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Sensory and Consumer
Sciences
The Salt Flip: Sensory mitigation of salt (and
sodium) reduction with monosodium glutamate
(MSG) in “Better-for-You” foods
Jeremia Halim, Ali Bouzari, Dan Felder, and Jean-Xavier Guinard
Abstract: We tested the hypothesis that reduced-salt versions of four “better-for-you” dishes enhanced with
monosodium glutamate (MSG) through a “Salt Flip” in an amount that still substantially reduced total sodium matched
the consumer acceptance of normal-salt versions. Three versions each—standard recipe with normal salt, reduced salt,
and reduced salt with MSG, of four dishes—roasted vegetables (RV), quinoa bowl (QB), savory yogurt dip (SD), and
pork cauliflower fried rice (CR) were evaluated by 163 consumers for overall liking and liking of appearance, flavor,
and texture/mouthfeel on the nine-point hedonic scale, preference, adequacy of flavor, saltiness, and aftertaste on just-
about-right (JAR) scales, likeliness to order, and sensory characteristics by check-all-that-apply. For each dish, the MSG
recipe was liked the same (or significantly more for SD, P<0.05) than the standard recipe, and better than the reduced
salt recipe for QB and CR. The same was true of likeliness to order. MSG recipes of QB and SD were significantly
preferred to the standard recipes, with no difference for RV and CR. MSG recipes were consistently described as “de-
licious,” “flavorful,” and “balanced.” Penalty-lift analysis showed that “delicious,” “flavorful,” “balanced,” “fresh,” and
“savory”; and “bland,” “rancid,” and “bitter,” were positive and negative drivers of liking, respectively. Two of three
uncovered preference clusters, accounting for 68% of consumers, consistently liked MSG recipes, and the same or more
so than standard recipes. We conclude that MSG can successfully be used to mitigate salt and sodium reduction without
compromising consumer acceptance of better-for-you foods.
Keywords: better-for-you foods, consumer testing, monosodium glutamate (MSG), preference mapping, salt and sodium
reduction, Salt Flip, sensory quality
Practical Application: The Salt Flip offers a promising dietary sodium reduction strategy through the addition of
monosodium glutamate (MSG) to reduced-salt, savory, better-for-you foods that does not compromise consumer accep-
tance of their sensory profile.
1. INTRODUCTION
Sodium intake is an important public concern in most coun-
tries, as it is linked to several chronic diseases such as hypertension,
cardiovascular disease, renal failure, and osteoporosis, among oth-
ers. Reducing sodium intake has been clinically shown to lower
blood pressure short term (Sacks et al., 2001) and mortality from
stroke and heart disease long term (Law, 2000). The main di-
etary source of sodium is sodium chloride (NaCl) or table salt.
A significant challenge to the public health community and the
food industry alike is that salt reduction typically compromises
the palatability of foods (Beauchamp, Bertino, & Moran, 1982;
Breslin & Beauchamp, 1997). Flavor-enhancing ingredients such
as monosodium glutamate (MSG) thus offer a possible sensory
strategy for the mitigation of salt reduction with regard to palata-
bility. Recently, the use of MSG has been acknowledged by the
National Academic of Sciences, Engineering, and Medicine as a
viable strategy to reduce sodium in the food supply (Stallings et al.,
2019).
JFDS-2020-0389 Submitted 3/11/2020, Accepted 6/15/2020. Authors Halim
and Guinard are with Department of Food Science and Technology, University of
California, Davis, California, USA. Authors Bouzari and Felder are with Pilot
R&D, Berkeley, California, USA. Direct inquiries to author Guinard (Email:
jxguinard@ucdavis.edu)
MSG is the sodium salt of L-glutamic acid, the most abundant
amino acid in nature, constituting up to 8% to 10% of most dietary
proteins either as free glutamate or bound to other amino acids.
The amount of sodium in MSG (12.28 g/100 g) is one third of
the sodium in salt (39.34 g/100 g), which makes it a promising
salt alternative in sodium reduction strategies. The majority of
glutamate intake is from that naturally present in food, with only
a small amount derived from MSG seasoning (Henry-Unaeze,
2017). Ever since the discovery of glutamate’s unique, umami taste
by Dr. Ikeda in 1908 (Kawamura & Kare, 1987), MSG has been
widely used as a flavor enhancer in savory foods. MSG imparts the
umami taste via a T1R1/T1R3 heteromeric receptor. Its umami
taste can be further potentiated by the 5’ ribonucleotides inosine
monophosphate and guanosine monophosphate, both naturally
found in foods like beef and mushrooms (Giovanni & Guinard,
2001; Zhang et al., 2008). Yamaguchi & Kimizuka (1979) also
verified that some intensification of salty taste takes place when
umami substances, such as MSG or other nucleotides are present.
In the United States, MSG is classified by the Food and Drug Ad-
ministration (FDA) as a “Generally Recognized as Safe” substance.
The usage level as a food additive is 0.1% to 0.8% by weight.
Research has previously documented the successful application
of MSG to substitute for salt without compromising the sen-
sory profile or consumer acceptance of several foods and dishes—
soups and broths (Altug & Demirag, 1993; Ball, Woodward, Beard,
C2020 The Authors. Journal of Food Science published by Wiley Periodicals LLC on behalf of Institute of Food Technologists
2902 Journal of Food Science rVol. 85, Iss. 9, 2020 doi: 10.1111/1750-3841.15354
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Sensory and Consumer
Sciences
MSG in “better-for-you” foods . . .
