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: stefan.noebel@mri.bund.de (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

4

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

References 632

Anadón, A., Martínez, M. A., Ares, I., Castellano, V., Martínez-Larrañaga, M. R., Corzo, N., 633

… Reglero, G. (2013). Acute and repeated dose (28 days) oral safety studies of alibird in 634

rats. Journal of Food Protection, 76(7), 1226–1239. https://doi.org/10.4315/0362-635

028X.JFP-13-032 636

Anonymous. (2002). Milk and milk products – Determination of nitrogen content – Routine 637

method using combustion according to the Dumas principle. ISO 14891 IDF 185. 638

Geneva. 639

Anonymous. (2010). Methodenbuch VI: Milch C 35.3 (7th edn). Darmstadt, Germany: 640

VDLUFA-Verlag 641

Cardelle-Cobas, A., Corzo, N., Olano, A., Peláez, C., Requena, T., & Ávila, M. (2011). 642

Galactooligosaccharides derived from lactose and lactulose: influence of structure on 643

Lactobacillus, Streptococcus and Bifidobacterium growth. International Journal of Food 644

Microbiology, 149(1), 81-87. https_//doi.org/10.1016/j.ijfoodmicro.2011.05.026 645

Chandan, R. C., & Kilara, A. (2013). Manufacturing yogurt and fermented milks (2nd edn) 646

Hoboken (NJ), USA: Wiley-Blackwell, Inc. https://doi.org/10.1002/9781118481301 647

Cruz, A. G., Cavalcanti, R. N., Guerreiro, L. M. R., Sant’Ana, A. S., Nogueira, L. C., 648

Oliveira, C. A. F., … Bolini, H. M. A. (2013). Developing a prebiotic yogurt: 649

Rheological, physico-chemical and microbiological aspects and adequacy of survival 650

analysis methodology. Journal of Food Engineering, 114(3), 323–330. 651

https://doi.org/10.1016/j.jfoodeng.2012.08.018 652

Da Silva, D. F., Junior, N. N. T., Gomes, R. G., dos Santos Pozza, M. S., Britten, M., & 653

Matumoto-Pintro, P. T. (2017). Physical, microbiological and rheological properties of 654

probiotic yogurt supplemented with grape extract. Journal of Food Science and 655

Technology, 54(6), 1608-1615. https://doi.org/10.1007/s13197-017-2592-x 656

29

Das, K., Choudhary, R., & Thompson-Witrick, K. A. (2019). Effects of new technology on 657

the current manufacturing process of yogurt-to increase the overall marketability of 658

yogurt. LWT. 108, 69-80. https://doi.org/10.1016/j.lwt.2019.03.058 659

De Castro, F. P., Cunha, T. M., Barreto, P. L. M., Amboni, R. D. D. M. C., & Prudêncio, E. S. 660

(2009). Effect of oligofructose incorporation on the properties of fermented probiotic 661

lactic beverages. International Journal of Dairy Technology, 62(1), 68–74. 662

https://doi.org/10.1111/j.1471-0307.2008.00447.x 663

De Souza Oliveira, R. P., Rodrigues Florence, A. C., Perego, P., De Oliveira, M. N., & 664

Converti, A. (2011). Use of lactulose as prebiotic and its influence on the growth, 665

acidification profile and viable counts of different probiotics in fermented skim milk. 666

International Journal of Food Microbiology, 145(1), 22–27. 667

https://doi.org/10.1016/j.ijfoodmicro.2010.11.011 668

Delgado-Fernández, P., Corzo, N., Lizasoain, S., Olano, A., & Moreno, F. J. (2019a). 669

Fermentative properties of starter culture during manufacture of kefir with new 670

prebiotics derived from lactulose. International Dairy Journal, 93, 22–29. 671

https://doi.org/10.1016/j.idairyj.2019.01.014 672

Delgado-Fernández, P., Corzo, N., Olano, A., Hernández-Hernández, O., & Moreno, F. J. 673

(2019b). Effect of selected prebiotics on the growth of lactic acid bacteria and 674

physicochemical properties of yoghurts. International Dairy Journal, 89, 77–85. 675

https://doi.org/10.1016/j.idairyj.2018.09.003 676

Delgado-Fernández, P., Hernández-Hernández, O., Olano, A., Moreno, F. J. & Corzo, N. 677

