RESEARCH ARTICLE
A simple optical pH sensor based on pectin and Ruellia
tuberosa L-derived anthocyanin for fish freshness monitoring
[version 2; peer review: 1 approved, 1 not approved]
Nazaruddin Nazaruddin
1
, Nurul Afifah
1
, Muhammad Bahi
1
,
Susilawati Susilawati
1
, Nor Diyana Md. Sani
2
, Chakavak Esmaeili
3
,
Muhammad Iqhrammullah
4
, Murniana Murniana
1
, Uswatun Hasanah
5
,
Eka Safitri
1
1
Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Banda Aceh, Aceh, 23111,
Indonesia
2
Sanichem Resources Sdn. Bhd., Bandar Estek, Negeri Sembilan, 71060, Malaysia
3
Center of Excellence in Electrochemistry, University of Tehran, Tehran, 14176-14411, Iran
4
Graduate School of Mathematics and Applied Sciences, Universitas Syiah Kuala, Banda Aceh, Aceh, 23111, Indonesia
5
Department of Fisheries, Universitas Teuku Umar, West Aceh, Aceh, 23615, Indonesia
First published: 27 May 2021, 10:422
https://doi.org/10.12688/f1000research.52836.1
Latest published: 21 Jul 2021, 10:422
https://doi.org/10.12688/f1000research.52836.2
v2
Abstract
A simple optical pH sensor using the active compound anthocyanin
(ACN), derived Ruellia tuberosa L. flower immobilized in a pectin
membrane matrix, was been fabricated and employed to monitor the
freshness of tilapia fish at room temperature and 4
o
C storage. The
quantitative pH values were measured based on the UV-Vis
spectroscopy absorbance. The optimum pectin weight and ACN
concentrations were 0.1% and 0.025 mg/L. The sensor showed good
sensitivity at 0.03 M phosphate buffer solution. The sensor’s
reproducibility was evaluated using 10 replicate sensors where a
standard deviation of 0.045 or relative standard deviation of 9.15 was
achieved. The sensor displayed an excellent response after 10 minutes
of exposure, possessing a response stability for 10 consecutive days.
The decrease in pH value of the Tilapia fish from 7.3 to 5 was observed
in a 48 hour test, which can be used as the parameter when
monitoring fish freshness. Overall, this reported optical pH sensor has
a novelty as it could be used to monitor the rigor mortis phase of fish
meat, which is useful in food industry.
Keywords
optical pH sensor, matrix membrane, pectin, anthocyanin, fish
freshness
Open Peer Review
Reviewer Status
Invited Reviewers
1 2
version 2
(revision)
21 Jul 2021
report
version 1
27 May 2021 report report
Sagir Alva, Universitas Mercu Buana, Jakarta,
Indonesia
1.
Nur Hamidah Abdul Halim, Universiti
Malaysia Perlis, Kangar, Malaysia
2.
Any reports and responses or comments on the
article can be found at the end of the article.
Page 1 of 25
F1000Research 2021, 10:422 Last updated: 11 AUG 2021
Corresponding author: Nazaruddin Nazaruddin ([email protected])
Author roles: Nazaruddin N: Conceptualization, Supervision, Writing – Original Draft Preparation; Afifah N: Data Curation,
Investigation; Bahi M: Formal Analysis; Susilawati S: Formal Analysis; Sani NDM: Writing – Original Draft Preparation, Writing – Review
& Editing; Esmaeili C: Formal Analysis; Iqhrammullah M: Visualization, Writing – Review & Editing; Murniana M: Supervision; Hasanah
U: Project Administration, Writing – Review & Editing; Safitri E: Funding Acquisition, Methodology, Resources, Supervision, Writing –
Original Draft Preparation
Competing interests: No competing interests were disclosed.
Grant information: We acknowledge financial support from Universitas Syiah Kuala for experiment via grants Lektor Kepala (Contract
Number 76/UN11.2/PP/PNDP/SP3/2019).
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Copyright: © 2021 Nazaruddin N et al. This is an open access article distributed under the terms of the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to cite this article: Nazaruddin N, Afifah N, Bahi M et al. A simple optical pH sensor based on pectin and Ruellia tuberosa L-
derived anthocyanin for fish freshness monitoring [version 2; peer review: 1 approved, 1 not approved] F1000Research 2021, 10
:422 https://doi.org/10.12688/f1000research.52836.2
First published: 27 May 2021, 10:422 https://doi.org/10.12688/f1000research.52836.1
Page 2 of 25
F1000Research 2021, 10:422 Last updated: 11 AUG 2021
Introduction
Fish freshness assessment is the main concern for consumers nowadays as people are more cautious about what they put
into their body. Eating spoiled products will cause food poisoning symptoms to various degrees. For example, eating
spoiled fish may result in an almost immediate onset of diarrhea, nausea and vomiting. According to the United Nations,
about 4.5 billion people rely on fish for 15% of their animal protein intake.
1
Therefore, it is imperative to monitor the
freshness and quality of fish. Currently, consumers rely on their own experience in determining fish freshness. This is
mostly based on the physical condition of the fish like its color and smell. This method is very subjective; hence, there is
a need for a more quantitative monitoring method for fish freshness. Heisinget al.(2012)
2
has produced a fish freshness
monitoring method by detecting total volatile basic nitrogen using an ammonia ion-selective electrode. However, not
all of the ammonia produced will dissociate in the aqueous phase, which is a challenge in the conductivity changes-
dependent method. Determination of fish freshness can also be performed by measuring trimethylamine (TMA) levels
using electrochemical sensing, as reported by Bouriguaet al.(2011)
3
However, determining the freshness of fish via
measuring TMA requires a complicated procedure and experts to operate the equipment. Fish freshness can be monitored
using an ammonia optical sensor. Wellset al.(2019)
4
reported the determination of fish freshness through ammonia
measurement that also used TMA solution standard and a dye indicator for pH measurement. Beside these two methods, a
pH sensor can also be employed to monitor fish freshness.
5–8
There have been several methods proposed to determine pH
levels of a fish sample. The most common methods used are optical sensors and ion-selective electrodes (ISEs).
9
The
measurement of pH using an H
+
ISE is dramatically affected by interferences from samples, especially the presence of
alkaline ions.
10
Thus, the determination of pH through optics may be an excellent alternative for samples that contain
interfering ions.
Several organic pH-sensitive dyes, immobilized in synthetic membranes, have been utilized in the construction of optical
pH sensors. Nonetheless, safer compounds derived from natural products have attracted the attention of researchers in
developing pH sensors. An earlier report of optical pH sensors includes the construction of a pH sensor using phenol
red as an active molecule.
11
The further report had described the development of a pH sensor utilizing polyvinyl chloride
as the matrix and the fluorescence compound fluorescein-O-methacrylate as the active molecule.
