Analysis of color development during roasting of hazelnuts using response surface methodology

Abstract

Hazelnut roasting was analyzed using response surface methodology to find out the effect of process variables on color development during roasting and to establish prediction models. The roasting temperature was found to be the main factor affecting color development. Developed prediction models satisfactorily described color development as a function of roasting temperature and exposure time for L-value, a-value and b-value of whole-kernel, ground-state and cut-kernel measurements. Whole-kernel measurements were significantly lighter in color compared to ground-state and cut-kernel measurements due to internal browning of the hazelnuts during roasting. The results also indicated that the L-value of ground-state measurements, which take into account internal browning during roasting, should be used to monitor roasting of hazelnuts.

Full text

Analysis of color development during roasting of hazelnuts using
response surface methodology
Murat

Ozdemir
a,b,*
, Onur Devres
b
a
Food Science and Technology Research Institute, TUBITAK-Marmara Research Center, P.O. Box 21, 41470 Gebze, Kocaeli, Turkey
b
Department of Food Engineering, Istanbul Technical University, Maslak, Istanbul, Turkey
Received 16 July 1999; accepted 24 January 2000
Abstract
Hazelnut roasting was analyzed using response surface methodology to ®nd out the eect of process variables on color devel-
opment during roasting and to establish prediction models. The roasting temperature was found to be the main factor aecting color
development. Developed prediction models satisfactorily described color development as a function of roasting temperature and
exposure time for L-value, a-value and b-value of whole-kernel, ground-state and cut-kernel measurements. Whole-kernel mea-
surements were signi®cantly lighter in color compared to ground-state and cut-kernel measurements due to internal browning of the
hazelnuts during roasting. The results also indicated that the L-value of ground-state measurements, which take into account in-
ternal browning during roasting, should be used to monitor roasting of hazelnuts. Ó2000 Elsevier Science Ltd. All rights reserved.
Keywords: Hazelnut; Roasting; Colour; Kinetics; Response surface methodology
1. Introduction
Roasting signi®cantly increases overall palatability of
nuts by enhancing their ¯avor, color, texture and ap-
pearance characteristics. These changes are mainly re-
lated to drying and non-enzymatic browning during
roasting (Buckholz, Daun & Stier, 1980; Mayer, 1985;
Moss & Otten, 1989; Perren & Escher, 1996a,b). The
possibility of enzymatic browning is low, since the en-
zymes responsible for enzymatic browning are dena-
tured due to the high temperatures employed during
roasting of nuts (>100°C) (Troller, 1989; Driscoll &
Madamba, 1994). Non-enzymatic browning starts with
a reaction between the carbonyl group of a reducing
sugar with a free, uncharged amine group of an amino
acid or protein with the loss of one mole of water.
Therefore, non-enzymatic browning causes a decrease in
nutritive value due to decreased protein digestibility and
loss of essential amino acids (Ames, 1988; Troller, 1989;
Labuza & Braisier, 1992; Jinap, Wan-Rosli, Russly &
Nordin, 1998). Non-enzymatic browning products also
have anti-oxidant and anti-nutritional properties. Anti-
oxidant properties are associated with the formation of
phenolic type structures and/or the metal chelating
properties of melanoidins (Ames, 1988; O'Brien &
Morrissey, 1989; Nicoli, Elizalde, Pitotti & Lerici, 1991;
Perren & Escher, 1996a,b). Non-enzymatic browning is
stated to be dependent on the temperature and water
activity of the food (Warbeir, Schnickels & Labuza,
1976; Saguy & Karel, 1980; Driscoll & Madamba, 1994;
Rapusas & Driscoll, 1995). Non-enzymatic browning
may develop at varying reaction rates in each section of
the samples due to drying which may cause dierences in
Journal of Food Engineering 45 (2000) 17±24
www.elsevier.com/locate/jfoodeng
Notation
a-value color dimension
b-value color dimension
Bi,Bij model coecients
Ccolor
eerror term
df degree of freedom
fmathematical function
L-value color dimension
MSE mean square error
NS not signi®cant
SSE sum of square error
R2percent variability explained
ttime (min)
Ttemperature (°C)
Ygeneral second-degree mathematical equation
Xcoded independent variables
*
Corresponding author.
E-mail addresses: mozdemir@mam.gov.tr (M. O
Èzdemir),
devres@itu.edu.tr (O. Devres).
0260-8774/00/$ - see front matter Ó2000 Elsevier Science Ltd. All rights reserved.
PII: S 0 2 6 0 - 8 7 7 4 ( 0 0 ) 0 0 036-4

