Influence of Heterogeneity of Salt Content in Food Structure on the Sensory Profile and Consumer Perception of Beef Burgers

Abstract

Contrast stimuli created between high- and low-taste concentration zones have been shown to enhance the perception of sensory trait intensity. The objective of this study was to determine if layering beef formulations with contrasting salt contents in salt-heterogeneous burger patties could evoke a more intense perception of sensory flavours compared to a burger matched in overall salt content but with a homogeneous salt distribution. The study material consisted of one patty batch with a homogeneous salt distribution (HM 0.7% NaCl) and six patty batches with an average NaCl content of 0.7% but distributed in six different heterogeneous (HT) salt structures. Sensory profiling and consumer tests in a group of 105 Irish residents were performed. The heterogeneity of salt in beef patties produced significant differences (p ≤ 0.05) among formulations in the intensity of salty taste, salty and beefy aftertaste, and taste uniformity. An analysis of the proximate composition of the burgers showed that the raw burgers did not differ in their moisture, protein, or fat contents, while the cooked ones did not differ in their salt contents. The results of a hedonic assessment of beef burgers with varied spatial distributions of salt did not show any significant differences in the liking of any sensory traits. Our data suggest an alternative approach involving preparing burgers with layers of varied salt concentrations with similar sensory experiences while potentially facilitating lower salt inclusion levels.

1. Introduction

There is an increasing focus worldwide on the need for food product reformulation to address high intakes of certain nutrients, including sugar, salt, and fat, to meet population health goals [1]. Unprocessed foods are the source of 15% of sodium in people’s diets, while manufactured foods account for 65–70% of Na sources [2]. In 2016, the EU encouraged all member states to develop Food Reformulation Roadmaps, and the targets set by, e.g., the Irish government, include a reduction in the daily salt intake from the current high level of 10 g to less than 6 g, and preferably closer to 5 g [2]. In more vulnerable groups, like the older Irish group, processed meats rank second only to bread as a dietary source of salt and account for over 25% of salt intake from foods [2]. Higher-than-necessary sodium intake has been linked to non-communicable diseases such as hypertension, cardiovascular disease, and stroke. Limiting sodium intake has been shown to reduce the risk of cardiovascular disease in hypertensive individuals [3].

While it is desirable to decrease the amount of salt in processed meats, due to the important role of salt functionality in processed meat products in terms of supporting water-holding, protein-binding, and fat-binding, as well as its roles in sensory quality and maintaining product safety, successful salt reduction, i.e., achieving a reduction in the salt content without compromising on technological performance and sensory appeal, is challenging [4,5].

Salt reduction strategies, such as the development of low-salt products, have drawn global interest. There are a lot of approaches for salt reduction, including reduction by stealth, salt alternatives, flavour enhancers, changes in the salt crystal size and structure, and alternative processing techniques [4,6]. Among them, heterogeneous spatial distributions of salt and aroma–taste interactions are promising strategies for taste enhancement [7].

A proposal for a fundamental perceptual mechanism causing an increased perception of a specific tastant, as a result of a heterogeneous spatial distribution (i.e., uneven locations of various concentrations of tastants, e.g., salt within a food product), was initiated by Meiselman and Halpern [8]. They found that alternating salt concentrations in aqueous salt solutions improved the saltiness intensity compared to non-alternating models. The pulsing of taste stimuli results in repeated relatively short duration presentations of stimuli to the tongue. Later studies by Bush [9] suggest that the frequency, timing, and concentration of salt stimuli can impact the perceived saltiness. A short, intense stimulus may increase salt perception, potentially through reducing the adaptation induced by fast concentration changes in the mouth. Eddy et al. [10] confirmed that taste perception may be distorted by the intermittent delivery of a stimulant. They concluded that applying this mechanism to the production of processed foods may support the successful reduction in salt and sugar intake in processed foods, thereby improving public health.

Layering food products with different salt contents, surface coatings, and coated salt particles, or creating spatially distributed compartments with different water contents (juiciness) can all be used to achieve inhomogeneous salt distribution [5,11,12].

The majority of previous works investigating heterogeneous spatial distribution in food were carried out on starch-based matrices, i.e., bread [11,12,13,14,15] and cream-based foods [7,16,17], but limited studies have focused on protein-based foods, such as gels and sausages [12,18], beef frankfurters [19], and beef patties [20].

As contrasting stimuli between high and low concentration zones within a food product are known to enhance, among others, the perceptions of saltiness and fattiness, a growing body of food scientists [15,16,17,21] supports the view that the magnitude of saltiness enhancement increases with an increase in the salt contrast intensity. The location of a high stimulus concentration (such as salt) on the outer layers of a food product can cause an enhancement in taste perception [7,21]. This approach could permit food processors to move forward with salt reduction steps without diminishing the saltiness perception and liking of foods among consumers.

