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ISSN 2310-9599 (Online). Foods and Raw Materials Vol.1 (No. 2) 2013
ISSN 2308-4057 (Print)
ISSN 2310-9599 (Online)
The Ministry of Education and Editor-in-Chief
Science of the Russian Aleksandr Yu. Prosekov, Dr. Sci. (Eng.), Kemerovo Institute of Food
Federation Science and Technology, Kemerovo, Russia
Kemerovo Institute of Food Deputy Editor-in-Chief
Science and Technology Olga V. Koroleva, Dr. Sci. (Biol.), Bach Institute of Biochemistry, Moscow,
Foods and Russia;
Raw Materials Zheng Xi-Qun, Dr., Prof., Vice President, Qiqihar University
Vol.1, (No. 2), 2013 Heilongjiang Province, Qiqihar, P.R. China.
ISSN 2308-4057 (Print) Editorial Board
ISSN 2310-9599 (Online) Gosta Winberg, M.D., Ph.D. Assoc. Prof., Karolinska Institutet, Stockholm,
Published twice a year. Sweden;
Founder: AleksandrN. Avstrievskikh, Dr. Sci. (Eng.), ООО ArtLaif , Tomsk, Russia;
Kemerovo Institute of Food Sci- Berdan A. Rskeldiev, Dr. Sci. (Eng.), Shakarim Semipalatinsk State
ence and Technology (KemIFST), University, Semei, Kazakhstan;
The juridical address: Aram G. Galstyan, Dr. Sci. (Eng.), All-Russian Research Institute of Dairy
bul’v. Stroitelei 47, Kemerovo, Industry, Moscow, Russia;
650056 Russia Tamara A. Krasnova, Dr. Sci. (Eng.), Kemerovo Institute of Food Science
Editorial Office, Publishing Office: and Technology, Kemerovo, Russia;
650056, Russia, Kemerovo, bul’v. Olga A. Neverova, Dr. Sci. (Biol.), Institute of Human Ecology,
Stroitelei 47, office 1212, Siberian Branch, Russian Academy of Sciences, Kemerovo, Russia;
tel.: +7(3842)39-68-45 Aleksei M. Osintsev, Dr. Sci. (Eng.), Prof., Kemerovo Institute of Food
http: frm-kemtipp.ru Science and Technology, Kemerovo, Russia;
e-mail: fjournal@mail.ru Viktor A. Panfilov, Dr. Sci. (Eng.), Prof., Moscow State University of Food
Printing Office: Production, Moscow, Russia;
650056, Russia, Kemerovo, Sergei L. Tikhonov, Dr. Sci. (Eng.), Ural State Academy of
ul. Institutskaya 7, office 2006, Veterinary Medicine, Troitsk, Russia;
tel.: +7(3842)39-09-81 Irina S. Khamagaeva, Dr. Sci. (Eng.), East-Siberian State University of
Signet for publishing Technology and Management, Ulan-Ude, Russia;
December 23, 2013 Lidiya V. Shul’gina, Dr. Sci. (Biol.), Pacific Research Fishery Center,
Date of publishing Vladivostok, Russia.
December 27, 2013 Secretary of Editorial Office
Circulation 300 ex. Anna I. Loseva, Cand. Sci. (Eng.), Kemerovo Institute of food
Open price. Science and Technology, Kemerovo, Russia.
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ISSN 2310-9599 (Online). Foods and Raw Materials Vol.1 (No. 2) 2013
CONTENTS
The Edition is registered by Feder- FOOD PRODUCTION TECHNOLOGY
al Service for Supervision in the Analysis of Living and Reproductive Parameters of Microorganisms
Sphere of Telecom, Information A. A. Maiorov............................................................................ 3
Technologies and Mass Communi- Effect of Freezing on the Biochemical and Enzymatic Activity of Lactobacillus
cations (Media Registration Certif- Bulgaricus E.V. Korotkaya, I.A. Korotkiy............................................ 9
icate PI no. FS77-52352 Identification and Prevention of the Formation of Meat with PSE and DFD
dated December 28, 2012). Properties and Quality Assurance for Meat Products from Feedstocks Exhib-
iting an Anomalous Autolysis Behavior I. F. Gorlov, E. I. Pershina, and
S. L. Tikhonov............................................................................ 15
Regularities of the Drying of Lactulose Solutions O. V. Kozlova, A. I. Piskae-
va, V. F. Dolganyuk, and B. G. Gavrilov............................................. 22
Developing Fermented Goat Milk Containing Probiotic Bacteria Chuluunbat
Opinions of the authors of pub- T send-Ayusha and Yoh-Chang Yoon................................................. 30
lished materials do not always co- BIOTECHNOLOGY
incide with the editorial staff’s A Method for Processing of Keratin-Containing Raw Material Using
viewpoint. Authors are responsible A Keratinase-Producing Microorganism Streptomyces Ornatus S 1220
for the scientific content of their Yu. Poletaev, O. V. Kriger, and P. V. Mitrokhin....................................
papers. Histidine Biotransformation Mediated by L-Histidine-Ammonia-Lyase
G. V. Borisova and O. V. Bessonova..................................................
Identification of Industrially Important Lactic Acid Bacteria in Foodstuffs
The Edition « Foods and Raw Ma- A. Yu. Prosekov, O. O. Babich, and K. V. Bespomestnykh........................
terials» is included in the Russian Investigation of the Biotechnological Activity of Direct-Set Starter Cultures in
index of scientific citation (RISC) Structured Dairy Products A. N. Arkhipov, A. V. Pozdnyakova,
and registered in the Scientific and K. A. Shevyakova................................................................... 46
electronic library eLIBRARY.RU Study of Physicochemical and Thermal Properties of L-Phenylalanine Am-
The information about edition is monia-Lyase O. O. Babich and E. V. Ulrikh.......................................... 50
published in international reference PROCESSES, EQUIPMENT, AND APPARATUSES
system of periodical and proceed- OF FOOD INDUSTIRY
ing editions of "Ulrich’s Periodi- Intensification of Yeast Biomass Culturing in a Film Bioreactor N.A. Voinov,
cals Directory". O.P. Zhukova, and A.N. Nikolaev.....................................................
