Available online at www.sciencedirect.com
ScienceDirect Procedia Food Science 7 (2016) 121 – 124
9th International Conference on Predictive Modelling in Food
A predictive modelling study for using high hydrostatic pressure, a food processing technology, for protein extraction Ergin Murat ALTUNER a* a
Kastamonu University, Department of Biology, Kuzeykent, Kastamonu, TR-37150, Turkey
Abstract
The aim of this study is to fit a response model to one response, extracted protein concentration by using high hydrostatic pressure, a food processing technology, as a function of two particular controllable factors of extraction procedure. These factors are “pressure” (applied in MPa) and the “extraction solvent”. Data were taken from a previously published data, where the minimum and maximum values chosen for pressure were 100 MPa and 300 MPa with a center point of 200 MPa. The solvents were PBS, TCA-Acetone and Tris-HCl. Protein concentration values were the mean values of 3 replicates. Firstly, a regression statistics were conducted by the data mentioned above to identify coefficients for intercept, pressure and solvents. The coefficients for intercept, pressure and solvents were identified as 34.29753333, 0.008442 and 0.85425 respectively with p-values of 0.03 for pressure and 0.10 for solvents. A predictive analysis model was fitted to the protein concentration response by using the predictive analysis model proposed with the analysis conducted. © Published by Elsevier Ltd. This ©2016 2015The TheAuthors. Authors. Published by Elsevier Ltd. is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of Department of Food Science, Faculty of Food Engineering, University of Campinas. Peer-review under responsibility of Department of Food Science, Faculty of Food Engineering, University of Campinas. Keywords: High hydrostatic pressure; protein extration
* Corresponding author. Tel.: +90-366-280-1914; fax: +90-366-216-4969. E-mail address:
[email protected]
2211-601X © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of Department of Food Science, Faculty of Food Engineering, University of Campinas.
doi:10.1016/j.profoo.2016.02.103
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Ergin Murat Altuner / Procedia Food Science 7 (2016) 121 – 124
1. Introduction High Hydrostatic Pressure (HHP) processing is a non-thermal food processing technology, in which food samples are subjected to 100 to 800 MPa or even higher pressures such as 1000 MPa in some cases1. HHP processing is a cold isostatic super high hydraulic pressure and it is not only used in food engineering. It has some other application areas, for example the extraction of active ingredients from natural biomaterials2,3. There are several studies which show that HHP can be used to extract biomaterials from plants4. HHP processing has some advantages such as not requiring heating process. This is important in extraction of biomaterials, such as proteins, which can cause some deformation5. It is a well-known issue that during HHP processing the solubility increases. Due to the pressure increase pressurized cells show increased permeability, which can be explained by the mass transfer theory3,6,7,8,11. When the cells are pressurized, more solvent can enter into the cell. This will cause more compounds to permeate the cell membrane and increases yield of extraction9. A rapid permeation is observed according to the large differential pressure between the cell interior and the exterior3. These are the main ideas behind using HHP processing to extract proteins from pollens successfully, which was shown by previous studies2,10. The aim of this study is to fit a response model to one response, extracted protein concentration by using high hydrostatic pressure, as a function of two particular controllable factors of extraction procedure. 1.1. Experiment description The aim of this study was to fit a response model to one response, extracted protein concentration (γ), as a function of two particular controllable factors of extraction procedure. The experimental design and the data were taken from a previous study published previously10. The factors used in the previous study were: x Pressure and x The extraction solvent. The minimum and maximum values chosen for Pressure were 100 MPa and 300 MPa with a center point of 200 MPa. Three different types of extraction solvents were used in the study. The extraction solvents were as follows: x Phosphate buffer saline (PBS) x Trichloroacetic acid (TCA-Acetone) x Tris-HCl 1.2. Design and experimental responses As it was mentioned before, data used in this study were provided from a study published previously10. Table 1 shows the design and experimental responses, in the order in which they were run. The last two columns in the Table 1 show coded values of the factors. 1.3. Regression statistics First of all a regression statistics were conducted by the data mentioned in Table 1 to identify coefficients for intercept, pressure and solvents by MS Excel 2013. The results for this regression statistics are given in Table 2. The coefficients for intercept, pressure and solvents were identified as 34.29753333, 0.008442 and 0.85425 respectively with p-values of 0.03 for pressure and 0.10 for solvents.