The utilisation of layers with varied salt concentrations might appear feasible or practical for the entire industry [12]; modern processing plants are capable of complex food structuring in production, while in the era of additive manufacturing, 3D food printing, and other technologies, these approaches are likely to be both relevant and practical in the near future [22]. The production of layered beef patties as a mechanism of creating heterogenous salt distributions is thus worthy of investigation.

The purpose of this study was to examine if layered beef formulations with contrasting salt contents in salt-heterogeneous burger patties may confer a stronger taste intensity, thereby eliciting a greater sensory score, relative to a patty with a similar total salt content but a homogeneous salt distribution.

2. Materials and Methods

2.1. Study Design

The study design was based on two hypotheses: firstly, that a higher salt contrast would promote the sensory perception of saltiness and potentially other flavour attributes, and secondly, that locating a higher tastant stimulus concentration on the outer parts of the product would be more effective in promoting sensory perception of flavour attributes, compared with locating higher levels of the stimulus on the inner part of the product.

One beef burger batch with a homogeneous salt distribution (0.7% NaCl HM) and six beef patty batches with an average NaCl content of 0.7%, but distributed in six different heterogeneous (HT) salt structures (HT-L-EX, HT-L-IN, HT-M-EX, HT-M-IN, HT-H-EX, and HT-H-IN) were formulated (Figure 1). For each formulation, salt was added to either the internal (IN) or external (EX) part of the burger with a view of creating contrast stimuli and evoking a higher taste bud response. The composition of beef patties varied in the concentration and volume of internal layers (L, M, and H). Salt content varied between 0% and 2.1% of added salt per layer, and the volumes (proportion) of layers were varied accordingly to achieve an overall similar salt content in all formulations with a final patty weight of 170 g.

2.2. Study Material

The study samples and reference materials were produced in the Meat Industry Development Unit (Teagasc Food Research Centre, Dublin, Ireland) in accordance with GHP/GMP guidelines. Beef chucks (95% visual lean) were procured from Kepak Group (Clonee, Ireland), the excess fat and connective tissue were hand-trimmed off, and then the chucks were cut into cubes, mixed all together to unify, and coarsely processed through a 7.5 mm plate in a mixer mincer (La Minerva Mixer Mincer, Bologna, Italy). Eight formulations (

Table 1. Compositions of layers with varied salt distributions.

Layer	Intendent Composition		Actual Proximate Composition (%)
	95%VL Beef	Salt	Moisture	Protein	Fat	Ash	Salt
O% NaCl	100.0	0.00	73.18	21.49	4.86	1.13	0.19
0.7% NaCl	99.3	0.70	74.41	20.62	4.16	1.74	0.70
1.05% NaCl	99.0	1.05	73.61	20.06	4.60	1.94	0.95
1.15% NaCl	98.9	1.15	74.18	20.02	4.00	2.13	1.16
1.4% NaCl	98.6	1.40	73.76	19.97	4.36	2.29	1.38
1.75% NaCl	98.3	1.75	73.57	19.98	4.28	2.62	1.61
2.1% NaCl	97.9	2.10	73.62	20.04	3.92	2.97	1.97

) with varied table salt (Redbrook Ingredient Services, Dublin, Ireland) were manually mixed with the coarse ground beef for 15 min before being further minced using a 3 mm mincer plate (La Minerva Model No. CIE701, Bologna, Italy). The individual formulation layers (Figure 1) were weighed with accuracy to 0.1 g, placed between round wax paper, and moulded using a hamburger patty press (Vevor, Cannock, UK) to a 10 cm diameter. Then, all layers were unpeeled, merged, and pressed again in the burger press. Prepared burgers were placed in wax paper, blast-frozen for 60 min, vacuum-packed, and stored at −20 °C for downstream analysis.

2.3. Proximate Composition Analysis

Proximate composition analysis was performed in raw and cooked burgers, which were thawed under refrigeration condition the day before and then homogenised in a Robot Coupe (R101, Robot-Coupe S.N.C., France). Moisture content was assayed using air drying method accordingly with AOAC (1991) procedure no. 950.46, while fat concentration was assayed using the NMR Smart Trac Rapid Fat Analyser (CEM Corporation, Matthews, NC, USA) following AOAC (1990) method no. 985.26. Protein content based on Dumas combustion method was determined using an FP628 (LECO Corp., St. Joseph, MI, USA) according to AOAC (1990) method no. 992.15. Ash content was determined via gravimetric weight loss while ashing the samples in a muffle furnace at 525 °C (920.153, AOAC, 1990). Salt content was determined via titrating chloride anions in ashed samples with silver nitrite using the Mohr method [23]. All of these analyses were performed with 4 repetitions.

