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Salvador D, Acosta Y, Zamora A, Castillo M. Rennet-Induced Casein Micelle Aggregation Models: A Review. Foods 2022; 11:foods11091243. [PMID: 35563966 PMCID: PMC9101341 DOI: 10.3390/foods11091243] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 04/07/2022] [Accepted: 04/12/2022] [Indexed: 01/27/2023] Open
Abstract
Two phases are generally recognized in the enzymatic coagulation of milk: hydrolysis and aggregation, although nowadays more and more researchers consider the non-enzymatic phase to actually be a stage of gel formation made up of two sub-stages: micellar aggregation and hardening of the three-dimensional network of para-κ-casein. To evaluate this controversy, the main descriptive models have been reviewed. Most of them can only model micellar aggregation, without modeling the hardening stage. Some are not generalizable enough. However, more recent models have been proposed, applicable to a wide range of conditions, which could differentiate both substages. Manufacturing quality enzymatic cheeses in a cost-effective and consistent manner requires effective control of coagulation, which implies studying the non-enzymatic sub-stages of coagulation separately, as numerous studies require specific measurement methods for each of them. Some authors have recently reviewed the micellar aggregation models, but without differentiating it from hardening. Therefore, a review of the proposed models is necessary, as coagulation cannot be controlled without knowing its mechanisms and the stages that constitute it.
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Affiliation(s)
- Daniel Salvador
- Department of Agroindustrial Science, National University of Trujillo, AV. Juan Pablo II s/n—University City, Trujillo 13011, Peru;
| | - Yoseli Acosta
- School of Agroindustrial Engineering, National University of Trujillo, AV. Juan Pablo II s/n—University City, Trujillo 13011, Peru;
| | - Anna Zamora
- Department of Animal and Food Science, Centre d’Innovació, Recerca i Transferència en Tecnologia dels Aliments (CIRTTA), Universitat Autònoma de Barcelona, Travessera dels Turons s/n, Bellaterra, 08193 Barcelona, Spain;
| | - Manuel Castillo
- Department of Animal and Food Science, Centre d’Innovació, Recerca i Transferència en Tecnologia dels Aliments (CIRTTA), Universitat Autònoma de Barcelona, Travessera dels Turons s/n, Bellaterra, 08193 Barcelona, Spain;
- Correspondence: ; Tel.: +34-93-581-1123
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Grassi S, Strani L, Alamprese C, Pricca N, Casiraghi E, Cabassi G. A FT-NIR Process Analytical Technology Approach for Milk Renneting Control. Foods 2021; 11:foods11010033. [PMID: 35010158 PMCID: PMC8750718 DOI: 10.3390/foods11010033] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 12/14/2021] [Accepted: 12/20/2021] [Indexed: 01/24/2023] Open
Abstract
The study proposes a process analytical technology (PAT) approach for the control of milk coagulation through near infrared spectroscopy (NIRS), computing multivariate statistical process control (MSPC) charts, based on principal component analysis (PCA). Reconstituted skimmed milk and commercial pasteurized skimmed milk were mixed at two different ratios (60:40 and 40:60). Each mix ratio was prepared in six replicates and used for coagulation trials, monitored by fundamental rheology, as a reference method, and NIRS by inserting a probe directly in the coagulation vat and collecting spectra at two different acquisition times, i.e., 60 s or 10 s. Furthermore, three failure coagulation trials were performed, deliberately changing temperature or rennet and CaCl2 concentration. The comparison with fundamental rheology results confirmed the effectiveness of NIRS to monitor milk renneting. The reduced spectral acquisition time (10 s) showed data highly correlated (r > 0.99) to those acquired with longer acquisition time. The developed decision trees, based on PC1 scores and T2 MSPC charts, confirmed the suitability of the proposed approach for the prediction of coagulation times and for the detection of possible failures. In conclusion, the work provides a robust but simple PAT approach to assist cheesemakers in monitoring the coagulation step in real-time.
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Affiliation(s)
- Silvia Grassi
- Department of Food, Environmental and Nutritional Sciences, Università degli Studi di Milano, Via Giovanni Celoria 2, 20133 Milan, Italy; (S.G.); (L.S.); (E.C.)
| | - Lorenzo Strani
- Department of Food, Environmental and Nutritional Sciences, Università degli Studi di Milano, Via Giovanni Celoria 2, 20133 Milan, Italy; (S.G.); (L.S.); (E.C.)
