植基於EEM技術的魚鮮度指標

國

立

交

通

大

學

生醫工程研究所

碩

士

論

文

植基於 EEM 技術的魚鮮度指標

Evaluation index for fish freshness based on EEM analysis

研 究 生：吳繼武

指導教授：蕭子健 博士

植基於 EEM 技術的魚鮮度指標

Evaluation index for fish freshness based on EEM analysis

研 究 生：吳繼武 Student: Chi-Wu Wu

指導教授：蕭子健 Advisor: Tzu-Chien Hsiao

國 立 交 通 大 學

生醫工程所

碩 士 論 文

A Thesis

Submitted to Institute of Biomedical Engineering College of Computer Science

National Chiao Tung University in partial Fulfillment of the Requirements

for the Degree of Master

in

Biomedical Engineering

July 2012

Hsinchu, Taiwan, Republic of China

i

植基於 EEM 技術的魚鮮度指標

研究生：吳繼武

指導教授：蕭子健

國立交通大學

生醫工程研究所

摘 要

本篇論文主要是利用光學螢光量測來探討並分析魚肉之新鮮度並找出光學的指標， 期許對於食品及工業上希望能有所貢獻與發展。相較於傳統新鮮度檢測方法，化學性判 讀時間過長、易破壞魚體而造成漁業及食品業的損失，此種光學方法具有非侵入式檢測 特性，並期望能達到快速檢測之目的。實驗選用兩種魚類，八隻澎湖縣養殖場的海鱺， 平均重量約為 5±1.0 公斤，以及八隻新竹縣活魚餐廳的紅魽，平均重量約 1±0.2 公斤。 檢測部分與方式係將活魚處理切成相同大小的魚肚及魚背，利用自行架設的螢光光譜量 測系統來進行實驗，觀察死亡後 24 小時內魚體光譜的時序變化。同一時間亦進行魚新 鮮度的傳統檢測法，利用商用高效能液相層析儀(HPLC)來進行定性及定量分析，以獲得 傳統方法的新鮮度標準 K 值作為魚肉新鮮度標準。由螢光的激發放射矩陣光譜之結果顯 示，在激發光 330~360 nm、放射光 400~500 nm 之間有明顯的螢光訊號。此訊號的最大 值位在螢光波長 470 nm 及 430 nm 處，與菸鹼醯胺腺嘌呤二核苷酸(NADH)及第一型和 第五型膠原蛋白在激發光 330~360 nm 所產生的螢光光譜位置雷同。而根據正規化處理 而獲得光學指數數值，以變異數分析此數值與死亡後 24 小時之關聯性，發現此數值隨

ii 著死亡後時間逐漸地降低，且具顯著性差異(p value<0.05)，這表示可將此一數值視為另 外一種新鮮度指標。由 HPLC 結果顯示，每隻紅魽的代謝變化速度皆不相同，推測原因 可能是不同魚體差異性造成、環境及處理過程的差異性，因此會影響 K 值變化，推測也 會影響魚體裡某些螢光成分的代謝。但整體結果來說光學指標與 K 值的數值大小大致呈 負相關。而光學指標的高低結果也代表著魚死後肌肉所進行的僵直化及嫩化效應所造成 的。是故，以目前的研究結果，此光學指標是可以用來判斷剛死亡的魚肉及生魚片的品 質。

iii

Evaluation index for fish freshness based on EEM analysis

Student: Chi-Wu Wu

Advisors: Tzu-Chien Hsiao

Institute of Biomedical Engineering

National Chiao Tung University

ABSTRACT

In this study, the autofluorescence emitted from fish tissue is measured as an optical

evaluation index for freshness identification. Because of the time-consuming and invasive

nature of the traditional method, it causes property loss in the fishery and food industries. A

quick and noninvasive method is necessary. The result can be applied to the fishery and food

industries for quality control. With the quickness of the fluorescence technique, it could

improve the procedure of detection. The species chosen are eight cobias, which weigh 5±1.0

kilograms, from a marine products farm in Penghu and eight Seriola dumerili, which weigh

1±0.2 kilograms, from a seafood restaurant near Hsinchu Science Park. The fish were sliced at

the abdomen and dorsum. Then, the fluorescence from the tissue was measured within 24

hours after the fish had died by using Y-type fiber. Meanwhile, traditional detection was

employed by extracting ATP degradation products and calculating K value to confirm fish

freshness. From the results of the Excitation-Emission matrix (EEM), the two peaks in

excitation wavelength were 330 to 360 nm, and emission wavelengths were 400 to 500 nm.

The two peaks were at the 470 nm and 430 nm emission wavelengths, respectively. It has

been shown that the fluorescence indicates that the major contributors are from Nicotinamide

adenine dinucleotide (NADH), collagen type I, and collagen type V. Analysis of variance

(ANOVA) showed that the intensity of fluorescence decreases with refrigeration time (p value

iv

different fish species. It is known that with different treatments and growing environments of

fish can affect the K value and even the fluorophores in fish tissue. On the whole, the optical

index is negatively correlated to the K value index. The value of the optical index is that it can

measure the process of rigor mortis and the tenderization of fish muscle. The optical index

v

Acknowledgement

This study was completed with the support of many people. My advisor, Dr. Tzu-Chien

Hsiao, gave me many suggestions for the experiment and full support to participate in the

top-tier SPIE-BiOS conference in San Francisco. Under his professional instruction, I always

kept my focus on the right track of research. Dr. Shou-Chia Chu laid a good foundation for

this study, and the chefs in the restaurant helped me slaughter and gut fresh fish. Also, I really

appreciate all the lab team members’ support. They gave me lots of suggestions and also

helped me to finish the fish experiment. Without them, I could not have finished this thesis

smoothly. In addition, I appreciate all the defense committee members for their attention to

my oral defense. These professionals contributed to my thought process so that I could

produce a more informative thesis. Finally, I appreciate my parents, Huan-Ching Wu and

Mei-Yu Chou; they encouraged me to continually study and rendered some economic

assistance.

My VBM Lab is full of challenges and brings me happiness every day. My team

members are outstanding. It has been an honor to work with them, not only to due to their

partnership in our high-end research, but also due to the positive ways that they have affected