Shoobridge, & Ferrier, 2002; Chi & Chen, 1992; Chung et al.,
2019; Jinap et al., 2016; Mojet, Heidema, & Christ-Hazelhof,
2004; Okiyama & Beauchamp, 1998; Roininen, Lahteenmaki, &
Tuorila, 1996; Yamaguchi & Takahashi, 1984), pork patties (Chun
et al., 2014), sausages (Dos Santos, Campagnol, Morgana, & Pollo-
nio, 2014; Woodward, Lewis, Ball, & Beard, 2003), potato chips,
puffed rice (Buechler & Lee, 2019) and mixed dishes (Leong,
Kasamatsu, Ong, Hoi, & Loong, 2016). Those studies support up
to 30% reduction in sodium from salt with MSG to maintain taste
parity. The strategy has not been tested as fully in complex dishes,
however, particularly those deemed “better-for-you” foods. The
term “Better-for-You Foods” was introduced recently to describe
those plant-forward foods with a desirable nutritional profile that
consumers should be eating more of. Some research initiatives
have focused on the class of foods and beverages labeled as such
(Elliott, 2012).
Negative consumer attitudes toward MSG, as documented for
United States (Wang & Adhikari, 2018) and New Zealand con-
sumers (Prescott & Yong, 2002), have also been an obstacle to its
broader adoption. Yet it is worth noting that sensory properties
weighed more than ingredient information in the acceptance of
vegetable soups with MSG (Prescott & Young, 2002), and that
college students’ response to MSG could be improved through
education (Jin & Han, 2019). With more convincing scientific ev-
idence and better communication, those attitudes have improved
and the outlook for the use of MSG in foods is positive (Mintel,
2019).
We have tested a number of sensory and culinary strategies for
dietary change with some success. The most impactful was our
proof-of-concept research on the ability of mushrooms to substi-
tute partially for meat without compromising the flavor profile or
consumer acceptance because of their umami properties (Guinard
et al., 2016; Myrdal-Miller et al., 2014). This led to the develop-
ment of the (beef-mushroom) blend and the widespread adoption
of blended burgers as a healthier alternative to traditional burgers in
US schools, cafeterias, and restaurants nationwide, as highlighted
in Scientific American (Jacewicz, 2016) and Nature (2018) editori-
als. Sonic’s Slinger C(Sonic Corp., Oklahoma City, OK, USA) has
since come to symbolize the success of blended burgers in fast
casual restaurants. We have also developed and tested, with suc-
cess, other “flip” strategies for the replacement of nutritionally-
contested ingredients with healthier ones with flavor-boosting
or matching properties, that is, the Flexitarian Flip (Spencer &
Guinard, 2018; Spencer, Cienfuegos, & Guinard, 2018a, 2018b)
and the Dessert Flip (Kurzer, Wiriyaphanich, Cienfuegos, Spang,
& Guinard, 2020).
We therefore hypothesized that because of its umami taste and
flavor-enhancing properties, MSG could be used as a flavor po-
tentiator in reduced-salt dishes in what essentially is a salt flip for a
lesser total sodium than the normal-salt, standard recipes without
compromising the consumer acceptance of those dishes. Corol-
lary hypotheses in this study were that reduced-salt versions of the
dishes would be liked less than the standard (regular-salt) recipes,
and that reduced-salt recipes with MSG added would be liked
more than the reduced-salt recipes.
2. MATERIALS AND METHODS
2.1 Dishes and recipes
This research investigated the mitigation of salt and sodium
reduction in four plant-forward, better-for-you dishes—roasted
vegetables (RV), a quinoa bowl (QB), a savory yogurt dip (SD),
Table 1–Sodium level (in g) for each recipe and percent sodium
reduction from the standard recipe.
Added sodium level (g)
Dish
RACC
(g)
Standard
recipe Reduced salt recipe MSG recipe
RV 110 0.27 0.14 (−47.81%) 0.19 (−31.26%)
QB 140 0.37 0.20 (−46.81%) 0.25 (−30.98%)
SD 28 0.16 0.07 (−58.56%) 0.09 (−46.46%)
CR 119 0.17 0.06 (−62.80%) 0.07 (−60.91%)
RACC, reference amount customar ily consumed.
and pork and cauliflower fried rice (CR). The criteria for their
selection were plant-based or focused, resonant, iconic, and easy
for consumers to replicate. The recipes for each dish were devel-
oped and kitchen tested at Pilot R&D (San Francisco, CA, USA)
in three versions—a standard recipe with a typical salt content for
the dish, a reduced-salt recipe, and the same reduced salt recipe
with MSG added at a level such that total sodium was still sub-
stantially lower than in the standard recipe. The salt (and sodium)
levels for the regular or typical version of each dish were established
through tastings of original iterations of the dishes at Pilot R&D.
The salt (and sodium) reduction levels and the MSG addition lev-
els were then determined in consultation with the manufacturer
(Ajinomoto) for best practices in the use of their Ac’cent MSG
ingredient. The sodium reduction in the reduced salt recipes, as
estimated through ingredient composition, ranged from 47% to
63% for the reduced-salt recipes and from 31% to 61% for the
MSG recipes (Table 1).
All recipes were prepared according to the specifications in Sup-
plement A the day before the tests. On the day of the tests, the
refrigerated, vacuum-sealed, 500 g, food grade polyethylene bags
with the prepared RV, QB, and CR recipes were reheated in a
steam vapor oven on full (100%) steam setting to 150 °Fand
plated 10 to 15 min before testing time. The savory dip (SD) was
kept refrigerated until session time and served at 38 °C. Serv-
ing sizes were 3 to 4 oz per plate for the RV, QB, and CR dishes,
and 2 oz per cup with 5 pieces of unsalted crackers for SDs.
2.2 Consumers
One hundred and sixty-three (163) consumers were recruited
via advertisement and listservs from the Davis and Sacramento ar-
eas in Northern California. The screener verified consumption of
both animal- and plant-based ingredients such as those in the BFY
foods in this study, and no food allergies. It did not inquire specif-
ically, however, about Better-for-You food consumption per se,or
MSG acceptance, so as not to reveal too much about the purpose
of the research and potentially bias consumer responses. The con-
sumers’ age ranged from 18 to 62 years, with a median of 26 years.
