ArticleFood chemistry: X2023
Rapid identification of adulteration in raw bovine milk with soymilk by electronic nose and headspace-gas chromatography ion-mobility spectrometry.
Article in Food chemistry: X, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Sulfur Supplementation Potentiates the Formation of Meat Aroma Compounds in Thermally Treated Chicken Carcass Hydrolysate.Journal of food science · 2025Article
- Rapid Detection of Antibiotic Mycelial Dregs Adulteration in Single-Cell Protein Feed by HS-GC-IMS and Chemometrics.Foods (Basel, Switzerland) · 2025Article
- Volatile and non-volatile compound analysis of ginkgo chicken soup during cooking using a combi oven.Food chemistry: X · 2025Article
- Analysis of flavor formation and metabolite changes during production of Double-Layer Steamed Milk Custard made from buffalo milk.PloS one · 2025Article
- Changes in the Physical Properties and Volatile Odor Characteristics of Shiitake Mushrooms (Foods (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
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Abstract
The adulteration of soymilk (SM) into raw bovine milk (RM) to gain profit without declaration could cause a health risk. In this study, electronic nose (E-nose) and headspace-gas chromatography ion-mobility spectrometry (HS-GC-IMS) were applied to establish a rapid and effective method to identify adulteration in RM with SM. The obtained data from HS-GC-IMS and E-nose can distinguish the adulterated samples with SM by principal component analysis. Furthermore, a quantitative model of partial least squares was established. The detection limits of E-nose and HS-GC-IMS quantitative models were 1.53% and 1.43%, the root mean square errors of prediction were 0.7390 and 0.5621, the determination coefficients of prediction were 0.9940 and 0.9958, and the relative percentage difference were 10.02 and 13.27, respectively, indicating quantitative regression and good prediction performances of SM adulteration levels in RM were achieved. This research can provide scientific information on the rapid, non-destructive and effective adulteration detection for RM.
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