2.4. Samples Preparation and Presentation

All samples were removed from the freezer 24 h prior to sensory assessment and thawed at refrigerated temperature of 4 °C. Beef patties were grilled using a clamshell grill (Velox, Oxfordshire, UK) set at 170 °C until an internal temperature of 75 °C (TH103TC, Eurolec Instrumentation Ltd., Dundalk, Ireland) was reached [24]. Each beef patty was cut into four pieces (34 g each), and either wrapped in aluminium foil (sensory profiling) or placed on a white paper plate (consumer testing), which was pre-labelled with a random three-digit number. Samples were served immediately in sets of two according to a randomised presentation order to prevent potential carry-over effects. Filtered water and plain crackers (Carr’s, Pladis, London, UK) were provided as palate cleansers between samples. Informed consent was given by all participants for their data to be used and analysed.

2.5. Sensory Profiling

Sensory profiling of burgers was completed using Quantitative Descriptive Analysis (QDA) [25] with a trained sensory panel (n = 8; all female) with significant experience in the sensory assessment of beef [26,27]. Sensory profiling was conducted under white light in a sensory laboratory (Teagasc, Dublin, Ireland) that meets the requirements of ISO 8589:2007 [28] using the computerised system, Compusense^® (Guelph, ON, Canada).

Nine sensory attributes (

Table 2. List of sensory attributes and lexicons and reference materials used in the study.

Sensory Attribute	Definition	Scale	Reference Material
odour
beef odour	the amount of beef odour in the sample	none—very strong	Weak: beef patty boiled in plenty of water to reach 75 °C in the core; Medium: beef patty cooked in microwave oven to reach 75 °C; Strong: beef patty grilled to reach 75 °C in the core.
texture
hardness	force required to bite completely through sample with molar teeth	none—very strong	Low: beef patty grilled to reach 95 °C in the core; Medium: beef patty grilled to reach 75 °C in the core; High: beef patty grilled to reach 71 °C in the core.
juiciness	amount of liquid released from sample during chewing; the amount of wetness/fattiness exuded	none—very strong
flavour/taste
beef flavour	intensity of beef flavour in the sample	none—very strong	Weak: beef patty boiled in plenty of water to reach 75 °C in the core; Medium: beef patty cooked in microwave oven to reach 75 °C; Strong: beef patty grilled to reach 75 °C in the core.
salty taste	intensity of saltiness in the sample	none—very strong	Very weak: unsalted burger patties; Weak: burger patty with 0.5% NaCl; Medium: burger patty with 0.8% NaCl; Strong: burger patty with 1.6% NaCl.
umami taste	intensity of umami taste in the sample	none—very strong	Very weak: 0.0595% MSG aqueous solution; Weak: no MSG burger; Medium: beef burger with the addition of 0.5% of MSG; High: beef burger with the addition of 1.0% of MSG.
taste uniformity	degree of flavour uniformity within the whole sample	none—very strong	No reference material needed.
Residual texture and flavour
beef aftertaste	intensity of beef flavour in the mouth 30 s after swallowing	none—very strong	Weak: beef patty boiled in plenty of water to reach 75 °C in the core; Medium: beef patty cooked in microwave oven to reach 75 °C; Strong: beef patty grilled to reach 75 °C in the core.
salty aftertaste	intensity of saltiness in the mouth 30 s after swallowing	none—very strong	Very weak: unsalted burger patties; Weak: burger patty with 0.5% NaCl; Medium: burger patty with 0.8% NaCl; Strong: burger patty with 1.6% NaCl.

) were selected and defined following three 2 h training sessions. The reference materials used to demonstrate each attribute were determined via panel consensus.

Panellists assessed the burgers in duplicate over two 1 h sessions, which took place between 10 a.m. and 12 p.m. A break of 30 min was enforced between sessions. To reduce first-order bias and calibrate the panellists, a warm-up sample was served at the beginning of each session. Panellists scored samples using the assessment protocol defined during panel training. The intensity of sensory attributes was assessed on a 10 cm unstructured linear graphic scale, with specific word anchors ranging from none on the left to very strong on the right.

2.6. Consumer Testing

Consumer testing involved study-related survey completion and a sensory assessment of burger samples during one afternoon session. The study involved the assessment of three burger samples, which were chosen based on the sensory profiling results. Two samples that had the highest saltiness amplitude between the heterogeneous samples (HT-L-EX and HT-L-IN) and the control sample (HM) were selected.

2.6.1. Participants

Consumer testing was conducted in the first week of February 2022 at the sensory suite in the School of Food and Nutritional Sciences, University College Cork, with a group of 105 consumers. Participants were recruited using a convenience sampling method from a UCC database. Consumers received a EUR 20 voucher incentive as a thank you for their participation in the study.

The study group (

Table 3. Characteristics of participants (n = 105).