vi

Table of Content

摘 要 ... i ABSTRACT ... iii Acknowledgement ... v Table of Content ... vi

List of Figures ... viii

List of Tables ... ix

I. Introduction ... 1

1.1. Background ... 1

1.1.1. Fishery issues in Taiwan ... 1

1.1.2. Biochemistry metabolism of fish tissue ... 2

1.1.3. The definition of K value... 4

1.1.4. The history of developing freshness detection ... 4

1.2. Literature review... 6

1.2.1. The principle of fluorescence technology ... 6

1.2.2. Fluorescence measurement of freshness... 7

1.3. Objective ... 9

II. Material and Method ... 11

2.1. Experiment flow chart ... 11

2.2. Fish subject ... 12

2.2.1. Cobias ... 12

2.2.2. Seriola dumerili ... 12

2.3. Pretreatment for live fish ... 12

2.4. Optical fluorescence measurement ... 14

2.4.1. Measurement system ... 14

2.4.2. Measurement process ... 16

2.4.3. Measurement program and related parameters ... 16

2.4. Chemistry detection method for freshness ... 17

2.4.1 Chemistry reagents and instruments ... 18

2.4.1.1 Instruments ... 18

2.4.1.2 Chemicals and reagents ... 18

2.4.2 Chemistry method procedure ... 19

2.4.3 Recovery of extraction process... 20

2.4.4 HPLC analysis ... 20

2.4.5 K value Calculation ... 22

2.5. Data Analysis ... 22

2.5.1. Excitation-Emission Matrix ... 22

2.5.2. Optical index ... 22

2.5.3. Time variant analysis for optical index ... 23

2.5.4. The relationship between optical index and K value ... 24

III. Experiment Result ... 25

3.1. Optical fluorescence results ... 25

3.1.1. The results for cobias ... 25

3.1.2. The results for Seriola dumerili ... 27

3.2. Chemical results for Seriola dumerili by HPLC ... 29

vii

3.2.2. The results by HPLC ... 30

3.2.3. The results of Seriola dumerili by HPLC ... 32

3.2.4. The K value of eight Seriola dumerili ... 34

3.3. The correlation between optical index and K value ... 35

IV. Discussion ... 38

4.1 The fluorophores of EEM spectra ... 38

4.2 The optical index G ... 39

4.3 The slaughter method effect for spectrum ... 40

4.4 The changes of other fluorophores in fish tissue within 24 hours refrigeration ... 41

4.5 The white and red fish meat ... 43

4.6 The problems in this study ... 44

4.7 To develop an portable detector for fish freshness ... 44

4.7.1. The potential of nitrogen laser as excitation power ... 44

4.7.2. The usage and problem of G index for freshness ... 45

V. Conclusion ... 46

5.1 The optical index represents ... 46

5.2 The application of the index ... 46

VI. Future Work ... 48

VII. Reference ... 49

Appendix A ... 52

viii

List of Figures

Figure 1 The electron energy level and energy conversion between different states ... 7

Figure 2 Measurement system accompanied by the fiber ... 10

Figure 3 The optical and chemical experiment flow chart ... 11

Figure 4 Before and after pretreatment of live fish by chef ... 14

Figure 5 The Y-type measurement system ... 15

Figure 6 The front panel of measurement program ... 17

Figure 7 Abdomen of cobias in at different time point ... 26

Figure 8 Summary the fluorescence ratio of eight cobias ... 27

Figure 9 Abdomen of Seriola dumerili in at different time point ... 28

Figure 10 Summary the fluorescence ratio of eight Seriola dumerrili ... 29

Figure 11 The standards (ATP, ADP, AMP, IMP, Hx, HxR) separated by HPLC ... 30

Figure 12 The checking measuring curve of six ATP degradation products ... 31

Figure 13 HPLC result of fish tissue extracts in abdomen from 0 to 12 hours storage time.... 33

Figure 14 Summary the six nucleotides of 8 Seriola dumerili in abdomen ... 34

Figure 15 Summary the K value of 8 Seriola dumerili in abdomen ... 35

Figure 16 The fluorescence index of Seriola dumerili that get tense by low temperature .... 41

Figure 17 Eight Seriola dumerili analyzed by PCA ... 42

ix

List of Tables

Table 1 The metabolism of fish in postmortem ... 2

Table 2 The traditional methods for measuring fish freshness and their meaning ... 3

Table 3 The related study on fish fluorescence spectral analysis ... 8

Table 4 Gradient condition for ATP degradation products ... 20

Table 5 The standard concentration (mg/L) of six ATP degrade production ... 21

Table 6 The recovery of six ATP degradation products ... 29

Table 7 The R2 value of checking measuring curve of six ATP degradation products ... 31

Table 8 The RSD (%) of HPLC detection during one day ... 31

Table 9 The abdomen of Seriola dumerili for the correlation of optical index and K value .... 36

1

I. Introduction

1.1. Background

1.1.1. Fishery issues in Taiwan

Taiwan is an island country, so fishing is an important industry. But compared to other

marine countries with an interest in aquaculture, the Taiwan government is more focused on

the domestic market. Moreover, the quality of aquatic products and processed farm products

are controlled only before reaching customs, and the standard operation performance is too

complicated to control. If the products are imported to another country, quality management is

a big issue because the inconsistencies of laws and standards make it hard to track in the

importing country. Given the trend of trade liberalization and internationalization, the

enhancement of industrial competitiveness and the need for lower production costs have

grown in importance for maintaining industry sustainable.

Generally, the traditional process of detecting freshness is to judge the shape, color, and

smell of the fish [1, 2]. When necessary, magnifiers are used for further detection. However,

if the fish products are in doubt, fishermen are required to coordinate with the Fisheries

Department or its delegate agencies for sampling and are supposed to notify the inspection

bodies to carry out biological tests and extraction and colorimetric measures. Tests for volatile

basic nitrogen (total volatile basic nitrogen: TVB-N) and trimethylamine nitrogen

(trimethylaminenitrogen: TMA-N) are frequently used.

In detecting drug residue, enzyme-linked immunosorbent assay (ELISA), thin layer

chromatography (TLC), high-performance liquid chromatography-ultraviolet (HPLC-UV)

detection, liquid chromatography-Mass (LC-MS) spectrometry, or liquid

2

Although these chemistry type methods are precise and accurate, it is hard to meet the

business requirement nowadays by executing the complicated and time-consuming procedures.

When encountering a large number of fish, the inspector may make an error and spend more

time confirming the report.It is inevitable that a depletion of fish products occurs during the

process of detection.

1.1.2. Biochemistry metabolism of fish tissue

From Table 1.1, it can be seen that the process of anaerobic respiration begins just after

the fish start dying. In this time, metabolic glycolysis carries on with degrading creatine

phosphate to generate adenosine triphosphate (ATP). Creatine phosphate breaks down into

creatine and creatinine. Then, because of the anaerobic respiration, lactic acid accumulates

and the pH value starts to decline, causing other enzyme activity. After that, the muscle starts

the period of rigor mortis, which results from the complete consumption of ATP and the

structural changes in myosin and actin. Almost at the same time, the muscle structure starts to

break down following the resolution of rigor, as microbial activity multiplies quickly in the

muscles. In the next step, proteins, lipids, and nucleotides start to decompose; e.g., proteins

are degraded to peptides and amino acid; lipids are degraded to aldehyde, ketone, peroxide,

and lipid acid; ATP is degraded to adenosine diphosphate (ADP), adenosine monophosphate

(AMP), inosine monophosphate (IMP), inosine (HxR), and hypoxanthine (Hx). Finally, more

and more accumulation of the above metabolites makes the muscle tissue putrefied.

Table 1 The metabolism of fish tissue in the postmortem period [3]

Stage Period Biochemical meaning

1st death of fish 1. anaerobic glycolysis: ADP → creatine phosphate → ATP 2. formation of lactic acid: pH value descends

3

2nd rigor mortis 1. rigor mortis: acting & myosin → actomyosin 2. complete consumption of ATP: rigor mortis 3rd resolution of

rigor

muscle structure change: the degradation of z disc, myosin and actin

4th autolysis 1. protein: protein → peptide → amino acid

2. lipid: lipid → acetone → aldehyde, ketone, peroxide, and lipid acid

3. nucleotides: ATP → ADP → AMP → IMP → HxR → Hx 5th putrefaction 1. protein: accumulate many amino acids

2. lipid: accumulate many aldehydes, ketones, peroxides, and lipid acids

3. nucleotides: accumulation of HxR and Hx

4. low-molecule-weight compounds: microbiological degraded

Fish freshnesscan be detected by investigating the metabolites above. The processes are

based on color, texture, flavor, and the metabolites of tissue [4], e.g., T-VBN, TMA-N, and

histamine, which are the metabolites of protein [5]. Also, measuring the pH value in fish

tissue or calculating ATP degradation products for K value are alternative procedures [6, 7].

Though they are accurate and precise, these traditional methods waste many times. Moreover,

the complicated detection procedures waste resources.

Table 2 The traditional methods for measuring fish freshness and their meanings

operation (Media) meaning drawback

sensory organ

coloring, smelling, touching be smelly, stiff, and less red fish muscle for several hours after fish died

know-how

pH value pH meter (glass electrode) pH value is changed by glycolysis and other metabolism processes

invasive, time consuming

T-VBN total VBN main metabolite of amino acid

invasive, time consuming, complicated

TMA-N trimethylaminenitro-gen main metabolite of amino acid

Histamine histamine concentration the metabolite of glycine

K value 1. ATP, ADP, AMP, Hx, and hypoxanthine

2. K value calculation

ATP is not generated and the fish muscle will be stiff.

4

1.1.3. The definition of K value

In this study, the K value is used as a freshness standard to compare with the optical

index. ATP is the energy used directly in the creature. After fish die, ATP is degraded into ADP,

AMP, IMP, HxR, and Hx during the process of storing of fresh fish or preserving seafood.

IMP is formed by AMP deaminase, which is an autolytic enzyme, and spoilage bacteria result

in HxR and Hx formation. IMP has a flavorful taste, whereas Hx has a bitter taste, which

indicates spoilage of the fish. However, the metabolism rate from ATP to Hx is different from

fish to fish. The K value was suggested as an index of fish freshness in 1959 by Japanese

researchers. A K value of 40 represents the spoilage of fish, which indicates that the product

should not be supplied to customers, whereas a K value of 20 can be used to restrict

consumption as raw fish or sashimi. Following are the metabolism of ATP and the equation of

K value:

ATP → ADP → AMP → IMP → HxR → Hx



  



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

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

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

 



  

 100   Hx HxR IMP AMP ADP ATP Hx HxR value K (1)

where [ATP], [ADP], [AMP], [IMP], [HxR], and [Hx] indicate the concentration of the

metabolites. K value is calculated by the concentration of the six ATP degradation products. In

most fish, K values increase linearly during the first days of refrigeration storage, and it is an

index of freshness detection. When the K value is higher, it means the fish meat is less fresh.

5

The food detection techniques have been developed for many years. In the early stage,

the researchers attached importance to the accuracy (direct detection and multi-index

combination) of detection techniques. The first modern method used dependent parameters

(the Torry scheme) for freshness [8]. Later, it was modified by combining many characteristic

features to calculate a score called "QIM." This gave a single numerical value to a broad

range of characteristics. In 1962, the standard method was named Conway’s method; it distills

off volatile amines (or the microdiffusion of an extract) and includes measurements of

di-methylamine, tri-methylamine, ammonia, and other volatile basic nitrogenous compounds

associated with meat spoilage. Afterwards, more and more detection instruments were

developed to establish better performance. One of the most popular methods, established in

1985, is utilizing K value calculation by High Performance Liquid Chromatography (HPLC).

This K value is decided by six components, which are the metabolites of ATP in muscles, i.e.,

ATP, ADP, AMP, IMP, HxR, and Hx [9, 10]. HPLC is more accurate and precise than

ion-exchange chromatography (IEC), which was used previously.

Nowadays in the food industry, researchers are focused on developing a low-cost system

for monitoring freshness. Some of the previously used methods have been modified. Gil

developed an electronic tongue by using metallic potentiometric electrodes for fish freshness

analysis in 2008 [11]. Yapar measured the refractive index of eye fluid to determine changes

of fish freshness in 2004 [12]. Okuma and Nanjyo combined enzyme electrodes sensors with

an injection flow device to develop a system for measuring fish deterioration in 2002 [13, 14].

In 2008, Barbri produced a portable electronic nose system to measure peculiar fish smells

produced over time to evaluate differences in fish freshness [15]. Kroeger adopted machine

vision analysis of whole fish and fillets with respect to freshness in 2003 [16]. Also, visible

and near-infrared spectroscopy has been used to analyze the quality of fish [17]. Several new

6

there are many limitations for these techniques, including detecting limitations in storage time

and limited applicability to certain fish species.

Amino acids, proteins, and enzymes are well-known fluorescent molecules, and the

potential to use fluorescence spectroscopy to serve as an analytical tool in the chemical,

biological, biomedical, and food sciences has increased in recent years. For example, the

fluorescence spectra of tryptophan (amino acids), collagen (protein), and NADH (coenzyme)

with linear multivariate analysis methods have been adopted to differentiate differences in

normal and dyplasia tissues in humans [18]. It is also known that changes in intrinsic

fluorophores can be measured in fish muscle. Also, the fluorescence spectra can be described

during refrigeration storage. The destruction of aromatic amino acids, the deposition of

protein, and the action of metabolic enzyme can be treated as biomarkers for fish freshness.

1.2. Literature review

1.2.1. The principle of fluorescence technology

The vibration level of electrons for most molecules is generally lowest at room

temperature. When one molecule is excited by a specific wavelength, the electron energy

level moves from a ground state (S1) up to an excited state (S2). After that, most electron

activity drops quickly to the lowest level of vibration excitation. In the process, similar

molecules hit each other and lose energy, which is called vibration relaxation or internal

conversion. Then after about 10-9 second, the electrons drop on every vibration level to a

7

Fig. 1 The electron energy level moves from a ground state to an excited state by excited power, and the energy conversion by vibration relaxation, internal conversion, and electron jumping from excited state to ground state will emit heat and fluorescence [19].

1.2.2. Fluorescence measurement of freshness

Recently, many groups have distinguished the stages of fish freshness from

fluorescence spectra. NADH, lipid oxidation, chlorophyll, tissue structure (collagen), and

aromatic amino acid (tryptophan) have been investigated as the targets of fluorophores to

monitor freshness. For example, Aubourg and Duflos measured the fluorescence spectra of

lipid oxidation products as an index of fish freshness in 1999 [20, 21]. During refrigeration

storage, fish will deteriorate with lipid degradation, which causes the proteins of the muscle to

denature and change texture [22, 23]. Thus, Aubourg investigated free fatty acids, the

thiobarbituric acid index (TBA-i), and fluorescence formation. The results showed that the

lipid damage rate varied with difference species and storage temperatures. Dufour found that

the fluorescence spectra of tryptophan and NADH could be used as fingerprints of fish. Fresh

8

Analysis (PCA) and Flexible Discriminant Analysis (FDA). Karoui adopted PCA and

detrended fluctuation analysis (DFA) methods to extract NADH fluorescence information for

determining a precise classification [24]. In addition, Andersen discussed the auto

fluorescence of collagen type I and type V, which are detectable from the fluorescence spectra

of salmon and cod muscle [25]. The spectra at fluorescence wavelengths 470 and 430 nm

from fish tissue were assumed as collagen type I and type V, which were considered related

with resolution of rigor.