Consumer ethnicities were 50% Asian, 28% White/Caucasian, 7%
Latino, 2% Black/African, and 1% Native American.
2.3 Consumer test setting, design, and protocol
Testing took place in the Silverado Vineyards Sensory Theater,
a central location on the UC Davis campus designed for sensory
testing which can accommodate up to 50 consumers in partitioned
testing stations. All samples were prepared in the adjacent Carlos
Alvarez Food Innovation Laboratory.
Consumers completed two 30-min sessions at approximately the
same time on two consecutive days. Testing took place between
10 am and 6 pm. RV and then QB recipes were tested on the first
day and SD and then CR recipes on the second. For each dish
Vol. 85, Iss. 9, 2020 rJournal of Food Science 2903
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MSG in “better-for-you” foods . . .
Table 2–Mean (and SEM) of overall liking, liking of appearance, flavor and texture, likeliness to order, and preference rank mean.
Dish Recipe Overall liking Appearance Flavor Texture Likeliness to order Mean Rank
RV S 5.644 (0.140)a4.601 (0.124)a5.669 (0.140)a5.804 (0.133)a2.620 (0.095)a2.009 (0.062)a
R 5.767 (0.131)a4.546 (0.121)a5.773 (0.129)a5.613 (0.140)a2.595 (0.088)a1.966 (0.058)a
M 5.828 (0.138)a4.577 (0.120)a5.767 (0.143)a5.687 (0.134)a2.650 (0.092)a2.024 (0.066)a
QB S 5.785 (0.123)a3.534 (0.131)b6.147 (0.117)a5.521 (0.128)b2.699 (0.093)a1.951 (0.064)a
R 5.233 (0.127)b3.933 (0.126)a5.331 (0.125)b5.564 (0.124)b2.313 (0.086)b2.294 (0.057)b
M 5.908 (0.129)a3.828 (0.129)a6.190 (0.126)a5.877 (0.119)a2.847 (0.095)a1.755 (0.058)a
SD S 5.644 (0.139)b6.012 (0.103)a5.571 (0.142)b6.301 (0.109)a2.595 (0.102)a2.144 (0.061)b
R 5.810 (0.124)ab 6.117 (0.100)a5.810 (0.119)ab 6.239 (0.111)a2.620 (0.084)a2.049 (0.059)b
M 6.067 (0.123)a6.135 (0.102)a6.031 (0.127)a6.393 (0.105)a2.791 (0.095)a1.807 (0.065)a
CR S 4.939 (0.139)a5.006 (0.131)b4.951 (0.142)a5.859 (0.114)a2.190 (0.091)a1.819 (0.060)a
R 4.380 (0.135)b4.945 (0.129)b4.344 (0.139)b5.644 (0.124)b1.840 (0.075)b2.371 (0.054)b
M 4.933 (0.135)a5.528 (0.136)a4.853 (0.137)a5.926 (0.116)a2.178 (0.088)a1.810 (0.059)a
S, Standard; RS, reduced salt; M, MSG recipe.
Different superscripts indicate significant differences (P<0.05) among the three recipes of a particular dish for each measure.
the order of serving of the three recipes—standard, reduced-salt,
and reduced-salt with MSG, was randomized across consumers.
Consumers were asked to cleanse their palates with water and
crackers between samples; and to take a 10-minute break between
the first and the second dish on each day.
At the end of the second day, consumers completed an
exit survey with questions regarding their demographics, cook-
ing and eating habits, and attitudes regarding food and health
(Supplement B).
For each recipe, consumers were asked to indicate their degree
of liking overall, and then for the appearance, flavor (taste and
smell), and texture/mouthfeel of the dishes on the nine-point he-
donic scale (Peryam & Pilgrim, 1957); to rate the adequacy of
the flavor (taste and smell), saltiness, and aftertaste of the recipes
on five-point just-about-right (JAR) scales; and to describe the
sensory characteristics of the recipes using a check-all-that-apply
(CATA) list of 16 terms—flavorful, salty, sweet, sour, bitter, com-
plex, bland, delicious, fresh, rancid, balanced, savory, lingering
aftertaste, nutty, cheesy, and meaty. Consumers were then asked
how likely they would be to order the recipe at a restaurant on
a five-point bipolar scale from “I would definitely not order this
dish” to “I would definitely order this dish.” They were then asked
what specifically they liked and disliked about the dish in an open
comment section. And finally, consumers were asked to rank the
three recipes for each dish from most liked to least liked.
2.4 Data analysis
To compare the hedonic ratings and other parametric values
of the three recipes across all consumers, two-factor ANOVAs
with a repeated measure design were conducted separately for
each of the four dishes, with recipes and consumers as fixed and
random effects, respectively. Duncan’s multiple range test was used
for post hoc comparisons (P<0.05). We assessed the relation
among the various hedonic measures with Pearson’s correlation
coefficient.
A nonparametric Friedman rank sum analysis was performed on
the preference ranking data for each dish separately. In addition,
R-index analyses (Xia et al., 2020) were applied to these ranking
data, giving an actionable choosing probability (RMAT value) of
one recipe being preferred over the others.
For each dish, penalty analyses were conducted to relate hedonic
ratings to the JAR scores for flavor, saltiness, and aftertaste. The
difference between the average liking score of each non-JAR level
and the average liking score of the JAR level was computed for
each attribute. For each product and each attribute, an ANOVA
was performed including contrast analysis in such a way that the
main effect for the JAR level was zero (αJAR =0; Lˆ
e&Worch,
2015).
For the CATA descriptors, Cochran-Q analyses with family-
wise controlled significance level were conducted to assess overall
differences among recipes for each attribute. For multiple com-
parisons among the recipes, permutation tests with Benjamini–
Hochberg adjusted P-value (Benjamini & Hochberg, 1995) were
used. This test controls for the false discovery rate and thus is
more powerful and suitable for parity testing. The descriptors
were also linked to the overall liking data by penalty-lift analysis.
