Glycemic Takahiro
response
Nishirnune,
Sumio
Tsumoru
Nakahara,
Tomio
ABSTRACT
The
dietary fiber relationship
and fiber Yakushiji,
Ichikawa,
proposed
pirical
was
equation were
obtained also
(IDF).
The
obtained two
lation coefficient the IDF regression for SDF
Sumimoto,
Kunita
mechanisms
by using a nonlinear
DF
Tatsuo
and Nobuharu
for the action
of
(0.780),
but
ofSDF
stronger of SDF
dependency in the TDF
newly regression
reported curve.
total DF The em
l9.9X#{176}322. Similar
=
for soluble
regression
between curve
bohydrate)
Y
the
DF
curves
(SDF)
insoluble
that
the
observed GI and GI calculated (0.78 1) was virtually identical a given
gave
content
a lower
(eg,
GI (39)
did
IDF
car
GI to predict published GI.
such
WORDS
Glycemic
index,
dietary
fiber,
G11, glycemic
response
Introduction The
dietary
the glycemic Mechanisms
fiber
(DF)
component
offood
response in patients for the hypoglycemic
with effect
posed (2, 3) and some representative as follows: 1) DF can retard the rate
is thought
to lower
diabetes mellitus of DF have been
theories ofdigestion
(1). pro
are summarized afstarchy poly
in the upper
of absorption
small
intestine;
and
of monosaccharides
5) DF
through
can
the
lower
the
micravilli
rate
of the
epithelial cells in the jejunum and upper ileum. In 1, 4, and 5 above, the functions of DF are probably nonlinearly dependent an the concentration of DF. The effect of DF as a substrate analogue ofan enzymatic reaction or the effect of DF
as a competitor
of sugar
uptake
based an the binding sites being an increase in DF concentration,
through
saturated because
a membrane
asymptotically in both cases
that
extent
the
relative
increases
(2).
We deduced
effects responses 414
of DF
mentioned
in the utilization
above,
to which
pastprandial
that the GI represents together
ofblood
with
glucose.
other
blood
the overall physiological
Therefore, tm J C/in
we tried Nuir
(8) or boiling
for a
of cellular
structures
that
bind
chemically
processing,
an effect
states,
by heat
on the value
ofGI.
or physical
1 and 2 are factors
to be predominant
Because
it is difficult
in usual
to use
in the literature
usually
for determining nonetheless
DF more GI value,
it appears
a large
number
and
enzymes. desirable to 3, DF of starchy effect by
content
to be much
of subjects,
variation.
the
Similarly,
in foods easier we tried
accurately than GI. Therefore, which was unknown, from the available
Materials
increase
diets.
show some
the DF
might
that
the accessibility ofstarchy polysaccharides to digestive Specific GI values for various cooking conditions are information for diabetes mellitus patients. In relation might be considered to be a natural structural analogue palysaccharides acting as an inhibitor. The role of this
or subcelchem
is not
per
to determine to predict the
DF data.
methods
Available GI data (2, 4, 9 1 5), TDF data by Prosky’s (16), and IDF and soluble DF (SDF) data (1 723) were
method collected
is
with each other for the same binding approximate a linear regression line (GI) has been accepted as an index
indicates
butter
pro
foods (7), pal2) cooking,
or structural
with DF and
the innate substrate compete site. This effect might not (4, 5). The glycemic index sugar
1) food
as follows:
for preparing instant refining or powdering; or peanut
most
there are physio
ical
but
rides
are
of the
response, postprandial
exert
DF seems
of polysaccha
factors
total
as reported
in various ofthose
method
of hydrolysis
Some
a puree
complexity
fect,
rate
(6).
