Detection of milk powder in liquid whole milk using hydrolyzed peptide and intact protein mass spectral fingerprints coupled with data fusion technologies. Issue 3 (3rd February 2020)

• Record Type: Journal Article
• Authors: Du, Lijuan; Lu, Weiying; Zhang, Yaqiong; Gao, Boyan; Yu, Liangli
• Is Part Of: Food science & nutrition. Volume 8:Issue 3(2020)
• Page Start: 1471
• Page End: 1479
• Publication Date: 2020-02-03
• Subjects: data fusion -- intact protein fingerprints -- milk adulteration -- peptide fingerprints -- principle component analysis; Food industry and trade -- Periodicals; Food -- Periodicals; Nutrition -- Periodicals; 664
• DOI: 10.1002/fsn3.1430
• Languages: English
• ISSNs: 2048-7177

Abstract

Abstract: Detection of the presence of milk powder in liquid whole milk is challenging due to their similar chemical components. In this study, a sensitive and robust approach has been developed and tested for potential utilization in discriminating adulterated milk from liquid whole milk by analyzing the intact protein and hydrolyzed peptide using ultra‐performance liquid chromatography with quadrupole time‐of‐flight mass spectrometer (UPLC‐QTOF‐MS) fingerprints combined with data fusion. Two different datasets from intact protein and peptide fingerprints were fused to improve the discriminating ability of principle component analysis (PCA). Furthermore, the midlevel data fusion coupled with PCA could completely distinguish liquid whole milk from the milk. The limit of detection of milk powder in liquid whole milk was 0.5% (based on the total protein equivalence). These results suggested that fused data from intact protein and peptide fingerprints created greater synergic effect in detecting milk quality, and the combination of data fusion and PCA analysis could be used for the detection of adulterated milk. Abstract : A sensitive and robust approach has been developed and tested for potential utilization in discriminating adulterated milk from liquid whole milk by analyzing the intact protein and hydrolyzed peptide using UPLC‐QTOF‐MS fingerprints combined with data fusion. The limit of detection of milk powder in liquid whole milk was 0.5% (based on the total protein equivalence). Results suggested that fused data from intact protein and peptide fingerprints created greater synergic effect in detecting milk quality, and the combination of data fusion and principle component analysis (PCA) analysis could be used for the detection of adulterated milk.