papers jumbo squid(1)
DESCRIPTION
paper jumbo siqudTRANSCRIPT
![Page 1: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/1.jpg)
Kinetics and modelling of drying process of jumbo squid
(Dosidicus gigas) slices subjected to an (high pressure
impregnation process) osmotic pretreatment under high
pressure impregnation.
Mario Pérez-Won 1, Roberto Lemus-Mondaca 1, Gipsy Tabilo-Munizaga 2, Fernanda Marín 1,
Constanza Olivares 1
1 Departamento de Ingeniería en Alimentos, Universidad de La Serena, Av. Raúl Bitrán 1305, Box 599, La Serena, Chile. 2 Departamento de Ingeniería en Alimentos, Universidad del Bío-Bío, Av. Andrés Bello s/n, Box 447, Chillán, Chile.
Abstract Simultaneous application of osmotic dehydration and high pressure as a pretreatment to
drying process at 40 and 60°C on jumbo squid (Dosidicus gigas) slice samples was studied in this
research. The process time was reduced by increasing drying temperature along with the application
of different pretreatment conditions: high pressure (350 and 550 MPa), pressure time (5 and 10
min), and osmotic solution (10 and 15% NaCl). The Weibull, Logarithmic and Midilli–Kucuk
models were applied to drying experimental data, where this last model was found to be the best
fitting model. Effective moisture diffusivity values varied from 3.82 to 6.59 ×10 -9 m2/s, for both
control and pretreated samples (R2≥0.98). Furthermore, all drying curves were normalized and then
modelled by the same three above models showing a R2≥0.96. Finally, as regards the energy
consumption and efficiency values for drying process (control and pretreated samples) were found
to be in the range of 777–1815 kJ/kg and 8.22–19.20%, respectively. Thus, knowledge about
moisture transfer kinetics, as well as energy consumption and/or data normalization, is needed by
the industry to manage and control efficiently drying process under different pretreatment
conditions.
Keywords: jumbo squid; drying process, high pressure impregnation; modelling; energy
consumption.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
![Page 2: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/2.jpg)
1. Introduction
Dosidicus gigas is the largest and the most one abundant jumbo squid in the eastern Pacific Ocean
from California to southern Chile (Torres et al., 2013 ).The highest concentrations occur off the
Peruvian coast in the southern hemisphere and in the Gulf of California in the northern hemisphere
It belongs to the family Ommastrephidae and the sub-family Ommastrephinae. Over the recent
years D. gigas has become one of the most important cephalopod fisheries in the Pacific Ocean,
mainly in Peru and Mexico (Torres et al., 2013). Recent evidence has shown that the consumption
of squid value-added products has increased in the last years. Considering that jumbo squid muscle
has properties such as low fat content, high quality proteins, mild flavor, and white color, it has
been a useful raw material for developing several value-added products. (Sanchez et al., 2014).
Drying is a traditional process that has been used for many centuries to preserve food and seafood
(Barakat Mahmoud et al., 2006; Jain & Pathare, 2007; Vega-Gálvez, Andres, et al., 2009). The
main objective of dehydration is the reduction of the food moisture content to a level at which
microbial spoilage and deterioration reactions are minimized, which allows safe storage over an
extended period of time (Doymaz, 2008; Vega-Gálvez, Di Scala, et al, 2009).
It is known that the dehydration process by itself can lead to non-uniformity, slow drying rates, and
changes in final product quality. Nevertheless, these disadvantages can be reduced using a
combination of convective drying with different pretreatments. Among other pretreatments more
used during convective drying are: osmotic dehydration (OD), blanching, microwave drying,
enzyme solution, etc. (Fito and Chiralt, 2003; Perez and Schmalko, 2009). Thus, the combination of
convective drying with different pretreatments could not only be used to reduce drying time but also
to enhance quality of dehydrated products (Fito and Chiralt 2003).
Osmotic dehydration, heat treatment is not used to reduce the water content of food in order to
extend its life and maintain sensory, functional and nutritional characteristics., Almost it does not
affect the color, taste, aroma and texture of the food as it prevents the loss of most nutrients and
possesses a strong need, for it is performed at low temperatures (typically close to ambient).
Increasing consumer preference for fresh and minimally processed food products rather than
processed and frozen products requires research into new processing and preservation methods. In
this context, high hydrostatic pressure (HHP) is an alternative non-thermal food preservation
technology, which provides a way to increase fish product shelf-life when combined with good
refrigeration and handling practices (Briones et al., 2010, Erkan and Üretener, 2010 and Senturk
and Alpas, 2012). As a food preservation technology, HHP is useful due to the inactivation suffered
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
![Page 3: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/3.jpg)
by microbial populations and endogenous enzymes that cause spoilage; this substantially increases
shelf-life and enhances the safety of many perishable foods (Considine et al., 2008, Murchie et al.,
2005 and Rendueles et al., 2011)
Predicting of the drying process by mathematical modelling is an important tool for improving these
processes and minimizing operative problems for example final product damage and excessive
consumption of energy, among others (Akpinar 2006; Lemus-Mondaca et al. 2014). That is why,
there are various empirical equations frequently used to model drying kinetics such are Newton,
Henderson–Pabis, Page, Modified Page, Logarithmic, Two terms, Midilli–Kucuk, etc. (Doymaz &
Pala, 2002; Lemus-Mondaca et al. 2014). Even though most of the models are empirical, they are
mainly are based on Fick’s second law diffusion model. In addition, another model very used is the
Weibull model, which has been applied in different studies about dehydration–rehydration process
modelling of foods and biological materials (Corzo et al. 2008).
Therefore, the aim of this work was to evaluate the influence simultaneous osmotic dehydration and
high pressure as pretreatment to convective drying process of jumbo squid (Dosidicus gigas) slices,
and thus to evaluate mass transfer kinetics as well as obtaining moisture diffusion coefficients.
2. Materials and methods
2.1. Raw material
Jumbo squid samples were obtained at the local fish market at the seaport of Coquimbo, Chile.
