# Microbiological, physicochemical, and sensory changes throughout ripening of an experimental soft smear-ripened cheese in relation to salt concentrations

Marie-Noëlle Leclercq-Perlat, Anne Saint-Eve, Daniel Picque, Ioan-Cristian

Trelea

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Marie-Noëlle Leclercq-Perlat, Anne Saint-Eve, Daniel Picque, Ioan-Cristian Trelea. Microbiological, physicochemical, and sensory changes throughout ripening of an experimental soft smear-ripened cheese in relation to salt concentrations. Journal of Dairy Science, 2024, 107 (8), pp.6393-6411. 10.3168/jds.2024-24307. hal-05246766

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# Microbiological, physicochemical, and sensory changes throughout ripening of an experimental soft smear-ripened cheese in relation to salt concentrations

Marie-Noëlle Leclercq-Perlat, Anne Saint-Eve, Daniel Picque, and Ioan-Cristian Trelea*

Université Paris-Saclay, INRAE, AgroParisTech, UMR SayFood, F-91120, Palaiseau, France.

## ABSTRACT

To evaluate the effect of NaCl content on microbiological, biochemical, physicochemical, and sensorial characteristics, Munster cheeses were prepared from pasteurized milk seeded with 3 yeasts (Kluyveromyces marxianus, Debaryomyces hansenii, and Geotrichum candidum) and 5 ripening bacteria (Arthrobacter arilaitensis, Brevibacterium aurantiacum, Corynebacterium casei, Hafnia alvei, and Staphylococcus equorum). Experiments were performed in triplicate under 1.0%, 1.7%, and 2.4% NaCl levels in cheese. Ripening (d 2–27) was carried out at 12°C and 96% relative humidity. These kinetics were both reproducible and repeatable at a 99% confidence level. For each microbial, biochemical, and physicochemical parameter, 2 kinetic descriptors (the maximal or minimal rate and its occurrence time) were defined. On d 2, the physicochemical variables (water activity, dry matter, and water content) were strongly dependent on the salting level. From d 2 to d 27, K. lactis was insensitive to salt, whereas D. hansenii was stimulated. Geotrichum candidum growth appeared very sensitive to salt in cheese: at 1.0% NaCl, G. candidum exhibited overgrowth, negatively affecting rind appearance, underrind consistency and thickness, and off-flavor flaws. A salt concentration of 2.4% induced death of G. candidum. A total of 4 bacteria (A. arilaitensis, B. aurantiacum, C. casei, and H. alvei) were moderately sensitive to salt, but S. equorum was insensitive to it. Salt level in cheese had a significant effect on carbon substrate consumption rates. The lactate consumption rate in 1.0% salted cheeses was approximately twice higher than under 2.4% NaCl. Data analysis of microorganism, biochemical, and physicochemical kinetics, as well as sensory analysis, showed that 1.7% NaCl was the best salt level in Munster-type cheeses to achieve an optimum balance between cheese characteristics, sensory qualities, and marketability.

**Key words:** salt level, soft smear cheese ripening, kinetic descriptors, sensory analysis

## INTRODUCTION

Because the excessive consumption of sodium by humans (between 8 and 10 g d⁻¹ for an adult) causes diseases, the World Health Organization (2012) as well as national health agencies have recommended reducing sodium intake by 30% (i.e., to around 5 g d⁻¹). Salt reduction in cheeses is a challenge for dairy industries: many factors must be studied, such as safety, texture, flavor, and consumer acceptability (Costa et al., 2018). Substantial steps in this direction have already been accomplished: A few decades ago, the salt level in Munster-type cheeses was 2.5 ± 0.2% (± SD), and it has now been decreased to 1.7 ± 0.2%. However, French and international health agencies encourage cheesemakers to decrease the salt level further, by at least 0.3% or more. These recommendations motivated the present study, which explores the consequences of such a decrease, compared with current and past salt levels.

Cheese salting is a highly important step for the control of microbiological and enzymatic activity (Reddy and Marth, 1995; Hardy et al., 2000; Guinee and Fox, 2004) and their influence on syneresis, mineral balance, moisture, water activity, and other physicochemical characteristics, as well as on physical changes in cheese protein (e.g., texture, solubility) and on taste and flavor (McSweeney et al., 2017; Costa et al., 2018). The impact of salt on cheese ripening depends on salting methods, cheese variety, and the cheesemaker (Guinee and Fox, 2004; Agarwal et al., 2011; Seratlić et al., 2011).

In the past, most studies on salt effects were conducted with individual microbial strains in synthetic media or in highly simplified cheese models. The originality of this work includes experiments with real cheese and a comparatively complex microflora (3 yeasts, 5 bacteria), for which relatively little data are available in the literature. To our knowledge, very few works have studied salt content influence on changes in the complex ecosystem

Received October 13, 2023.

Accepted February 11, 2024.

*Corresponding author: cristian.trelea@agroparistech.fr

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes.
in soft smear-ripened cheeses. These cheeses are characterized by the growth of a heterogeneous smear on their surface, with the consequent development of a strong flavor due to the metabolic activities of the bacteria and yeasts forming this microflora. These cheeses are brined or surface salted, which also influences the growth of surface microbiota (Bertuzzi et al., 2018). If the salt impact on yeasts in a model medium has been relatively well studied, there is still little data on the influence of salt reductions on surface bacteria (Dugat-Bony et al., 2019).

The major yeasts found in smear cheeses have different levels of salt tolerance (Lages et al., 1999). *Debaryomyces hansenii*, the predominant yeast in the smear-ripened cheese rind (Fröhlich-Wyder et al., 2019) is well known for its high halotolerance (class IV; Lages et al., 1999; Prista et al., 2016) and can be stimulated by NaCl (Almagro et al., 2000, 2001; Corbaci et al., 2012). *Kluyveromyces* spp. are frequently found in the early stage of ripening in French traditional cheeses (Leclercq-Perlat et al., 2012; Dugat-Bony et al., 2016). Their salt tolerance (class III; Lages et al., 1999) could be explained by an adaption to salted cheese (Sohier et al., 2009; Fröhlich-Wyder et al., 2019). *Geotrichum candidum* is well known to be particularly sensitive to salt, but this dependency is strain dependent (Boutrou and Guéguen, 2005). Its growth in cheese is generally limited at NaCl concentrations above 1% (Fröhlich-Wyder et al., 2019). However all *G. candidum* strains isolated from Armada cheeses exhibit good growth at 1.8% NaCl (Tornadijo et al., 1998). In a Camembert-type cheese, *G. candidum* was able to grow at 1.7 ± 0.1% salt (i.e., 2–3 d after brining), and 3.5 ± 0.1% salt in the rind (just after brining) only delays its growth (Leclercq-Perlat et al., 2004a, 2012).

Contrary to yeasts, the surface bacterial flora is complex and poorly understood (Dugat-Bony et al., 2015), and little knowledge is available on the impact of salt level on surface-ripened cheese (Dugat-Bony et al., 2019). The interactions between yeasts and bacteria on cheeses are also complex and very poorly comprehended (Bertuzzi et al., 2018; Dugat-Bony et al., 2019). Usually cheese deacidification and growth factor secretion by yeasts lead to growth of surface bacteria (Leclercq-Perlat et al., 2000; Fröhlich-Wyder et al., 2019). Whatever the salt level, *D. hansenii* is the more efficient for deacidification (Leclercq-Perlat et al., 2004b). Reducing salt causes a disequilibrium in microbial developments (Dugat-Bony et al., 2016).

The aim of this study was to evaluate the salt level effects on a complex microflora of Munster-type cheeses throughout the ripening. We measured microbial developments and biochemical, physicochemical and sensory changes induced, and their corresponding kinetics when cheeses were salted at 1.7 ± 0.1% (control), and this

value increased and decreased by 40% (i.e., 1.0% and 2.4% of salt).

# MATERIALS AND METHODS

## Biological Material

For the ripening cultures, we used 3 yeast strains, namely *Debaryomyces hansenii* 304 (DH) and *Kluyveromyces lactis* 3550 (KL) from the SayFood (Palaiseau, France) collection and *Geotrichum candidum* (GC, ATCC 204307, American Type Culture Collection, Manassas, VA), and 5 bacteria strains, namely *Arthrobacter arilaitensis* Re111 (AA), *Hafnia Alvei* GB001 (HA), *Brevibacterium aurantiacum* (BA, ATCC 9174), *Corynebacterium casei* 2M01 (CC), and *Staphylococcus equorum* Mu2 (SE). Of these, AA, CC, HA and SE (SayFood collection) have been isolated from Livarot, a French Protected Designation of Origin cheese. The mesophilic lactic acid bacteria (LAB) culture consisted of *Lactobacillus lactis* var. *lactis* S3⁺ and its protease-negative variant S3⁻ (Say-Food collection). The preparations of the ripening strains and their numeration were carried out as described by Dugat-Bony et al. (2016).

## Cheesemaking and Ripening

Cheeses were prepared on a pilot scale under aseptic conditions in a sterilized 3-m³ chamber, in which the coagulation, cutting, draining, and shaping of the curds were carried out (Leclercq-Perlat et al., 2012). The chamber and all the nonautoclavable pieces of equipment were cleaned and sterilized (Leclercq-Perlat et al., 2004a). The temperature of the cheesemaking chamber was maintained at 28 ± 1°C. For each cheesemaking replicate, 50 L of milk was used to make 115 smear-ripened type cheeses, each weighting 50.0 ± 2.5 g (diameter = 68 mm and height = 21–23 mm). The pasteurized (2 min at 80°C) raw milk and the pasteurized semi-skim milk (Alsace Lait, Hoerdt, France) were obtained at the local supermarket. The milk was standardized at 2.8% (wt/wt) of fat by mixing semi-skimmed (1.6% wt/wt fat) and full-cream (3.6% wt/wt fat) milks. The protein content of the resulting cheesemaking milk was 3.4% (wt/wt). The pH of the milk varied between 6.6 and 6.7. After pouring the first liters of milk into the temperature-controlled coagulation tank at the incubation temperature (34 ± 1°C), that milk was inoculated with the LAB starter at 10⁶ cfu/mL of milk and the ripening starters. After the tank was filled with the remaining pasteurized milk, the concentrations of DH and KL were 6 × 10³ cfu/mL, the concentration of GC was 10² cfu/mL, and the concentrations of the 5 ripening bacteria were 8 × 10⁵ cfu/mL. Due to the LAB activity, the milk pH reached 6.3 after 180
min. The Rennet 520 (520 mg/L of chymosin, Chr. Hansen) was then added (30 mL/100 L). Coagulation took 20 min, following by 40 min of hardening. The curd was then cut into 2-cm cubes. After another 30 min, roughly 20 L of whey was drained. The average DM of the cheese on demolding was between 40% and 42%. The curd was then shaped in polyurethane molds with bottom (upper diameter 70 mm, lower diameter 60 mm, height 58 mm, reference no. 058 BDA, Ets Coquard, Villefranche-sur-Saône, France). After the end of molding, the molds were turned after 30 min, 5 h, and 19 h.

