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Niero G, Thomas SA, Mouratidou K, Visentin G, De Marchi M, Penasa M, Cassandro M. Lactoferrin concentration in bovine milk: validation of radial immunodiffusion technique, sources of variation, and association to udder health status. ITALIAN JOURNAL OF ANIMAL SCIENCE 2023. [DOI: 10.1080/1828051x.2023.2180440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
Affiliation(s)
- Giovanni Niero
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, University of Padua, Legnaro, Italy
| | - Steffi Anna Thomas
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, University of Padua, Legnaro, Italy
| | - Kassiani Mouratidou
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, University of Padua, Legnaro, Italy
| | - Giulio Visentin
- Dipartimento di Scienze Mediche Veterinarie, Alma Mater Studiorum, Università di Bologna, Ozzano dell’Emilia, Italy
| | - Massimo De Marchi
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, University of Padua, Legnaro, Italy
| | - Mauro Penasa
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, University of Padua, Legnaro, Italy
| | - Martino Cassandro
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, University of Padua, Legnaro, Italy
- Associazione Nazionale Allevatori della Razza Frisona, Bruna e Jersey Italiana, Cremona, Italy
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Delhez P, Colinet F, Vanderick S, Bertozzi C, Gengler N, Soyeurt H. Predicting milk mid-infrared spectra from first-parity Holstein cows using a test-day mixed model with the perspective of herd management. J Dairy Sci 2020; 103:6258-6270. [PMID: 32418684 DOI: 10.3168/jds.2019-17717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 02/27/2020] [Indexed: 11/19/2022]
Abstract
The use of test-day models to model milk mid-infrared (MIR) spectra for genetic purposes has already been explored; however, little attention has been given to their use to predict milk MIR spectra for management purposes. The aim of this paper was to study the ability of a test-day mixed model to predict milk MIR spectra for management purposes. A data set containing 467,496 test-day observations from 53,781 Holstein dairy cows in first lactation was used for model building. Principal component analysis was implemented on the selected 311 MIR spectral wavenumbers to reduce the number of traits for modeling; 12 principal components (PC) were retained, explaining approximately 96% of the total spectral variation. Each of the retained PC was modeled using a single trait test-day mixed model. The model solutions were used to compute the predicted scores of each PC, followed by a back-transformation to obtain the 311 predicted MIR spectral wavenumbers. Four new data sets, containing altogether 122,032 records, were used to test the ability of the model to predict milk MIR spectra in 4 distinct scenarios with different levels of information about the cows. The average correlation between observed and predicted values of each spectral wavenumber was 0.85 for the modeling data set and ranged from 0.36 to 0.62 for the scenarios. Correlations between milk fat, protein, and lactose contents predicted from the observed spectra and from the modeled spectra ranged from 0.83 to 0.89 for the modeling set and from 0.32 to 0.73 for the scenarios. Our results demonstrated a moderate but promising ability to predict milk MIR spectra using a test-day mixed model. Current and future MIR traits prediction equations could be applied on the modeled spectra to predict all MIR traits in different situations instead of developing one test-day model separately for each trait. Modeling MIR spectra would benefit farmers for cow and herd management, for instance through prediction of future records or comparison between observed and expected wavenumbers or MIR traits for the detection of health and management problems. Potential resulting tools could be incorporated into milk recording systems.
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Affiliation(s)
- P Delhez
- National Fund for Scientific Research (FRS-FNRS), Brussels 1000, Belgium; TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux 5030, Belgium.