Fillets of jumbo squid were selected and the external and stomach skin areas were discarded.
Finally, the fillets were chopped into slices of 5.0±0.1 cm each side and 1.0±0.1 cm thickness. The
samples were then packed in polyethylene pouches and kept in a refrigerated room (4°C) until
further analysis. The moisture content was determined following the method of AOAC 934.06,
using an analytical balance(CHYO, Jex-120, Kyoto, Japan) with an accuracy of ±0.0001 g and a
vacuum drying oven at 60°C (Gallenkamp, OVA–031, Leicester, UK). The crude protein content
was determined using the Kjeldahl method with a conversion factor of 6.25 (AOAC 960.52). The
lipid content was analyzed gravimetrically following Soxhlet extraction (AOAC 960.39). The crude
ash content was estimated by incineration in a muffle furnace (Felisa, FE-341, Jalisco, Mexico) at
550°C (AOAC 923.03). The salt content was determined by the Mohr method (AOAC, 1990). The
aw will be measured at 25°C by a water activity meter (Novasina TH-500). All measurements were
done in triplicate.
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
![Page 4: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/4.jpg)
2.2. Experimental design
Thus, the experimental design used for osmotic dehydration is based upon a multi-factorial design
nk, where n is the number of levels and k is the number of factors, where high pressure (HP),
pressure time (PT), osmotic solution (OS) and drying temperature (DT) are the four factors to
evaluate (k=4), each with two levels (n=2). Therefore, 16 experiments were required (24). Table 1
shows the decoding levels of the technological variables to be used in the experimental design to
later represent the experiments already codified in Table 2.
Table 1 Decoded levels of the technological variables.
Codified levels Decodified levelsDT HP PT OS
-1 40 350 5 10+1 60 550 10 15
Table 2 Codified matrix levels of the operative variables.Run DT HP PT OS
1 -1 -1 -1 -12 -1 -1 -1 +13 -1 -1 +1 -14 -1 -1 +1 +15 -1 +1 -1 -16 -1 +1 -1 +17 -1 +1 +1 -18 -1 +1 +1 +19 +1 -1 -1 -110 +1 -1 -1 +111 +1 -1 +1 -112 +1 -1 +1 +113 +1 +1 -1 -114 +1 +1 -1 +115 +1 +1 +1 -116 +1 +1 +1 +1
2.3. Processing experiments
The osmotic solutions were prepared using commercial salt and distilled water. The salt
concentrations used were of 10% and 15% w/v. From each jumbo squid 10 slices were obtained.
Then, they were weighed individually and submerged in the hypertonic solution in a 1/8 (w/w)
jumbo squid to brine ratio and packaged in polyethylene bags prior to high pressure processing.
High pressure treatment was carried out in a cylindrical loading container at 15°C in a 2 L pilot
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
![Page 5: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/5.jpg)
high pressure unit (Avure Technologies Incorporated, Kent, WA, USA). Samples were subjected to
two different conditions, 350 and 550 MPa and measurements were performed at two selected time,
5 and 10 minutes. Water was employed as the pressurizing medium, working at 17 MPa/s ramp
rate; decompression time was less than 5 s. The samples were removed from the brine solution after
high pressure treatment and the excess of solution in the surface was eliminated with tissue paper.
Drying process was performed in a convective tray dryer, which has a control unit to set the air inlet
velocity and temperature, which is heated through electrical resistances. Two temperatures were
used in the study of the drying kinetics, 40 and 60 °C, and each experiment was made in triplicate.
Drying air flow was held constant at 2.0 ± 0.2 m/s measured with an omnidirectional anemometer
(451112, Extech Instrument, Inc., Waltham, MA). The inlet relative humidity was of 74.5±4.6%,
measured by a digital hygro-thermometer (445703, Extech Instrument, Inc.). Also, two control
samples (un-pretreatment) were carried out at 40° and 60°C. Samples (102.4 ±1.2 g) were arranged
as a thin layer in a stainless steel basket. This mass was measured on an analytical balance (SP402,
Ohaus, China) with an accuracy of ±0.01 g at time intervals defined, connected by a system
interface (RS232, Ohaus, China) to a personal computer, which recorded and stored the
weightdecrease data. The experiments were finished at the point of reaching constant weight (i.e.,
equilibrium condition).
2.4. Moisture effective diffusivity
To predict drying process behavior that takes place during the falling rate period, during which
water is transported to the surface material by diffusion transport phenomena is necessary to use
Fick’s second diffusion law (Di Scala and Crapiste 2008). In this model the dependent variable is
the moisture ratio (MR) which relates the gradient of the sample moisture content in real time to
both initial and equilibrium moisture content (Eq. 1). The integrated equation of Fick’s second law
was also used for long time periods and thin-layer in one dimension (Eq. 2) which leads to Eq. (3),
representing the first term in the development of the series (Crank 1975), from which the diffusion
coefficient is obtained for each temperature.
MR=X t−X e
Xo−X e (1)
MR= 8π 2∑
i=0
∞ 1(2 i+1 )2
exp [−(2 i+1 )2 Dwe π 2 t
4 L2 ] (2)
MR=8π 2 exp [−Dwe π2 t
4 L2 ] (3)
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
![Page 6: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/6.jpg)
2.5. Mathematical models
Several mathematical models have been proposed to describe the characteristics of food and
agricultural products during drying process (Toğrul and Pehlivan 2003). All the equations (Eqs. 4–
6) applied in this study to model the drying kinetics of jumbo squid slices are shown:
Logarithmic MR=a exp (−kt )+c (4)Midilli-Kucuk MR=a exp (−ktn )+bt (5)
Weibull MR=exp [− (t / β )α ] (6)3. Quality parameters
3.1. Surface color
Surface color of the samples was measured using a colorimeter (HunterLab, model MiniScan XE
Plus, Reston, VA, USA). Color was expressed in CIE L* (whiteness or brightness), a*
(redness/greenness) and b* (yellowness/blueness) coordinates, standard illuminant D65 and
observer 10 (Vega-Gálvez, Di Scala, et al., 2009). Ten replicate measurements were performed and
results were averaged. In addition, total color difference (ΔE) was calculated using the following
Eq. (7), where Lo, ao and bo are the control values determined for fresh squid.
