohydrates; square: added lactulose, triangle: added OsLu, at mass fractions of 2% (open 848
symbols) and 4% (closed symbols); average points and standard errors calculated from i ≥ 3, 849
n ≥ 6 850
851
Figure 4: Correlation of the first and second factor (a) and second and third factor (b) from 852
multiple factor analysis (MFA) of the reduced data set; italic print: qualitative parameters' 853
correlations in quadrant I, dashed vector: supplementary parameters, parentheses: proportion 854
of the variance explained by each factor 855
856
Figure 5: Hierarchical clustering dendrogram (Euclidean distance, Ward's method) of all 857
individual trials (n = 66) cut at three levels and their representation as factor map (inset 858
subfigure); open diamond: control without added carbohydrates; circle: added maltodextrin, 859
triangle up: added lactose, square: added lactulose, triangle down: added OsLu; parentheses: 860
four most significant (P < 0.001) parameters contributing to the clustering, labels referring to 861
sample codes in the supplementary table 862
38
Supplementary Material 863
Supplementary table: Complete data set consisting of 66 experiments (rows), 6 independent, 864
and 21 dependent variables (columns) as named according to the scheme ‘group.parameter’; 865
R script used to perform the multiple factor analysis (MFA) and hierarchical clustering is 866
included 867
868
Figure S1: Correlation matrix of all dependent parameters extracted from pH measurement 869
and modelling (pH), penetration tests of set-style gels (pen), laser diffraction spectroscopy 870
(lds) and rheology (rheo) of all stirred yoghurt samples; Pearson coefficient of correlation 871
determined by linear regression, insignificant correlations are crossed out red (P > 0.05); bold 872
print: parameters remaining for the reduced data set 873
874
Figure S2: Scree plot of all factors derived from the dependent parameters; circle: observed 875
eigenvalues, square: eigenvalues from Horn's parallel analysis of uncorrelated random data; 876
Horn criterion: observed eigenvalue > random eigenvalue, Kaiser criterion: observed 877
eigenvalue > 1 878
879
880
881
882
883
884
885
886
887
39
Table 1: Compositional analysis of milk fortified with skim milk powder (SMP) and total milk protein (TMP) for producing yogurt; averages and 888
standard errors calculated from i ≥ 3, n ≥ 9 889
Added sugar
