SIZE SCALE UP OF PASTA DRYING PROCESS: MODELLING APPROACH

Bruno de Cindio♦, Massimo Migliori, Domenico Gabriele, Claudio M. Pollini1

ABSTRACT

The use of Very High Temperature (VHT) treatments in high quality pasta production has been the

most relevant innovation in pasta technologies since twenty years. This technology allows to

increase the plants productivity because of its reduced process time but, using a VHT a good

process control is required in order to reduce the thermal damage on pasta due to the severe

process conditions. This paper aims to show the use of a simulative drying model in order to adapt

the process conditions when the pasta size is changed. Using either long or short pasta shape

(spaghetti and rigatoni) the optimisation of drying curves is carried out in order to guarantee for

different pasta size a right fixed final pasta humidity. As main result all the drying profiles overlap

each other when plotted against the dimensionless treatment time. This suggests that a “master

curve” may be obtained for any pasta shape and this curve can be used as reference in scaling-up

total process time when the pasta size has to be changed. The results have been also compared in

terms of furosine content, assumed as an index of thermal damage, and it appears that the thermal

damage is still acceptable also for longer treatment time in agreement with the expectations of

pasta makers.

KEYWORDS: Pasta production, Drying process modelling, Process Scale-up.

♦ Corresponding author

INTRODUCTION

During pasta drying, due to the inherent difficulty to directly access to the processing material, the

process control is completely demanded to models that act according to the imposed set conditions

of temperature and humidity of the drying wet air. How to choose these latter is often the result of

trial and error tests that are rather time consuming, and even do not ascertain the goodness of the

result. Recently a predictive model of the pasta drying has been proposed (Migliori et al., 2002),

with the aim to avoid these problems through a deeper understanding of the transport phenomena

occurring during water removal, coupled with constitutive equation describing pasta dough

behaviour. Steps characterized by high temperature and low moisture, alternated with low

temperatures and high moisture, seemed to ensure contemporary high quality product and process

optimisation, as found by industrial tests run with TAS – Thermo Active System plant (Pavan,

Italy). The predictive models play a crucial role to transfer the external conditions to internal value

of the main variables that are temperature and water content, maintaining the desired quality

characteristics. Generally speaking, the validation of such models is done for a given shape and a

given size. Thus to make very effective their use, it is necessary to establish simple rules to make

them applicable to different geometrical conditions, with a minimum additional validation test. It is

worthy to notice that typical industrial productions show a wide range of different pasta shape and

size. As concerning with shape, because its importance on the fluid dynamic and in turn on the heat

and mass transport coefficients, it is possible to approximate most of the produced pasta cylinder

like formats, to filled cylinders or cylindrical hollows by a proper fluid dynamic equivalence. Once

obtained an optimized drying profile for these two shapes but for only one size, the problem of the

effect of size change is expected that should be solved by the model, and not pursued by manually

adjusting the process conditions. If the drying profiles are assumed to be still a good choice, the

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total process time can be obtained from simulation. In the following the results of this approach are

presented by taking as target variable the average final humidity of the pasta.

DRYING MODEL

The pasta drying process consists in a simultaneous transfer of mass and energy between drying

medium (often wet air) and pasta sample. At the early stage of the process, when the water content

inside the pasta is sufficiently high that the heat coming from air just equates the heat due to water

evaporation, no water gradient inside pasta arises. In this case, the temperature remains constant at

the so called “wet bulb conditions” and the controlling transport mechanism is the external mass

transfer. This process period is usually called “constant evaporation rate period”, because water is

removed at a constant rate.

When drying proceeds, the water removed by evaporation is not sufficient to balance the external

heat supply and, as a consequence, a water concentration gradient arises. During this step a decrease

of the evaporation rate is observed because the internal mass transfer becomes the controlling step.

When water content becomes even lower, the external shell of pasta becomes dry and a moving

evaporation front must be considered. Under this condition, a third slower drying period is attained

due to vapour transport inside the dry crust. Usually, this condition is reached when humidity

becomes lower than 8% and, for this reason may be neglected, in considering pasta drying where

the final average water content is close to 12.5%.

From an engineering point of view, all these phenomena can be described using mass and energy

balance equations in the two-phase systems (air and dough), assuming equilibrium conditions at the

interfaces. The obtained result is a general system of coupled differential equations that can be

solved by adopting appropriate initial and boundary conditions and proper material parameters (i.e.

thermal and mass diffusivity, specific heat), depending on the considered system.