ΔE=¿ (7)
3.3. Rehydration indexes
The dried samples were placed in distilled water at 40 C for 6 h, using a solid to liquid ratio of 1:50.
The samples were then removed, drained for 30 s, and weighed. The rehydration ratio (RR) was
calculated according to Eq. (8) and expressed as grams of water absorbed per gram dry matter. The
Water Holding Capacity (WHC) was determined by centrifuging the rehydrated samples at
3500g for 15 min at 20° C in tubes fitted with a centrally placed plastic mesh which allowed water
to drain freely from the sample during centrifugation. The Water Holding Capacity was calculated
from the amount of water removed following Eq. (9), according to previous work (Vega-Gálvez, Di
Scala, et al., 2009). All measurements were done in triplicate.
RR=xreh∗xreh−wdried∗xdried
xdried∗(1−xdried ). (8)
WHC=wreh∗xreh−w l
wreh∗xreh∗100 (9)
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
![Page 7: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/7.jpg)
Where Wreh is the weight of the sample after the rehydration process, Xreh is the corresponding
moisture content on a wet basis, Wdried is the weight of the sample after the drying process, Xdried
is the corresponding moisture content on a wet matter and Wl is the weight of the drained liquid
after centrifugation.
3.2. Texture TPA
The instrumental texture profile analysis (TPA) of jumbo squid samples were conducted using a
texture analyser (Model TAXT2, Texture Technologies, Scarsdale, N.Y., U.S.A.).The core of the
sample was compressed twice to 20% of its original thickness with crosshead speed of 1.7 mm/s
using a cylindrical flat-probe (25 mm diameter; aluminium). Texture analysis was automatically
performed by the texture expert software (version 2.63 Stable Micro Systems Ltd.), and the
following parameters were recorded: hardness, cohesiveness, springiness, and chewiness as defined
by Bourne, Moyer, and Hand (1966). All measurements were done at ambient temperature (20 °C).
TPA-hardness is the peak force (kg) sensed on the first curve cycle. TPA-cohesiveness is the ratio
of area under the second curve to the area under the first curve and relates to the samples strength of
internal bonds. TPA-springiness is the ratio of distance (D2) travelled by the probe on the 2nd cycle
from sample contact point to the set compression percentage to the distance (D1) the probe travelled
on the 1st down-stroke. Springiness relates to recovery from the 1st down-stroke deformation. TPA-
chewiness is a secondary parameter derived from multiplying hardness by cohesiveness and
springiness.
3.4. Statistical evaluation
The determination coefficient (R2), Sum Squared Error (Eq. 11), and Chi-squared (Eq. 12)
statisticaltests values were applied. The tests mentioned were selected as optimal criteria in order to
evaluatethe fit quality of the empirical models, and then to select the equation which best described
the drying curves. Statistical analysis of data was carried out using Statgraphics Plus® v.5.1
software (Statgraphics Corp., 1991), applying an analysis of variance (ANOVA) to estimate least
significant differences (LSD) for a confidence level of 95% (p-value<0.05), and a multiple range
test (MRT) was also used to determine possible homogeneous groups for diffusion coefficients and
kinetic parameters regarding to experimental design.
SSE= 1N ∑
i=0
N
( MRe,i−MRc , i ) 2 (11)
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
![Page 8: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/8.jpg)
χ2=∑i=0
N( MRe,i−MRc ,i )2
N−z (12)
Results and discussion
Drying kinetics behaviour
Proximate analysis of jumbo squid (on 100 g of fresh weight) presented an initial moisture content
of 88.31±0.69 g; crude protein (nitrogen×6.25) of 18.42±0.80 g; total lipids of 0.10±0.01 g; ash of
1.06±0.04 g and salt content of 1.92±0.01 g. Similar results were reported by other authors
(Abugoch et al. 1999; Cortés-Ruiz et al. 2008, Uribe et al. 2009).
La figura 1 muestra la relación de humedad experimental frente al tiempo de secado de los 16
experimentos y muestras control. Se puede observar que la humedad disminuye continuamente al
aumentar la temperatura de secado. Para muestras secadas a 40 y 60°C con un tratamiento previo
las humedades son más baja en comparación con las muestras control por lo que requieren menor
tiempo de secado. Por lo tanto, se puede evidenciar que la aplicación de pretratamiento (DO+HHP)
mejora la migración de humedad de las muestras. Ade-Omowaye y col. (2001), aplicaron
pretratamiento de alta presión hidrostática al pimentón rojo concluyendo que esta tecnología podría
inducir la permeabilidad celular, dando lugar a un aumento de la velocidad de secado, reduciendo
así el tiempo de secado. Por otro lado lalalala aplicaron deshidratación osmótica como
pretratamiendo a la deshidratación
Pretratamiento Deshidratación osmótica
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
![Page 9: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/9.jpg)
Estimation of mass diffusion coefficient
Table 1 Effect of the NaCl concentration in mass diffusion coefficients in each run of Jumbo Squid.
