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Mezzetti M, Passamonti MM, Dall’Asta M, Bertoni G, Trevisi E, Ajmone Marsan P. Emerging Parameters Justifying a Revised Quality Concept for Cow Milk. Foods 2024; 13:1650. [PMID: 38890886 PMCID: PMC11171858 DOI: 10.3390/foods13111650] [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: 04/22/2024] [Revised: 05/22/2024] [Accepted: 05/22/2024] [Indexed: 06/20/2024] Open
Abstract
Milk has become a staple food product globally. Traditionally, milk quality assessment has been primarily focused on hygiene and composition to ensure its safety for consumption and processing. However, in recent years, the concept of milk quality has expanded to encompass a broader range of factors. Consumers now also consider animal welfare, environmental impact, and the presence of additional beneficial components in milk when assessing its quality. This shifting consumer demand has led to increased attention on the overall production and sourcing practices of milk. Reflecting on this trend, this review critically explores such novel quality parameters, offering insights into how such practices meet the modern consumer's holistic expectations. The multifaceted aspects of milk quality are examined, revealing the intertwined relationship between milk safety, compositional integrity, and the additional health benefits provided by milk's bioactive properties. By embracing sustainable farming practices, dairy farmers and processors are encouraged not only to fulfill but to anticipate consumer standards for premium milk quality. This comprehensive approach to milk quality underscores the necessity of adapting dairy production to address the evolving nutritional landscape and consumption patterns.
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Affiliation(s)
- Matteo Mezzetti
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti (DIANA), Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy; (M.M.); (M.M.P.); (M.D.); (G.B.); (E.T.)
| | - Matilde Maria Passamonti
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti (DIANA), Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy; (M.M.); (M.M.P.); (M.D.); (G.B.); (E.T.)
| | - Margherita Dall’Asta
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti (DIANA), Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy; (M.M.); (M.M.P.); (M.D.); (G.B.); (E.T.)
| | - Giuseppe Bertoni
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti (DIANA), Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy; (M.M.); (M.M.P.); (M.D.); (G.B.); (E.T.)
| | - Erminio Trevisi
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti (DIANA), Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy; (M.M.); (M.M.P.); (M.D.); (G.B.); (E.T.)
- Romeo and Enrica Invernizzi Research Center for Sustainable Dairy Production of the Università Cattolica del Sacro Cuore (CREI), 29122 Piacenza, Italy
| | - Paolo Ajmone Marsan
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti (DIANA), Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy; (M.M.); (M.M.P.); (M.D.); (G.B.); (E.T.)
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Gruber S, Rienesl L, Köck A, Egger-Danner C, Sölkner J. Importance of Mid-Infrared Spectra Regions for the Prediction of Mastitis and Ketosis in Dairy Cows. Animals (Basel) 2023; 13:ani13071193. [PMID: 37048449 PMCID: PMC10093284 DOI: 10.3390/ani13071193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 03/22/2023] [Accepted: 03/27/2023] [Indexed: 03/31/2023] Open
Abstract
Mid-infrared (MIR) spectroscopy is routinely applied to determine major milk components, such as fat and protein. Moreover, it is used to predict fine milk composition and various traits pertinent to animal health. MIR spectra indicate an absorbance value of infrared light at 1060 specific wavenumbers from 926 to 5010 cm−1. According to research, certain parts of the spectrum do not contain sufficient information on traits of dairy cows. Hence, the objective of the present study was to identify specific regions of the MIR spectra of particular importance for the prediction of mastitis and ketosis, performing variable selection analysis. Partial least squares discriminant analysis (PLS-DA) along with three other statistical methods, support vector machine (SVM), least absolute shrinkage and selection operator (LASSO), and random forest (RF), were compared. Data originated from the Austrian milk recording and associated health monitoring system (GMON). Test-day data and corresponding MIR spectra were linked to respective clinical mastitis and ketosis diagnoses. Certain wavenumbers were identified as particularly relevant for the prediction models of clinical mastitis (23) and ketosis (61). Wavenumbers varied across four distinct statistical methods as well as concerning different traits. The results indicate that variable selection analysis could potentially be beneficial in the process of modeling.
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Affiliation(s)
- Stefan Gruber
- Institute of Livestock Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU), Gregor-Mendel-Straße 33, 1180 Vienna, Austria
| | - Lisa Rienesl
- Institute of Livestock Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU), Gregor-Mendel-Straße 33, 1180 Vienna, Austria
- Correspondence: ; Tel.: +43-1-476-549-3201
| | - Astrid Köck
- ZuchtData EDV-Dienstleistungen GmbH, Dresdner Straße 89/19, 1200 Vienna, Austria
| | - Christa Egger-Danner
- ZuchtData EDV-Dienstleistungen GmbH, Dresdner Straße 89/19, 1200 Vienna, Austria
| | - Johann Sölkner
- Institute of Livestock Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU), Gregor-Mendel-Straße 33, 1180 Vienna, Austria
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