Furthermore, correspondence analyses with chi-square distances
were conducted to examine the associations between the recipes
and the CATA descriptors.
To study preference segmentation, a hierarchical clustering on
principal components (HCPC) algorithm was performed on the
overall liking data pooled across all dishes and recipes (12 samples
in total), using Ward’s criterion and the Euclidean distance. All
statistical analyses were performed in R (R Core Team, Vienna,
Austria).
3. RESULTS AND DISCUSSION
3.1 Hedonic ratings
The main hypothesis in this study—that reduced-salt recipes
with added MSG would be liked as much as the standard recipes,
was proven correct. The reduced-salt recipe with added MSG was
liked the same as the standard recipe for RV, QB, and CR, and
significantly more (P<0.05) for SD (Table 2).
An examination of specific hedonic ratings for appearance, fla-
vor, and texture shows that the appearance of the MSG recipes
was liked more than that of the standard recipe in the QB and CR
dishes; the flavor liking ratings mirrored the overall liking ratings.
And even though salt reduction and MSG addition would mostly
be expected to alter the flavor of a dish, the texture of the QB
with MSG was liked better than that of the other two recipes,
and its appearance was liked better than that of the standard recipe
(P<0.05).
The corollary hypothesis that salt reduction would lower liking
for the dishes was only verified for the QB and CR dishes (Table 2).
Similarly, the other corollary hypothesis that MSG addition
would enhance liking of a reduced-salt recipe was only verified
for the QB and CR dishes (Table 2).
All hedonic ratings were significantly correlated with each other
for all four dishes (P<0.001), but we found the highest correlation
2904 Journal of Food Science rVol. 85, Iss. 9, 2020
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MSG in “better-for-you” foods . . .
Table 3–Pearson’s correlation coefficients among hedonic ratings across (a) RV, (b) QB, (c) SD, and (d) CR dishes.
Overall liking Appearance liking Flavor liking Texture liking Likeliness to order
(a) RV dishes
Overall liking 1.00
Appearance liking 0.42∗∗∗ 1.00
Flavor liking 0.90∗∗∗ 0.36∗∗∗ 1.00
Texture liking 0.61∗∗∗ 0.36∗∗∗ 0.58∗∗∗ 1.00
Likeliness to order 0.75∗∗∗ 0.39∗∗∗ 0.74∗∗∗ 0.58∗∗∗ 1.00
(b) QB dishes
Overall liking 1.00
Appearance liking 0.37∗∗∗ 1.00
Flavor liking 0.85∗∗∗ 0.28∗∗∗ 1.00
Texture liking 0.57∗∗∗ 0.39∗∗∗ 0.57∗∗∗ 1.00
Likeliness to order 0.74∗∗∗ 0.38∗∗∗ 0.74∗∗∗ 0.59∗∗∗ 1.00
(c) SD dishes
Overall liking 1.00
Appearance liking 0.33∗∗∗ 1.00
Flavor liking 0.92∗∗∗ 0.31∗∗∗ 1.00
Texture liking 0.54∗∗∗ 0.54∗∗∗ 0.52∗∗∗ 1.00
Likeliness to order 0.77∗∗∗ 0.28∗∗∗ 0.77∗∗∗ 0.50∗∗∗ 1.00
(d) CR dishes
Overall liking 1.00
Appearance liking 0.42∗∗∗ 1.00
Flavor liking 0.92∗∗∗ 0.40∗∗∗ 1.00
Texture liking 0.62∗∗∗ 0.53∗∗∗ 0.57∗∗∗ 1.00
Likeliness to order 0.78∗∗∗ 0.38∗∗∗ 0.77∗∗∗ 0.53∗∗∗ 1.00
∗∗∗Significant correlation (P<0.001, Bonferroni adjusted significance level for pairwise comparison at α=0.001).
between flavor liking and overall liking for all four dishes (r=0.85
or higher, P<0.001; Table 3).
3.2 Likeliness to order
This new variable that we added to our assessment tools to
account for the fact that dishes may be ordered in a restaurant
setting or for takeout produced the same outcomes as the hedonic
ratings of the recipes. There was no difference in likeliness to
order between the standard recipes and the reduced-salt recipes
with MSG, thus verifying further our main hypothesis (Table 2).
And likeliness to order was again significantly higher in the MSG
recipes than in the reduced-salt ones for QB and CR only.
3.3 Relation among hedonic and likeliness to order
ratings
The relationship between hedonic and likeliness to order rat-
ings was explored using Pearson’s correlation coefficient across
the recipes for each dish. Those with a significant correlation
(P<0.001, Bonferroni adjusted P-value for all pairwise com-
parisons at family-wise significance level of 0.001) are noted in
Table 3. A highly significant correlation was observed between
likeliness to order and overall liking for all four dishes (r=0.74
or higher, P<0.001), as well as with liking of flavor (r=0.74 or
higher, P<0.001).
3.4 Preference rankings
The outcomes of the hedonic ratings on the nine-point hedonic
scale were confirmed by the preference rankings with, as expected,
even greater discrimination (Table 2). Our R-index analysis on
the preference ranks found that there was no difference in prefer-
ence probability between the standard recipe and the reduced-salt
recipe with added MSG for RV and CR, and that the reduced-salt
recipe with MSG actually was significantly more likely to be pre-
ferred for QB and SD (P<0.05; Table 4), and the addition of
MSG led to significant preference probability over the reduced-salt
Table 4–RMAT indices showing the probability of choosing the
MSG recipes over the others.
Probability of choosing MSG recipe over
Dish Standard recipe Reduced salt recipe
RV 49.49% 47.94%
QB 56.65%∗69.25%∗
SD 61.36%∗58.40%∗
CR 50.17% 70.19%∗
∗Signifi cant prefe rences (P<0.05), based on Bi and O’Mahony (2007).
recipe for QB, SD, and CR, but not RV (no preference; P<0.05;
Tabl e 4 ) .