| | - F Colinet
- TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux 5030, Belgium
| | - S Vanderick
- TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux 5030, Belgium
| | - C Bertozzi
- Walloon Breeding Association (awé Groupe), Ciney 5590, Belgium
| | - N Gengler
- TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux 5030, Belgium
| | - H Soyeurt
- TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux 5030, Belgium
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Grelet C, Pierna JAF, Dardenne P, Soyeurt H, Vanlierde A, Colinet F, Bastin C, Gengler N, Baeten V, Dehareng F. Standardization of milk mid-infrared spectrometers for the transfer and use of multiple models. J Dairy Sci 2017; 100:7910-7921. [PMID: 28755945 DOI: 10.3168/jds.2017-12720] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Accepted: 06/05/2017] [Indexed: 11/19/2022]
Abstract
An increasing number of models are being developed to provide information from milk Fourier transform mid-infrared (FT-MIR) spectra on fine milk composition, technological properties of milk, or even cows' physiological status. In this context, and to take advantage of these existing models, the purpose of this work was to evaluate whether a spectral standardization method can enable the use of multiple equations within a network of different FT-MIR spectrometers. The piecewise direct standardization method was used, matching "slave" instruments to a common reference, the "master." The effect of standardization on network reproducibility was assessed on 66 instruments from 3 different brands by comparing the spectral variability of the slaves and the master with and without standardization. With standardization, the global Mahalanobis distance from the slave spectra to the master spectra was reduced on average from 2,655.9 to 14.3, representing a significant reduction of noninformative spectral variability. The transfer of models from instrument to instrument was tested using 3 FT-MIR models predicting (1) the quantity of daily methane emitted by dairy cows, (2) the concentration of polyunsaturated fatty acids in milk, and (3) the fresh cheese yield. The differences, in terms of root mean squared error, between master predictions and slave predictions were reduced after standardization on average from 103 to 17 g/d, from 0.0315 to 0.0045 g/100 mL of milk, and from 2.55 to 0.49 g of curd/100 g of milk, respectively. For all the models, standard deviations of predictions among all the instruments were also reduced by 5.11 times for methane, 5.01 times for polyunsaturated fatty acids, and 7.05 times for fresh cheese yield, showing an improvement of prediction reproducibility within the network. Regarding the results obtained, spectral standardization allows the transfer and use of multiple models on all instruments as well as the improvement of spectral and prediction reproducibility within the network. The method makes the models universal, thereby offering opportunities for data exchange and the creation and use of common robust models at an international level to provide more information to the dairy sector from direct analysis of milk.
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Affiliation(s)
- C Grelet
- Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium
| | - J A Fernández Pierna
- Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium
| | - P Dardenne
- Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium
| | - H Soyeurt
- Agriculture, Bio-Engineering, and Chemistry Department, University of Liège, Gembloux Agro-Bio Tech, 5030 Gembloux, Belgium
| | - A Vanlierde
- Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium
| | - F Colinet
- Agriculture, Bio-Engineering, and Chemistry Department, University of Liège, Gembloux Agro-Bio Tech, 5030 Gembloux, Belgium
| | - C Bastin
- Walloon Breeding Association, B-5590 Ciney, Belgium
| | - N Gengler
- Agriculture, Bio-Engineering, and Chemistry Department, University of Liège, Gembloux Agro-Bio Tech, 5030 Gembloux, Belgium
| | - V Baeten
- Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium
| | - F Dehareng
- Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium.
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Bonfatti V, Vicario D, Lugo A, Carnier P. Genetic parameters of measures and population-wide infrared predictions of 92 traits describing the fine composition and technological properties of milk in Italian Simmental cattle. J Dairy Sci 2017; 100:5526-5540. [DOI: 10.3168/jds.2016-11667] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2016] [Accepted: 03/15/2017] [Indexed: 11/19/2022]
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Pomastowski P, Sprynskyy M, Žuvela P, Rafińska K, Milanowski M, Liu JJ, Yi M, Buszewski B. Silver-Lactoferrin Nanocomplexes as a Potent Antimicrobial Agent. J Am Chem Soc 2016; 138:7899-909. [DOI: 10.1021/jacs.6b02699] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Paweł Pomastowski
- Department
of Environmental Chemistry and Bioanalytics, Faculty of Chemistry,
Interdisciplinary Centre for Modern Technologies, Nicolaus Copernicus University, 87-100 Toruń, Poland
| | - Myroslav Sprynskyy
- Department
of Environmental Chemistry and Bioanalytics, Faculty of Chemistry,
Interdisciplinary Centre for Modern Technologies, Nicolaus Copernicus University, 87-100 Toruń, Poland
| | - Petar Žuvela
- Department
of Chemical Engineering, Pukyong National University, 365 Sinseon-ro,
Nam-gu, 608-739 Busan, Korea
| | - Katarzyna Rafińska
- Department
of Environmental Chemistry and Bioanalytics, Faculty of Chemistry,
Interdisciplinary Centre for Modern Technologies, Nicolaus Copernicus University, 87-100 Toruń, Poland
| | - Maciej Milanowski
- Department
of Environmental Chemistry and Bioanalytics, Faculty of Chemistry,
Interdisciplinary Centre for Modern Technologies, Nicolaus Copernicus University, 87-100 Toruń, Poland
| | - J. Jay Liu
- Department
of Chemical Engineering, Pukyong National University, 365 Sinseon-ro,
Nam-gu, 608-739 Busan, Korea
| | - Myunggi Yi
- Department
of Biomedical Engineering, Pukyong National University, 45 Yongso-ro,
Nam-gu, 608-737 Busan, Korea
| | - Bogusław Buszewski
- Department
of Environmental Chemistry and Bioanalytics, Faculty of Chemistry,
Interdisciplinary Centre for Modern Technologies, Nicolaus Copernicus University, 87-100 Toruń, Poland
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