12
Nevertheless, these
aforementioned pH sensors could only be used on solutions with near-neutral pH as more basic or acidic solutions will
give an insignificant response time. Pourjavaheret al.(2017)
13
has designed a pH sensor using bacterial cellulose (BC)
nanofiber matrix to immobilize anthocyanin (CAN) from red cabbage (Brassica oleracea) extract. The sensor has a fairly
wide pH range but it needs further characterization to evaluate the sensor performance, especially, for real foodstuff
analysis. The use of anthocyanin ACN from blackberries and chitosan membrane in an optical pH sensor has been
established.
14
The interaction and mechanical properties of chitosan membrane with entrapped ACN have also been
reported.
15
Anthocyanins are flavonoids possessing a number of hydroxyl groups contributing a strong interaction with
chitosan via hydrogen bonding.
A more recent study on fish freshness monitoring through optical methods was reported by Moradiet al.(2019)
16
using
nanofiber bacterial cellulose with ACN. However, this method requires a relatively long analytical time as the pH
measurement could not be conductedin situ.Chenet al. (2020)
7
has developed a sensitive novel film prepared from starch
polyvinyl alcohol and starch polyvinyl alcohol glycerol. The study used curcumin from turmeric and anthocyanin from
purple sweet potatoes. The results showed that the mixture of curcumin and ACN improved the stability than that of the
individual active substances. As the consequence, the sensor could be employed to detect volatile ammonia as the fish
freshness indicator.
Herein, we constructed a new optical pH sensor based on pectin (PC) matrix and ACN extract from theRuellia tuberosa
L flower. The ACN derived from the crude extract ofRuellia tuberosaL flower has been reported to be pH sensitive.
17
PC
is a non-toxic biopolymer that can be crosslinked with the assistance of CaCl
2. PC membrane is transparent, deeming it
suitable as a matrix for optical measurements. Moreover, PC is also a hydrogel that will enable easy diffusion of analytes
leading to a faster response time compared to another hydrophobic matrices.
18
In addition, PC application as an optical
pH sensor for fish freshness monitoring has not been well-explored. ACN is well known to be pH sensitive and will
REVISEDAmendments from Version 1
Abstract has been added with the statement of this study's novelty at the end of the paragraph. More elaboration on the
introduction. Methods now contains Study Design subsection. Two figures have been added namely, Figure 1 and Figure 7;
as a consequence, the order has been changed as well. A paragraph before Table 1, was reordered. Discussion on pH
decrease during rigor mortis has been more elaborated with an additional explanation of this study's novelty. Citation has
been reordered, where some have been removed.
Any further responses from the reviewers can be found at the end of the article
Page 3 of 25
F1000Research 2021, 10:422 Last updated: 11 AUG 2021
undergo color changes at different pH.
19
This compound is easily obtained from nature and is relatively cheap compared
to other pH sensitive active molecules. In the present work, ACN has been extracted from the flowerRuellia-tuberosa
L. The ACN was immobilized onto PC membrane to produce CAN/PC composite membrane which can be used forin situ
detection of fish freshness without requiring a destructive procedure.
Methods
Materials
All chemicals used in this research are analytical grade. Monopotassium phosphate (KH
2PO4) and dipotassium phosphate
(K
2HPO4) were purchased from Merck (Merck Millipore, Darmstadt, Germany); PC, ethanol, and CaCl2–from Sigma-
Aldrich (Sigma Aldrich Chemie GmbH, München, Germany); and methanol and acetic acid–from Fluka (Fluka Chemie
GmbH, Buchs, Switzerland). As for the plant sample, wildRuellia tuberosaL. was collected from the area near Universitas
Syiah Kuala in Banda Aceh, Aceh, Indonesia. To study the application of the optical pH sensor on the real sample, dead
tilapia fishes were used and purchased from the traditional market in Banda Aceh, Aceh, Indonesia.
Study design
The first step in sensor fabrication was the extraction of anthocyanin fromRuellia tuberosaL. The extracted anthocyanins
were then mixed with pectin solution and printed proportionally as an optical pH sensor. The optical pH sensor was then
characterized and the optimized and then applied to monitor the freshness of tilapia. The image below is a schematic
diagram summarizing research procedures conducted in this work (Figure 1).
Anthocyanin extraction
The procedure follows a previous report.
20
Briefly, 200 g freshR. tuberosaL. was macerated in 85 mL methanol for 24 h
at room temperature (32-34°C). The residue was then separated from the filtrate by simple filtration. Finally, ACN was
obtained after the solvent was removed from the filtrate by means of steaming at 50°C until the volume reached 50 mL.
Construction of optical pH sensor with various ACN concentrations
The optical pH sensor was constructed by dissolving PC powder into a matrix solution (0.1% w/v) in 100 mL CaCl
20.1 M
solution, heated at 60°C. After the mixture was cooled down, the previously obtained ACN extract (1.503 mg/L)
was added to 1.66, 2.49 and 3.33 mL PC matrix solution to produce three different 100 mL ACN/PC solutions with
respective ACN concentrations of 0.025, 0.0375 and 0.05 mg/L. A total of 40μL the ACN/PC solution was dropped onto
a polyvinylchloride plastic mold surface with a diameter of 0.8 cm (Figure 2). The sensor was allowed to dry for 24 h
at 4
o
C.
Fourier Transform Infrared (FTIR) Cary 630 Anti Agilent (Penang, Malaysia) was used to identify the structure and
functional groups. The membrane morphology was observed under Zeiss Merlin/Merlin Compact/Supra 55VP Field
Emission Scanning Electron (FESEM) (Selangor, Malaysia). Thermal stability of the constructed membrane was
analyzed using Shimadzu DTG-60 Thermal Gravimetric Analyzer (Kyoto, Japan) and Differential Scanning Calorimetry
(DSC) Shimadzu DSC-60 (Kyoto, Japan). Unless otherwise stated, the conditions for these characterizations followed
that of reported work for film specimens.
21,22
Figure 1.Schematic diagram of optical sensor fabrication and its application for fish freshness monitoring.
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F1000Research 2021, 10:422 Last updated: 11 AUG 2021
To test its response and evaluate its analytical performance, each sensor was dripped with 30μL 0.1 M phosphate buffer
solution with a variety of pH values ranging from 5.0 to 8.5 with 0.5 interval–the pH values of each phosphate solution on
the sensor were checked by pH-meter Thermo Orion Star A2111 (Selangor, Malaysia). The sensor color changed
corresponding to the different pH values of the administered buffer solutions. It consequently resulted in the difference of
the absorbance that was then measured nm using UV-VIS Spectrophotometer (Shimadzu Uv-mini-1240, Kyoto, Japan) at
λ
max= 635,
17
until the sensitivity value for pH determination was obtained.