Amount
Composition analysis Physical analysis
Fortified with Protein
b Dry matter
c
Total of
carbohydratesd
Osmotic pressure
– – % (w/w) % (w/w)
% (w/w) % (w/w) MPa
SMP
Control
– 5.01 ± 0.18a
13.1 ± 0.1 8.09 ± 0.13 1.05 ± 0.01
Maltodextrin 2.0
2.0
2.0
2.0
4.85 ± 0.12 14.6± 0.1 9.75 ± 0.09 1.09 ± 0.04
Lactose 4.91 ± 0.13 14.6 ± 0.1 9.69 ± 0.11 1.22 ± 0.09
Lactulose 4.79 ± 0.06 14.5 ± 0.1 9.71 ± 0.10 1.24 ± 0.01
OsLue 4.70 ± 0.09 15.7 ± 0.1 11.0 ± 0.10 1.43 ± 0.02
Maltodextrin 4.0 4.72 ± 0.19 15.5 ± 0.9 10.8 ± 0.90 1.12 ± 0.01
Lactose 4.0 4.75 ± 0.09 15.6 ± 0.6 10.9 ± 0.60 1.34 ± 0.08
Lactulose 4.0 4.67 ± 0.11 15.8 ± 0.1 11.1 ± 0.10 1.44 ± 0.07
OsLue 4.0 4.52 ± 0.09 17.8 ± 0.1 13.3 ± 0.10 1.89 ± 0.05
TMP
Control – 5.18 ± 0.26a
10.8 ± 0.3 5.62 ± 0.31 0.721 ± 0.016
Maltodextrin 2.0 4.82 ± 0.10 12.4 ± 0.1 7.58 ± 0.11 0.772 ± 0.012
Lactose 2.0 4.88 ± 0.13 12.3 ± 0.1 7.42 ± 0.11 0.895 ± 0.020
Lactulose 2.0 4.98 ± 0.20 12.3 ± 0.3 7.32 ± 0.28 0.909 ± 0.017
OsLue 2.0 4.89 ± 0.25 13.4 ± 0.2 8.51 ± 0.20 1.07 ± 0.01
Maltodextrin 4.0 5.04 ± 0.11 14.1 ± 0.3 9.06 ± 0.25 0.805± 0.007
Lactose 4.0 4.86 ± 0.16 13.5 ± 0.7 8.64 ± 0.66 1.02 ± 0.07
Lactulose 4.0 4.85 ± 0.19 13.8 ± 0.2 8.95 ± 0.16 1.08 ± 0.05
OsLue 4.0 4.66 ± 0.19 15.8 ± 0.3 11.1 ± 0.30 1.44 ± 0.04
890 a Protein content of the liquid milk base was adjusted to 4.92 ± 0.04 % (SMP) and 5.01 ± 0.15 % (TMP) prior to adding carbohydrates (control) as measured by mid-infrared 891
spectroscopy (FTIR). Targeted protein content was 5%. 892 b Protein content of the liquid milk was analyzed by Dumas method (Anonymous, 2002; IDF 185) after adding sugars 893
c Dry matter content of the liquid milk base was analyzed by a gravimetric method (Anonymous, 2010; C 35.3) after adding sugars 894
d Total of all carbohydrates: native milk lactose, lactose from SMP or TMP, and from added sugars (calculated) 895
e Oligosaccharides derived from Lactulose (OsLu) 896
40
Table 2: Gel firmness and microgel particle size of yogurts fortified with skim milk powder (SMP) and total milk protein (TMP); averages and 897
standard errors calculated from i ≥ 3, n ≥ 6 898
Fortified with
Added sugar
Amount Penetration
testb
Laser diffractionb
Fmax �̅�c d10,3 d25,3 d50,3 d75,3 d90,3
– – % mN µm µm µm µm µm µm
SMP
Control
– 233 ± 23 34.9 ± 2.0 12.8 ± 0.6 19.2 ±1.3 29.9 ±1.7 41.8 ± 2.4 55.3 ±3.7
Maltodextrin 2.0
2.0
2.0
2.0
229 ± 32 34.1 ± 1.3 13.2 ± 0.6 20.6 ± 0.9 31.3 ± 1.1 43.5 ± 1.6 57.7 ± 2.2
Lactose 204 ± 10 34.0 ± 1.6 13.2 ± 0.5 19.9 ± 0.9 30.3 ± 1.1 42.2 ± 1.6 56.9 ± 2.8
Lactulose 210 ± 26 28.8 ± 2.5 11.8 ± 0.6 17.1 ± 1.3 26.8 ± 2.1 37.2 ± 2.9 48.6 ± 4.4
OsLua
177 ± 13 21.7 ± 0.9* 9.54 ± 0.38* 13.1± 0.5* 19.4 ± 0.8* 27.9 ± 1.0* 35.5 ± 1.3*
Maltodextrin 4.0 237 ± 37 31.0 ± 4.4 12.1 ± 0.8 18.2 ± 2.1 28.4 ± 3.5 40.0 ± 5.4 53.0 ± 8.5
Lactose 4.0 221 ± 36 29.5 ± 5.4 12.0 ± 1.6 17.8 ± 3.0 27.3 ± 4.8 37.9 ± 6.5 49.8 ± 10.7
Lactulose 4.0 183 ± 33 20.9 ± 2.0* 9.37 ± 0.67* 12.8 ± 1.1* 18.8 ± 2.0* 27.4 ± 2.6* 35.0 ± 3.7*
OsLua 4.0 134 ± 43* 15.4 ± 1.0* 7.36 ± 0.38* 9.94 ± 0.57* 13.9 ± 0.8* 19.6 ± 1.4* 26.2 ± 1.7*
TMP
Control – 312 ± 27 46.4 ± 3.7 16.4 ± 0.7 26.8 ± 1.6 41.5 ± 2.9 60.6 ± 5.2 84.2 ± 8.2
Maltodextrin 2.0 318 ± 18 43.6 ± 3.5 15.5 ± 0.7 25.5 ± 1.4 39.2 ± 2.6 56.8 ± 4.9 77.1 ± 8.0
Lactose 2.0 281 ± 11 41.7 ± 3.7 15.3 ± 0.8 24.8 ± 1.7 37.7 ± 2.9 54.0 ± 4.9 72.8 ± 7.8
Lactulose 2.0 286 ± 47 38.7 ± 4.5 14.3 ± 1.3 22.7 ± 2.5 34.9 ± 3.6 50.2 ± 5.9 67.9 ± 9.3
OsLua 2.0 223 ± 55 30.3 ± 3.9* 11.5 ± 0.9* 17.3 ± 1.9* 27.0 ± 3.0* 38.8 ± 4.6* 52.3 ± 7.2*
Maltodextrin 4.0 287 ± 32 39.8 ± 3.8 14.7 ± 1.3 23.4 ± 2.5 35.7 ± 3.4 60.0 ± 4.9 69.0 ± 6.7
Lactose 4.0 230 ± 29* 33.4 ± 5.3* 13.0 ± 1.7* 19.9 ± 3.1* 29.4 ± 4.6* 42.8 ± 6.6* 56.8 ± 9.8*
Lactulose 4.0 221 ± 56 29.6 ± 5.6* 12.1 ± 1.7* 17.6 ± 3.2* 27.3 ± 5.2* 38.5 ± 7.1* 50.6 ± 10.0*
OsLua 4.0 194 ± 50* 22.5 ± 3.1* 9.03 ± 0.78* 12.8 ± 1.1* 19.9 ± 2.1* 28.7 ± 3.5* 39.1 ± 6.0*
899
a Oligosaccharides derived from Lactulose (OsLu)
900 b Non-parametric Mann–Whitney U-test of two samples (control vs. yogurt with added sugar) 901
c Arithmetic mean from volume-weighted particle size distribution 902
* Probability P < 0.05 903 904
41
Table 3: Rheological parameters of synbiotic yogurts fortified with skim milk powder (SMP) and total milk powder (TMP) at 𝜗 = 10ºC; averages 905
and standard errors calculated from i ≥ 3, n ≥ 9 906
Fortified
with Added sugar Amount
Oscillation Rotation
Storage modulusb Yield point
b Apparent viscosities
b
G' (10 rad 1/s) 𝜎y η (0.1 1/s) η (50 1/s) η (631 1/s)
– – % (w/w) Pa Pa Pa s Pa s Pa s
SMP
Control
– 266 ± 48 0.808 ± 0.078 68.4 ± 11.1 1.31 ± 0.14 0.161 ± 0.017
Maltodextrin 2.0
2.0
2.0
2.0
287 ± 55 0.804 ± 0.092 67.2 ± 11.4 1.19 ± 0.13 0.148 ± 0.014
Lactose 256 ± 38 0.779 ± 0.045 60.1 ± 7.0 1.14± 0.14 0.136 ± 0.016
