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Salunke P, Metzger LE. Transglutaminase Crosslinked Milk Protein Concentrate and Micellar Casein Concentrate: Impact on the Functionality of Imitation Mozzarella Cheese Manufactured on a Small Scale Using a Rapid Visco Analyzer. Foods 2024; 13:2720. [PMID: 39272486 PMCID: PMC11394472 DOI: 10.3390/foods13172720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2024] [Revised: 08/23/2024] [Accepted: 08/26/2024] [Indexed: 09/15/2024] Open
Abstract
In dairy-based imitation mozzarella cheese (IMC) formulations, intact casein is critical and imparts IMC with a firm and elastic, stringy, melted texture. Rennet casein (RCN) is the desired ingredient to provide intact casein in IMC and is preferred over milk protein concentrate (MPC) and micellar casein concentrate (MCC). Transglutaminase (TGase), a crosslinking enzyme, alters the physical properties of MPC or MCC and may change IMC functionality. The objective of this study was to determine the effect of TGase-crosslinked MPC and MCC powders on the functionality of IMCs. The TGase treatment included TGase at 0.3 (L) and 3.0 (H) units/g of protein and a control (C) with no TGase addition. Each IMC formulation was balanced for constituents and was produced in a Rapid Visco Analyzer (RVA). The MCC or MPC powder with high TGase enzyme in IMC formulation did not form an emulsion. The IMC containing TGase-treated powders had a significantly (p ≤ 0.05) higher RVA-viscosity during manufacture and transition temperature (TT), and a significantly (p ≤ 0.05) lower Schreiber melt test area. The IMC made from MPC (with or without TGase) had lower TT values and Schreiber melt test area as compared with that made from MCC. The TGase-treated MPC and MCC, when used for IMC manufacture, were comparable to IMC manufactured with RCN in texture and some measured melted characteristics. In conclusion, TGase treatment alters the melt characteristics of MCC and MPC in IMC applications.
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Affiliation(s)
- Prafulla Salunke
- Department of Dairy and Food Science, Midwest Dairy Foods Research Center, South Dakota State University, Brookings, SD 57007, USA
| | - Lloyd E Metzger
- Department of Dairy and Food Science, Midwest Dairy Foods Research Center, South Dakota State University, Brookings, SD 57007, USA
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2
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Alsaleem KA, Hammam ARA, Metzger LE. Lactose-6-phosphate as an alternative to disodium phosphate in the production of processed cheese food. J Dairy Sci 2024; 107:3420-3428. [PMID: 38246552 DOI: 10.3168/jds.2023-24157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 12/18/2023] [Indexed: 01/23/2024]
Abstract
Processed cheese food (PCF) is a dairy product prepared by blending dairy ingredients with nondairy ingredients and heating the blend with agitation to produce a homogeneous product with an extended shelf life. Emulsifying salts (ES), such as disodium phosphate (DSP) and trisodium citrate, have a critical effect on the emulsification characteristics of casein by sequestering the calcium from the calcium-paracaseinate phosphate complex in natural cheese. Lactose-6-phosphate (LP) is an organic compound produced from lactose that has the potential to function as ES. Lactose-6-phosphate is not approved for use as a substitute for ES in the large-scale production of PC. The objective of this study was to produce PCF with LP instead of DSP. Lactose-6-phosphate was prepared by mixing 1 mol of α-lactose with 0.5 mol of sodium cyclo-triphosphate. The pH of recombined solutions was adjusted using sodium hydroxide to get a pH of 12 to obtain 60.74% LP. The solution was stirred for 3 d at room temperature and then concentrated to 52% total solids (TS). The ingredients in the PCF formulations were Cheddar cheese, butter, water, milk permeate powder, and LP (at a ratio of 2.0, 2.4, 2.8, 3.2, 4.0, 5.0, and 6.0%) were formulated to contain 17.0% protein, 25.0% fat, 44.0% moisture, and 2.0% salt. Processed cheese food made with 2.0% DSP was also produced as a control. The PCF was prepared by mixing all ingredients in a Kitchen Aid stand mixer to make a homogeneous paste. A 25-g sample of the mixture was cooked in the rapid visco analyzer (Perten RVA 4500, Macquarie Park, Australia) for 3 min at 95°C at 1,000 rpm for the first 2 min and 160 rpm for the last minute. The PCF was then transferred into molds and refrigerated till further analyses. The PCF was analyzed for moisture, pH, end apparent cooked viscosity, hardness, melted diameter, and melting temperature. The experiment was repeated 3 times using different batches of LP. The moisture of PCF ranged from 42.3% to 44.0% with a pH of 5.6 to 5.8. The end apparent cooked viscosity increased from 818.0 to 2,060.0 cP as the level of LP raised from 0.63% to 1.90%, whereas it was 660.0 cP in control. The hardness of PCF made with LP elevated from 61.9 to 110.1g as the level of LP increased; however, it was 85.6 g in control. The melted diameter decreased from 43 mm in control to 29 mm in 1.90% LP, while the melting temperature of PCF increased from 37.7°C in control to 59.0°C in 1.90% LP. We conclude that LP can be used as a substitute for DSP in PCF manufacture and has more capacity than DSP.