The cheeses were demolded and turned out 20 h after the end of molding, and the cheesemaking chamber temperature was reduced to 22 ± 1°C. This moment is designated as the initial ripening time (d 0). The cheeses were then turned after 4 and 9 h after demolding, and this yeasting phase lasted 24 h. A total of 3 cheeses were sampled on d 0 (after demolding) and on d 1 (end of yeasting). At the end of yeasting, each cheesemaking replicate was separated into 3 batches of 36 mini-cheeses before brining (2 × 30 min at 120°C) in sterile brine (15.0% NaCl wt/vol, pH 5.5) at 14 ± 1°C. Preliminary experiments were performed to determine the brining times to reach the target salt concentrations of 1.0%, 1.7%, and 2.4% NaCl. The determined times were 13 min, 50 min, and 100 min, respectively for the selected brine composition, temperature, and the considered cheese size and shape. Then, after 1 h of drying (22°C, 97% relative humidity [RH]) to eliminate the excess brine, all cheeses were transferred to the ripening chambers, which had been previously sterilized with peracetic acid. From d 2 to d 27, the cheeses were kept at 12.0 ± 0.5°C at 96 ± 1% relative humidity, with the renewed atmosphere. On d 2, d 6, d 13, d 20, and d 27, all cheeses were turned, and 3 cheeses per lot were removed under sterile conditions for microbiological and physicochemical analyses. On d 27, a total of 21 cheeses were sampled for sensory analysis. These cheesemaking and ripening experiments were done in triplicate.

## Experimental Design

The analyses were carried out using a 1-factor, 3-level complete factorial experimental design (3¹). The 1 factor was salt level (g of NaCl per 100 g of wet cheese [% wt/wt]), and its 3 levels that were tested were 1.7 ± 0.1% (S1.7, central), 1.0 ± 0.1% (S1.0, low), and 2.4 ± 0.1% (S2.4, high). The central salt level of 1.7% (control) was chosen according to the one usually used for Munster-type cheeses. These salting levels correspond to the following concentrations in the aqueous fraction of the cheese on d 0 (after demolding), in g of NaCl per 100 g of water in cheese (% wt/wt): 2.9 ± 0.2% (S1.7), 1.7 ± 0.2% (S1.0), and 4.1 ± 0.2% (S2.4).

## Analyses of the Cheeses

After measurements of rind pH, color, and underrind thickness (TUR), as well as texture analyses, each cheese was ground with a Moulinette blender (DPA141, Moulinex, Alençon, France) without separation between core and rind, and this mixture was called blended cheese. Before using, the blender elements (bowl, shedder blade, top) were cleaned with a hot (50–60°C) 2% RBS T105 (Traitements chimiques des surfaces, Frelinghem, France) water solution, rinsed, dried with Aniospay (Laboratoires Anios, Hellemmes, France), and finally sterilized by UV under a laminar flow hood (2 × 30 min).

**Microbiological Analyses.** For each cheese sample, under sterile conditions, 10 g of homogeneous blended cheese were put in a sterile bag containing 90 mL of sterile saline (0.9% NaCl wt/vol) and left at 50°C for 30 min (Leclercq-Perlat et al., 1999). This suspension was then homogenized (Stomacher, Intersciences, France; maximum speed for 3 min). Ripening microorganisms were enumerated by surface plating in triplicate on brain heart agar (Biokar Diagnostics) with amphotericin (50 mg/L) for surface bacteria and yeast extract-glucose-chloramphenicol (Biokar Diagnostics) with 2,3,5-triphenyltetrazolium chloride (10 mg/L) for yeasts differentiated on this medium by their morphotype (Dugat-Bony et al., 2016).

**Physicochemical Analyses.** Cheeses were analyzed for DM (%), water activity (a_w), pH of the rind (pH_rind), pH of the blended cheese (pHblend), lactose (LO), and lactate (LA) contents (in g kg⁻¹ of wet cheese), as well as underrind thickness (TUR; in %) as described by Leclercq-Perlat et al. (2004a, 2012, 2019).

The NaCl concentration measurements were done using a Na probe (ROSS sodium ion selective electrode, Thermo Scientific, Strasbourg, France). The preparation, use, known-addition calibration, and Na measuring of this electrode were conducted as proposed by the manufacturer's ROSS Na ion selective electrode guide. We then homogenized 20 mL of 10% (salt concentrations ≤2%) or 5% (salt concentrations >2%) cheese suspension with an Ultra-Turrax homogenizer (24,000 rpm for 1 min; IKA-Werke GmbH, Staufen, Germany). After homogenization, suspensions were filtered twice, first through ash-free filter paper (Whatman N°40; Sigma Aldrich, Saint-Quentin-Fallavier, France), and then through a cellulose filter (0.2 µm, Minisart SP25, Sartorius, Tigery, France). After filtrations, 10 mL of filtrate solution were added with 10 mL of ionic strength adjustor (reference no. 84111, ROSS, Thermo Scientific) to adjust the sample pH between 9 and 10, and this mixture was stirred. The NaCl concentrations in those solutions were determined from the NaCl calibration curve (ROSS
guide). Three measurements per cheese were done. The reported cheese NaCl concentrations were the arithmetic averages of these measurements.

Cheese color measurements were determined with a CM-2002 spectrocolorimeter (Minolta, Carrières-sur-Seine, France), using SpectraMagic 1.01 software (Minolta) as proposed by Leclercq-Perlat et al. (2004b). Data were logged into the L*C*h° colorimetric system, where L* is lightness, C* is metric saturation, and h° is hue angle. We conducted 3 measurements per cheese face. The reported cheese color (L*, C* and h°) was the arithmetic average of these 6 measurements.

Cheese hardness (measured in N) on d 27 was determined by penetration with a 3-mm diameter stainless steel cylinder as described by Leclercq-Perlat et al. (2019). On d 27 6 measurements per cheese sample were done with a penetration speed of 1 mm s⁻¹ and in a depth of 10 mm. The reported cheese hardness was the arithmetic average of these 6 measurements. The penetration method was selected because it enabled several measurements per cheese sample, and hence a statistical analysis of the results.

**Sensory Analysis on Day 27.** A 3-alternative forced-choice (3-AFC) procedure (Dessirier et al., 1999; Lee et al., 2009) was chosen to discriminate the 3 salted cheese lots. To be as close as possible to the consumer's choices, 20 panelists (age range from 20 to 55 yr), students and staff at SayFood participated in these analyses. Panelists were asked not to eat or drink anything except water for at least 1 h before testing and were naive to the specific aim of the study. To ensure that the samples were representative for each sampled lot, sampling rules specified by the International Organization for Standardization were respected (13301:2018; ISO, 2018). All cheese samples were identified by 3-digit random number to ensure that the judges could not recognize cheese lots.

Sensory analyses were carried out in separate booths under white light at 20°C. Each panelist analyzed 3 sets of 3 samples (1 with 1.0% NaCl, 1 with 1.7% NaCl, and 1 with 2.4% NaCl cheeses) on d 27. For each set, panelists had to answer 3 questions: (1) Which cheese was the most odorful? (2) Which cheese was the most colored? (3) Which cheese was the hardest?

## Statistical Analysis

All statistical tests were performed with XLSTAT-Base software 2016.05 (Addinsoft, Paris, France). All statistical tests with distribution into homogeneous clusters or ranks were carried out with a Bonferroni test at a 99% confidence level.

**Reproducibility of Cheesemaking and Repeatability of Cheese Sampling.** Whatever the ripening time and the microbial and physicochemical criteria, the normality of

these values for all replicates were checked at the 0.01 level. The repeatability of the microbiological and physicochemical variable means of the cheesemaking replicates and the 3 cheese samples on sampling days were compared using a 2-way (replicate and time) ANOVA. On each time, the hypotheses examined were the equality of the replicates and the absence of false interpretation. To control the equality of replicates, this test was significant for the risk α ≤ 0.01. To evaluate the risk of false interpretation, the test power (1 - β) was determined according to the Mann-Whitney method (Cohen, 1992).

**Determination of Physicochemical and Microbiological Descriptors.** For each replicate, the changes in each ripening parameter in time were fitted with a Weibull model (Schepers et al., 2000) as proposed by Leclercq-Perlat et al. (2012, 2015). From this model, the maximum rate of increase or decrease and its occurring time were determined.

**Influence of Salt Level on Cheese Descriptors Throughout the Ripening.** To check the influences of cheese salt level on cheese characteristics throughout the ripening, the Pearson correlation matrix was calculated with a 99% confidence level. To visualize these influences, a principal component analysis (PCA) of the mean values in a 2-dimensional plane was carried out. A variable was deemed significant with a 99% confidence level if the correlation coefficient or the absolute value of its cosine on 1 of 2 axes was higher than 0.60. To identify the group of homogeneous or atypical observations in this 2-dimensional plane, a PCA between individual replicates was carried out.

**Interpretation of 3-AFC Sensory Test.** The statistical test used to analyze sensory results was the Marascuilo procedure (Wagh and Razvi, 2016) with a confidence level of 95% (risk α = 0.05). The hypothesis tested was the equality of the sets. In this case of nonequality of all 3 salted cheese sets (experimental χ² > 5.99), the Marascuilo procedure enables to make multiple comparisons between all pairs of groups for testing equality among salting levels.

## RESULTS AND DISCUSSION

For each replicate, the mean decimal logarithms of viable cell concentrations and the mean of physicochemical parameters, as well as their SEM on d 0 (demolding) and d 1 (end of yeasting), are given in Table 1. From d 0 to d 1, the mean growth rate and generation time, calculated from the 3 replicates, were 0.07 ± 0.01 h⁻¹ and 9 h 50 min (± 20 min), 0.04 ± 0.01 h⁻¹ and 18 h (±1 h), and 0.11 ± 0.01 h⁻¹ and 6 h 42 min (±20 min) for DH, KL, and GC, respectively. For bacteria, 2 different behaviors were observed. First, AA and CC concentrations on d 1 were lower than on d 0. These bacteria showed mean death
<table><caption>**Table 1.** Mean values and SEM of the decimal logarithm (Log₁₀) of viable cell concentrations in ripening starter and measured physicochemical variables on d 0 (after demolding) and on d 1 (end of yeasting)<fnref n="1" /></caption><thead><tr><th>Time</th><th>Replicate 1</th><th>Replicate 2</th><th>Replicate 3</th><th>Replicates 1–3</th></tr></thead><tbody><tr><td>Day 0</td><td></td><td></td><td></td><td></td></tr><tr><td>[DH]</td><td>5.8 ± 0.1</td><td>5.8 ± 0.1</td><td>5.8 ± 0.1</td><td>5.8 ± 0.1</td></tr><tr><td>[KL]</td><td>7.16 ± 0.04</td><td>7.18 ± 0.06</td><td>7.14 ± 0.04</td><td>7.16 ± 0.04</td></tr><tr><td>[GC]</td><td>4.1 ± 0.2</td><td>4.1 ± 0.2</td><td>4.1 ± 0.2</td><td>4.1 ± 0.2</td></tr><tr><td>[AA]</td><td>5.89 ± 0.07</td><td>5.89 ± 0.08</td><td>5.90 ± 0.09</td><td>5.89 ± 0.08</td></tr><tr><td>[BA]</td><td>6.14 ± 0.06</td><td>6.12 ± 0.08</td><td>6.1 ± 0.1</td><td>6.1 ± 0.1</td></tr><tr><td>[CC]</td><td>6.60 ± 0.06</td><td>6.58 ± 0.06</td><td>6.59 ± 0.09</td><td>6.6 ± 0.1</td></tr><tr><td>[HA]</td><td>6.29 ± 0.06</td><td>6.3 ± 0.1</td><td>6.27 ± 0.07</td><td>6.3 ± 0.1</td></tr><tr><td>[SE]</td><td>5.9 ± 0.2</td><td>5.9 ± 0.1</td><td>5.91 ± 0.05</td><td>5.9 ± 0.1</td></tr><tr><td>DM (%)</td><td>40.8 ± 0.4</td><td>40.9 ± 0.2</td><td>40.9 ± 0.2</td><td>40.9 ± 0.2</td></tr><tr><td>a<sub>w</sub></td><td>0.963 ± 0.002</td><td>0.963 ± 0.002</td><td>0.963 ± 0.002</td><td>0.963 ± 0.002</td></tr><tr><td>pH<sub>rind</sub></td><td>4.67 ± 0.03</td><td>4.66 ± 0.04</td><td>4.68 ± 0.02</td><td>4.67 ± 0.04</td></tr><tr><td>pH<sub>blend</sub></td><td>4.65 ± 0.03</td><td>4.66 ± 0.06</td><td>4.65 ± 0.03</td><td>4.65 ± 0.03</td></tr><tr><td>LO (g kg<sup>-1</sup>)</td><td>17.3 ± 0.3</td><td>17.4 ± 0.4</td><td>17.4 ± 0.3</td><td>17.4 ± 0.3</td></tr><tr><td>LA (g kg<sup>-1</sup>)</td><td>15.6 ± 0.4</td><td>15.8 ± 0.3</td><td>15.4 ± 0.6</td><td>15.6 ± 0.4</td></tr><tr><td>L*</td><td>89.8 ± 0.6</td><td>89.8 ± 0.8</td><td>89.7 ± 0.8</td><td>89.8 ± 0.8</td></tr><tr><td>C*</td><td>13.5 ± 0.6</td><td>13.0 ± 0.9</td><td>13.7 ± 0.5</td><td>13.4 ± 0.9</td></tr><tr><td>h°</td><td>86.8 ± 0.4</td><td>86.8 ± 0.3</td><td>86.8 ± 0.5</td><td>86.8 ± 0.4</td></tr><tr><td>Day 1</td><td></td><td></td><td></td><td></td></tr><tr><td>[DH]</td><td>7.5 ± 0.1</td><td>7.5 ± 0.1</td><td>7.5 ± 0.1</td><td>7.5 ± 0.1</td></tr><tr><td>[KL]</td><td>8.09 ± 0.05</td><td>8.08 ± 0.08</td><td>8.06 ± 0.06</td><td>8.08 ± 0.08</td></tr><tr><td>[GC]</td><td>6.8 ± 0.1</td><td>6.8 ± 0.1</td><td>6.8 ± 0.1</td><td>6.8 ± 0.1</td></tr><tr><td>[AA]</td><td>3.2 ± 0.3</td><td>3.3 ± 0.2</td><td>3.3 ± 0.1</td><td>3.3 ± 0.2</td></tr><tr><td>[BA]</td><td>5.17 ± 0.06</td><td>5.3 ± 0.1</td><td>5.1 ± 0.2</td><td>5.2 ± 0.2</td></tr><tr><td>[CC]</td><td>6.43 ± 0.06</td><td>6.4 ± 0.1</td><td>6.59 ± 0.09</td><td>6.6 ± 0.1</td></tr><tr><td>[HA]</td><td>6.44 ± 0.07</td><td>6.39 ± 0.09</td><td>6.38 ± 0.07</td><td>6.4 ± 0.1</td></tr><tr><td>[SE]</td><td>5.33 ± 0.08</td><td>5.34 ± 0.08</td><td>5.3 ± 0.1</td><td>5.3 ± 0.1</td></tr><tr><td>DM (%)</td><td>46.2 ± 0.2</td><td>46.3 ± 0.2</td><td>46.2 ± 0.2</td><td>46.2 ± 0.2</td></tr><tr><td>a<sub>w</sub></td><td>0.977 ± 0.002</td><td>0.977 ± 0.002</td><td>0.977 ± 0.002</td><td>0.977 ± 0.002</td></tr><tr><td>pH<sub>rind</sub></td><td>4.59 ± 0.04</td><td>4.60 ± 0.03</td><td>4.62 ± 0.07</td><td>4.60 ± 0.04</td></tr><tr><td>pH<sub>blend</sub></td><td>4.56 ± 0.03</td><td>4.56 ± 0.04</td><td>4.56 ± 0.03</td><td>4.56 ± 0.03</td></tr><tr><td>LO (g kg<sup>-1</sup>)</td><td>9.8 ± 0.3</td><td>9.9 ± 0.3</td><td>9.6 ± 0.3</td><td>9.8 ± 0.3</td></tr><tr><td>LA (g kg<sup>-1</sup>)</td><td>19.6 ± 0.5</td><td>19.4 ± 0.2</td><td>19.3 ± 0.4</td><td>19.4 ± 0.4</td></tr><tr><td>L*</td><td>88.4 ± 0.8</td><td>88.6 ± 0.7</td><td>88 ± 1</td><td>88 ± 1</td></tr><tr><td>C*</td><td>14.6 ± 0.7</td><td>15.0 ± 0.6</td><td>14.6 ± 0.9</td><td>14.8 ± 0.8</td></tr><tr><td>h°</td><td>86.2 ± 0.8</td><td>86.3 ± 0.7</td><td>86.2 ± 0.8</td><td>86.2 ± 0.8</td></tr></tbody></table>

rates of 0.11 and 0.04 h⁻<fnref n="1" />, respectively. Second, BA, HA, and SE exhibited no significant change. On d 0 and d 1, the pH<sub>rind</sub>, pH<sub>blend</sub>, L*, C*, and h° were not significantly different. The other chemical composition parameters of the blended cheeses changed significantly (P < 0.01) between d 0 and d 1: cheeses were drier (DM 5.3% higher) with higher a<sub>w</sub> (0.014 increase), lower lactose content (7.6 g kg⁻<fnref n="1" /> decrease), and higher lactate content (3.9 g kg⁻<fnref n="1" /> increase).

## Reproducibility and Repeatability

Whatever the replicate and the ripening time, the reproducibility of cheese samples was studied, and no significant differences in microbiological counts and physicochemical analyzes were found between the 3 cheeses sampled (results not shown). Indeed, the hypotheses of equality were verified with a 99% confidence level. For each replicate, the reproducibility of the microbiological (viable cell counts) and physicochemical measurements

(carbon substrate concentrations, pH<sub>rind</sub>, pH<sub>blend</sub>, a<sub>w</sub>, and color parameters) were studied in relation to ripening time. From the 2-way (replicate, time) ANOVA results, it was apparent that (1) the hypotheses of equality of the changes were satisfied with a confidence level of 99%, and (2) the risks of a false interpretation estimated by the test power were less than 0.02. Thus, the replicates carried out with the same salt level were statistically identical. Consequently, in the following figures and tables, the results were reported as means of the 3 replicate replicates and 3 cheeses per replicate.

## Yeasts

Figure 1 and Table 2 show the viable cell concentrations of the studied yeasts together with their kinetic parameters calculated from the Weibull model. A detailed description and discussion of the observed trends is given in Appendix 1. We found that DH presented a similar growth trend regardless of the salting level (Fig-

<footnote n="1">¹[ ] = mean decimal logarithm of viable cell concentration in cfu g⁻¹.</footnote>
<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

A : *Debaryomyces hansenii*

B : *Kluyveromyces lactis*

C : *Geotrichum candidum*

**Figure 1.** Decimal logarithm of yeast viable cell concentrations throughout ripening (d 1–27) in room phase (12°C, 96% relative humidity) in relation to cheese NaCl concentration. (A) *Debaryomyces hansenii*, (B) *Kluyveromyces lactis*, and (C) *Geotrichum candidum*. S1.0 = 1.0% NaCl (red circles and solid lines); S1.7 = 1.7% NaCl (dark blue squares and short-dash lines); S2.4 = 2.4% NaCl (black triangles and long-dash lines). μ and t_μ = maximal growth rates (d⁻¹) and their associated day calculated from Weibull model; D and t_D = maximal death rate (d⁻¹) of first death phase and its associated day calculated from Weibull model. Lowercase letters (a–c) indicate homogeneous statistical groups from Bonferroni test with 99% confidence level from one-way (NaCl) ANOVA. ***Indicates very significant, *P* < 0.001. Error bars represent SEM.

ure 1A), with a shorter and slower growth phase for the lowest salt level (S1.0). We also found that KL displayed a death phase until d 2, then its concentration remained constant, except for the highest salting level (S2.4), when a second death phase was observed after d 20 (Figure 1B). Additionally, GC showed a growth phase for the lower salting levels (S1.0 and S1.7), but no growth and even a death phase after d 13 for the highest salt level (S2.4; Figure 1C).