STANDARDIZATION, CERTIFICATION, QUALITY, AND SAFETY
Aspects of Production of Functional Emulsion Foods L. V. Tereshchuk and
K. V. Starovoitova........................................................................
CHEMISTRY AND ECOLOGY
Kemerovo Institute of Food Sci- A Study of the Complexing and Gelling Abilities of Pectic Substances
ence and Technology (KemIFST), O. V. Salishcheva and D. V. Donya................................................... 76
bul’v. Stroitelei 47, Kemerovo, Immobilization of chymotrypsin on magnetic Fe3O4 nanoparticles
650056 Russia L. S. Dyshlyuk, M. V. Novoselova, and T. A. Rozalenok.......................... 85
ECONOMY OF THE AGROINDUSTRIAL COMPLEX
© 2013, KemIFST. Specific Development of the Baking Industry in Kemerovo Oblast
All rights reserved. A. N. Kiryukhina and N. M. Guk...................................................... 89
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ISSN 2310-9599 (Online). Foods and Raw materials Vol.1 (No. 2) 2013
FOOD PRODUCTION TECHNOLOGY
ANALYSIS OF LIVING AND REPRODUCTIVE PARAMETERS OF MICROORGANISMS
A. A. Maiorov
Siberian Research Institute for Cheese-Making, Russian Academy of Agricultural Sciences, ul. Sovetskoi Armii 66, Barnaul, 656016 Russia, phone: (3852) 56-46-12, e-mail: sibniis.altai@mail.ru
Received August 18, 2013; accepted in revised form September 3, 2013
Abstract: A probability correlation between various transitions and the number of microorganisms at different stages of growth has been analyzed. Comparison of the given parameters with those of the environment (temperature, active acidity, oxidation-reduction potential, etc.) allows defining the influence of each parameter. The obtained results and correlations can be recommended for modeling the growth of microorganisms in different environments, cheese mass being one of them.
Key words: microorganism growth, environment, cheese, cultivation process, optimization algorithm
UDC 637.1
DOI 10.12737/2045
The ability of microorganisms to grow plays an important role in dairy production [1, 2]. The microorganisms, owing to enzymes they produce, impact the texture, smell, and flavor of a dairy product. The probiotic characteristics of such a product play an important role, too. To ensure successful reproduction of microorganisms, appropriate growth conditions must be provided.
Reproductive capacity is best assessed by using the probability theory. In this case, the probability of division of one cell living in specific conditions, characterized by the presence and concentration of a substrate, water activity, active acidity, the salt weight fraction, and a number of other parameters that influence the cell’s life, is calculated [3, 5, 7].
This can be done on the basis of either special or previously conducted experiments provided that the conditions of such experiments were recorded. Both methods require compiling a rather large database that helps predict the behavior of bacteria in any given conditions. As complicated as it may seem at first glance, this task requires a strictly formalized approach to the description of the properties of both microorganisms and their environment. The present-day methods of mathematical modeling make it possible to predict the behavior of objects and their interaction with the environment [6, 10].
As regards the growth of microorganisms, a distinction should be made between a closed (uncontrolled) and controlled environment. Partially controlled systems can also exist. An uncontrolled system is such that is not exposed to external influences or when such exposure is negligible. The ideal uncontrolled system is a thermally insulated and hermetically sealed tub containing a substrate with the original number of microorganisms. Nominally, cheese mass at the ripening stage can be
considered such a system [11, 13]. The main physical and chemical processes in cheese are influenced by ferments, i.e., chemical components that make up the cheese mass. Microorganisms are actively involved in this process as they take up nutrients, release metabolic products, and change the environment. Their activity during cheese ripening can only be affected by changing the temperature. A decrease in the temperature results in the reduced reproductive rate; an increase in the temperature accelerates the rate of cell division.
The majority of cheeses ripen within a temperature range of 8-20оС. During cheese ripening, its moisture content changes owing to water evaporation off the surface. This content is not large as opposed to the total cheese mass, but it can be of paramount importance as it influences the life of microorganisms.
Therefore, cheese can be referred to a group of systems with partially controlled parameters. In practical terms, it means that the living conditions of microorganisms inside cheese mass can only be controlled by changing its ripening and storage temperature.
The manufacture of fermented milk products is controlled more easily. Fermented milk products are normally manufactured in tanks equipped with a temperature control system (cooling and heating) and agitators. This setup makes it possible to stir the mass during production and influence the temperature. Moreover, various ingredients that influence the living conditions of microorganisms can be added to the mixture. Such ingredients may be salt, sugar, flavoring agents, preservatives, emulsifiers, stabilizers, etc. This system, although isolated from external influences, can be controlled in a wider context. However, the volume of this system and, consequently, its resources are limited, which means that only a certain number of microorganisms can be
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ISSN 2310-9599 (Online). Foods and Raw Materials Vol.1 (No. 2) 2013
grown in this volume. Their maximum concentration is limited not only by the nutrients in the substrate but also by a variety of other factors.