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Affiliation(s)
- Khalid A Alsaleem
- Dairy and Food Science Department, South Dakota State University, Brookings, SD 57007; Department of Food Science and Human Nutrition, College of Agriculture and Food, Qassim University, Buraydah 51452, Saudi Arabia.
| | - Ahmed R A Hammam
- Dairy and Food Science Department, South Dakota State University, Brookings, SD 57007; Dairy Science Department, Faculty of Agriculture, Assiut University, Assiut 71526, Egypt
| | - Lloyd E Metzger
- Dairy and Food Science Department, South Dakota State University, Brookings, SD 57007
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Atik DS, Huppertz T. Melting of natural cheese: A review. Int Dairy J 2023. [DOI: 10.1016/j.idairyj.2023.105648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
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Salunke P, Marella C, Amamcharla J, Muthukumarappan K, Metzger L. Use of micellar casein concentrate and milk protein concentrate treated with transglutaminase in imitation cheese products—Melt and stretch properties. J Dairy Sci 2022; 105:7904-7916. [DOI: 10.3168/jds.2022-22253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 06/16/2022] [Indexed: 11/19/2022]
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Highly concentrated micellar casein: Impact of its storage stability on the functional characteristics of process cheese products. Lebensm Wiss Technol 2022. [DOI: 10.1016/j.lwt.2022.113384] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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6
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Salunke P, Metzger LE. Functional characteristics of process cheese product as affected by milk protein concentrate and micellar casein concentrate at different usage levels. Int Dairy J 2022. [DOI: 10.1016/j.idairyj.2022.105324] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Chudy S, Makowska A, Krzywdzińska‐Bartkowiak M, Piątek M, Henriques M, Borges AR, Gomes D, Pereira CD. The effect of microparticulated whey protein on the characteristics of reduced‐fat cheese and of the corresponding microwave vacuum‐dried cheese puffs and finely ground puffs. INT J DAIRY TECHNOL 2021. [DOI: 10.1111/1471-0307.12796] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Sylwia Chudy
- Faculty of Food Science and Nutrition Poznań University of Life Sciences Wojska Polskiego 28 60‐637 Poznań
| | - Agnieszka Makowska
- Faculty of Food Science and Nutrition Poznań University of Life Sciences Wojska Polskiego 28 60‐637 Poznań
| | | | - Michał Piątek
- Faculty of Food Science and Nutrition Poznań University of Life Sciences Wojska Polskiego 28 60‐637 Poznań
| | - Marta Henriques
- Department of Food Science and Technology Polytechnic Institute of Coimbra Bencanta Coimbra3045‐601Portugal
- CERNAS‐Research Centre for Natural Resources, Environment and Society College of Agriculture Bencanta 3045‐601 Coimbra Portugal
| | - Ana Raquel Borges
- Department of Food Science and Technology Polytechnic Institute of Coimbra Bencanta Coimbra3045‐601Portugal
| | - David Gomes
- Department of Food Science and Technology Polytechnic Institute of Coimbra Bencanta Coimbra3045‐601Portugal
| | - Carlos Dias Pereira
- Department of Food Science and Technology Polytechnic Institute of Coimbra Bencanta Coimbra3045‐601Portugal
- CERNAS‐Research Centre for Natural Resources, Environment and Society College of Agriculture Bencanta 3045‐601 Coimbra Portugal
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Le Tohic C, O'Sullivan JJ, Drapala KP, Chartrin V, Chan T, Morrison AP, Kerry JP, Kelly AL. Effect of 3D printing on the structure and textural properties of processed cheese. J FOOD ENG 2018. [DOI: 10.1016/j.jfoodeng.2017.02.003] [Citation(s) in RCA: 165] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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9
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Bi W, Li X, Zhao Y, Zhao W, He S, Ge W, Jiang C. Imitation Cheese Manufacture Using Rapid Visco-Analyzer and Its Optimization. INTERNATIONAL JOURNAL OF FOOD PROPERTIES 2016. [DOI: 10.1080/10942912.2015.1047515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Stephani R, Borges de Souza A, Leal de Oliveira MA, Perrone ÍT, Fernandes de Carvalho A, Cappa de Oliveira LF. Evaluation of the synergistic effects of milk proteins in a rapid viscosity analyzer. J Dairy Sci 2015; 98:8333-47. [PMID: 26409966 DOI: 10.3168/jds.2015-9300] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2015] [Accepted: 08/09/2015] [Indexed: 11/19/2022]
Abstract
Protein systems (PS) are routinely used by companies from Brazil and around the globe to improve the texture, yield, and palatability of processed foods. Understanding the synergistic behavior among the different protein structures of these systems during thermal treatment under the influence of pH can help to better define optimum conditions for products and processes. The interpretation of the reactions and interactions that occur simultaneously among the protein constituents of these systems as dispersions during thermal processing is still a major challenge. Here, using a rapid viscosity analyzer, we observed the rheological changes in the startup viscosities of 5 PS obtained by combining varying proportions of milk protein concentrate and whey protein concentrate under different conditions of pH (5.0, 6.5, and 7.0) and heat processing (85°C/15min and 95°C/5min). The solutions were standardized to 25% of total solids and 17% of protein. Ten analytical parameters were used to characterize each of the startup-viscosity ramps for 35 experiments conducted in a 2×3 × 5 mixed planning matrix, using principal component analysis to interpret behavioral similarities. The study showed the clear influence of pH 5.5 in the elevation of the initial temperature of the PS startup viscosity by at least 5°C, as well as the effect of different milk protein concentrate:whey protein concentrate ratios above 15:85 at pH 7.0 on the viscographic profile curves. These results suggested that the primary agent driving the changes was the synergism among the reactions and interactions of casein with whey proteins during processing. This study reinforces the importance of the rapid viscosity analyzer as an analytical tool for the simulation of industrial processes involving PS, and the use of the startup viscosity ramp as a means of interpreting the interactions of system components with respect to changes related to the treatment temperature.
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Affiliation(s)
- Rodrigo Stephani
- Núcleo de Espectroscopia e Estrutura Molecular, Departamento de Química, Universidade Federal de Juiz de Fora, 36036-330, Juiz de Fora, MG, Brazil; Tate & Lyle Gemacom Tech, Bruno Simili, 36092-050, Juiz de Fora, MG, Brazil
| | | | - Marcone Augusto Leal de Oliveira
- Núcleo de Espectroscopia e Estrutura Molecular, Departamento de Química, Universidade Federal de Juiz de Fora, 36036-330, Juiz de Fora, MG, Brazil
| | - Ítalo Tuler Perrone
- Department of Food Technology, Federal University of Viçosa, 36571-000, Viçosa, MG, Brazil
| | | | - Luiz Fernando Cappa de Oliveira
- Núcleo de Espectroscopia e Estrutura Molecular, Departamento de Química, Universidade Federal de Juiz de Fora, 36036-330, Juiz de Fora, MG, Brazil.