3.5 Just-About-Right (JAR) ratings
Consumers’ JAR ratings of the adequacy of flavor, saltiness, and
aftertaste are collapsed into three categories in Table 5—too little,
just-about-right, or too much. For RV, the three recipes showed a
similar distribution. More than 50% of consumers rated the flavor,
saltiness, and aftertaste of the three recipes as JAR, with the MSG
recipe receiving slightly more JAR ratings for flavor and saltiness,
but not significantly. The reduced salt recipe was found to be
significantly more lacking in saltiness compared to the other two
recipes. For QB, more than 50% of consumers rated the reduced
salt version as lacking in flavor and saltiness. In contrast, both the
MSG and the standard recipe for this dish received more than 60%
flavor and saltiness JAR ratings. For SD, only the MSG recipe
received more than 50% JAR ratings for flavor. It also received
the highest JAR selection (69.33%) for saltiness. Yet, its rating
distribution was not different from that of the reduced salt recipe.
Finally, for CR, the three recipes received high “too much” ratings
for flavor and ‘too little’ ratings for saltiness, more than JAR ratings
for each attribute. There was no difference between the JAR rating
distributions of the MSG recipe and the reduced salt recipe for all
three attributes.
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Table 5–Percentage of JAR category choice by consumers across all dishes and recipes for adequacy of flavor, saltiness, and
aftertaste (n=163 consumers).
Flavor Saltiness Aftertaste
Dish Recipe TL JAR TM SigaTL JAR TM SigaTL JAR TM Siga
RV S 10.43 54.60 34.97 a 9.82 66.87 23.31 a 9.20 59.51 31.29 a
R 20.86 50.92 28.22 a 22.09 68.10 9.82 b 15.95 60.12 23.93 a
M 14.72 55.83 29.45 a 14.11 76.69 9.20 a 9.20 57.67 33.13 a
QB S 14.11 60.12 25.77 a 15.34 63.80 20.86 a 9.82 57.67 32.52 a
R 53.37 38.04 8.59 b 62.58 34.36 3.07 b 27.61 56.44 15.95 b
M 23.93 61.35 14.72 c 27.61 66.87 5.52 c 14.11 60.12 25.77 a
SD S 11.04 44.17 44.79 a 13.50 56.44 30.06 a 13.50 55.83 30.67 a
R 31.29 39.88 28.83 b 28.83 61.35 9.82 b 19.63 61.35 19.02 a
M 23.31 50.92 25.77 b 20.25 69.33 10.43 b 16.56 55.83 27.61 a
CR S 17.18 39.26 43.56 a 47.24 42.33 10.43 a 11.04 50.92 38.04 a
R 33.13 21.47 45.40 b 63.80 27.61 8.59 b 18.40 47.24 34.36 a
M 36.20 30.67 33.13 b 57.06 36.20 6.75 b 15.34 56.44 28.22 a
S, Standard; R, reduced salt; M, MSG recipe; TL, too little; JAR, just about right; TM, too much.
aDifferent letters (a, b, c) in Sig column indicate significant differences among the JAR scores distribution, determined using CMH method and Stuart–Maxwell as post-hoc at
family wise significance level of 0.05.
Figure 1–Penalty analyses of the three roasted vegetables (RV) recipes for three attributes: saltiness (“salt”), flavor (“flav”), and aftertaste (“aft”).
Note: Significant non-JAR categories (P<0.05) are shown in larger font size and marked with “∗.”
Penalty analyses were performed on the JAR data to relate
the impact of an attribute being rated as too low or too high
on overall liking of the recipes by consumers. The outcomes are
plotted in Figures 1 to 4 as mean drops in overall liking against
the percentage of consumer selecting too low or too high. A
proportion of 20% was used as the minimum for inclusion in the
figures. Of special interest are attributes located in the upper right
quadrant of the plots, because they represent a high percentage
of consumers and large penalties. Moreover, significant non-JAR
attributes (P<0.05) are highlighted with an asterisk (∗)and
printed with a larger font size on those figures (1 to 4).
Figure 1 shows the penalty analyses for the three RV recipes.
They received significant penalties (about two points on the
nine-point hedonic scale) when flavor was deemed too much.
2906 Journal of Food Science rVol. 85, Iss. 9, 2020
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MSG in “better-for-you” foods . . .
Figure 2–Penalty analyses of the three quinoa bowl (QB) recipes for three attributes: saltiness (“salt”), flavor (“flav”), and aftertaste (“aft”).
Note: significant non-JAR categories (P<0.05) are shown in larger font size and marked with “∗.”
Additionally, too much of an aftertaste in the three recipes caused
a significant drop in overall liking. For QB (Figure 2), the reduced
salt recipe suffered significant penalties from flavor, saltiness, and
aftertaste being rated as too low. The lack of flavor and saltiness
in particular were reported by high proportions of consumers. In
the MSG version of QB, inadequate flavor intensity (too much
for some consumers and too little for others) correlated to signif-
icant mean drops in overall liking. This so-called equal bimodal
data (ASTM MNL-63), however can be disregarded as both ends
corresponded to less than 50% consumers (Table 5). For the three
SD recipes (Figure 3), too much flavor caused the greatest penal-
ties. This was especially important for both the standard and MSG
recipes, for which mean drops in overall liking exceeded 2 points
on the nine-point hedonic scale. Finally, the same trend was also
seen for CR (Figure 4)—too much flavor resulted in significant
penalties for the three recipes. In addition, significant mean drops
were also associated with the samples having too much aftertaste.
