fish quality evaluation using quality index method

Fish Quality Evaluation Using Quality Index Method (QIM), Correlating with Physical, Chemical and Bacteriological Changes

During the Ice-Storage Period

National Taiwan Ocean University

Department of Food Science

Seminar

Seminar Instructor:

Yeuk-Chuen Liu, Ph.D

Hong-Ting Victor Lin, Ph.D

Advisor:

Hsiao Hsin-I, Ph.D

Presented by:

Nodali Ndraha

10432071

Outline

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‐ Introduction

‐ Fish freshness determination using quality index method (QIM)

‐ Shelf-life estimation of the fish, correlating with physical, chemical and bacteriological changes during the ice-storage period

‐ Summary and conclusion

The objectives

To evaluate the current status of fish quality using Quality Index Method (QIM), correlating with physical, chemical and bacteriological changes that occurred during the storage period

To estimate product shelf-life of fish

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Problems and urgently

• Fish is perishable (5 – 20 days)

• Freshness and change in sensory attributes are critical parameters during fish chain

• Fish is transported all over

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Postharvest Transport Processing

TransportWarehousingTransport

Retail

Cold Chain in Food Sector

Source: 2015 ITA Cold Chain Top Markets Report

Sensory Evaluation

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Introduction of Quality Index Method (QIM)

• Quality Index Method (QIM) developed by the Tasmanian Food Research Unit (TFRU) to determine the fish freshness and quality.

• A descriptive, fast and simple method to evaluate the freshness of seafood.

• Estimate the remaining shelf-life of the fish.

• Based on significant sensory parameters for raw fish and a scoring system from 0 to 3 demerit points.

• Evaluates that change most significantly, in each species, during degradation processes

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Developing quality index

Pre-Observation

Development of the QIM scheme and training of a QIM

panel

Validation of QIM scheme

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Figure 1. Linear regression between the quality index and storage time of fish

(Martinsdottir et al., 2003)


Pre-Observation


panel


2 or 3 experts in sensory evaluation of fish observe

fish that have been stored for different periods in ice.

All changes occurring in appearance, odor and

texture during storage are listed in a preliminary

scheme

8(Martinsdottir et al., 2003)


Pre-Observation

Development of the QIM scheme and training of a

QIM panel






scheme

3–4 different groups of fish, stored different periods

of time in ice are observed. First, preliminary

scheme is explained to the panelists, fish being

stored for different periods

9(Martinsdottir et al., 2003)


Pre-Observation


panel






scheme

3–4 different groups of fish, stored different periods

of time in ice are observed. First, preliminary

scheme is explained to the panelists, fish being

stored for different periods

Shelf-life study, at least every third day, The shelf

life study should be repeated to observe if the same

slope was found between the Quality Index and

storage time in ice10(Martinsdottir et al., 2003)

Table 1a. Quality Index Method (QIM) protocol for ice stored gutted Amazonian Pintado (Pseudoplatystoma fasciatum

Leiarius marmoratus) (Lanzarin et al., 2016)

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Table 1b. QIM protocol for gutted ice-stored tambatinga (Colossoma macropomum Piaractus brachypomum) (Ritter et

al., 2016)

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Fish freshness determination

• The correlation between the quality index (QI) and storage time of fish

• The correlation between the quality attributes of fish and storage time

• Quality attributes of fish that most changes

• Quality attributes of fish remained stable

• Variable importance in the projection (VIP)

• Principal Component Analysis of quality parameters

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(Billar dos Santos et al., 2014)(Borges et al., 2014)

1. The correlation between the quality index (QI) and storage time of fish

The QI tends to increase linearly with increasing storage time 14

TambacuAcoupa weakfish

Figure 2. Linear regression between the quality index and storage time of fish (Billar dos Santos et al., 2014;

Borges et al., 2014)

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(Lanzarin et al., 2016)

The QI tends to increase linearly with increasing storage time


(Ritter et al., 2016)