Table 3 The related study on fish fluorescence spectral analysis

Authors Journal Excitation

(nm) Emission (nm) Target Analysis Method Result E. Dufour, J.P. Frencia, E. Kane Food research International 36,415–423 (2003) 250 290 336 280-480 305-400 360-600 amino acid nucleic acid tryptophan NADH

PCA PC1 and PC2 shows discrimination of day1, day 3 and day 5 C. M. Anderson J. P. Wold J. Agric. Food Chem. 51, 470-476 (2003) 332 350-600 collagen NADH

PCA The spectrum could be the fluorophore of collagen R. Karoui, E. Thomas, E. Dufour Food research International 39 349-355 (2006) 290 340 305-400 360-570 tryptophan NADH

PCA NADH can predict frozen and thawed fish 100% J. Christensen, L. Nørgaard, R. Bro, S. B. Engelsen Chemical review 106 (2006) 332 350-600 amino acid chlorophyll collagen NADH PCA FDA PARAFA C model Summary of the research of fluorophores in fish tissue for food study J. F. Hunt T. Ohno J. Agric. Food Chem. 55, 2121-2128 (2007) 240-400 300-500 tryptophan tyrosine PARAFAC model 2 nd component is related to freshness J. SádeCká J. TóThoVá

Czech J. Food Sci. 25, 159–173 (2007) 250 290 336 280-480 305-400 360-600 tryptophan nucleic acid NADH PCA FDA Summary of the research of the fluorophores of nucleo acid, amino acid, and NADH in fish tissue

Above all, the fluorescence spectra have been analyzed for many kinds of foods. Fish

9

studied for a long time. However, there was almost no study focusing on fresh fish that

discussed fluorophore changes as a quick detection technique. Investigating the fluorophores

in fresh fishes is necessary because of the importance of maintaining good fish quality. After

all, fishermen could enjoy better sales if they had better quality control.

To develop a portable fluorescence measurement system for monitoring fish freshness

during the delivery process in various environments, the focus of this study is on fiber-optic

fluorescence spectroscopy for monitoring freshness during refrigeration time. This academic

investigation can provide value for consumers and suppliers by drawing a successful roadmap

for establishing an unsophisticated portable device using selective excitation light to

understand the quality of fish freshness.

1.3. Objective

Because of the importance of controlling the quality of fresh fish, my study will perform

optical fluorescence measurements to find an optical index related to freshness within 24

hours after the fish have died. It is very important to maintain the quality of fish for fishermen

and customers till the fish has been cooked. In this study, all the metabolic processes of fish

tissues are observed at different stages as the fish become less fresh. The optical index is

developed to find the correlation between the optical measures and the freshness in these fresh

fish. Live fish were chosen as our experiment subjects to study the metabolism of fresh fish.

We assume that some fluorophores in the tissue of fresh fish will degrade or degenerate in the

process of becoming spoiled. The fish samples will be sliced into equal sizes to analyze the

fish fillets as they change with refrigeration time. Based on this concept, the fluorophores

related to freshness can be found and analyzed. After the index is developed, it can be applied

as a faster method to test sashimi or fish fillets. The optical index will be validated by

10

analyzing the concentration of nucleotides using HPLC, we can learn more about the

freshness within 24 hours. Finally, the index can be applied as a quick-detection instrument

for fish freshness.

Fig. 2 depicts the measurement system, which includes a light source, illumination fiber, pick-up fiber, a miniature spectrometer, and a computer. The illumination fiber releases a specific power, and the pick-up fibers receive fluorescence to transport to the spectrometer. Finally, the signal is analyzed by a computer.

11

II. Material and Method

2.1. Experiment flow chart

Fig. 3 represents the flow chart of the experiment, which includes two stages. The main

purpose is developing an optical technique to compare the time variant and the chemical

index of different species of fish. In the first stage, cobias are used for qualitative analysis to

search a spectrum area related to freshness from the Excitation-Emission Matrix (EEM). The

optical index is developed by normalizing and comparing different storage times. In the

second stage, we use the same spectrum area from the cobia to investigate different species of

fish. Seriola dumerili are measured for narrower refrigeration time intervals to compare with

the K value and to monitor the detail in the fish tissue. Statistics are developed using the

optical index and these two kinds of fish species.

Fig. 3 depicts the experimental flow chart. The upper-side and lower-side procedures are for optical and chemical experiments, respectively.

12

2.2. Fish subject

2.2.1. Cobias

Cobias live in temperate and tropical zones of the sea and grow up to 6~8 kg and 1.5 m

long in their first year. Cobias are mainly captured from March to May. Nowadays, cobias are

the main type of fish used in offshore cage aquaculture in the world. The fish are most famous

for sashimi preparation in Asia. In Taiwan, cobia is fed in a net/box in warm water in Penghu

County. Since Taiwan is a desirable environment to exploit cobia offshore cage aquaculture,

5-to-7-month-old cobias, which are suitable for sashimi preparation, have been chosen as the

monitoring target in this study.

2.2.2. Seriola dumerili

Seriola dumerili also live in temperate and tropical zones of the sea. The fish can grow

up to 30 to 40 centimeters long. The color of the fish body is slightly brown. The meat is full

of lipids and nutrients, and because of its texture and its deliciousness, it is also famous for

sashimi preparation.

2.3. Pretreatment for live fish

Initial experiment

A total of eight cobias (averaged weight was 5.0±1.0 kg) in Penghu Country were

adopted as experimental species. Each cobia was slaughtered and gutted by a fishmonger after

the blood was washed out of the tissue by secondary water and then transported to lab as soon

as possible. Equal sizes of fish fillets (4×3×1 cm3) had to be sliced in order to keep different

13

refrigerator at 4 oC for 24 hours. The steps of the pretreatment process were:

I. The fishmonger stroked the fish on the head with a hammer, causing it to lose consciousness;

II. The fishmonger gutted the cobias and cleaned the blood from the tissue;

III. The fish were put into a crisper and transported with an ice bucket to the lab as soon as possible;

IV. The fish were cut into fillets of equal sizes (4×3×1 cm3);

V. Fillets were refrigerated at 4 oC, and optical measurements were begun immediately.

Advanced experiment

A total of eight fish (averaged weight was 1.0±0.2 kg) were collected from a local

seafood restaurant in Hsinchu County. We needed to measure the fluorescence spectrum in a

shorter time interval compared with the cobias to analyze the differences at different time

points and to ensure the freshness of the fish. The samples were validated by K value using

HPLC. The steps of the pretreatment process of Seriola dumerili were similar to that applied

on the cobias:

I. The chef stroked the fish on the head with a hammer, causing it to lose consciousness; II. The chef gutted the Seriola dumerili and cleaned the blood from the tissue;

III. The chef sliced the meat in the abdomen and dorsal parts, respectively, and washed the fish again with secondary water;

IV. The fish were put into a crisper and transported with an ice bucket to the lab within 25 min;

V. The fish were cut into equal-size fillets (4×3×1 cm3);

VI. Fillets were refrigerated at 4 oC, and optical measurements and chemical processing began immediately.

14

Fig. 4 depicts Seriola dumerili before and after pretreatment of live fish by the chef: (a) the space for the fish in the local restaurant, (b) slaughtered fish, (c) cut fish meat, and (d) slices of abdomen and dorsum.