Effect of PC concentration
The effect of PC concentration was tested based on % weight of PC in CaCl
20.1 M solution; 0.05, 0.10, and 0.15%. In
total, 40μL of the three different PC solutions containing 0.025 mg/L ACN were casted as previously explained above.
Finally, the pH sensor was pipetted with 30μL phosphate buffer 0.1 M (pH 4-9), and its absorbance was measured.
Selection of the optimum buffer solution and concentration
The optical pH sensor with optimum ACN and PC concentrations was used to test its performance against phosphate and
citrate buffers 0.1 M (pH 5.0-8.5) to select which buffer generated the best outcome. To select the optimum buffer
concentration (once the best buffer had been chosen; phosphate), the best buffer solution was varied in concentration
(0.01, 0.03, and 0.05 M) and used in the optical pH sensor performance with pH ranging from 6-8 following the
previously explained procedure. The optimum concentration was selected based on its sensitivity and linearity of the
absorbance versus pH plotting curve.
Evaluation of reproducibility, response time and lifetime study of the optical pH sensor
Response time of the optical pH sensor was determined by measuring the optimum absorbance of the pH sensor at a range of
5, 10, 15, 20, 25 and 30 minutes. For reproducibility, the performance was conducted 10 times using ten optical pH sensors.
For the determination of the optical pH sensor’s lifetime, the absorbance measurement was carried out after 1, 2, 3, 4, 5, 10,
15 and 20 days after the sensor preparation. All of these studies were conducted under optimum buffer conditions.
Optical pH sensor test on fish sample
The pH values of the tilapia fishes were measured by attaching the sensors onto the fishes' surface for 5 minutes before
measuring the absorbance, as explained before. The fish were stored at 4°C and ambient temperature (32-34°C). The pH
analysis was carried out every 7, 12, 24, and 48 h of the storage time.
Results and discussion
Characteristics: structure, crystallinity, morphology, and thermal behavior
Anthocyanin (ACN) is one of the most important components in the construction of this optical pH sensor other than
PC. ACN is obtained from the extract ofR. tuberosaL. flower that displays different colors at different acidic or basic
pH levels.
23,24
FTIR analysis of the extract showed that the broadening vibrational band with medium intensity at the
wavenumber, ranged between 3333 cm
-1
and 3291 cm
-1
, indicating the presence of free O-H groups (Figure 3). The presence
Figure 2.(a) The designed shape and (b) the visual appearance of ACN/PC optical pH sensor.
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F1000Research 2021, 10:422 Last updated: 11 AUG 2021
of the aromatic C=C vibrations at wavelength region 1644 cm
-1
and 1454 cm
-1
indicates the typical characteristics of an
ACN compound.
25
The vibrations by group C-O were recognized from wavelength range 1111 and 1015 cm
-1
. The FT-IR
characterization shows that the ACN is in the form of cyanidin-3-glucoside; similar vibration patterns has been reported
previously.
26
FT-IR characterization on PC displayed typical PC functional groups at wavenumber range of 1000-2000 cm
-1
. Spectral
band at 1717 cm
-1
and 1624 cm
-1
are assigned to be vibrations of C=O stretching from ester and carboxylate. The presence
of other spectral band at 3370 cm
-1
is assigned to the vibrational absorbance of O–H functional groups. The ether bonds of
C–O–C is observed by the presence of the absorbance peaks at 1219 and 1096 cm
-1
. In the case of ACN/PC, free O–H
groups from the PC molecule were observed from the overlapping band at 3200-3650 cm
-1
. The other spectral bands at
1630–1850 cm
-1
and 1050–1260 cm
-1
are assigned to carbonyl groups (C=O) and symmetrical ether groups (C–O–C)
from glycoside bonds, respectively.
27,28
TGA/DTGA and DSC profiles of PC membrane
Thermal stability is one of preferable characteristics when it comes to a bio-sensor as it may influence its performance. We
conducted thermal gravimetry analysis (TGA) and differential scanning calorimetry (DSC) studies to assess whether the
PC membrane has ideal thermal stability. The thermograms of TGA and its derivative (DTGA) and DSC have been
presented inFigure 4aandb. At around 58°C, the release of solvent (water) was observed on the TGA and DTGA
thermograms (Figure 4a). The second peak of DTGA suggests thermal degradation with 30% weight loss.
29
A better
insight regarding the thermal stability of the PC membrane can be seen in the DSC thermogram.
21,22
The first endothermic peak that appears in the DSC thermogram (Figure 4b) agrees with the water content release
observed in the TGA. T-
onset= 83°C indicates the first observable thermal transition, in which it is assigned to melting
temperature. It is because within the temperature range (83-118°C), the decrease in weight does not occur in the TGA
thermogram. This finding is in line with a previous report investigating PC powder.
30
The exothermal peak (T-
peak=
309°C) observed afterward indicates the degradation of the PC polymeric chain. From these data, we can conclude that
the PC membrane is thermally stable at room temperature range.
SEM images of PC membrane
SEM images of PC (Figure 5a) and ACN/PC (Figure 5b) depict a clear difference of surface morphology between the
two.
18
PC surface has a morphology that is uniform and smooth. With the addition of ACN into the membrane, wavy
layers are shown as the result of the presence of the liquid that, as the consequence, possibly creates a stress tension or air
gap. Other study showing severe cracks on the membrane surface, associated with the presence of water.
31
This change
Figure 3.FT-IR spectral profile of PC, ACN, and ACN/PC.
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F1000Research 2021, 10:422 Last updated: 11 AUG 2021
may lead to poorer sensor performance as a transparent membrane is preferred for optical sensor to allow the UV light
passing through the membrane. Hence, investigation on the sensitivity of the optical pH sensor with respect of ACN or PC
loads is important.
Effect of ACN concentration on the sensitivity of the optical pH sensor
The constructed optical pH sensor based on the ACN derived fromR. tuberosaL flower has hydrogel characteristics. The
advantage of a hydrogel membrane in an optical system is the quick interaction between analyte and active membrane
which in turn will accelerate the response time.
18,32
The PC membrane with the immobilized ACN is transparent, where
the color change is sensitive against the pH value (Figure 6). This optical pH sensor is optimized by means of ACN
variation to achieve the best sensitivity, observed by a wide linear range and good linearity. Further characterization is
followed by the determination of sensor performance.
Color change of ACN can be affected by several factors such as temperature, pH, light intensity, sugar moiety
and different phenolic derivatives.
18
Due to its solubility in aqueous solution, the color change of ACN is caused by
structural transformations of carbon skeleton affected by the levels of H
+
. Four major anthocyanin skeletons have been
reported in the literature at different pH values (Figure 7); the red flavylium cation (pH < 3), the blue quinoidal base
(pH 6-7), the colorless carbinol pseudo-base (pH 4-5), and the yellowishcis-chalcone (pH > 6) (Figure 7).