A so-called flow-through fermenter that ensures control over the living conditions of microorganisms (bacteria) is used to produce various biopreparations. In addition to agitators and temperature control tools, such machines are also fitted with a waste products discharge system, a nutrient supply system, and a system that regulates the gas-phase composition supplied to the substrate. This fermenter must be equipped with special tools to control the parameters of cultivation of microorganisms. The main output controlled parameter can be either the volumetric number of microorganisms (biomass volume) or the concentration of waste products produced by microorganisms (ferment). These two indicators do not always correlate with each other. In this event, it is important to have information on how the qualitative and quantitative parameters of the substrate (environment) affect the output parameters (the number of microorganisms and the concentration of the ferment of interest). This information is obtained through special tests by varying environmental parameters and measuring the efficiency of separate and cumulative influence of the environmental parameters. On the basis of the obtained regularities, a cultivation control program is formed to determine the main and supplementary algorithms of cultivation optimization [14, 15].
By analyzing the capabilities of various systems, it is possible to determine ranges of their controllability and build a control algorithm focused on the optimization of the output parameter.
In practical terms, there is a necessity to analyze the dynamics of bacterial flora growth in a given environment. With a high microorganism concentration in a volume unit, the population influence on the chemical composition of the environment is very significant and often plays a decisive role. Special chemostats that ensure steady cultivation conditions can be used for quite an accurate study of the influence of environmental parameters on the growth of microorganisms [12, 13].
When cultivating in a changing environment, it is more difficult to analyze the effect of individual factors, which leads to the ambiguous interpretation of the obtained results. A more detailed picture of the growth of microorganisms in an environment can be obtained using the living environment reconstruction method (LER). Analysis of the dynamics of microflora growth in cheeses is an example of the application of this method.
The growth of microflora in cheese is assessed by the results analyzed at different production stages. As cheese transitions from one stage to the next, it is very difficult to take into account the influence of various factors on both the cheese and its microflora. In reality, as each factor is a time-dependent variable, it is a challenging task to measure a share of influence that each of them exerts on the microflora growth.
Additional information relating to the influence of such factors can be obtained on the basis of the dynamics of changes in the microflora population. For this purpose, time sampling of the microflora growth at given intervals must be conducted. The sampling interval must be proportionate to the period of microorganism
generation, for instance, 0.5 h. A differential curve can then be built, which, in its simplest form, is a difference in the microflora population at the previous and the next sampling interval:
D = Qi+1 - Qi.
Ideally, each cell of microorganisms is divided in two:
Qi+1 = 2Qi;
i.e., the population of microorganisms doubles at every interval.
In practical terms, not all microorganisms are capable of division.
The division capability is determined by a combination of factors and can be defined as follows:
Qi+1
Ki =------,
2Qi
where Qi+1 is the number of microorganisms in the next generation; Qi is the number of microorganisms in the previous generation; and Ki is a coefficient that characterizes what portion of microorganisms achieves their capacity to divide.
This coefficient can be interpreted as a cell division probability at interval i. This helps calculate the probability of cell division at every division stage. In this case, it is more accurate to speak not about the cell division probability but about a cell division coefficient at a given stage, which is a cumulative influence coefficient embracing all factors affecting the microorganisms.
When the general influence regularities of each factor on the probability of MO cell division are known, it is possible to determine the share of influence of each factor at various stages.
When analyzing a population change as an elementary process of cell division, the approach based on the assessment of division probability becomes appropriate. As a matter of fact, the reproduction of microorganisms is based on the division of individual microorganisms, and the population growth, on the whole, depends on what portions of the microorganisms will divide. In other words, the division process can be thought of as random or stochastic. A cell transition from being undivided into being divided (two cells) is a discrete process. The probability of division, in this case, is a function of a whole number of factors, a time factor being one of many.
In some cases, this factor can be of paramount importance since normally the microflora growth is described in “number”-“time” coordinates.
The use of random processes to describe microorganism growth allows moving on to criterial assessments, which are very important when studying regularities based on the multistage influence of many factors.
When using deterministic functions, any indicator can be calculated with a 100% certainty by changing its functionally dependent argument; this, however, cannot be applied to cell division. Even when dealing with strictly defined parameters of reproduction environment
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ISSN 2310-9599 (Online). Foods and Raw Materials Vol.1 (No. 2) 2013
and a strictly selected strain of microorganisms, it cannot be stated with assurance that a cell will divide into two cells at a strictly determined interval (for instance, 23.4 minutes). This only means that a cell division process can occur within 22-25 minutes under specific cultivation conditions. In other words, there is a high probability that a cell will divide between the 22nd and 25th minutes of cultivation. In terms of the strict wording, one should speak of the probability of cell division within a given timeframe. A cell division probability curve can be asymmetrical due to the different nature of restrictions which accelerate or decelerate the division process. Variations in the cultivation conditions change both the coordinates of the curve maximum point and the steepness of the ascending and descending slopes. When the cultivation conditions move outside of an optimal zone, the probability decreases; as the distance grows, the probability value becomes more negligible. The envelope of these curves represents a biokinetic zone, i.e., a zone where the existence of microorganisms with a specified probability is possible.
The cell division probability describes an increment or, rather, an increment rate over time. To complete the picture, it is necessary to consider the duration of a cell reproduction age, which can be quite lengthy but not lead to the increase in cell population. Finally, an important element in the overall picture of the growth of microorganisms is the end of their life or the cell death.
Depending on the environmental conditions, microorganisms can stay at each ‘stage of life’ for a different period. On the whole, life cycle duration for a microorganism can be assessed on the basis of the probabilities for such microorganisms to stay in three main states.
In mathematical terms, it is not quite appropriate to use the system of differential equations to describe the reproduction of microorganisms as it can be used only for continuous functions, whereas the division process in itself, as it has been previously stated, is discrete, i.e. discontinuous.
Speaking about the application of mathematical systems, it is worth noting that the queuing theory along with the Markov chains is an effective method of analyzing the reproduction of microorganisms. [17]
Thus, transition from one state to another can be described by calculating the probability or intensity of transitions. The reproduction process can be represented as a transition from one state to another.
