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Ezenarro Garate, JokinAuthor

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March 14, 2024
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Yoghurt standardization using real-time NIR prediction of milk fat and protein content

Publicated to:Journal Of Food Composition And Analysis. 128 106015- - 2024-02-02 128(), DOI: 10.1016/j.jfca.2024.106015

Authors: Castro-Reigía, D.; Ezenarro, J.; Azkune, M.; Ayesta, I.; Ostra, M.; Amigo, J.M.; García, I.; Ortiz, M.C.

Affiliations

Universitat Rovira i Virgili. Universitat Rovira i Virgili - Author

Abstract

A system based on near-infrared (NIR) spectroscopy has been developed for the in-line control of the composition of the milk used as raw material for yoghurt production to control the content of protein and fat in the final product, and, therefore, to reduce variability in the production process. Firstly, after selecting the appropriate method for preprocessing NIR data, Partial Least Squares Regression models were built to predict fat and protein content in milk, obtaining good performances. The variance explained of y-block in prediction (R2P) was 0.99 and 0.80, while the Root Mean Square Error of Prediction (RMSEP), was 0.26 and 0.16 for fat and protein, respectively. With those models, it was possible to determine the fat and protein contents in milk in real time, and therefore, the quantity of milk powder and cream added in the manufacturing process of yoghurt could be readjusted. The presented strategy allows the improvement of the homogeneity of the final product, reducing the variability of the nutritional values in more than 70% with respect to the traditional recipe, and also meet the target values according to yoghurt producers for fat and protein content, that is, 10% of fat and 5% of protein.

Keywords

FatIn-lineNear-infrared (nir)Partial least squares regression (plsr)Proof of conceptProteinYoghurt

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Journal Of Food Composition And Analysis due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Food Science.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-08-02:

  • Google Scholar: 3
  • Scopus: 5

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-08-02:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 30 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is: