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Molle A, Cipolat-Gotet C, Stocco G, Ferragina A, Berzaghi P, Summer A. The use of milk Fourier-transform infrared spectra for predicting cheesemaking traits in Grana Padano Protected Designation of Origin cheese. J Dairy Sci 2024; 107:1967-1979. [PMID: 37863286 DOI: 10.3168/jds.2023-23827] [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: 06/01/2023] [Accepted: 10/03/2023] [Indexed: 10/22/2023]
Abstract
The prediction of the cheese yield (%CY) traits for curd, solids, and retained water and the amount of fat, protein, solids, and energy recovered from the milk into the curd (%REC) by Bayesian models, using Fourier-transform infrared spectroscopy (FTIR), can be of significant economic interest to the dairy industry and can contribute to the improvement of the cheese process efficiency. The yields give a quantitative measure of the ratio between weights of the input and output of the process, whereas the nutrient recovery allows to assess the quantitative transfer of a component from milk to cheese (expressed in % of the initial weight). The aims of this study were: (1) to investigate the feasibility of using bulk milk spectra to predict %CY and %REC traits, and (2) to quantify the effect of the dairy industry and the contribution of single-spectrum wavelengths on the prediction accuracy of these traits using vat milk samples destined to the production of Grana Padano Protected Designation of Origin cheese. Information from 72 cheesemaking days (in total, 216 vats) from 3 dairy industries were collected. For each vat, the milk was weighed and analyzed for composition (total solids [TS], lactose, protein, and fat). After 48 h from cheesemaking, each cheese was weighed, and the resulting whey was sampled for composition as well (TS, lactose, protein, and fat). Two spectra from each milk sample were collected in the range between 5,011 and 925 cm-1 and averaged before the data analysis. The calibration models were developed via a Bayesian approach by using the BGLR (Bayesian Generalized Linear Regression) package of R software. The performance of the models was assessed by the coefficient of determination (R2VAL) and the root mean squared error (RMSEVAL) of validation. Random cross-validation (CVL) was applied [80% calibration and 20% validation set] with 10 replicates. Then, a stratified cross-validation (SCV) was performed to assess the effect of the dairy industry on prediction accuracy. The study was repeated using a selection of informative wavelengths to assess the necessity of using whole spectra to optimize prediction accuracy. Results showed the feasibility of using FTIR spectra and Bayesian models to predict cheesemaking traits. The R2VAL values obtained with the CVL procedure were promising in particular for the %CY and %REC for protein, ranging from 0.44 to 0.66 with very low RMSEVAL (from 0.16 to 0.53). Prediction accuracy obtained with the SCV was strongly influenced by the dairy factory industry. The general low values gained with the SCV do not permit a practical application of this approach, but they highlight the importance of building calibration models with a dataset covering the largest possible sample variability. This study also demonstrated that the use of the full FTIR spectra may be redundant for the prediction of the cheesemaking traits and that a specific selection of the most informative wavelengths led to improved prediction accuracy. This could lead to the development of dedicated spectrometers using selected wavelengths with built-in calibrations for the online prediction of these innovative traits.
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Affiliation(s)
- Arnaud Molle
- Department of Veterinary Science, University of Parma, 43126 Parma, Italy
| | | | - Giorgia Stocco
- Department of Veterinary Science, University of Parma, 43126 Parma, Italy.