All microorganisms (cells) can be conventionally divided into three groups representing different states. The first group includes microorganisms that are capable of dividing within the timeframe of one generation (the productive category).
The second group includes microorganisms that are presently nonproductive but have the potential to divide at the next stages (the reversible category). This category can be further divided into subcategories depending on their previous history. This category must include cells in an adaptation state after division, cells exposed to mutation or antagonistic pressure from other cells, or cells deprived of sufficient nutrition, etc. These factors can be specified when modeling biochemical and biophysical processes. In any case, it is assumed that cells that belong to this category maintain the potential for future division.
Fig. 1. Pattern of microorganism division.
The third group comprises microorganisms whose reproductive capability is irreversibly lost (the irreversible group). This group cannot be identified by microbiological tests such as inoculation of media but can distort the interpretation of the dynamics of growth of microorganisms when the population is measured by nephelometric or turbidimetric analysis. This subtle detail of using population data should be taken into consideration as it plays an important role in building an accurate model and interpreting test results. Regarding lactate microflora, it is assumed that cells formed as a result of mother-cell division are equal. Accumulation of defects leading to infertility of cells happens with an equal degree of probability for both branches that evolve in the reproduction process. It does not mean a limitless num
ber of cell divisions even when reproduction conditions are favorable. Part of a cell population can be exposed to mutation as a result of errors accumulated during successive generations, and, consequently, take on new properties; the other part loses the capability to reproduce owing to irreversible changes in the genetic apparatus.
When building a mathematical model of population development based on the Markov chains, an overall schematic diagram can be represented by a marked graph that includes all states of the system with the specified transition intensities (Fig. 1). The number of states depends on the complexity of the process model under consideration.
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ISSN 2310-9599 (Online). Foods and Raw Materials Vol.1 (No. 2) 2013
At the initial stage, there is a population containing D1 of microorganisms. Influenced by a combination of internal and external factors, the population transits into state V with a number of productive units equal to D1V, thus, distinguishing N (irreversible) and R (reversible) categories with populations D1N and D1R, respectively. The transition intensity from state K into states V, N, and R is described by coefficients Х™л (т) XL ( (t)
K/ V K/ N
, and X¹ (т) . The value of these coefficients depends
on the combination of factors that influence the population. When there exists a probability of reverse transitions, appropriate coefficients Xₙ/ᵢcan be used to describe the processes. Each transition may be characterized by certain intensities. In this case, based on the given definitions, part of the reversible category can replenish the productive category in the next reproduction period; the remaining part of the reversible category may transit into the similar category during the future reproduction process.
In terms of the formal approach, the part of the reversible category that transits into the similar category of the next period can be considered as a part of the irreversible category as it plays the same role in population development as the irreversible group under the steady process of changing environmental parameters. However, for building an accurate model and for the correct interpretation of its behavior during research, the transition structure should be kept in the state as it is shown in Fig. 1.
The pattern shown in Fig. 1 can be replaced with a recursive pattern, i.e., repeating itself at every stage of reproduction. Then, as was mentioned before, the reproduction pattern will have five groups of microorganisms (five states). In reality, there are three groups involved in the pattern: productive, reversible nonproductive, and irreversible nonproductive (dying cells). The fourth and fifth groups are made of a hypothetical part of microorganisms consisting of microorganisms in a metastable state and a group that represents a new generation, i.e., a productive group from the previous generation doubled in number.
The state graph for such system is shown in Fig. 2. A group of microorganisms in state S1 (the metastable state) transits into states S2 (the reversible group) and S5 (the irreversible group). Part of microorganisms transits from state S1 into state S3 (the productive group). The intensity of transitions from one state to another is characterized by appropriate coefficients X ᵢ .
Fig. 2. State graph of the system of microorganisms.
Based on the assumption that the number of microorganisms found in an environment in any state of system Si is a random value with an exponential distribution function and transition intensity at this stage ( Xᵢ ), the reproduction process corresponding to the flow graph can be described by a system of equations:
P1(t) = (X₂₁ — X₁₂ — X₁₃ +2X₄₁ -X₁₅)T>(T);
P2( t) = (X₁₂-X₂₁)^(t);
Рз(т) = Х₁₃^ (т)-Х₃₄Р₃(т);
P4( t) = X₃₄P₃(t)-2X₄₁P₄(t);
P₅( t) = X₁₅P₅(t),
where Pᵢ (т) is probability that a microorganism at time т is in state Si.
By analyzing the correlation between various transition probabilities and the number of microorganisms at different stages of growth and by measuring these parameters against those of the environment (temperature, active acidity, oxidation-reduction potential, etc.), it is possible to determine the degree of influence that each of them exerts. The obtained results and correlations can be used in further modeling the growth of microorganisms in different environments, cheese mass being one of them.
All probabilities can become permanent provided the cultivation conditions remain invariable.
Trial experiments in modeling the growth of microorganisms in a closed uncontrolled environment with a limited supply of nutrients, have proved that a suitable model created on the basis of the approach suggested in this article, is quite possible.
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1. Tutel'yan, V.A., Novye tekhnologii v nauke o pitanii (New Technologies in Food Science), Moscow, 2001.
2. Lipatov, N.N., Aspects of modeling amino-acid balance in food products, Pishchevaya i pererabatyvayushchaya promyshlennost (Food and Food Processing Industry), 1986, no. 4, pp. 49-52.
3. Maiorov, A.A., Razrabotka metodov upravleniya biosistemoi syra s tsel'yu sovershenstvovaniya traditsionnykh i soz-daniya novykh tekhnologii (Development of methods of cheese biosystem regulation to improve conventional and create new technologies), Extended Abstract of Doctoral Dissertation in Engineering, (Kemerovo, 1999).
4. Osintsev, A.M., Braginskii, V.I., Ostroumov, L.A., and Gromov, E.S., Ispol'zovanie metodov dinamicheskoi reologii dlya issledovaniya protsessa koagulyatsii moloka (Application of dynamic rheology in studying milk coagulation process), Khranenie i pererabotka sel'khozsyr'ya (Agricultural Commodities Storage and Processing), 2002, no. 9, pp. 4649.
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ISSN 2310-9599 (Online). Foods and Raw Materials Vol.1 (No. 2) 2013 5. Shamanova, T.P., Mikrobiologicheskie i tekhnologicheskie podkhody k proizvodstvu fermentirovannykh produktov (Microbiological and technological approaches to fermented milk production), Molochnaya promyshlennost' (Dairy Industry), 1998, no. 3, pp. 18-20. 6. Adler, Yu.P., Markova, E.V., and Grankovskii Yu.V. Planirovanie eksperimenta pri poiske optimal'nykh uslovii (Planning an Experiment in Search of Optimal Conditions), Moscow, Mir, 1976. 7. Polishchuk, P.K., Derbinova, E.S., and Kazantseva, N.N., Mikrobiologiya moloka I molochnykh produktov (Microbiology of Milk and Dairy Products), Moscow, Pishchevaya promyshlennost', 1978. 8. Babak, O., Ispol'zovanie mikroorganizmov v pishchevoi promyshlennosti (Usage of microorganisms in the food industry, Produkt BY (Product BY), 2008, no. 11. http://www.produkt.by 9. Borunova, S.B., and Furik, N.N., Analiz vyzhivaemosti termofil'nykh molochnokislykh mikroorganizmov pri zamo-razhivanii (Analysis of survival capabilities of thermophilic lactate microorganisms during freezing) in Sovremennye tekhnologii sel'skokhozyaistvennogo proizvodstva: materially XIV Mezhdunar. nauch.-prakt. konf. (Present-day Technologies in Agricultural Production: Proceedings of the XIV International Research and Practice Conference), Grodno, 2011, part 2, pp. 273-274. 10. Glazova, A.A., Botina, S.G., and Tipiseva, I.A., Ustoichivost' otechestvennykh proizvodstvennykh kul'tur bakterii roda Lactobacillus k antibakterial'nym preparatam (Resistance of nationally manufactured Lactobacillus bacteria cultures to antimicrobials), in Sbornik trudov Moskovskogo gosudarstvennogo universiteta pishchevykh proizvodstv (Collected Works of Moscow State University of Food Industries), Moscow, 2010, pp. 67-77. 11. Gudkov, A.V., Syrodelie: tekhnologicheskie, biologicheskie - flziko-khimicheskie aspekty: monografiya -CheeseMaking: Technological, Biological, Physical, and Chemical Aspects: A Monograph), Moscow, DeLi Print, 2003. 12. Emel’yanov, S.A., Khramtsov, A.G., Suyunchev, O.A., et. al., Vliyanie temperatury na razvitie mikroorganizmov v moloke i molochnykh produktakh (Temperature impact on microorganism growth in milk and dairy products), Vestnik -evKavGTU -North Caucasus -TUBulletin), 2006, no. 2, pp. 54-57. 13. Knyazhev, V.A. and Tutel'yan, V.A., Mikroorganizmy i pishcha. Risk i pol'za (Microorganisms and food: Risks and benefits), Vestnik Rossiiskoi akademii meditsinskikh nauk (Herald of the Russian Academy of Medical Sciences), 2000, no. 12, pp. 3-6. 14. Holt, G., Krieg, N., Sneath, P., Staley, J., and Williams, S., Bergey's Manual of Determinative Bacteriology, in 2 vols., 9th ed., Baltimore, Williams & Wilkins, 1994; Moscow, Mir, 1997. 15. Ostroumov, L.A., Prosekov, A.Y., Kurbanova, M.G., and Kozlova, O.V., Pitatel'nye sredy dlya bifidobakterii (Nutritional environments for bifidus bacteria), Molochnaya promyshlennost' (Diary Industry), 2010, no. 1, pp. 20-21. 16. Prosekov, A.Yu., Kozlov, S.G., and Kurbanova, M.G., Vliyanie fermentatsii zakvasochnoi floroi na nekotorye svoistva molochnogo belkovo-uglevodnogo syr’ya (Influence of starter culture fermentation on certain properties of dairy protein and carbohydrate raw materials), Khranenie ipererabotka sel'khozsyr'ya (Agricultural Commodities Storage and Processing), 2004, no. 9, pp. 31-33. 17. Gorban, A.N., Gorban, P.A., and Judge, G., Entropy: The Markov Ordering Approach, Entropy, 2010, vol. 12, no. 5, pp. 1145-1193. 8
ISSN 2310-9599 (Online). Foods and Raw Materials Vol.1 (No. 2) 2013
EFFECT OF FREEZING ON THE BIOCHEMICAL
AND ENZYMATIC ACTIVITY OF LACTOBACILLUS BULGARICUS
E.V. Korotkaya and I.A. Korotkiy
Kemerovo Institute of Food Science and Technology, bul'v. Stroitelei 47, Kemerovo, 650056 Russia, phone/fax: +7 (3842) 73-43-44, e-mail: krot69@mail.ru
Received March 1, 2013; accepted in revised form April 1, 2013
Abstract: The problem of preserving the viability, stability and activity of thermophilic lactic acid bacteria Lactobacillus bulgaricus upon freezing is considered. The effect of different freezing conditions and low-temperature storage on the biochemical and morphological properties and stability of the DNA of L. delbrueckii ssp. bulgaricus has been investigated. Sensory evaluation has been carried out for non-frozen bacterial starter cultures containing L. bulgaricus, and their basic physical and chemical parameters (titratable and active acidity and relative viscosity) have been determined. The influence of low temperature on these parameters has been investigated. The effect of freezing and low-temperature storage on the antagonistic activity of L. delbrueckii ssp. bulgaricus strains has been elucidated. The optimum freezing and storage temperatures for the starters containing L. bulgaricus have been determined.
Key words: freezing, low temperature storage, biochemical and morphological properties of L. bulgaricus, antagonistic activity
UDC 573.4.086.13
DOI 10.12737/2046
INTRODUCTION
The quality of cultured dairy foods depends directly on their production technology and on proper selection, preservation, and subsequent culturing of the starter microflora. The microorganism conservation methods known today consist in bringing the vegetative cells of the microorganisms into an anabiotic state. Since these cells are incapable of passing to the endogenous dormancy state, immersing them into exogenous dormancy (by drying, lyophilization, freezing, etc.) and bringing them out of this state produce stressful situations that cause death of a considerable part of the microorganism population and lead to phenotypic and genotypic changes. Bacterial cells are known to induce nuclease in response to a cold shock, so the lethal effect of low temperatures is due to DNA destruction [1, 2].
Advantages of freezing technologies and low-temperature storage of bacterial starter cultures over the other conservation methods are that they are simple and convenient, require only a small amount of preparative work, and allow rapid recovery of the stored material from the frozen state. Compared to drying and lyophilization, freezing causes less damage to microorganism cultures and leaves them more viable [1, 3 - 5]. In addition, freezing rarely induces genetic changes [1, 3, 4, 6].
The purpose of this work was to study the effects of various freezing temperatures and conditions and low-temperature storage conditions on the biochemical properties, enzymatic activity, morphology, and genetic stability of thermophilic lactic acid microorganisms of the L. bulgaricus genus.
EXPERIMENTAL
Bacterial starters were obtained from lyophilized bacterial starter cultures produced by Barnaul’skaya Biofabrika Co. (L. Bulgaricus; BBV = Bulgarian bacillus, viscous; BBNV = Bulgarian bacillus, nonviscous) and from the L. bulgaricus strains В-3964, В-6516, В-3141, В-6543, and В-6515 from the Russian National Collection of Industrial Microorganisms (RNCIM) at the Institute of Genetics and Selection of Industrial Microorganisms.
The lactic acid bacteria culturing medium was reconstituted nonfat dry milk (RF State Standard GOST R 52090-2003), which had no off-flavors or foreign odors and did not contain inhibitors.
The milk was sterilized in an autoclave (steam sterilizer, DGM-500 model) for 10-15 min at a pressure of 0.1 MPa and a temperature of 121 ± 2°С.
The laboratory fermentation starter was prepared under sterile conditions in an abacterial air environment PCR box (Laminar-S). Lyophilized starter cultures were introduced into sterile milk cooled to 38-39°С, which was then thoroughly stirred. Fermentation was performed in a TSO-1/80 SPU thermostat at 40-41°С until the formation of a clot of desired quality.
The starter cultures were frozen at -45, -25,
or -10°С in air and in a liquid coolant (ethanol). Freezing was carried out in special-purpose low-temperature chambers.
The starter culture temperature during freezing was measured with chromel-copel thermocouples, whose signal was received by an MVA-8 analog input module
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ISSN 2310-9599 (Online). Foods and Raw Materials Vol.1 (No. 2) 2013
and an AS-4 interface transformer and was recorded on a personal computer.
The DNA of lactic acid bacteria was isolated using a bacterial genomic DNA isolation kit (Sintol, Moscow) [7]. The 16S rRNA gene was amplified on a Tertsik amplifier (DNK-Tekhnologiya, Moscow) using thermostable Taq polymerase (SibEnzim, Novosibirsk) according to the manufacturer’s recommendations. The following species-specific primers were used in amplification: 16SbulF: 5’- CAA CAG AAT CGC ATG ATT CAA GTT TG (26) and 16SbulR: 5’- ACC GGA AAG TCC CCA ACA CCT A (22) [7].
The antagonistic activity of L. bulgaricus was determined by perpendicular-stroke coculturing [8] on the surface of dense nutrient medium no. 2. Experiments were performed on 16- to 16-h-old bacterial cultures grown in liquid nutrient medium no. 1.
Liquid nutrient medium no. 1 had the following composition: skim milk hydrolysate (amine nitrogen, 200-250 mg%), 250.0 mL; concentrated yeast autolysate (amine nitrogen, 200-250 mg%), 100.0 mL; agar, 0.8 g; distilled water, to 1 L; 20% NaOH solution, to рН 6.4 ± 0.1. Dense nutrient medium no. 2 had the following composition: skim milk hydrolysate (amine nitrogen, 200-250 mg%), 250.0 mL; concentrated yeast autolysate (amine nitrogen, 200-250 mg%), 100.0 mL; agar, 20.0 g; distilled water, to 1 L; 20% NaOH solution, to рН 6.4 ± 0.1.
The morphological properties of thermophilic lactic acid bacterial cultures were studied by immersion microscopy using a Rathenow microscope with lens 90. The specimens were stained by Gram’s method or with methylene blue.
The following physical and chemical properties of the laboratory fermentation starters were determined: titratable and active acidity (рН), relative viscosity at 25°С (measured with Ostwald’s capillary viscometer), number of viable lactic acid microorganisms (measured by the limiting dilution analysis), and pathogenic microflora content (quantified according to the USSR State Standard GOST 9225-84).
RESULTS AND DISCUSSION
The most important properties characterizing the industrial applicability of a starter culture are its acid production capacity and fermentation activity, the structural and mechanical properties of its clot, the micropattern and organoleptic properties of the resulting clot, and viable microflora content.