(2019c). Probiotic viability in yoghurts containing oligosaccharides derived from 678

lactulose (OsLu) during fermentation and cold storage. International Dairy Journal (In 679

press). https:/doi.org/10.1016/j.idairyj.2019.104621 680

30

Fernández, J., Moreno, F. J., Olano, A., Clemente, A., Villar, C. J., & Lombó, F. (2018). 681

Galacto-oligosaccharides derived from lactulose protects against colorectal cancer 682

development in a animal model. https:/doi.org/10.3389/fmicb.2018.02004 683

Ferreira-Lazarte, A., Gallego-Lobillo, P., Moreno, F. J., Villamiel, M., & Hernandez-684

Hernandez, O. (2019). In vitro digestibility of galactooligosaccharides: effect of the 685

structural features on their intestinal degradation. Journal of Agricultural and Food 686

Chemistry, 61 (16), 4662-4670. https://doi.org/10.1021/acs.jafc.9b00417. 687

Fysun, O., Nöbel, S., Loewen, A. J., & Hinrichs, J. (2018). Tailoring yield stress and viscosity 688

of concentrated microgel suspensions by means of adding immiscible liquids. LWT-Food 689

Science and Technology, 93, 51–57. https://doi.org/10.1016/j.lwt.2018.03.013 690

Gibson, G. R., Hutkins, R., Sanders, M. E., Prescott, S. L., Reimer, R. A., Salminen, S. J., … 691

Reid, G. (2017). Expert consensus document: The International Scientific Association 692

for Probiotics and Prebiotics (ISAPP) consensus statement on the definition and scope of 693

prebiotics. Nature Reviews Gastroenterology and Hepatology, 14(8), 491–502. 694

https://doi.org/10.1038/nrgastro.2017.75 695

Granato, D., Branco, G. F., Nazzaro, F., Cruz, A. G., & Faria, J. A. (2010). Functional foods 696

and nondairy probiotic food development: trends, concepts, and products. 697

Comprehensive Reviews in Food Science and Food Safety, 9(3), 292-302. 698

https://doi.org/10.1111/j.1541-4337.2010.00110.x 699

Guggisberg, D., Cuthbert-Steven, J., Piccinali, P., Bütikofer, U., & Eberhard, P. (2009). 700

Rheological, microstructural and sensory characterization of low-fat and whole milk set 701

yoghurt as influenced by inulin addition. International Dairy Journal, 19(2), 107–115. 702

https://doi.org/10.1016/j.idairyj.2008.07.009 703

Guven, M., Yasar, K., Karaca, O. B., & Hayaloglu, A. A. (2005). The effect of inulin as a fat 704

replacer on the quality of set-type low-fat yogurt manufacture. International Journal of 705

Dairy Technology, 58(3), 180–184. https://doi.org/10.1111/j.1471-0307.2005.00210.x 706

31

Hahn, C., Sramek, M., Nöbel, S., & Hinrichs, J. (2012). Post-processing of concentrated 707

fermented milk: Influence of temperature and holding time on the formation of particle 708

clusters. Dairy Science and Technology, 92(1), 91–107. https://doi.org/10.1007/s13594-709

011-0046-1 710

Hernández-Hernández, O., Muthaiyan, A., Moreno, F. J., Montilla, A., Sanz, M. L., & Ricke, 711

S. C. (2012). Effect of prebiotic carbohydrates on the growth and tolerance of 712

Lactobacillus. Food Microbiology, 30(2), 355–361. 713

https://doi.org/10.1016/j.fm.2011.12.022 714

Horne, D. S. (1999). Formation and structure of acidified milk gels. International Dairy 715

Journal, 9(3–6), 261–268. https://doi.org/10.0.3.248/S0958-6946(99)00072-2 716

Jacob, M., Nöbel, S., Jaros, D., & Rohm, H. (2011). Physical properties of acid milk gels: 717

Acidification rate significantly interacts with cross-linking and heat treatment of milk. 718

Food Hydrocolloids, 25(5), 928–934. https://doi.org/10.1016/j.foodhyd.2010.09.003 719

Jørgensen, C. E., Abrahamsen, R. K., Rukke, E. O., Hoffmann, T. K., Johansen, A. G., & 720

Skeie, S. B. (2019). Processing of high-protein yoghurt–A review. International Dairy 721

Journal, 88, 42-59. https://doi.org/10.1016/j.idairyj.2018.08.002 722

Karam, M. C., Gaiani, C., Hosri, C., Burgain, J., & Scher, J. (2013). Effect of dairy powders 723

fortification on yogurt textural and sensorial properties: A review. Journal of Dairy 724

Research, 80(4), 400–409. https://doi.org/10.1017/S0022029913000514 725

Kárnyáczki, Z., & Csanádi, J. (2017). Texture profile properties, sensory evaluation, and 726

susceptibility to syneresis of yoghurt prepared from lactose-free milk. Acta Alimentaria, 727

46(4), 403–410. https://doi.org/10.1556/066.2016.0018 728

Körzendörfer, A., Nöbel, S., & Hinrichs, J. (2017). Particle formation induced by sonication 729

during yogurt fermentation – Impact of exopolysaccharide-producing starter cultures on 730

physical properties. Food Research International, 97(February), 170–177. 731

https://doi.org/10.1016/j.foodres.2017.04.006 732

32

Kristo, E., Biliaderis, C. G., & Tzanetakis, N. (2003). Modelling of the acidification process 733

and rheological properties of milk fermented with a yogurt starter culture using response 734

surface methodology. Food Chemistry, 83(3), 437–446. https://doi.org/10.1016/S0308-735

8146(03)00126-2 736

Krzeminski, A., Tomaschunas, M., Köhn, E., Busch-Stockfisch, M., Weiss, J., & Hinrichs, J. 737

(2013). Relating Creamy Perception of Whey Protein Enriched Yogurt Systems to 738

Instrumental Data by Means of Multivariate Data Analysis. Journal of Food Science, 739

78(2). https://doi.org/10.1111/1750-3841.12013 740

Lé, S., Josse, J., & Husson, F. (2008). FactoMineR: An R package for multivariate analysis. 741

Journal of Statistical Software, 25(1), 1–18. https://doi.org/10.18637/jss.v025.i01 742

Lee, W.J., & Lucey, J. A. (2004). Structure and Physical Properties of Yogurt Gels: Effect of 743

Inoculation Rate and Incubation Temperature. Journal of Dairy Science, 87(10), 3153–744

3164. https://doi.org/10.0.12.96/jds.S0022-0302(04)73450-5 745

Lee, W. J., & Lucey, J. A. (2010). Formation and physical properties of yogurt. Asian-746

Australasian Journal of Animal Sciences, 23(9), 1127–1136. 747

https://doi.org/10.5713/ajas.2010.r.05 748

Longinotti, M. P., & Corti, H. R. (2008). Viscosity of concentrated sucrose and trehalose 749

aqueous solutions including the supercooled regime. Journal of Physical and Chemical 750

Reference Data, 37(3), 1503–1515. https://doi.org/10.1063/1.2932114 751

López-Sanz, S., Montilla, A., Moreno, F. J., & Villamiel, M. (2015). Stability of 752

oligosaccharides derived from lactulose during the processing of milk and apple juice. 753

Food Chemistry, 183, 64–71. https://doi.org/10.1016/j.foodchem.2015.03.020 754

Medeiros, A. C., Souza, D. F., & Correia, R. T. P. (2015). Effect of incubation temperature, 755

heat treatment and milk source on the yoghurt kinetic acidification. International Food 756

Research Journal, 22(3), 1030–1036. 757

33

Meletharayil, G. H., Patel, H. A., Metzger, L. E., & Huppertz, T. (2016). Acid gelation of 758

reconstituted milk protein concentrate suspensions: Influence of lactose addition. 759

International Dairy Journal, 61, 107–113. https://doi.org/10.1016/j.idairyj.2016.04.005 760

Mensink, M. A., Frijlink, H. W., Van Der Voort Maarschalk, K., & Hinrichs, W. L. J. (2015). 761

Inulin, a flexible oligosaccharide I: Review of its physicochemical characteristics. 762

Carbohydrate Polymers. Elsevier Ltd. https://doi.org/10.1016/j.carbpol.2015.05.026 763

Mokoonlall, A., Nöbel, S., & Hinrichs, J. (2016). Post-processing of fermented milk to stirred 764

products: Reviewing the effects on gel structure. Trends in Food Science and 765

Technology, 54, 26–36. https://doi.org/10.1016/j.tifs.2016.05.012 766

Montilla, A., Van De Lagemaat, J., Olano, A., & Del Castillo, M. D. (2006). Determination of 767

oligosaccharides by conventional high-resolution gas chromatography. 768

Chromatographia, 63(9–10), 453–458. https://doi.org/10.1365/s10337-006-0770-5 769