33,34
The effect of ACN concentrations on optical pH sensors response has also been studied and shown (Table 1andFigure 8).
The sensitivity of the sensor toward variations in ACN concentrations showed not significantly different, but the
absorbance vs pH plot showed an increase in the value of the intercept. This indicates the intensity of the sensor color
increases with increasing ACN concentrations. Furthermore, the ACN concentration of 0.025 mg/L will be used to
construct the optical pH sensor for the next characterization.
Figure 5.SEM profile of (a) PC and (b) ACN/PC membranes.
Figure 4.(a) TGA/DTGA and (b) DSC thermograms of thermal analysis on PC membrane.
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F1000Research 2021, 10:422 Last updated: 11 AUG 2021
Figure 7.Anthocyanin molecular structures with respect of pH changes.
Figure 6.Optical pH sensor color changes at different pH values.
Table 1.Effect of ACN concentrations on the sensitivity of the optical pH sensors on phosphate buffer.
Concentration (mg/L) pH range Sensitivity R
2
0.025 6-8 0.14 0.03 0.999
0.0375 6-8 0.108 0.05 0.999
0.05 6-8 0.094 0.01 0.995
Figure 8.Effect of ACN concentration on sensitivity optical pH sensor.
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Effect of PC weight towardssensorsensitivity
The weight variation of PC (0.05, 0.1, and 0.15% w/v) was studied to find the best sensor sensitivity. At varied weights,
PC was dissolved using CaCl
20.1 M to construct cross linking between Ca
2+ ion
and galacturonate until a pectin solution
in the form of gel was produced.
35
The effect of PC weight towards the sensitivity of optical pH sensor has been presented
(Figure 9). The optimal weight percentage of PC was found at 0.1 % w/v. The membrane with 0.1% w/v pectin has a
flatter surface thus making it as the most suitable optical sensor. PC membrane with only 0.05% w/v PC possessed a gel
like texture due to the excess of water which causes a longer time to form a solid membrane. This phenomenon is quite
similar for membrane preparation using a phase inversion method.
21,36,37
On the other hand, membrane with 0.15% PC is
very dense and has a non-homogenous surface which is not preferred for optical pH membrane application.
38
Effect of type and concentration of buffer on the sensor performance
The performance of an optical pH sensor may be affected by the types and concentration of the buffer.Figure 10shows
that the sensitivity of the sensor with phosphate buffer was 0.0877 with an R-square value of 0.993. On the other hand, the
Figure 10.Effect of buffer type towards the sensitivity of optical pH sensor.
Figure 9.Effect of pectin weight towards the sensitivity of optical pH sensor.
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F1000Research 2021, 10:422 Last updated: 11 AUG 2021
ACN/PC sensor with citrate buffer had a sensitivity of 0.074 (R
2
= 0.981). Through physical observation, the ANC in the
sensor would display a higher color intensity when in phosphate buffer compared to citrate buffer even in the same pH
range. This is due to the lower K
avalue of phosphate buffer compared to citrate buffer. Altogether, we conclude that the
phosphate buffer contributes to better sensitivity of our pH sensor as opposed to citrate buffer. Therefore, the effect of
concentration was studied using the phosphate buffer.
The effect of phosphate buffer concentration towards this sensor’s sensitivity is shown inFigure 11. This pH sensor
produces the best sensitivity of 0.1238 (R
2
= 0.9989) when the phosphate buffer 0.03 M was used. Meanwhile, the
sensitivities of the pH sensor using phosphate buffer with concentrations of 0.05 M and 0.1 M were found lower at 0.072
(R
2
= 0.9745) and 0.084 (R
2
= 0.9805), respectively. The pH sensor with phosphate buffer 0.03 M gave a more contrast in
the color change at different pH levels, in comparison with that of citrate buffer. In comparison to other earlier studies,
11,12
our ACN/PC optical pH sensor has a wider working range of pH.
Response time and reproducibility measurement
The response time of this sensor was determined by the required duration (minutes) that the sensor achieves a stable result.
Response time was determined at 0, 5, 10, 15, 20, 25, and 30 minutes (Figure 12). The absorbance increased drastically
from the first 5 minutes, indicating a good diffusion of the sample onto the membrane. The increase was later observed
at minute 10, but no observable significant change afterward. Therefore, the optimum response time of this optical pH
sensor is 10 minutes.
Figure 12.The response time profile of pH sensor.
Figure 11.Effect of phosphate buffer concentration towards pH sensor’s sensitivity.
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F1000Research 2021, 10:422 Last updated: 11 AUG 2021
In addition, the reproducibility measurement was conducted on 10 different sensors with the same condition, where the
relative standard deviation (RSD) was 9.15. This shows that there is a small difference in the absorbance values obtained
from the repetition using new sensors. However, RSD that is below 10% is still acceptable for qualitative measurement.
38
Lifetime of pH sensor
The investigated optical pH sensor had a stable response until the tenth day of storage (Figure 13). Afterward, the sensor
response fell as much as 8.3% from the initial response, in which further decline was observed on the 15
th
day. At the
same time, the %RSD also become poor; increasing as much as 36.61% from its initial state. The decrease in sensor
performance after particular days of storing depends on the stability of the anthocyanin in maintaining its color. The
lifetime of the optical pH sensor in this study is worse in comparison to that of our previous study,
18
in which the
performance did not drop until the 15
th
day. However, previously we used the synthetic chromoionophore ETH 5294
(CI); unlike in this study where we used natural anthocyanin that can be considered more sustainable. Furthermore, in this
study, the lifetime is better in comparison to our currently reported sensor using ACN fromDioscorea alataL.
38
Fish freshness test using real samples
Optical pH sensor with the optimal conditions was used to monitor the freshness of tilapia fish that was kept at 4
o
C. The
pH profile of the fish at two conditions, namely room temperature and 4°C storage temperature, is shown inFigure 14.
A living fish has a pH value of around 7.4, but after death the pH decreases.
39
The pH of the fish samples was measured
Figure 13.Lifetime of optical pH sensor.
Figure 14.Fish freshness monitoring using optical pH sensor.
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after 0, 7, 12, 24 and 48 h storage time at room temperature and 4°C. Fish freshness was measured based on the
absorbance value that is converted to pH value based on the constructed calibration curve.
Fish samples kept at room temperature possess a higher pH compared to the fish sample stored at 4°C. Fresh fish that was
measured at 0 hours displayed pH of around 7.3-7.4. Following that, the pH decreases to 5.5-5.9, indicating that the fish
has reached rigor mortis or postmortem rigidity. The decrease is attributed to the accumulation of lactic acid from post
mortem glycolysis. After the rigor mortis phase, the fish will undergo putrefaction due to the microbial activity in the fish
sample.
