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J Food Process Preserv. 2021;00:e16027. wileyonlinelibrary.com/journal/jfpp
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1 of 16
https://doi.org/10.1111/jfpp.16027
© 2021 Wiley Periodicals LLC.
1 | INTRODUCTION
Seafood is one of the most important sources of highly bioavailable
animal proteins and can play an important role in the human health
(Bhat et al., 2021a, 2021b). Different kinds of trout- fish (including
rainbow) are good sources of protein (>18%w/w), potassium (0.49 g/
kg), and zinc (0.75 g/kg) (Kiczorowska et al., 2019). The modernity
and new lifestyle changed the traditional eating habit of families
from “making food at home” from scratch to use “ready- to- cook
food” (RTCF). One of the RTCF is fish burger, which is produced
with different fish category, color, shape, and quality aspects (mainly
nutritional and sensory characteristics). Although fish burger is fro-
zen (at −18°C) after pro duction to ex tend its she lf life, it remains
safeonlyforfewdayswhenisstored at1to4°C (Mahmoudzadeh
et al., 2010; Shaviklo et al., 2016). The fish and fish burger are sensi-
tivetooxidativespoilage,enzymaticreactions,andmicrobialgrowth
even in frozen storages. Although cooling and freezing processes
can protect the safety and nutritional values of seafoods (such as
fishburger),theirnaturalcolor,andorganoleptic(textureandsmell)
properties will change during storage due to physiochemical and
Received:27May2021
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Revised:7S eptember2021
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Accepted:29Septem ber2021
DOI: 10.1111/jfpp.16027
ORIGINAL ARTICLE
Effects of extracted propolis (Apis mellifera) on physicochemical
and microbial properties of rainbow- trout fish burger patties
Marjan Shabani1 | Mohsen Mokhtarian1 | Ahmad Kalbasi- Ashtari2 |
Reza Kazempoor3
1Department of Food Science and
Technology, Roudehen Branch, Islamic Azad
University, Roudehen, Iran
2Biological and Agricultural Engineering
Depar tment,TexasA&MUniversity,College
Station,Texas,USA
3Department of Biology, Roudehen Branch,
Islamic Azad University, Roudehen, Iran
Correspondence
MohsenMokhtarian,DepartmentofFood
Science and Technology, Roudehen Branch,
Islamic Azad University, Roudehen, Iran.
Email: mokhtarian.mo@riau.ac.ir
Ahmad Kalbasi- Ashtari, Biological and
AgriculturalEngineeringDepartment,Texas
A&MUniversity,CollegeStation,TX,USA .
Email: akalbasia@tamu.edu
Abstract
Freeze-drying of p ropolis (FDP) obtaine d from ethanol ext raction of raw prop olis
enhanced its total phenolic and reduced effective concentration (EC50) substantially
>95%and99%.Thenthegroundfishofrainbow-troutwasmixedwithdifferent(0.1,
0.2 and 0.4%) levels of FDP to make frozen fish burger (FFB), and analyzed for phys-
icochemicalandmicrobialcharacteristicson0-,30-,60-,and90-daysof−18°Cstor-
age.WhilethePV,TBA,TVN-B,andoverallcolorchanges(∆E) of FFB with highest
FDP increased only ~30, 120, 25%, and 7.3 unit, they increased in control sample up
to 90, 183, 40%, and 13.1 unit after 90- days frozen storage. Whereas the cooked
FFB patties (containing 0.4% FDP) had significantly higher cooking yield, its fat and
moisture retentions were considerably more than the control sample. Additionally, its
colony forming unit (CFU) for Staphylococcus aureus, coliform, yeast, and mold counts
were 1,040, 219, and 19.3 times less than the control.
Novelty impact statement
• Freeze-dryingofpropolis(FDP)afterethanolextractionofrawpropolisimproved
its TPC (total phenolic content) and reduced its effective concentration (EC50)
substantially more than 95% and 99%.
• Addition of FDP to rainbow- trout fish burger patties significantly reduced its dete-
riorativechemicalindexes(PV,TBARS,TVN-B),andmicrobialloadsfor3months
storageat−18°C.
• Combining of FDP with fish burger patties (at 0.4 g/100 g) could significantly in-
creaseitscookingproperties(extrayieldandmoreretentionsoffatandmoisture)
even after 90- day of frozen stowage.
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SHABANI et Al.
microbiological factors (Licciardello et al., 2018). Furthermore, the
annoying off-flavorsandodorsoffishis the oxidationresultofun-
saturated fatty acids (mainly omega- 3fattyacid)existedinfish.The
freshness of fish burger (like other seafood) is evaluated by moni-
toring itsperoxidevalue (PV)and thiobarbituric acid reactive sub-
stances(TBARS)(Mahmoudzadehetal.,2010).
Although preser vatives (natural or synthetic) are added to fish to
prevent its undesirable chemical reactions and microbial activities,
their identifications and quantifications (at the permissible levels)
should be easy, simple, and without any difficulty ( Tzima et al., 2015).
Thesyntheticantioxidants(suchastert-butyl-hydroxyanisole[BHA],
2 , 6 - d i - t e r t - b u t y l - p - h y d r o x y t o l u e n e [ B H T ] , t e r t - b u t y l h y d r o q u i n o n e
[TBHQ], ascorbic acid, and propyl gallate [PG]) can inhibit fat oxi-
dation through “their reaction with free radicals, chelating catalytic
metals and alsoby actingasreactivespecies scavenger,”However,
there is a large debate about their safety, as they may cause tera-
togenicity,carcinogenicity,andresidualtoxicityespeciallyinstored
food. This is the key reason that consumers are doubtful and hesit ate
to consume food having synthetic preservatives. Since some combi-
nationsofsyntheticpreservativewithdifferentfoodmaymaketoxic
and undesirable compounds, there is more and more requests for
natural preservatives (Tzima et al., 2015).
Although RTCF products have numerous demands in the mar-
ket, they need safe and healthy preservatives at permissible levels
to protect them during production, storage, transportation, and
consumption.In this regard, severalunexploredplant extractsand
ingredients, such as grape seed extract, green coffee bean, pine
needles, fig, Terminalia arjuna, Tinospora cordifolia, oleuropein, red
pepper, lemon peel, clove oil and mung bean, have been recently
used for flourished storage quality of meat, fish, and other seafood
products(Bhat&Pathak,2009;Dilnawazetal.,2017a,2017b;Dua
etal.,2015a,2015b;Hassanzadehetal.,2018;Jamwaletal.,2015;
Kalem, Bhat, Kumar, & Jayawardena, 2018; Kalem, Bhat, Kumar,
Noor, & Desai, 2 018; Mahajan et al. , 2016; Singh, Kumar, Bhat , &
Kumar,2015; Singh,Kumar, Bhat,Kumar,& Kumar, 2015). Forex-
ample, Schelegueda et al. (2016) used chitosan, nisin, and sodium
lactatealongwithmodifiedatmospherepackaging(MAP)forburger
made with Argentine hake (Merluccius hubbsi)fishandcouldextend
its shelf-life and safety up to 30days at 4°C storage successfully.
However,few studies have beenpublished for shelf-life extension
of seafood (especially fish burgers) based on usage of natural preser-
vatives (such asplant extracts,compoundswithnatural origin,and
essential oils).