temperature and moisture distribution within the food
and subsequently localized concentration of reactants
(G
o
g
us, Wedzicha & Lamb, 1998).
Color is an important quality attribute of dehydrated
foods (Driscoll & Madamba, 1994). Many authors used
color as a quality control indicator of processes because
brown pigments increase as the browning and caramel-
ization reactions progress (Moss & Otten, 1989; Cam-
marn, Lange & Beckett, 1990). These included onion
drying (Rapusas & Driscoll, 1995), garlic drying (Dris-
coll & Madamba, 1994), rice parboiling (Bhattacharya,
1996), peanut roasting (Moss & Otten, 1989) and ha-
zelnut roasting (Perren & Escher, 1996a,b; Richardson
& Ebrahem, 1996;

Ozdemir & Devres, 2000).
Hazelnuts are roasted to give products a variety of
colors: whitened hazelnuts, golden yellow, dark roast,
and very dark roast. The roasting conditions generally
used by processors are 100±160°C and 10±60 min. Per-
ren and Escher (1996a,b) suggested using roasting tem-
peratures below 150°C with a initial pre-roasting step at
about 135°C, depending upon the desired product.
Quality control of the roasted products is based on color
observations made by an operator to determine the de-
gree of the roasted product (Moss & Otten, 1989). But it
is subjective and selection of a roast on the basis of color
alone could lead to ¯avor defects (Moss & Otten, 1989).
Therefore, establishment of objective quality control
system for hazelnut roasting is necessary, and it requires
determination of the eect of roasting conditions on the
main quality attributes of roasted hazelnuts: moisture
(related to texture), color and rancidity. It also requires
prediction of roasting conditions for a desired color with
acceptable level of shelf-life.
Response surface methodology, a statistical tech-
nique for investigation of processes, is a useful tool to
describe quality indicators during food processing. It
has been successfully applied to food processes (Thom-
son, 1982; Muhadar, Toledo & Jen, 1990; Shieh, Akoh
& Koehler, 1995; Guerrero, Almazora & Senser, 1996;
Kaleo
glu, 1996). Its main advantage is its ability to de-
crease the experimental runs required to provide su-
cient information for statistically acceptable results.
Response surface methodology is also faster and less
expensive than classical one-variable-at-a-time or full-
factorial experimentation (Shieh et al., 1995).
Although the eect of roasting conditions on the
color of roasted hazelnut was previously studied, using
one-variable-at-a-time approach (Perren & Escher,
1996a,b; Richardson & Ebrahem, 1996;

Ozdemir &
Devres, 2000), there is no information about the eect of
interactions of process variables on the color attributes
of hazelnuts during roasting, and about development of
internal browning during hazelnut roasting. Therefore,
in this study the eect of roasting temperature and ex-
posure time on the color of hazelnuts during roasting,
including internal browning, was studied using response
surface methodology. This information will contribute
to the establishment of an objective quality control
system for hazelnut roasting and the selection of roast-
ing conditions to control internal browning.
2. Material and methods
2.1. Hazelnuts
Freshly harvested and sun-dried hazelnuts (season
1998) were supplied from the Hazelnut Research Center
(Giresun, Turkiye) and kept at 4°C until used. Tombul,
the major Turkish hazelnut variety, was used in the
study. The samples were temperature-equilibrated
overnight and cracked using a modi®ed laboratory grain
scale miller. After calibrating the samples, 9±11 mm-
sized hazelnut samples were used in the experiments.
Hazelnuts were roasted at exposure times and roast-
ing temperatures (given in Table 1) using a forced air
pilot scale roaster (Pasilac, APV, England). This range
of exposure times and temperatures represent the range
commonly used in the hazelnut industry. Prior to plac-
ing the samples in the roasting chamber, the equipment
was run for at least 2 h to obtain steady-state conditions.
The kernels were placed on the drying trays in single
layer in the drying chamber. Air velocity was kept
constant at 0.8 m/s throughout the experiments. The
roasted samples were cooled to room temperature in a
desiccator and stored at 4°C until analysis.
2.2. Color measurements
All color measurements were conducted within 10
days of roasting experiments. The measurements were
performed after hand-blanching the samples to remove
skins. The poor quality hazelnuts were also removed.
The color of the roasted samples was measured using
Minolta Chroma Meter II Re¯ectance system. The in-
strument is a tristimulus colorimeter which measures
four speci®c wavelengths in the visible range, speci®ed
by the Commission Internationale de lÕEsclairage (CIE).
Tristimulus values give a three-dimensional value for
color in which equal distances approximate equally
perceived color dierences. The L-, a-, and b-values are
the three dimensions of the measured color which gives
speci®c color value of the material. The L-value repre-
sents the light-dark spectrum with a range of 0 (black) to
100 (white), the a-value represents the green±red spec-
trum with a range of )60 (green) to +60 (red) while the
b-value represents the blue±yellow spectrum with a
range of )60 (blue) to + 60 (yellow) (Moss & Otten,
1989; Driscoll & Madamba, 1994). These values are
dependent on measurement factors such as the type and
size of the material, the angle of the measurements and
18 M.