Lactulose 240 ± 44 0.751 ± 0.061 58.8 ± 7.3 1.19 ± 0.07 0.153 ± 0.009
OsLua 194 ± 27 0.621 ± 0.071 43.9 ± 7.2 1.08 ± 0.12 0.134 ± 0.005
Maltodextrin 4.0 273 ± 53 0.778 ± 0.066 59.9 ± 7.2 1.20 ± 0.15 0.144 ± 0.019
Lactose 4.0 226 ± 76 0.758 ± 0.091 57.9 ± 10.9 1.16 ± 0.27 0.151 ± 0.041
Lactulose 4.0 158 ± 33* 0.598 ± 0.053* 44.7 ± 5.8* 1.13 ± 0.15 0.149 ± 0.004
OsLua 4.0 116 ± 16* 0.432 ± 0.070* 26.5 ± 3.0* 0.874 ± 0.179* 0.117 ± 0.011*
TMP
Control – 387 ± 71 1.013 ± 0.121 103 ± 25.9 1.53 ± 0.24 0.170 ± 0.016
Maltodextrin 2.0 355 ± 75 0.925 ± 0.128 85.6 ± 25.2 1.48 ± 0.31 0.173 ± 0.021
Lactose 2.0 361 ± 74 0.959 ± 0.144 98.0 ± 22.6 1.52± 0.31 0.172 ± 0.023
Lactulose 2.0 349 ± 75 0.919 ± 0.121 83.4 ± 20.6 1.43 ± 0.23 0.156 ± 0.015
OsLua 2.0 268 ± 81 0.771 ± 0.125 58.8 ± 16.9 1.36 ± 0.25 0.142 ± 0.023
Maltodextrin 4.0 357 ± 17 0.911 ± 0.044 82.2 ± 10.0 1.65 ± 0.11 0.175 ± 0.018
Lactose 4.0 270 ± 57 0.813 ± 0.092* 61.7 ± 12.3* 1.35 ± 0.17 0.154 ± 0.023
Lactulose 4.0 251 ± 70 0.728 ± 0.098* 54.8 ± 11.3* 1.39 ± 0.27 0.156 ± 0.023
OsLua 4.0 223 ± 30 0.598 ± 0.057 40.6 ± 5.0 0.995 ± 0.143 0.120 ± 0.015
907 a Oligosaccharides derived from Lactulose (OsLu) 908
b Non-parametric Mann–Whitney U-test of two samples (control vs. yoghurt with added sugar) 909
* Probability P < 0.05 910
42
Table 3: Rheological parameters of synbiotic yogurts fortified with skim milk powder (SMP) and total milk powder (TMP) at 𝜗 = 10ºC; averages 911
and standard errors calculated from i ≥ 3, n ≥ 9 912
Fortified
with Added sugar Amount
Oscillation Rotation
Storage modulusb Yield point
b Apparent viscosities
b
G' (10 rad 1/s) 𝜎y η (0.1 1/s) η (50 1/s) η (631 1/s)
– – % (w/w) Pa Pa Pa s Pa s Pa s
SMP
Control
– 266 ± 48 0.808 ± 0.078 68.4 ± 11.1 1.31 ± 0.14 0.161 ± 0.017
Maltodextrin 2.0
2.0
2.0
2.0
287 ± 55 0.804 ± 0.092 67.2 ± 11.4 1.19 ± 0.13 0.148 ± 0.014
Lactose 256 ± 38 0.779 ± 0.045 60.1 ± 7.0 1.14± 0.14 0.136 ± 0.016
Lactulose 240 ± 44 0.751 ± 0.061 58.8 ± 7.3 1.19 ± 0.07 0.153 ± 0.009
OsLua 194 ± 27 0.621 ± 0.071 43.9 ± 7.2 1.08 ± 0.12 0.134 ± 0.005
Maltodextrin 4.0 273 ± 53 0.778 ± 0.066 59.9 ± 7.2 1.20 ± 0.15 0.144 ± 0.019
Lactose 4.0 226 ± 76 0.758 ± 0.091 57.9 ± 10.9 1.16 ± 0.27 0.151 ± 0.041
Lactulose 4.0 158 ± 33* 0.598 ± 0.053* 44.7 ± 5.8* 1.13 ± 0.15 0.149 ± 0.004
OsLua 4.0 116 ± 16* 0.432 ± 0.070* 26.5 ± 3.0* 0.874 ± 0.179* 0.117 ± 0.011*
TMP
Control – 387 ± 71 1.013 ± 0.121 103 ± 25.9 1.53 ± 0.24 0.170 ± 0.016