3.6 Check-All-That-Apply (CATA)
The frequencies of selection of the 16 CATA attributes for the
recipes are shown in Supplement C. There were no differences in
frequency of selection of the attributes among the RV recipes after
adjusting for the family-wise significant level (Padj >0.05). For
QB, Cochran Q analyses with permutation test and Benjamini–
Hochberg P-value adjustment showed that the reduced salt version
had lesser selections of the flavorful, salty, complex, delicious,
balanced, savory, and aftertaste attr ibutes (P<0.001), and greater
selection of the bland one (P<0.001), compared to the other
two recipes. For SD, the MSG recipe was identified more often
as sweet (P=0.0018) than the others. For CR, sour and rancid
were picked significantly less often for the MSG recipe (P<
0.001), whereas the reduced salt recipe was described less often as
flavorful or savory than the others (P<0.001).
To visualize these relationships, symmetric biplots showing both
the recipes and the CATA descriptors were constructed from cor-
respondence analysis of the matrix of CATA selections across
recipes for each dish (Figure 5). Generally, it can be seen that
the reduced salt recipes of the four dishes were always associated
with the attribute “bland.” They were also associated with the
term “bitter” in both QB and CR dishes. The standard recipes
were associated with the attribute “salty” in the four dishes. Inter-
estingly, they were also associated with the term “sour” in both RV
and QB dishes. The MSG recipes were positioned toward terms
such as “delicious,” “flavorful,” and “balanced.” In addition, they
were also associated with the term “savory” in the SD and CR
dishes.
Finally, the selection of CATA attributes was linked to the hedo-
nic ratings for the recipes through penalty-lift analysis (Figure 6).
We found that for all dishes, the attributes delicious, flavorful,
balanced, fresh, and savory consistently were positive drivers of
liking (P<0.05), whereas the attributes rancid, bitter, and bland
consistently were negative ones (P<0.05).
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Figure 3–Penalty analyses of the three savory dip (SD) recipes for three attributes: saltiness (“salt”), flavor (“flav”), and aftertaste (“aft”).
Note: significant non-JAR categories (P<0.05) are shown in larger font size and marked with “∗.”
3.7 Preference mapping and clustering
HCPC of the overall liking ratings across the twelve (four dishes
×three recipes) better-for-you foods in this study separated con-
sumers into three preference clusters—cluster 1 (n=52), cluster
2(n=43), and cluster 3 (n=68; Figure 7). Consumers were
loosely divided into those who liked everything (clusters 2 and
3) and those who were neutral or disliked everything along the
first dimension (which accounted for 29% of the variance, a large
amount given the dimensions of the data matrix). By contrast,
differences in liking among the three versions within each dish
were not as segmenting.
It is potentially misleading to represent consumer acceptance
as an average liking vector (shown in blue in Figure 7) when
preference segmentation exists. So we examined the respective
mean overall liking ratings of the three preference clusters for the
various dishes and recipes (Figure 8). It is apparent that cluster
1, with 52 consumers, did not particularly like the (BFY) foods
they tested, with mean hedonic ratings ranging between 4 and 6
on the nine-point hedonic scale. But they liked (or disliked) the
standard recipe and the MSG recipe the same for the RV and CR
dishes, and actually liked the MSG recipe best for the QB and SD
dishes. The 43 consumers in cluster 2 on the other hand, preferred
the MSG recipe over the standard one for the RV and SD dishes,
and showed parity in liking between them for the QB and CR
dishes. Cluster 3, the largest with 68 consumers, liked the MSG
and the standard recipes across all dishes (with almost all mean
ratings above 6 on the scale), and the same.
An examination of the characteristics of the consumers in each
preference segment (Table 6), as measured through the exit survey
shows that cluster 1 included more Asians and consumers who used
MSG more often than the other two clusters, yet those differences
were not quite significant. Cluster 2 had the most diverse ethnicity
and was characterized by a significantly higher stated liking for the
taste and flavor of MSG (P=0.026). Cluster 3, which liked the
recipes more than the other two clusters, had more women and
more Caucasians, yet the differences were not quite significant.
3.8 MSG for mitigation of salt (and sodium) reduction
Our findings support the hypothesis that MSG can be added to
plant-forward, better-for-you dishes in which salt has been sub-
stantially reduced to maintain (or even improve) consumer accep-
tance and still achieve significant sodium reduction. Furthermore,
all the measures of consumer acceptance we collected consistently
support this hypothesis—overall degree of liking (both as aver-
age liking and liking by the preference segments we uncovered),
liking of flavor, preference rankings, flavor, saltiness and after-
taste JAR ratings and likeliness to order (Tables 2, 4, 5 and Fig-
ures 7, 8). The sensory map that was derived from correspondence
analysis of the CATA selections also serves to explain why that is, as
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Figure 4–Penalty analyses of the three pork cauliflower rice (CR) recipes for three attributes: saltiness (“salt”), flavor (“flav”), and aftertaste (“aft”).
Note: Nonsignificant JAR categories (P<0.05) are shown in larger font size and marked with “∗.”
all MSG recipes were characterized as “savory,” “flavorful,” “de-
licious,” and “balanced”—all holistic and/or hedonic descriptors
with positive connotations in the context of these dishes (Figure 5).
What the preference mapping and clustering analysis showed is
that the addition of MSG to the reduced-salt recipes led to parity
in (or even higher) liking with the standard recipes for a majority of
the consumers in this study. We can make this statement because
for any given dish, those preference segments with consumers
rating the MSG recipe the same or higher than the standard recipe
added up to more consumers than those with consumers who did
not (Figure 8).
Our findings are therefore consistent with previous research
that showed successful mitigation of salt reduction with MSG in a
range of foods (Altug & Demirag, 1993; Chun et al., 2014; Jinap
et al., 2016).
It is also worth noting that very little MSG was required to
accomplish parity of consumer acceptance between standard and
reduced-salt recipes of four “better-for-you foods.” The sodium
increase from the reduced-salt recipe to the reduced salt with
MSG recipe ranged from only 2% to 15% depending on the recipe
(Table 1).