| | - Alessandro Ferragina
- Food Quality and Sensory Science Department, Teagasc Food Research Centre, D15 KN3K, Ireland
| | - Paolo Berzaghi
- University of Padova, Department of Animal Medicine, Production and Health, Padova, Italy 35020
| | - Andrea Summer
- Department of Veterinary Science, University of Parma, 43126 Parma, Italy
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Franceschi P, Formaggioni P, Brasca M, Natrella G, Faccia M, Malacarne M, Summer A. Fatty acids composition and lipolysis of Parmigiano Reggiano PDO cheese: effect of the milk cooling temperature at the farm. Anim Biosci 2023; 36:132-143. [PMID: 35798045 PMCID: PMC9834655 DOI: 10.5713/ab.22.0080] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 05/23/2022] [Indexed: 01/27/2023] Open
Abstract
OBJECTIVE The aim was to study the influence of cooling milk at 9°C at the farm versus keeping it at 20°C on Parmigiano Reggiano cheese lipolysis. METHODS A total of six cheesemaking trials (3 in winter and 3 in summer) were performed. In each trial, milk was divided continuously into two identical aliquots, one of which was kept at 9°C (MC9) and the other at 20°C (MC20). For each trial and milk temperature, vat milk (V-milk) and the resulting 21 month ripened cheese were analysed. RESULTS Fat and dry matter and fat/casein ratio were lower in MC9 V-milk (p≤0.05) than in MC20. Total bacteria, mesophilic lactic acid and psychrotrophic and lipolytic bacteria showed significant differences (p≤0.05) between the two V-milks. Regarding cheese, fat content resulted lower and crude protein higher (p≤0.05) both in outer (OZ) and in inner zone (IZ) of the MC9 cheese wheels. Concerning total fatty acids, the MC9 OZ had a lower concentration of butyric, capric (p≤0.05) and medium chain fatty acids (p≤0.05), while the MC9 IZ had lower content of butyric (p≤0.05), caproic (p≤0.01) and short chain fatty acids (p≤0.05). The levels of short chain and medium chain free fatty acids (p≤0.05) were lower and that of long chain fatty acids (p≤0.05) was higher in MC9 OZ cheese. The principal component analysis of total and free fatty acids resulted in a clear separation among samples by seasons, whereas slight differences were observed between the two different milk temperatures. CONCLUSION Storing milk at 9°C at the herd affects the chemical composition of Parmigiano Reggiano, with repercussion on lipolysis. However, the changes are not very relevant, and since the cheese can present a high variability among the different cheese factories, such changes should be considered within the "normal variations" of Parmigiano Reggiano chemical characteristics.
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Affiliation(s)
- Piero Franceschi
- Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126, Parma,
Italy
| | - Paolo Formaggioni
- Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126, Parma,
Italy
| | - Milena Brasca
- Institute of Sciences of Food Production, National Research Council, Via Celoria 2, IT-20133 Milano,
Italy
| | - Giuseppe Natrella
- Department of Soil, Plant and Food Sciences, University of Bari, Via Amendola 165/A, 70125 Bari,
Italy,Corresponding Authors: Giuseppe Natrella, Tel: +39-080-5443012, Fax: +39-080-5442942, E-mail: . Massimo Malacarne, Tel: +39-0521-032615, Fax: +39-0521-032611, E-mail:
| | - Michele Faccia
- Department of Soil, Plant and Food Sciences, University of Bari, Via Amendola 165/A, 70125 Bari,
Italy
| | - Massimo Malacarne
- Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126, Parma,
Italy,Corresponding Authors: Giuseppe Natrella, Tel: +39-080-5443012, Fax: +39-080-5442942, E-mail: . Massimo Malacarne, Tel: +39-0521-032615, Fax: +39-0521-032611, E-mail:
| | - Andrea Summer
- Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126, Parma,
Italy
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Mariani E, Malacarne M, Cipolat-Gotet C, Cecchinato A, Bittante G, Summer A. Prediction of fresh and ripened cheese yield using detailed milk composition and udder health indicators from individual Brown Swiss cows. Front Vet Sci 2022; 9:1012251. [PMID: 36311669 PMCID: PMC9606222 DOI: 10.3389/fvets.2022.1012251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 09/20/2022] [Indexed: 11/04/2022] Open
Abstract
The composition of raw milk is of major importance for dairy products, especially fat, protein, and casein (CN) contents, which are used worldwide in breeding programs for dairy species because of their role in human nutrition and in determining cheese yield (%CY). The aim of the study was to develop formulas based on detailed milk composition to disentangle the role of each milk component on %CY traits. To this end, 1,271 individual milk samples (1.5 L/cow) from Brown Swiss cows were processed according to a laboratory model cheese-making procedure. Fresh %CY (%CYCURD), total solids and water retained in the fresh cheese (%CYSOLIDS and %CYWATER), and 60-days ripened cheese (%CYRIPENED) were the reference traits and were used as response variables. Training-testing linear regression modeling was performed: 80% of observations were randomly assigned to the training set, 20% to the validation set, and the procedure was repeated 10 times. Four groups of predictive equations were identified, in which different combinations of predictors were tested separately to predict %CY traits: (i) basic composition, i.e., fat, protein, and CN, tested individually and in