ANALYSIS OF THE PERFORMANCE OF THE DEHULLING SYSTEM OF
CONFECTIONARY SUNFLOWER GRAINS
Ana K. de Figueiredo, Luciana M. Rodríguez, Isabel C. Riccobene, and Susana M. Nolasco
Grupo de Investigación TECSE, Facultad de Ingeniería, Universidad Nacional del Centro de la Provincia
de Buenos Aires, Av. del Valle 5737, B7400JWI Olavarría, Buenos Aires, Argentina,
kdfiguer@fio.unicen.edu.ar, iriccobe@fio.unicen.du.ar, snolasco@fio.unicen.edu.ar
ABSTRACT
 Confectionary sunflower, which has a larger size and lower oil content than oilseed sunflower,
has a considerable market, since it is used for birdfeed and human consumption. The grains are
classified according to the characteristic dimensions. Medium-size grains are dehulled for use as
a snack, a topping on salads, breads, yogurt, and ice cream, or they can be blended into
numerous baked goods and confectionary products. Sunflower grains are composed by a
pericarp, also known as the “hull” that surrounds the botanic seed, usually called “kernel”. The
characteristics of use of confectionary grains require a dehulling process that is efficient in the
removal of the hull and that also allows to obtain a product consisting mainly of whole kernels.
In the industry, sunflower grains are dehulled by a process based on centrifugal force, where the
resulting impact causes the hull to open. The ability of sunflower grains to lose their hull is
affected by the moisture content of the grains and by process variables (dehuller rotation speed).
This ability can be quantified by means of the “dehulling ability” (DA), the percentage ratio of
the percentage of mechanically extracted hull to the total amount of hull. The aim of the present
work was to determine an optimal combination of working conditions (impact speed and
moisture content of the grain) in the dehulling process of confectionary sunflower grains in order
to maximize the DA, maintaining a high percentage of whole kernels (WK, percentage ratio of
the mechanically extracted whole kernels to the total amount of kernel of the grains), both
expressed on a dry basis (db).
 The confectionary sunflower hybrid Mycogen 9338 (Morgan) was used. The grains were
classified according to size (> 8.75 mm, between 6.50 and 8.75 mm, and < 6.5 mm), carrying out
the tests with the intermediate fraction. Grains with different moisture contents were obtained by
drying (forced circulation stove at 40-45 ºC) or by spraying a pre-calculated amount of distilled
water. Moisture determination was performed by forced-air oven (3 hours, 130 ºC). An
experimental design consisting of 11 experiments was used, adding three replicates of the center
and four points with star configuration to the full 2 2 factorial design. The impact speeds used
(pilot dehulling equipment) were between 2700 and 4000 rpm, and moisture content of the
grains was between 4-14% db.
 The experimental data were adequately fitted into second-order polinomial models (p < 0.0001)
that allow to predict the variation of DA and WK with the moisture content of the grain (MC)
and its impact speed (IS) within the experimental range studied (lack of fit not significant). The
models developed explain more than 82% and 94% of the variation in DA and WK, respectively,
based on the selected operating variables (MC and IS). Both response variables (DA and WK)
compete with each other, and the improvement of one of them has the opposite effect on the
other. The optimization of the system was carried out by using the desirability function (D). The
optimal values of the factors were determined by maximizing this function D, using maximum
WK and maximum DA as criteria.
 The results of the optimization technique suggest that by dehulling Mycogen 9338 confectionary
sunflower grains (size between 6.50 and 8.75 mm) at 12.3% db and 3100 rpm the maximum
values of DA and WK, 72.6% and 63% respectively, can be obtained. The moisture value
defined as optimal determines a requirement of humidification of the grain prior to dehulling,
establishing the need for a technical and economic feasibility study.
 The results obtained offer, especially for the oil industry, criteria for the dehulling process of
confectionary sunflower grains. This would help to optimize the process, obtain products of
better quality and higher profits.
Key words: Dehulling, Confectionary sunflower, Whole kernels
INTRODUCTION
Sunflower is mainly cultivated for commercial oilseed production by pressing and/or solvent
extraction. Although the non-oilseed variety (confectionery sunflower, of larger size and lower oil
content) is grown to a lesser extent, it presents a wide market because it is used for human consumption
and in the food industry for birds and others animals. Confectionary sunflower is generally classified into
three categories: the larger grains are roasted, salted and packaged for human consumption; medium size
grains are dehulled and packaged for use as snacks or in bakery foods; and the smaller grains are used as
poultry feed.