Ozdemir, O. Devres / Journal of Food Engineering 45 (2000) 17±24

the stability of the reference standards (Driscoll &
Madamba, 1994).
The outside color of the 20 randomly selected hazel-
nut kernels was measured for every sample and is re-
ferred to as whole-kernel measurements throughout the
manuscript. Measurements, conducted after milling
each sample to a constant grind size at 5 dierent parts
of the resulting sample were referred to as ground-state
measurements. Thirty randomly selected hazelnuts were
cut into two at the center and the color of the centers
was measured and referred to as cut-kernel measure-
ments throughout the manuscript.
2.3. Experimental design
Response surface methodology was employed to in-
vestigate the eect of exposure time and roasting tem-
perature on the color of hazelnuts and a central
composite design was adopted. A mathematical function
YYfT;t for each response variable, namely the
color dimensions of the L-value, the a-value and the b-
value, in terms of two independent process variables T
(roasting temperature) and t(exposure time) was as-
sumed. To approximate the function f, second-degree
polynomial equations were used:
YiB0B1Xi1B11X2
i1B2Xi2B22X2
i2
B12Xi1Xi2e1
where B0is the intercept when Yequals zero; Biand Bij
are constant coecients, and Xi
Õs are the coded inde-
pendent variables, linearly related to Tand t. In order to
select best ®t, analysis of variance (ANOVA), partial F-
test for individual parameters and analysis of residuals
for the color dimensions were performed following the
enter-method (Guerroro et al., 1996). The backward-
method together with a partial F-test was used to ®nd
the simplest equation. The partial F-test between a
proposed reduced model and a full second-order model
was calculated as follows:
FSSEReduced ÿSSEFull
=dfReduced ÿdffull

MSEfull
;2
where SSE is the sum of square of error; MSE the mean
square error; and df is degree of freedom. Either the full,
or the simplest reduced model that was not signi®cantly
dierent from the full model at the 5% level was selected
as the ®nal model for each response variable (Muego-
Gnanasekharan & Resurreccion, 1992). SPSS (ver 5.0)
was used for statistical analysis.
3. Results and discussion
The experimental values of the color dimensions, L-
value, a-value, and b-value for whole-kernel, ground-
state and cut-kernel measurements are given in Table 2.
The regression coecients of the second-degree poly-
nomial are given in Table 3. The equations obtained for
the color dimensions were tested for adequacy and ®t-
ness by analysis of variance, residual and by a partial F-
test (Guerroro et al., 1996). A summary of the linear,
quadratic and cross-product terms for L-, a- and b-
values of whole-kernel, ground-state and cut-kernel
measurements are given in Table 4 Non-signi®cant
terms were eliminated by applying the backward selec-
tion procedure (Guerroro et al., 1996). Except for the
b-value of cut-kernel measurements, the proposed
equations explained more than 85% of the variation of
the L-, a- and b-values of the three methods of mea-
surements. The relative importance of linear X1;X2and
quadratic terms X2
1;X2
2was highly important for the
three types of measurements while cross-product terms
X1;X2were highly important for ground-state and cut-
kernel measurements (Table 4).
For the evaluation of the adequacy of the prediction
models, the residual mean was calculated for each color
attribute for the three measurement methods and
yielded values in the range of 10ÿ14 ±10ÿ15 which may be
Table 1
Coding levels of independent variables used in developing experimental color for roasted hazelnuts
Independent variables Symbols Levels
Uncoded Coded Uncoded Coded
Roasting temperature (°C) TX
1158 1.4142
150 1
130 0
110 )1
102 )1.4142
Exposure time (min) tX
244 1.4142
40 1
30 0
20 )1
16 )1.4142
M.