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via Campi 103, 41125 Modena, Italy
| | - Cristina Alamprese
- Department of Food, Environmental and Nutritional Sciences, Università degli Studi di Milano, Via Giovanni Celoria 2, 20133 Milan, Italy; (S.G.); (L.S.); (E.C.)
- Correspondence: ; Tel.: +39-0250319187
| | - Nicolò Pricca
- Centro di ricerca Zootecnia e Acquacoltura (CREA-ZA), Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria, Via Antonio Lombardo 11, 26900 Lodi, Italy; (N.P.); (G.C.)
| | - Ernestina Casiraghi
- Department of Food, Environmental and Nutritional Sciences, Università degli Studi di Milano, Via Giovanni Celoria 2, 20133 Milan, Italy; (S.G.); (L.S.); (E.C.)
| | - Giovanni Cabassi
- Centro di ricerca Zootecnia e Acquacoltura (CREA-ZA), Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria, Via Antonio Lombardo 11, 26900 Lodi, Italy; (N.P.); (G.C.)
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Sheidaei Z, Sarmadi B, Hosseini SM, Javanmardi F, Khosravi-Darani K, Mortazavian AM. Influence of κ-Carrageenan, Modified Starch and Inulin Addition on Rheological and Sensory Properties of Non-fat and Non-added Sugar Dairy Dessert. CURRENT NUTRITION & FOOD SCIENCE 2020. [DOI: 10.2174/1573401315666190301152645] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
<P>Background: The high amounts of fat, sugar and calorie existing in dairy desserts can lead
to increase the risk of health problems. Therefore, the development of functional and dietary forms of
these products can help the consumer health.
</P><P>
Objective: This study aims to investigate the effects of κ-carrageenan, modified starch and inulin addition
on rheological and sensory properties of non-fat and non-added sugar dairy dessert.
</P><P>
Methods: In order to determine the viscoelastic behavior of samples, oscillatory test was carried out
and the values of storage modulus (G′), loss modulus (G″), loss angle tangent (tan δ) and complex
viscosity (η*) were measured. TPA test was used for analysis of the desserts’ texture and textural parameters
of samples containing different concentrations of carrageenan, starch and inulin were calculated.
</P><P>
Results: All treatments showed a viscoelastic gel structure with the storage modulus higher than the
loss modulus values. Increasing amounts of κ-carrageenan and modified starch caused an increase in
G′ and G″ as well as η* and a decrease in tan δ. Also, firmness and cohesiveness were enhanced. The
trained panelists gave the highest score to the treatment with 0.1% κ-carrageenan, 2.5% starch and
5.5% inulin (sucralose as constant = 0.25%) and this sample was the best treatment with desirable attributes
for the production of non-fat and non-added sugar dairy dessert.
</P><P>
Conclusion: It can be concluded that the concentration of κ-carrageenan and starch strongly influenced
the rheological and textural properties of dairy desserts, whereas the inulin content had little
effect on these attributes.</P>
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Affiliation(s)
- Zhaleh Sheidaei
- Student Research Committee, Department of Food Technology, Faculty of Nutrition Sciences and Food Technology/ National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Bahareh Sarmadi
- Student Research Committee, Department of Food Technology, Faculty of Nutrition Sciences and Food Technology/ National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Seyede M. Hosseini
- Department of Food Science and Technology, National Nutrition and Food Technology Research Institute, Faculty of Nutrition Sciences, Food Science and Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fardin Javanmardi
- Student Research Committee, Department of Food Technology, Faculty of Nutrition Sciences and Food Technology/ National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Kianoush Khosravi-Darani
- Department of Food Technology Research, National Nutrition and Food Technology Research Institute, Faculty of Nutrition Sciences, Food Science and Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Amir M. Mortazavian
- Department of Food Science and Technology, National Nutrition and Food Technology Research Institute, Faculty of Nutrition Sciences, Food Science and Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Arango O, Trujillo AJ, Castillo M. Inline control of yoghurt fermentation process using a near infrared light backscatter sensor. J FOOD ENG 2020. [DOI: 10.1016/j.jfoodeng.2019.109885] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Panthi RR, Kelly AL, O'Callaghan DJ, Sheehan JJ. Measurement of syneretic properties of rennet-induced curds and impact of factors such as concentration of milk: A review. Trends Food Sci Technol 2019. [DOI: 10.1016/j.tifs.2019.07.023] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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7