Commercial processing of sunflower grains requires achieving an efficient separation of the hull
from the grain in the dehulling process. In the oil industry, partial dehulling of the grain presents many
advantages, such as a suitable bulk porosity for the oil extraction process, better quality of both raw oil
(lower wax content) and de-oiled meal (higher protein content), as well as an increase of the life span of
the machinery (Tranchino et al., 1984; Subramanian et al., 1990). On the other hand, regarding
confectionary sunflower, the size of the grains and the easiness to remove the hull are two properties that
have an essential role in the quality of the obtained product. The characteristics of use of this grain require
a dehulling process that is efficient in the removal of the hull and that also allows to obtain a product
consisting mainly of whole kernels.
The most efficient method for industrial proccessing of sunflower grains is based on a combination of
impact and centrifugal forces. During impact dehulling, grains are fed into the top of a spinning rotor,
which expels the grains against an impact frame. The force of the impact causes the hull to break away
from the kernel, and then the hull is removed by aspiration as the kernels are separated by vibratory
sieves.
Many investigations have shown that the dehulling ability depends on different characteristics of the
grains, such as size and density (Tranchino et al., 1984; Subramanian et al., 1990; Merrien et al., 1992),
hull content (Dedio and Dorrell, 1989; Denis et al., 1994), oil content (Beauguillaume and Cadeac, 1992;
Merrien et al., 1992) and moisture content (Subramanian et al., 1990; Merrien et al., 1992; Gupta and
Das, 1997; Riccobene et al., 2001; de Figueiredo et al., 2011). Subramanian et al. (1990) and Gupta and
Das (1999) analyzed the effect of feed rate and the impeller speed on dehulling performance of oilseed
sunflower varieties grown in India. Previous studies investigated the effect of moisture content of the
grains on the dehulling ability of a non-oilseed sunflower hybrid (de Figueiredo et al., 2011), but the
literature does not show studies on confectionary sunflower involving other process variables or a
combined study of them. Therefore, the present work was undertaken to determine an optimal
combination of the operating conditions (moisture content of the grains and dehuller impact speed) in the
dehulling process in order to maximize the dehulling ability maintaining a high percentage of whole
kernels.
MATHERIALS AND METHODS
Sample preparation
The confectionary variety Mycogen 9338 (Morgan) was selected for this study. The sunflower grains
used were grown Olavarría (36.5º S, 60.5º W), Buenos Aires province, Argentina. The grains were
manually cleaned to remove all foreign matter, broken or immature grains. The moisture content of the
grains (MC) was determined according to the ASAE S352.2 Method (ASAE, 1999). Both the hull total
content (Htotal) and the kernel total content (Ktotal) were determined by manual dehulling from a sample
of 10 grams and were expressed as dry basis percentage (%, d.b.). The desired moisture content was
obtained by drying the grains in a convection air oven at 40-45 ºC or by spraying with pre-calculated
amounts of distilled water, and then thoroughly mixing and sealing them in separate polyethylene bags.
The samples were kept in a refrigerator for at least 72 hours to allow a homogeneous moisture
distribution. Before starting a test, the required amount of grains was taken out of the refrigerator and
allowed to equilibrate to ambient temperature.
Dehulling ability and whole kernel percentage
The mechanical dehulling was carried out by impact in a dehulling pilot equipment based on a
centrifugal process (Figure 1). The rotor speed was adjusted with a variable frequency drive and
calibrated with a tachometer. After mechanical dehulling of the sample, the resulting product was
classified into hull, whole kernels and rest (undehulled grains, partially dehulled grains, broken kernels
and fines, i.e. material smaller than 2 mm). The fractions were dried in a forced-air oven at 130 °C for
three hours, and the mechanically-extracted hull/kernel percentages were calculated by equation (1) and
(2), respectively, expressed as percentages in dry basis (%, d.b.).
Fig. 1. Dehulling pilot equipment.
Hmec 
tota l hull extracted (g)
 100
total hull extracted (g)  whole kernels extracted (g)  rest (g)
WK mec 
whole kernels extracted (g)
 100
total hull extracted (g)  whole kernels extracted (g)  rest (g)
(1)
(2)
The dehulling ability (DA) and the whole kernels production (WK) were determined as the
percentage ratio of the percentage of mechanically extracted hull/whole kernels to the total amount of
hull/kernels of the grains, equations (3) and (4), respectively.
