A variety of methods are used for identification, but morphometric and meristic phenotyping is considered one of the first and most valid ways for fish species identification in fish biology (El-Saidi et al. 2017). Another application of morphological and meristic traits in aquaculture is the measurement of hormone treatment (Yanong et al., 2010). The length-weight relationship (LWR) is an essential measure to understand the growth dynamics of a fish population, and it is used to calculate the growth rate in fisheries research (Bintoro et al. 2019).
Hossain et al. Liza subviridis was studied by Khan et al. 2013) due to its length-to-weight ratio and the condition factor on India's south-east coast. 9 | Str In the Pinang Estuary, Malaysia, Liza subviridis was studied by Zolkhiflee et al. 2017) for length-to-weight ratio and relative fitness factor.
Liza subviridis and Sillago sihama were studied by Gondal et al. 2014) in Sonmiani Bay (Miani Hor), Pakistan, for different morphometric traits. To assess the taxonomic importance of certain morphometric and meristic scale features in four mugil belonging to the family Mugilidae, Zubia et al.
Sampling area
Working schedule
Sample collection
It is a probability sampling method where the entire population is divided into equal groups to carry out the sampling process. To avoid bias, three related measures were categorized into small, medium, and large samples that were taken as a sample to represent the population.
Sample transportation
The laboratory measurements were done in the Oceanography laboratory under the Faculty of Fisheries of Chattogram Veterinary and Animal Sciences University as shown in Figure 4. Measured the total weight of the sample and also measured the weight of the single sample. The graphic representation of the morphometric and meristic characteristics was also recorded during this study.
Morphometric characters
Forepelvic Length (PrVL) = Length of fish in sentimeters from that very first point of head to beginning of that pelvic fin base. Pre-dorsal Length (PrDL) = Length of fish in sentimeters from that very first point of head to beginning of dorsal fin base. Pre-anal Length (PrAL) = Length of fish in sentimeters from that first point of head to anal-fin base.
Species identification
Formula of Shannon Diversity Index (SDI)
CHAPTER FOUR RESULT
- Identification of the Species
- Species availability
- Intra-species variability
- Chelon parsia
- Liza subviridis
- Morphometric characteristics
- Regression
- Meristic counts
- Univariate analysis (ANOVA)
- Principal Component Analysis (PCA)
It can be found in the South Asian countries of India, Bangladesh, Nepal and the rivers and estuaries of Myanmar (Rahman, 2005). This section shows data on the morphometric and meristic characteristics of the mugil species collected through monthly sampling. Here applies: TL = Total length, SL = Standard length, HL = Head length, PrOL = Preorbital length, PrPL = Prepectoral length, PrVL = Prepelvic length, PrDL = Predorsal length, PrAL = Preanal length, BP = Depth of the body.
Description – TL= total length, SL = standard length, HL= head length, PrOL = preorbital length, PrPL = prepectoral length, PrVL = prepelvic length, PrDL = predorsal length, PrAL = preanal length, BD = body depth. Preorbital length, PrPL = prepectoral length, PrVL = prepelvic length, PrDL = predorsal length, PrAL = preanal length, BD = body depth. Description - TL= total length, SL = standard length, HL= head length, PrOL = preorbital length, PrPL = prepectoral length, PrVL = prepelvic length, PrDL = predorsal length, PrAL = preanal length, BD = body depth.
29 | Scroll against the total length of Rhinomugil corsula, Chelon parsia, Mugil cephalus and Liza subviridis shown in figure 14. In other cases on the experiment, the relationship between total height and body weight is depicted in figure 15. For Mugil cephalus, Total length and weights are quite similar, also Liza subviridis weights are close to total length.
The linear relationship between total length and standard length (SL) in the graph showed that R2 = 0.978 (Figure 16). The linear relationship with total length predicted 97.8 percent, 96.8 percent, 87.3 percent, 77.6 percent, 98.6 percent, 94.4 percent, 53.6 percent, and 77.8 percent of standard length , head length, pre-orbital length, pre-dorsal length, pre-pelvis length, pre-anal length, and weight. To see if there was a difference in the mean of different parameters between two separate species groups, an independent t-test was used. Independent T-test analysis illustrated that all parameters showed a significant difference between the mean in the case of Rhinomugil corsula, Chelon parsia and Mugil cephalus.
Here, HL, PrPL, PrVL, PAL, PrDL revealed a significant difference in the case of Rhinomugil corsula. The value of the meristic counts in this study almost corresponds to the previous research results. As part of the findings, the results section showed that there were both similarities and differences between the species.