## Bacteria

Figure 2 and Table 3 provide the viable cell concentration in the 5 studied bacterial strains, as well as their Weibull modeling. A detailed description and discussion of the observed trends is given in Appendix 2. We observed a growth phase for AA between d 13 and d 25, and for the lowest salt concentration (S1.0), a death phase was additionally observed between d 1 and d 2 (Figure
<table><caption>**Table 2.** Kinetic descriptors of DH, KL, and GC viable cell concentrations throughout the ripening in room phase (12°C, 96% relative humidity) in relation to cheese NaCl concentration (S1.0, S1.7, and S2.4)<fnref n="1" /></caption><thead><tr><th rowspan="2">Kinetic descriptor from<br>Weibull analysis</th><th colspan="3">Salt concentration (%) in smear-type cheese</th></tr><tr><th>S1.0 = 1.0 ± 0.1<sup>2</sup></th><th>S1.7 = 1.7 ± 0.1<sup>2</sup></th><th>S2.4 = 2.4 ± 0.1<sup>2</sup></th></tr></thead><tbody><tr><td>μ<sub>DH</sub> ± SEM (d<sup>-1</sup>)</td><td>0.30 ± 0.02</td><td>0.35 ± 0.02</td><td>0.35 ± 0.02</td></tr><tr><td>t<sub>DH</sub> ± SEM (d)</td><td>3.7 ± 0.1</td><td>4.2 ± 0.1</td><td>4.2 ± 0.1</td></tr><tr><td>df; R; P-value</td><td>159; 0.946; &lt;1 × 10<sup>-7</sup></td><td>159; 0.979; &lt;1 × 10<sup>-7</sup></td><td>159; 0.979; &lt;1 × 10<sup>-7</sup></td></tr><tr><td>[DH] ± SEM on d 27</td><td>8.5 ± 0.1</td><td>9.1 ± 0.2</td><td>9.1 ± 0.1</td></tr><tr><td>KL</td><td></td><td></td><td></td></tr><tr><td>Stationary phase</td><td>d 2–6</td><td>d 2–13</td><td>d 2–20</td></tr><tr><td>Log<sub>10</sub>(X<sub>KL</sub> (cfu g<sup>-1</sup>)) ± SEM on d x</td><td>7.5 ± 0.1 on d 6</td><td>7.5 ± 0.1 on d 13</td><td>7.5 ± 0.1 on d 20</td></tr><tr><td>Death phase</td><td>—</td><td>—</td><td>d 20 – d 27</td></tr><tr><td>D<sub>KL</sub> ± SEM (d<sup>-1</sup>)</td><td>—</td><td>—</td><td>0.08 ± 0.02</td></tr><tr><td>t<sub>KL</sub> ± SEM (d)</td><td>—</td><td>—</td><td>22.0 ± 0.2</td></tr><tr><td>df; R; P-value</td><td>—</td><td>—</td><td>107; 0.782; &lt;6 × 10<sup>-4</sup></td></tr><tr><td>[KL] ± SEM on d 27</td><td>—</td><td>—</td><td>7.1 ± 0.1</td></tr><tr><td>GC</td><td></td><td></td><td></td></tr><tr><td>Growth phase</td><td>d 1–27</td><td>d 1–27</td><td></td></tr><tr><td>μ<sub>GC</sub> ± SEM (d<sup>-1</sup>)</td><td>0.22 ± 0.01</td><td>0.21 ± 0.01</td><td>—</td></tr><tr><td>t<sub>GC</sub> ± SEM (d)</td><td>6.1 ± 0.1</td><td>9.9 ± 0.2</td><td>—</td></tr><tr><td>df; R; P-value</td><td>159; 0.986; &lt;1 × 10<sup>-7</sup></td><td>159; 0.986; &lt;1 × 10<sup>-7</sup></td><td>—</td></tr><tr><td>[GC] ± SEM on d 27</td><td>8.8 ± 0.3</td><td>8.9 ± 0.1</td><td>—</td></tr><tr><td>Death phase</td><td>—</td><td>—</td><td>d 13–27</td></tr><tr><td>D<sub>GC</sub> ± SEM (d<sup>-1</sup>)</td><td>—</td><td>—</td><td>0.06 ± 0.01</td></tr><tr><td>t<sub>GC</sub> ± SEM (d)</td><td>—</td><td>—</td><td>19.7 ± 0.2</td></tr><tr><td>df; R; P-value</td><td>—</td><td>—</td><td>159; 0.921; &lt;1 × 10<sup>-7</sup></td></tr><tr><td>[GC] ± SEM on d 27</td><td>—</td><td>—</td><td>6.0 ± 0.1</td></tr></tbody></table>

2A). We observed a death phase for BA between d 1 and d 6, followed by a growth phase until d 27, with maximum rates dependent on the salt level (Figure 2B). In addition, CC also started with a death phase until d 13, followed by growth (Figure 2C), the highest salting level (S2.4) inducing a slower growth. We found that HA exhibited growth until d 27 for the lower salting levels (S1.0 and S1.7), but 2 death phases between d 1 and 2 and d 13 and 27 for S2.4 (Figure 2D). Lastly, SE was not affected by the salt level and presented a growth phase between d 6 and d 27.

## Summary of Influence of Salt on Microbial Growth During Ripening

In our study, reducing or increasing the salt level by 40% on Munster-type cheeses led to a disturbance of the microbial balance in comparison to control (S1.7) cheeses. Salt effects on yeasts were species- and strain-dependent (Lages et al., 1999). Specifically, DH was stimulated by salt, and KL was not affected by it, whereas GC was not inhibited at cheese salt levels at or below

1.7%, but showed a significant inhibition in 2.4% salted cheeses.

Regardless of the cheese salting level, the death or stationary phases observed for 5 bacteria could be explained during the first days of ripening (d 1–6) by the yeast growth disturbance and their acid sensitivity. We found that SE appeared to be insensitive to salt in the studied range, contrary to the 4 other bacteria. Indeed, CC and HA exhibited a salt insensitivity for S1.0 and S1.7. For S2.4, CC growth kinetics were weaker for all ripening times, whereas HA concentrations remained constant or decreased. The AA and BA kinetics exhibited a growth maximum for S1.7.

## Physicochemical and Biochemical Indicators

The time change in DM content, a<sub>w</sub>, pH<sub>rind</sub>, pH<sub>blend</sub>, carbon substrate concentrations, T<sub>UR</sub>, and color parameters (L*, C*, and h°) versus ripening time (d 1–27) and their Weibull modeling are shown in Figure 3 and Table 4.

**Dry Matter Content.** No significant differences in DM kinetics were observed between S1.0 and S1.7 cheeses

<footnote n="1">¹RH = relative humidity; μ = maximal growth rate (d⁻¹) calculated from Weibull model; tμ = day associated to μ; D = maximal death rate (d⁻¹) calculated from Weibull model; tD = time (d) associated with D; — = not applicable; [ ] = decimal logarithm of maximal concentration (cfu g⁻¹); R = Weibull model determination coefficient; P-value = probability to reject the Weibull model (if P < 0.001, the model is highly statistically significant).</footnote>

<footnote n="2">²With respect to total cheese mass on d 0 (after demolding).</footnote>

<footnote n="3">³With respect to water mass in cheese on d 0 (after demolding).</footnote>
<figure><img src="image_6.png" /></figure>

A: *Arthrobacter arilaitensis*

B: *Brevibacterium aurantiacum*

C: *Corynebacterium casei*

D: *Hafnia alvei*

E: *Staphylococcus equorum*

**Figure 2.** Decimal logarithm of viable cell concentrations throughout the ripening (d 1–27) in ripening room (12°C, 96% relative humidity) in relation to cheese NaCl concentration. (A) *Arthrobacter arilaitensis*, (B) *Brevibacterium aurantiacum*, (C) *Corynebacterium casei*, (D) *Hafnia alvei*, and (E) *Staphylococcus equorum*. S1.0 = 1.0% NaCl (red circle and solid line); S1.7 = 1.7% NaCl (dark blue square and short-dash line); S2.4 = 2.4% NaCl (black triangle and long-dash line). µ = maximal growth rates (d⁻¹) calculated from Weibull model; tµ = day for which µ was obtained; D = maximal death rate (d⁻¹) calculated from the death phase of the Weibull model; tD = day for which D was obtained. Lowercase letters (a–c) indicate homogeneous statistical groups from Bonferroni test with 99% confidence level from one-way (NaCl) ANOVA. ***Indicates very significant, P < 0.001. Error bars represent SEM.
<table><caption>**Table 3.** Kinetic descriptors of ripening bacteria viable cell concentrations (cfu·g⁻<fnref n="1" />·d⁻<fnref n="1" />) in decimal logarithm throughout the ripening in room (12°C, 96% relative humidity) in relation to cheese NaCl concentration (S1.0, S1.7, and S2.4)<fnref n="1" /></caption><thead><tr><th rowspan="2">Item</th><th colspan="3">AA</th><th colspan="3">BA</th><th colspan="3">CC</th><th colspan="3">HA</th><th colspan="3">SE</th></tr><tr><th>S1.0</th><th>S1.7</th><th>S2.4</th><th>S1.0</th><th>S1.7</th><th>S2.4</th><th>S1.0</th><th>S1.7</th><th>S2.4</th><th>S1.0</th><th>S1.7</th><th>S2.4</th><th>S1.0</th><th>S1.7</th><th>S2.4</th></tr></thead><tbody><tr><td>Station phase (d)</td><td>2-13</td><td>1-13</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Growth phase (d)</td><td>13-27</td><td>13-27</td><td>6-27</td><td>—</td><td>—</td><td>—</td><td>13-27</td><td>13-27</td><td>13-27</td><td>13-27</td><td>13-27</td><td>13-27</td><td>13-27</td><td>13-27</td><td>13-27</td></tr><tr><td>μ ± SEM (d⁻<fnref n="1" />)</td><td>0.55 ± 0.04</td><td>0.24 ± 0.02</td><td>0.25 ± 0.03</td><td>0.215 ± 0.005</td><td>0.57 ± 0.02</td><td>0.209 ± 0.005</td><td>0.66 ± 0.04</td><td>0.63 ± 0.03</td><td>0.20 ± 0.02</td><td>0.101 ± 0.004</td><td>0.098 ± 0.004</td><td>0.098 ± 0.004</td><td>0.24 ± 0.02</td><td>0.21 ± 0.02</td><td>0.22 ± 0.02</td></tr><tr><td>tₐ ± SEM (d)</td><td>19.3 ± 0.2</td><td>19.8 ± 0.1</td><td>20.0 ± 0.1</td><td>19.4 ± 0.1</td><td>18.4 ± 0.1</td><td>24.7 ± 0.5</td><td>19.4 ± 0.2</td><td>19.4 ± 0.2</td><td>20.3 ± 0.1</td><td>13.8 ± 0.2</td><td>14.1 ± 0.2</td><td>14.1 ± 0.2</td><td>20.7 ± 0.5</td><td>20.6 ± 0.5</td><td>20.6 ± 0.5</td></tr><tr><td>df</td><td>132</td><td>132</td><td>132</td><td>105</td><td>105</td><td>105</td><td>78</td><td>78</td><td>78</td><td>158</td><td>158</td><td>158</td><td>105</td><td>105</td><td>105</td></tr><tr><td>R</td><td>0.995</td><td>0.983</td><td>0.982</td><td>0.997</td><td>0.997</td><td>0.997</td><td>0.994</td><td>0.996</td><td>0.993</td><td>0.986</td><td>0.986</td><td>0.986</td><td>0.997</td><td>0.995</td><td>0.995</td></tr><tr><td>P-value</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td></tr><tr><td>[cfu] ± SEM d 27</td><td>4.3 ± 0.2</td><td>5.3 ± 0.1</td><td>4.7 ± 0.1</td><td>7.03 ± 0.04</td><td>7.95 ± 0.04</td><td>5.98 ± 0.04</td><td>7.4 ± 0.1</td><td>7.3 ± 0.1</td><td>5.8 ± 0.2</td><td>7.8 ± 0.2</td><td>7.7 ± 0.2</td><td>7.2 ± 0.2</td><td>7.5 ± 0.2</td><td>7.5 ± 0.3</td><td>7.5 ± 0.3</td></tr><tr><td>Death phase (d)</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>1-13</td><td>1-13</td><td>1-13</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>D ± SEM (d⁻<fnref n="1" />)</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>0.27 ± 0.02</td><td>0.274 ± 0.008</td><td>0.38 ± 0.02</td><td>—</td><td>—</td><td>—</td><td>0.45 ± 0.05</td><td>—</td><td>—</td></tr><tr><td>tₐ ± SEM (d)</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>1.130 ± 0.09</td><td>1.13 ± 0.05</td><td>1.13 ± 0.06</td><td>—</td><td>—</td><td>—</td><td>19.6 ± 0.3</td><td>—</td><td>—</td></tr><tr><td>df</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>132</td><td>132</td><td>132</td><td>—</td><td>—</td><td>—</td><td>158</td><td>—</td><td>—</td></tr><tr><td>R</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>0.993</td><td>0.993</td><td>0.993</td><td>—</td><td>—</td><td>—</td><td>0.992</td><td>—</td><td>—</td></tr><tr><td>P-value</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>&lt;10⁻⁷</td><td>—</td><td>—</td><td>—</td><td>&lt;10⁻⁷</td><td>—</td><td>—</td></tr><tr><td>[cfu] ± SEM d 13</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>4.45 ± 0.05</td><td>4.5 ± 0.1</td><td>4.0 ± 0.1</td><td>—</td><td>—</td><td>—</td><td>4.6 ± 0.2²</td><td>—</td><td>—</td></tr></tbody></table>

(Figure 3A and Table 4). For these 2 salt levels, a slow increase of DM was observed with the same maximal increase rate. In contrast, S2.4 displayed a very strong increase in DM. For example, the DM of S2.4 was 45% higher on d 27 than for the other salt levels. These results are somewhat surprising because NaCl is expected to increase the amount of bonded and coordinated water and reduce evaporation. They may be explained by the absence of GC growth in the S2.4 condition, as GC development may reduce water loss (Dugat-Bony et al., 2016).