combination; (ii) udder health indicators (UHI), i.e., fat + protein or CN + lactose and/or somatic cell score (SCS); (iii) detailed protein profile, i.e., fat + protein fractions [CN fractions, whey proteins, and nonprotein nitrogen (NPN) compounds]; (iv) detailed protein profile + UHI, i.e., fat + protein fractions + NPN compounds and/or UHI. Aside from the positive effect of fat, protein, and total casein on %CY, our results allowed us to disentangle the role of each casein fraction and whey protein, confirming the central role of β-CN and κ-CN, but also showing α-lactalbumin (α-LA) to have a favorable effect, and β-lactoglobulin (β-LG) a negative effect. Replacing protein or casein with individual milk protein and NPN fractions in the statistical models appreciably increased the validation accuracy of the equations. The cheese industry would benefit from an improvement, through genetic selection, of traits related to cheese yield and this study offers new insights into the quantification of the influence of milk components in composite selection indices with the aim of directly enhancing cheese production.
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Affiliation(s)
- Elena Mariani
- Department of Veterinary Science, University of Parma, Parma, Italy
| | | | - Claudio Cipolat-Gotet
- Department of Veterinary Science, University of Parma, Parma, Italy,*Correspondence: Claudio Cipolat-Gotet
| | - Alessio Cecchinato
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Legnaro, Italy
| | - Giovanni Bittante
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Legnaro, Italy
| | - Andrea Summer
- Department of Veterinary Science, University of Parma, Parma, Italy
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Tarhan Ö, Kaya A. Investigation of the compositional and structural changes in the proteins of cow milk when processed to cheese. Lebensm Wiss Technol 2021. [DOI: 10.1016/j.lwt.2021.112102] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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5
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Zicarelli L, Napolano R, Campanile G, Zullo G, Zicarelli F, Neri D, Di Luccia A, Di Palo R, la Gatta B. Influence of milk protein polymorphism of Italian Brown and French Holstein cows on curd yield. Int Dairy J 2021. [DOI: 10.1016/j.idairyj.2021.105083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Pegolo S, Giannuzzi D, Bisutti V, Tessari R, Gelain ME, Gallo L, Schiavon S, Tagliapietra F, Trevisi E, Ajmone Marsan P, Bittante G, Cecchinato A. Associations between differential somatic cell count and milk yield, quality, and technological characteristics in Holstein cows. J Dairy Sci 2021; 104:4822-4836. [PMID: 33612239 DOI: 10.3168/jds.2020-19084] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 11/24/2020] [Indexed: 11/19/2022]
Abstract
The aim of this study was to investigate the associations between differential somatic cell count (DSCC) and milk quality and udder health traits, and for the first time, between DSCC and milk coagulation properties and cheesemaking traits in a population of 1,264 Holstein cows reared in northern Italy. Differential somatic cell count represents the combined proportions of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in the total somatic cell count (SCC), with macrophages (MAC) making up the remaining proportion. The milk traits investigated in this study were milk yield (MY), 8 traits related to milk composition and quality (fat, protein, casein, casein index, lactose, urea, pH, and milk conductivity), 9 milk coagulation traits [3 milk coagulation properties (MCP) and 6 curd firming (CF) traits], 7 cheesemaking traits, 3 cheese yield (CY) traits, and 4 milk nutrient recovery in the curd (REC) traits. A linear mixed model was fitted to explore the associations between SCS combined with DSCC and the aforementioned milk traits. An additional model was run, which included DSCC expressed as the PMN-LYM and MAC counts, obtained by multiplying the percentage of PMN-LYM and MAC by SCC in the milk for each cow in the data set. The unfavorable association between SCS and milk quality and technological traits was confirmed. Increased DSCC was instead associated with a linear increase in MY, casein index, and lactose proportion and a linear decrease in milk fat and milk conductivity. Accordingly, DSCC was favorably associated with all MCP and CF traits (with the exception of the time needed to achieve maximum, CF), particularly with rennet coagulation time, and it always displayed linear relationships. Differential somatic cell count was also positively associated with the recovery of milk nutrients in the curd (protein, fat, and energy), which increased linearly with increasing DSCC. The PMN-LYM count was rarely associated with milk traits, even though the pattern observed confirmed the results obtained when both SCS and DSCC were included in the model. The MAC count, however, showed the opposite pattern: MY, casein index, and lactose percentage decreased and milk conductivity increased with an increasing MAC count. No significant association was found between PMN-LYM count and MCP, CF, CY, and REC traits, whereas MAC count was unfavorably associated with MCP, CF traits, some CY traits, and all REC traits. Our results showed that the combined information derived from SCS and DSCC might be useful to monitor milk quality and cheesemaking-related traits.
