Infant gender‐based differentiation in concentration of milk fats using near infrared Raman spectroscopy

Ullah, Rahat; Khan, Saranjam; Khan, Asifullah; Saleem, Muhammad; Ali, Hina; Bilal, Muhammad; Ahmed, Mushtaq

doi:10.1002/jrs.5047

Cited by 16 publications

(7 citation statements)

References 35 publications

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“…(b), it is very clear that Raman peaks at 1150 and 1510 cm −1 are present only in cow milk but absent in buffalo milk. Raman peaks at these positions correspond to carotenoids more specifically to the β‐carotene . β‐carotene is a red–orange pigment and is mostly found in plants.…”

Section: Resultsmentioning

confidence: 99%

Raman‐spectroscopy‐based differentiation between cow and buffalo milk

Ullah

Khan

Ali

et al. 2017

J Raman Spectroscopy

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In this study, Raman spectroscopy together with chemometric techniques has been demonstrated to differentiate between cow and buffalo milk. The Raman spectra of milk samples of bovine contain peaks which show significant variation in intensity as well as in Raman shift positions. The outcome of results indicates that Raman spectroscopy successfully differentiates between cow and buffalo milk based on the presence and absence of β-carotene, respectively. It also shows that buffalo milk contains comparatively high fat (unsaturated/saturated) content. Principal component analysis-based algorithm further highlighted the difference and shows clear separation between the two data sets on the basis of features obtained from their Raman spectra. Consequently, β-carotene could be a good biomarker for differentiating cow and buffalo milk. Present study will help to establish the use spectroscopic technique for the detection of adulterants in milk which is of significant concern worldwide.

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Section: Resultsmentioning

confidence: 99%

Raman‐spectroscopy‐based differentiation between cow and buffalo milk

Ullah

Khan

Ali

et al. 2017

J Raman Spectroscopy

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“…In contrast, in the current study milk samples are collected from mothers feeding infants with age ranges from 20 days to 15 months. So there is comparatively more spread in the data due to extended ages groups [20]. For better separation, the number of principal components have been gradually increasd, an improved classification efficieny has been observed by increasing the number of PC's to 5 (considering first five PC's).…”

Section: Dimensionality Reduction and Support Vector Machine (Svm)mentioning

confidence: 99%

Raman spectroscopy combined with a support vector machine for differentiating between feeding male and female infants mother’s milk

Ullah

Khan

Javaid

et al. 2018

Biomed. Opt. Express

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This study presents differentiation in milk samples of mother's feeding male and female infants using Raman spectroscopy combined with a support vector machine (SVM). Major differences have been observed in the Raman spectra of both types of milk based on their chemical compositions. Overall, it has been found that milk samples of mother's having a female infant are richer in fatty acids, phospholipids, and tryptophan. In contrast, milk samples of mother's having a male infant contain more carotenoids and saccharides. Principal component analysis and SVM further highlighted the differences between the two groups on the basis of differentiating features obtained from their Raman spectra. The SVM model with two different kernels, i.e. polynomial kernel function (order-2) and Gaussian radial basis function (RBF sigma-2), are used for gender based milk differentiations. The performance of the proposed model in terms of accuracy, precision, sensitivity, and specificity using the polynomial kernel function of order-2 have been found to be 86%, 88%, 85% and 88%, respectively.

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“…It shows that a buffalo with a female infant produces comparatively high fat milk. The spectral difference has been further highlighted by applying a PCA‐based algorithm to the Raman spectra of the milk samples . van Dalen et al applied Raman hyperspectral imaging to the analysis of fat spreads.…”

Section: Pharmaceutical Food and Forensic Applicationsmentioning

confidence: 99%

Recent advances in linear and nonlinear Raman spectroscopy. Part XII

Nafie

2018

J Raman Spectroscopy

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This annual review is an overview of advances in the field of Raman spectroscopy as found in papers published in the previous calendar year in the Journal of Raman Spectroscopy (JRS), as well as in trends over the past decade across journals that have published papers important to the field of Raman spectroscopy. This information is gleaned from statistical data on article counts obtained from the Clarivate Analytic's Web of Science Core Collection by year and by subfield of Raman spectroscopy. Additional information is gleaned from presentations at the XXVI International Conference on Raman Spectroscopy (ICORS 2018) in Jeju Island, Korea in August 2018, and contributions on Raman scattering at SCIX 2018, organized by the Federation of Analytical Chemistry and Spectroscopy Societies (FACSS) in Atlanta, Georgia, USA in October 2018. Coverage is also provided for topics from the European Conference on Nonlinear Optical Spetroscopy (ECONOS 2018) held in April in Milan, Italy and GeoRaman 2018 in Catania, Italy in June. Finally, papers published in JRS in 2017 are highlighted and arranged by topics at the frontier of Raman spectroscopy. On the basis of this survey information, it is clear that Raman spectroscopy continues as in recent years as a rapidly expanding field of research across a wide range of novel disciplines and applications that provide sensitive photonic information of matter at the molecular level.

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Infant gender‐based differentiation in concentration of milk fats using near infrared Raman spectroscopy

Cited by 16 publications

References 35 publications

Raman‐spectroscopy‐based differentiation between cow and buffalo milk

Raman‐spectroscopy‐based differentiation between cow and buffalo milk

Raman spectroscopy combined with a support vector machine for differentiating between feeding male and female infants mother’s milk

Recent advances in linear and nonlinear Raman spectroscopy. Part XII

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