Propolis (Apis mellifera) is a resin, being dark green or brown, with
apleasantpoplarbudsandvanillaflavor.Ithashighantioxidantand
antimicrobial activities (due to its high content of polyphenols, qui-
nones,coumarins,steroids,amino acids,andinorganiccomplexes),
and also a good potential to extend the shelf-life of foodstuffs
(e.g., fish b urger) (Kahram anoğlu et al., 202 0; Probst et al., 2 011;
Schelegueda et al., 2016; Tzima et al., 2015). On the other hand,
using the whole propolis (as a natural preservative in foodstuff) is
relativelyexpensiveandsometimesimpractical.
Spinelli et al. (2015) added 5% (w/w) the microencapsulated
propolis (after spray- drying) to fresh sea- bass fillets (Dicentrarchus
labrax) fish burgers prepared with new ingredients including potato
flakesandextravirginoliveoil.Theyindicatedthattheadditionof
encapsulated propolis increased phenolic compounds and conse-
quentlyantioxidantactivityinfinalproduct.
Since, addition of propolis extract (as an alternative natural
preservative) for preventing lipid oxidationa ndmicrobial ac tivity
of fish burger patties made with rainbow trout has received little
scientific attention, and there is a need to develop RTCF (ready- to-
cook food), it was our objective to make fish burger patties of cold
rainbow trout (Oncorhynchus mykiss) combined with different levels
ofpropolisextract.Theninvestigatethecharacteristicsofthisex-
tract and quality indicators (physicochemical and microbiological)
properties of the resulting fish burger patties for 3 months storage
at−18°C.
2 | MATERIAL AND METHODS
2.1 | Raw material preparation
Ten fishes of cold rainbow trout (each one with average weight and
length of respectively 800 ± 100 g and 30 ± 2 cm) were prepared
fromalocalmarketandcarriedwithanicebox(1–4°C)tothe Food
Science Lab. The raw propolis was obtained from a Koorosh Bee-
Breeding Center (located in the West of Iran).
2.2 | Propolis extraction
About 75 g of raw propolis was stored in a refrigerator at
−18 ° C ± 1 over- night. Later, the frozen propolis was grinded
(by a home miller) to average particle size of ~250 μm (Reis
et al., 2017). After cleaning and removing its foreign materials,
it was soaked with ~250 ml mix ture of ethan ol: water (70:3 0).
After 4- day decanting of the insoluble portion of propolis with
slowstirringrateof3revolution/dayat 20–25°C,the resulting
extract was clarifiedbya (Whatman, No.4)filter paper.Later,
the solve nt portion of th e filtrated ex tract was rem oved by a
vacuumrotaryevaporator(IKGerman,IK,Germany)at35°Cand
0.1MPa,untiltheweightofconcentratedextractbecame con-
stant.Aftermixingtheconcentratedextractwith Maltodextrin
(75:25 W/W), it was dehydrated in a freeze- dr yer (Dena- Sanat,
Tehran, Iran) at − 40°C and 0.0 01 mbar (air pressu re) to make
freeze-dried propolis (FDP) and kept at −18 ±1°Cuntilused
(IranianNationalStandardizationOrganization[INSO],2014;Jin
etal., 2015; Sayarietal.,2015). Figure1showsthe extraction
processesusedtomakeFDP fromitsrawmaterial. The extrac-
tion efficiency was evaluated via three quality indicators of final
dried pro duct inclu ding yield, s weeping of DPPH· f ree radica l,
and total phenolic content (TPC).
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SHABAN I et Al.
2.3 | Fish burger patties formulation and processing
Initially, the prepared rainbow- trout fishes (O. mykiss) were washed
by tap water. After removing the heads, bones, and intestines
of fishes, the resulting lean meat were washed, cut into fillets,
and minced to ~5 mm particle sizes by a homemade meat grinder
(Panasonic,MK-ZJ3500,Japan).
The supplementary ingredients had 2% recrystallized salt, 2%
blended spices (mainly curry powder, pepper, and turmeric), 5%
bread crumble powder, 0.5% sugar, 1.5% garlic powder, and 4.0%
onion powder.Theseingredientswere mixed uniformly andex-
posedtolaminarflowofultraviolet(at200–280nm)lightinside
ofa safety hood (Jal-Teb, Tehran, Iran) for 20 minto eliminate
possible fungal and microbial contamination. Based on the con-
ventional formulation of fish burger patties, 85% (w/w) ground
fish fillet was mixed with15%(w/w)clean additives tomake a
uniform paste. Then the FDP powder at different levels (0, 0.1,
0.2, and 0.4%) was combined with the resulting fish paste. The
prepared fish pastes were shaped into round and circular burgers
each one with 1 cm thickness, 10 cm diameter, and weight of
100 ± 5 g. The formed fish burger patties were packed manually
in polyethylene (PE) bags (with 0.2 mm thickness) and stored at
−18°Cfor3months.Itisnecessar ytoemphasizethatallthepro-
cessing and storing stages took place in a completely sterilized
environment. Then the frozen fish burgers (FFB) were taken out
of the freezer at different time intervals (0, 30, 60, and 90 days)
and used for further tests. The flow chart of preparing fish burger
patties was given in Figure 2.
2.4 | Quality analysis of freeze- dried propolis
(FDP) and frozen fish burger (FFB)
2.4.1 | Yieldextraction
ThenEquation1wasusedtocalculatetheyieldextractionofpropo-
lis (Spinelli et al., 2015):
where, YE isyield extractionof propolis(%),Wi and Wf are the initial
andfinalweightsofpropolis(g)beforeafterextraction,respectively.
2.4.2 | Determinationoftotalphenoliccontent
(TPC)andantioxidantactivityofFDP
The Folin–Ciocalteu colorimetric method used by different re-
searche rs (Jabri-Ka roui et al., 2012; M oosazad et al ., 2019)wa s
applied to measure its TPC. First, the standard solution of FDP
(with concentration of 10 mg/g) in methanol (96% purity) was pre-
pared in room temperature. Then, a 10 ml falcon tube was used to
mix0.75mlofthe FDP solution with 0.75ml of Folin–Ciocalteu
reagent,andther es ul ti ngmixturew asagit atedin25° Cwaterbath
(consists of a reciprocating shaker with 250 rev/min) for 30 s. After
3 min resting time, 0.75 ml of sodium carbonate (Na2CO3 with 20%
concentration) was added to each sample, and its volume was ad-
jus tedto10mlbyaddingdistilledwater.Nexteachtubeofsample
was agitated again at the same time and conditions of water bath
andkeptina25° Cdarkstoragefor1hr.Subsequently,t heabsorb-
ances of the resulting trial and blank sample (containing 0.75 ml
distill ed water, 0.75 ml Folin–Ci ocalteu reagent , and 0.75 ml of
20% Na2CO3) were measured by a Shimadezu spectrophotometer
(modelUV–Vis, mini-1240,Japanspectrophotometer)at725nm.
Each test was performed in three replicates. The TPC of each
samplewasobtainedfromthestandardGallicacidcurve(plotted
from 25, 50, up to 100 μg/g)andexpressedasmgGAE(gallicacid
equivalent)/gdriedmatter(DM)ofpropolis.Theregressionequa-
tion (with R2 equal to 0.9437) was accomplished from calibration
curveofGallicacidshowninEquation2:
where, A is absorbance of solution at 725 nm and C is concentration of
phenoliccompoundsinmgGAE/gDMofpureFDP.