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As concerning to geometry, the most diffused pasta shape may be distinguished as short and long

pasta (fig.1). Therefore for the model approach the first one was modelled as a long fulfilled

cylinder (Fig. 1a), reminding the classic “spaghetto” with:

1LD

S

S << (1)

and the second one (Fig. 1b), was considered as a classic “rigatone” format, assumed equivalent to a

hollow cylinder with:

1L

DD

R

iR

eR <<

− (2)

Both samples were considered fully submerged in the flowing wet air and a pure diffusive

mechanism of water in dough was assumed for the internal transport. It is worthy to remind that the

most of the used pasta geometries may be reduced to one of those, by a fluid dynamic equivalence

(Migliori et al., 2003).

Following the approach elsewhere described in more detail (Migliori, 2002), in a cylindrical co-

ordinate system, under the geometrical assumption (1) and (2), only a radial variation may be

considered:

∂∂

⋅∂∂

⋅=∂∂

⋅⋅rTkr

rr1

tTC dddρ

(3)

∂∂

⋅∂∂

⋅=∂

∂rUDr

rr1

tU

d (4)

where U is the wet basis pasta humidity and T the sample temperature. The material properties, kd

thermal conductivity, ρd mass density, Cd specific heat, Dd Fick’s diffusivity of water in dough, are

considered as temperature and humidity functions (de Cindio et al., 1992).

4

As explained above, the boundary conditions describing the particular geometry are different for the

two systems. Therefore, for the short pasta sample the heat and mass flux continuity, at dough and

air interface, was imposed on both internal and external surfaces:

( ) wD

dDN

rTkTTh

RR

⋅+∂∂

−=−⋅ ∞ λ (5)

( ) wDwxD

dd NyyMsrUD

RR

=−=∂∂

∞ρ (6)

where sx and h are the external molar mass and thermal transport coefficients respectively; λ is

the evaporation latent heat of water and y the water molar fraction in air.

For long pasta, the same continuity equation holds on the external surface, while the second

condition imposes finite mass and heat flux on the symmetry axis (r=0):

0rTk

0rd =

∂∂

−=

(7)

0rUD

0rd =

∂∂

−=

(8)

For both geometries, the initial conditions are uniform temperature (T0) and humidity (U0) inside

the samples. The thermodynamic equilibrium at the dough air interface is ensured by:

(9) wweq

w apPy 0=

where P is the external air pressure, pw0 the water vapour pressure and aw the water activity in dough.

The model may be applied for different external conditions, in terms of T, U and air velocity and it supplies, as

output, the transient temperature and moisture content of pasta during the treatment. The model was completely

validated elsewhere either with a pilot plant (Migliori et al., 2002) or with industrial plant production (Migliori et

al., 2003).

In the industrial practice, two different objectives have to be reached: the process time has to be as short as

possible and, on the other hand, a high quality level of the production is required. In order to increase the plant

productivity, it is needed to accelerate the drying, by increasing temperature and by reducing humidity of air. It is

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well known, that these conditions may lead to both thermal and mechanical damage of pasta, reducing the final

quality of the product. Aiming to reach both the objectives, processes alternating drastic and soft drying

conditions may be used. Concerning to thermal damage, it is well known that furosine production rate may be

assumed as quality parameter (Peressini et al., 2003). In the following the mechanical damage was not considered.

Once the optimal drying profile has been founded out for a fixed geometry, if it would be desired to

change the dimension of sample, a new optimisation process should be required, using expensive

trial and error procedures. On the contrary, in the following, it is reported a simulative procedure

that allows to scale up the process, following a modelling approach, with the aim to obtain either

the desired final pasta water content (12.5%) or a good quality of the product.

SIMULATIONS SET UP

The simulation set up requires the definition of two main parameters:

− The main geometrical parameter of both geometries i.e. the diameter of the cylinder DS for

spaghetti and the internal diameter DRi for rigatoni;

− The drying profiles for both geometries.

As for the first parameter a classical dimension was chosen, respectively for spaghetti (DS= 2.5

mm) and rigatoni (DRi=1.4 mm), and the optimised drying profile have been determined, as a

consequence, from industrial experience. The adopted drying process applies an alternating

profile and in fig. 2-3 the two drying curves are reported, in terms of air temperature and

humidity, versus the dimensionless process time t* defined as:

p

*

ttt = (9)

where tp is the total drying time (for spaghetti tp =110 min; rigatoni tp=100 min). The air

velocity was assumed to be, for all the considered cases equal to 1 m·s-1. This kind of plot

allows individuating easily the percentage of each treatment zone with respect to the total

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treatment time. It clearly appears that, according to the industrial process trend (Pollini, 1996),

both profiles are characterised by the presence, at the beginning of the process, of a drastic

drying conditions followed by a rest period (2nd drying period) and eventually by a 3rd drying

period. A correct balance between the first and second period allows to maintain the sample

humidity sufficient to avoid mechanical damage due to unrelaxed viscoelastic stresses (de

Cindio et al., 2003)

It is worthy to remind also that for short pasta, the drying conditions are smoother due to the

presence of two evaporating surfaces. Therefore the drying efficiency is greater than the case of

spaghetti, where the filled cylinder offers a higher resistance to the internal water diffusion. As

a consequence, for the rigatoni shape, the severe conditions period is 10% of the entire

treatment, whilst for spaghetti is 30% of the drying profile.

