Monitoring the composition, authenticity and quality dynamics of commercially available Nigerian fat-filled milk powders under inclement conditions using NIRS, chemometrics, packaging and microbiological parameters

Ejeahalaka, Kizito Kene; McLaughlin, Peter; On, Stephen L.W.

doi:10.1016/j.foodchem.2020.127844

Cited by 7 publications

(2 citation statements)

References 20 publications

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“…It can be inferred that there was a difference in lactose content between milk from Neimenggu and Ningxia, and milk from Heilongjiang, Hebei, and Henan. The fluctuation at 10,417

is related to the O-H bond content in water [ 52 ]. It can be inferred that the content of water in milk from Ningxia and Henan is similar, while the content of water in milk from the other three origins is more different.…”

Section: Resultsmentioning

confidence: 99%

Several Feature Extraction Methods Combined with Near-Infrared Spectroscopy for Identifying the Geographical Origins of Milk

Wu,

Wang,

et al. 2024

Foods

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Milk is a kind of dairy product with high nutritive value. Tracing the origin of milk can uphold the interests of consumers as well as the stability of the dairy market. In this study, a fuzzy direct linear discriminant analysis (FDLDA) is proposed to extract the near-infrared spectral information of milk by combining fuzzy set theory with direct linear discriminant analysis (DLDA). First, spectral data of the milk samples were collected by a portable NIR spectrometer. Then, the data were preprocessed by Savitzky–Golay (SG) and standard normal variables (SNV) to reduce noise, and the dimensionality of the spectral data was decreased by principal component analysis (PCA). Furthermore, linear discriminant analysis (LDA), DLDA, and FDLDA were employed to transform the spectral data into feature space. Finally, the k-nearest neighbor (KNN) classifier, extreme learning machine (ELM) and naïve Bayes classifier were used for classification. The results of the study showed that the classification accuracy of FDLDA was higher than DLDA when the KNN classifier was used. The highest recognition accuracy of FDLDA, DLDA, and LDA could reach 97.33%, 94.67%, and 94.67%. The classification accuracy of FDLDA was also higher than DLDA when using ELM and naïve Bayes classifiers, but the highest recognition accuracy was 88.24% and 92.00%, respectively. Therefore, the KNN classifier outperformed the ELM and naïve Bayes classifiers. This study demonstrated that combining FDLDA, DLDA, and LDA with NIR spectroscopy as an effective method for determining the origin of milk.

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“…It can be inferred that there was a difference in lactose content between milk from Neimenggu and Ningxia, and milk from Heilongjiang, Hebei, and Henan. The fluctuation at 10,417

Section: Resultsmentioning

confidence: 99%

Several Feature Extraction Methods Combined with Near-Infrared Spectroscopy for Identifying the Geographical Origins of Milk

Wu,

Wang,

et al. 2024

Foods

View full text Add to dashboard Cite

show abstract

“…Different analytical techniques, such as near-infrared spectroscopy and real-time polymerase chain reaction (PCR), have been used to recognize and identify the origins of different mammalian milks. − With the development of lipidomics, milk lipids are often used as an indicator for the detection of dairy food fraudulence, considering their abundance in milk. Nuclear magnetic resonance spectroscopy, gas chromatography, liquid chromatography-mass spectrometry, and matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry are the frequently used lipidomic methods. − Besides, ambient ionization mass spectrometry, especially rapid evaporative ionization mass spectrometry (REIMS), circumvents the limitations of chromatographic separation methods.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Profiling and Distinction of Lipids from Different Mammalian Milks Using Rapid Evaporative Ionization Mass Spectrometry Combined with Chemometric Analysis

Cui

et al. 2022

J. Agric. Food Chem.

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The price of mammalian milk from different animal species varies greatly due to differences in their yield and nutritional value. Therefore, the authenticity of dairy products has become a hotspot issue in the market due to the replacement or partial admixture of high-cost milk with its low-cost analog. Herein, four common commercial varieties of milk, including goat milk, buffalo milk, Holstein cow milk, and Jersey cow milk, were successfully profiled and differentiated from each other by rapid evaporative ionization mass spectrometry (REIMS) combined with chemometric analysis. This method was developed as a real-time lipid fingerprinting technique. Moreover, the established chemometric algorithms based on multivariate statistical methods mainly involved principal component analysis, orthogonal partial least squares-discriminant analysis, and linear discriminant analysis as the screening and verifying tools to provide insights into the distinctive molecules constituting the four varieties of milk. The ions with

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Flow of spore-forming bacteria between suppliers of dairy powders and users in some developing countries: challenges and perspectives

Malek

2022

J Food Sci Technol

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Monitoring the composition, authenticity and quality dynamics of commercially available Nigerian fat-filled milk powders under inclement conditions using NIRS, chemometrics, packaging and microbiological parameters

Cited by 7 publications

References 20 publications

Several Feature Extraction Methods Combined with Near-Infrared Spectroscopy for Identifying the Geographical Origins of Milk

Several Feature Extraction Methods Combined with Near-Infrared Spectroscopy for Identifying the Geographical Origins of Milk

Real-Time Profiling and Distinction of Lipids from Different Mammalian Milks Using Rapid Evaporative Ionization Mass Spectrometry Combined with Chemometric Analysis

Flow of spore-forming bacteria between suppliers of dairy powders and users in some developing countries: challenges and perspectives

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