Ozdemir, O. Devres / Journal of Food Engineering 45 (2000) 17±24 19

Table 2
Experimental data of L-value, a-value and b-value for whole-kernel, ground-state and cut-kernel measurements under dierent roasting conditions of
temperature (X1) and exposure time (X2)
Treatment no. X1X2Measurement method
Whole-kernel Ground-state Cut-kernel
L-value a-value b-value L-value a-value b-value L-value a-value b-value
1)1)1 84.66 0.93 24.52 81.45 0.37 21.44 78.41 4.10 22.93
21)1 77.28 4.44 25.62 67.15 6.27 24.42 63.49 10.10 24.25
3)1 1 84.09 1.41 24.24 76.29 2.44 22.82 72.91 6.27 22.41
4 1 1 71.79 7.47 28.33 59.12 9.37 25.29 56.33 11.24 22.70
5 0 0 83.32 3.13 25.66 70.09 4.97 24.88 64.83 9.75 23.92
6 0 0 82.05 2.98 25.30 65.82 6.09 24.62 66.22 8.88 23.36
7)1.4142 0 85.42 1.08 24.50 80.83 0.21 22.16 80.83 2.58 22.42
8 1.4142 0 72.32 7.25 27.69 54.52 9.89 23.98 55.21 10.97 22.24
90)1.4142 82.39 2.26 23.83 77.81 2.23 22.45 74.68 5.52 22.79
10 0 1.4142 83.96 2.43 26.30 64.94 7.62 24.78 62.82 9.73 23.12
11 0 0 84.41 2.97 25.18 70.33 5.80 24.88 63.33 9.96 23.87
12 0 0 85.14 2.39 25.03 68.35 5.32 24.51 66.04 9.04 24.17
Mean 81.40 3.23 25.52 69.73 5.05 23.85 67.09 8.18 23.18
Standard deviation 4.87 2.16 1.36 8.31 3.19 1.28 8.08 2.84 0.72
Table 4
Analysis of variance table showing the eect of treatment variables as a linear term, quadratic term and interactions (cross-product) on the L-value,
a-value, b-value of roasted hazelnuts
Sum of squares
Whole-kernel measurements Ground-state measurements Cut-kernel measurements
Source df L-value a-value b-value L-value a-value b-value L-value a-value b-value
Model 5 241.92 49.37 19.75 734.95 110.08 16.80 705.92 85.79 3.703
Linear 2 184.40 43.63 16.14 712.04 108.30 11.91 681.17 75.85 0.559
Quadratic 2 196.95 44.89 16.31 696.93 105.55 10.61 657.73 71.40 0.555
Cross-product 1 50.65 16.22 12.03 411.37 64.68 8.58 378.68 39.31 0.134
Residual 6 18.57 1.89 0.43 25.14 1.92 1.32 11.70 3.04 1.981
Lack of ®t 3 17.70 1.55 0.04 24.25 1.74 1.06 9.76 2.45 1.525
Pure error 3 0.87 0.34 0.47 0.89 0.18 0.26 1.94 0.58 0.456
R286.93 93.25 97.86 93.94 96.86 86.68 97.01 93.73 36.10
**
Signi®cant at 1% level.
***
Signi®cant at 0.1% level.
Table 3
Values of second-order polynomial regression coecients for the relationships between roasting conditions and color changes in roasted hazelnuts
Coecient Measurement method
Whole-kernel Ground-state Cut-kernel
L-value a-value b-value L-value a-value b-value L-value a-value b-value
B0)35.043 31.561 48.687 152.56 )21.42 )22.263 202.169 )67.363 )11.998
B11.812 )0.485 )0.344 )0.431 0.167 0.568 )1.279 0.8858 0.468
B11 )0.007 0.002 0.001 NS NS )0.002 0.003 )0.0029 )0.002
B12 )0.006 0.003 0.004 NS NS NS NS NS )0.001
B21.157 )0.367 )0.412 )1.470 0.161 0.381 )1.381 0.5413 0.344
B22 )0.007 NS NS 0.018 NS )0.005 0.017 )0.0071 )0.003
20 M.