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Amamcharla J, Metzger L. Prediction of process cheese instrumental texture and melting characteristics using dielectric spectroscopy and chemometrics. J Dairy Sci 2015; 98:6004-13. [DOI: 10.3168/jds.2015-9739] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2015] [Accepted: 05/23/2015] [Indexed: 11/19/2022]
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Giri A, Kanawjia SK, Khetra Y. Textural and Melting Properties of Processed Cheese Spread as Affected by Incorporation of Different Inulin Levels. FOOD BIOPROCESS TECH 2013. [DOI: 10.1007/s11947-013-1235-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Ye A, Hewitt S, Taylor S. Characteristics of rennet–casein-based model processed cheese containing maize starch: Rheological properties, meltabilities and microstructures. Food Hydrocoll 2009. [DOI: 10.1016/j.foodhyd.2008.08.016] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Ye A, Hewitt S. Phase structures impact the rheological properties of rennet-casein-based imitation cheese containing starch. Food Hydrocoll 2009. [DOI: 10.1016/j.foodhyd.2008.05.004] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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16
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Utilisation of front face fluorescence spectroscopy as a tool for the prediction of some chemical parameters and the melting point of semi-hard and hard cheeses: a preliminary study. Eur Food Res Technol 2007. [DOI: 10.1007/s00217-007-0640-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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17
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Purna SKG, Pollard A, Metzger LE. Effect of Formulation and Manufacturing Parameters on Process Cheese Food Functionality—I. Trisodium Citrate. J Dairy Sci 2006; 89:2386-96. [PMID: 16772554 DOI: 10.3168/jds.s0022-0302(06)72311-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
The objective of this research was to use a Rapid Visco Analyzer to study the effect of natural cheese age, trisodium citrate (TSC) concentration, and mixing speed on process cheese food (PCF) functionality. In this study 3 replicates of natural cheese were manufactured, and a portion of each cheese was subjected to 6 different PCF manufacturing treatments at 2, 4, 6, 12, and 18 wk of ripening. These treatments were factorial combinations of 3 levels of TSC (i.e., 2.0, 2.5, and 3.0%) and 2 mixing speeds during manufacture (450 and 1,050 rpm). Functional properties of the PCF evaluated included manufacturing properties [apparent viscosity after manufacture (VAM)], unmelted textural properties (firmness), melted cheese flow properties [hot apparent viscosity (HAV)], and cheese thickening during cooling [time at 5000 cP (T5)]. All 4 parameters (VAM, firmness, HAV, and T5) were significantly affected by natural cheese age and mixing speed, whereas VAM, HAV, and T5 were also significantly influenced by the amount of TSC. The VAM and firmness decreased as cheese age increased, whereas T5 values increased as cheese age increased. Similarly, VAM, HAV, and firmness values increased because of the increased mixing speed, whereas T5 values decreased. The age x mixing speed interaction was significant for VAM and firmness. The age x concentration of the TSC interaction term was significant for VAM, whereas the age x age x TSC concentration term was significant for HAV. The results demonstrate that natural cheese age, mixing speed during manufacture, and concentration of TSC have a significant impact on process cheese functionality.
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Affiliation(s)
- S K Garimella Purna
- Minnesota-South Dakota Dairy Foods Research Center, Department of Food Science and Nutrition, University of Minnesota, St. Paul 55108, USA
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Takahashi K, Nakanou KI, Mizuno R, Iwatsuki K. Characterization by Rapid Visco Analyzer of Suitability of Different Types of Cheese as Ingredients for Processed Cheese. J JPN SOC FOOD SCI 2006. [DOI: 10.3136/nskkk.53.312] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Abstract
Numerous formulation and processing parameters influence the functional properties of process cheese. Recently, a small-scale (25 g) manufacturing and analysis method was developed using a rapid visco analyzer (RVA), which was designed to evaluate the functional properties of process cheese when subjected to various formulations and processing conditions. Although this method successfully manufactured process cheese, there was a significant difference in the functional properties of the process cheese compared with process cheese manufactured on a pilot scale. In the present study, adjustments in the RVA methodology involving the RVA processing conditions, preblend preparation, and texture profile analysis (TPA) techniques for the final process cheese were investigated. Fourteen samples of pasteurized processed cheese food (PCF) were manufactured from 14 different preblends. Each pre-blend was prepared using 1 of the 14 different natural cheeses and was balanced for moisture, fat, and salt. Each of these 14 preblends was split into 3 portions and each portion was subjected to 3 different manufacturing treatments. The first treatment was manufactured in a pilot-scale Blentech twin screw (BTS) cooker, and the remaining 2 treatments were manufactured in an RVA with different processing profiles. The RVA treatments were produced in triplicate. The resulting process cheeses were analyzed for moisture and functional properties. Texture profile analysis and RVA melt analyses were performed on all PCF treatments. Additionally, for the RVA treatments, the data for time of emulsification and end apparent viscosity during RVA manufacture were collected and recorded. The functional properties of the PCF manufactured using the RVA treatments showed good correlation with the functional properties of the PCF produced on the pilot scale. Additionally, the end apparent viscosity during RVA manufacture was correlated with the functional properties of the process cheese. Consequently, the RVA can be used as a small-scale manufacturing and analysis tool for predicting the functional properties of process cheese, and for evaluating how various formulations and processing parameters affect these functional properties. Moreover, the adjustments in the RVA methodology produced process cheese with functionality similar to process cheese produced in the BTS.
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Affiliation(s)
- R Kapoor
- MN-SD Dairy Foods Research Center, Department of Food Science and Nutrition, University of Minnesota, St. Paul 55108, USA
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