**Hardness on Day 27.** The S1.0 and S1.7 cheeses had the same hardness at the end of ripening (3.0 N), but S2.4 was much harder (54 N; Table 4). Although NaCl can contribute to a modification of mineral equilibria of caseins and in consequence decrease hardness, for S2.4 this effect was likely overbalanced by a much higher DM, higher water loss and lower a<sub>w</sub>, as well as by a reduced development of ripening microorganisms, especially GC and some bacteria, and hence a lower proteolysis and lipolysis.

**Water Activity.** No significant differences in a<sub>w</sub> kinetics were observed for S1.0 and S1.7. For these 2 cheese salt levels, a slow decrease of a<sub>w</sub> was observed with a maximal decrease rate of −1.5 × 10⁻⁴ d⁻<fnref n="1" /> occurring at 24.4 ± 0.2 d, and their water activity on d 27 was 0.972 ± 0.002. On the contrary, the water activity of S2.4 was strongly affected, reaching 0.902 ± 0.003, confirming a significant free water loss.

Among various actions on cheeses, salting provides additional drainage (measured by DM) and contributes greatly to regulating the cheese water activity (Mietton and Chablain, 2018). The higher the salt level in the soft cheese, the harder the finished cheese will be. Moreover, salting has the effect of reducing water activity, thus suppressing microbial growth and directing the enzymatic activities of ripening microorganisms (Richoux and Mietton, 2018). However, no significant differences in DM, hardness, and water activity were observed for S1.0 compared with the control S1.7. A possible explanation is that water production related to GC respiration could balance water losses due to the cheese salting level, as also shown by Dugat-Bony et al. (2016). For S2.4, water losses were higher from the beginning of ripening (d 2) and could not be balanced by GC respiration due to the lack of development of this yeast.

**pH of the Rind.** As shown in Figure 3C and Table 4, the pH<sub>rind</sub> kinetics showed significantly different trends. From d 20 to d 27, the pH<sub>rind</sub> values of S1.0 and S1.7 were statistically equal, but the increase rate of S1.7 pH<sub>rind</sub> was about 1.2 times higher, and the final pH was reached around 2 d earlier than those of S1.0. The pH<sub>rind</sub> increase rate of S2.4 was about 1.9 times lower, and the final value was reached around 4 d later than for S1.7. The pH<sub>rind</sub> of S1.7 showed the fastest deacidification.

<footnote n="1">¹RH = relative humidity; μ = maximal growth rate (d⁻¹); calculated from Weibull model; tₐ = day associated with μ; [] = decimal logarithm of maximal concentration mean (cfu·g⁻¹); D and tₐ = maximal death rate (d⁻¹) calculated from Weibull model and its time of occurrence (d); — = not applicable</footnote>

<footnote n="2">²On d 27.</footnote>
<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>

**Figure 3.** Physicochemical variables throughout ripening (d 1 to d 27) in room phase (12°C, 96% relative humidity) in relation to cheese salt concentration. (A) Dry matter content, (B) water activity, (C) pH of the rind, (D) blended cheese pH, (E) lactose concentration (g kg⁻¹), (F) lactate concentration (g kg⁻¹), (G) underrind thickness, (H) lightness, (I) saturation, and (J) hue angle. S1.0 = 1.0% NaCl (red circle and solid line); S1.7 = 1.7% NaCl (dark blue square and short-dash line); S2.4 = 2.4% NaCl (black triangle and long-dash line). Positive V = maximal increase rates (unit per day) and negative V = maximal decreasing rates (unit per day) calculated from Weibull model; t<sub>V</sub> = day associated with V; C = maximal consumption rate (g kg⁻¹ d⁻¹) calculated from Weibull model for LO and LA substrates; t<sub>C</sub> = day associated with C. Lowercase letters (a-c) indicate homogeneous statistical groups from Bonferroni test with 99% confidence level from one-way (NaCl) ANOVA. ***Indicates very significant, *P* < 0.001. Error bars represent SEM.
<figure><img src="image_13.png" /><figcaption>**Figure 3 (Continued).** Physicochemical variables throughout ripening (d 1 to d 27) in room phase (12°C, 96% relative humidity) in relation to cheese salt concentration. (A) Dry matter content, (B) water activity, (C) pH of the rind, (D) blended cheese pH, (E) lactose concentration (g kg⁻¹), (F) lactate concentration (g kg⁻¹), (G) underrind thickness, (H) lightness, (I) saturation, and (J) hue angle. S1.0 = 1.0% NaCl (red circle and solid line); S1.7 = 1.7% NaCl (dark blue square and short-dash line); S2.4 = 2.4% NaCl (black triangle and long-dash line). Positive V = maximal increase rates (unit per day) and negative V = maximal decreasing rates (unit per day) calculated from Weibull model; t<sub>v</sub> = day associated with V; C = maximal consumption rate (g kg⁻¹ d⁻¹) calculated from Weibull model for LO and LA substrates; t<sub>c</sub> = day associated with C. Lowercase letters (a–c) indicate homogeneous statistical groups from Bonferroni test with 99% confidence level from one-way (NaCl) ANOVA. ***Indicates very significant, P < 0.001. Error bars represent SEM.</figcaption></figure>

The pH<sub>rind</sub> kinetics, measuring the deacidification phenomenon, were clearly dependent on the cheese salt level. For reduced-salt cheeses, a delay of ~2 d in the deacidification was observed in comparison to the control. This could be explained by DH behavior, the main deacidification yeast in soft smear cheeses (Leclercq-Perlat et al., 2000), which had been found to develop less in S1.0 than in control cheeses. For S2.4, this could be explained by the slowing down of carbonaceous substrates diffusion phenomena due to cheese water losses measured by DM.