RUN Deff (*10^9 m²/s) R²
1 3,82±0,37a 0.98
2 4,00±0,05ab 0.98
3 4,02±0,11ab 0.99
4 4,09±0,11ab 0.99
5 3,99±0,13ab 0.99
6 4,07±0,03ab 0.99
7 4,15±0,15b 0.98
8 3,97±0,13ab 0.99
9 6,11±0,31A 0.98
10 6,39±0,18B 0.98
11 6,38±0,05AC 0.98
12 6,62±0,20C 0.99
13 6,41±0,25AC 0.99
14 6,50±0,08AC 0.99
15 6,59±0,57C 0.99
16 6,40±0,16AC 0.99
Lowercase letter (a and b) show the effect of osmotic concentration to drying temperature 40 °C at a
constant HP and PT, (run:1-8). Uppercase letter (A, B and C) show the effect of osmotic
concentration to drying temperature 60 °C at a constant , HP and PT (run: 9-16). DT: drying
Temperature; HP: high pressure; PT: Time pressure
La tabla 1 muestra los valores de los coeficientes de difusión, durante el proceso de secado para
todas las muestras pretratadas (OD + HHP) del calamar gigante, los cuales variaron entre 4.82 y
229
230
231
232
233
234
235
236
237
238
239
240
241
242
![Page 10: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/10.jpg)
6.59 ×10-9 m2 / s (R2> 0,98), valores mayores a las muestra no tratadas 1.76×10-9 m2/s y 5.16×10-9
m2/s de 40°C y 60°C respectivamente. Se observó el efecto de la temperatura de secado en D eff ya
que un aumento en esta variable operativa, desde 40 ° a 60 ° C, conduce a un aumento en D eff. Los
valores de Deff mencionados son similares a los reportados por varios autores que trabajan con
pretratamientos similares al proceso de secado por convección, tales como en aloe vera pretratado
usando HHP a 350 MPa durante un período de 30 s, y secado a 70° C, D eff = 8,90 × 10-10 m2 / s
(Vega- Gálvez et al 2010.); deshidratación osmótica (60% de sacarosa) y aire de secado (50-70 ° C)
de calabazas, Deff = 1,34 a 4,16 × 10-10 m2 / s (García et al., 2006), pero mayores para los
reportados por Medina-Vivanco, Sobral, y Hubinger (2002) que trabajaron con un tratamiento
osmótico de filetes de tilapia (relación 4:1, NaCl:filete ), obteniendo un valor de Deff = 0,91 × 10 -
9 m2/s. Jain y pathare (2007) en su estudio con gambas y peces chelwa (carpa menor de la India)
con tratamiento de secado al sol lograron valores de Deff= 1.11 × 10 -11 y 8,708 × 10 -11 m2 /s
respectivamente. Vega- Gálvez et al (2010) trabajaron en secado convectivo a 50 y 60°C con
pretratamiento osmotico sobre calamar gigante, obteniendo valores de Deff = 0.78 y 1,47 × 10-9 m2/s.
Estas diferencias podrían explicarse por la diversidad de especies marinas, temperatura de secado,
orientación de los músculos, contenido de grasa y presencia o ausencia de piel (Medina-Vivanco et
al., 2002), además de las diferentes condiciones de los pretratamientos utilizados.
Se evidencia que las temperaturas más altas parecen promover la pérdida de agua más rápido a
través de la sudoración y la plastificación de las membranas celulares así como el aumento de la
velocidad de transferencia de agua en la superficie del producto debido a la menor viscosidad del
medio osmótico (Burhan Uddin et al. 2004). Por otra parte, la aplicación de alta presión modifica la
estructura de la pared celular, dejando las células más permeables, lo que conduce a cambios
significativos en la estructura de los tejidos resultando en el aumento de las tasas de transferencia de
masa durante la deshidratación (Rastogi et al., 2000).Con respecto al análisis estadístico (ANOVA),
los pretratamientos (DO,HP y PT) se mantuvieron constantes, donde se ve una clara influencia de la
temperatura de secado en el coeficiente de difusión, mostrando un efecto directamente proporcional.
Para el caso de la temperatura de 40°C, no se observaron diferencias significativas (p-value>0.05).
Por otro lado, los pretratamientos a la temperatura de 60°C mostraron diferencias estadísticamente
significativas (p-value<0.05). Asimismo, se realizó un análisis ANOVA para evaluar la influencia
de la presión (350 y 550MPa) y solución osmótica (10 y 15%) sobre los coeficientes de difusión.
Se obtuvieron diferencias significativas sólo para los tratamientos a temperatura de 60°C (p-
value<0.05). En relación a la influencia del tiempo de presurización (5 y 10 min) sobre los valores
de difusividad (Deff) no se encontraron diferencias estadísticamente significativas (p-value>0.05).
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
![Page 11: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/11.jpg)
Además cabe mencionar que las muestras con tratamiento previo se deshidrataron más rápidamente
que las muestras control. También se obtuvieron valores de coeficientes de difusión más bajos,
evidenciando una influencia de estos tratamientos sobre el tiempo de secado.
Mathematical modelling
La Figura 1 muestra una curva con tendencia exponencial decreciente de las curvas de secado de los
16 experimentos pre tratados además de las curvas control (40° y 60°C). Los modelos Page,
logarítmico y Weibull fueron utilizados para modelar el proceso de secado de cubos de jibia. El
promedio del coeficiente de determinación (R2) para el modelado de las curvas control fue
R2>0.994.
La tabla 2 muestra el promedio de los parámetros empíricos calculados para los 16 experimentos
donde el modelo de page mostró valores de 0.019, 0.869 para k y n de 40°C, respectivamente y
0.014 y 0.898 para k y n de 60°C, respectivamente. En el caso del modelo logarítmico los resultados
fueron 0.928, 0.005 y c-0.002 para a, k y c de 40°C, respectivamente y 1.004, 0.007 y -0.034 para a,
k y c de 60°C, respectivamente. El modelo de weibull, mostró valores de 0.896 y 168.7 para α y β
de 40°C y 0.898, 116.2 para α y β de 60 °C, respectivamente.