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Affiliation(s)
- S Pegolo
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell' Università 16, 35020, Legnaro PD, Italy.
| | - D Giannuzzi
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell' Università 16, 35020, Legnaro PD, Italy
| | - V Bisutti
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell' Università 16, 35020, Legnaro PD, Italy
| | - R Tessari
- Department of Animal Medicine, Productions and Health (MAPS), University of Padua, Viale dell' Università 16, 35020, Legnaro, PD, Italy
| | - M E Gelain
- Department of Comparative Biomedicine and Food Science (BCA), University of Padua, Viale dell' Università 16, 35020, Legnaro PD, Italy
| | - L Gallo
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell' Università 16, 35020, Legnaro PD, Italy
| | - S Schiavon
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell' Università 16, 35020, Legnaro PD, Italy
| | - F Tagliapietra
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell' Università 16, 35020, Legnaro PD, Italy
| | - E Trevisi
- Department of Animal Science, Food and Nutrition (DIANA), Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122, Piacenza, PC, Italy
| | - P Ajmone Marsan
- Department of Animal Science, Food and Nutrition (DIANA), Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122, Piacenza, PC, Italy; Nutrigenomics and Proteomics Research Center (PRONUTRIGEN),Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122, Piacenza, PC, Italy
| | - G Bittante
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell' Università 16, 35020, Legnaro PD, Italy
| | - A Cecchinato
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell' Università 16, 35020, Legnaro PD, Italy
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Saavedra-Jiménez LA, Ramírez-Valverde R, Núñez-Domínguez R, Ruíz-Flores A, García-Muñiz JG. Genetic parameters for nitrogen fractions content in Mexican Brown Swiss cattle milk. Trop Anim Health Prod 2019; 51:2235-2241. [DOI: 10.1007/s11250-019-01926-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 03/28/2019] [Accepted: 05/15/2019] [Indexed: 10/26/2022]
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8
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Barbosa SBP, Araújo ÍIMD, Martins MF, Silva ECD, Jacopini LA, Batista ÂMV, Silva MVBD. Genetic association of variations in the kappa-casein and β-lactoglobulin genes with milk traits in girolando cattle. REVISTA BRASILEIRA DE SAÚDE E PRODUÇÃO ANIMAL 2019. [DOI: 10.1590/s1519-9940200312019] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
SUMMARY In dairy farm animals, one the most important goal of the selection is the improvement of milk yield and composition. Several studies have demonstrated that the candidate genes of the kappa-casein (CSN3) and β - lactoglobulin (β-LG) are associated with milk yield, milk quality and health traits in dairy animals. Therefore the aim of this study was to detect polymorphisms in CSN3 and β-LG genes and its association with milk yield in up to 305 days (305MY) and predicted transmission capacity (PTA) for 305MY in Girolando cattle. Totally, 138 bulls and 729 cows (n=867) were sampled. The genotypes of both genes were obtained by the PCR-RFLP method using HinfI and HaeIII enzymes for CSN3 and β-LG genes, respectively. Statistical results revealed two alleles A and B for both genes. The genotypes and alleles more frequents for CSN3 and β-LG genes were respectively: AA (0.7324) and A (0.8558), and AB (0.4827) and A (0.5017). The x2 test revealed that the two loci were at Hardy-Weinberg equilibrium (p<0.001). The allele substitution effects for the variants were not significant on 305MY and PTA for 305MY (p>0.05). The allele variants of β-LG and CSN3 might be more investigated before include them into future breeding schemes designed for Girolando dairy cattle with objective of improving milk traits as milk yield in up to 305 days (305MY) and predicted transmission capacity (PTA) for 305MY..