40
This activity causes the pH to become more basic due to the breakdown of proteins in the fish sample to become
ammonia and trimethylamine.
23–25
Results achieved from pH measurements at 7, 12, 24 and 48 hours at 4°C using the
optical sensor yielded results of pH 5.9, 6.9, 7.1 and 7.9. Based on these results, it can be said that fish that is kept at room
temperature will undergo a faster decomposition. This is due to the exposure to sunlight thus a higher temperature that will
accelerate the process of decomposition.
Our method of measuring the change of pH is different to the most reported studies using colorimetric response.
4,5,7,14,16
Indeed, one may argue that colorimetry could give the best practicality of the sensor use. However, it suffers from
quantitative information, as it depends on the RGB profiles that requires complex model to convert the response into
measured pH value. Moreover, the reported studies rely on the volatile basic compounds released from the meat. Taken
altogether, the reported studies were unable to capture the decrease of pH during rigor mortis phase. In food industry, fish
meat is best processed by the filleting machine during the pre- or post-rigor mortem. This is the novelty of our optical pH
sensor which is useful for the quality control and processing of fish meat in industrial settings.
Conclusion
ACN extracted fromRuellia tuberosaL can be immobilized into a PC matrix to produce a sensitive optical pH sensor. The
extracted ACN has a similarity over the FT-IR profile of cyanidin-3-glucoside. The amount of ACN and PC in the
membrane composite affected the optical pH performance, which was largely indicated by intercept and linearity values.
The constructed optical pH sensor works best in phosphate buffer with a long lifetime. Its application in monitoring the
freshness of fish has been successfully conducted against the storing time, where the decrease in pH values during rigor
mortis period were observed. More studies indeed need carried out to obtain smooth surface morphology to improve the
optical sensor performance.
Data availability
Underlying data
Harvard Dataverse: Data Set for Optical pH Sensor Based on Pectin and Ruellia tuberosa L-derived Anthocyanin for Fish
Freshness Monitoring,https://doi.org/10.7910/DVN/ZYCXAM.
40
Data are available under the terms of theCreative Commons Zero“No rights reserved”data waiver(CC0 1.0 Public
domain dedication).
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Page 13 of 25
F1000Research 2021, 10:422 Last updated: 11 AUG 2021
Open Peer Review
Current Peer Review Status:
Version 2
Reviewer Report 11 August 2021
https://doi.org/10.5256/f1000research.58582.r90078
© 2021 Abdul Halim N. This is an open access peer review report distributed under the terms of the Creative
Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.
Nur Hamidah Abdul Halim
Institute of Nano Electronic Engineering, Universiti Malaysia Perlis, Kangar, Malaysia
I would suggest the writer to include "non destructive/by in situ detection or measurement for fish
freshness" in the abstract and title to highlight the novelty of this work.
"The extracted ACN has a similarity over the FT-IR profile of cyanidin-3-glucoside" is suddenly
introduced in the conclusion is hanging. Suggest elaborating how glycoside bonds are important
and how it contributed to the pH changes or how it related to freshness. Then it can be concluded
how the similarity by having FT-IR profile of cyanidin-3-glucoside in the ACN is desired in this work.
Is having "cyanidin-3-glucoside in ACN" the actual highlight in this work? If yes, the novelty
statement in the abstract, introduction and title need to be revised accordingly.
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Electrochemical biosensors
I confirm that I have read this submission and believe that I have an appropriate level of
expertise to confirm that it is of an acceptable scientific standard.
Version 1
Reviewer Report 18 June 2021
https://doi.org/10.5256/f1000research.56160.r86281
© 2021 Abdul Halim N. This is an open access peer review report distributed under the terms of the Creative
Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.
Page 14 of 25
F1000Research 2021, 10:422 Last updated: 11 AUG 2021
Nur Hamidah Abdul Halim
Institute of Nano Electronic Engineering, Universiti Malaysia Perlis, Kangar, Malaysia
This paper shows an experimental work on optical sensor using simple optical approach. This
paper shows a good work with a potential study on optical pH sensor for fish freshness
monitoring. However, it is suggested to elaborate further on discussion how the mechanism and
reaction with illustrated figure. The novelty should be explicitly mentioned in the introduction,
abstract and findings. A table on reported or published and comparison should also be made
available to see the research contribution. It is suggested that the authors may revise based on
few comments below:
Abstract
“The sensor displayed an excellent response after 10 minutes of exposure, possessing a response
stability for 10 consecutive days. The decrease in pH value of the Tilapia fish from 7.3 to 5 was observed
in a 48 hour test, which can be used as the parameter when monitoring fish freshness.“
Comment: The statement of decrease in pH value need to be elaborated to highlight the novelty of
this research. The authors may add comparison in terms of performance and mechanism that
differentiate this works and other reported work. E.g How pH value decrease mechanism is
evaluated and correlated to observe the fish freshness.
Introduction
Para 2: "Nevertheless, these aforementioned pH sensors could only be used on solutions with near-
neutral pH as more basic or acidic solutions will give an insignificant response time. Pourjavaher et al.
11
has designed an optical pH sensor based on cellulose nanofibers with red cabbage (Brassica oleracea)
extract, while Rajan et al. (2018)
12
has produced an optical pH sensor using peonidin pigment. However,
this study did not report the working pH range of peonidin. The use of anthocyanin (ACN) from
blackberries and chitosan membrane in an optical pH sensor has been established.13 The interaction
and mechanical properties of chitosan membrane with entrapped ACN have also been reported."
Comment: This paragraph should elaborate more on fish freshness and its correlation to pH
based on previous study. The use of ACN should be illustrated for reader to understand more as
the sentences is hanging (Referring to “The interaction and mechanical properties of chitosan
membrane with entrapped ACN have also been reported.”). It is more helpful if a table or illustrated
mechanism is shown to support this study and having a good flow of this paper.
Para 3: "A more recent study on fish freshness monitoring through optical methods was reported by
Moradi et al.
15
using nanofiber bacterial cellulose with ACN. However, this method requires a relatively
long analytical time as the pH measurement could not be conducted in situ. Chen et al. (2020)
6
has
developed a sensitive novel film prepared from starch polyvinyl alcohol and starch polyvinyl alcohol
glycerol."
Comment: Again, this paragraph does not add the value on published work with this work. The
mechanism on optical pH to monitor fish freshness is still not addressed. No comparison on the
electrochemical performance (LOD, Linear range, selectivity) was mentioned here. How long
analytical time is related to pH measurement by having different material like nanofiber and
optical properties coming from ACN dye. The ACN sensitivities towards pH correlation to ACN
optical properties may need to be added here as well.
Page 15 of 25
F1000Research 2021, 10:422 Last updated: 11 AUG 2021
Research and Methodology
Comment: The methodology shows a sufficient description a to give reader a good understanding
on how this study is conducted. It is suggested that the authors may add process flow/illustration
to complete the overall picture on steps and its mechanism.