GI and
the hypoglycemic
structurally with the starchy polysaccharides lular organdIes. Hence, the extent ofdestruction
the
the
between
whether
by insoluble DF (IDF) regression model (5). of a food might be one
as processing (2), or excess
as preparing
intestine;
lower
curve
longer period (2); 3) other food components, such as antinutrients (6) that retard the amylase activity by chelating calcium ions (eg, phytic acid), accelerators for membrane sugar transport (sodium ion), or amylase stabilizer (chloride ion); and 4) the chemical nature of starchy polysaccharides, eg, amylose or amylopectin, which might affect the rate of digestion, together with
GI values
can
regression
for the prediction of glycemic to consider in foods far the
outcome
saccharides in the stomach; 2) DF can retard the rate of passage of the contents of the stomach into the duodenum; 3) DF can lower the rate of diffusion of various saccharides in the small 4) DF
Konishi,
we investigated
effect was exerted mainly with use ofthe nonlinear Although fiber content
the KEY
a nonlinear
cessing, such ishing grains
This
Yosimasa
Further,
logical
of GI on SDF suggests a major function hypoglycemic effect. From the regression
curve of 01 vs TDF, we propose a supplemental the glycemic response to foods with no Am J CliiiNutr l99l;54:4l49.
to construct
from to that
(48).
foods13
Taguchi,
corre
5% vs available
than
Syuzo
reliable clues other factors
regression
and
indicated
of some
DF (TDF).
(DF) on the glycemic response suggest a nonlinear between glycemic index (GI) and DF content. This
relationship was analyzed (TDF) values, assuming curves
content
I
1991:54:4149.
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From
the Osaka
Prefectural
Institute
ofPublic
Health,
Osaka,
lapan;
the Ministry of Health and Welfare, Tokyo; and the National Institute of Health and Nutrition, Tokyo. 2 Supported in part by a research grant from the Iapan Ministry of Health and Welfare. 3 Address reprint requests to T Nishimune, Osaka Prefectural Institute at Public Health, 1369 Nakamichi, Higashinari, Osaka 537 Iapan. Received October 16, 1990. Accepted for publication January 9, 1991. Printed
in USA.
© 1991 American
Society
for Clinical
Nutrition
GLYCEMIC from value
literature. far each
When mare than food was obtained
TDF
and available fresh
foods water
were converted content measured
Most
edible
portion
GI data are reported
hand,
GI data
boiling
change
general
and
between
bailed
be 56 (vs glucose) rice
bailed
5 and
this
for
(2),
study. There are
by using
few
plus
SDF
[mainly
modified Prosky’s
versions] method
available
carbohydrate
standard of TDF ference
values
table of the
value method
reported
case
by dividing
obtained
had
vs white by
been
Two adopted
different the value
in data
was
described
in Table
sample
used
seemed anese).
to be different The content
tween
strains
of
TDF
GI
from that of available
pumpkin
in
total
(25)
were
author
In the
determination
In
equations,
we
to elaborate
the
values. of reported
adopted
the
equations, the
predicted analyses
the
most
regression same
conversion
functions.
calculation
of variables
calculations
were
a personal
computer
carried
out
by
the
and we deviation analysis
of the
regression
were
by an original
ofsoluble
regression followed
logarithmus. BASIC
after The
program
on
in IDF
equations
beiveen data
total in Table
dietaryjiber
and
I , we evaluated
glycemic
4. 4 as was
1. The
linear
to a multiple the equation
4type
curve.
We
expression TDF,
car1
propose
for the
but
the
oh
theoretical
to be elucidated.
fibers
and
(5) reported that foods rich in SDF low blood glucose responses and that
were
traditional SDF
most
closely
different
related
understanding
The
importance effect
equation.
fitted
ofthe
from
in Figures
improved
a simple
linear
the coefficient
ofdetermination
to be much
smaller
than
Soluble
insoluble
the
type
shown
our
3, both
regression
equa
by
changing
(Eq
the
1) to the power to 0.781 of SDF was
SDF is expected
r2 against
value
of IDF
2 and
type (Eq 4) from 0.665 to 0.780 and from 0.724 for SDF and IDF, respectively. If the contribution small,
from
BS by using
powercurvetype
coefficients
equation
perspective
function
contribution
ofpostprandial
As shown
similar
correlation
This
of DF
do not uronic
(1).
the relative
regression
to GI.
interpretation
in the repressing
derived
and
When
in Table
2.
dietart’jiher
we consider
content
of DF
relationship give
in IDF.
For
‘20
for SDF
smaller
fiber
concentrations
hydrate)
the
for IDF).