TheDPPH·(2,2-diphenyl-1-picrylhydrazyl)isafreeradicalform
of this compound, and it is used to measure radical scavenging ac-
tivit y (RSA) or antiox idant activ ity of each FDP s ample based o n
Uribe et al. (2016) method. After transferring 1.5 ml of FDP solu-
tion (from each concentration of 10, 50, 100, and 200 μg/g) to 4
(1)
YE
(%)=
W
f
W
i
×
100
(2)
C
=
[(A
𝜆=725 nm
0.0018
)
−15.56
]
FIGURE 1 The flow chart prepared for making powder of
freeze- dried propolis (FDP)
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SHABANI et Al.
separatefalcontubes,1.5mloffreshly preparedDPPH· indicator
was adde d to each sampl e and all the tes t tubes shaken a t 25°C
for 30 s and then held in a dark place for 30 min. Later, the absor-
bance of each solution was read by the same spectrophotometer at
517 nm. The control sample prepared was the same way, but 1.5 ml
methanol was used instead of each concentration of FDP solution
(i.e., 1.5 ml methanol +1.5ml DPPH· indicator). The measuredab-
sorbency of the control sample was deducted from the absorbency
of each solution of FDP concentration to eliminate the color effects
and measure RSA, accurately. Finally, Equation 3 was used to cal-
culate the RSA:
where, ASisthelightabsorptionofs ample(Extract+DPPH·),ASB is ab-
sorptionofthecheck(withoutDPPH·orExtract+Methanol)sample,
and ABisabsorption ofmethanolsample (Methanol+DPPH·).After
the determination of RSA, EC50 value (the effective concentration at
whichDPPH·radicalsscavengedby50%)calculatedfromthelinearre-
gres sionbyplotting ofRSAvalu esversu se xtr actconce nt rat io ns(Urib e
et al., 2016).
2.5 | Measuring of pH of frozen fish burger (FFB)
ThepHofFFB(afterdefrostingat25°C)wasmeasuredbyaMotrihm
pHmeter(Model827,Switzerland).Onegramofeachspecimenwas
weightedandhomogenizedwith10mlofdistilledwater(withpH= 7)
(3)
RSA
(%)=
[
1−
(A
S−
A
SB
A
B)]
×
100
FIGURE 2 Flow processes
accomplished to produce frozen fish
burger (FFB) patties
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SHABAN I et Al.
onahotplatewithmagneticstirrer(Mtops,HP100,LabsellCo.Iran).
After 5 min stirring, it was filtered and its pH values after 2 min
adjustment was read and recorded (Comi et al., 2015; Fernandes
et al., 2017).
2.6 | Lipid oxidation quantification
The oil sa mples of FFB were ex tracted f rom differen t fish burger
pattiesbyusingtheSoxhletextractor(VelpScientific,SER148,Italy)
and diethyl ether as a solvent as described by Ali et al. (2019). Then
the iodometric method of Akcan et al. (2017) was applied to measure
peroxide v alue (PV) of th e oil extra cted from eac h sample of fish
burger patties. About1goilwasdissolvedin6 ml of mixedacetic
acid: chloroform (3:2). Then 0.5 ml of standard solution of potassium
iodide (KI) wasadded tothe resultant mixture veryslowlyuntil its
yellowcolorappeared.Next,0.5mlof1%starchsolution(asindica-
tor)wasaddedtothenewmixtureandshakenfor1mintodevelop
a blue color in the solution. After adding 30 ml of distilled water, the
test was titrated with 0.01 N sodium thiosulfate solutions until its
blue color disappeared. All the above steps were repeated for the
control sample, which it did not have the oil content. Equation 4 was
used to calculate PV.
where Vs, and VB are the volumes (ml) of sodium thiosulfate solution
usedforthe experimentalandcontrol samples,respectively.N is the
concentration of sodium thiosulfate solution (0.01 N) and W is the ac-
curate weight of oil used for this measurement.
Thiobarbituric acid reactive substances (TBARS) of fish burger
pattiesweremeasuredbyGiorgio-Peirettietal.(2011)methodwith
some modification. First, 1 g of FFB was weighted and poured in
falcon tube. Then, 3 ml 4% perchloric acid and 2 ml of 10% trichloro-
acetic acid (TCA) were added into the falcon tubes and stirred with
amixerfor3min(toseparatesuspendedproteinsinsolution).Next,
theobtainedextractswereplacedinacentrifuge(Behdad,BH-1200,
Iran) at 4,000 rpm for 15 min to precipitate their suspended solids
intheextracts.Next,1mloftheupperphase(supernatant)ofeach
extractwastransferredtoacleantesttubeandmixedwith1mlof
0.02 M reagent of TBARS reagent. Then, eachprepared test tube
washeatedto90°CinawaterbathofFater-Riz-Pardaz(Tehran,Iran)
for 60 min or until its pinkish- orange color appeared. After cooling,
its optical density was read against the control (contains all materials
except the propolis extract) by usingthesame spectrophotometer
at530nm. The standardcurve ofmalondialdehyde(MDA)wasob-
tained by measuring its absorbency at different concentrations (0,
0.1, 0.2, and 0.3 ppm dissolved in distilled water and added thiobar-
bituric acid solution) in 530 nm. The amounts of thiobarbituric acid
in the tested samples were calculated using the prepared malondi-
aldehyde calibration curve. Later, Equation 5 for showing regression
equation and R2 value equal to 0.9088 was used to calculate TBA
(mgMDA/kgsample)infishburgerpatties.
where, A is absorbance of solution at 530 nm.
2.7 | Total volatile basic nitrogen (TVB- N)
measurement
The total volatile basic nitrogen of FFB was measured according
to method INSO (2007) in two stages of distillation and titration.
After placing 10 g of FFB (weighted by a précised digital balance) in a
Kajeldalballoonflask,2gofmagnesiumoxideand300mlofdistilled
water were added to the FFB. Then, 25 ml of 2% Boric acid and a few
drops of color reagent were transferred to a recipient Erlenmeyer
flask and m ixed thoroughl y. Then t he content of Kajelda l balloon
flask was heated until it was boiled. Distillation of resulting vapors
was continued until at least 100 ml of condensed solution with a
dark green color was collected in the recipient Erlenmeyer flask (held
underneath of distillation part). After titrating the collected solution
inErlenmeyerflaskwith0.1NH2SO4 (until pink dye was developed),
the Equation 6 was used to calculate the TVB- N of each sample.
where, VisthevolumeofH2SO4 consumed (ml), N is the concentration
ofH2SO4 (0.1 N), and W is the accurate weight of each sample (g).
2.8 | Color measurement
The color attributes (L*, a*, and b* values) were measured by an
Image J sof tware versi on 1.48. A woo den box with whi te interior
walls and a fluorescent lamp (12 W) were used to measure the color
propertiesofFFB.AdigitalCanoncamera(Canon,SX230HS,Japan)
was used to take photos of prepared samples and transfer them to a
color determination software installed in a laptop- computer. Three
color parameters of FFB including, “a*” (redness), “b*” (yellowness),
and “L*” (lightness) were measured in their standard ranges. The
color parameters (L*, a*, and b*) of fish burger patties were measured
beforeandafters toragetocalculatecolorchange(∆E) of FFB during
storage according to Equation 7.
where,∆Listhelightnessdifference,∆a is the red/green difference,
and∆bistheyellow/bluedifference(Hemmatkhahetal.,2020).Itis
necessar ytomentionthat∆E represents the color difference between
the control sample of FFB (with no FDP at 0 day of storage) with FFB
samples at different FDP concentrations and days of storage.
(4)
PV (
meqO2∕kg oil
)
=
(
VS−VB
)
×N×
1, 000
W
(5)
TBARS
mgMDA∕[kg sample]
=
A
𝜆=530 nm
2.697
+
0.0327
(6)
TVB - N(mg N
2∕
[
100gsample]
)
=
V×N×14
W
×
100
(7)
Δ
E=
√
(ΔL)2+(Δa)2+(Δb)2
6 of 16
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SHABANI et Al.