Results and Discussion
Figure 4. SEM profile of (a) PC and (b) ACN/PC membranes.
Comments: The morphology of ACN/PC membrane does not seem like a crack. It seems to have a
wavy layer of membrane that might be the contributed to the adhesion/stress tension or air gap
of the ACN/PC compared to PC alone. Is there any study on different ration of CAN added to this
PC, or is it already optimized? The caption should be more detailed.
"Color change of ACN can be affected by several factors such as temperature, pH, light intensity, sugar
moiety and different phenolic derivatives. Due to its solubility in aqueous solution, the color change of
ACN is caused by structural transformations of carbon skeleton affected by the levels of H+."
Comments: The color change mechanism is important to be introduced earlier in the introduction
section and can be help with illustration. How different phenolic derivatives change this CAN, and
which phenolic derivatives took place in this reaction? The authors may put or add this point to
support the color change mechanism towards fish freshness from the finding.
Effect of PC weight towards sensor sensitivity
Comments: The pectin is a membrane that hold the ACN dye to improve the sensitivities. From Fig
4, the importance of having optimum load/weight of pectin is important the membrane with less
surface tension, and this is the reason of having crack or wavy like membrane. It is very important
optimum ratio of CAN/PC to have smooth ACN/PC membrane in this study.
Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Yes
Page 16 of 25
F1000Research 2021, 10:422 Last updated: 11 AUG 2021
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Electrochemical biosensors
I confirm that I have read this submission and believe that I have an appropriate level of
expertise to confirm that it is of an acceptable scientific standard, however I have
significant reservations, as outlined above.
Author Response 09 Jul 2021
Nazaruddin ., Universitas Syiah Kuala, Banda Aceh, Indonesia
Reviewer Nurhamidah
Thank you very much for valuable comments
Comment: The statement of decrease in pH value need to be elaborated to highlight the
novelty of this research. The authors may add comparison in terms of performance and
mechanism that differentiate this works and other reported work. E.g How pH value
decrease mechanism is evaluated and correlated to observe the fish freshness.
Response: The pH of fresh tilapia was 7.3, and the pH decreased to 5 after 7 hours of
storage in two storage conditions (room temperature and 4oC). Changes in pH from 7.3 to
8.7 are the condition of fish monitoring within 48 hours. The post mortem glycolysis-derived
lactic acid accumulation is also responsible for the pH decrease.
Additionally, we have amended the manuscript with the following text:
“Our method of measuring the change of pH is different to the most reported studies using
colorimetric response. Indeed, one may argue that colorimetry could give the best practicality of
the sensor use. However, it suffers from quantitative information, as it depends on the RGB
profiles that requires complex model to convert the response into measured pH value. Moreover,
the reported studies rely on the volatile basic compounds released from the meat. Taken
altogether, the reported studies were unable to capture the decrease of pH during rigor mortis
phase. In food industry, fish meat is best processed by the filleting machine during the pre- or
post-rigor mortem. This is the novelty of our optical pH sensor which is useful for the quality
control and processing of fish meat in industrial settings.”
Comment: This paragraph should elaborate more on fish freshness and its correlation to
pH based on previous study. The use of ACN should be illustrated for reader to understand
more as the sentences is hanging (Referring to “The interaction and mechanical properties
of chitosan membrane with entrapped ACN have also been reported.”). It is more helpful if a
table or illustrated mechanism is shown to support this study and having a good flow of this
paper.
Response: The paragraph 2 has been elaborated:
Nevertheless, these aforementioned pH sensors could only be used on solutions with near-neutral
pH as more basic or acidic solutions will give an insignificant response time. Pourjavaher et al.
11
has designed a pH sensor using bacterial cellulose (BC) nanofiber matrix to immobilize
anthocyanin (CAN) from red cabbage (Brassica oleracea) extract. The sensor has a fairly wide pH
Page 17 of 25
F1000Research 2021, 10:422 Last updated: 11 AUG 2021
range but it needs further characterization to evaluate the sensor performance, especially, for
real foodstuff analysis. The use of ACN from blackberries and chitosan membrane in an optical
pH sensor has been established.
13
The interaction and mechanical properties of chitosan
membrane with entrapped ACN have also been reported.
14
Anthocyanins are flavonoids
possessing a number of hydroxyl groups contributing a strong interaction with chitosan via
hydrogen bonding.
Comment: Again, this paragraph does not add the value on published work with this work.
The mechanism on optical pH to monitor fish freshness is still not addressed. No
comparison on the electrochemical performance (LOD, Linear range, selectivity) was
mentioned here. How long analytical time is related to pH measurement by having different
material like nanofiber and optical properties coming from ACN dye. The ACN sensitivities
towards pH correlation to ACN optical properties may need to be added here as well.
Response: The paragraph 3 has been elaborated:
A more recent study on fish freshness monitoring through optical methods was reported by
Moradi et al.
15
using nanofiber bacterial cellulose with ACN. However, this method requires a
relatively long analytical time as the pH measurement could not be conducted in situ. Chen et al.
(2020)
6
has developed a sensitive novel film prepared from starch polyvinyl alcohol and starch
polyvinyl alcohol glycerol. The study used curcumin from turmeric and anthocyanin from purple
sweet potatoes. The results showed that the mixture of curcumin and ACN improved the stability
than that of the individual active substances. As the consequence, the sensor could be employed
to detect volatile ammonia as the fish freshness indicator.
Comment: The methodology shows a sufficient description a to give reader a good
understanding on how this study is conducted. It is suggested that the authors may add
process flow/illustration to complete the overall picture on steps and its mechanism.
Response: The steps have been added Methods:
Study Design
The first step in sensor fabrication was the extraction of anthocyanin from Ruellia tuberosa L. The
extracted anthocyanins were then mixed with pectin solution and printed proportionally as an
optical pH sensor. The optical pH sensor was then characterized and the optimized and then
applied to monitor the freshness of tilapia. The image below is a schematic diagram
summarizing research procedures conducted in this work.
[Figure]
Comment: The morphology of ACN/PC membrane does not seem like a crack. It seems to
have a wavy layer of membrane that might be the contributed to the adhesion/stress
tension or air gap of the ACN/PC compared to PC alone. Is there any study on different
ration of CAN added to this PC, or is it already optimized? The caption should be more
detailed.
Response: The ratio of ACN has been optimized based on the sensitivity and R
2
, see Table 1
and Figure 8. The description for SEM images analysis has been revised per suggestion.
Comment: The color change mechanism is important to be introduced earlier in the
Page 18 of 25
F1000Research 2021, 10:422 Last updated: 11 AUG 2021
introduction section and can be help with illustration. How different phenolic derivatives
change this CAN, and which phenolic derivatives took place in this reaction? The authors
may put or add this point to support the color change mechanism towards fish freshness
from the finding.