This
a greater response
0.5
the could
GI was
g fiber/g
minor,
but
0.05
even
2 and
g fiber/g
greater
was
(38.5
because
GI.
the than
predicted 3), and
available
as indicating
function
and
in SDF the
(Figs
did IDF on the determination We also deduce that IDF
a small,
type
GI
carbohydrate,
(eg, was
DF
lower
25 for IDF
fact was interpreted
not
of the same
between
a much
available
and
difference
effect than of a food.
for
carbo
for
SDF
vs 47.9
that
SDF
exerted
ofthe glycemic might have same
the
regression
curve
applicable.
qfglycemic
the
four
=
dietary
The
response
(4,
regression
(1)
Y
=
AeB
(2)
Y
=
AB’
(3)
Y
=
B
(or
lnY
=
lnA
+ B laX)
(4)
Downloaded from https://academic.oup.com/ajcn/articleabstract/54/2/414/4694211 by St Bartholomew's & the Royal London School of Medicine and Denistry user on 24 March 2018
or SDF
afnot by using
GI
GI. Until vide
being the
tile
curve
regression
estimate.
se accompanies data but
(GI
curve predicted are shown
to confirmation
is available,
same
in Figure
most
the GI values
regression
obtained response)
is open
per
small,
the true value
a useful
from
of plotted
to predict
amples ofvalues index afglycemic of the
ofGI
deviation
SD. We tried
A + BX,
index
fiber
measurement
12). The
impression
of the types
Y
of
equation obtained
in Figure
and
av
value equation
1 improved by changing
GI
the
smallest
we adapted The equation
as an empirical
consistent
between
the
is shown
0.62 0.658
is still
not
powercurvefitting
between
a slightly
to total
the
could
(27).
Results
Using
=
was
difference
to an equation
Wolever produce
Prediction
Relationship
R
dietarv
Recently, necessarily
same
method
nonlinear
of Y(=GI)
African)
regression
natural
Role
=
this
values,
the
r
equation
with
using
procedures into
for the
IDF and SDF
leastsquares For
basis
regression
(South
data general
and
for the
the graph
relationship
tions.
equations the multiple correlation coefficient (R) was calculated as the square root of the coefficient of determination between observed and In statistical
for
line
were
because
nonlinear
predicted
equation
We studied
used for chemical analysis (Japcarbohydrate varies greatly be
squashes.
used
and
obtained
regression
served
shown),
all these results together, curve for GI to TDF.
regression
this
not
was
19.9X#{176}322, and
=
the
1).
reported, artificial
(3).
Y
presents
vs glu
values
furnished
for pumpkin
was
acids
GI had
data
GI
2, the value
or its
Japanese
the
into and
t test
correlation coefficient relation coefficient of
subtractiondif
(Table
the value
for
the sum
When
1 8 ofthese
by another
pumpkin
used
to on the
by the
the
(data data.
of observed
type
for
the TDF value by from averaging. The
carrots had been 1 because a possible
1 , we excluded
brawn
equation
of DF
method
it was converted and
to
boiled not
When
DF determination
GIs for in Table
rice were
values).
As a result,
items,
of differential
the
being corrected for the amount value (the original available
obtained
bread,
of instant
referred
crudefiber
1 .44.
for 33 food
data
(24) after crudefiber
by using
been
were
3 was ‘60 the observed
Considering the regression
GI values
determination
greatly from were excluded
2 and
(0.589)
foods
is reported
regression
be explained when the value of X(=DF) was zero. When DF = 0, GI = A and the value ofA for the regression equations
erages
other
in same
rice
Southgate
exponential
are
specified
415
FIBER
not
with
By studying
brawn
method.
differed
the
with
we avoided
differential
by the
( 16), some
nutrition instead
carbohydrate
data
of the
For
When
GI
values
DIETARY
the
they
On
values
latter
for dry
when
(2).
DF,
other
all of the
results
the
or parboiled
the enzymaticgravimetric
of IDF
the
with
6 mm
but
that
eg, GI for brown
together
data
along
conditions GI and
foods,
I and
25 mm
it is clear
a single data for
by using
condition.
are published
bailing
IDF foods (24).
