International Journal of Aquaculture, 2015, Vol.5, No.7 1
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and Whitehead, 1974), and then by Golani and Sonin
(2006). Recently, its biological characters have been
studied in different regions (ElHaweet, 2013).
N.
japonicus
is widely distributed in the Indo-Pacific
Ocean, and Mediterranean Sea, and can be fished all
year around in coastal areas of the South China Sea.
Pampus argenteus
is widely distributed along the
coastal areas of the Indo-West Pacific (Azad et al.,
2007) which is an economically important fishery
species of China Sea, Bay of Bengal and Arabian Sea
(Almatar and James, 2007; Shi et al., 2009). However,
the wild resource of this species is under threatened
due to over fishing. Long term survey indicates that
the market size of
P.
argenteus
reduced dramatically,
and the resources are deteriorating in China (Liu and
Zhan, 1999).
The present study measured basic morphological
characters and estimated the length-weight
relationship of wild collected
P. sextarius, N.
japonicas
and
P. argenteus
from the Fiery Cross Reef,
South China Sea. Results from this study can provide
biological information to conserve the natural resource
of these species in South China Sea.
1 Materials and methods
In November 2013, a total of 187 samples of three fish
species were collected from Fiery Cross Reef of the
South China Sea (9
o
37’ N, 112
o
58’ E). Samples were
kept in ice after collection, and taken to the South China
Sea Fisheries Research Institute, Chinese Academy of
Fishery Sciences. Upon samples’ arrival, morphological
studies were immediately conducted (Table 1).
Table 1 Numbers and sizes of samples collected from Fiery Cross Reef
Length(mm)
Weight(g)
Species
Numbers
Min-max
Mean±SD
Min-max
Mean±SD
Polydactylus sextarius
66
100.36-119.43
110.10±4.89
10.04-45.42
38.44±.17
Nemipterus japonicus
52
88.37-159.54
132.08±19.48
22.42-128.39
86.01±32.71
Pampus argenteus
69
75.13-92.07
81.53±3.32
20.58-42.27
26.70±3.99
1.1
Measurement procedure
The fishes’ weights were measured using an electronic
balance (accurate to ± 0.01g). A SONY (NEX-F3)
digital camera was used to capture the images of the
187 fish samples with a calibration ruler placed in
down-side view in each image. The image analysis
software of Matlab (R2011a) was used to perform the
morphometric data analyses. The truss network
consisted of 12 landmarks to describe the major
features of
those fishes including (A) origin of the
pectoral fin, (B) tip of maxillary, (C) origin of the
pelvic fin, (D) top of operculum, (E) origin of the anal
fin, (F1 or F) origin of the first dorsal fin, (F2) origin
of the second dorsal fin, (G) end of the anal fin, (H1 or
H) end of the first dorsal fin, (H2) end of the second
dorsal fin, (I) ventral attachment of the caudal fin to
the tail, and (j) dorsal attachment of the caudal fin to
the tail. Morphometric character including (1) body
length, (2) height, (3) head length, (4) head height, (5)
snout length, (6) eye diameter, (7) caudal peduncle
length, (8) caudal peduncle height, (9) the first dorsal
fin length(or dorsal fin length), (10) pectoral fin
length, (11) pelvic fin length, (12) anal fin base length,
(13) anal fin length, and (14) the second dorsal length.
The selection criteria for these landmarks must be
linked closely to the skeletal structure of
P. sextarius
,
N. japonicus
and
P. argenteus
, easily observed and
assessed by eye. Lengths of the truss between these
landmarks were measured according to the method of
Hockaday et al. (2000), where all the distance
measured in the study were assumed to represent
straight lines lying on the same plane.
1.2
Statistical analysis
The relationship between body length (
L
) and wet
weight (
W
) were calculated by the power regression
W
=
aL
b
(PASW Statistics 19.0). Values of the
exponent
b
provide information of fish growth. When
b
= 3, the increase in weight is isometric. When the
exponent value of
b
> 3, the weight increase is
positive allometric, and when
b
< 3 the weight
increase is negative allometric (LeCren, 1951). All the
truss measurements were log transformed and tested
for normality using the SPSS 19.0.
Significant correlations between body size and truss
measurements were found in this study. The absolute
measurements were transformed into size-dependent
shape variable to perform further analysis. The
transformation method was done following Nie et al.
(2014), using the equation:
BL
BLmean
D
Dtrans