**pH of Blended Cheese.** As shown in Figure 3D and Table 4, the pH<sub>blend</sub> kinetics showed significant differences after 12 d of ripening. Indeed, for S1.0, the pH<sub>blend</sub> increase was 1.7 and 2 times slower than for S1.7 and S2.4, respectively. On d 27, the higher the cheese salt content, the lower the pH<sub>Blend</sub>. The pH<sub>blend</sub> measures lactate consumption chiefly by ripening yeasts (DH and GC) and alkaline peptides and ammonia produced by GC and some bacteria. In our study, microbial kinetics are likely to explain observed differences in pH<sub>blend</sub>.
<table><caption>**Table 4.** Kinetic descriptors of physicochemical variables throughout ripening in room (12°C, 96% RH) in relation to cheese NaCl concentration (S1.0, S1.7, and S2.4)</caption><thead><tr><th rowspan="2">Kinetic descriptor from<br>Weibull analysis</th><th colspan="3">Salt concentration (%) in smear-ripened type cheese</th></tr><tr><th>S1.0 = 1.0 ± 0.1<sup>2</sup></th><th>S1.7 = 1.7 ± 0.1<sup>2</sup></th><th>S2.4 = 2.4 ± 0.1<sup>2</sup></th></tr></thead><tbody><tr><td>DM content (%)</td><td></td><td></td><td></td></tr><tr><td>V<sub>DM</sub> ± SEM (% d<sup>-1</sup>)</td><td>0.105 ± 0.007</td><td>0.105 ± 0.007</td><td>1.44 ± 0.03</td></tr><tr><td>t<sub>DM</sub> ± SEM (d)</td><td>10.3 ± 0.2</td><td>10.3 ± 0.2</td><td>16.3 ± 0.2</td></tr><tr><td>df; R; P-value</td><td>159; 0.917; &lt;10<sup>-7</sup></td><td>159; 0.917; &lt;10<sup>-7</sup></td><td>159; 0.992; &lt;10<sup>-7</sup></td></tr><tr><td>DM ± SEM on d 27 (%)</td><td>49.2 ± 0.4</td><td>49.6 ± 0.4</td><td>72 ± 1</td></tr><tr><td>Hardness (N)</td><td></td><td></td><td></td></tr><tr><td>Hardness on d 27</td><td>3.2 ± 0.3</td><td>3.2 ± 0.2</td><td>52 ± 4</td></tr><tr><td>Water activity a<sub>w</sub></td><td></td><td></td><td></td></tr><tr><td>V<sub>aw</sub> ± SEM (d<sup>-1</sup>)</td><td>(-1.5 ± 0.1) × 10<sup>-4</sup></td><td>(-4.7 ± 0.1) × 10<sup>-4</sup></td><td>(-6.4 ± 0.1) × 10<sup>-3</sup></td></tr><tr><td>t<sub>aw</sub> ± SEM (d)</td><td>24.5 ± 0.2</td><td>24.4 ± 0.2</td><td>21.2 ± 0.2</td></tr><tr><td>df; R; P-value</td><td>132; 0.801; &lt;10<sup>-7</sup></td><td>132; 0.937; &lt;10<sup>-7</sup></td><td>132; 0.998; &lt;10<sup>-7</sup></td></tr><tr><td>a<sub>w</sub> ± SEM on d 27</td><td>0.972 ± 0.005</td><td>0.970 ± 0.005</td><td>0.902 ± 0.005</td></tr><tr><td>pH of the rind</td><td></td><td></td><td></td></tr><tr><td>V<sub>pHrind</sub> ± SEM (d<sup>-1</sup>)</td><td>0.372 ± 0.006</td><td>0.42 ± 0.02</td><td>0.226 ± 0.006</td></tr><tr><td>t<sub>pHrind</sub> ± SEM (d)</td><td>10.2 ± 0.2</td><td>8.0 ± 0.2</td><td>12.0 ± 0.2</td></tr><tr><td>df; R; P-value</td><td>537; 0.996; &lt;10<sup>-7</sup></td><td>537; 0.998; &lt;10<sup>-7</sup></td><td>537; 0.986; &lt;10<sup>-7</sup></td></tr><tr><td>pH<sub>rind</sub> ± SEM on d 27</td><td>7.49 ± 0.04</td><td>7.49 ± 0.03</td><td>7.1 ± 0.1</td></tr><tr><td>pH of the blended cheese</td><td></td><td></td><td></td></tr><tr><td>V<sub>pHblend</sub> ± SEM (d<sup>-1</sup>)</td><td>0.18 ± 0.02</td><td>0.11 ± 0.01</td><td>0.090 ± 0.006</td></tr><tr><td>t<sub>pHblend</sub> ± SEM (d)</td><td>14.5 ± 0.2</td><td>14.8 ± 0.2</td><td>12.6 ± 0.2</td></tr><tr><td>df; R; P-value</td><td>321; 0.985; &lt;10<sup>-7</sup></td><td>321; 0.987; &lt;10<sup>-7</sup></td><td>321; 0.985; &lt;10<sup>-7</sup></td></tr><tr><td>pH<sub>blend</sub> ± SEM on d 27</td><td>6.7 ± 0.1</td><td>6.28 ± 0.08</td><td>5.8 ± 0.1</td></tr><tr><td>Lactose content (g kg WC<sup>-1</sup> d<sup>-1</sup>)</td><td></td><td></td><td></td></tr><tr><td>C<sub>LO</sub> ± SEM (g kg<sup>-1</sup> d<sup>-1</sup>)</td><td>5.0 ± 0.4</td><td>1.7 ± 0.1</td><td>1.5 ± 0.1</td></tr><tr><td>t<sub>LO</sub> ± SEM (d)</td><td>1.5 ± 0.1</td><td>1.5 ± 0.1</td><td>1.5 ± 0.1</td></tr><tr><td>df; R; P-value</td><td>213; 0.987; &lt;10<sup>-7</sup></td><td>213; 0.997; &lt;10<sup>-7</sup></td><td>213; 0.996; &lt;10<sup>-7</sup></td></tr><tr><td>Lactate content (g kg WC<sup>-1</sup> d<sup>-1</sup>)</td><td></td><td></td><td></td></tr><tr><td>C<sub>LA</sub> ± SEM (g kg<sup>-1</sup> d<sup>-1</sup>)</td><td>3.6 ± 0.2</td><td>3.7 ± 0.2</td><td>2.6 ± 0.2</td></tr><tr><td>t<sub>LA</sub> ± SEM (d)</td><td>4.0 ± 0.2</td><td>4.0 ± 0.2</td><td>4.0 ± 0.2</td></tr><tr><td>df; R; P-value</td><td>249; 0.999; &lt;10<sup>-7</sup></td><td>249; 0.999; &lt;10<sup>-7</sup></td><td>249; 0.994; &lt;10<sup>-7</sup></td></tr><tr><td>LA ± SEM on d 27 (g kg<sup>-1</sup>)</td><td>0.39 ± 0.03</td><td>0.41 ± 0.03</td><td>1.92 ± 0.05</td></tr><tr><td>Underrind thickness (%)</td><td></td><td></td><td></td></tr><tr><td>V<sub>TUR</sub> ± SEM (%/d)</td><td>1.7 ± 0.1</td><td>1.01 ± 0.07</td><td>0.74 ± 0.06</td></tr><tr><td>t<sub>TUR</sub> ± SEM (d)</td><td>16.0 ± 0.3</td><td>13.5 ± 0.2</td><td>12.0 ± 0.3</td></tr><tr><td>df; R; P-value</td><td>267; 0.989; &lt;10<sup>-7</sup></td><td>267; 0.984; &lt;10<sup>-7</sup></td><td>267; 0.980; &lt;10<sup>-7</sup></td></tr><tr><td>T<sub>UR</sub> ± SEM (%) on d 27</td><td>27 ± 1</td><td>18 ± 1</td><td>14 ± 1</td></tr><tr><td>L*</td><td></td><td></td><td></td></tr><tr><td>V<sub>L*</sub> ± SEM (d<sup>-1</sup>)</td><td>-0.18 ± 0.08</td><td>-0.6 ± 0.1</td><td>-1.2 ± 0.02</td></tr><tr><td>t<sub>L*</sub> ± SEM (d)</td><td>3.5 ± 0.1</td><td>3.5 ± 0.1</td><td>3.90 ± 0.09</td></tr><tr><td>df; R; P-value</td><td>213; 0.776; 3.3 × 10<sup>-6</sup></td><td>223; 0.960; &lt;10<sup>-7</sup></td><td>213; 0.978; &lt;10<sup>-7</sup></td></tr><tr><td>L* ± SEM on d 27</td><td>86 ± 1</td><td>83 ± 1</td><td>77.6 ± 0.7</td></tr><tr><td>C*</td><td></td><td></td><td></td></tr><tr><td>V<sub>C*</sub> ± SEM (d<sup>-1</sup>)</td><td>—</td><td>0.31 ± 0.04</td><td>0.8 ± 0.1</td></tr><tr><td>t<sub>C*</sub> ± SEM (d)</td><td>—</td><td>18.2 ± 0.2</td><td>13.4 ± 0.2</td></tr><tr><td>df; R; P-value</td><td>—</td><td>249; 0.941; &lt;10<sup>-7</sup></td><td>249; 0.975; &lt;10<sup>-7</sup></td></tr><tr><td>C* ± SEM on d 27</td><td>15.5 ± 0.9</td><td>21 ± 1</td><td>26.1 ± 0.5</td></tr><tr><td>h°</td><td></td><td></td><td></td></tr><tr><td>V<sub>h°</sub> ± SEM (°.d<sup>-1</sup>)</td><td>+0.46 ± 0.01</td><td>0.00 ± 0.01</td><td>-0.41 ± 0.02</td></tr><tr><td>t<sub>h°</sub> ± SEM (d)</td><td>8.9 ± 0.2</td><td>—</td><td>11.2 ± 0.2</td></tr><tr><td>df; R; P-value</td><td>231; 0.811; 1.6 × 10<sup>-3</sup></td><td>231; 0.829; &lt;10<sup>-7</sup></td><td>231; 0.976; &lt;10<sup>-7</sup></td></tr><tr><td>h° ± SEM on d 27</td><td>88.0 ± 0.8</td><td>85.5 ± 0.8</td><td>79.6 ± 0.7</td></tr></tbody></table>

<footnote n="1">¹RH = relative humidity; V = maximal rates (unit per day) calculated from Weibull model; t<sub>V</sub> = day for which V was obtained; C<sub>LO</sub> and C<sub>LA</sub> = maximal consumption rates of LO and LA, respectively (g kg<sup>-1</sup> d<sup>-1</sup>); t<sub>CLO</sub> and t<sub>CLA</sub> = days associated with C<sub>LO</sub> and C<sub>LA</sub>.</footnote>

<footnote n="2">²With respect to total cheese mass on d 0 (after demolding).</footnote>

<footnote n="3">³With respect to water mass on d 0 (after demolding).</footnote>
**Lactose Changes in Blended Cheese.** Lactose concentration kinetics and their Weibull models showed significant differences between S1.0 and the 2 higher cheese salt contents, for which no statistically significant difference was observed (Figure 3E, Table 4). The lactose concentrations of S1.0 decreased around 3 times faster than for the other 2 cheese sets. They were null on d 6 for S1.0 and on d 16 for S1.7 and S2.4.

**Lactate Changes in Blended Cheese.** No statistically significant differences in lactate concentration kinetics were observed between S1.0 and S1.7, whereas significant differences appeared with S2.4 (Figure 3F, Table 4). The lactate concentrations of S1.0 and S1.7 decreased around twice as fast as S2.4. The lactate concentration was $0.4 \text{ g kg}^{-1}$ after d 13 for S1.0 and S1.7, whereas it remained nearly 3.75 times higher after d 16 for S2.4.

Carbon substrate metabolization takes place in the aqueous phase of the cheese. Lactose is assimilated by LAB and mainly metabolized by KL, consuming first lactose then lactate. DH breaks these 2 carbon substrates down at the same time, but at different rates (Leclercq-Perlat et al., 2000). Ripening bacteria can also metabolize these 2 carbon substrates. However, from our results, the KL influence on lactose and lactate concentrations was not readily apparent. Lactose was metabolized faster in reduced-salt cheeses that also had a higher moisture content. This could be due to a better uptake of this substrate by the ripening bacteria. In this study, the changes in lactate concentrations could be explained by differences in GC, DH and ripening bacteria growths and could be directly related to cheese water activity and dry matter content as further investigated in the correlation analysis below.

**Underrind Thickness.** As shown in Figure 3G, the $T_{UR}$ kinetics and their Weibull models showed significant differences after 6 d of ripening (Figure 3G and Table 4): The lower the cheese salt content, the thicker the creamy underrind. Moreover, on d 27, $T_{UR}$ was around twice as thick, and its rate of increase was approximately twice as high for S1.0 than for S2.4. However, the underrind consistency was also influenced by the cheese salt level: The underrind appeared runny for S1, soft for S1.7, and very dry for S2.4 Munster.

The underrind thickness provides information on the overall proteolysis and lipolysis of the cheeses (Leclercq-Perlat et al., 2012, 2015). The underrind begins to grow when proteins, and to a lesser degree lipids, begin to be used by ripening microorganisms near the rind (Leclercq-Perlat et al., 2012). From our results, the creamy underrind thickness and consistency seemed to be mostly related to GC growth. Indeed, when GC predominates on a cheese rind, it determines the texture, cohesiveness, and thickness of the rind (Marcellino et al., 2001). Among

the strains used, GC is the most proteolytic and lipolytic species (Boutrou and Guéguen, 2005). In addition, GC growth consumes lactate and increases cheese pH, which enables ripening bacteria development and in turn enhances proteolysis. Moreover, proteolysis takes place in the aqueous phase of cheeses, so if the water activity is too low (as in S2.4), proteolysis may be limited.

**Color of the Rind.** Values for L* (Figure 3H), C* (Figure 3I), and $h^\circ$ (Figure 3J) kinetics and their Weibull models showed significant differences after 2 d of ripening.

**Lightness.** The higher the salt content, the darker the cheese (Figure 3H, Table 4). Indeed, the maximum decreasing rate of L* was around 3 times lower for S1.0 than for S1.7, which in turn appeared to be around twice as low as for S2.4. On d 27, L* was significantly related to the salt level of cheeses.

**Metric Saturation.** From Figure 3I, the higher the salt content, the greater the metric saturation (Table 4). Indeed, for S1.0, regardless of the ripening time (d 1–27), no change in C* was observed. The maximum increasing rate was around 1.5 times higher for S2.4 than for S1.7. On d 27, S2.4 ($C^* = 26$) appeared slightly more intense than S1.7% ($C^* = 21$).

**Hue Angle.** As shown in Figure 3J, the higher the cheese salt content, the lower the hue angle (Table 4). Indeed, no change in hue angle of S1.7, corresponding to cream color, was observed from d 6 to d 27. For S1.0, the hue angle maximum change rate was positive and occurred around d 9, corresponding to a color change from cream to yellow (d 13–27). For S2.4, the maximum hue angle change rate was negative and occurred on d 11, corresponding to a color change from cream to orange obtained after d 20.