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Cipolat-Gotet C, Cecchinato A, Malacarne M, Bittante G, Summer A. Variations in milk protein fractions affect the efficiency of the cheese-making process. J Dairy Sci 2018; 101:8788-8804. [DOI: 10.3168/jds.2018-14503] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2018] [Accepted: 06/25/2018] [Indexed: 11/19/2022]
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10
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Vacca GM, Stocco G, Dettori ML, Summer A, Cipolat-Gotet C, Bittante G, Pazzola M. Cheese yield, cheesemaking efficiency, and daily production of 6 breeds of goats. J Dairy Sci 2018; 101:7817-7832. [DOI: 10.3168/jds.2018-14450] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Accepted: 04/20/2018] [Indexed: 12/12/2022]
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11
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Pazzola M, Stocco G, Paschino P, Dettori ML, Cipolat-Gotet C, Bittante G, Vacca GM. Modeling of coagulation, curd firming, and syneresis of goat milk from 6 breeds. J Dairy Sci 2018; 101:7027-7039. [DOI: 10.3168/jds.2018-14397] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Accepted: 03/24/2018] [Indexed: 02/04/2023]
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12
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Wolanciuk A, Barłowska J, Litwińczuk Z, Florek M. Suitability of the milk of native breeds of cows from low-input farms for cheese production, including rennet curd texture. INT J DAIRY TECHNOL 2016. [DOI: 10.1111/1471-0307.12310] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Anna Wolanciuk
- Department of Commodity Science and Processing of Raw Animal Materials; University of Life Sciences; Akademicka 13 20-950 Lublin Poland
| | - Joanna Barłowska
- Department of Commodity Science and Processing of Raw Animal Materials; University of Life Sciences; Akademicka 13 20-950 Lublin Poland
| | - Zygmunt Litwińczuk
- Department of Breeding and Protection of Genetic Resources of Cattle; University of Life Sciences; Akademicka 13 20-950 Lublin Poland
| | - Mariusz Florek
- Department of Commodity Science and Processing of Raw Animal Materials; University of Life Sciences; Akademicka 13 20-950 Lublin Poland
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Cecchinato A, Bittante G. Genetic and environmental relationships of different measures of individual cheese yield and curd nutrients recovery with coagulation properties of bovine milk. J Dairy Sci 2016; 99:1975-1989. [DOI: 10.3168/jds.2015-9629] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2015] [Accepted: 11/11/2015] [Indexed: 11/19/2022]
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Bruna ADG, Priscila ADS, Liomar DSA, Cristiane IG, Rodrigo BSN, Edmar SN, Marco APDS. Effect of the somatic cell count on physicochemical components of milk from crossbred cows. ACTA ACUST UNITED AC 2015. [DOI: 10.5897/ajb2015.14540] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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Cipolat-Gotet C, Cecchinato A, De Marchi M, Bittante G. Factors affecting variation of different measures of cheese yield and milk nutrient recovery from an individual model cheese-manufacturing process. J Dairy Sci 2013; 96:7952-65. [DOI: 10.3168/jds.2012-6516] [Citation(s) in RCA: 71] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2012] [Accepted: 07/29/2013] [Indexed: 11/19/2022]
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16
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Bittante G, Cipolat-Gotet C, Cecchinato A. Genetic parameters of different measures of cheese yield and milk nutrient recovery from an individual model cheese-manufacturing process. J Dairy Sci 2013; 96:7966-79. [DOI: 10.3168/jds.2012-6517] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2012] [Accepted: 07/29/2013] [Indexed: 11/19/2022]
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17