Response: The anthocyanin structure under different pHs has been added in the
manuscript as suggested (see Figure 7).
[Figure]
Comment: The pectin is a membrane that hold the ACN dye to improve the sensitivities.
From Fig 4, the importance of having optimum load/weight of pectin is important the
membrane with less surface tension, and this is the reason of having crack or wavy like
membrane. It is very important optimum ratio of CAN/PC to have smooth ACN/PC
membrane in this study.
Response: We have optimized the PC weight and the optimum was reached for 0.1% PC to
find optimum sensitivity. The membrane with 0.1% w/v pectin has a flatter surface thus
making it as the most suitable optical sensor. SEM characterization was carried out on the
optimum pectin weight. The wavy like surface structure was probably due to the addition of
anthocyanin.
Added as a recommendation in conclusion:
More studies indeed need carried out to obtain smooth surface morphology to improve the
optical sensor performance.
Due to the limited features in this comment column, we have uploaded our full response
through this link.
Competing Interests: None
Reviewer Report 04 June 2021
https://doi.org/10.5256/f1000research.56160.r86206
© 2021 Alva S. This is an open access peer review report distributed under the terms of the Creative Commons
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the
original work is properly cited.
Sagir Alva
Department of Mechanical Engineering, Faculty of Engineering, Universitas Mercu Buana, Jakarta,
Indonesia
After I read and reviewed this article, I found the theme of this article quite interesting. However,
unfortunately, there are shortcomings in this article which make it unfit for indexing. Therefore, I
suggest a Not Approval status for this article. However, it can be improved in the revision with the
Page 19 of 25
F1000Research 2021, 10:422 Last updated: 11 AUG 2021
following comments:
1. It is true, when fish begin to undergo a process of decomposition, in addition to producing H
+
,
ammonia is also produced. In the first paragraph, the authors only compared it with ammonia-ISE,
where basically, the concept of measuring ammonia-ISE is an indirect measurement of ammonia
based on the dissociation of ammonia in solution to form NH
4
+
. So naturally not all ammonia will
be detected. However, there are actually a lot of research on ammonia optical sensors. In other
words, the ammonia optical sensor is nothing new. So there needs to be an explanation added to
the introduction why choosing an optical pH sensor in detecting the freshness of fish compared to
an ammonia optical sensor. What are the advantages of an optical pH sensor compared to an
optical ammonia sensor?
2. At the end of the first paragraph, you stated that measuring pH using an optical sensor might
be good for samples that have interfering ions. With fish, what ions are supposed to be can
interfere with the pH-ISE sensor, so you end up choosing the optical pH sensor over the pH-ISE
sensor? An explanation of this needs to be added in the introduction section.
3. Basically, a lot of plants and fruits also have ACN, and here you have also given examples such
as blackberries. But why in this study have you focused on the Ruellia flower? Instead, you can also
use ACN from blackberries immobilized using Pectin. What are the advantages of ACN from Ruellia
compared to other plants? It is worth mentioning in the introduction the reasons for this.
4. The use of a hydrogel membrane will indeed facilitate the diffusion of the analyte. However, the
hydrogel membrane has serious problems such as easy to swell and break, so that the dye used
can be leached and the sensor life time is decreased. There needs to be some clarification on this.
In addition, there needs to be additional experimental data on the % swelling index of the pectin
membrane used.
5. In optical sensor, leaching study is an important thing to do. However, in this article there are
no leaching study data, so it is necessary to add experimental data for leaching study testing.
6. There are several natural hydrogel polymers. It is necessary to add reasons why choose Pectin
over other natural hydrogel polymers. What are the advantages of pectin over other natural
hydrogel polymers?
7. On page 7 and the beginning of the first paragraph, there is the sentence: “The constructed
optical pH biosensor based on the ACN derived from R. tuberosa L flower has hydrogel
characteristics.” - It need clarification, is this really an optical biosensor? Because here I don't see
any use of enzymes, peptides, micro-organisms etc.
8. On page 7 it is stated that the colour change is caused by a structural transformation of the
ACN. It is necessary to add pictures of the changes in the chemical structure of ACN at various pH
variations, such as acidic, neutral and basic.
9. Still from page 7, you stated that one of the factors that caused the change in ACN colour was
caused by light. You need to clarify, how do you control the light intensity during the test period,
so that the colour of the ACN remains stable and how long can the light change the colour of the
ACN?
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F1000Research 2021, 10:422 Last updated: 11 AUG 2021
10. In the ACN variation data, the resulting absorbance will also decrease with the lower ACN
concentration, and in the end you use a concentration of 0.025 mg/L as the optimum
concentration of ACN. What if the concentration of the ACN is less than 0.025 mg/L? Is ACN still
able to respond to changes in pH or not able to respond to changes in pH? Additional data are
needed for testing less than 0.025 mg/L.
11. In sensor development, validation testing is very important to ensure that the fabricated
sensor performs at least the same as standard test equipment. Here, I don't see that. There needs
to be additional validation data with standard methods to test the freshness of fish based on pH
changes.
Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
No
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Yes
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Yes
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: My specialty is the synthesis and characterization of materials such as
polymers for the development of chemical sensors/biosensors.
I confirm that I have read this submission and believe that I have an appropriate level of
expertise to state that I do not consider it to be of an acceptable scientific standard, for
reasons outlined above.
Author Response 09 Jul 2021
Nazaruddin ., Universitas Syiah Kuala, Banda Aceh, Indonesia
Comment: It is true, when fish begin to undergo a process of decomposition, in addition to
producing H
+
, ammonia is also produced. In the first paragraph, the authors only compared
it with ammonia-ISE, where basically, the concept of measuring ammonia-ISE is an indirect
measurement of ammonia based on the dissociation of ammonia in solution to form NH
4+
.
Page 21 of 25
F1000Research 2021, 10:422 Last updated: 11 AUG 2021
So naturally not all ammonia will be detected. However, there are actually a lot of research
on ammonia optical sensors. In other words, the ammonia optical sensor is nothing new. So
there needs to be an explanation added to the introduction why choosing an optical pH
sensor in detecting the freshness of fish compared to an ammonia optical sensor. What are
the advantages of an optical pH sensor compared to an optical ammonia sensor?
Response:
The literature on the development of the NH3 optical biosensor was developed by
Dan-Feng Lu and Zhi-mei Qi in 2019 using bromothymol blue and a porous glass
membrane. This sensor can only work at low concentrations of ammonia.
○
Another ammonia sensor has also been developed by Maximilian Maierhofer et al.
(2020), who fabricated the sensor using fluorescence properties of aza-BODIPY dyes
with a response time of 390 seconds.
