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Fishery Bulletin 111(4) 
Table 1 
Results of the regression analyses between batch fecundity (BF), relative fecundity (RF), and oocyte 
dry weight (DW) and the variables of total length (TL), gutted weight (GW), age (A), hepatosomatic 
index (HSI), and relative condition index (Kn) for female Argentine Hake ( Merluccius hubbsi) of the 
Patagonian stock obtained from bottom trawls during research surveys in January 2010 and 2011. 
r 2 =coefficient of determination; a and b=parameters of the equation, n=sample size, P=P-value of the 
relationship. The sample size for regressions with age (n = 173) was smaller than the sample size for 
regressions with other variables («=181) because some otoliths were broken or otherwise unusable for 
age determination. 
Relationship 
r 2 
a 
b 
n 
P 
TL 
Power 
0.75 
10.07 
2.74 
181 
<0.01 
GW 
Linear 
0.81 
-64235.60 
675.48 
181 
<0.01 
BF 
A 
Power 
0.68 
38103.41 
1.67 
173 
<0.01 
HSI 
Power 
0.47 
126319.30 
1.17 
181 
<0.01 
Kn 
Linear 
0.04 
-528543.19 
1183337.78 
181 
<0.01 
TL 
Linear 
0.03 
396.99 
2.37 
181 
>0.01 
GW 
Linear 
0.04 
471.76 
0.05 
181 
<0.01 
RF 
A 
Linear 
0.03 
448.49 
15.12 
173 
>0.01 
HSI 
Linear 
0.11 
388.49 
33.56 
181 
<0.01 
Kn 
Linear 
0.07 
21.68 
500.84 
181 
<0.01 
TL 
Logarithmic 
0.18 
2.62 
0.0001 
181 
<0.01 
GW 
Logarithmic 
0.17 
1.48 
0.20 
181 
<0.01 
DW 
A 
Logarithmic 
0.14 
2.31 
0.34 
173 
<0.01 
HSI 
Linear 
0.18 
2.49 
0.08 
181 
<0.01 
Kn 
Linear 
0.05 
2.01 
0.82 
181 
<0.01 
Relative fecundity ranged from 85 to 1040 hydrated 
oocytes g _1 (female weighed without ovaries), with a 
mean value of 526 hydrated oocytes g^ 1 (standard er- 
ror [SE] 183). Positive linear significant relationships 
(P<0.01) between RF and the morphophysiological vari- 
ables of GW, HSI, and Kn were observed, but r 2 values 
were low for all variables, explaining in some cases 3% 
or 4% of the variance (Fig. 3, Table 1). The strongest 
correlation, with an r 2 of 0.11, was obtained with the 
relationship of RF to the HSI (Table 1). 
In the multiple regression analysis of the influence 
of maternal characteristics on BF, 87% of the variabil- 
ity in BF was explained by GW, DW, and the HSI. and 
described by the following equation: 
BF = 5.08 + 0.96LnGW + 1.08LnZ)W (3) 
+ 0.27LnHS7 
(r 2 =0.87, ?i=178, [P<0.01]) 
Most of this variability was explained exclusively by 
GW (95%). The forward stepwise method gave evidence 
that inclusion of other variables did not improve BF 
predictions significantly. 
Egg quality 
For 100 hydrated oocytes, DW estimated from Argen- 
tine Hake females collected during the spawning peak 
in January 2010 and 2011 ranged from 1.8 to 3.95 mg, 
and had a mean value of 2.83 mg (SE 0.36). There 
were significant positive relationships between DW 
and all morphophysiological variables considered dur- 
ing this study: TL, GW, age, HSI, and Kn (Fig. 4, Table 
1). Moreover, positive significant relationships (P<0.01) 
also were obtained between DW and fecundity (BF and 
RF), described by the following equations: 
DW = 2.62 + 0.0003BP (4) 
(r 2 =0.25, n=181) 
DW = 2.42 + 0.0008RF. (5) 
(r 2 =0.16, n=181) 
In general, r 2 values were low for all relationships 
estimated and BF was the variable best correlated with 
DW, although it is possible that size may have some in- 
fluence on this relationship. Regardless, RF, which was 
uncorrelated with TL, also showed a significant posi- 
tive relationship to DW. 
In the multiple regression analysis carried out with 
DW as the dependent variable and morphophysiologi- 
cal variables, only the HSI and GW were included be- 
cause the other variables did not improve DW predic- 
tions significantly. This model explained 20% of the 
total variability, and 90% of this percentage was con- 
tributed by the HSI: 