cooked
the cooking
AND
as the percentage
and
are usually
foods
these
relationship
for specifically
that
without
with
SDF
into values for fresh for Japanese foods
of some
conditions,
might
are presented
of foods,
for foods
eaten
one value was reported, by averaging. Because
carbahydrate
of the
INDEX
variation
1 may
data
are well
from
the value
in Figure
give within
however,
1 or 2 and
cx
or fiber validity
measurements the GI
the
of TDF
from fiber. GI, in Table 3. The
by actual
the
may
of pro
416
NISHIMUNE
TABLE 1 GI, total DF, soluble
DF, insoluble
DF, and available
Average 01
Food
Reference for GI
carbohydrate
ET
AL
values
Available carbohydrate
TDF : carbohydrate
TDF
%
%
60.5 70.2 45.6 43.2
7.50 5.30 2.60 5.20
0.057 0.120
70.7
2.72 2.92 0.72 4.70 2.89 2.30 1.35
Average SDF
Average IDF
Average TDF
Reference SDF and
%
%
%
0. 124



0.075



1.00 2.30
1.03 3.11
2.03 5.33
0.038 0.042 0.010 0.071 0.035 0.085 0.085
1.5 0.84 0.16
1.4 1.90 0.65
2.9 2.74 0.87


1.12
1.58


1.11
1.55
3.40
0.067



1.40 7.66 2.50t 19.8 5.20 16.0 0.20 1.00 7.74 3.00









5.2 0.56
16.5 4.96
21.7 5.52









0.65 0.64 0.3
3.93 0.93 1.4
4.58 1.57 1.7
19 (78.5% 23 21
for IDF
1 Oatmeal
64
9
2 Barley
22
14, 2
3 White bread 4 Ryebread
71 42
4, 10, 13 9
5 Spaghetti 6 Brown rice 7 White rice 8 Buckwheat 9 Corn flakes 10 Sweet potato 11 Potato
47 63 61 51 83 49 54
4, 12, 14 4, 12, 2 4, 10, 12, 14 4, 12, 2 4, 10, 12, 14, 15 4, 12, 2 9,4, 10, 11, 15
12 Potatochips
55
15,2
13 14 15 16 17 18 19 20 22
Yam Peanuts Broadbeams Kidney beans Peas Soybeans Milk Sausages Greenpeas Pumpkin
51 I1 80 33 51 15 34 28 23 75
4, 12, 14, 2 4, 13, 14, 2 4, 14 4, 12, 2 4, 12 4, 12,2 12, 14 4, 2 9 13
15.9 S 1.0 19.4 1 1.1 I5.2 38.0 20.0 21.4 4.3 3.7 9.0 5.9
23
Sweet
58
4, 12, 13, 14, 15, 2
21.5
2.00
0.073 0.690 0.164 0.521 0.260 0.748 0.047 0.270 0.860 0.508 0.093
24
Carrot
16
ll
4.6
2.55
0.554
1.56
1.62
3.19
18,23,19
25
Orange Grapefruit Plum Pear Bananas
0.81 0.22
0.58 0.94
1.90 1.16
(86.5% water) 19 (87.9% water) 23
21
27
28 29 30
corn
31 Grapes 32 Raisins 33 Apples
S
The water
content
69.9 75.1
65.8 82.2 27.1
43 26 24 33 61
9, 4, 12, 13, 14, 2 9, 12, 14 12, 14 12, 14 4, 10, 13, 12, 14, 2
9.9 7.6 9.0 I3.5 21.4
1.9011 0.70 0.80 1.70 1.48
0.192 0.092 0.089 0.126 0.069
43 64 39
12, 14 4, 12, 14 9, 4, 1 1, 12, 14, 2
14.2 79.7 12.0
0.40 4.60 1.63
0.028 0.058 0.136
shown
is the value
used for the correction
t NDF plus pectin (26). t Excluded from the analyses and graph drawings § References 4 and 14 were not used (see text). II From the Sauthgate method (25).

0.46 
0.49



3.84 1.51






1.26
1.90
response.