2.9 | Cooking characteristics of fish burger patties
2.9.1 | Cookingyield
Three prepared fish burger patties were weighted before and after
cooking to calculate its cooking yield by using Moulinex Oven
(modelAM-30,France)andEquation8describedbyAlietal.(2019)
and Bochi et al. (2008). The frying time and temperature were se-
lectedfor5minat180°C,respectively.Additionally,deep-fatfrying
method was used to cook fish burger patties, so that both burger
surfaces were cooked evenly.
where, Y is cooking yield (%), Wi an d Wf are the we ight of uncooked and
cooked fish burger patties (g), respectively.
2.9.2 | Fatandmoistureretention
After fr ying the fish burger patties two Equations 9 and 10 (Ali
et al., 2019) were applied to calculate their fat and moisture
retentions.
where, i (initial) and f (final) subscriptions are related to the uncooked
and cooked fish burger patties, respectively. The W, M, and O are
the weight (g), moisture, and oil content (% wet basis) of the fish
burger patties, respectively. The moisture content noted in Equation
9 was measured in accordance with AOAC (2016) and calculated by
Equation 11.
2.10 | Microbiological analysis
The microbial counts on the sample were performed immediately
afterinoculationon0, 30, 60, and90daysofstorage.Exactly10g
of FFB was homogenized with 90 ml sterile water (containing 0.1%
peptone)inaverticallaminar-flowhood(Jal-Teb,Iran)usingastom-
acher blender (Stomacher® 400 Circulator, England) for 1 min. A
set of serially diluted samples were prepared and then cultured
with surface plate technique and appropriate media for enumera-
tion (Joukar et al.,2017). Total viablebacteria (T VC) of eachsam-
ple were enumerated by using plate count agar of Fater- Riz- Pardaz
(ModelB630,Tehran,Iran)followedbyincubationat37°Cfor48hr
(INSO, 2015). Similar incubation conditions applied to count the
Staphylococcus aureus of fish burger patties using Baird- parker agar
(BPA) (INSO, 2005a). The counting of Escherichia coli and Salmonella
were per formed resp ectively on t he Eosin Methylen e Blue (EMB)
and Salmonella Shigella Agar (SSA) media after 24 hr incubation
under ana erobic/aerobic co nditions at 37° C (INSO, 2005b, 2017).
The fungal mold and yeast of FFB samples were enumerated after
their inoculation in Yeast Extract Glucose Chloramphenicol Agar
(YEGC)andusingthesurfaceplatetechniquefollowedbyincubation
at25°Cfor5–7daysbeforeenumeration(INSO,2008)andcounting
the plates between 30 and 300 colonies only. The results were re-
ported as logarithms of colony forming units per gram (log10 CFU/g)
for each sample.
2.11 | Statistical analysis of data and optimization
All determination tests (antioxidant activity, cooking param-
eters, and microbiological) for measuring quality characteris-
tics of ex tracted prop olis along with it s freeze-d ried product
wereperformedintriplicate.TheStatistixversion8(Analytical
Software Inc., Tallahassee, FL 32312, USA) program was ap-
plied to make analysis of variances (ANOVA) and perform least
significant difference (LSD) test for different treatments at the
confidence level of 99%. To optimize the level of each quality
indicator in the final products, the response surface methodol-
ogy (RSM) technique with the central composite design (CCD)
class incl uding 13 experi ments (with 3 le vels of −1,0, a nd +1
and 5 replications in central point) were used (Table 1). Days of
storage (X1) and FDP concentration in FFB (X2) were selected
as indepe ndent variable s and the quality i ndicators of perox-
ide value (Y1), thiobarbituric acid reactive substances (Y2), p H
(Y3), total volatile basic nitrogen (Y4), lightness index (Y5), red-
nessi nd ex(Y6),yellownessindex(Y7), and color change (Y8) were
considered as responses. The relationship between the actual
andcodedvaluesoftheindependentvariables(Table1)wasex-
pressed by Equation 12.
where, Va and Vc are the actual and coded values of the ith factor,
respectively. The Xi and Xj are the upper and lower limits of the ith
parameters, respectively (Mokhtarian et al., 2014). To optimize the
final product specifications, thegraphical software of DesignExpert
(version 6 .01) was used for eac h quality par ameter, and the expe ri-
mental data of the two variables were fitted using a quadratic polyno-
mial model. The best model for each quality indicator was evaluated
byexaminingthelackoffit(LOF)testofqualityindicatorsversusthe
independent variables (days of storage and FDP concentrations). Also,
their coefficients of determination (R2 and R2
adj) were found to show
the relations of independent and dependent variables (Mokhtarian
et al., 2014).
(8)
Y
(%)=
W
f
W
i
×
100
(9)
M
r(%)=
W
f
×M
f
W
i
×M
i
×
100
(10)
F
r(%)=
W
f
×O
f
W
i
×O
i
×
100
(11)
MC(
%w.b. ) =
W
i
−W
f
W
i
×
100
(12)
V
c=Va−
[(
Xi+Xj
)
∕2
]
(
X
i
−X
j)
∕2
|
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SHABAN I et Al.
3 | RESULTS AND DISCUSSION
3.1 | Extraction yield and dry matter of propolis
Our results indicated that the efficiency and dry matter of pure and
active propolisafter 4 days extraction with ethanol at 37°C were
42.46% (±0.19) and 12.74% (±0.057),respectively.The extraction
efficiency of polish propolis depends on harvesting season when
70%ethanolisusedasasolventforitsextraction.Therecover yval-
ues for spring, summer and fall are 41.7%, 66.6% and 46.6%, respec-
tively(Wozniaketal.,2019).Theextractionefficiencyalsochanges
due with the geographical area of propolis production. Furthermore,
Seibert et al. (2019) used different solvents including ethanol, ethyl
acetate,andhexaneandobtainedextractefficiencyofrespectively
23%, 15,% and 6% from raw propolis, which were lower than our
values. Sherif et al. (2018) stated that the difference in polarity be-
tween t he solvents ha d a positive influ ence on the ext raction ef-
ficiency. Because of the most constituents of propolis are soluble in
alcohol,thepurityofthissolventincreasestheextractionefficiency.
Moreover, Janse n-Al ves et al. (2019) obtain ed the extr action ef fi-
ciency between 18.82% and 54% for propolis, which is consistent
with our results in this study.