○
Detection of ammonia as a total volatile basic nitrogen (TVB-N) to determine fish
spoilage requires a sample destruction process (Nathan Wells et al.(2019), Talanta
194: 830–836). Then, the standard curve was obtained from measuring the
absorbance of the trimethylamine (TMA) compound that produces ammonia through
a complicated procedure. On the other hand, this method was also based on pH
measurements. So it can be concluded that ammonia is also correlated with changes
in pH to determine the freshness of fish. The same concept has also been previously
reported by T. Werner et al. (1995) Analyst 120 1627–1631 where the determination of
ammonia was based on measuring pH using an ion-pair indicator. Therefore, the
detection of fish freshness through pH measurements is more representative of the
actual condition of in-situ tests.
○
An explanation of the ammonia optical sensor and its drawbacks for determining fish
freshness has been described in the introduction.
○
Comment: At the end of the first paragraph, you stated that measuring pH using an optical
sensor might be good for samples that have interfering ions. With fish, what ions are
supposed to be can interfere with the pH-ISE sensor, so you end up choosing the optical pH
sensor over the pH-ISE sensor? An explanation of this needs to be added in the introduction
section.
Response: Literature reported ISE H
+
response is strongly affected by alkaline ions has
been added in the Introduction.
Comment: Basically, a lot of plants and fruits also have ACN, and here you have also given
examples such as blackberries. But why in this study have you focused on the Ruellia
flower? Instead, you can also use ACN from blackberries immobilized using Pectin. What are
the advantages of ACN from Ruellia compared to other plants? It is worth mentioning in the
introduction the reasons for this.
Response: Mostly, coloured plants contain anthocyanins, including blackberries.
Anthocyanins from blackberries can also be used as pH-sensitive active ingredients to
develop optical pH sensors. On the other hand, sources of anthocyanins from blackberries
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are difficult to obtain in our area. In this study, Ruellia anthocyanins were used as a sensitive
pH compound for optical pH sensor development because the flowers are easy to obtain. In
addition, based on a preliminary study on the sensitivity of the anthocyanin at various pHs,
we found that the anthocyanin has a great potential to be further applied in developing
optical pH sensor.
Comment: The use of a hydrogel membrane will indeed facilitate the diffusion of the
analyte. However, the hydrogel membrane has serious problems such as easy to swell and
break, so that the dye used can be leached and the sensor life time is decreased. There
needs to be some clarification on this. In addition, there needs to be additional
experimental data on the % swelling index of the pectin membrane used.
Response: Firstly, the membrane use as optical pH sensor is not applied by immersion into
aqueous samples therefore swelling index is not relevant. Secondly, there have been
extensive research pertaining to the swelling profile of pectin, of which are Fong H. WEH et
al. (2014) Lat. Am. J. Pharm. 33(3): 420-31 and Naziha Chirani et al. 2015. Journal of
Biomedical Sciences. Vol. 4 No. 2:13. P 1-23.
Below is swelling index of pectin in different media based on the reported study.
[Figure]
Comment: In optical sensor, leaching study is an important thing to do. However, in this
article there are no leaching study data, so it is necessary to add experimental data for
leaching study testing.
Response: In our opinion, not all leaching tests need to be carried out in sensor or
biosensor manufacturing studies. It depends on the sensor application. In this study, we did
not immerse the sensor in the sample. The sensor is placed directly on the surface of the
fish, and then the colour changes are measured. For a liquid sample, only a small amount of
sample dropped onto the sensor surface. The sensor produced is a disposal sensor.
Comment: There are several natural hydrogel polymers. It is necessary to add reasons why
choose Pectin over other natural hydrogel polymers. What are the advantages of pectin
over other natural hydrogel polymers?
Response: Pectin was chosen because of:
Its non-toxicity; because the application is for a foodstuff, the sensor should not be
toxic.
1.
Its ability in forming membrane structure.
2.
Transparent and homogenous.
3.
In the case of optical pH sensor for fish freshness monitoring, other studies have
reported chitosan, starch, and cellulosic materials; while pectin is scarcely reported.
Hence, the use of pectine is a novelty.
4.
Those characteristics have been added in the last paragraph of introduction.
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Comment: On page 7 and the beginning of the first paragraph, there is the sentence: “The
constructed optical pH biosensor based on the ACN derived from R. tuberosa L flower has
hydrogel characteristics.” - It need clarification, is this really an optical biosensor? Because
here I don't see any use of enzymes, peptides, micro-organisms etc.
Response: It is a sensor not as a biosensor. Has been modified: “biosensor” to “sensor”
Comment: On page 7 it is stated that the colour change is caused by a structural
transformation of the ACN. It is necessary to add pictures of the changes in the chemical
structure of ACN at various pH variations, such as acidic, neutral and basic.
Response: Has been added, see figure 7 [Figure].
Comment: Still from page 7, you stated that one of the factors that caused the change in
ACN colour was caused by light. You need to clarify, how do you control the light intensity
during the test period, so that the colour of the ACN remains stable and how long can the
light change the colour of the ACN?
Response: The sensor has been made through a storage process in a dark condition and a
temperature of 4
o
C. At the time of measurement, the sensor is also kept in the dark and
needs a short time of exposure to light during the measurement process. We predict no
significant colour change. In addition from our preliminary experiment, immobilized
anthocyanins on the pectin matrix have good stability.
Comment: In the ACN variation data, the resulting absorbance will also decrease with the
lower ACN concentration, and in the end you use a concentration of 0.025 mg/L as the
optimum concentration of ACN. What if the concentration of the ACN is less than 0.025
mg/L? Is ACN still able to respond to changes in pH or not able to respond to changes in
pH? Additional data are needed for testing less than 0.025 mg/L.
Response: The effect of anthocyanin concentration is not significantly different on sensor
sensitivity and linear range. Anthocyanin concentrations less than 0.025 mg/L are predicted
still to respond to pH changes. Due to the intensity of the colour decreases, the sensitivity
will also decrease. Thus, the determination of sensitivity for anthocyanin concentrations
lower than 0.025 mg/L was not determined.
Comment: In sensor development, validation testing is very important to ensure that the
fabricated sensor performs at least the same as standard test equipment. Here, I don't see
that. There needs to be additional validation data with standard methods to test the
freshness of fish based on pH changes.
Response: We have validated the optical sensor method using H
+
ion-selective electrodes.
However, we do not report it. In this paper, we focus more on how the pH changes in fish
stored at room temperature and 4
o
C. The following are the results of the validation of
measurements carried out on fish measured using an optical pH sensor with H
+
ISE.
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[Table]
From the results obtained that the ISE measurement is influenced by temperature (as also
suggested by other reported studies) so that the results obtained are different from the
optical pH sensor.
Due to the limited features available in this comment column, we choose to upload our full
response in an accessible link. Please find it through this link.
Competing Interests: None
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