In this
0.63
Regression
ofGI
contains
the
above
the preprandial
equation
ofwhite total
bread
amount
value.
or dextrose of blood
This
integral
composed of two parts of rising and tians. In the former part, absorption and
ileum
at the glucose
initial into
into
the
blood
stream
stage whereas cells of organs
actual blood sugar curve could two curves describing the two
would from
be restricted the alimentary
to the steps tract
to be dominant
and
before should
is
at least
part, uptake of blood to be dominant. The
be regarded parts. The
as the
sum
of the
effectiveness of DF the absorption of sugars
be analyzed
in the
farmer
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whole
the effect ofDF kinetics, two
postprandial
tract
measurements
increments
falling glucose concentraof glucose in the jejunum
seems
ofthe
the digestive
(as the reference
glucose
area of increments
in the latter was deduced
water)
22 22 (75.7%
water)
water)
23 17, 19 (73.9%
water)
17, 18, 23, 19 (84.3% water)
(see test).
saturation kinetics seems if the available carbohydrate
The concept
20(77.2%
into fresh food.
part
food)
19 (4.4% water)
2.80 0.88
1.04 0.63
Discussion
to a powercurve
19 (36.9% water)5 18, 21, 20 (35.1% water) 21 19 (5. 1% water) 20 (13.8% water)
even
is high enough
ofGI
against
Insoluble
than
might
be analogous
if the
In linear magnitude
GI
soluble
30 mm
itself curves.
DF is consistent
and
and ifdata
earlier
glycemicresponse
part
ofthe
curve,
to be applicable to the reported data (the concentration of glucose) in
dietary
(28,
This
to an inhibitor
is a ratio The
are shown
29). of the
nonlinear
with the
suggests
that
of saturation
integral regression
areas
of
curve
with this concept. fiber
regression the causal inference that determines the of the effect of X an Y is based on the estimated
slope and not on the correlation coefficient (r). We can alter by changing the variance of X or Y, eg, by selecting different
r
GLYCEMIC
INDEX
AND
DIETARY
417
100
100
;;
FIBER
;
50
50
0
0 0
0.2
0.4
0.6
1
I DF
0.8
0
1.0
0.1
0.2
CH
0.3 I DF/
0.4
0.5
C H
FIG 1 . Regression of GI on total dietary fiber. Glycemic index (vs glucose) was plotted vs the value for total dietary fiber divided by available carbohydrate. The regression equation is GI = 19.9 (TDF/CH)#{176}322 and R = 0.658 (n = 32). 4.786, P < 0.001.
FIG 3. Regression of GI on insoluble dietary fiber. Glycemic index (vs glucose) was plotted vs the value for insoluble dietary fiber divided by available carbohydrate. The regression equation is GI = 21.4 (IDF/ CH)#{176}269and R = 0.781 (n = 18). ‘i6 = 5.002, P < 0.001.
foods, without we estimated
foods, but indicated,
from might
the slope ofFigure 2 or 3 to obtain the inference play a mare important role in the hypoglycemic
of DF.
Given
3 1), the
(28,
changing the slope ofthe fitted line (30). Similarly, the magnitude of the effect of IDF or SDF on GI
retarding
the
effect
through the the product. using other
reported
function
ofSDF
importance
of enzymatic
inhibition of the diffusion It is conceivable that this
in which
the scanning the smaller foods
electronmicroscopic sugar molecules
containing
should tribution
complex
be taken of the
both
IDF
into account twa putative
and
and
of IDF.
of SDF
Glycemic
from
sugar
the
absorption
of the substrate and/ar effect could be proved by
of IDF as a whale, on but may originate from
steric
structures
in the
viscosity
to originate
digestion
purified SDF (1). The effect hand, is still to be elucidated
function
of the
was deduced
that SDF response
of IDF
the the
shown
by
observations adsorb or enclose small intestine. For natural
SDF,
both
simultaneously. mechanisms
above
mechanisms
index
In a food
lower the
than
very
low fiber
a certain curve
if we exclude
content
level
(eg, 0.03
may
not
tion
the data
regression
compared
with
the avail
from
predict
the slope
any
could
for white
equation
better
rice
was
of the curve),
meaningful
glycemic
1 it is understandable in many foods. Thus,
(the
ratio
obtained
is 0.01,
(Table
Table
2). This
1),
equa
predict the GIf(a value closer to the published before the data for white rice were excluded
GI) than was possible
not shown). When SDF is available, better GIf (Table 3). It is possible that
different
cultivars degrees
chemical
of the
same
of milling)
analysis
vegetable
were
of broad
TABLE 2 Effect of the exclusion
50
fiber
response for the food. In this part afFigure that variations from the curve are higher
various
(
with
regression
(data even 100
predictedfrom
able carbohydrate, the fiber could not exert a major effect in determining the postprandial blood glucose concentration. Thus, when the value of TDF divided by available carbohydrate is
another
The relative conwould be variable in
analysis by the correlation curves shown in this paper on average, the effect of SDF to be greater than that
used
beans,
of white
we can different
predict foods
or milled in the
oatmeal,
grain
with
GI estimation or barley.