3.2 | Antioxidant activity of propolis
Theextracted bioactive compounds of propolis were evaluated by
two chemical quality indicators of EC50 (effective concentration) and
total phenolic content (TPC). The EC50 indicator is a concentration
ofbioactivecompoundsthatcanscavenge50%ofDPPH·freeradi-
cals in the medium. The lower concentration value of EC50 means
thehigherradicalscavengingpower(Burits&Bucar,2000).Figure3
compares the bioactive compounds in three different forms of
ethanolicextractofpropolis (EEP),freeze-driedpropolis(FDP),and
freeze- dried propolis after 20 min UV radiation (FDPUV). The FDP
showed significantly higher TPC and lower EC50 than EEP samples
respectivelyatconfidencelevelsof95%and99%.However,itdidnot
show any noticeable difference FDPUV. Wozniak et al. (2019) stated
thatthenumberoffreeradicalsscavengingof DPPH· forethanolic
extractofPolish propolis(at100mg/ml)wasequal to 31%(equiv-
alent to EC50 = 161.29 mg/ml), which has a higher EC50 or lower
radical inhibitory power than the FDP in this study (EC50 = ~30 mg/
TABLE 1 The selected independent variables along with their
calculated codes to optimize the quality indicators' levels of frozen
fishburger(FFB)pattiesduring90-daysstorageat−18°C
Independent variables
Actual (coded)1 values of the
variables
Lower
limit
Mean
limit
Upper
limit
Storage time (day) 0(−1) 45 (0) 90 (+1)
Addition of FDP (%) 0(−1) 0.2 (0) 0.4 (+1)
1The following numbers show the coded values of 0- , 45- , and 90- days
of storage by using Equation 12:
Coded value for lower limit (ST
=0 - day): Vc=Va−
[(
Xi+Xj
)
∕
2]
(Xi−Xj)∕2
=0−[(90+0)∕2]
(90−0)∕2
=0−45
+45
=−45
+45
=−
1
Coded value for mean limit (ST
=45 - day): Vc=Va−
[(
Xi+Xj
)
∕2
]
(Xi−Xj)∕2
=45−[(90+0)∕2]
(90−0)∕2
=45−45
+45
=0
+45
=
0
Coded value for upper limit (ST
=90 - day): Vc=Va−
[(
Xi+Xj
)
∕2
]
(Xi−Xj)∕2
=90−[(90+0)∕2]
(90−0)∕2
=90−45
+45
=+45
+45
=+
1.
FIGURE 3 The mean values (average
of three replication) of indicators (EC50
[mg/mlormg/g]andTPC[mgGAE/
mlormgGAE/g])formeasuringthe
effectiveness of bioactive compounds
in different forms of propolis including
ethanolicextract(PEE),freeze-dried
propolis (FDP) and freeze- dried propolis
after 20 min UV radiation (FDP- UV).
Indices of 1 and 2 denote to EC50 and
total phenolic content (TPC), respectively.
The letters of a and b show the highest
and the lowest amount of each quality
indicator.Differentlettersoneachindex
show the significant (PEC50 < 0.05 and
PTPC < 0.01) differences between the
specific quality indicator of different
forms of propolis
0
20
40
60
80
100
120
140
VU-PDFPDFEEP
Value
Different forms of propolis
EC50TPC
a1
b1b1
a2
a2
b2
8 of 16
|
SHABANI et Al.
ml).MostprobablythecoatingofEEPwithmaltodextrinfollowedby
freeze-dryingcouldprotectitsantioxidantactivitiesandincreaseits
inhibiting power (reducing EC50).
Another bioactive compound found in propolis is phenolic com-
pounds. These compounds are secondary metabolites and are classi-
fied into two groups of simple phenols and polyphenols based on the
number of phenolic units in the molecule (Angiolillo et al., 2015). The
highest TPC (corresponding to the lowest EC50) was equal to 91.26
(mgGAE/gDM)andrelated totheFDPsample which didnothave
a statistically significant (p > .05) difference with FDP- UV sample.
Wozniak et al. (2019) reported the total phenolic (mainly p- coumaric
andcaffeic) acids intheethanolic extractofpropolisfrom16.18to
19.34mgGAE/gDM.Andradeetal.(2017)reportedtheamountof
total phenolic compounds for three types (brown, green, and red) of
propolis (found in Brazil) respectively are 55.74, 90.55 and 91.32 mg
GAE/gDM.
3.3 | Peroxide value (PV) and thiobarbituric acid
reactive substances (TBARS) of FFB
Figure 4a shows the changing trend of PV for the FFB under the
influence of storage time and addition of FDP at different concentra-
tions. The PV of control sample had an upward trend when days of
storageincreased.However,byincreasingtheFDPconcentrationin
FFB this trend changed to downward, and the PV of FFB with 0.4 g
FDP/100 g reduced >30% (from ~24.1 to ~16.46 meq O2/k g oil) after
90daysofstorage.Increasingthisindexdenotesseveredegradation
ofunsaturated fatty acids andformation of mono-hydroperoxides
infish burgerpatties(Hu & Jacobsen, 2016).Additionally,the two
independent variables of days of storage (x1) and FDP concentration
(x2) had significant (p < .01 or p < .05) effects on the PV of FFB in dif-
ferent forms of linear ( x1 and x2), interaction (x1x2), and quadratic ( x1
2
and x2
2) (see Table 2). The ANOVA analysis showed that the F- values
and regression coefficient (βx1) of polynomial trend of storage time
were 59.96 and (+3.35),respectively.However,theF- values and re-
gression coefficient (βx2) of polynomial trend of propolis concentra-
tionrespectivelywere24.22and(−2.13).Thepositiveandnegative
signs of regression coefficients confirmed respectively the synergic
and retarding effects of storage time and propolis concentration in
changing PV of FFB. Since the positive effects of storage time was
stronger than propolis concentration on changing PV of FFB, the
regression coefficient (βx2^2 resulted from the interaction of these
two parameters x1x2) still had positive effect on increasing PV of
FFB, but in lower rate (+1.09). The high coefficient of determina-
tion (R2 = 0.9864)alsorepresentstheextremedependence ofPV
on storage time of FFB (Table 1). Shavisi et al. (2017) added propolis
ethanolicextract(1%and2%)toamincedbeefandshowedthatits
peroxidevaluewasmuchlowerthan thecontrolwhenthisproduct
was stored at +4°Cfor11days.AccordingtoTokuretal.(2004),the
permissible PV should be below 20 meq O2/[kg oil]tohaveanac-
ceptable fat rancidity. When Ozogul and Uçar (2013) added natural
plantextracts(suchasoregano,greentea,sage,andlaurel)tofrozen
burgers made with chopped mackerel, their PVs became signifi-
cantly lower than the control sample at similar storage time.
Anotherlipidoxidationindicatorinproteinproductsisthethio-
barbitu ric acid (TBA ) index. The co ncentratio ns of secondar y me-
tabolites(suchasmalondialdehydeorMDA,alcohol,acetone,acids,
etc.) of the fat decomposition cause the fish products to become
acidic (rancid) with unpleasant taste (Hu & Jacobsen, 2016). The
ANOVA results of our study showed that the linear (x1) and qua-
dratic (x1
2) forms of storage- time variable and its interaction with
FDP concentration (x1x2) all had positive and significant (p < .01 or
p < .05) effects on TBA reduction of FFB (see Table 2 and Figure 4b).
The statistical analysis also showed that the days of storage with
F- values of 188.12 had the highest influence on increasing TBA. As
Figure 4b shows the TBA value has an upward trend with increas-
ing storage time and much lower increasing rate with addition of
propolis concentration to FFB. While the TBA of FFB without FDP
(control) increased from0.34 to 0.97 mg MDA/kg (183%increase)
after3monthsfreezingstorage,itincreasedtomaximumof0.75mg
MDA/kg(120%)whenFFBcontained0.4gofFDP/100gandstored
at similar conditions. The TBA permissible values in high, medium,
and acceptable quality of food should be less (<) than 3, 5 and 7 mg
MDA/kg,respectively(El-Lahamyetal.,2018).Thehighestvalueof
TBA we found in this study was for the control fish burger patties
~1.27mgMDA/kg. ThelownumberofTBAincontrolsample after
3 months of frozen storage was due to the usage of fresh fish fillets,
sterilized conventional additives, and preparing burgers in the com-
pletely sanitized conditions. The high coefficients of determination
(R2 = 0.9931) in suggestive polynomial regression model (prepared
from the actual data) denotes its high validity for prediction of TBA
in FFB during storage (Table 2).