Ozdemir, O. Devres / Journal of Food Engineering 45 (2000) 17±24

considered as close to zero. The adequacy of the ®tted
models was also veri®ed by the F-lack of ®t statistic and
the sum of squares which is an indicator of common
variance (Table 4). Normality plots and the normality of
residual distribution also veri®ed the adequacy of the
®tted models (results not shown). These results led to the
conclusion that there is no doubt about the adequacy of
the proposed model for each color attribute of whole-
kernel, ground-state and cut-kernel measurements.
The regression equations obtained were used to gen-
erate response surfaces (Figs. 1±3). The shape of re-
sponse surfaces diered between measurement methods.
The response surface for the L-value of whole kernel
measurements was vertically displaced to signi®cantly
lower L-values (P< 0.0001) in both the ground-state and
cut-kernel measurements. In fact the L-value ranged
from 85.42 to 71.79 for whole-kernel measurements,
from 81.45 to 54.52 for ground-state measurement
and from 80.83 to 55.21 for cut-kernel measurements
over the experimental conditions. The mean L-value of
whole-kernel measurements 81:40 4:87was higher
than the ground-state measurements 69:73 8:31) and
cut-kernel measurements 67:09 8:08(Table 2).
L-value of whole-kernel measurements remained rela-
tively constant before a signi®cant color change was
observed (Fig. 1). In fact, a slight lightening of the nuts
at the beginning of the roast was also observed. The
length of this time delay or induction period was in-
versely proportional to temperature as also reported by

Ozdemir and Devres (2000). During the induction pe-
riod several precursor reactions such as Amadori rear-
rangements and concentration of substrates are likely to
occur. The induction period was followed by the main
browning period near the half-way point of a full roast.
The induction period and main browning period during
roasting were previously reported for peanuts by Moss
and Otten (1989) and for hazelnuts by

Ozdemir and
Devres (2000).
The response surface of a-value of whole-kernel
measurements vertically was displaced to signi®cantly
Fig. 1. Response surfaces for L-value of: (A) whole-kernel measure-
ments; (B) ground-state measurements and (C) cut-kernel measure-
ments.
Fig. 2. Response surfaces for a-value of: (A) whole-kernel measure-
ments; (B) ground-state measurements and (C) cut-kernel measure-
ments.
M.

Ozdemir, O. Devres / Journal of Food Engineering 45 (2000) 17±24 21

higher a-values (P< 0.0001) in both the ground-state
and cut-kernel measurements. The a-value ranged from
0.93 to 7.47 for whole-kernel measurements, from 0.37
to 9.89 for ground-state measurements and from 2.58 to
11.24 for cut-kernel measurements over the experimen-
tal conditions. The mean a-values of whole-kernel
measurements 3:23 2:16were lower than the
ground-state measurements 5:05 3:19and cut-kernel
measurements 8:18 2:84(Table 2). The higher a-
values in ground-state measurements, related to an in-
crease in redness, are indication of the internal browning
(Table 2). The a-value of whole-kernel measurements
was greater than 5 for only two treatments: 150°C, 40
min and 158°C, 30 min. However, the a-value of
ground-state measurements at roasting temperatures is
equal to or higher than 130°C and exposure times longer
than 20 min was equal to or greater than 5. Cut-kernel
measurements showed that the a-value was greater than
5 even at the roasting condition 110°C, 20 min. The
higher roasting temperature and longer exposure time
resulted in the greater a-value, and subsequently darker
internal browning. The internal browning is especially a
problem for the roasted product that is consumed as
whole-kernels because the dierence between outside
color and inside color of roasted product makes the
product unpleasant for the consumer. Internal browning
was also reported by