Amazonian Pintado Tambatinga

Figure 3. Linear regression between the quality index and storage time of fish (Lanzarin et al., 2016; Ritter et al.,

2016)

(Agüeria et al., 2015) (Gutiérrez et al., 2015)


The QI tends to increase linearly with increasing storage time

- An estimate can be calculated for the remaining shelf-life 16

Red tilapiaCommon carp

Figure 4. Linear regression between the quality index and storage time of fish (Agüeria et al., 2015; Gutiérrez et

al., 2015)

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Figure 5. Changes occurring in Acoupa weakfish appearance during 16 days of iced storage. a: Fresh gutted fish; b, f

and j: details of eyes shape, cornea and pupil; c, g and k: gills color and mucus; d, h and l: peritoneal membrane, kidney

color and blood vessels; e, i and m: caudal fin (Billar dos Santos et al., 2014)

Figure 6. Mean of demerit points for the quality

attributes for the gutted ice-stored Amazonian

Pintado; A). overall appearance; B). eyes; C). gills;

D). abdomen; and E). fins (Lanzarin et al., 2016)

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2. The correlation between the quality attributes of fish and storage time

Fins

AbdomenGills

Overall Appearance Eyes

The quality

attributes

tends to

increase with

increasing

storage time

Figure 7. The quality attributes that most changes during storage for the gutted ice-stored Amazonian Pintado and

tambatinga (Lanzarin et al., 2016; Ritter et al., 2016)

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3. Quality attributes of fish that most changes

Amazonian Pintado Tambatinga

Fins

Storage time (days)Storage time (days)

Qu

alit

y I

nd

ex

Qu

alit

y I

nd

ex

(Lanzarin et al., 2016) (Ritter et al., 2016)

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3. Quality attributes of fish that most changes


Gills

Odor

Abdomen

Odor

Overall appearance

Eyes

Off-odor generally is the primary cause of reduction of acceptability of fish. The significant

change of odor during storage may be due to large amounts of non-protein nitrogen, high content

of fat and autolytic enzymes in the fish tissues (Ritter et al., 2016)

Figure 8. Mean of demerit points for the quality attributes for gutted ice-stored tambatinga (Ritter et al., 2016)

Color

Color

Figure 9. Mean of demerit points for the quality attributes for the gutted ice-stored Amazonian

Pintado (Pseudoplatystoma fasciatum x Leiarius marmoratus); A). overall appearance; B). eyes; C).

gills; D). abdomen; and E). fins (Lanzarin et al., 2016)21

4. Quality attributes of fish remained stable


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A B

Figure 10. The changes of quality attributes of Amazonian Pintado fish during storage, (A) Gills; (B) abdomen

(Lanzarin et al., 2016)

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Flesh firmness Eye

intactness

Abdomen colorHead color

Figure 11. The changes of quality attributes of tambacu fish during storage, (A) general appearance; (B)

eyes; (C) head; (D) abdomen (Borges et al., 2014)


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Figure 12. Mean of demerit points for the quality

attributes for the gutted ice-stored tambatinga : (A)

Overall aspect; (B) eyes; (C) gills; (D) abdomen; and (E)

Fins. (Ritter et al., 2014)


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Godet

Eyes shape

Figure 13. The changes of quality attributes of tambacu fish during storage, (A) general appearance; (B)

eyes; (C) head; (D) abdomen (Borges et al., 2014)


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5. Variable importance in the projection (VIP)

Figure 14. Values of variable importance in the projection (VIP) of the Quality Index Method (MIQ)

parameters developed for ice stored gutted Amazonian Pintado (Pseudoplatystoma fasciatum (Leiarius

marmoratus) at 95% reliability (Lanzarin et al., 2016)