DA (%) 
H
H
WK (%) 
mec  100
(3)
total
WK
K
mec  100
(4)
total
Experimental design and statistical analysis
The response surface methodology (RSM) combined with a central composite rotatable design
(CCRD) were employed to point out the relationship between the response functions and the process
variables, as well as to determine the conditions of these variables able to optimize the performance of the
dehulling system for confectionary sunflower grains. The design consisted of 11 experiments with three
center points and four axial points added to the 22 full factorial design (Table 1).
STATGRAPHICS Centurion XV software (Version 15.2.06, StatPoint, Inc.) was used to perform the
statistical analysis of the results, develop multiple regression models from experimental data, and predict
process conditions that improve the performance of the dehulling system. Experimental data were fitted to
a generalized second order model by the following equation:
Yi  b0  b1X1  b2X 2  b11X12  b22 X 2
2  b12 X1X 2
(5)
where Yi is one of the two predicted responses (dehulling ability of the grains or the percentage of whole
kernels) and X1, X2 represent the coded levels of the independent variables.
Table 1. Experimental program for the independent variables X1 (moisture content of the grains, d.b.)
and X2 (impact speed, rpm)
Coded levels
Run
1
2
3
4
5
6
7
8
9
10
11
X1
X2
-1
-1
-1
1
1
-1
1
1
-1.41 0
1.41
0
0
-1.41
0
1.41
0
0
0
0
0
0
Actual levels
Moisture
content
(%, d.b.)
6
6
12
12
4.76
13.2
9
9
9
9
9
Impact
speed
(rpm)
2900
3700
2900
3700
3300
3300
2734
3865
3300
3300
3300
Statistical significance of the terms in the regression equation was examined by analysis of variance
(ANOVA) for each response.
The optimization of the responses was carried out by using the desirability function (D). The optimal
values of the factors (independent variables) were determined by maximizing this function D. A high
value of D, from 0 to 1, indicates the best combinations of the factors in order to optimize the studied
system (Eren and Kaymak-Ertekin, 2007; Corzo et al., 2008). In the present work, D function was
developed for the maximum WK and maximum DA criteria.
RESULTS AND DISCUSSION
Estimated values of regression coefficients and their corresponding p-values for the DA response are
presented in Table 2. They demonstrate that moisture content of the grain (X1) and impact speed (X2) had
the largest effect on the DA. These effects were followed by the quadratic term of impact speed (X2). The
quadratic term of moisture content (X12) and the interaction between moisture content of the grain and
impact speed (X1X2) did not present a significant effect on DA (p > 0.05).
Table 2. Regression coefficients of the development model for the dehulling ability
bo
b1
b2
b11
b22
bi
81.29
-4.49
0.49
-2.97
6.88
p-value
0.001
0.000
0.688
0.026
b12
-0.86
0.555
Table 3 shows the estimated values of regression coefficients and their corresponding p-values for the
WK response. All the coefficients were significant (p  0.05), except the interaction moisture content of
the grain/impact speed (X1X2).
Table 3. Regression coefficients of the development model for the whole kernel percentage
bo
b1
b2
b11
b22
bi
49.71
12.86
-4.58
-6.90
-13.27
p-value
0.000
0.000
0.006
0.000
b12
0.95
0.577
The prediction models were rearranged by removing the terms that were not significant at 5% in the
second order polynomial models, and the corresponding equations are shown in Table 4.
Table 4. Adjusted models with only significant coefficients
Response
DA
WK
Model equation
DA  81.75  4.49X 1  6.88X 2  3.11X 2
2
WK  49.71  12.86X 1  13.27X 2  4.58X 12  6.90X 2
2
Model (p-value)
< 0.0001
< 0.0001
0.8282
0.9467
0.7996
0.6308
0.9341
2
R
2
Adjusted R
Lack of fit (p-value)b
b
0.7643
Want the selected model to have non-significant lack of fit (p > 0.05).
ANOVA test revealed that quadratic polinomial models adequately represent the responses of DA
and WK with coefficients of determination, R2 = 0.8282 and R2 = 0.9467, respectively (Table 4). R2 and
the adjusted R2 values for the studied response variables were equal or higher than 0.80, hence there is a
close agreement between the experimental results and the theoretical values predicted by the proposed
models. The model adequacy was tested using the lack of fit test which was not significant for p > 0.05.
Since the models were found to show insignificant lack of fit (Table 4), the responses were sufficiently
explained by the regression equations.
The coefficients in Table 4 are presented in terms of coded factors. Thus the size of the coefficients
could directly be related to the observed change in the response, enabling a straight comparison between
the coefficients. Accordingly, the importance of each factor in the response could be evaluated. The
coefficients of moisture content (X1) were, in absolute value, in the same order as those of impact speed
(X2), indicating that both factors had the same impact on the considered response.
