Vergara - 1976 - Physiological and morphological adaptability of ri

TEh-TPERATTTRE AND LIGHT, REPRODUCTIVE GROWTH AND RIPENING 209
or ils components). that is. the sensitivity of rice plant to climatic factors in each stage. as far
as this paper is concemed.
However. generally speaking, the difference in RP values may change with the following:
(l) fitness of the model used. (2) the difference in variation ofelimatic factors in each stage. and
(3) the interrelation of climatic thctors among stages when climatic factors in some stage unexpectedly
correlated closely to those in the stage with high physiological response to climate,
high R1 value between climatic factors and plant characters in the former stage may be attained
and lead to misunderstanding.
The models used in Figs. 9 and l3 are polynominal. When some terms in the equation were
not significant in one stage but were significant in another stage. they were not removed. Thus.
this model was intended to fit various types of curves in each stage. Therefore, the differences
in R? values among stages are not considered to be due to fitness of the model.
When we analyze the data from various prefectures with different temperature conditions.
attention must be paid to (2) and (3) items. In order to remove the effect of (2) and (3) items. the
annual data of each prefecture in which (7) and (3) items are negligible were analyzed. The time
courses of RP in this case value were similar to those of Figs. 9 and l3 showing low R‘ value
at heading time.
On the other hand. Matsushima et al. (1961) found that the weight of 1,000 grains and grain
yield were decreased more remarkably by shading at [-16] and [-I4) stage than at heading
stage.
From this evidence. the fact that RI value has less for ripening of yield at heading stage than
at [-20] and [+20] does not mean that the model was not good at the heading stage. but means
that the sensitivity of rice plants to climatic factors is relatively lower at heading stage in
farmers" fields in Japan.
1. The functional relationships between climatic factors and plant response are complex and
differ with stages. although the reactions at one stage have close interactions with those of
other stages. Therefore. it is quite natural that the model for analyzing such complex biological
objectives becomes comples.
‘Lao: l. Was an analysis of tiariancc performed?
2. Was the equation tested for significance‘?
3. If it were tested. what degree of freedom was used’?
ilfimakara: Significance of equations in this report and of R values is checked by F-test. For
example the F value of the equation in Fig. l4 is 77.1 and is remarkably higher than l~‘,;.;.'i=
2.36 at the level of l9». Thus, this regression equation is significant (degree of freedom of error
was 119).
Hovrever, this high F value does not necessarily mean that all terms of the equation are significant.
It might be possible to remove a few terms as long as the R value is kept at significant
level.
FISCHER: Much emphasis is placed on change nf multiple correlation coefficients from one
date to the next. llow can one demonstrate that there are statistically significant changes‘?
ilfimakara: The significance of the difference In R values differs with the levels of R value.
In Figs. 9 and l3. the significant difference in R value is above 0.07 at the level of about 0.3 and
above 0.15 at the level of about (1.5 in R value; thus. the difference in R value between heading
time and [—20] or [+20] stage in Fig. l3 is significant.
NISHlYAhiAI It is very interesting to knovt; that some properties in reproductive growth show
bimodal curves concerning temperature. and a comparative minimum at 27° 30°C.
I suggest the possibility that this phenomenon is explained by Dr. Drost-Hansens water
structure theory which “as discussed in my paper.
The fact that all optimum temperatures appeared in your paper are between 20"‘ and 26"‘C
favors the Wfllfil’ theory.
FISCHER: Since temperature in the pre-heading stage and therefore rate of development
varied considerably between prefectures. would it be better to work out a biological time scale
before calculating the regression‘?
Afunakcitci: As you pointed out, the biological time scale differs slightly with location. even
if it is based on heading time. For example, the period from initiation of panicle formation to
heading time in a cool area (Hokkaido) is S days shorter than that in a warm area (Kyushu).
However the model used in this paper seems to be hardly affected by such a small difference in
biological time scale.