Feature *	Group	Participants
		Number (n)	Percentage (%)
Total		105	100.0
Gender	women	68	64.8
	men	37	31.2
Age	19–24 years	76	72.4
	25–44 years	26	24.8
	45–65 years	2	1.9
	65 years and over	1	0.9
Education	upper secondary	5	4.8
	third-level non-degree	46	43.8
	third-level degree and higher	54	51.4
Dwelling place	city	67	63.8
	urban town	21	20.0
	rural area	17	16.2
Financial situation in own opinion	healthy	59	56.2
	okay	40	38.1
	tight	6	5.7
Burger consumption frequency	never	3	2.8
	once or twice a month	59	56.2
	three-four times a month	24	22.9
	once a week	15	14.3
	two or three times a week	4	3.8
Burger consumption venue	at my home or at friend’s house	53	50.5
	fast food outlet	35	33.3
	gourmet burger outlet	12	11.4
	street food vendors	3	2.9
	other food service venue or place	2	1.9
Type of used burgers	hand-made (prepared from scratch)	43	40.9
	refrigerated beef patties	47	44.8
	frozen beef patties	15	14.3
Level of habitual dietary salt intake	average salt intake	56	53.3
	higher salt intake	49	46.7

* Stratification of socio-demographical features according to Central Statistics Office in Ireland.

) was dominated by females (64.8%) under the age of 24. Almost half (51.4%) of the participants held a third-level degree or higher, while 43.8% were undergraduate students. The distribution between genders was not equal, but similar to that reported by Emorine [16]. However, women generally outperform men in sensory abilities related to food perception [29,30].

The majority of participants (63.8%) lived in a big city, while a fifth person lived in an urban town (20.0%) or a rural area (16.2%). Most of the participants declared that their financial situation was healthy (56.4%) or okay (38.1%). More than half of the participants (56.2%) consume burgers once or twice a month, while almost every fourth (22.9%) of the subjects consume burgers 3–4 times a month. Most consumers eat burgers most often either at home, at a friend’s house (50.5%), or at a fast food outlet (33.3%). Hand-made beef patties (40.9%) and refrigerated ones (44.8%) were the most popular in a study group, while only 14.3% of the participants used frozen patties.

2.6.2. Protocol

The participants assigned to sensory booths were instructed on the testing procedures and asked to complete the questionnaire. After that, they received samples and assessed the liking, saltiness, and purchase intent of each sample.

2.6.3. Survey

The questionnaire consisted of three sections. The first section covered formal consent for participation in the study. The second section explored social–demographic features (gender, age, education, financial situation, and dwelling place), beef burger consumption frequency, preferred degree of doneness, and intensity of hunger sensation using a validated scale by Friedman et al. [31], as well as the level of their habitual dietary salt intake using a short, validated questionnaire by Manfredi et al. [32]. The assessment of salt habits consisted of five questions with three answers with assigned points ranging from 1 to 3. Actual total scores ranged from 6 to 13 (possible range: 5–15), wherein higher values were related to a greater salt intake. The participants who obtained 5–9 points were classified as individuals with average salt intake, while those with 10 or more points were perceived as having a high salt consumption [32]. There was only one subject with a very high salt intake (13) who was incorporated into the high salt intake group.

The third section was sensory assessment. Hedonic reaction—the degrees of aroma, appearance, flavour, texture, and overall liking—was assessed by participants on a 10-point category scale with word anchors (ranging from dislike to like very much).

Consumer perception of saltiness and buying intent [33] were also assessed using a category scale with bipolar adjectives on the scale edges, respectively, not salty–very salty and highly unlikely–highly likely.

2.7. Statistical Analysis

The IBM SPSS Statistics 27.0.1.0 (New York, NY, USA) software was used to explore the statistical significance of the results obtained.

A mixed three-way analysis of variance (MANOVA) with a general linear model (GLM) and Fisher Least Significant Difference (LSD) post hoc test was performed to examine the differences in the intensity of attributes. The sample was set as a fixed factor, while panellists and replicates were set as random factors. Moreover, Dunnett’s post hoc test was used to compare the mean values of the HT samples to the mean of the control sample, HM.

A MANOVA was also used to examine the difference in saltiness rank-based variable, wherein the sample and level of habitual dietary salt intake were fixed factors.

The one-way ANOVA with Fisher’s Least Significant Difference was used to compare the results of food composition analyses. The results were considered statistically significant at a level of materiality equal to 0.05.

To compare the differences in consumer perception of saltiness, purchase intent, and degree of burger liking and the effects of participant characteristics on them, a Kruskal–Wallis one-way analysis of variance (ANOVA) with Dunnett’s post hoc test was performed.

The Pearson correlation coefficient was computed to evaluate the relationship between given macronutrient contents, while Spearman’s rank correlation coefficient was used to relate participants’ responses to their characteristics.

