General trends in carp farming
453
In the period studied, 0.374 thousand tons of K1 Were stocked annually
(arithematical mean) into the fattening ponds to produce table fish; 1.9405
‘
thousand tons of K2 were stocked annually. The correlation between stocking K1
in the rearing ponds to produce K2 (z3) and K
production (z6) is expressed
by the coefficient of correlation r = 0.9397 (P > 0.001) and the regression
equation :
y6 = 0.7498 + 2.0585z3
Substituting the average stocking rate of K1 used to produce table fish
(0.374), for z3, we obtain a K2 production of y6 = 1.5197.
The regression equation between K2 stocking in the fattening ponds (22)
and the production of K2 (y6) is :
22 = —0.071 + 0.8995y6
the coefficient of correlation being 0.9919 (P > 0.001). Substituting this
additional K2 production of 1.5197 thousand tons for y6 in this equation, we
obtain the additional amount of K2
available for stocking into the fattening
ponds; this amount is 1.2960 thousand tons. If it was used to produce table
fish, average K2 stocking in the fattening ponds (ZZ) would equal :
ZZ =
1.9405 + 1.2960 = 3.2365 thousand tons.
The multiple regression equation between table carp production (y5) and rate
of stocking the fattening ponds with KI (21) and K2 (22) is :
y5 = 3.6094 + 3.106821 + 1.7545z2
If zl = 0 and 22 = 3.2365, table fish production is y5 = 9.288 thdusand
In the period studied, the average annual production of table carp amounted to
8.176 thousand tons,
i.e.
1.112 thousand tons or 13.6 % less.
,
The economic consequences of this result are obvious. They are all the
more
so
since increased production of K2
would certainly require much less
additional cost than the additional profit obtained from increased production
of table fish.
'
Also, when linear correlation between table carp production (y5) and
stocking the fattening ponds with K2 (ZZ), (paying no attention to stoch1ng
With K1 —zl—) is calculated the coefficient of correlation is very Slgnlf1—
cant
(r = 0.6724, P > 0.001). Using the method of partial correlation, the
effect of stocking with K1 is eliminated from this dependence and the resul—
tant coefficient of partial correlation increases to 0.7630. Thus, it can be
concluded that stocking K1 in the fattening ponds has a specific negative
effect on the final production of table carp.
If this is so,
the potential increase of table carp production, estimated
as
1.112 thousand tons,
is underestimated. This could be due to the fact that
the calculations were based on a multiple regression equation in which thls
negative effect of stocking With K1
is
integrated, even when its numerical
value is reduced to zero.
453
In the period studied, 0.374 thousand tons of K1 Were stocked annually
(arithematical mean) into the fattening ponds to produce table fish; 1.9405
‘
thousand tons of K2 were stocked annually. The correlation between stocking K1
in the rearing ponds to produce K2 (z3) and K
production (z6) is expressed
by the coefficient of correlation r = 0.9397 (P > 0.001) and the regression
equation :
y6 = 0.7498 + 2.0585z3
Substituting the average stocking rate of K1 used to produce table fish
(0.374), for z3, we obtain a K2 production of y6 = 1.5197.
The regression equation between K2 stocking in the fattening ponds (22)
and the production of K2 (y6) is :
22 = —0.071 + 0.8995y6
the coefficient of correlation being 0.9919 (P > 0.001). Substituting this
additional K2 production of 1.5197 thousand tons for y6 in this equation, we
obtain the additional amount of K2
available for stocking into the fattening
ponds; this amount is 1.2960 thousand tons. If it was used to produce table
fish, average K2 stocking in the fattening ponds (ZZ) would equal :
ZZ =
1.9405 + 1.2960 = 3.2365 thousand tons.
The multiple regression equation between table carp production (y5) and rate
of stocking the fattening ponds with KI (21) and K2 (22) is :
y5 = 3.6094 + 3.106821 + 1.7545z2
If zl = 0 and 22 = 3.2365, table fish production is y5 = 9.288 thdusand
In the period studied, the average annual production of table carp amounted to
8.176 thousand tons,
i.e.
1.112 thousand tons or 13.6 % less.
,
The economic consequences of this result are obvious. They are all the
more
so
since increased production of K2
would certainly require much less
additional cost than the additional profit obtained from increased production
of table fish.
'
Also, when linear correlation between table carp production (y5) and
stocking the fattening ponds with K2 (ZZ), (paying no attention to stoch1ng
With K1 —zl—) is calculated the coefficient of correlation is very Slgnlf1—
cant
(r = 0.6724, P > 0.001). Using the method of partial correlation, the
effect of stocking with K1 is eliminated from this dependence and the resul—
tant coefficient of partial correlation increases to 0.7630. Thus, it can be
concluded that stocking K1 in the fattening ponds has a specific negative
effect on the final production of table carp.
If this is so,
the potential increase of table carp production, estimated
as
1.112 thousand tons,
is underestimated. This could be due to the fact that
the calculations were based on a multiple regression equation in which thls
negative effect of stocking With K1
is
integrated, even when its numerical
value is reduced to zero.