2.4. Optical fluorescence measurement

When the electrons of fluorophores in fish tissue are excited, these electrons jump into an

excited state. When these electrons go back to a ground state, fluorescence is emitted

instantaneously. The wavelength of emitted fluorescence depends on the energy level between

the ground state and the excited state. For a variety of fluorophores in fish tissue, different

features of fluorescence are emitted. Based on the fluorescence emitted by the fish tissue, the

fluorophores can be found and identified. Finally, the optical index for freshness detection

will be developed for the time points within 24 hours after the fish have died.

2.4.1. Measurement system

Fig. 5 is an overview of the Y-type fiber-optic measurement system. This system

15

monochromator (HORIBA Jobin Yvon, Longjumeau, France), a Y-type optical fiber, a

MicroHR180 spectrometer (HORIBA Jobin Yvon, Longjumeau, France), an R928

photomultiplier tube (PMT) (Hamamatsu, Shizuoka, Japan), a 1,000 voltage power supply

(HORIBA Jobin Yvon, Longjumeau, France), a DataScan2 (HORIBA Jobin Yvon,

Longjumeau, France), and an anti-vibration table (Newport, Taipei, R.O.C.). The xenon lamp

is set up as a light source in this study for broadband wavelengths from 260 nm to 600 nm. In

order to slice a narrow band of excitation light, the slit (width is 0.5mm) is put into the export

of the monochromator to filter through a pure light source. The Y-type fiber, which is set up

on a black platform, can transfer excitation light and emission light. After transferring the

emission light, the spectrometer separates the light into mono wavelengths. Finally, the mono

wavelength light is transformed into an electrical signal by PMT, and then the signal is

acquired by DatasScan2 controller. The computer gathers the signal from DataScan2 by using

an RS232 serial cable. All instrumentation drivers of the monochromator, spectrometer, and

PMT were designed by LabVIEW (v. 7.1, National Instruments, Austin, USA). As well, the

front panel of the system and the operating protocols were also designed by LabVIEW (v.

2011).

Fig. 5 shows the Y-type fiber-optic measurement system. The room lighting is turned off,

spectrometer

DataScan

High

voltage _Y-typefiber

Xenonlamp Power supply Computer PMT Monochromator Anti-vibration Table Mask

16

and a black mask is utilized to avoid light leakage during measurement.

2.4.2. Measurement process

The measurement environment is always kept around 25±3 oC, and samples are

preserved at 4±2 oC refrigerator. In order to avoid unexpected noises, a 30 min warm-up step

is necessary for the lamp and power supply. After finishing this, one fish fillet of abdomen or

dorsum is put on a sample holder. Cobia fillets are taken out for measurement every 6 hours

between 0 and 18 hours. As well, Seriola dumerili fillets are taken out of the refrigerator for

measurement every 2 hours between 0 and 24 hours. The excitation wavelength is set from

320 to 420 nm, and the emission wavelength is set from the excitation wavelength + 30 nm

(Exci+30 nm) to two times the excitation wavelength (2×Exci-80 nm) to remove second

harmonic generation. For example, the emission wavelength is set from 350~560 nm at the

320 nm excitation wavelength. By the wide range of fish tissue scanning, the fluorophore

regions can clearly be located. The fiber cable contains up two kinds of fibers called "Y-type

fibers." One of the fibers is for the transmittal of the excitation light source, and another is for

reception of the emission signal. In addition, two different sites on each fillet are measured for

an average to reduce the non-homogenous effect of the fish tissue.

2.4.3. Measurement program and related parameters

Fig. 6 shows the front panel of the measurement system program. Although all

instrumentation drivers were designed by LabVIEW 7.1, the front panels of the system and

the block diagrams of the operating protocols were implemented modally and hierarchically at

the LabVIEW 2011 environment. Before measurement, the spectrometer and monochromator

17

the entire procedure. The “STOP” button is designed for sending an emergency command

from the software to the external devices immediately. The fluorescence amplitudes of every

excitation wavelength are shown on the waveform graph and are saved as an American

Standard Code for Information Interchange (ASCII) text file. Another drawing program is

designed for the Excitation-Emission Matrix (EEM) display. Following are the measurement

parameters of this system:

I. Excitation wavelength: from 320 to 420 nm with 10 nm interval

II. Emission wavelength: from (Exci+30 nm ) to (2×Exci-80 nm ) with 2 nm interval for

each excitation

III. Integration time: 300 ms

IV. High voltage: 600 V

V. Grating: 1200 mm

Fig. 6 shows the front panel of the measurement program.

2.4. Chemistry detection method for freshness

Fish subjects can be quite fresh even after the fish have died and 24 hours of storage. It is

18

which was developed by six kinds of ATP degradation products, can be a proper way to

evaluate fish freshness. ATP, ADP, and AMP all exist in live fish but decompose to IMP, Hx,

and HxR soon after the fish die. Based on this concept, K value calculation is used to

accurately judge the freshness of fresh fish. Moreover, the result with HPLC methods can

achieve K value calculation more precisely and more accurately.

2.4.1 Chemistry reagents and instruments

2.4.1.1 Instruments

A high-speed refrigerated centrifuge (6200, KUBOTA) was rented from Jen An

Technology Co. Ltd. for three months. Ultrapure water was borrowed from The Department

of Biochemical Science and Technology at National Chiao Tung University (NCTU). A -70

o

C refrigerator was borrowed from the Department of Applied Chemistry from NCTU. An

analyze column (5 μm ODS-2 4.6x250 mm, Inersil) was purchased from Vercotech Inc.,

HPLC (ProStar 210, liquid chromatography system, Dynamax, Thermo Finnigan, San Jose,

CA, USA) and a UV-Vis Detector (ProStar 325, Dynamax, Thermo Finnigan, San Jose, CA,

USA) and other tools for HPLC were borrowed from the precision instrument room at NCTU.

2.4.1.2 Chemicals and reagents

Perchloric acid (Chemical pure, KGaA, Merck) was used to extract the ATP degradation

productions. Potassium hydroxide (Chemical pure, Schuchardt OHG, Merck) was used to

neutralize the acidity of perchloric acid. Methanol (HPLC grade, Merck) was used as mobile

phase A, and Na2HPO4 (HPLC grade, Merck) was used as mobile phase B for HPLC.

19

disodium salt hydrate (ATP), Adenosine 5'-diphosphate sodium salt (ADP), Adenosine

5'-monophosphate sodium salt (AMP), Inosine 5'-monophosphate sodium salt (IMP), Inosine

(HxR), and Hypoxanthine (Hx), which are standards of the ATP degradation products.