3.4 | Total volatile basic nitrogen (TVB- N) and
pH of FFB
Total volatile basic nitrogen (TVB- N) is a protein compounds that
is released due to the breakdown of protein structures and pro-
teolytic enzyme's activity in FFB. Figure 4d shows the changing
(three- dimensional) trend of TVB- N in the FFB under the influence
of storage time and FDP concentrations. Furthermore, when FDP
concentration increased from 0.0 to 0.4 g in100 g of FFB, its TVB- N
decreased >26% (from ~23.80 to ~18.90 mg N2/100 g) at the end
of the thre e months stora ge. Decreasing t his index in fish b urger
patties denotes the lower formation of volatile basic nitrogen and
in fact the lesser protein spoilage in the food (INSO [No. 9626],
2007). Additionally, the two independent variables (storage time or
x1 and FDP concentration or x2) had significant (p < .01 or p < .05)
effects in different forms of linear (x1 and x2), interaction (x1x2) and
quadratic (x1
2 and x2
2) effects on the T VB- N of FFB (see Table 2).
The ANOVA analysis showed that the F- values of storage time in
linear and quadratic trends were 91.36 and 7.62, respectively. El-
Lahamy et al. (2018) suggested that four limit values of TVB- N for
very good, good, acceptable, and unacceptable food products for
|
9 of 16
SHABAN I et Al.
25, 30, 35, and >35 mg/100 mg, respectively. Ozogul and Uçar
(2013)usedvariousnatural plant extractsincludingoregano,green
tea, sage, and laurel on the quality changes of burger made with fro-
zen Pacific chub- mackerel (Scomber japonicus) fish. They indicated
that the TNB- V value of resulting burgers which had different plant
extractswaslowerthantheircontrol samples,duetotheirantioxi-
dant and antimicrobial contents. The coefficients of the suggested
polynomial regression model (obtained from real data) are reported
in Table 2. As seen, the coefficient of determination for this model
was high (R2 = 0.9907), which represented its high validity of TVB- N
value with FDP concentrations and days of storage. The kind of fish
used for making fish burger patties has effects on physiochemical
characteristics (including PV, TBA, and TVB- N) of fish burger pat-
ties duri ng storage. Mahm oudzadeh et al . (2010) studied the f ish
burger pat ties made with two kinds of fishes including deep flounder
(Pseudorhombus elevatus) and brush- tooth lizard fish (Saurida undos-
quamis)and storedat−18°Cfor5months. WhilethePVincreased
significantly in deep flounder and brush- tooth lizard fish burgers
after 2 months storage. But a significant reduction was observed at
the end of 3rd and 4th months in deep flounder and brush- tooth
lizard fish burgers. While th e TBA value of deep flounder fish burgers
reduced significantly (p < .05) as storage time continued, it increased
significantly in brush- tooth lizard fish burgers at the end of second
month (p < .006). However, this quality indicator of brush-tooth
lizard fish burgers decreased at the end of 5 months storage. The
total volatile basic nitrogen (TVB- N) values increased significantly
for both fish burgers at the end of the second month; however, no
significant changes were observed in this parameter after ward. As
a result of the above- mentioned research, there is a good chance
to decrease the PV, TBA, and TVB- N of fish burger fortified with
FDP during long time storage if rainbow- trout is substituted with the
deep flounder fish.
The accept able pH-value s of fish are betwe en 6.8 and 7.0. In
other word s, when pH of fish is >7.0, it is not acceptable due to
its possible spoilage (El- Lahamy et al., 2018). The ANOVA results
showed that the linear (x1 or x2), interaction (x1x2), and quadratic
(x1
2)effectsofincreasingFDPconcentrationinFFBandextension
of storage days both had positive effect (p < .01 and p < .05) on
changing t he pH of frozen fish bur ger (Table 2). Additiona lly, the
days of storage had much stronger influence (with F = 461.19) on
FIGURE 4 Three- dimensional effects of 90- days storage time (X1) and addition of freeze dried propolis or FDP (X2) on Y or
physicochemicalresponseofFFBat−18°C.Thesubscriptsof1,2,3,4,5,6,7,and8arerelatedtoperoxidevalue(PV),thiobarbituricacid
reactivesubstances(TBARS),pH,totalvolatilebasicnitrogen(T VB-N),lightness,redness,yellowness,andoverallcolorchanges(∆E) on FFB,
respectively
(a) (b)
(c) (d)
0.0
22.5
45.0
67.5
90.0
0.00
0.10
0.20
0.30
0.40
12
15.25
18.5
21.75
25
Y1 (meq O2/kg oil)
X1 (day)
X2 (g/100g)
0.0
22.5
45.0
67.5
90.0
0.00
0.10
0.20
0.30
0.40
0.32
0.4825
0.645
0.8075
0.97
Y2 (mg MDA/kg)
X1 (day)
X2 (g/100g)
0.0
22.5
45.0
67.5
90.0
0.00
0.10
0.20
0.30
0.40
6.24
6.3025
6.365
6.4275
6.49
Y3 (-)
X1 (day)
X2 (g/100g)
0.0
22.5
45.0
67.5
90.0
0.00
0.10
0.20
0.30
0.40
14.1
16.525
18.95
21.375
23.8
Y4 (mg N2/100 g)
X1 (day) X2 (g/100g)
10 of 16
|
SHABANI et Al.
changing pHofthe FFB thanFDP concentration(with F = 18.77).
While the p H-va lues of the contro l sample drop ped from 6.47 to
6.24(3.6%reduction)after3 monthsstorageat−18°C, thepH's of
FFB with 0.4 g of FDP/100 g lowered from 6.48 to 6.29 (2.9% re-
duction) stored at similar conditions (Figure 4c). These results were
agreed with El- Lahamy et al. (2018) report when they measured
thepHchangesof plainfrozen fish burgers at similarstorage con-
ditions.SeveralstudiesshowedthatthepHchangesoffishesduring
storage highly depend on their species and biological characteris-
tics (Bilgin et al., 2011; Cadun et al., 2005; El- Lahamy et al., 2018;
Mahmoudzadehetal.,2010;Vareltzisetal.,1997).
3.5 | Color assessment of FFB
TheproposedRSMmodelshowedthat the storagetime and FDP
concentration had significant (p < .01 and p < .05) effects on chang-
ing the color parameters (L*, a*, b*,and∆E) of FFB before cooking
(Table2).When the storage time wasextendedandFDPconcen-
tration became higher, its color characteristics including L* (bright-
ness), a* (redness) and b* (yellowish) and overall color changes
(∆E) respectively amplified, diminished, increased, and decreased
(Figure 4e–g). Whilethestorage time(x1) had unfavorable effects
on changing the a* (with F value = 103.03) and L* (F value = 70.45),
the FDP concentration in FFB (x2) had much lower effects on alter-
ing these parameters in FFB during storage (see Table 2). Similar
studie s have shown that the a ddition of medi cinal plant ex tracts
can reduce the brightness (L*), increase the redness (a*), and in-
crease yellowness (b*) of the product compared with the control
sample (Akcan et al., 2017; Fernandes et al., 2017). Table 3 presents
the overall lighter color of FFB with 0.4 FDP g/100 g compared with
thecontrolsamples(af te r90daysstorageat−18°C),whichwasdue
toitslowerphysiochemicaldeteriorativeindexes(PV,TBARS, and
TVB- N generation) during long- time frozen storage. Furthermore,
the less color changes are due to the protective role of phenolic
compoun ds (existing in pl ant extrac ts) in preventin g the pigment
oxidation of myoglobin(Mb)andtheir consequence conversionto
Met-myoglobin(Met-Mb) (Georgantelis et al., 2007).Additionally,
the tworeactions of meat discoloration and fat oxidation are re-
lated and synergistic to each other. The discoloration of meat
productsduringstoragetakesplacemainlywithinthepigmentoxi-
dation. In this reaction the central iron of myoglobin (heme protein
ofmeat)isoxidized (byconvertingFe+2 to Fe+3) and replaced by a
watermolecule.ThisprocessoxidizestheredOxy-myoglobin(Mb-
O2)pigmentofmeattobrownishMet-myoglobin(Met-Mb)(Estévez
et al., 2003; Faustman et al., 2010).