The results of principal component analysis (PCA) were interpreted accordingly by Borgognone et al. [34].

3. Results

3.1. Effect of Heterogeneous Salt Distribution on Proximate Composition of Raw and Cooked Beef Patties

An analysis of the proximate composition of burgers revealed that the raw burgers did not differ in the moisture, protein, or fat contents (

Table 4. Proximate compositions of beef patties used in the study.

	Sample	Raw Beef Patties					Cooked Beef Patties
		Moisture	Protein	Fat	Ash	Salt	Moisture	Protein	Fat	Ash	Salt
		$\mathbf{Percentage}\mathbf{Content}[\%]\overline{\mathbf{X}}$ ± SD
	HM 0.7%	74.41 a ± 0.08	20.62 a ± 0.29	4.16 a ± 0.03	1.74 a ± 0.07	0.70 a,b ± 0.04	66.2 a ± 0.5	27.55 c,d ± 0.33	5.36 a,b ± 0.13	1.81 a,b ± 0.03	0.69 a ± 0.03
	HT-L-EX	74.39 a ± 0.05	20.23 a ± 0.07	4.23 a ± 0.04	1.65 a,b ± 0.06	0.66 a,b ± 0.08	64.72 c ± 0.23	29.06 a ± 0.35	5.53 a ± 0.07	1.87 a,b ± 0.04	0.81 a ± 0.04
	HT-L-IN	74.15 a ± 0.16	20.30 a ± 0.04	4.26 a ± 0.10	1.71 a,b ± 0.02	0.76 a ± 0.03	66.02 a,b ± 0.09	28.09 b,c,d ± 0.3	5.02 c ± 0.03	1.92 a ± 0.05	0.79 a ± 0.05
	HT-M-EX	74.33 a ± 0.04	20.24 a ± 0.10	4.2 a ± 0.02	1.60 a,b ± 0.02	0.70 a,b ± 0.09	65.8 a,b ± 0.52	28.23 a,b,c ± 0.41	5.33 a,b,c ± 0.17	1.47 a,b ± 0.35	0.74 a ± 0.06
	HT-M-IN	74.37 a ± 0.06	20.51 a ± 0.08	4.17 a ± 0.06	1.69 a,b ± 0.07	0.70 a,b ± 0.04	66.22 a ± 0.22	27.69 c,d ± 0.14	5.16 b,c ± 0.03	1.83 b ± 0.07	0.71 a ± 0.05
	HT-H-EX	74.42 a ± 0.15	20.38 a ± 0.06	4.18 a ± 0.10	1.62 a,b ± 0.03	0.67 a,b ± 0.04	65.13 b,c ± 0.23	28.69 a,b ± 0.38	5.52 a ± 0.04	1.83 a,b ± 0.04	0.73 a ± 0.05
	HT-H-IN	74.17 a ± 0.08	20.34 a ± 0.14	4.26 a ± 0.03	1.59 b ± 0.02	0.60 b ± 0.03	66.25 a ± 0.24	27.24 d ± 0.23	5.30 a,b,c ± 0.18	2.02 a ± 0.06	0.73 a ± 0.02

a, b, c, d—mean values marked by different letters in columns differ significantly at p ≤ 0.05 in Least Significant Difference (LSD) test.

). The HT-H-IN sample had significantly higher ash and salt contents than the HT-L-IN sample. Nevertheless, there were no significant differences in the salt content between the cooked burger samples. The changes in the protein and fat content results are negatively related to the moisture content as follows, respectively: r= −0.87, p ≤ 0.000; r = −0.80, p ≤ 0.000. A similar effect was noted for the salt content (r = −0.47, p ≤ 0.05), but the strength of the correlation was lower.

3.2. Effect of Heterogeneous Salt Distribution on Sensory Profile of Beef Patties

Despite there not being a significant effect of salt content across the patty treatments, the heterogeneous salt distribution (HSD) treatment caused significant differences (p ≤ 0.05) in the intensity of the salty taste, the salty and beefy aftertaste intensities, as well as the taste uniformity in the beef patties. Significant differences were also noted in the hardness and juiciness. No significant differences in the intensity of beef odour, beef flavour, or umami taste were observed across the burger samples (

Table 5. Sensory profiles of beef patties with spatially varied salt distributions.