2.4.2 Chemistry method procedure

During the fish fillet extraction process, it was important to keep the fillets at 4 oC

temperature to prevent the ATP products from being degraded [26]. The ATP products were

extracted by perchloric acid and neutralized by potassium hydroxide. To remove the crystal

from the extraction solution, the samples were frozen at 0 oC to precipitate more KCl4 crystals.

The extraction process steps:

Smash 5 g fish meat by Homogenizer for 1 min ↓

Add 5 g meat into 25 mL of 6 % perchloric acid and then centrifuge for 15 min (5000 r/min)

↓

Remove 10 mL supernatant to another centrifugal tube ↓

Use potassium hydroxide to neutralize to pH 6.4 (10 mol/L solution at first and then 1 mol/L solution)

↓

Storage in refrigerator at 0 oC for 30 min ↓

Sintered filter to filtrate the Crystallization of KClO4

↓

RC25 membrane syringe filter ↓

Diluted by ultrapure water to 20 mL ↓

Storage in refrigerator at -70 oC ↓

Analyze by HPLC ↓

20

2.4.3 Recovery of the extraction process

In order to confirm the coefficient of recovery of the extraction process, the standards of ATP, ADP, AMP, IMP, Hx, and HxR were added into the fish fillets. We added two concentration levels of 1ml of standard solution, which contained 1,000 mg/L and 3,000 mg/L of ATP, ADP, AMP, IMP, Hx, and HxR, to compare with the fish fillet, in which the standard solutions were not added. A total of 10 g of fish meat was homogenized and divided into two groups: one was 5 g of fish meat; another was 5 g of meat plus 1 mL of standard solution to perform the extraction process. Finally, the recovery was calculated to evaluate the efficiency of extraction.

2.4.4 HPLC analysis

In the study, two kinds of mobile phases were used for HPLC analysis. Mobile phase A

(0.1M Na2HPO4 and 6.0 pH value by H3PO4) and mobile phase B (Methanol) were degassed

before running. The mobile phases were filtered through a 0.22 μm × 47 mm nylon membrane

filter (Supelco, Bellefonte, PA, USA). After melting the extraction samples from -70 oC, the

samples were centrifuged to remove redundant crystallization and then 5 L of the sample solutions were injected into the injector. Mobile phase A and mobile phase B were used as the

mobile phases at a flow rate of 0.7 mL min-1. The initial composition was 98% A and 2% B

for 3.0 min, then changed linearly to 50% A and 50% B for 12 mins, and then changed to

35% and 65% B for 3 mins. Finally, the composition was changed to 98% A and 2% B for 5

mins of equilibrium. Following are the gradients for phase A and B (Table 4).

21 Time (min) Flow (ml/min) Mobile phase A (%) Mobile phase B (%) 0 0.7 98 2 3 0.7 98 2 15 0.7 50 50 18 0.7 35 65 20 0.7 98 2 25 0.7 98 2

* Mobile phase A is 0.1M Na2HPO4 and 6.0 pH value by H3PO4

* Mobile phase B is methanol.

Table 5 lists five different concentration standards by serial dilution for calibration curve.

For the higher concentrations of IMP, ATP, and ADP of fish tissue, it was necessary to

heighten the concentrations appropriately.

Table 5 The standard concentration (mg/L) of six ATP degrade production

Standard IMP ATP ADP AMP Hx HxR

1 37.5 37.5 87.5 37.5 37.5 37.5

2 75.0 75.0 175.0 75.0 75.0 75.0

3 150.0 150.0 350.0 150.0 150.0 150.0

4 300.0 300.0 700.0 300.0 300.0 300.0

5 3,000.0 1,200.0 1,400.0 600.0 600.0 600.0

In order to avoid environmental bias, three HPLC analyses of the same standard sample

within 24 hours were needed, and the relative standard deviation (RSD) was also calculated

for precise confirmation of HPLC analysis. The calculation of RSD value is

n x x n 1 i i



  (2) 2 1           



 1 n ) x (x S n 1 i 2 i (3)

22 % 100 value RSD   x S (4)

where x _{, S, and n denote as mean, standard deviation, and the number of {}x_i}, respectively.

2.4.5 K value Calculation

K value and nucleotide concentration are calculated by following equations:



  



 



 



 



 



  

 100   Hx HxR IMP AMP ADP ATP Hx HxR value K (5)

Where [Hx], [HxR], [ATP], [ADP], [AMP], and [IMP], are treated as the concentrations

of Hx, HxR, ATP, ADP, AMP, IMP, and Inosine, respectively.

2.5. Data Analysis

2.5.1. Excitation-Emission Matrix

The fluorescence amplitudes of specific excitation wavelengths were saved as an ASCII

text file. The data were retrieved as a two-dimensional plot of EEM for distinguishing the

variability of the fluorescence spectra clearly. Because of the line scan property of the Y-type

fiber-optic measurement system and the unstable power output of the xenon lamp, every

fluorescence waveform was normalized by dividing by the amplitude of (exci+30) nm

emission wavelength.

2.5.2. Optical index

23

we define an optical index for further multivariate analysis. The optical index value,

) , (emi exci G , is: ) , 50 ( ) , ( ) , ( exci exci F exci emi F exci emi G   (6)

where F(emi, exci) denotes the fluorescence amplitude of a certain excitation wavelength

(exci nm) and emission wavelength (emi nm), and F(exci+50, exci) denotes the fluorescence

amplitude of a certain excitation wavelength (exci nm) and emission wavelength (exci+50

nm).

2.5.3. Time variant analysis for optical index

One principle of ANOVA is to evaluate the experimental error. When the effect of an

independent variable has much more influence than a dependent variable on an experimental

error, we assume the result of dependent variable have significant difference by different

independent variable. The confirmation of the optical index was made by using analysis of

variance (ANOVA) of SPSS 17.0 (SPSS Inc., Chicago, USA) for evaluating the variation of

fluorescence over time. To investigate all the time points, a post hoc test was performed. Sum

of squares between groups ( SS_B ) means the variance between different groups:



   k i i i B n (x x) SS 1 2 , xi is the mean of i th

class, x is the mean of all; sum of square due to

error (SSE) means the variance in one class :

 

    k i n j i ji i E j ) x x ( n SS 1 1 2 , x_ji is the values of

24

calculate Mean Square (MS):

i i i .) F . D ( SS

MS  , where D.F. means the degree of freedom. By

calculating F value, the differentiation between different classes can be found out.

Following is the equation:

K n SS K SS MS MS F E B E B     1 (7)

where MS_B is mean square between groups, MS _E is mean square due to error, K is the

number of all classes, and n is the number of all elements in one class.

If F is larger, it presents the more dispersed data. When F is large enough, it presents the

significant difference between two classes.

2.5.4. The relationship between optical index and K value

Pearson correlation analysis was used because of the interval scale of our experiment.