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Navas-Carretero S, Abete I, Cuervo M, Zulet MÁ, Martínez JA. A regular curd consumption improves gastrointestinal status assessed by a randomized controlled nutritional intervention. Int J Food Sci Nutr 2013; 64:674-81. [DOI: 10.3109/09637486.2013.775222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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Real-time evaluation of milk quality as reflected by clotting parameters of individual cow's milk during the milking session, between day-to-day and during lactation. Animal 2013; 7:1551-8. [PMID: 23537499 DOI: 10.1017/s1751731113000542] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Real-time analysis of milk coagulation properties as performed by the AfiLab™ milk spectrometer introduces new opportunities for the dairy industry. The study evaluated the performance of the AfiLab™ in a milking parlor of a commercial farm to provide real-time analysis of milk-clotting parameters -Afi-CF for cheese manufacture and determine its repeatability in time for individual cows. The AfiLab™ in a parlor, equipped with two parallel milk lines, enables to divert the milk on-line into two bulk milk tanks (A and B). Three commercial dairy herds of 220 to 320 Israeli Holstein cows producing ∼11 500 l during 305 days were selected for the study. The Afi-CF repeatability during time was found significant (P < 0.001) for cows. The statistic model succeeded in explaining 83.5% of the variance between Afi-CF and cows, and no significant variance was found between the mean weekly repeated recordings. Days in milk and log somatic cell count (SCC) had no significant effect. Fat, protein and lactose significantly affected Afi-CF and the empirical van Slyke equation. Real-time simulations were performed for different cutoff levels of coagulation properties where the milk of high Afi-CF cutoff value was channeled to tank A and the lower into tank B. The simulations showed that milk coagulation properties of an individual cow are not uniform, as most cows contributed milk to both tanks. Proportions of the individual cow's milk in each tank depended on the selected Afi-CF cutoff. The assessment of the major causative factors of a cow producing low-quality milk for cheese production was evaluated for the group that produced the low 10% quality milk. The largest number of cows in those groups at the three farms was found to be cows with post-intramammary infection with Escherichia coli and subclinical infections with streptococci or coagulase-negative staphylococci (∼30%), although the SCC of these cows was not significantly different. Early time in lactation together with high milk yield >50 l/day, and late in lactation together with low milk yield<15 l/day and estrous (0 to 5 days) were also important influencing factors for low-quality milk. However, ∼50% of the tested variables did not explain any of the factors responsible for the cow producing milk in the low - 10% Afi-CF.
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Real-time visual/near-infrared analysis of milk-clotting parameters for industrial applications. Animal 2012; 6:1170-7. [DOI: 10.1017/s175173111100245x] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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Emmons D, Modler H. Invited review: A commentary on predictive cheese yield formulas. J Dairy Sci 2010; 93:5517-37. [DOI: 10.3168/jds.2010-3262] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2010] [Accepted: 07/16/2010] [Indexed: 11/19/2022]
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NESPOLO CASSIAR, CORREA ANAPF, RITTER ANAC, BRANDELLI ADRIANO. Comparison of Fascal cheese produced with natural, commercial or autochthonous cultures. INT J DAIRY TECHNOL 2010. [DOI: 10.1111/j.1471-0307.2010.00579.x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Use of milk protein concentrate to standardize milk composition in Italian citric Mozzarella cheese making. Lebensm Wiss Technol 2010. [DOI: 10.1016/j.lwt.2009.08.007] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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23
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Wedholm A, Møller H, Stensballe A, Lindmark-Månsson H, Karlsson A, Andersson R, Andrén A, Larsen L. Effect of Minor Milk Proteins in Chymosin Separated Whey and Casein Fractions on Cheese Yield as Determined by Proteomics and Multivariate Data Analysis. J Dairy Sci 2008; 91:3787-97. [DOI: 10.3168/jds.2008-1022] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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24
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Aquino A, Lima Y, Botaro B, Alberto C, Peixoto K, Santos M. Effects of dietary urea levels on milk protein fractions of Holstein cows. Anim Feed Sci Technol 2008. [DOI: 10.1016/j.anifeedsci.2007.03.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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SULTANEH ALI, ROHM HARALD. Using near infrared spectroscopy for the determination of total solids and protein content in cheese curd. INT J DAIRY TECHNOL 2007. [DOI: 10.1111/j.1471-0307.2007.00347.x] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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