The FDA standard for a “reduced-sodium” product is at least
25% less sodium than the original product. In this study, the ap-
plication of MSG was successful in reducing sodium level by more
than 30% from the standard recipes. This highlights the poten-
tial of MSG application in the formulation of “reduced-sodium”
foods. Moreover, for the CR dish, the MSG application reduced
sodium by as much as 60%. This meets the FDA requirements
for “light in sodium” labeling. We should also mention that pork,
one of the main ingredients in the CR dish, contains 9 mg free
glutamate and approximately 200 mg of other ribonucleotides per
100 g (Ninomiya, 1998), thus potentially working synergistically
with MSG to boost flavor. This suggests that the extent of MSG
application should consider the natural occurrence of glutamic
acid and other naturally occurring flavor enhancing principles.
3.9 Cutting salt alone is not viable
The main challenge of reducing sodium content in foods may
be the negative impact on the flavor profile and consumer accep-
tance (Hoppu et al., 2017; Liem, Miremadi, & Keast, 2011). This
was confirmed in this study, as the reduced-salt recipes received
mostly lower ratings across most of the four dishes and most of
the acceptance measures we collected. The fact that salt reduction
only lowered overall liking for two of the four dishes (quinoa bowl
and pork cauliflower fried rice), however, came as a surprise be-
cause the salt reduction (of 48% to 63%, depending on the dish)
was substantial and comparable across dishes. Liem et al. (2011)
indicate that a sodium reduction of up to 30% may be acceptable
in processed foods if introduced gradually (over 3 years), and that
the reduction can be up to 50% as long as it is in parallel with the
addition of a flavor-boosting ingredient, such as soy sauce or dried
bonito.
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Figure 5–Correspondence analysis plots of CATA attributes for the three recipes (S: Standard, R: Reduced Salt, M: MSG recipe) of each dish (RV, QB, SD,
and CR).
And interestingly, the quinoa bowl and the pork cauliflower
fried rice again were the only two dishes in which the hypoth-
esis that MSG addition to the reduced-salt recipe would increase
liking was verified. It could be that the greater complexity of
these two dishes, compared to the roasted vegetables or the savory
yogurt dip, made for a better platform to illustrate the sensory
effects of combined salt reduction and MSG addition. Indeed,
all three hypotheses in this research were verified with these two
dishes.
3.10 Hedonic scaling, preference ranking, and likeliness
to order produce consistent results
As expected, preference rankings were consistent with the he-
donic ratings, but they were also more discriminating, with a
significant preference probability found by R-index analysis for
the recipes with MSG over the standard recipes in both QB and
SD, whereas overall liking was only significantly higher in the case
of SD; and a significant preference probability for the recipes with
MSG over the reduced-salt recipes for QB, SD, and CR, whereas
overall liking was only significantly higher in the case of QB and
CR (Tables 2 and 3).
Given that the main variables in this study were salt reduction
and flavor enhancement with MSG, it was logical that the highest
correlator to overall liking was liking of flavor.
Because the concept of Better-for-You foods is equally applica-
ble to homes, takeout or food service and restaurants, we wanted
to explore another measure of consumer acceptance in “likeliness
to order.” We found some use of the measure in the literature
(Anzman-Frasca et al., 2014; McCall & Lynn, 2008). In their
study of the effects of menu item descriptions on perception of
quality, price, and purchase intention, McCall and Lynn (2008)
found a highly significant correlation between perceived quality
of the dish and likelihood of purchasing the item. Similarly, we
found a highly significant correlation between hedonic ratings and
likeliness to order. One would indeed expect a consumer to be
likely to order a dish that he or she liked. There could also have
been a halo effect from one measure (degree of liking) appearing
first on the scorecard to another (likeliness to order) appearing
after.
3.11 Flavor, saltiness, and aftertaste JAR scaling and
CATA selections document how MSG works
The saltiness JAR ratings serve to validate our experimental
design with regard to salt reduction. The incidence of just-about-
right saltiness ratings were lower, and that of too-low saltiness
higher for the reduced salt recipes in all four dishes, especially
for the QB dish even though the salt reduction was the low-
est in that dish (Tables 1 and 5). Those findings were mirrored
by the flavor JAR ratings, with too-low flavor percentages go-
ing up for all four reduced salt recipes (again, most notably for
the QB dish), thus emphasizing the key role of sodium chlo-
ride in flavor strength adequacy. And then, saltiness adequacy
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Figure 6–Penalty-Lift Analyses relating CATA attribute selections to hedonic ratings for the four dishes.
and flavor adequacy improved with the addition of MSG to the
reduced salt recipes, with more just-right saltiness ratings than re-
duced salt recipes for all dishes except CR, and more just-right
flavor ratings across all four dishes. These findings are all consis-
tent with MSG boosting flavor and mitigating salt (and saltiness)
reduction.
We included aftertaste in our JAR evaluations because it is a
typical sensory characteristic of MSG and other umami tastants,
and an overly lingering aftertaste can become an undesirable fea-
ture (Burseg, Camacho, & Bult, 2012; Giovanni & Guinard, 2001;
Horio & Kawamura, 1990; Yamaguchi ad Ninomiya, 2000). But
that did not seem to be the case here, as the MSG recipes did
not receive significantly more too-much aftertaste ratings than the
standard, regular-salt recipes (Table 5).
3.12 Consumers and MSG
Of all the consumers who participated in the study, the exit sur-
veys revealed that only 16% considered themselves regular users
of MSG. Of the remaining nonusers, 54% admitted that either
they didn’t know how to use MSG or they were not aware of it.