Se realizó un análisis estadístico ANOVA utilizando el software Statgraphics v.5.1 a un nivel de
confianza del 95%, para todos los parámetros empíricos de cada modelo respectivo con el fin de
observar la influencia de todas las variables tecnológicas utilizadas (DT, HP, PT y OS). A partir de
este análisis realizado a los parámetros empíricos para a (logarítmica), n (page) y α (weibull) se
obtuvo p-value> 0.05, por lo tanto no hay diferencias significativas a 40°C para los diferentes
tratamientos (véase el cuadro 2). Sin embargo, se observó que para los parámetros k y c
(logarítmica), k y n (page), y α y β (Weibull), se obtuvo un valor de p <0.05, lo que indica que
existen diferencias estadísticamente significativas. Además, se encontró que la mayoría de estos
parámetros aumentaron al aumentar la temperatura, similar a lo que ocurre en el coeficiente de
difusión . Por lo tanto, se puede suponer que estos parámetros empíricos podrían ser directamente
proporcionales a la temperatura.
Statistical analysis on mathematical modelling
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
![Page 12: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/12.jpg)
As to statistical evaluation on mathematical models (Logarithmic, page and Weibull), these showed
low values of SSE and χ2 (Table x), when these were applied to all runs 1-16. Also, these same
models showed low results of SSE (0.020–0.113) and χ2 (0.022–0.126) for control data (40° and
60°C). The equation that best described the drying process for all experiments, both control as runs,
was the logarithmic model (0.9945<R2<0.999; 0.0000<SSE<0.0019, and 0.0000<χ2×<0.0022).
Therefore, Figure 2 presents a comparison between experimental and modelled drying curves using
the logarithmic model. Similar results were reported by other authors when simulating dehydration
process of diverse foods under selected pretreatments conditions, such as blueberries (Vega-Gálvez
et al., 2012), plantain (Tunde-Akintunde, 2014), and pumpkin (Tunde-Akintunde and Ogunlakin,
2011). As a result the foregoing, according to statistical tests applied to three mathematical models
showed low values for SSE and χ2 implying a good fit quality on the experimental data, as far as it
is suggested its usefulness for predicting and modelling moisture transfer kinetics during the
convective drying process of this seafood product under different OD+HHP applied pretreatments.
0 200 400 600 800 1000 12000
0.2
0.4
0.6
0.8
1
1.2Control 40°C Control 60°CRun 1 Run 2Run 3 Run 4 Run 5 Run 6Run 7 Run 8Run 9 Run 10Run 11 Run 12Run 13 Run 14Run 15 Run 16Logarithmic
Time (min)
Moi
stur
e Ra
tio (d
imen
sion
less
)
Figura 1. Comparison between experimental data and logarithmic model-estimated values for all the
runs
310
311
312
313
314
315
316
317
318
319
320
321
322
323324
325
326
327
328
329
330
![Page 13: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/13.jpg)
Surface color
Rehydration indexes
TPA
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
![Page 14: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/14.jpg)
Table 2. Effect of osmotic pretreatment on the 16 treatments dehydrated on color (ΔE). chromatic
coordinates L*, a*, b* jumbo squid samples
Run L* a* b* ΔE
1 69.85±0.16a -3.30±0.03b 12.66±0.01d 26-61±0.11a
2 74.02±0.09f -3.84±0.05a 10.64±0.08a 30.84±0.10e
3 70.93±0.13bc -3.28±0.06bc 12.30±0.14c 27.60±0.10b
4 71.72±0.23d -3.25±0.09bc 12.07±0.07c 28.22±0.15c
5 76.52±0.05g -2.77±0.04d 14.35±0.22f 30.35±0.12d
6 71.20±0.08cd -3.90±0.07a 12.61±0.02d 27.93±0.06bc
7 70.47±1.12b -3.17±0.11c 11.43±0.26b 27.74±0.68b
8 72.66±0.22e -3.22±0.06bc 13.23±0.25e 28.23±0.29c
9 40.80±0.34A 12.11±0.13D 23.86±0.27A 10.20±0.38A
10 47.93±0.67BC 10.80±0.13B 23.33±0.40A 17.00±0.70B
11 41.74±0.19A 12.95±0.11E 23.75±0.73A 10.86±0.26A
12 46.83±0.21B 12.91±0.02E 26.92±0.19C 16.72±0.26B
13 52.98±1.13D 7.68±0.38A 24.77±0.07B 22.88±1.17C
14 48.30±0.35C 11.40±0.17C 24.90±0.11B 17.61±0.32B
15 56.26±1.64E 7.57±0.40A 25.29±0.48B 26.09±1.75D
16 53.96±0.85D 7.70±0.14A 25.29±0.22B 23.90±0.86C
Lowercase letter (a,b,c,d,e, and f) show the effect of osmotic concentration to drying temperature 40
°C at a constant HP and PT, (run:1-8). Uppercase letter (A, B and C) show the effect of osmotic
concentration to drying temperature 60 °C at a constant , HP and PT (run: 9-16). DT: drying
Temperature; HP: high pressure; PT: Time pressure
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
![Page 15: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/15.jpg)
Table 3Effect of osmotic pretreatment on the 16 treatments rehydrated on color (ΔE). chromatic
coordinates L*, a*, b* jumbo squid samples
Run L* a* b* ΔE
1 69.67±0.16a -3.30±0.03b 12.63±0.03d 35.67±0.12a
2 74.01±0.09f -3.84±0.05a 10.64±0.03a 40.24±0.10e
3 70.93±0.13bc -3.28±0.06bc 12.30±0.14c 37.54±0.18b
4 71.72±0.23d -3.25±0.09bc 12.07±0.07c 37.54±0.18cd
5 76.52±0.05g -2.77±0.04d 14.35±0.22f 40.59±0.10e
6 71.20±0.08cd -3.90±0.07a 12.61±0.02d 37.17±0.07bc
7 70.47±1.12b -3.17±0.11c 11.43±0.26b 36.77±0.88b
8 72.66±0.22e -3.22±0.06bc 13.23±0.25e 37.85±0.28d
9 58.24±0.38A 6.77±0.05D 24.27±0.12A 11.72±0.31A
10 57.54±0.24BC 6.31±0.15B 23.45±0.22A 11.57±0.08B
11 56.63±0.16A 7.84±0.04E 24.10±0.26A 9.92±0.10A
12 59.12±0.42B 7.59±0.20E 25.59±0.24C 11.94±0.29B
13 59.09±0.38D 5.44±0.06A 23.30±0.32B 13.30±0.23C
14 61.37±0.41C 6.68±0.11C 23.17±0.04B 14.80±0.41B
15 67.68±0.25E 4.46±0.02A 24.78±0.03B 21.02±0.22D
16 62.88±0.19D 5.82±0.08A 24.83±0.11B 16.15±0.21C
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
![Page 16: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/16.jpg)
Table 4. Efecto de la deshidratación con pretratamiento osmótico sobre los parámetros de perfil de
textura (TPA) de muestras rehidratadas de jibia de los 16 experimentos.
Hardness Springiness Cohesiveness Chewiness
Control 1977.636±621.981c,B 0.695±0.117a,A 0.583±0.139a,A 909.583±435.856c,B
E1 507.241±199.954a 0.909±0.031c 0.826±0.013bc 419.108±178.277ab
E2 723.567±343.797a 0.843±0.145b 0.777±0.108b 560.624±229.798ab
E3 432.995±156.343a 0.862±0.093bc 0.825±0.018bc 329.728±179.147a
E4 1050.561±457.747ab 0.898±0.039bc 0.808±0.047bc 630.236±237.335abc
E5 420.663±170.526a 0.912±0.022bc 0.836±0.021c 397.219±168.436a
E6 445.419±250.817a 0.902±0.026c 0.830±0.027c 338.250±183.672a
E7 2860.755±1896.671d 0.861±0.072bc 0.791±0.022bc 1372.506±626.795d
E8 1566.681±591.255bc 0.908±0.019c 0.831±0.012c 739.929±405.685bc
E9 307.802±68.148A 0.959±0.016B 0.821±0.047B 277.147±101.064A
E10 402.164±178.393A 0.963±0.015B 0.823±0.043B 320.406±142.145A
E11 534.541±169.122A 0.958±0.018B 0.823±0.033B 422.708±136.682A
E12 484.817±231.687A 0.960±0.031B 0.804±0.034B 337.512±169.452A
E13 439.859±200.338A 0.962±0.012B 0.791±0.047B 387.563±187.766A
E14 267.075±130.286A 0.946±0.041B 0.837±0.030B 238.965±88.807A
E15 441.769±281.470A 0.958±0.024B 0.801±0.038B 439.329±244.452A
E16 414.216±165.507A 0.967±0.012B 0.817±0.024B 336.289±182.354A
Análisis de perfil de textura (TPA) se realizó para describir el efecto de los distintos tratamientos
sobre las características de textura del tejido del calamar gigante rehidratado. La tabla 4 muestra los
valores medios para los parámetros de textura, dureza que indica la firmeza del musculo,
cohesividad la cual se relaciona con la viscosidad, elasticidad y Masticabilidad que indica ternura
del manto. Se detectaron diferencias significativas (pN0.05) para la muestra control con respecto a
todos los experimentos, mostrando para la mayoría de estos una disminución del parámetro en
términos dureza y Masticabilidad , el menor valor de dureza se observó para el experimento E14 y
el mayor para E7, mostrando así una tendencia poco uniforme respecto a los valores obtenidos de
la serie de experimentos E1-E8, por lo tanto se puede decir que la alta presión combinado con una
temperatura de deshidratación de las muestras a 40°C no influyo sobre disminución del parámetro
dureza Hurtado y col. (2001) observó endurecimiento del músculo pulpo presurizado a 200, 300 y
398
399
400
401
402
403
404
405
406
407
408
409
410
411
![Page 17: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/17.jpg)
400 MPa a 7 °C y 40 °C. A partir del experimento E9 al E16 los resultados arrojaron valores de
dureza y masticabilidad mas uniformes y menores, no encontrándose diferencias significativas
(pN0.05) entre estos para ninguno de los parámetro de textura evaluados
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
![Page 18: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/18.jpg)
Table 2. Values of empirical parameters for each mathematical model based on all runs.
Ru
n
logaritmic Weibull Page
a k c α β k n
1 0.974± 0.012a 0.005±0.000b -0.002±0.002abc 0.896±0.079a 168.7±7.129bc 0.010±0.004a 0.896±0.079a
2 0.963±0.032a 0.006±0.000d 0.011±0.007d 0.846±0.081a 179.2±3.512c 0.014±0.007a 0.847±0.079a
3 0.986±0.013a 0.005±0.000b -0.001±0.004abc 0.877±0.041a 176.7±11.41c 0.010±0.002a 0.877±0.041a
4 0.975±0.014a 0.006±0.000bcd 0.001±0.004bcd 0.864±0.022a 174.6±10.04c 0.012±0.001a 0.851±0.020a
5 0.989±0.029a 0.005±0.000b -0.003±0.005ab 0.904±0.084a 185.8±10.27c 0.009±0.005a 0.904±0.084a
6 0.970±0.018a 0.006±0.000cd 0.008±0.004cd 0.847±0.037a 141.5±9.582b 0.013±0.003a 0.847±0.037a
7 0.980±0.022a 0.005±0.000bc -0.001±0.007abc 0.818±0.018a 96.27±3.569a 0.023±0.002b 0.818±0.018a
8 0.975±0.028a 0.004±0.000a -0.013±0.013a 0.824±0.021a 93.91±2.143a 0.023±0.002b 0.824±0.021a
9 1.004±0.012AB 0.007±0.000B -0.034±0.003A 0.898±0.068BC 116.2±10.34E 0.014±0.003A 0.898±0.068BC
10 1.014±0.009AB 0.006±0.000A -0.026±0.006A 0.840±0.016AB 61.21±2.405B 0.031±0.003B 0.840±0.016AB
11 1.014±0.031AB 0.007±0.000B -0.035±0.012A 0.850±0.017AB 70.99±0.916C 0.026±0.003B 0.850±0.017AB
12 0.996±0.028AB 0.009±0.000C -0.007±0.006B 0.864±0.041AB 63.35±1.965BC 0.028±0.006B 0.864±0.041AB
13 1.028±0.022B 0.007±0.000B -0.033±0.003A 1.013±0.066D 109.2±3.477E 0.009±0.003A 1.013±0.066D
14 1.019±0.007AB 0.009±0.000C -0.028±0.001A 0.961±0.022CD 94.59±0.775D 0.012±0.001A 0.961±0.022CD
15 1.008±0.031AB 0.007±0.000B -0.029±0.004A 0.828±0.044AB 57.79±3.176AB 0.035±0.009B 0.828±0.044AB
16 0.982±0.012A 0.009±0.000C -0.004±0.004B 0.791±0.050A 48.99±3.374A 0.046±0.012C 0.791±0.050A
Lowercase letter (a, b and c) show the effect of osmotic concentration to drying temperature 40 °C at a constant HP and PT, (run:1-8). Uppercase
letter (A, B and C) show the effect of osmotic concentration to drying temperature 60 °C at a constant , HP and PT (run: 9-16). DT: drying
Temperature; HP: high pressure; PT: Time pressure
431
432
433
434
435
![Page 19: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/19.jpg)
Table 3 Values of statistical test for each mathematical model based on all runs.
Run logaritmica weibull Page
R2 SSE X2 R2 SSE X2 R2 SSE X2
1 0.9988 0.0001 0.0001 0.9694 0.0001 0.0001 0.9694 0.0001 0.0001
2 0.9941 0.0003 0.0003 0.9322 0.0014 0.0016 0.9322 0.0007 0.0008
3 0.9978 0.0008 0.0000 0.9351 0.0004 0.0005 0.9351 0.0006 0.0007
4 0.9987 0.0001 0.0001 0.9382 0.0004 0.0005 0.9344 0.0004 0.0005
5 0.9988 0.0000 0.0000 0.9428 0.0005 0.0005 0.9428 0.0005 0.0005
6 0.9983 0.0001 0.0001 0.9356 0.0005 0.0005 0.9356 0.0006 0.0007
7 0.9945 0.0000 0.0001 0.9254 0.0100 0.0117 0.9254 0.0111 0.0124
8 0.9975 0.0019 0.0022 0.9928 0.0127 0.0148 0.9928 0.0133 0.0148
9 0.9985 0.0001 0.0001 0.9463 0.0007 0.0008 0.9463 0.0007 0.0008
10 0.9992 0.0000 0.0001 0.9899 0.2092 0.2391 0.9899 0.0405 0.0459
11 0.9986 0.0000 0.0001 0.9921 0.0149 0.0169 0.9921 0.0149 0.0169
12 0.9988 0.0000 0.0000 0.9891 0.0112 0.0127 0.9891 0.0112 0.0127
13 0.9990 0.0000 0.0001 0.9714 0.0006 0.0007 0.9713 0.0009 0.0010
14 0.9984 0.0002 0.0003 0.9727 0.0004 0.0005 0.9727 0.0004 0.0004
15 0.9984 0.0001 0.0001 0.9878 0.0225 0.0239 0.9878 0.0225 0.0239
16 0.9988 0.0001 0.0001 0.9816 0.0226 0.0256 0.9816 0.0213 0.0240
436
437
438
439
440
441
![Page 20: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/20.jpg)
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
![Page 21: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/21.jpg)
Referencias
Torres, G., Troncoso, O., Rivas, E., Gomez, C., Lopez, D. 2013. Reversible stress softening of
collagen based networks from the jumbo squid mantle (Dosidicus gigas). Materials Science and
Engineering C.
Guillermina García-Sanchez * , Carlos Roberto Sotelo-Romero, Ramon Pacheco-Aguilar, Juan
Carlos Ramírez-Suarez, Rogerio Sotelo-Mundo, Susana María Scheuren-Acevedo, Celia Olivia
García-Sifuentes, Marcel Martínez-Porchas. 2014. Microbial shelf-life extension of chilled Coho
salmon (Oncorhynchus kisutch) and abalone (Haliotis rufescens) by high hydrostatic pressure
treatment. LWT - Food Science and Technology.
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
![Page 22: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/22.jpg)
Resultados y discusiones
Estimation of mass diffusion coefficients
Los coeficientes de difusión del agua para muestras de abulón secos sin pretratamientos eran de
4,35 ± 0,33 × 10-9 m2 / s para 40 ° C (R2 = 0,99) y 5,60 ± 0,41 × 10-9 m2 / s para 60 ° C (R2 =
0,97). Los valores de Deff a 40 ° C y 60 ° C fueron inferiores a los valores de las muestras de
abulón pretratados (OD + HHP) con respecto a la gestión 1.8 y 9.16, respectivamente. Sobre la base
de los valores de Deff anteriores, durante el proceso de secado para todas las muestras pretratadas
de abulón, varió de 4,54 - 9,95 × 10-9 m2 / s (R2> 0,97), como se puede observar en la tabla 3. Se
observó el efecto de la temperatura de secado en Deff ya que un aumento en esta variable operativa,
desde 40 ° a 60 ° C, conduce a un aumento en Deff (respeto independiente para pretratamiento). Por
lo tanto, un aumento en los resultados de concentración de sal en un aumento de la gradiente de
presión osmótica, el aumento de la fuerza motriz para la eliminación de agua de rebanadas muestras
de abulón, y las tasas de transferencia de masa de ese modo más altos y coeficiente de difusión
eficaz del agua (Corzo y Bracho, 2007). Basado en lo anterior, también se puede mencionar que la
permeabilización de la membrana celular aumentó con el aumento de presión y la solución
osmótica. Sin embargo, el aumento marginal se convirtió después de la aplicación de 550 MPa y 10
min, de acuerdo con aún más el análisis estadístico (ANOVA). Resultados comparables fueron
reportados por varios autores que trabajan con pretratamientos similares a un proceso de secado por
convección, tales como aloe vera pretratado usando HHP a 350 MPa durante un período de 30 s, y
el secado a 70 ° C, Deff = 8,90 × 10-10 m2 / s (Vega- Gálvez et al 2010.); osmo-seca papaya
chilena a 40-60% v / v de sacarosa y 60 ° C, Deff = 1,28 a 1,62 × 10-9 m2 / s (Lemus-Mondaca et al
2009.); deshidratación osmótica (65% de azúcar) de los melones seguido por el aire de secado (65 °
C), Deff = 2,74 × 10-7 m2 / s (Teles et al 2006.); deshidratación osmótica (60% de sacarosa) y aire
de secado (50-70 ° C) de calabazas, Deff = 1,34 a 4,16 × 10-10 m2 / s (García et al., 2006).