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Salvador D, Arango O, Castillo M. In-line estimation of the elastic module of milk gels with variation of temperature protein concentration. Int J Food Sci Technol 2018. [DOI: 10.1111/ijfs.13944] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Daniel Salvador
- Departament de Ciència Animal i dels Aliments; Centre d'Innovació, Recerca i Transferència en Tecnologia dels Aliments (CIRTTA); Universitat Autònoma de Barcelona; Edifici V - Campus de la UAB 08193 Bellaterra (Cerdanyola del Valles) Barcelona Spain
| | - Oscar Arango
- Facultad de Ingeniería Agroindustrial; Ciudad Universitaria Torobajo; Universidad de Nariño; calle 18 carrera 50 Pasto Nariño Colombia
| | - Manuel Castillo
- Departament de Ciència Animal i dels Aliments; Centre d'Innovació, Recerca i Transferència en Tecnologia dels Aliments (CIRTTA); Universitat Autònoma de Barcelona; Edifici V - Campus de la UAB 08193 Bellaterra (Cerdanyola del Valles) Barcelona Spain
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Panikuttira B, O'Shea N, Tobin JT, Tiwari BK, O'Donnell CP. Process analytical technology for cheese manufacture. Int J Food Sci Technol 2018. [DOI: 10.1111/ijfs.13806] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Bhavya Panikuttira
- School of Biosystems and Food Engineering; University College Dublin; Belfield D4 Dublin Ireland
| | - Norah O'Shea
- Food Chemistry and Technology Department; Teagasc Food Research Centre; Moorepark, Fermoy Co.Cork Ireland
| | - John T. Tobin
- Food Chemistry and Technology Department; Teagasc Food Research Centre; Moorepark, Fermoy Co.Cork Ireland
| | - Brijesh K. Tiwari
- Food Chemistry and Technology Department; Teagasc Food Research Centre; Ashtown D15 Dublin Ireland
| | - Colm P. O'Donnell
- School of Biosystems and Food Engineering; University College Dublin; Belfield D4 Dublin Ireland
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Derra M, Bakkali F, Amghar A, Sahsah H. Estimation of coagulation time in cheese manufacture using an ultrasonic pulse-echo technique. J FOOD ENG 2018. [DOI: 10.1016/j.jfoodeng.2017.08.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Panthi RR, Kelly AL, Hennessy D, McAuliffe S, Mateo M, O'Donnell C, O'Callaghan DJ, Sheehan JJ. Kinetics of moisture loss during stirring of cheese curds produced from standardised milks of cows on pasture or indoor feeding systems. INT J DAIRY TECHNOL 2017. [DOI: 10.1111/1471-0307.12489] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Ram R Panthi
- School of Food and Nutritional Sciences; University College Cork; Ireland
- Teagasc Food Research Centre; Moorepark, Fermoy, Co.; Cork Ireland
| | - Alan L Kelly
- School of Food and Nutritional Sciences; University College Cork; Ireland
| | - Deirdre Hennessy
- Teagasc Animal and Grassland Research and Innovation Centre; Moorepark, Fermoy, Co.; Cork Ireland
| | - Stephen McAuliffe
- Teagasc Animal and Grassland Research and Innovation Centre; Moorepark, Fermoy, Co.; Cork Ireland
- School of Biological Sciences; Queen's University; Belfast BT7 1NN UK
| | - Maria Mateo
- UCD Schools of Biosystems and Food Engineering; Dublin Ireland
| | - Colm O'Donnell
- UCD Schools of Biosystems and Food Engineering; Dublin Ireland
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11
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Prediction of milk coagulation time using an ultrasonic experimental and theoretical method based on Argand diagram. JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION 2017. [DOI: 10.1007/s11694-017-9567-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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12
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Bent Fiber Sensor for Preservative Detection in Milk. SENSORS 2016; 16:s16122094. [PMID: 27941703 PMCID: PMC5191074 DOI: 10.3390/s16122094] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Revised: 11/29/2016] [Accepted: 12/06/2016] [Indexed: 11/16/2022]
Abstract
A fiber optic sensor sensitive to refractive index changes of the outer region of the fiber cladding is presented. The sensor uses bent plastic optical fibers in different bending lengths to increase sensitivity. Measurements were made for low-fat milk, the refractive index of which is altered by some preservatives such as formaldehyde, hydrogen peroxide, and sodium carbonate. Concentrations of the preservatives in the milk were changed between 0% and 14.3% while the refractive indices occurred between 1.34550 and 1.35093 for the minimum (0%) and maximum (14.286%) concentrations of sodium carbonate, respectively. Due to bending-induced sensitivity, the sensor is able to detect refractive index changes less of than 0.4%. The results show that there is excellent linearity between the concentration and normalized response of the sensor.
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