Sensory Attributes	HM 0.7%	HT-L-EX	HT-L-IN	HT-M-EX	HT-M-IN	HT-H-EX	HT-H-IN
	$\overline{\mathit{x}}$ Intensity (0–10 c.u.) ± SE
beef odour	4.8 a ± 0.6	5.2 a ± 0.5	5.2 a ± 0.4	5.5 a ± 0.6	5.2 a ± 0.5	5.4 a ± 0.6	4.5 a ± 0.5
hardness	3.9 c ± 0.4	4.9 a ± 0.5	4.0 b,c ± 0.5	4.2 a,b,c ± 0.5	4.0 b,c ± 0.5	4.7 a,b ± 0.6	3.2 c ± 0.4
juiciness	6.1 a,b ± 0.4	5.6 b ± 0.4	6.3 a,b ± 0.5	5.5 b ± 0.4	6.7 a ± 0.4	6.0 a,b ± 0.5	6.5 a,b ± 0.5
beef flavour	5.5 a ± 0.5	5.3 a ± 0.5	5.4 a ± 0.4	5.7 a ± 0.4	5.3 a ± 0.5	5.6 a ± 0.4	5.0 a ± 0.4
salty taste	4.8 b ± 0.7	4.8 b ± 0.5	6.1 a ± 0.4	5.8 a,b ± 0.5	6.3 a ± 0.4	4.8 b ± 0.5	6.0 a ± 0.4
umami taste	4.3 a ± 0.6	4.9 a ± 0.4	4.7 a ± 0.5	4.5 a ± 0.4	4.7 a ± 0.4	4.5 a ± 0.4	4.8 a ± 0.5
uniformity of taste	7.7 a ± 0.4	7.5 a,b ± 0.4	7.3 a,b ± 0.4	6.4 c ± 0.4	7.9 a ± 0.3	7.9 a ± 0.3	6.7 b,c ± 0.3
beefy aftertaste	4.2 a,b,c ± 0.6	3.8 c ± 0.5	3.9 b,c ± 0.4	4.8 a ± 0.5	4.6 a,b ± 0.6	3.8 c ± 0.5	3.7 b,c ± 0.5
salty aftertaste	3.9 b ± 0.6	4.0 b ± 0.7	5.1 a,b ± 0.4	4.0 b ± 0.6	5.3 a ± 0.6	4.3 a,b ± 0.6	4.7 a,b ± 0.6

a, b, c,—mean values marked by different letters in columns differ significantly at p ≤ 0.05 in Least Significant Difference (LSD) test.

).

Surprisingly, the inhomogeneous spatial distribution of salt in the burger meat increased the saltiness intensity when salt was located in the internal parts of the burger. A clear effect was demonstrated by the HT-M-IN sample, in which case Dunnett’s multiple comparison test revealed a significant (p < 0.05) difference from the homogeneously salted patty. Placing salt in the external parts of burger meat increases the perceived hardness of beef burgers. The samples with equal proportions of salted (1.4% NaCl) and unsalted meat were perceived as having a more intense beef aftertaste. The uniformity of taste scaling revealed that all of the samples, with the exception of HT-M-EX and HT-H-IN, were perceived as uniform.

The datasets were subjected to principal component analysis (PCA), and the findings show that the variation between the beef burger samples in two principal components explains 73.5% of the variance. The PCA biplot graphs (Figure 2) provide a clearer presentation of the data position and relationships between the axes and components. The first factor explained 49.8% of the total variance and shows a close relationship of the salty taste and aftertaste with juiciness, and shows a negative relationship with hardness. The second dimension accounts for 23.6% of the total variability and demonstrates a relationship between the salty taste and beef flavour and aftertaste and demonstrates a negative relationship with the uniformity of taste. The samples with internally located salt were characterised by saltiness attributes and juiciness, while those with externally located salt were characterised by hardness, which is proven by the location of those attributes on the opposite side of the plot origin.

3.3. Effect of Heterogeneous Salt Distribution on Consumer Reaction

The results of a hedonic assessment of the beef burgers with a varied spatial distribution of salt did not show any significant differences in the liking of any sensory traits (

Table 6. Hedonic scores of beef patties with spatial distribution of salt in the opinions of consumers (n = 105); mean values do not differ significantly.

	Sample	Aroma	Appearance	Flavour	Texture	Overall Liking	Purchase Intent	Saltiness
		Mean Value of Hedonic Scores (1–10 c.u.) ± SE					(1–7c.u.) ± SE	(1–10 c.u.) ± SE
	HM 0.7%	7.4 ± 0.2	7.6 ± 0.2	7.8 ± 0.2	7.0 ± 0.2	7.6 ± 0.2	5.1 ± 0.1	5.8 ± 0.2
	HT-L-IN	7.3 ± 0.2	7.5 ± 0.2	7.7 ± 0.2	7.0 ± 0.2	7.6 ± 0.2	4.9 ± 0.1	5.9 ± 0.2
	HT-L-EX	7.4 ± 0.2	7.5 ± 0.2	7.6 ± 0.2	7.2 ± 0.2	7.6 ± 0.1	5.2 ± 0.1	5.9 ± 0.2

). There was no effect on the purchase intent. A spatial salt distribution did not affect the saltiness enhancement, and the scores of the consumers’ saltiness perception ranged between 5.8 and 5.9 c.u. The assessment using a visual analog scale did not show any significant differences. Perhaps the untrained panellists could not distinguish differences, or the data were inconsistent in a study group. For this reason, to reanalyse the data, a new rank-based variable was created, wherein a relationship between individual samples was indicated. The sample that was less salty than the others received a rank of 1, the samples that were perceived as equally salty received a rank of 2, and the sample that was saltier than the others received a rank of 3. The sum of the ranks was as follows:

• HM 0.7%, ∑ = 204;
• HT-L-EX, ∑ = 203;
• HT-L-IN, ∑ = 211.