Moussier, M., Huc-Mathis, D., Michon, C., & Bosc, V. (2019). Rational design of a versatile 770

lab-scale stirred milk gel using a reverse engineering logic based on microstructure and 771

textural properties. Journal of Food Engineering, 249, 1–8. 772

https://doi.org/10.1016/j.jfoodeng.2018.12.018 773

Nöbel, S., Protte, K., Körzendörfer, A., Hitzmann, B., & Hinrichs, J. (2016). Sonication 774

induced particle formation in yogurt: Influence of the dry matter content on the physical 775

properties. Journal of Food Engineering, 191, 77–87. 776

https://doi.org/10.1016/j.jfoodeng.2016.07.007 777

Özer, D., Akin, S., & Özer, B. (2005). Effect of inulin and lactulose on survival of 778

lactobacillus acidophilus LA-5 and bifidobacterium bifidum BB-02 in acidophilus-779

bifidus Yoghurt. Food Science and Technology International, 11(1), 19–24. 780

https://doi.org/10.1177/1082013205051275 781

Pagès, J. (2015). Multiple Factor Analysis by Example Using R. Boca Raton (FL): CRC Press. 782

34

Papadimitriou, K., Alegría, Á., Bron, P. A., De Angelis, M., Gobbetti, M., Kleerebezem, M., 783

... & Turroni, F. (2016). Stress physiology of lactic acid bacteria. Microbiology and 784

Molecular Biology Reviews, 80(3), 837-890. https://doi.org/10.1128/MMBR.00076-15 785

Paseephol, T., Small, D. M., & Sherkat, F. (2008). Rheology and texture of set yogurt as 786

affected by inulin addition. Journal of Texture Studies, 39(6), 617–634. 787

https://doi.org/10.1111/j.1745-4603.2008.00161.x 788

Remeuf, F., Mohammed, S., Sodini, I., & Tissier, J. P. (2003). Preliminary observations on 789

the effects of milk fortification and heating on microstructure and physical properties of 790

stirred yogurt. International Dairy Journal, 13(9), 773–782. 791

https://doi.org/10.1016/S0958-6946(03)00092-X 792

Ruszkowski, J., Witkowski, J. (2019). Lactulose: Patient-and dose-dependent prebiotic 793

properties in humans. Anaerobe, 59, 100-106. 794

https://doi.org/10.1016/j.anaerobe.2019.06.002 795

Sah, B. N. P., Vasiljevic, T., McKechnie, S., & Donkor, O. N. (2016). Physicochemical, 796

textural and rheological properties of probiotic yogurt fortified with fibre-rich pineapple 797

peel powder during refrigerated storage. LWT - Food Science and Technology, 65, 978–798

986. https://doi.org/10.1016/j.lwt.2015.09.027 799

Schmidt, C., Mende, S., Jaros, D., & Rohm, H. (2016). Fermented milk products: effects of 800

lactose hydrolysis and fermentation conditions on the rheological properties. Dairy 801

Science and Technology, 96(2), 199–211. https://doi.org/10.1007/s13594-015-0259-9 802

Schorsch, C., Wilkins, D. K., Jones, M. G., & Norton, I. T. (2001). Gelation of casein-whey 803

mixtures: Effects of heating whey proteins alone or in the presence of casein micelles. 804

Journal of Dairy Research, 68(3), 471–481. 805

https://doi.org/10.1017/S0022029901004915 806

35

Sodini, I., Lucas, A., Tissier, J. P., & Corrieu, G. (2004). Physical properties and 807

microstructure of yoghurts supplemented with milk protein hydrolysates. International 808

Dairy Journal, 15(1), 29–35. https://doi.org/10.1016/j.idairyj.2004.05.006 809

Vénica, C. I., Bergamini, C. V., Rebechi, S. R., & Perotti, M. C. (2015). Galacto-810

oligosaccharides formation during manufacture of different varieties of yogurt. Stability 811

through storage. LWT - Food Science and Technology, 63(1), 198–205. 812

https://doi.org/10.1016/j.lwt.2015.02.032 813

Villegas, B., & Costell, E. (2007). Flow behaviour of inulin-milk beverages. Influence of 814

inulin average chain length and of milk fat content. International Dairy Journal, 17(7), 815

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