The rind color is one of the main characteristics that consumers appreciate in a cheese such as Munster, for which the quality of the color is linked to the ripening microbial flora (Gagnaire et al., 2018). This color is often associated with the pigmentation of the ripening bacteria (mainly BL and AA). However, the interactions between some ripening bacteria and deacidification yeast (DH) can modify the color metric saturation ($C^*$; Leclercq-Perlat et al., 2004b). Moreover, GC is mainly responsible for the appearance of the cheese, imparting a uniform, white-cream, velvety coat to the surface (Boutrou and Guéguen, 2005). Growth of GC could explain S1.0 having a light cream color characterized by an achromatic intensity ($C^* < 16$) and a hue angle close to the +b axis (i.e., yellow). The absence of GC in S2.4 also explained the rind color observed: The rind color due to the other microorganisms was no longer hidden by the GC mycelium coat and appeared orange. Only the S1.7 had the targeted light cream color of Munster cheeses.
<table><caption>**Table 5.** Results of panel sensory analyses of the Pearson's χ² test and Marascuilo procedure<fnref n="1" /></caption><thead><tr><th rowspan="2">Characteristic</th><th rowspan="2">Pearson test<br>χ² value</th><th colspan="3">Marascuilo procedure<fnref n="1" /></th></tr><tr><th>S1.0</th><th>S1.7</th><th>S2.4</th></tr></thead><tbody><tr><td>Odor</td><td>9.1</td><td>A</td><td>B</td><td>B</td></tr><tr><td>Color</td><td>28.9</td><td>B</td><td>B</td><td>A</td></tr><tr><td>Firmness</td><td>40.0</td><td>B</td><td>B</td><td>A</td></tr></tbody></table>

¹If χ² value is higher than 5.99, the null hypothesis is rejected with a confidence level of 95%. The Marascuilo procedure allows us to classify the salted cheeses in classes. Class A includes the cheese that was significantly different from the 2 others (class B).

## Influence of Cheese Salt Content Assessed by Sensory Analysis

From the sensory analysis (Table 5), the statistical χ² test showed that the cheeses salted at the different salt levels were not equal at a 95% confidence level. The Marascuilo procedure showed that S1.0 cheeses were significantly perceived as more intense from an aromatic point of view, whereas S2.4 was significantly perceived as the most colored and firm.

The driest and hardest textures were typical of S2.4 cheeses, which were qualified by panelists as the least aromatic, the most colored, and with a thin and hard underrind. In contrast, S1.0 cheeses were assessed by panelists as the most aromatic, least colored and with a runny underrind. The S1.7 cheeses were evaluated by panelists as the closest to S1.0 in terms of coloring and firmness, and the closest to S2.4 in terms of aroma. The control cheeses (S1.7) were the only ones to have the soft and creamy underrind typical of Munster-type cheese.

Our panel results were in agreement with previously published sensory analyses (Abraham et al., 2007). Indeed, the lower the salt concentration in cheeses, the more ripening enzymes are active, the more proteolysis is advanced, and the firmness is lower. Moreover, the

higher the moisture content in cheeses, the more active the enzymes (Gagnaire et al., 2018); consequently, the creamy underrind was more developed and assessed as runny by the panelists for S1.0, whereas they evaluated it as thin and hard for S2.4. Only for S1.7, the panelists judged the underrind as soft and creamy, corresponding to the texture and consistency of target Munster.

## Relationships Between Microorganism Growth and Physicochemical Variables

Table 6 shows the part of the correlation matrix established between microorganism viable cell concentrations and physicochemical variables throughout the ripening (d 1–27) for which correlations were found significant at a 99% confidence level. All significant correlation coefficients were higher than 0.60.

As an example, DH viable cell concentration was positively linked to pH of rind, pH<sub>blend</sub> and color intensity as well as negatively related to L*, lactate concentration (LA), and lactose concentration (LO). Similar conclusions for the viable cell concentrations of all studied microorganisms can be drawn from Table 6.

Principal component analyses made it possible to visualize the relationships between the microorganism viable cell concentration and physicochemical measurements as well as the cheese salting levels (Figure 4). We carried out PCA on the 8 microorganism viable cell concentrations as active variables and the 10 physicochemical variables as supplementary ones. The first 2 principal components explained 81.0% of the total variance.

As shown in Figure 4A, factor axis 1 captured the time change of cheeses during ripening: Positive values correspond to DH, GC, AA, BA, SE growth, pH<sub>rind</sub>, pH<sub>blend</sub>, T<sub>UR</sub>, DM, and C* increase, and negative values correspond to KL death, LO, LA, L*, a<sub>w</sub>, and h° decrease. Factor axis 2 denoted the salt effect: Positive values cor-

<table><caption>**Table 6.** Correlation matrix between physicochemical variables and microbiological variables according to a Pearson correlation matrix test with 99% confidence level</caption><thead><tr><th rowspan="2">Physicochemical<br>variable</th><th colspan="8">Decimal logarithm of microorganism viable cell concentration</th></tr><tr><th>DH</th><th>KL</th><th>GC</th><th>AA</th><th>BA</th><th>CC</th><th>HA</th><th>SE</th></tr></thead><tbody><tr><td>DM (%)</td><td>—<sup>1</sup></td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>-0.68</td><td>—</td></tr><tr><td>a<sub>w</sub></td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>0.74</td><td>—</td></tr><tr><td>pH<sub>rind</sub></td><td>0.78</td><td>-0.72</td><td>0.63</td><td>—</td><td>0.61</td><td>—</td><td>—</td><td>0.71</td></tr><tr><td>pH<sub>blend</sub></td><td>0.61</td><td>-0.81</td><td>0.64</td><td>0.64</td><td>0.73</td><td>—</td><td>—</td><td>0.81</td></tr><tr><td>L*</td><td>-0.84</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>-0.61</td></tr><tr><td>C*</td><td>0.73</td><td>—</td><td>—</td><td>0.63</td><td>—</td><td>—</td><td>—</td><td>0.70</td></tr><tr><td>h°</td><td>—</td><td>—</td><td>0.61</td><td>—</td><td>—</td><td>—</td><td>0.76</td><td>—</td></tr><tr><td>LA (g kg<sup>-1</sup>)</td><td>-0.89</td><td>0.63</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>-0.61</td></tr><tr><td>LO (g kg<sup>-1</sup>)</td><td>-0.85</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>T<sub>UR</sub> (%)</td><td>—</td><td>-0.82</td><td>0.65</td><td>0.61</td><td>0.72</td><td>—</td><td>—</td><td>0.79</td></tr></tbody></table>

<footnote n="1">¹— = not significant at P = 0.01 level.</footnote>
<figure><img src="image_14.png" /><figcaption>**Figure 4.** Principal component analysis plots of NaCl concentration replicates on the factor axes 1 and 2. (A) Factor loadings between microorganism concentration means and physicochemical variable means. (B) Factorial map of scores where sample code was NaCl concentration and sampling day. LO = lactose concentration (g kg⁻¹); LA = lactate concentration (g kg⁻¹). Red circle and solid line indicate 1.0% NaCl; dark blue square and short-dash line indicate 1.7% NaCl; black triangle and long-dash line indicate 2.4% NaCl. Variables outside the dashed box have loadings >0.6. [] = mean decimal logarithm of viable cell concentration in cfu g⁻¹.</figcaption></figure>

respond to variables favored by low salt content, such as GC, HA, and BA growth and $a_w$, L*, and h° increase, whereas negative values correspond to variables favored by a high salt content, such as DH growth, DM, and C* increase.

The ripening pathways for the 3 tested salting levels clearly appear in Figure 4B. On d 1 (the end of yeast-ing), no differentiation was observed, but from d 2 (one day after brining) until the end of the ripening, the 3 salted cheese sets followed different routes. Overall, the least salted cheeses (S1.0) appeared closer to the control (S1.7) than the most salted ones (S2.4), suggesting that a moderate reduction in salt level should be possible with-out excessive altering of cheese properties.

On d 27, the odor and the color of 1.0% salted cheeses were yeasty and creamy, respectively. The creamy under-rind represented about one-third of cheese thickness and was completely runny. These descriptors were indicative of over-ripened cheeses, mainly due to GC overgrowth. In contrast, the odor and the color of 2.4% salted cheeses scored the worst on d 27: The cheeses were too dry, their color was dark orange (similar to those of the defectively ripened cheeses), the underrind was the driest and very thin near the surface, and the core was too hard. The optimum between sensory qualities and cheese ripening properties appeared to be 1.7% NaCl.

## Summary of the Salting Level Effects

In the studied range, NaCl contents in cheese did not affect KL growth, stimulated DH growth, and greatly influenced GC kinetics at 1.0 % NaCl. The growth of GC was excessive, inducing rind appearance flaws and off-flavor; 1.7 % NaCl showed defect-free rind develop-ment and 2.4 % induced GC death. Salt level in cheese also had an effect on the growth of ripening bacteria in cheese surface, mainly *A. arilaitensis*, *B. aurantiacum*, *C. casei*, and *H. alvei*, whereas *S. equorum* was insensi-tive to salt level. The biological, physicochemical, and sensory properties of Munster-type cheeses assessed by an expert panel were highly dependent on NaCl level. All sensory descriptor changes (overall cheese odor and color, creamy underrind thickness and consistency, core hardness) can be explained by microorganism growth, pH increase, carbon substrate diffusion and assimilation, and cheese moisture, as well as microbial enzymatic activity.

## CONCLUSIONS

Our study confirmed that salting strongly contributes to the regulation of cheese water activity and level of moisture. The higher the cheese salt content, the lower the water activity and the more the cheese was drained
and dry. This strongly influenced ripening microorgan-
ism growths and their enzymatic activities. As salt reduc-
tion in cheeses is a challenge for dairy industries, this
type of study will provide the knowledge necessary to
evaluate the salt level effects on a complex microflora of
soft ripened cheeses throughout the ripening. In addition,
studies on the influence of the salting rate of soft cheeses
with more moderate reduction levels (5%, 10%, or 20%)
could allow the development of cheeses with better nutri-
tional qualities without technological defects.

NOTES

The E-MUSE project has received funding from the
European Union's Horizon 2020 Research and Innova-
tion Programme under the Marie Skłodowska-Curie grant
agreement no. 956126. The authors thank F. Lecornué
and J. Buissière (UMR SayFood, Palaiseau, France) for
their technical assistance and sensor monitoring during
cheese production and ripening, M. Joly (UMR Say-
Food, Palaiseau, France) for her technical assistance in
the microbiological and physicochemical analyses of the
cheeses and the panelists for their analyses of the percep-
tion of the cheeses. We also thank G. Wagman (Sauve,
France) for his editorial advice on the English version of
this article. The sensory analysis protocol was approved
by the Ethics Committee of INRAE, France. No animal
subjects were used, so this analysis did not require ap-
proval by an Institutional Animal Care and Use Commit-
tee. The authors have not stated any conflicts of interest.