The Pearson’s chi-squared test value was 2.98, and the difference was insignificant (p = 0.5614).

There were no significant effects of gender, age, education, financial situation, dwelling place, beef burger consumption frequency, or preferred degree of doneness. There was a positive relationship between hunger intensity and saltiness perception (rho = 0.13; p ≤ 0.05).

Participants who had high scores for habitual dietary salt intake assessed a lower saltiness of HM 0.7% (homogeneously distributed salt) than HT-L-IN (Figure 3), while the results of the means of saltiness intensity were not statistically significant; when saltiness was included as a rank-based variable, the difference was significant. This result is aligned with the findings from the trained sensory panel and offers the intriguing possibility that people with a higher salt intake in their diet may be more sensitive to a contrast-induced saltiness enhancement. More detailed studies potentially on specific population subgroups and cohorts would be enlightening.

4. Discussion

Alternating low and high sodium concentrations within a food product can reduce taste adaptation, meaning that sensations are more intensely perceived compared to a continuous stimulus [35]. Our study design involved beef burger samples of varied salt contrast intensities between salted and unsalted meat, as well as their varied proportions or location.

The majority of studies investigating the impact of layered salt distribution on saltiness were performed on starch- or dairy-based products. In the study by Emorine et al. [16], a heterogeneous salt distribution showed a significant saltiness enhancement in two snack types (a bi-layer cereal product and four cream-based layers). A high heterogeneity of salt located on the outermost layer of the four-layer cream-based products enhanced saltiness perception. The snack was evaluated to be 25% saltier than the reference sample. This finding implies that the salt content in the salted layer is a crucial component in enhancing saltiness in such a heterogeneous food product. In further research [16,17], in which the odour-induced saltiness enhancement and special salt distribution strategies were evaluated, the saltiness enhancement was significantly greater for products with only one layer of added salt, especially when the salt was concentrated in an external layer. Moreover, a four-layer cream-based snack with a heterogeneous distribution of salt was significantly saltier than a snack with a homogeneous distribution, regardless of the aroma distribution (including the sample without added aroma) [7]. The data obtained by Fahmy et al. [35] indicated that a heterogeneous spatial sodium chloride distribution in starch-based 3D food snacks increased saltiness as long as the sensory contrast was strong enough and the overall NaCl concentration was low. The saltiness enhancement in bread, which was studied by Noort et al. [15], was the most significant at a low salt content, with a 117% increase due to heterogeneity. The magnitude increased with sensory contrast. The spatial heterogeneity of NaCl allowed for a 28% salt reduction in bread without a loss of saltiness intensity or the use of sodium substitutes, taste, or aroma additives. Beyond the heterogeneous distribution of NaCl, the improvement in saltiness can be further extended by utilising lactic acid [11].

Our sensory profiling results supported the hypothesis that the heterogeneity of salt content in meat products, through the layering of different salt contents, stimulated a perception of increased intensity of saltiness in all meat products where it did not exist. Therefore, our first hypothesis can be accepted. With regard to the second hypothesis, our findings were not consistent with the proposal that a higher sensory perception would reside in products with higher salt contents in the outer layers of the foodstuff. Instead, the trained panel analysis and the ranking analysis of the consumer study provided supporting evidence that increasing the salt content in the inner layers of the product enhanced the perception of saltiness, indicating that burger samples with internally located salt resulted in a higher perception of saltiness. The hardening effect on the surface coupled with cooking perhaps explains why the heterogeneity did not have a high impact on the external high salt layer formulations. The current study contrasts with previous research in this aspect [7]. Discrepancies between our results and those previously reported are likely due to the specificity of the different food matrices utilised in the different studies in this area. An alternative reason could be the salt diffusion phenomenon. Fahmy et al. [35], who studied starch-based snacks, concluded that sodium diffusion from high to low NaCl layers reduces the initial concentration ratios, so high concentration gradients must be applied while maintaining a low overall NaCl content. Moreover, to reduce the diffusion effects, configuration patterns other than layer configurations can be used, where concentrated spots are site-specifically introduced in the matrix without salt addition [35].

The food matrix is one of the factors involved in sodium release and the consequent saltiness perception. The interaction of sodium with food matrix components is crucial for saltiness perception. An increased protein content in meat reduces the sodium availability, while water improves the salinity perception [36].