The bacterial starter cultures obtained in this study were characterized by a white, delicate, and uniform clot with slight signs of whey separation. The fermented milk clots were readily dividable and acquired a uniform texture upon stirring. All of the starters had a pleasant odor, a fermented milk flavor, and no off-flavors or off-odors. The color of the clot was milk white and was uniform throughout the product bulk. There was no pathogenic microflora in the laboratory starters. The lactic acid microorganism content and some physical and chemical properties of the fresh bacterial starter cultures are listed in Table 1.
Table 1. Characteristics of the fresh bacterial starters
Bacterial Lactic acid Relative
culture microorganism pH viscosity
content, CFU/cm3
BBV 6.0 • 109 4.2 4.31
BBNV 3.0 • 109 4.2 1.75
В-3964 4.5 • 109 4.2 1.72
В-6516 5.0 • 109 4.0 1.80
Fig. 1. Titratable acidity as a function of fermentation time: ■, BBNV; ▲, BBV; ♦ , В-6516; •, В-3964.
The variation of the titratable acidity of milk during clotting is illustrated in Fig. 1.
All of the bacterial starters had the necessary acidity. The relative viscosity of the bacterial starter obtained using BBV was 2.6 times higher than that of the starters from the nonviscous starter cultures.
The next step of our study was investigation of the effect of low temperature on the viability of the starter microorganisms.
The freezing resistance of microorganisms depends on several factors, including the microorganisms’ genus and species, the stage of their development, temperature, freezing rate, freezing medium, and storage time. The effect of low temperature on microorganisms is characterized in terms of intracellular and extracellular changes. The heaviest damage is caused by intracellular ice formation, which disrupts plasma membranes and cell walls. In addition, ice formation increases the concentration of intracellular and extracellular solutions, and this leads to protein denaturation and to the disruption of permeability barriers [2].
The fresh starters were poured into 10-mL test-tubes under sterile conditions and were then frozen at -45, -25, or -10°С in air or in the liquid coolant. After freezing, the tubes with fermentation starters were stored in heat-insulated containers at the temperature equal to the freezing temperature. The frozen starters were stored for 6 months.
The frozen starters were examined to determine their microbiological, biochemical, and physicochemical characteristics. Before being examined, the starters frozen at -10°С were thawed in a refrigeration chamber at 4-8°С. The starters frozen at -25 or -45°С were thawed in a water bath at 20°С.
The data characterizing the dependence of lactic acid microorganism content of the laboratory starters on the
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freezing technique and storage time are presented in Table 2.
Table 2. Number of L. bulgaricus cells in the starters after freezing
Storage Number of microorganisms, CFU/cm3 • 10 9
time, t = -10°C t = -25° t = -45°C
days 1* 2" 1 2 1 2
BBV
1 2.19 3.00 4.50 4.60 5.21 6.00
14 1.10 2.10 3.30 3.80 4.00 4.50
30 0.50 1.30 2.50 3.00 3.50 3.60
60 0.08 0.45 1.50 2.00 2.20 2.50
90 0.03 0.12 0.60 1.10 1.50 1.70
180 0.009 0.009 0.30 0.50 0.5 1.10
BBNV
1 1.10 1.20 1.90 2.00 2.50 2.70
14 0.30 0.50 1.40 1.50 2.00 2.20
30 0.10 0.25 1.10 1.20 1.60 2.00
60 0.01 0.07 0.60 0.70 1.1 1.40
90 0.007 0.007 0.30 0.45 0.80 1.10
180 0.003 0.005 0.12 0.20 0.30 0.50
Freezing in air;** freezing in the liquid coolant.
The freezing temperature and rate and the storage temperature can significantly affect the survival of the microorganisms [9-11]. Throughout the storage period, the highest survival rate of the microorganisms was observed in the starters frozen and stored in the liquid coolant at -45°C, i.e., at the minimum storage temperature used in this study. This finding is in agreement with data of other authors [9-11]. After 6-month-long storage, the average survival rate of the microorganisms was 17% of their initial number; that is, the microorganism content decreased by less than one order of magnitude. The survival rate of the microorganisms in the starters frozen in air at -45°C was somewhat lower: in 6 months: their number was approximately 10 times smaller than their initial number. The number of microorganisms in the starters frozen at -25°C was, on the average, 5-10% of their initial number, depending on the freezing regime. The lowest survival rate was observed for the microorganisms in the starters frozen at -10°C.
The rather high survival rate of the microorganisms frozen in the liquid coolant can be explained as follows. The efficiency of heat transfer in the freezing of the starters in the liquid coolant is much higher than in their freezing in air. As a consequence, the freezing time for the starters frozen in the liquid coolant is much shorter than for the starters frozen in air. Accordingly, the water crystallization rate for the starters in the liquid coolant is one order of magnitude higher. These freezing conditions minimize the destructing factors associated with water crystallization in the cells and intercellular space, which cause death of a large number of microorganisms in the starter.
The high survival rate of the lactic acid microorganisms after freezing does not ensure that they completely retain their properties and viability. The functional activity of the starter bacteria was judged from acid formation intensity data.
The acid formation activity was determined from the time required to reach pH 4.5 in culturing the microor
ganisms in reconstituted dry skim milk. Table 3 lists acid production activity data for the lactic acid bacterial cultures frozen in the liquid coolant at -45°C.
Table 3. Acid production activity data for L. bulgaricus bacteria
Bacterial Fermentation time
starter for 100 mL milk + 1 mL starter, h
before freezing after freezing
BBV 7-8 7-8
BBNV 15-16 16-17
В-3964 10-11 10-12
В-6516 10-11 10-12
These data demonstrate that, after 6-month-long storage, the starters retained their high biochemical activity; the fermentation time increased, on the average, by 1 h. The growth dynamics of the thawed L. bulgaricus cultures that were frozen in the liquid coolant at -45°C and were stored for 6 months is illustrated in Fug. 2.