Además, los valores de Deff fueron similares a algunos investigador que trabaja con otros
pretratamientos y un secado adicional, por ejemplo: Ade-Omowaye et al. (2003) para el pimiento
rojo pretratados con campo pulsado eléctrica y la deshidratación osmótica y luego secado al aire a
60 ° C, Deff = 0,87 a 1,36 × 10-5 m2 / s. Sin embargo, hasta el momento no es la investigación que
estudia el efecto de la deshidratación osmótica a alta presión sobre la cinética de secado de aire
caliente de algunos mariscos, es por eso que estas diferencias podrían explicarse por la diversidad
de productos (frutas, mariscos, etc.), el uso de diversos pretratamiento y las condiciones
(temperatura solución, concentración osmótica, escaldado), tipo de agente osmótico (sal, azúcar,
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
![Page 23: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/23.jpg)
etc.), espesor de las muestras, el contenido proximal, entre otro factor (Collignan et al 2001;.
Medina-Vivanco et al., 2002; Nicoletti Telis et al 2003;. Gallart-Jornet et al 2007;.. Villacis et al
2008;. Villamonte et al, 2013). Desde un punto de vista estadístico con respecto a la Tabla 3,
también se puede observar que el aumento de la temperatura causado que el aumento de los
coeficientes de difusión, es decir, hubo un efecto directamente proporcional de la temperatura de
secado en Deff, cuando los pretratamientos se mantuvieron constantes, donde se obtuvo pvalue
<0,05, con respecto al análisis ANOVA. Del mismo modo, al mantener otras variables constante y
la observación de la influencia de la presión del sistema, el análisis ANOVA sobre los coeficientes
de difusión masiva no mostró diferencias significativas (p-valor> 0,05). También, se realizó el
mismo análisis estadístico, pero evaluar el efecto del tiempo y la presión osmótica en solución Deff,
donde se encontró pvalue <0,05, ambos tratamientos previos. De esta manera, es evidente la
importancia de estos tratamientos previos ya que favorece a disminuir el tiempo de secado, sino
también para mejorar la calidad de los productos deshidratados (Fito y Chiralt, 2003).
comportamiento cinética de secado
Análisis proximal de las muestras de abulón frescas exhibió un contenido de humedad inicial de
76,15 ± 0,73%, proteína cruda (N x 6,25) de 15,49 ± 0,17%, los lípidos totales de 0,66 ± 0,06%,
ceniza bruta de 1,07 ± 0,02%, y un contenido de sal de 0,61 ± 0,07%, base húmeda. Barrios-Peralta
et al. (2.012), Gao et al. (2.002), y Britz Hecht (1997), y Grubert et al. (2004) encontraron valores
similares para las diferentes especies de abulón como Haliotis rufescens, Haliotis discus, Haliotis
midae y Haliotis rubra, respectivamente. Los perfiles de la relación de humedad experimental frente
al tiempo de secado y la velocidad de secado relación de humedad de las muestras rebanada abulón
para todos los tratamientos de secado en comparación con (corre 1-16 y de control de muestras) se
muestran en la Figura 1a y 1b, respectivamente. Se puede observar que la proporción de humedad
disminuye continuamente en primer lugar con el aumento de temperatura de secado, a continuación,
aumentar el tiempo de la presión y por último el uso de la mayor concentración osmótica. No
obstante, la presión del sistema demostró no tener un efecto significativo sobre la cinética de
secado. Se observó que el uso de pretratamiento (DO + HHP) para mejorar la migración de
humedad de las muestras. Para las temperaturas de secado considerados, 40 ° y 60 ° C, las muestras
pretratadas tenían proporciones de humedad más bajos que las muestras de control y por lo tanto
generalmente se secan más rápido que ellos. Esto se ve confirmado por la observación de los
autores anteriores que aplica tratamientos previos como impulsos eléctricos, escaldado, sumergirse
en una solución osmótica de sal aumenta la migración de humedad desde las regiones internas del
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
![Page 24: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/24.jpg)
producto (Kingsly et al 2007;.. Ade-Omowaye et al 2003 ). Por lo tanto, la aplicación de la
deshidratación osmótica bajo alta presión hidrostática podría ser utilizado como una técnica
novedosa, ya sea como un tratamiento previo o de un proceso de preservación en sí.
Esta investigación demostró que la combinación simultánea entre la deshidratación osmótica y alta
presión como un pretratamiento influenciada la cinética de transferencia de masa durante el proceso
de secado de las rebanadas de abulón. Muestras rebanadas de abulón pretratados generalmente
tenían tiempos de secado más bajas y más altas velocidades de secado que las muestras no tratadas.
El proceso de secado se llevó a cabo en su totalidad en el período de secado tasa decreciente. Los
valores de humedad difusividades eficaces de carreras (1-16) se estimaron, en donde estos valores
fueron más altos que las muestras de control. Esto hace que sea un método rentable de proceso de
secado, junto con una combinación apropiada de los pre-tratamientos utilizados.
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
![Page 25: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/25.jpg)
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
![Page 26: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/26.jpg)
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
![Page 27: Papers Jumbo Squid(1)](https://reader034.vdocuments.net/reader034/viewer/2022051519/577c78021a28abe0548e589e/html5/thumbnails/27.jpg)
664
665
666
667