About 23% of the non-users did not use MSG due to availability
issues. Finally, about 47% of the non-users thought that MSG was
not good for their health or were told not to use it by household
members. It is unfortunate to see that the main reasons for not
using MSG continue to be mainly awareness issues, either of its
applications or health connotations. Despite a widespread belief
that MSG can be detrimental for health (e.g. trigger for asthma
or migraine headache), there is no consistent clinical evidence to
support this claim. In fact, the safety of MSG has been evalu-
ated by scientific committees and regulatory agencies and MSG
is deemed to be safe. For comprehensive reviews on the safety
aspects of MSG, see Freeman (2006), Jinap and Hajeb (2010), and
Maluly, Arisseto-Bragotto, and Reyes (2017). This research did
not purport to examine consumer attitudes regarding MSG but
rather focused on the sensory effectiveness and appeal of MSG in
the mitigation of sodium reduction in a salt flip. Yet it is worth
reiterating that attitudes regarding MSG have improved and that
the outlook for its application in foods is positive. As stated in a
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MSG in “better-for-you” foods . . .
Figure 7–HCPC on uncentered overall liking matrix. Left: Factor map showing the PCA of the 12 samples and the vector of average overall liking. Right:
Variable map showing the distribution of the three clusters of consumers on the first two principal components space.
Figure 8–Average overall liking and mean standard error (SEM) by recipe for clusters 1 (n=52), 2 (n=43), and 3 (n=68) based on HCPC of raw
hedonic ratings.
recent Mintel report (2019), “Americans have been historically
somewhat squeamish about seafood sauces (e.g., fish sauce, oyster
sauce) and MSG for different reasons, but both of these items of-
fer appealing umami taste benefits that consumers have only just
begun to embrace with the help of celebrity chefs and restaurants.
Look for fast future growth of these ingredients on restaurant
menus in the coming years.”
3.13 Study limitations
Several ratings point to significant issues with the formulation
of the pork cauliflower fried rice dish. In this study, however, we
purposely used a simple baseline seasoning to be able to showcase
the effects of salt and MSG more clearly. Furthermore, the recipes
were plated without garnish to avoid possible halo effects from the
presentation of the food, and that might have brought the hedonic
ratings for the recipes down.
Finally, it should be noted that this study could have included
many more versions of these prototypes with varying levels of
salt and MSG to optimize results. Some optimization method,
like response surface methodologies have been used to predict
the optimum combination of MSG and salt in the past (Chi &
Chen, 1992; Yamaguchi & Takahashi, 1984). However, this study
provides a starting point for these prototypes of better-for-you
foods.
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Table 6–Characteristics of consumer preference clusters based on HCPC on overall liking data.
Cluster 1 (n=52) Cluster 2 (n=43) Cluster 3 (n=68)
Liking characterization Dislikes everything
Likes RV, dislikes CR and QB
(“low salt” and MSG) Likes everything
Female (%)a48.08 30.88 70.59
White/Caucasian (%) 19.23 27.91 35.29
Asian (%) 65.38 41.86 42.64
Mixed (%) 3.85 16.28 13.23
bFollow healthy and balanced diet 4.79 4.49 4.50
bDiet low in sodium 4.29 3.84 4.21
bHealthiness of food does not impact food choice 3.00 3.72 3.25
bLike the taste and flavor of MSGc4.56a 5.26b 4.56a
bAware that MSG can be used to reduce sodium level 3.88 4.30 3.94
dFrequency of meal preparation at home 3.92 3.72 3.91
dFrequency of using MSGa1.77 1.46 1.37
Note: For gender and ethnicities, values represent percentages of the sample population. Percentage data were analyzed using Chi-square analysis on the raw nominal data. For
questions regarding eating habits and attitudes, values represent means of the raw data within clusters. The means were compared using nonparametric Kruskal–Wallis statistics.
aAlmost significant at P<0.10.
bStatements were evaluated on a seven-point bipolar agreement scale with words, from “Strongly disagree” to “Strongly agree.”
cSignificant at P<0.05, different superscript indicates differences using Duncan multiple comparisons.
dStatements were evaluated on a 5-point frequency categories: “Never or almost never” (1), “1-3 times/month” (2), “1-5 times/week” (3), “Daily or almost daily” (4), “Twice or
more per day” (5).
4. CONCLUSION
We conclude that MSG can successfully be used in a Salt Flip to
mitigate salt and sodium reduction without compromising con-
sumer acceptance of better-for-you foods, particularly in complex
dishes such as a quinoa bowl or pork cauliflower fried rice. This
conclusion is supported across all the measures of consumer ac-
ceptance we collected in this study—overall liking (on average or
by preference segment), liking of appearance, flavor and texture,
preference ranking, likeliness to order and just-about-right scaling
of flavor, saltiness, and aftertaste.
We can also document that for the better-for-you dishes we
tested, the MSG recipes were consistently described as “savory,”
“flavorful,” “delicious,” and “balanced” by consumers, thus point-
ing to the desirable way in which the parity in consumer accep-
tance between standard recipes and reduced-salt with MSG recipes
was achieved, and confirming MSG’s already well-documented
flavor-boosting properties.
ACKNOWLEDGMENTS
This research was funded by a grant from Ajinomoto Co, Inc.
We thank Stephanie Walker and Tia Rains for their advice re-
garding study design, execution and reporting, and Tyler Simons,
Amalie Kurzer, Mackenzie Batali, Natalie Garcia, and Andrew
Weiss for their assistance with sample preparation and serving.
AUTHOR CONTRIBUTIONS
Author Halim collected and analyzed the data, and co-drafted
the manuscript. Authors Bouzari and Felder designed and prepared
the recipes. Author Guinard designed the research and co-drafted
the manuscript.
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Supporting Information
Additional supporting information may be found online in the
Supporting Information section at the end of the article.
Tabl e A 1 .RV dishes formulae; weight of ingredients (g) per
110 g.
Tabl e A 2 .QB dishes formulae; weight of ingredients (g) per
140 g.
Tabl e A 3 .SD dishes formulae; weight of ingredients (g) per 28 g.
Tabl e A 4 .CR dishes for mulae; weight of ingredients (g) per 119 g.
2914 Journal of Food Science rVol. 85, Iss. 9, 2020