In order to show the scale up procedure, different pasta size have been individuated by changing

DS and DRi as reported in Tab.1.

It was assumed as scale up criterion the constancy of the percentage distribution of the different

zones whilst the total process time, at witch the final pasta moisture content is 12.5%, obviously

must change.

RESULTS AND DISCUSSION

Spaghetti format

Simulations have been performed with different values of DS, in order to fit the proposed

criterion. Consequently different values of tp were found as shown in Fig.4, where the reported

black line represents the target moisture content of 12.5%. In Tab.2 the total process time for

each size is reported and, as expected, the process time increases when the spaghetti diameter

increases too. But if the water content is reported versus the dimensionless time t*, as shown in

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Fig.5, the three curves overlap generating a sort of “master curve”. This may be used as good

manufacturing guideline for choosing drying profiles. In facts because the drying curve slope is

the same, this implies that all the pasta sizes tend to follow the same drying mechanism at any

time t*, even though they look completely different at any time t. This result gives an useful tool

when changing pasta size because gives directly the required process time tp. In fact, whatever

is the spaghetti size, a good estimation of the process time may be obtained by simply imposing

that the adopted drying curve should be as close as possible to the “master curve”. In such a

way a sort of quasi-optimization is obtained for every dimension, starting from a single

optimized condition. The model gives as output also the values of the quality indices of the final

product, and in Fig.6 is reported the furosine evolution during the treatment for all the samples.

This index is a measure of the thermal damage and it clearly appears that, even though the

process conditions are the same in terms of applied thermal and humidity profiles of the drying

wet air, nevertheless it was found that greater are the dimensions greater will be the furosine

content, as a consequence of the longer treatment time.

Rigatoni format

The same approach described above was used for the rigatoni shape, and the simulations were

performed for different DRi (Tab.3). The results of this simulated process are shown in Fig.7,

and again different values of tp were found. Even in this case the drying curves were reported

versus t*, as shown in Fig.8. It clearly appears as for the above case of spaghetti that the three

curves overlap each other, even though the pasta format has changed, and therefore the

suggested criterion of the “master curve” still applies.

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As already done for spaghetti format, the furosine content was computed and the results are

shown in Fig.9. Also in this case it was found that the final quality of pasta strongly depends on

the total process time, when the drying profile is fixed.

From the furosine diagrams, it clearly appears that, for both formats, the final quality of pasta

strongly depends on the characteristics of the setted drying profile. In fact, a more aggressive

drying profile as in the case of spaghetti, increases the final furosine content (about 150 mg⋅100

g of proteins-1), more than the case of a mild process such as the case of rigatoni (about 40

mg⋅100 g of proteins-1). Anyway, from all the simulation results the final pasta quality may be

considered satisfactory, in terms of furosine content if compared to the industrial expectations

(Peressini et al., 2003) the highest value being 150 mg⋅100 g of proteins-1.

Finally it should be remarked that if the two master curves are compared (Fig.10), it obviously

appears that drying conditions for cylindrical pasta format, shows a resulting drying rate higher

than the case of the hollowed format, as expected being due to the different imposed external

conditions.

CONCLUSIONS

The use of physical based predictive models once again resulted to be very important in

conducting process were the only possibility of control stands on the external conditions. Even

if these are strictly fixed, then a simple change of shape or size of the pasta format, can give

drastic changes in the products, resulting in loss of quality. Often this requires a marked change

of the process conditions and particularly of the total process time.

The main issue of this work was the possibility to have a rather helpful criterion to determine

the processing time directly, from a single optimized validated process corresponding to a given

size. Because the result is demonstrated to extend to different shapes, in principle it is possible

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to apply the suggested scale up criterion, to any size and shape. Owing to the fact that several

shapes are industrially produced, a reduction of any shape to the two above considered by

means of a fluid dynamic equivalence, allows to apply the method to a wide range of products

just as a tool capable to avoid expensive and often useless trial and error tests.

ACNOWLEDGEMENTS

This work was developed in the frame of PNR TEMA 8 Industrial Research, granted by

MURST that is acknowledged. The authors would also acknowledge Mr. Francesco Carbone for

software preparation and set up.

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REFERENCES

− de Cindio, B., Brancato,B., Saggese, A., (1992). Modellazione del processo di essiccamento

di Paste Alimentari (Modelling of pasta drying process). University of Naples, IMI-PAVAN

Project - Final report (Italian language).