The linear terms of the factors showed an opposite effect on both considered responses. On the other
hand, any change in one of the studied factors in order to improve one response has the opposite effect on
the other one. Namely, an increase in the impact speed improves the DA of the grains, but reduces the
WK percentage. Likewise, an increase in moisture content of the grains in order to achieve a higher WK
production reduces the ability of the grains to dehull, (i.e., the DA of the grains). This situation makes
difficult the optimization of the dehulling system. In the present work, the optimization procedure was
carried out by using the D function. The optimum conditions for dehulling of confectionary grains were
determined with the criteria of maximum DA and maximum WK.
The regression models developed were used for each response in order to determine the specified
optimum conditions. These regression models are valid only in the experimental selected domain, which
was determined taking into account some economic and operational considerations of the industry, and
quality characteristics of the grains. By applying the desirability function method, the optimal operating
conditions, obtained with a desirability value of 0.9460, were 12.3% db for the moisture content of the
grains and an impact speed of 3100 rpm for the dehuller equipment. This combination of the factor level
would achieve the maximum response values (72.6% and 63.2% for DA and WK, respectively) for
Mycogen 9338 confectionary sunflower grains. Considering that confectionary sunflower grains should
not be stored with a moisture content above 10-11%, the optimal optimum moisture value obtained from
the experimental data (12.3%,d.b.) determines the need to moisturize the grains prior to the dehulling
process. Hence, studies of technical and economic feasibility may be necessary.
Optimization of the processing operations should be performed in order to obtain the best conditions
for the dehulling of grains, resulting in a superior quality product as well as maximizing throughput
capacity.
ACKNOWLEDGMENTS
The authors acknowledge the financial support from Universidad Nacional del Centro de la Provincia de
Buenos Aires, Argentina.
REFERENCES
ASAE Standards. 1999. Standard Engineering Practices Data, 46th edn, St Joseph MI: American Society
of Agricultural Engineers.
Beauguillaume, A., and Cadeac, F. 1992. Elements of explication of the variability of the hulling ability
in sunflower. p. 993-999. In: Proc. of 13th Int. Sunfl. Conf., Pisa, Italy.
Corzo, O., Bracho, N., Vásquez, A. and Pereira, A. 2008. Optimization of a thin layer drying process for
coroba slices. Journal of Food Engineering. 85: 372-380.
Dedio, W., and Dorrel, D. G. 1989. Factors affecting the hullability and physical characteristics of
sunflower achenes. Canadian Institute of Food Science and Technology Journal. 22(2): 143-146.
de Figueiredo, A.K., Baümler, E., Riccobene I.C., Nolasco, S.M. 2011. Moisture-dependent engineering
properties of sunflower grains with different structural characteristics. Journal of Food Engineering. 102:
58–65.
Denis, L., Cohelo, V., and Vear, F. 1994. Pericarp structure and hullability in sunflower inbred lines and
hybrids. Agronomie. 14: 453-461.
Eren, I., and F. Kaymak-Ertekin. 2007. Optimization of osmotic dehydration of potato using response
surface methodology. Journal of Food Engineering. 79: 344-352.
Gupta R.K., and Das S.K. 1999. Performance of centrifugal dehulling system for sunflower seeds.
Journal of Food Engineering. 42: 191-198.
Gupta R.K., and Das S.K. 1997. Physical properties of sunflower seeds. Journal of Agricultural
Engineering. Research. 66: 1-8.
Merrien A., Domínguez, J. Vannozzi G. P., Baldini, M., Champolivier, L., and Carré, P. 1992. Factors
affecting the dehulling ability in sunflower. p. 260-267. In: Proc. of the 13th Int. Sunfl. Conf., Pisa, Italy.
Riccobene, I.C., Fernández, M.B., and Nolasco, S.M. 2001. Efecto de la humedad de la semilla en la
aptitud al descascarado de frutos de girasol (Helianthus annuus L.). CIT. Información Tecnológica. 12(1):
3-8.
Subramanian, R., Shamanthaka Sastry, M.C., and Venkateshmurthy, K. 1990. Impact dehulling of
sunflower seeds: Effect of operating conditions and seed characteristics Original Research Article.
Journal of Food Engineering. 12: 83-94.
Tranchino, L. Melle, F., and Sodoni, G. 1984. Almost complete dehulling of high oil sunflower seed.
Journal of the American Oil Chemists Society. 6(7): 1261-1265.