Pearson correlation results show the linear correlation coefficient between two continuous

variables. The correlation coefficient of r value is between -1 and 1. The negative and positive

are to distinguish the negative and positive correlation. However, the result can only represent

the correlation but not the cause-and-effect relationship. Following is the equation of Pearson

correlation:







        n i i n i i i n i i ) y y ( ) x x ( ) y y )( x x ( r 1 2 1 2 1 ₍₈₎

25

where xi is i th

of x variables, x is the mean of x variables, yi is i th

of y variables, y

is the mean of y variables. We analyze every fishes sample by using LabVIEW 2011.

III.

Experiment Result

3.1. Optical fluorescence results

3.1.1. The results for cobias

Fig. 7 shows the excitation-emission matrix (EEM) from a measurement of fish tissue in

the abdomen. EEM consists of hundreds of measurement combinations of a single fish fillet

sample, with excitation wavelength on one axis, emission wavelength on the second, and

fluorescence intensity forming a third axis presented by color. With building up EEM from

the fluorescence by scanning and recording a group of individual emission spectra, the

fluorophores can be clearly indentified. From the results of EEM, fluorescence was observed

throughout the whole collection range, with two peaks (excitation wavelength/emission

wavelength) located at 340/430 nm and 340/470 nm. A ridge extended from 360/400 nm to

350/600 nm). A valley was seen between 440 and 460 nm emission wavelengths. The changes

were observed between 330 and 360 nm excitation wavelengths in 12 hours, so their emission

spectra was extracted to analyze the relationship between fluoresce intensities and

refrigeration time.

It was the same for the dorsum samples with two peaks located at the 340/430 nm

(excitation wavelength/emission wavelength) and 340/470 nm wavelengths and changes

26

Fig. 7 depicts abdomens of cobia at different time points: (a) 0 hour, (b) 6 hours, (c) 12 hours, and (d) 18 hours.

The optical index is presented by the value ofG(emi ,exci ), which is set up by the

equation (5). It presents that the indexes of G(470,exci) and G(430,exci), where exci are 330

nm, 340 nm, 350 nm, and 360 nm, have relations with storage time. The labeled vertical error

bars indicate the standard deviations of the mean. The results illustrated that the G value

decreased by increasing refrigeration time. In addition, the large drop heights appeared

between 6 and 12 hours at different excitation wavelengths. The statistical comparison of G

values at different refrigeration times was also calculated through the tests of within-subject

effects. The compared results indicated that the ratio values at 0, 6, 12, and 18 hours were

significantly different (p < 0.05) under the same excitation wavelength. Furthermore, the

post-hoc analysis was used to investigate the details of the relation between the refrigeration

times. The results presented that the ratio values of abdomen specimens at 0 hour were no

different with the ratio values of abdomen specimens at 6 hours, whereas the ratio values of

abdomen specimens at 0 hour were significantly different (p < 0.05) at 12 and 18 hours under

27

specimens at 6 hour were significantly different (p < 0.05) with these at 12 and 18 hours too.

Nevertheless, in summary, the mean of the G value has a descending trend with refrigeration

time in the eight cobias.

Fig. 8 shows a summary of the fluorescence ratios of eight cobias excited by 330, 340, 350, and 360 nm of excitation wavelengths: (a) G(470,exci) in abdomen, (b) G(470,exci) in dorsum, (c) G(430,exci) in abdomen, and (d) G(430,exci) in dorsum samples.

3.1.2. The results for Seriola dumerili

From fig. 9, fluorescence is observed almost at the same location as the cobias, with two

peaks located at the 340/430 nm (excitation wavelength/emission wavelength) and 340/470

nm wavelengths. The descending trend of fluorescence intensity is observed between 330 and

360 nm excitation wavelengths within several hours from EEM. However, the peak intensity

is weaker than for cobias. Nevertheless, the trend of fluorescence for Seriola dumerili is

28

abdomen samples.

Fig. 9 shows abdomens of Seriola dumerili at different refrigeration time points: (a) 0 hour, (b) 2 hours, (c) 4 hours, (d) 6 hours, (e) 8 hours, (f) 10 hours, (g) 12 hours, (h) 14 hours, (i) 16 hours, (j) 18 hours, (k) 20 hours, and (l) 22 hours.

The optical index, as previously thought, presents that the refrigeration time (0 to 24

hours) was related to G(470,exci) and G(430,exci) at 330 nm, 340 nm, 350 nm, and 360 nm

excitation wavelengths. The labeled vertical error bars indicated the standard deviations of the

mean. The results illustrated that the value decreased by increasing refrigeration time. In

addition, the range of G index is approximately from 1.5 to 0.5, which is approximately the

same range as for the cobia. The large drop heights appeared at initial time points at every

29

Fig. 10 depicts a summary of the fluorescence ratios of eight Seriola dumerrili excited by 330, 340, 350, and 360 nm of excitation wavelengths and for cobias, respectively: (a) G(470,exci) in abdomen, (b) G(470,exci) in dorsum, (c) G(430,exci) in abdomen, and (d) G(430,exci) in dorsum samples.

3.2. Chemical results for Seriola dumerili by HPLC

3.2.1. Recovery of ATP degradation products

The recovery of extraction samples was around 85 to 90 %, which was acceptable for our extraction process.

Table 6 The recovery (%) of six ATP degradation products

Spike level(mg/L) IMP ATP ADP AMP Hx HxR

30

3.2.2. The results by HPLC

Fig. 11 shows the six ATP degradation standard products by HPLC, the retention time of

IMP, ATP, ADP, AMP, Hx, and HxR are approximately 6.55, 8.29, 9.0, 10.0, 10.28, and 12.4

minutes respectively. The checking-measuring curve is shown in fig. 12. It presents the linear

correlation of the integral area and the concentration between the maximum and minimum

standard concentration. The concentration range of fish samples are in the range of a standard

curve. Also, the R2 values are all around 0.99 to indicate the great linear regression line of the

standards. The standards are executed three times in a day to confirm the stability of our

HPLC detection in different periods of time. The values are around 5 1 to indicate the precision of our detection.

Fig. 11 shows the six nucleotide standards (ATP, ADP, AMP, IMP, Hx, and HxR) separated by HPLC.

31

Fig. 12 depicts the checking measuring curve of the six ATP degradation products.

Table 7 The R2 value of checking measuring curve of the six ATP degradation products

Table 8 The RSD (%) of HPLC detection during one day

Compounds mg/L RSD(%) Compounds mg/L RSD(%) IMP 37.5 4.87 AMP 37.5 4.58 75 3.48 75 4.67 150 4.79 150 4.11 300 4.72 300 4.65 3000 4.15 600 3.21 ATP 75 5.32 Hx 37.5 4.93 150 4.93 75 3.87 300 3.46 150 4.67 600 4.35 300 4.12 1200 4.41 600 4.89

Components IMP ATP ADP AMP Hx HxR

32 ADP 87.5 4.12 HxR 37.5 3.74 175 4.63 75 5.16 350 3.69 150 5.21 700 5.52 300 3.78 1400 3.87 600 4.53

3.2.3. The results for Seriola dumerili by HPLC

Fig. 13 shows the HPLC results of our Seriola dumerili samples. The six ATP

degradation products can be determined by the retention times. The figure presents the high

concentration of IMP; the degradation of ATP, ADP, and AMP; and the increase of Hx and

HxR. In summary of all the results, we find that the eight fish subjects differ from fish to fish

for the metabolism rates in postmortem (fig. 13). Some fishes started the decomposition of

ATP, ADP, and AMP earlier, and it caused the earlier accumulation of IMP. Because of the

accumulation of IMP, it may degrade to HxR and Hx faster after the fish die. The difference

in these fishes may be caused by factors such as how they are cultivated, how they are treated,

how they were slaughtered, and so on. However, the HPLC result confirms the different

33

Fig. 13 shows the HPLC results of fish tissue extracts in the abdomen from 0 to 12 hours of storage time.