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flesh firmness, spot on pupil, eye

shape, gill color and odor,

abdominal color and odor and

pelvic fin moisture and color

Figure 15. Values of VIP of the QIM parameters developed for ice-stored pacu (Piaractus mesopotamicus),

with a 95% regression confidence. (Blue = descriptor terms that contribute positively to QIM; white =

descriptor terms low significant contribution to QIM scheme) (Borges et al., 2013)


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Eye shape, lateral line, gill color,

skin glossiness, white spot on pupil,

iris color, flesh firmness, gill odor

and abdomen, eyeball integrity and

abdomen color

Figure 16. Values of VIP of the QIM parameters developed for ice-stored tambacu, with a 95% regression

confidence. (Blue = descriptor terms that contribute positively to QIM; white = descriptor terms low

significant contribution to QIM scheme) (Borges et al., 2014)

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Figure 17. Principal Component Analysis of the hybrid quality parameters of gutted ice-stored tambacu (A): A1-

A10 represents the parameters of the quality index. BHAM = heterotrophic aerobic mesophilic bacteria, BHAP =

heterotrophic aerobic psychrotrophic bacteria; pH = hydrogen potential, TVB-N = total volatile bases nitrogen,

TBARS = thiobarbituric acid reactive substances (Borges et al., 2014)

A1-A13

BHAM

BHAP

pH

TVB-N

TBARS

Resilience,

Springiness,

Hardness and

Instrumental

glossiness

6. Principal Component Analysis of quality parameters

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6. Principal Component Analysis of quality parameters

Figure 18. Principal Component Analysis of the hybrid quality parameters of gutted ice-stored tambacu. DI =

day 1, DIV = day 4, DVII = day 7, DXI = day 11, DXIII = day 13, DXVI = day 16 (Borges et al., 2014)

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Figure 19. Principal Component Analysis of the hybrid quality parameters of gutted ice-stored tambatinga (A):

A1-A10 represents the parameters of the quality index. BHAM = heterotrophic aerobic mesophilic bacteria,

BHAP = heterotrophic aerobic psychrotrophic bacteria; pH = hydrogen potential, TVB-N = total volatile bases

nitrogen, TBARS = thiobarbituric acid reactive substances (Ritter et al., 2016)

A1-A10

BHAM

BHAP

pH

TVB-N

TBARS

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Figure 20. Principal Component Analysis of the hybrid quality parameters of gutted ice-stored tambatinga. 1 =

day 1, 5 = day 5, 9 = day 9, 12 = day 12, 16 = day 16, 19 = day 19, 23 = day 23, 26 = day 26 and 30 = day 30


Estimation of the fish shelf-life

Shelf life: number of days that whole fish can be stored in ice until it becomes unfit for human consumption.

Bacterial activity

• Heterotrophic aerobic mesophilic counts (BHAM)

• Heterotrophic aerobic psychrotrophic (BHAP)

• FAO/ICMSF (Food and Agriculture Organization of the United Nations/ International Commission on Microbiological Specifications for Foods) 107 CFU

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Estimation of the fish shelf-life

Chemical activity

• Total volatile basic nitrogen (TVB-N)

Critical limits of 25, level of 35-40 mg TVB-N/100g of muscle is the limit of acceptability.

• Hydrogen potential (pH)

• Thiobarbituric acid reactive substances (TBARS), formed as a byproduct of lipid peroxidation (i.e. as degradation products of fats).

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Heterotrophic aerobic

psychrotrophic

bacteria (BHAP)

Heterotrophic aerobic

mesophilic counts

(BHAM)

Total volatile basic

nitrogen (TVB-N)

Figure 21. Linear regression between the variables BHAP, BHAM, (TVB-N) and storage time of ice stored gutted

Amazonian Pintado (Lanzarin et al., 2016)

FAO/ICMSF

11

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Figure 22. Linear regression for the variables heterotrophic aerobic mesophilic bacteria (BHAM), heterotrophic

aerobic psychrotrophic bacteria (BHAP), hydrogen potential (pH), total volatile bases nitrogen (TVB-N),

thiobarbituric acid reactive substances (TBARS) and ice storage time of the gutted hybrid tambatinga (Ritter et

al., 2016)