rice as a lowDF
an (eg, and
If we use
food5
Food
excluded
Total
Pumpkin
DF
Soluble
DF
Insoluble
DF
= 32 n 18 n = 18 19.9X#{176}322 GI = 16.6X#{176}28’ GI = 21.4X0269 r2 = 0.43 r2 = 0.61 r2 = 0.61
n
GI
=
GI
=
18.6X#{176}358 GI
r2
=
0
0
0.1
0.2
0.3
0.4
0.5
Pumpkin, white rice
SDF/CH
FIG 2. Regression ofGI on soluble dietary fiber. Glycemic index (vs glucose) was plotted vs the values for soluble dietary fiber divided by available carbohydrate. The regression equation is GI = 16.6 (SDF/ CH)#{176}28’and R = 0.780 (n = 18). ti6 4.986, P < 0.001.
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S
,
dietary
determination.
n
fiber
=
n
31 0.45
divided
by available
=
13.2X#{176}357
r2
=
0.69
carbohydrate:
17
n
17
=
GI
=
r2
20.4X0292 =
0.62
r2, coefficient
of
NISHIMUNE
418 TABLE 3 Glycemic index
predicted
from
ET
AL
fiber (vs glucose)
GI predicted Food
from
Oatmeal
5
6 7 8 9 10 11 12
13 14 15 16 17
18 19 20 21 22 23
24 25 26
27 28 29 30 31 32 33 34 35 36 37
38 39 40 41 42 43 44 5
milled and pressed White bread Rye bread Soft rolls Macaroni and Spaghetti, dry Brown rice grain Halfmilled rice, yield 9596% Undermilled rice, yield 9394% Wellmilled rice Rice bran Saba buckwheat noodle, raw, dry Corn flakes Sweet potatoes, raw tuber Potatoes, raw tuber Potato chips, fried Yam tuber, Ichoimo, raw Peanuts, dried Kidney beans, whole, dry Peas, frozen Broad beans, whale, dry Soybeans, dry Soybean curd (tofu), Momen medium Miso, darkyellow type Okara, residue of soybean curd prep’n Ham, mixed press Sausage, mixed Ordinary liquid milk Green soybeans, immature, raw Green peas, boiled and frozen Green peas. dried Pumpkin, raw Sweet corn, boiled Tomato, raw Carrot, raw root Orange (navel) Grapefruit, raw without membrane Japanese plum European pears without skin Bananas, raw Grapes, raw Raisins Apples, raw without skin Common mushroom, boiled
Calculated
from
the regression
equation
ofGI
22
sumed centage
ofavailable
carbohydrate.
carbohydrate
51 11 33 80 15
28 34 ± 6 47 34
43 23, 38
25
29
43 30 24
61
75 58 38 16 43 26 24 33 61 43 64 39
19 32 47
42 44 38 47 63 50 38 14 =
l9.9X#{176}322(X
33 47
38
TDF/available
carbohydrate).
Pumpkin
was excluded.
13.2X#{176}357(X = SDF/available predict any GIL.
carbohydrate).
See Table
2.
=
analysis, 01) pregood (data
GI not
foods, known
eg, intact cellwall fractions to inhibit the availability
cooking variability
can
and
However,
in the difference
TDF
was
the true varies
as
per
among
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alter the accessibility may be another reason important
reason
by different
to digestive enzymes. for the deviation
for the deviation
methods
carbohydrate, rectly
of foods of plant origin (5), and food processing
are or
This of GI
GI.
determined
to be the available
51 83 49 54
9
±
51
21
we obtained an extremely the data for broad beans
carbohydrate
59 82
31 36 22 13 24 6 38 30 51 20
two measurements in future better (closer to the observed
total
61, 72
27
25
carbohydrate between
l2l
55
from
difference
52 64
42 58 47 63
46
Another The
71 ± 7, 69 ± 5
22
shown). Available
GI reported
52 38
61 69t 89f 20 46 58 44 44 48 46
from the regression equation ofGI = DF content in food is too law (