(e) (f)
(g) (h)
0.0
22.5
45.0
67.5
90.0
0.00
0.10
0.20
0.30
0.40
48
51.5
55
58.5
62
Y5 (-)
X1 (day)
X2 (g/100g)
0.0
22.5
45.0
67.5
90.0
0.00
0.10
0.20
0.30
0.40
-4.1
-2.45
-0.8
0.85
2.5
Y6 (-)
X1 (day)
X2 (g/100g)
0.0
22.5
45.0
67.5
90.0
0.00
0.10
0.20
0.30
0.40
43.9
46.05
48.2
50.35
52.5
Y7 (-)
X1 (day)
X2 (g/100g)
0.0
22.5
45.0
67.5
90.0
0.00
0.10
0.20
0.30
0.40
-1
2.75
6.5
10.25
14
Y8 (-)
X1 (day)
X2 (g/100g)
FIGURE 4 (Continued)
|
11 of 16
SHABAN I et Al.
3.6 | Microbial analysis of FFB during storage period
Table 4 presents the ANOVA results of the microbial changes of FFB
within the3months storage time at −18°C. Although thetotal vi-
able count (TVC) of control sample after 90 days of freeze- storage
reached to 5.33 and it was <7 log10 CFU/g (the permissible num-
ber announced by INSO, 2016) (due to the addition of spices to fish
burger), increasing FDP concentration in FFB decreased the repro-
duction rate of TVC significantly (p < .01), and the lowest amount of
TVC was observed in FFB containing 0.4 g FDP/100 g and stored at
similar conditions. The retarding effects of propolis on microbial ac-
tivitiesofseafoodproductsareverysimilartoherbalextracts.Çoban
andKeleştemur(2017)couldreducethemicrobialloadofcatfishfish
burger sig nificantl y when they mixe d it with 0.4% (w/v) of ZMEO
(Zataria multiflora Boiss essential oil). When Özvural et al. (2016)
combinedhamburgerpattieswith 5%greenteaextract,theycould
decreaseitsmesophilic bacteriaandyeaststored at4°Cfor8days
significantly.Brooksetal.(1998)statedthatthehydroxylgroupsof
phenolic compounds react with biomolecules of cell bacteria and
delay their growth. Furthermore, phenolic compounds have ability
to get bound with the proteins and walls of cells, inactivate their en-
zymes, penetrate the bacteria's DNA, and prevent their replications.
3.7 | Cooking properties of FFB
Juiceleakageor transudationof meatproductswithhighmoisture
content (≥75%) during the cooking process represents economic
loses, releasing nutritional values (mainly soluble vitamins and
amino aci ds), and some negative ef fects on tex ture and juicine ss
TABLE 2 The ANOVA results for optimization of some chemical quality indicators of frozen fish burger patties by cubic regression
function
Source1
F- value2,3
Y1Y2Y3Y4Y5Y6Y7Y8
Model 51.77 * 102.87* 285.73* 75.96* 47. 71* 50.34* 7. 61** 21.14*
x159.96* 188 .12* 4 61.19* 91 .3 6* 70.45* 103.03* 2.45n.s.3 0.11*
x224.22* 1.09n.s.18.77* 53.49* 24.89* 7.8 8 * * 10.02** 6.11n.s.
x1x236.45* 20.1* 7. 10* * 31.61* 7.32 * * 3.13 n.s.0.054n.s.7. 51* *
x1
217. 39* 9.74** 357.23* 7.62 * * 0.15n.s.4.87n.s.0.30n.s.0.56n.s.
x2
28.80** 0.72n.s.1.55n.s.12.93** 7. 29** 1.53n.s.2.67n.s.3.28n.s.
x1
2x20.069n.s.3.54n.s.0.59n.s.5.31n.s.0.48n.s.1.37n.s.0.05n.s.0.19n.s.
x1x2
20.87n.s.1.87n.s.2.37n.s.3.58n.s.1.19n.s.0.21n.s.0.83n.s.1.21n.s.
Lack of fit (LOF) 3.26n.s.1 .74 n.s.0.55n.s.0.082n.s.0.011n.s.0.17n.s.0.02n.s.0.039n.s.
R20.986 4 0.9931 0.9975 0.9907 0.9852 0.9860 0 .9142 0.9673
R2
Adj 0.9673 0.9835 0.9940 0.9776 0.9646 0.9664 0.7941 0.9216
C.V. 4.02 4.26 0.099 2.41 1.23 53.92 2.02 22.05
SD 0.61 0.024 0.00625 0.41 0.66 0.37 0.98 1.06
PRESS 99.15 0.10 0.00298 3.19 3.85 4.13 9. 88 14.35
Source1
Coefficients of regression function (βn)
Y1Y2Y3Y4Y5Y6Y7Y8
Model +14.02 +0.54 +6.31 +16.31 +53.16 −0.79 +48.96 +4.49
x1+3.35 +0.23 −0.095 +2.78 +3.90 −2.65 −1.0 9 +4.11
x2−2.13 −0.018 +0.019 −2.13 −2. 32 +0.73 +2.20 −1.8 5
x1x2−1. 8 5 −0.054 +0.00833 −1 .16 −0.89 +0.33 +0.11 −1 .45
x1
2+1.54 +0.045 +0.071 +0.68 −0.15 +0.49 +0.32 −0.48
x2
2+1.09 +0.012 −0.00468 +0.89 +1.07 −0.28 − 0.97 +1.15
x1
2x2+0.14 −0.039 −0.00417 +0.82 +0.40 −0.38 +0.19 +0.40
x1x2
2+0.49 +0.028 −0.00833 +0.67 +0.62 − 0.15 −0.78 +1.01
1The parameters of x1 and x2relatedtoindependentvariablesofstoragetime(day)andfreeze-driedpropolis(gofFDP/[100goffishpaste]),
respectively.
2The parameter of Y is function response of polynomial regression and the subscripts of 1, 2, 3, 4, 5, 6, 7, and 8, respectively related to PV (meq O2/
kgoil),TBARS(mgMDA/kg),pH(−),TVB-N(mgN2/100g),lightnessindex(−),rednessindex(−),yellownessindex(−),andcolorchange(−).
3Differentsuperscriptslettersineachcolumnshowthesignificant([*]&[**]forp<0.01 and p<0.05, respectively) differences between the
treatments.
12 of 16
|
SHABANI et Al.