Nonstandard abbreviations used: µ = maximal
growth rate (d⁻¹) calculated from Weibull model; 3-AFC
= 3-alternative forced-choice; AA = *Arthrobacter arilai-
tensis*; a<sub>w</sub> = water activity; BA = *Brevibacterium auran-
tiacum*; C* = metric saturation; CC = *Corynebacterium
casei*; C<sub>LO</sub> and C<sub>LA</sub> = maximal consumption rates of LO
and LA, respectively (g kg⁻¹ d⁻¹); D = maximal death
rate (d⁻¹) calculated from Weibull model; DH = *Debaryo-
myces hansenii*; GC = *Geotrichum candidum*; h° = hue
angle; HA = *Hafnia alvei*; KL = *Kluyveromyces lactis*; L*
= lightness; LA = lactate concentration; LAB = lactic acid
bacteria; LO = lactose concentration; pHblend = pH of
the blended cheese; pHrind = pH of the rind; R = Weibull
model determination coefficient; RH = relative humidity;
S1.0, S1.7, S2.4 = cheese salt level of 1.0% NaCl, 1.7%
NaCl, and 2.4% NaCl; SE = *Staphylococcus equorum*;
t<sub>CLO</sub> and t<sub>CLA</sub> = days associated with C<sub>LO</sub> and C<sub>LA</sub>;
t<sub>D</sub> = time (d) associated with D; T<sub>UR</sub>; underrind thickness;
t<sub>v</sub> = day for which V was obtained; t<sub>µ</sub> = day associated to µ;
V = maximal rate (unit per day) calculated from Weibull
model; WC = wet cheese.

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ORCIDS

Ioan-Cristian Trelea ◉ https://orcid.org/0000-0001-6727-0716
# APPENDIX 1: TIME CHANGE OF YEAST CONCENTRATIONS

Figure 1 provide the decimal logarithm of DH, KL, and GC viable cell concentrations in relation to ripening time (d 1–27) as well as their Weibull models.

## *Debaryomyces hansenii*

Whatever the salt level, from d 1 to d 27, DH viable cell concentrations in relation to ripening time (Figure 1A) displayed the same trend, with a growth phase occurring from d 1 to d 6. However, DH maximal growth rate (μ<sub>DH</sub>) was dependent on cheese salt level (Table 2) as also shown by associated maximal generation times: it was 2.6 ± 0.2 d for S1.0 and 2.0 ± 0.2 d for S1.7 and S2.4. From d 6 to d 27, the maximal cell concentration of DH (X<sub>DH</sub>) remained constant.

Cheese *D. hansenii* strains, the main deacidification yeast on the cheese surface (Leclercq-Perlat et al., 2000), are classified as a highly salt-tolerant species able to grow between 14% and 24% NaCl wt/vol (Neves et al., 1997; Lages et al., 1999; Ramos, 1999; Cosentino et al., 2001; Masoud and Jakobsen, 2005; Aggarwal and Mondal, 2009; Corbaci et al., 2012). However, DH halotolerant ability is strain dependent (Corbaci et al., 2012). Due to its prevalence in traditional cheeses, considerable effort has been put to understanding of the mechanisms explaining the salt tolerance of DH (Prista et al., 1997; Sohier et al., 2009; de Nadal et al., 2011). Growth of some DH strains can be stimulated by NaCl (Almagro et al., 2000, 2001; Corbaci et al., 2012; Dugat-Bony et al., 2016). This could be illustrated by the differences of maximal viable cell concentration observed between S1.0 on one hand and S1.7 and S2.4 on the other. Prista et al. (2016) summarized the state of the art on DH salt tolerance and discussed its mechanisms and factors involved in saline stress.

## *Kluyveromyces lactis*

Concentrations of KL (Figure 1B) could not be determined after d 6 and d 13 for S1.0 and S1.7, respectively. Difficulties in determining KL concentrations, were due to the strong growth of GC for these cheeses. No significant differences in these KL concentrations were observed in relation to the salt level used. From d 1 to d 2, KL cell concentration displayed a death phase with a mean death rate (D<sub>KL1</sub>) of 0.43 ± 0.03 d<sup>-1</sup> occurring at t<sub>DKL</sub> of 1.32 ± 0.02 d (Table 2). Then, until d 6, d 13, or d 20 for S1.0, S1.7, and S2.4, respectively, KL maximal cell concentration remained constant at approximately 3.2 × 10<sup>7</sup> cfu/g. For S2.4, from d 20 to d 27, KL displayed a second death phase (Figure 1B; Table 2) reaching 1.3 × 10<sup>7</sup> cfu g<sup>-1</sup> on d 27.

## *Kluyveromyces* sp.

*Kluyveromyces* sp. strains, which are common cheese yeasts, are usually classified as a halotolerant able to grow at 11.5% NaCl wt/vol (Lages et al., 1999; Cosentino et al., 2001; Sohier et al., 2009). The genetic diversity of *Kluyveromyces* sp. could explain their salt tolerance by an adaption to salted cheese (Sohier et al., 2009). For 2.4% NaCl, the KL mortality observed was due to disappearance of easily assimilated nutrients (Klein et al., 2002) as also observed for Camembert-type cheeses (Leclercq-Perlat et al., 2004b, 2012). In the present study no salt influence on KL growth was observed.

## *Geotrichum candidum*

Cell concentrations of GC throughout ripening (Figure 1C) were dependent on the cheese salt content. For S1.7 GC grew with a same value of maximal growth rate (Table 2) as S1.0 but with a time lag close to 3.9 d. Then, from d 13 to d 27, maximal GC viable cell concentration of S1.0 or S1.7 remained constant around 7 × 10<sup>8</sup> cfu g<sup>-1</sup> on d 27. For S2.4 no growth phase was observed (Figure 2C). From d 1 to d 13, GC concentration remained constant at nearly 5.2 × 10<sup>6</sup> cfu g<sup>-1</sup>. From d 13 until the end of ripening, GC cell concentration displayed a death phase (Figure 1C; Table 2) reaching a cell concentration of 1.1 × 10<sup>6</sup> cfu g<sup>-1</sup> on d 27.

For Protected Designation of Origin French cheeses, the salt tolerance of *GC* isolates is function of the cheese salt levels (Marcellino et al., 2001). Indeed, GC growth in 1% NaCl salted cheese was better than growth without salt but worse than with 2% to 3% salt. Consequently, cheesemaking technologies play a central role in GC selections. Although GC is necessary to ripen a large number of cheeses due to its active role in the formation of the cheese typicality, it is dreaded by cheesemakers due to the risk of overgrowth, inducing rind appearance flaws and off-flavor flaws (Boutrou and Guéguen, 2005). Generally, salt appears as a key means to avoid overgrowth of GC. The GC used in this study showed a salt sensitivity: no inhibition on growth was observed for S1.0, but a lag phase was observed for S1.7 due to brining, which stopped GC growth until the end of salt diffusion (1–2 d), inducing a time lag. After this salting lag phase, GC did not appear to be sensitive to S1.7 salting level but did not grow and died at S2.4.

# APPENDIX 2: TIME CHANGE OF BACTERIA CONCENTRATIONS

Figure 2 provides the viable cell concentration in the 5 studied bacterial strains in relation to ripening time (d 1–27) as well as their Weibull modeling.
The AA cell concentration versus ripening time (Figure 2A) was significantly dependent on cheese salt level with a 99% confidence level. For S1.0 a death phase took place between d 1 and d 2 with a mean death rate of 1.2 d⁻¹. Then, from d 2 to d 13, AA cell concentration remained constant at 100 ± 10 cfu g⁻¹. From d 13 to d 27, AA grew with a generation time of 1.3 ± 0.1 d, reaching on d 27 a concentration 191 times higher than the one on d 13. For S1.7, from d 1 to d 6, no AA growth was observed (Figure 2A). From d 6 to d 27, bacteria grew with a generation time of 2.9 ± 0.2 d, reaching a viable cell concentration 104 times on d 27 higher than on d 13. For S2.4 from d 1 to d 13, AA viable cell concentration remained constant and was not significantly different from the one of S1.7. From d 13 to d 27, AA grew with a generation time of 2.5 ± 0.2 d reaching on d 27 a viable cell concentration around 33 times higher than the one on d 13.

From these results, this bacterium appeared sensitive to the salting level used in cheeses. Indeed, viable cell concentrations decreased or remained stable from d 1 to d 13 then increased with a maximal growth rate depending on cheese salting level.

The BA concentration in relation to ripening time (Figure 2B) was significantly dependent on cheese salt level. Whatever the cheese salt level, from d 1 to d 6, BA cell concentration displayed a death phase with a maximal death rate of 1.07 ± 0.05 d⁻¹ occurring on 1.10 ± 0.04 d, reaching 6.5 × 10³ cfu/g. Then, from d 6 to d 27, BA cell concentration displayed a growth phase depending on the cheese salt level (Figure 2B; Table 3). Indeed, the generation time was 3.2 ± 0.1 d, 1.9 ± 0.1 d, and 3.3 ± 0.1 d for S1.0, S1.7, and S2.4 respectively. On d 27, the viable cell concentration was 302 times, 908 times, and 56 times higher than the one obtained on d 13. The BA growth was between 40% and 45% quicker for S1.7 than for S1.0 and S2.4.

Contrary to Dugat-Bony et al. (2016) results, the BA strain used appeared sensitive to cheese salting level. Indeed, after a first phase (death or stagnation) from d 1 to d 13, BA grew with a maximal rate and reached a maximum concentration depending on the salting level.

The CC growth kinetics (Figure 2C), were significantly different for S2.4 compared with S1.0 and S1.7.

From d 1 to d 13, CC displayed a death phase whose maximal rate was significantly higher (around 29%) for S2.4 than S1.0 and S107 (Table 3). Then, from d 13 to d 27, no significant differences in maximum growth rate and associated time were observed for S1.0 or S1.7 which exhibited a generation time of 1.07 ± 0.07 d. The growth rates were significantly (3 times) slower for S2.4 exhibiting a generation time of 3.4 ± 0.2 d. These differences also appeared in the final CC concentration on d 27 (Table 3).

The growth of CC was not affected by a cheese salting level ≤1.7%. These results were not in agreement with those observed by Dugat-Bony et al. (2016) for another CC strain. Those authors have observed a lesser development of this bacterium for cheeses salted at 1.3%. This tends to show that CC growth was salt dependent and its salt tolerance would be strain dependent.

The growth of HA (Figure 2D) showed significantly 2 types of kinetics in relation to cheese salt levels. For S1.0 and S1.7, from d 1 to d 27, HA displayed a growth phase with a maximal rate (Table 3) corresponding to generation time of 7.0 ± 0.3 d and their maximal concentration reached 5.0 × 10⁷ cfu g⁻¹ on d 27. For S2.4, 2 death phases were observed: (1) from d 1 to d 2, with a mean death rate of 0.11 ± 0.03 d⁻¹ and (2) from d 13 to d 27, with a maximal death rate of 0.45 ± 0.05 d⁻¹ (Table 3) reaching a minimum concentration close to and 4.4 × 10⁵ cfu g⁻¹ on d 27.

In summary, no difference in HA growth was observed between reduced-NaCl (S1.0) and control (S1.7) cheeses for which HA exhibited a significant development. However, HA exhibited a significant mortality for S2.4.

### Staphylococcus equorum

Whatever the ripening time, no significant differences in SE kinetics were observed in relation to cheese salt levels (Figure 2E). From d 1 to d 6, SE viable cell concentrations remained constant close to 9.0 × 10⁴ cfu g⁻¹ (Table 3). From d 6 to d 27, SE grew with a generation time of 3.6 ± 0.2 d reaching maximal concentrations around 3.0 × 10⁷ cfu g⁻¹. SE exhibited a growth independent of the salting level used in the study range (1%–2.4%).