Discriminating milk storage time with mid-infrared spectra combined with machine learning

[en] Classification models for rapid discrimination of milk storage time were developed. Buffalo raw milk (BuR) and bovine raw (BoR), pasteurised (BoP) and ultra-high temperature sterilised (BUHT) milk were analysed by mid-infrared (MIR) spectroscopy at different storage times. A total of 175 (44), 96 (24), 252 (64) and 383 (97) samples were used in the developed (validated) models of BuR, BoR, BoP and BUHT milk, respectively. Seven, two, five, and three spectral regions were selected for BuR, BoR, BoP and BUHT, respectively, to develop their models, which reflect changes in milk protein, fat, lactose and urea nitrogen. Accuracies of the optimised models for BuR, BoR, BoP and BUHT milk were 0.95, 1.00, 0.89, and 0.93, respectively, in the validation dataset. All optimal models were obtained by machine learning methods. This preliminarily study shows that MIR combined with machine learning can rapidly identify the storage time of these four types of milk.

Precision for document type :

Review article

Disciplines :

Zoology

Author, co-author :

Su, J.

Chen, Yansen ; Université de Liège - ULiège > TERRA Research Centre

Nan, L.

Wang, H.

Luo, X.

Fan, Y.

Zhang, Y.

Du, C.

Gengler, Nicolas ; Université de Liège - ULiège > TERRA Research Centre > Animal Sciences (AS)

Zhang, S.

Language :

English

Title :

Discriminating milk storage time with mid-infrared spectra combined with machine learning

Publication date :

November 2023

Journal title :

International Dairy Journal

ISSN :

0958-6946

Publisher :

Elsevier BV

Pages :

105848

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://api.elsevier.com/content/article/PII:S0958694623002674?httpAccept=text/xml

Available on ORBi :

since 01 December 2023

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