2 4 6 8 10 12 14 16 18
Time, h
Fig. 2. Growth dynamics of L. bulgaricus cells in milk fermentation with the (■) BBNV and (▲) BBV starter cultures.
An important physicochemical property of a starter culture is its viscosity. Fig. 3 shows how the relative viscosity of BBV starter cultures as a result of freezing and storage under different conditions.
Fig. 3. Effect of freezing under different conditions on the relative viscosity of the BBV starter culture. Freezing in air: (1) -10°С, (3) -25°С, and (5) -45°С. Freezing in the liquid coolant: (2) -10°С, (4) -25°С, and (6) -45°С.
These data suggest that the strongest viscosityreducing effect is exerted by freezing as such: the relative viscosity decreases by a factor of 1.2-2.4, depend
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ing on the kind of starter culture and freezing technique. The largest, 2.4-fold decrease in relative viscosity was observed for BBNV frozen in air at -10 C; the smallest decrease in relative viscosity, for BBV frozen in the liquid coolant at -45°C. The decrease in relative viscosity of the bacterial starter cultures at -10°C is nearly independent of whether they were frozen in air or in the liquid coolant. In 14 days, the relative viscosity of the bacterial cultures frozen in air decreased, on the average, by a factor of 4.6 and that of the cultures frozen in the liquid coolant decreased by a factor of 3.7.
The marked decrease in the relative viscosity of the bacterial starter cultures frozen in air or in the liquid coolant at -10°C is due to the fact that slow freezing yields large ice crystals outside the cells, thus changing the initial ratio of the volumes of the intercellular and intracellular spaces through water redistribution and water-to-ice transition.
In extracellular ice formation, the growth of ice crystals in the intercellular space reduces the cell size. This leads to cell compression and to the formation of folds in the cell wall, causing mechanical damage to the protoplasm. The dehydration of the cell can lead to intimate contact between protoplasm layers located opposite to one another. As water enters the cell during thawing, the joined walls separate. This is often accompanied by protoplasm separation from the walls, with damage happening to the protoplasm structure [2, 9, 10, 12]. The disruption of the structure of the object being frozen causes a dramatic decrease in its viscosity.
Long-term storage of the frozen starters at -10°C leads to the growth of larger crystals through a decrease in the size of smaller crystals (recrystallization). In turn, this causes a still severer structural disruption in the frozen object. The viscous starter cultures BBV displayed a larger decrease in relative viscosity than the nonviscous ones. Upon 6-month-long storage, the relative viscosity of BBV frozen in air decreased by a factor of 45, while that of the nonviscous cultures decreased by a factor of 25 and 16, respectively.
The smallest decrease in viscosity was observed for the starter cultures frozen at -45°C. Upon 6-month-long storage, the relative viscosity of the starter cultures frozen in air decreased by a factor 3.8 and that of the cultures frozen in the liquid coolant decreased by a factor of 2. This insignificant decrease in the liquid viscosity is due to the high freezing rate. Rapid cooling (to -25°С or -45°C) prevents considerable water and solute redistribution by diffusion and favors the formation of small, uniformly distributed ice crystals, thus causing the least possible damage to the structure of the object.
The genetic stability of the lactic acid microorganisms in the bacterial starter cultures frozen at different temperatures and under different conditions was evaluated in terms of preservation of morphological and biochemical properties and antagonistic activity, as well as in terms of the retention of the molecular weight of, and the number of fragments in, the DNA of the bacteria— information gained using genus-specific primers (16S for-16S rev) [7].
Cell morphology depends on many factors, including the culturing conditions, the age of the culture, and the composition of the medium. In the culturing of L.
bulgaricus in the MRS Agar medium, the bacteria appear as bacilli, either separate or aggregated in chains. Figure 4 shows the micrographs of the lactic acid starter cultures recorded before their freezing and after their freezing and 6-month-long storage.
(a) (b)
(c) (d)
Fig. 4. Morphology of L. bulgaricus cells: (a) nonfrozen BBV, (b) nonfrozen BBNV, and (c, d) BBNV frozen and stored for 6 months at (c) -10 and (d) -45°С.
Considerable morphological changes were observed for all starter cultures frozen in air in all temperatures regimes and for the cultures frozen at -10°С in the liquid coolant. The microorganisms after freezing had curved cell walls, and most of then were separate. The BBNV starter cultures had lost their volutin granules, which were retained only in rare cases (Fig. 4c).
After freezing in the liquid coolant at -25 or -45°С, microorganisms with affected cell walls occurred sparsely, mostly in viscous starter cultures, and were separate or chained, and some of the bacilli had an elongated shape. Cells without volutin granules were observed in the BBNV cultures (Fig. 4f). Therefore, the freezing and low-temperature storage conditions were nondestructive.
We studied the antagonistic activity of L. delbrueckii ssp. bulgaricus strains contained in the starter cultures that had been frozen at -45°С in the liquid coolant and had been stored for 6 months. All of the strains retained a high antagonistic activity: the test bacteria growth suppression zone changed, on the average, by only 1-2mm (Table 4).
Table 4. Antagonistic activity of the L. bulgaricus cultures before and after freezing
RNCIM Growth suppression zone, mm (e ± 1.0)
number E. coli Sh. S. Proteus Proteus
Flexneri aureus vulgaris mirabilis
В-3964 22/20 -/- 26/24 23/20 19/16
В-6516 13/11 12/10 9/7 19/18 17/15
In the study of the biochemical properties of the frozen bacterial starter cultures, it was observed that the saccharolytic activity of the lactic bacteria in the frozen
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