Analysis of variance is used to determine the influence that independent variables have on the dependent variables in a study. Preanal (PAL) and predorsal length measurements contributed to the first discriminant function, while the remaining six [pre-orbital (PrOL), pre-pelvic (PrVL), head (HL), standard length (SL) and total length (TL)] measurements contributed to the second discriminant function according to the pooled within-group correlations between the discriminant variables and the discriminant functions (Table 10).
CHAPTER FIVE DISCUSSION
Variation of meristic counts
Meristic features such as dorsal, pectoral, pelvic and anal fins of the population showed no significant differences in the present study. In the genus Mugil, phenotypic plasticity resulted in the discovery of three new species: Mugil curema, M. Compared with the interaction of morphometric factors, meristic features such as the number of branchiospines on the superior and inferior sections and the number of microbranchiospines on the first branchial arch made clear distinction between species.
In another study, regarding morphometric and landmark data, the initial discriminant functions (DF) explained 89.8% and 83.33% of the variance, respectively, while the second DF explained 10.2 percent and 16.7 percent, respectively, including among group differences that should explain 100 percent of the number among group variations (Hossain et al. 2015). The well-separated stock groupings were not revealed by plotting discriminant functions for morphometric and truss network metrics.
Variation of morphometric counts
The strongest correlation was found between TL and SL, TL and HL, and TL and PrPL cells, with r = 0.98 and two-sided significance with p = 0.01. Murugan (2012) conducted a comprehensive study on Mugil cephalus in the Vellar Estuary from January 2004 to December 2005. Regression coefficient 'b' and 'a' tests were performed to compare b values of males and females from the theoretical value of 3.
ANOVA showed that only prepelvic length (PrPL) was significantly different at p=0.05 degrees between the four population subgroups based on nine morphometric measurements (Zubia on el. 2015). It is possible that the different environmental circumstances of these habitats may be the basis for the morphological differences between populations from different places. A study was conducted (Renjini, 2011) in which morphometric measurements and meristic counts of different body parts were performed.
As a result of the study, it was concluded that Liza parsia grew well in the Cochin estuary. Compared to almost any other vertebrate, fish have a wide range of morphological variation within and between populations and are more vulnerable to environmentally induced morphological changes (Allendorf, 1988). Because fish have high phenotypic plasticity, humans alter their physiological and behavioral changes to easily adapt to the changing environment, which generally changes their morphology (Stearns et al., 1983).
As a result, analyzing only gross morphometric and meristic traits may cause minor morphological variations in fish by making minimal environmental differences unthinkable to detect. Discriminant function analysis (DFA) can be a useful method to focus on different stocks of the same species, which can be useful in effective stock management initiatives (Karakousis et al. 1991). 41 | Page discrimination was ensured by canonical discriminant functions, which examined the pictorial analysis for each sample.
In the case of morphometric characters, both discriminant function analysis (DFA) and canonical discriminant functions suggested that Mugilidae populations have a lower degree of phenotypic differentiation in all three stations. Based on morphometric measurements, canonical discriminant functions suggested that populations of Mugilidae were similar among fish samples from three different stations. This similarity between the population can be attributed to a shared geographic location (Allendorf, 1988) One hundred percent of participants were correctly categorized in a discriminant function analysis (Khayyami, 2015).
Identification of principal components analysis
CHAPTER SIX CONCLUSIONS
CHAPTER SEVEN
RECOMMENDATIONS AND FUTURE PERSPECTIVES
Length-weight ratio and condition factor of gray mullet, Mugil cephalus Linnaeus, 1758 from Pulicat lake, Tiruvallur (dt), Tamil Nadu. A new distribution of the buffoon's river chub, Zenarchopterus buffonis (Valenciennes, 1847) in the southern coastal rivers of Bangladesh. Landmark-based morphometric and meristic variations of the endangered carp, kalibau Labeo calbasu, from stocks of two isolated rivers, the Jamuna and Halda, and a breeding site.
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Impact of fishing exploitation and climate change on the stock of cephalus cephalus in the Taiwan Strait. Phenotypic variation in Snowtrout Schizothorax richardsonii (Gray,1832) (Actinopterygii: Cypriniformes: Cyprinidae) from the Indian Himalayas. Freshwater Fishes of Bangladesh, First Edition, Zoological Society of Bangladesh, Department of Zoology, University of Dhaka, Dhaka-1000.
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APPENDICES
BRIEF BIOGRAPHY OF THE AUTHOR