− de Cindio B., Gabriele D., Migliori M., Pollini C.M. (2003), Modelling of drying for high quality pasta

production.Proceedings of “International Symposium of Rheology and Food Structure. Eurorheo 2003-01”

10th-13th February 2003 Zurich (CH), 635-636.

− Migliori, M. (2002). Rheological modelling of drying process of high quality pasta (Italian

language), PhD dissertation University of Calabria, Italy

− Migliori, M., Gabriele, D., de Cindio, B., & Pollini, C.M. (2002). Modelling and Simulation

of High Quality Pasta Driyng. Proceedings of II International Workshop “Durum Wheat and

Pasta Quality: Recent Achievements. November 19th – 20th 2003, Rome (Italy), 163-169.

− Migliori M., Gabriele D., de Cindio B., Pollini C.M. (2003). Mathematical Modelling of

High Quality Short Pasta Drying. International Workshop “Finite Element Modelling in

Chemical and Food Engineering FEM’03”, 9-10 October 2003, Salerno (Italy), 111-120

− Pollini, C.M. (1996). Pasta drying: consolidation of VHT technology. In Kruger, J.E.,

Matsuo, R.B., Dick, J.W. (Eds.), Pasta and Noodle Technology (pp. 19-37), American

Association of Cereal Chemistry, St. Paul (USA).

− Sensidoni, A., Peressini, D., & Pollini, C.M. (2003). Management of non-enzymatic browning in

pasta processing. Tecnica Molitoria International. 54 2/A, 99-110.

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LEGEND OF FIGURES

Figure 1 Pasta shape geometry

Figure 2 Drying profile for spaghetti format

Figure 3 Drying profile for rigatoni format

Figure 4: Drying profiles for spaghetti format

Figure 5 Drying profiles master curve for spaghetti format

Figure 6 Furosine content for spaghetti format

Figure 7 Drying profiles for rigatoni format

Figure 8 Drying profiles master curve for rigatoni format

Figure 9 Furosine content for rigatoni format

Figure 10 Master curve comparison for different pasta format

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TABLES

Pasta shape Code LS [mm]

DS [mm]

S1 250 15 S2 250 20 Spaghetti S3 250 25

LS [mm]

DRi

[mm] DR

e

[mm] R1 35 13.5 15 R2 35 14 15 Rigatoni R3 35 14.25 15

Table 1

Dimension of pasta samples used for simulation

13

Code tp [mm]

S1 74 S2 110 S3 150

Table 2

Optimised process time for spaghetti format

14

Code tp [mm]

R1 72 R2 100 R3 147

Table 3

Optimised process time for rigatoni format

15

LS

DS

r

LR

DRi

DRe

r

(a) (b)LS

DS

r

LR

DRi

DRe

r

(a) (b)LS

DS

r

LR

DRi

DRe

r

(a) (b)

Figure 1

16

60

70

80

90

100

0 0.2 0.4 0.6 0.8 1

t*, -

Tem

pera

ture

, °C

50

60

70

80

90

100

Air

hum

idity

, %

Temperature Air humidity

Figure 2

17

50

60

70

80

90

100

0 0.2 0.4 0.6 0.8 1

t*, -

Tem

pera

ture

, °C

50

60

70

80

90

100

Air

hum

idity

, %

Temperature Air humidity

Figure 3

18

10

15

20

25

30

35

0 20 40 60 80 100 120 140 160

time, min

Past

a w

ater

con

tent

, %

S1 S2 S3

Figure 4

19

10

15

20

25

30

35

0 0.2 0.4 0.6 0.8 1

t*, -

Past

a w

ater

con

tent

, %

S1 S2 S3

Figure 5

20

0

20

40

60

80

100

120

140

160

0 0.2 0.4 0.6 0.8 1 1.2

t*, -

Furo

sine

, mg/

(100

g o

f pro

tein

s)

S1

S2

S3

Figure 6

21

10

15

20

25

30

35

0 20 40 60 80 100 120 140 160

time, min

Past

a w

ater

con

tent

, %

R1 R2 R3

Figure 7

22

10

15

20

25

30

35

0 0.2 0.4 0.6 0.8 1

time, min

Past

a w

ater

con

tent

, %

R1 R2 R3

Figure 8

23

0

10

20

30

40

50

0 0.2 0.4 0.6 0.8 1

t*, -

Furo

sine

, mg/

(100

g o

f pro

tein

s)

R1 R2 R3

Figure 9

24

10

15

20

25

30

35

0 0.2 0.4 0.6 0.8 1

time, min

Past

a w

ater

con

tent

, %

Rigatoni Spaghetti

Figure 10

25