Ozdemir and Devres (2000) in
roasted hazelnuts, by King, Halbrook, Fuller &
Whitehand (1983) in roasted almond and pecans. The
internal browning may be due to dierences in the rate
of non-enzymatic browning between the outside and
inside of the kernel. The dierence in reaction rate may
result from the dierence in temperature and moisture
distribution within the kernel which may bring about
localized development of Maillard reaction as stated by
G
o
g
us
ßet al. (1998). Therefore, homogenous tempera-
ture and moisture distribution during roasting of ha-
zelnuts is important, and must be taken into account in
the design of hazelnut roasters. It is also necessary to
Table 5
Analysis of variance table showing signi®cance of the eect of the treatment variables on L-value, a-value and b-value of whole-kernel, ground-state
and cut-kernels measurements
Measurements df Sum of squares
L-value a-value b-value
Roasting temperature (X1)
Whole-kernel 11 260.4951.25 20.18
Ground-state 11 760.09 112.0 18.12
Cut-kernel 11 717.62 88.83 5.68
Exposure time (X2)
Whole-kernel 11 260.49 51.25 5.68
Ground-state 11 760.09 111.98 18.12
Cut-kernel 11 717.62 88.830 5.68
*
Signi®cant at 0.1% level.
**
Signi®cant at 1% level.
***
Signi®cant at 5%level.
Fig. 3. Response surfaces for b-value of: (A) whole-kernel measure-
ments, (B) ground-state measurements and (C) cut-kernel measure-
ments.
22 M.

Ozdemir, O. Devres / Journal of Food Engineering 45 (2000) 17±24

understand the mechanism of internal browning and to
develop roasting methods to control internal browning.
The response surface of b-value of whole-kernel
measurements was also vertically displaced to signi®-
cantly lower b-values (P< 0.0001) in ground-state and
cut-kernel measurements. The range of b-values was
23.83±28.33 in whole-kernel measurements, 21.44±25.29
in ground-state measurements and 22.24±24.25 in cut-
kernel measurements over the experimental conditions.
The mean b-value of whole-kernel measurements
25:52 1:36was higher than ground-state measure-
ments 23:85 1:28and cut-kernel measurements
23:18 0:72(Table 2). These results indicated that
whole-kernel measurements yielded signi®cantly lighter
color (higher L-value, higher b-value and lower a-value)
compared to ground-state and cut-kernel measurements.
The dierence between the measurement methods can be
attributed to the internal browning during roasting since
whole-kernel measurements do not measure any internal
browning.
The signi®cance of the eect of each variable (roast-
ing temperature and exposure time) on color attributes
of roasted hazelnuts is shown in Table 5. Temperature
aected the L- and a-values of whole-kernel, ground-
state and cut-kernel measurements signi®cantly but it
did not aect the b-value signi®cantly. Moreover, the
eect of exposure time was insigni®cant for the color
attributes for the three measurement methods.

Ozdemir
and Devres (2000) stated that for a signi®cant color
change in the outside color of kernels, a roasting tem-
perature above 120°C was required. Their results also
supported the ®nding that the roasting temperature was
the main factor governing color development.
Among the color attributes of roasted hazelnuts, the
b-value is not suitable for monitoring hazelnut roasting
since it is not aected by roasting conditions. Although
the a- and L-values are signi®cantly aected by roasting
conditions, the L-value is preferred for monitoring color
development during hazelnut roasting, because the L-
value (relative lightness of a product) is analogous to the
color observation made by the operator (Moss & Otten,
1989). However, the L-value of whole-kernel measure-
ments (outside color) underestimates the L-value of
ground-state measurements (meal color) due to internal
browning of the hazelnuts during roasting. Therefore,
the L-value of ground-state measurements is recom-
mended for monitoring the roasting process. The L-
value was also used to monitor non-enzymatic browning
in garlic drying (Driscoll & Madamba, 1994), peanut
roasting (Moss & Otten, 1989) and hazelnut roasting
(Perren & Escher, 1996b;

Ozdemir & Devres, 2000).
4. Conclusions
The results of this study showed that roasting tem-
perature is the main factor, aecting color development
during roasting of hazelnuts. Prediction models, derived
from second-degree polynomial, satisfactorily described
the L-value, a-value and b-value of whole-kernel,
ground-state and cut-kernel measurements as functions
of roasting temperature and exposure time. The relative
importance of roasting temperature and exposure time as
linear and quadratic terms was highly important for the
three types of measurements but the interaction between
the process variables was highly important for only the
ground-state and cut-kernel measurements. Whole-ker-
nel measurements produced signi®cantly lighter color
(higher L-value, higher b-value and lower a-value) com-
pared to ground-state and cut-kernel measurements due
to internal browning of hazelnuts during roasting. In-
ternal browning was observed even at 110°C and 20 min
of roasting. In order to take into account the internal
browning, and prevent darker color in hazelnut meal
after grinding, roasting process should be monitored
using L-value of ground-state measurements.
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