34

Fig. 14 summarizes the six nucleotides of eight abdomen samples of Seriola dumerili: (a) ATP, (b) ADP, (c) AMP, (d) IMP, (e) HxR, and (f) Hx, which vary with refrigeration time.

3.2.4. The K value of eight Seriola dumerili

The K value results of eight Seriola dumerili on average represent an ascending trend

from 0 to 24 hours, and we find they are different for freshness. It has been proven that the

different decomposition rates may affect the fish freshness, which could be caused by the

earlier ATP degradation [27, 28]. Because of earlier degradation of ATP, it could cause the

35

Fig. 15 summarizes the K values of eight Seriola dumerili in the (a) abdomen and (b) dorsum, which vary with refrigeration time.

3.3. The correlation between optical index and K value

For the differences in the eight samples of Seriola dumerili, the G indexes that we

develop are compared with K value. Table 7 and Table 8 present the abdomen and dorsum

results of the correlation coefficient between the value of optical index and K value at the

same refrigeration time point (0 to 24 hours) of eight Seriola dumerili. We find that the r

values of correlation coefficient represent a negative correlation between the two indexes (G

36

that 340 nm excitation wavelength can be the best level for the most negative correlation

coefficient with K value. For most of the linear correlations from the eight Seriola dumerili,

the r2 value is approximately in the range of 0.6 to 0.7. However, there were less clear

negative correlations in some fish samples. It was assumed that they ran out of NADH and

collagen in the initial stage after the fish died. The descending G index could present a

process of rigor mortis and tenderization of muscle. Depending on the specific condition

affecting the fishes, the descending G index may result in losing the correlation to the K value

and could cause the K value to ascend faster. However, the value of G can indicate the stage

of fish tissue in postmortem. The G index could confirm the early stage of fish tissue after a

fish has died.

Table 9 Summary of the eight abdomens of Seriola dumerili for correlation between optical index and K value

Wavelength (nm) Correlation coefficient of ith fish (G index V.S. K value)

Emi. Exci. 1 2 3 4 5 6 7 8 470 _{330 -0.755 -0.694 -0.851 -0.827 -0.564 -0.798 -0.276 -0.269} 340 -0.833 -0.792 -0.886 -0.786 -0.733 -0.813 -0.292 -0.258 350 -0.816 -0.804 -0.866 -0.626 -0.657 -0.814 -0.006 -0.375 360 -0.711 -0.763 -0.740 -0.565 -0.436 -0.809 0.032 -0.053 430 _{330 -0.683 -0.718 -0.834 -0.800 -0.684 -0.733 -0.495 -0.307} 340 -0.749 -0.689 -0.865 -0.725 -0.806 -0.716 -0.515 -0.536 350 -0.686 -0.642 -0.869 -0.390 -0.797 -0.721 -0.416 -0.368

37

360 -0.554 -0.586 -0.700 -0.368 -0.682 -0.678 -0.102 -0.025

Table 10 Summary of the eight dorsums of Seriola dumerili for correlation between optical index and K value

Wavelength (nm) Correlation coefficient of ith fish (G index V.S. K value)

Emi. Exci. 1 2 3 4 5 6 7 8 470 330 -0.651 -0.771 -0.825 -0.634 -0.531 -0.749 -0.604 -0.487 340 -0.776 -0.843 -0.883 -0.695 -0.736 -0.813 -0.651 -0.250 350 -0.695 -0.804 -0.847 -0.680 -0.660 -0.849 -0.612 -0.024 360 -0.380 -0.751 -0.699 -0.570 -0.451 -0.849 -0.525 0.503 430 330 -0.771 -0.834 -0.845 -0.613 -0.684 -0.758 -0.630 -0.503 340 -0.859 -0.820 -0.867 -0.670 -0.834 -0.808 -0.684 -0.371 350 -0.803 -0.799 -0.890 -0.632 -0.827 -0.817 -0.672 -0.173 360 -0.495 -0.751 -0.804 -0.459 -0.615 -0.773 -0.594 0.473

38

IV. Discussion

4.1 The fluorophores of EEM spectra

We have found the spectrum that represents the concentration of components, such as

collagen type I, collagen type V, and NADH [25]. NADH plays an important role for

supplying and transferring energy to living creatures. When a fish dies, NADH can be

generated by glycolysis, and it can maintain the NADH concentration in the fish body. After

the fish tissue is acidified, which is caused by the accumulation of many lactic acids, the

glycolysis of the fish muscle stops and no longer generates NADH or ATP. NADH and ATP

will be oxidized to NAD+ and ADP. During this time, the muscle starts rigor mortis, and the

concentration of NADH in the fish tissue has descended, causing the ATP to degrade into

ADP. We can conclude that the descending of NADH means the start of rigor mortis of fish

muscle. Collagen type I and type V have been proven to participate in the tenderization of

tissue in postmortem and are components of muscle structure [29, 30]. In the change of the

postmortem fish muscle structure, the collagen in the connective tissue degrades and

transforms. The transformation of the collagen structure participates in the process of muscle

proteolysis after a fish has died. Collagen is the main constituent of this matrix, which is

responsible for the integrity of the myocommata and the mechanical properties of the muscle.

At the time of collagen decomposition, it softens fish tissue. However, it cannot be proven

39

species (cobias and Seriola dumerili) and body parts (abdomen and dorsum), we are sure

that both collagen and NADH break down in the process of fish spoilage. The NADH and

collagen participate in the postmortem of rigor mortis and the tenderization of fish muscle.

The spectrum that we have established can be applied as a freshness or quality index to

determine the condition of fish muscle.

4.2 The optical index G

The optical index is built up by the fluorescence intensity of the 470 and 430 nm

emission wavelengths at 330 to 360 nm excitation wavelengths. After the process of

normalization, we have found that both G(470,exci) and G(430,exci) have a descending trend

with storage time. The range of G index is approximately from 1.5 to 0.5. However, it is

different from fish to fish. The optical index value has a large standard deviation in both

cobias and Seriola dumerili after several hours of storage time. In some fish cases, we do not

get the clear descending result. We consider that there are many factors affecting the

experiment result, e.g., the growing environment, temperature, slaughter method, and

experimental error [27, 28, 31]. In summary, for the eight Seriola dumerili, on the whole, the

value of G(470, exci) and G (430, exci) are negatively correlated to the K value within 24

hours. The correlation can be established only when it can be ensured that the fluorophores do

not initially degrade. If the fluorophores initially degrade, the descending trend of the G index