BHAP

BHAM

TVB-N

pH

TBARS

FAO/ICMSF

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Figure 23. Principal Component Analysis of the hybrid quality parameters of gutted ice-stored tambatinga. 1 =

day 1, 5 = day 5, 9 = day 9, 12 = day 12, 16 = day 16, 19 = day 19, 23 = day 23, 26 = day 26 and 30 = day 30


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Figure 24. Variation of pH, aerobic mesophilic heterotrophic bacterial count (AMHBC), aerobic psychrotrophic

heterotrophic bacterial count (APHBC) over gutted, ice-stored pacu's (Piaractus mesopotamicus) shelf life

(Borges et al., 2013).

FAO/ICMSF

The longer the ice storage, the greater the microbiological and physicochemical activities leading to changes that directly affect the sensory characteristics of fish, thus accumulating more demerit points (Agüeria et al., 2015; Billar dos Santos et al., 2014; Borges et al., 2014; Gutiérrez et al., 2015; Lanzarin et al., 2016; Ritter et al., 2016)

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Table 2. QIM schemes built between 2012 and 2016 for fish. The QIM references older than 2012, see Table 1 at Barbosa & Vaz-Pires (2004), Table 1 at Sant’Ana et al. (2011) and Table 1 at Bernardi et al. (2013)

Country Species Product Storage condition Quality IndexEstimated

shelf lifeReferences

Brazil Tambatinga (Colossoma

macropomum x Piaractus

brachypomum)

Gutted 0±0.5°C 0 - 18 10 d (Ritter et al., 2016)

Brazil Amazonian Pintado

(Pseudoplatystoma fasciatum x

Leiarius marmoratus)

Gutted 0±0.5°C 0 - 18 12 d (Lanzarin et al.,

2016)

Argentina Common carp (Cyprinus carpio) Gutted 2±1°C 0 – 19 18 d (Agüeria et al.,

2015)

Columbia Red tilapia (Oreochromis ssp) Gutted

Ungutted

4°C 0 – 21

0 – 29

11 d

9 d

(Gutiérrez et al.,

2015)

Spain Greenland Halibut (Reinhardtius

hippoglossoides)

Raw, whole 4±1°C 0 – 24 5 d (López-García et

al., 2014)

Iceland Tilapia (Oreochromis niloticus) Farmed, 1 and −1◦C 0 – 17 19 d (Cyprian et al.,

2014)

Brazil Tambacu (Colossoma

macropomum × Piaractus

mesopotamicus)

Gutted 0.5±0.1°C 0 – 26 11 d (Borges et al.,

2014)

Brazil Weakfish (Cynoscion acoupa) Gutted 0 – 1°C 0 – 23 14 d (Billar dos Santos

et al., 2014)

Argentina Anchovy

(Engraulis anchoita)

Raw, wholed 0 – 4°C 0 – 28 10 d (Massa et al., 2012)

Croatia Bogue (Boops boops) Ungutted,

cooked, Farmed

Non-farmed

1±1°C 0 - 20 17 d

12 d

(Bogdanović et al.,

2012)

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Conclusion

• The quality of fish gradually deteriorated with time during storage evaluated by QIM scheme.

• The quality parameters could be deteriorated quickly or slowly, depending on microbiological and chemical activities.

• The combination of microbiological, physicochemical, and sensory analysis provides a more concise and relevant results to assess the fish quality.

• Microbiology activities on fish during storage could be and indicate of shelf life and highly affected the fish quality.

• The changes on pH, TVB-N, and TBARs has occurred on fish during storage, these change could be an indicate for microbiology and chemical activity.

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NODALI NDRAHA

Student

National Taiwan Ocean University

M: +886 905 473 631

E: [email protected]

mailto:[email protected]

fish quality evaluation using quality index method

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