The data on protein-based products are limited. To the best of our knowledge, no other authors have studied multilayered beef patties. Previous research was performed on a model of layered pork sausages. An inhomogeneous sodium chloride distribution in sausage formulations with various layers was perceived as saltier than homogeneous sausage formulations at the same sodium chloride concentration [12]. In other studies, a heterogenous salt distribution was achieved in beef frankfurter by placing NaCl in the edible coating and reducing the salt content by over 50% while maintaining the saltiness intensity. Such sausages had higher consumer acceptability and purchase intention than traditional sausages with added salt [19]. A saltiness contrast may also be elicited by modifying the size of the salt crystals, e.g., from 0.2–0.4 mm (regular) to 3 mm, as most regular-sized NaCl crystals are swallowed without the consumer noticing the salty taste [36]. Gaudette et al. [20] found that coated 3 mm sized salt crystals in a reduced-sodium beef patty (0.7%) can achieve a saltiness comparable to table salt (1%). Low-sodium-chloride (0.7%) patties with 100% 3 mm salt crystals were perceived as being 20% saltier compared to a regular control patty and 34% saltier compared to a regular low-salt patty. However, unsalted meat patties struggle to entrap water and fat, causing cooking loss and affecting the meat texture and juiciness. Large-sized NaCl crystals cause incomplete solubilisation in the mouth, suggesting reduced-size alternatives for sodium reduction in meat products [36].

In our study, a saltiness enhancement via an inhomogeneous salt distribution was found by trained sensory panellists, while the consumers did not clearly perceive a difference between the samples. We believe that differences between analytical tests (trained sensory panels) and affective (consumer) responses may arise from the sensitivity of trained sensory panellists. In the analytical measurement, selected, sensory-screened, experienced, and well-trained panellists were used, while the consumer test involved regular burger eaters. The consumers were not aware that the study was focused on saltiness perception, while the professional panellists were trained using four samples of varied salt concentrations. Hence, their attention could be focused on other burger traits that diminished the perceived differences in saltiness. When the scores were converted to a rank-based variable and habitual salt intake was considered, subjects with a high dietary salt intake assessed a lower saltiness of HM 0.7% compared to the HT-L-IN sample.

Insignificant differences in the consumer perceptions of saltiness may result from the measurement tool used. Many approaches have been proposed by various authors. Some authors reported contrast-induced saltiness enhancement involving trained or only sensory-screened panellists using mainly visual analog scales [7,11,15,17] or a paired comparison test, 2-AFC [35]. Saltiness assessment in consumer tests conducted by other authors was performed using various methods, i.e., category scale [15], 2-AFC [12], and VAS [16,19].

In a recent study by Aveline et al. [37], the visual analog scales and ranking methods were compared to evaluate odour-induced saltiness enhancement (OISE). The authors did not find an OISE effect when using VAS in apple juice or green pea soup, while the ranking method revealed OITE in green pea soup and partially in apple juice (in one out of the two groups tested). They concluded that the ranking method is simple to use and preserves the configural processing required for flavour perception while focusing the participants’ evaluation on the target flavour. Line scales entail plenty of attributes to avoid dumping effects that hinder an OITE [37]. On the other hand, the ranking method usually does not allow for ties and is a forced choice [38].

This research has raised many points that need further investigation. A future study should be focused on a saltiness time–intensity assessment to determine how heterogeneously distributed salt in the food matrix is perceived during consumption. Future research could focus on recruiting a more demographically balanced consumer group. More extensive research is also needed to determine what subjects’ characteristics make them more sensitive to contrast-induced enhancement. An important issue is also methodological aspects, i.e., test selection and their adequacy in measuring consumers’ perception of saltiness.

5. Conclusions

This study investigated if layered formulations with contrasting salt contents in burger patties may evoke enhanced saltiness compared to burgers with a homogeneous salt distribution. Although the cooked burgers had the same salt content, trained panellists found significant differences (p ≤ 0.05) in the intensity of salty taste, salty and beefy aftertaste intensities, flavour uniformity, hardness, and juiciness. An inhomogeneous salt distribution in the burger meat increased the saltiness intensity when found in internal parts. Moreover, the samples with salt located internally were characterised by higher juiciness, while those with salt located externally were marked by higher hardness. While these differences were not perceived by untrained consumers when using the category scale, when the scores were converted to a rank-based variable, it showed that a group of participants with a high habitual salt intake scored lower on the saltiness of the homogeneous burgers when compared to the heterogeneously and internally located salt in the burgers.

These findings suggest an alternative burger preparation with salt-concentrated layers that can potentially lower the salt inclusion levels in a group of sensory-sensitive people, especially those with high salt intakes in their diets. The presented strategy could be practical in modern high-tech plants, especially in the era of 3D printing.