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Ergin Murat Altuner / Procedia Food Science 7 (2016) 121 – 124 Table 1. The design and experimental responses10. Run
Pressure
Extraction Solvent
1
0.1 MPa
PBS
2
0.1 MPa
TCA
3
0.1 MPa
4
100 MPa
5
Protein Concentration
Coded Pressure
Coded Solvent
34.235
Control
-1
34.905
Control
0
Tris-HCl
36.379
Control
1
PBS
33.029
-1
-1
100 MPa
TCA
33.699
-1
0
6
100 MPa
Tris-HCl
33.565
-1
1
7
200 MPa
PBS
36.245
0
-1
8
200 MPa
TCA
35.709
0
0
(µg/µL)
9
200 MPa
Tris-HCl
38.389
0
1
10
300 MPa
PBS
36.111
1
-1
11
300 MPa
TCA
36.379
1
0
12
300 MPa
Tris-HCl
38.121
1
1
Table 2. The regression statistics. Coefficients
Standard Error
t Stat
P-value
Intercept
34.29753333
0.648158925
52.91531443
1.54503E-12
Pressure
0.008442
0.003464555
2.43667644
0.037568888
Extraction Solvent
0.85425
0.474403757
1.800681356
0.105277073
1.4. Predictive analysis model A predictive analysis model was fitted to the protein concentration response, which was presented in Fig. 1.
40 38 36 34 32 30
1 0
0 100
200
300
400
-1 500
Pressure (MPa)
Fig. 1. Predictive analysis model fitted to the protein concentration response.
Extraction Solvent
Protein Concentration (µg/µL)
Predictive analysis model fitted to the protein concentration response
38-40 36-38 34-36 32-34 30-32
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Ergin Murat Altuner / Procedia Food Science 7 (2016) 121 – 124
According to the analysis, protein concentration response can be defined by the equation (1) given below.
J
0.008442 >Pressure@ 0.85425 >Extraction Solvent @ 34.29753
(1)
References 1. US Food and Drug Administration Center for Food Safety and Applied Nutrition. Kinetics of microbial inactivation for alternative food processing technologies - high pressure processing, http://www.cfsan.fda.gov/, accessed 03.08.2011. 2. Altuner EM, Çeter T, Alpas H. High hydrostatic pressure processing: a method having high success potential in pollen protein extraction. High Pressure Research 2012;32:291-8. 3. Zhang S, Xi J, Wang C. High hydrostatic pressure extraction of flavonoids from propolis. Journal of Chemical Technology and Biotechnology 2005;80:50-4. 4. Altuner EM, Tokuşoğlu Ö. The effect of high hydrostatic pressure processing on the extraction, retention and stability of anthocyanins and flavonols contents of berry fruits and berry juices. International Journal of Food Science and Technology 2013;40:1991-7. 5. Altuner EM, Alpas H, Erdem YK, Bozoglu F. Effect of high hydrostatic pressure on physicochemical and biochemical properties of milk. European Food Research and Technology 2006;222:392-6. 6. Richard JS. High Pressure Phase Behaviour of Multicomponent Fluid Mixtures. Amsterdam: Elsevier; 1992. 7. Le Noble WJ. Organic High Pressure Chemistry. Amsterdam: Elsevier; 1988. 8. Yan H. Separation Engineering. Beijing: China Petrochemical Press; 2002. 9. Altuner EM, Islek C, Çeter T, Alpas H. High Hydrostatic Pressure Extraction of Phenolic Compounds from Maclura pomifera fruits. African Journal of Biotechnology 2012;11:930-7. 10. Altuner EM, Çeter T, Alpas H. Effect of high hydrostatic pressure on the profile of proteins extracted from Betula pendula pollens. High Pressure Research 2014;34:470-81. 11. Islek C, Altuner EM, Çeter T, Alpas H. Effect of high hydrostatic pressure on seed germination, microbial quality, anatomy-morphology and physiological characters of the garden cress (Lepidium sativum) seedlings. High Pressure Research 2013;33:440-50.