(Fennema, 1996). The cooking process leads to water evaporation
along with lipid migration in the fish burger patties, and the intensity
of these changes have considerable effects on their consumers' ac-
ceptance.The roleofprotein matrix is to retain thewater andfat
and bind them together (Fennema, 1996). Since the moisture and
fatretentioninFFBarerelatedtothecookingyield(CY),theywere
measured to determine the influence of adding FDP to FFB during its
formulations. The ANOVA results showed that increasing the FDP
levels in fish burger patties had significant (p < .01) effects on in-
creasingtheCY(Table5),andthehighestCYwasobservedwhenthe
FDP concentration reached to 0.4 g/100 g of FFB. Similar findings
were observed in cooking yield of hamburgers when researchers
enrichedthemwithherbalextractscontainingphenoliccompounds
(Ali et al., 2019; Angiolillo et al., 2015; Bainy et al., 2015). The FDP
had no negative effects on the fat and moisture release during cook-
ing process in comparison with the control sample. Since addition of
FDP to FFB made no undesirable changes in the cooking characteris-
ticsoffishburgerpatties,theresultingFFBhadtextureandjuiciness
very similar to control or conventional fish burger patties.
4 | CONCLUSION
This study showed that freeze- drying process followed by water-
ethanolextractionofrawpropolisincreasedsignificantlyitsphe-
nolic contentand antioxidant activities in comparison with raw
and alcohol extraction of propolis.Later the addition of FDP to
FFB at different levels could prevent and retard degradation of
this nutritive and healthy product during long- time freezing stor-
age.Moreclearly,the qualityindicators includingperoxidevalue
(PV), thio- barbituric acid (TBA), total volatile basic nitrogen base
(TVB- N), total viable count (T VC), Staphylococcus aureus count
(SAC), mold, and yeast of FFB became below their permissible lev-
els and significantly lower than the control sample. Furthermore,
whenincorporatingFDPwithFFBat 0.4g/[100g]duringitsfor-
mulation, its PV generation reduced to <16 meq O2/kg oil (below
the permissible level (20 meq O2/kg oil)) even after 90 days in
−18°Cstorage.However,thePVofitscontrolsampleincreasedto
more than 24 meq O2/kg oil at similar conditions. Overall, fortifi-
cation of rainbow- trout fish burger patties with FDP can protect
TABLE 3 EffectsofaddingdifferentlevelsofFDP(freeze-driedpropolis)anddaysofstorage(at−18°C)onappearanceandvisualcolorof
FFB (frozen fish burgers) patties
Products1
Days of storage
030 60 90
Produc t- (I)
Produc t- (II)
Product- (III)
Produc t- (IV)
1TheGreeknumbersof(I),(II),(III),and(IV)representdifferentlevels(0,0.1,0.2,and0.4g)ofFDP/[100goffishpaste],respectively.
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SHABAN I et Al.
its high protein quality and polyunsaturated fats (in the form of
omega- 3s) of FFB is highly recommended.
The purity of propolis has a significant role for effective preser-
vation of different food. Therefore, the future study of this natural
compoundshouldbe focused on application of various extraction
procedures (such as ultrasound) and coating (encapsulation) with
proteincompoundstoenhanceitsantioxidantpowerandalsoenrich
its nutritional value.
TABLE 4 The microbiological mean values1alongdifferentlevelsofFDP(freeze-driedpropolis)mixedwithFFB(frozenfishburger)
during3monthsstorageat−18°C2
Products3
Storage time,
day
Type and number of target microorganism, log10 CFU/g4
TMC5SAC5SC EC MYC5
Produc t- (I)
0 4.06 ± 0.06i1.48 ± 0.0071lNeg. Neg. 2.65 ± 0.005i
30 4.48 ± 0.03g2.09 ± 0.0017iNeg. Neg. 2.79 ± 0.0035f
60 5.12 ± 0.001de 2.81 ± 0.0033bNeg. Neg. 2.89 ± 0.003b
90 5.33 ± 0.001a2.86 ± 0.0029aNeg. Neg. 2 .94 ± 0.0024a
Produc t- (II)
0 3.89 ± 0.064j1.44 ± 0.0079mNeg. Neg. 2.58 ± 0.0056l
30 4.43 ± 0.003g2.07 ± 0.0018jNeg. Neg. 2 .71 ± 0.0042h
60 5.08 ± 0.002de 2.70 ± 0.0043cNeg. Neg. 2.80 ± 0.0034e
90 5.27 ± 0.002b2.66 ± 0.0047dNeg. Neg. 2.88 ± 0.0028c
Product- (III)
03.87 ± 0.085j1.02 ± 0.021nNeg. Neg. 2.56 ± 0.0059m
30 4.35 ± 0.01h1.94 ± 0.0024kNeg. Neg. 2.64 ± 0.0048j
60 5.07 ± 0.002e2.48 ± 0.0071fNeg. Neg. 2.72 ± 0.0041g
90 5.19 ± 0.003c2.57 ± 0.0058eNeg. Neg. 2.82 ± 0.0032d
Produc t- (IV)
0 3.66 ± 0.038k0.00 ± 0.00oNeg. Neg. 2.43 ± 0.0079o
30 4.30 ± 0.039h1.93 ± 0.018kNeg. Neg. 2.53 ± 0.0063n
60 4.98 ± 0.002f2.13 ± 0.016hNeg. Neg. 2 .61 ± 0.0052k
90 5.13 ± 0.003cd 2 .19 ± 0.014gNeg. Neg. 2.70 ± 0.0043h
1Average of three replicates
2Different superscripts letters in each column indicate the significant (p < .01) differences between the treatments.
3TheGreeknumbersof(I),(II),(III),and(IV )representtheFFBcontaining0,0.1,0.2,and0.4(gofFDP/[100goffishpaste]),respectively.
4Abbreviation form of total mesophilic count, Staphylococcus aureus count, Escherichia coli count, Salmonella count and mold and yeast count
microorganismsarerespectively,TMC,SAC,EC,SC,andMYC.
5ThemaximumlimitofTMC,SA ,andYMmicroorganismsinaccordancetonationalstandardofIranarerespectively,7,3,and3log10 CFU/g for fish
burger patties.
TABLE 5 The mean1 values obtained for cooking properties of FFB (containing different levels of FDP2) when it was heated for 5 min at
180°C
Products3
Cooking properties
Cooking yield, % Fat retention, %
Moisture
retention, %
Produc t- (I) 76.027 ± 0.281b77.252 ± 5.562a65.582 ± 0.599b
Produc t- (II) 76. 29 0 ± 0.815b77.573 ± 1.484a66.931 ± 1.557ab
Product- (III) 76.792 ± 0.801b78.291 ± 5. 248a68.201 ± 1.226a
Produc t- (IV) 79.4 34 ± 1.228a81 .741 ± 1.777a68.463 ± 1.078a
1Average of three replicates.
2Different superscripts letters in each column indicate the significant (p < .01) differences between the treatments.
3TheGreecenumberof(I),(II),(III),and(IV)representtheFFBcontaining0,0.1,0.2,and0.4(gofFDP/[100goffishpaste]),respectively.
14 of 16
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CONFLICT OF INTEREST
The authors have declared no conflicts of interest for this article.
AUTHOR CONTRIBUTIONS
Marjan Shabani: Investigation; Resources. Mohsen Mokhtarian:
Project administration; Supervision; Writing-review & editing.
Ahmad Kalbasi- Ashtari: Project administration; Supervision;
Writing-review & editing. Reza Kazempoor: Investigation;
Resources.
DATA AVAIL ABI LIT Y S TATEM ENT
The data that support the findings of this study are available from
the corresponding author upon reasonable request.
ORCID
Mohsen Mokhtarian https://orcid.org/0000-0003-4551-7065
Ahmad Kalbasi- Ashtari https://orcid.org/0000-0002-3153-2232
Reza Kazempoor https://orcid.org/0000-0002-4986-4307
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How to cite this article:Shabani,M.,Mokhtarian,M.,
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