Maltodextrin 2.0 355 ± 75 0.925 ± 0.128 85.6 ± 25.2 1.48 ± 0.31 0.173 ± 0.021
Lactose 2.0 361 ± 74 0.959 ± 0.144 98.0 ± 22.6 1.52± 0.31 0.172 ± 0.023
Lactulose 2.0 349 ± 75 0.919 ± 0.121 83.4 ± 20.6 1.43 ± 0.23 0.156 ± 0.015
OsLua 2.0 268 ± 81 0.771 ± 0.125 58.8 ± 16.9 1.36 ± 0.25 0.142 ± 0.023
Maltodextrin 4.0 357 ± 17 0.911 ± 0.044 82.2 ± 10.0 1.65 ± 0.11 0.175 ± 0.018
Lactose 4.0 270 ± 57 0.813 ± 0.092* 61.7 ± 12.3* 1.35 ± 0.17 0.154 ± 0.023
Lactulose 4.0 251 ± 70 0.728 ± 0.098* 54.8 ± 11.3* 1.39 ± 0.27 0.156 ± 0.023
OsLua 4.0 223 ± 30 0.598 ± 0.057 40.6 ± 5.0 0.995 ± 0.143 0.120 ± 0.015
913 a Oligosaccharides derived from Lactulose (OsLu) 914
b Non-parametric Mann–Whitney U-test of two samples (control vs. yoghurt with added sugar) 915
* Probability P < 0.05 916
43
Table 4: Correlation of the first, second and third factor from multiple factor analysis (MFA) 917
of all dependent parameters (n = 66) 918
Parameter
Correlation coefficienta ri
Factor 1
Factor 2 Factor 3
pH.
raw.start 0.0411 0.0306 −0.407***
raw.455b −0.842*** 0.228 0.199
raw.620b −0.637*** −0.103 0.109
log.0 0.717*** 0.544*** 0.145
log.inf −0.370** 0.504*** 0.117
log.lagb 0.592*** −0.693*** 0.148
log.rateb 0.734*** 0.234*** 0.979***
pen.
fMAXb 0.821*** 0.448*** 0.0715
slope 0.379** 0.145 0.0719
lds.
meanb 0.898*** 0.302* 0.0445
d10 0.917*** 0.216 0.0871
d25 0.908*** 0.260* 0.0639
d50 0.915*** 0.261* 0.0494
d75 0.904*** 0.311* 0.0576
d90 0.893*** 0.332** 0.0394
spanb 0.538*** 0.558*** −0.0204
rheo.
modulusb 0.830*** 0.433*** −0.0377
eta01 0.846*** 0.353** 0.0692
eta50 0.647*** 0.246* 0.163
eta631 0.573*** 0.128 0.230
yieldb 0.875*** 0.279* 0.0605
ing.
sugc 0.769*** 0.209** 0.706***
addc 0.170** 0.101* 0.0547
powdc 0.104* 0.333*** 0.0453
osmoc −0.822*** −0.221 −0.110
dmc −0.684*** −0.259* −0.178
protc 0.656*** 0.215 0.0619
Exp. varianced 56.6% 17.8% 14.9%
919 a Coefficient ri and significance of correlation between factor i (column) and parameter (row) 920
b Parameters remaining for the reduced data set 921
c Correlation of the independent ingredients parameters without contribution to MFA construction 922
d Proportion of the variance explained by each factor (column) 923
italic print: qualitative parameters' correlation 924 bold print: four most contributing parameters within each factor (column) 925 *,**,*** Probability P < 0.05, P < 0.01, and P < 0.001 respectively 926 927 928