Detection of Adulterants and Contaminants in Liquid Foods—A Review

Jha, Shyam Narayan; Jaiswal, Pranita; Grewal, Manpreet Kaur; Gupta, Mansha; Bhardwaj, Rishi

doi:10.1080/10408398.2013.798257

Cited by 66 publications

(36 citation statements)

References 224 publications

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“…Adulteration of milk by addition of water can easily be detected in the field using a lactometer [18]. Other substances have been reported as milk adulterants, such as: chlorine, antibiotics, non-milk proteins, low value milk, milk powder, colour, preservatives, urea, liquid whey and water [17,19,20]. In north eastern Brazil, 41.2% of goat milk presented to the market was found to contain bovine milk [21].…”

Section: Discussionmentioning

confidence: 99%

Antimicrobial residues and compositional quality of informally marketed raw cow milk, Lamu West Sub-County, Kenya, 2015

et al. 2017

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Introductionunadulterated milk, free of antimicrobial residues is important for industrial processing and consumers’ health. Antimicrobial residues in foods of animal origin can cause adverse public health effects like drug resistance and hypersensitivity. Milk produced in Lamu West sub-county is sold raw directly to consumers. We estimated the compositional quality and prevalence of antimicrobial residues in informally marketed raw cow milk in Lamu West Sub-County, Kenya.Methodswe randomly recruited 152 vendors and 207 farmers from four randomly selected urban centers in a cross-sectional study and interviewed them using a pretested standardized questionnaire. A100-ml raw milk sample was aseptically collected from each vendor and farm and tested for antimicrobial residues using Charm Blue Yellow II kit following the European Union Maximum Residue Limits (EU-MRLs) while an Ekomilk® Analyzer was used to measure compositional quality where samples with either solid not fat (SNF) < 8.5 or added water ≥ 0.01% or both were considered adulterated. We analyzed data using univariate analysis and unconditional logistic regression to calculate odds ratios (OR) and 95% confidence intervals (CI).Resultsthirty-two of the 207 (15.5%) samples from farmers and 28 (18.4%) of the 152 samples from vendors tested positive for antimicrobial residues. Thirty-six (17.4 %) samples from farmers and 38 (25.0%) from vendors were found to be adulterated with water. Farmers’ awareness of the danger of consuming milk with antimicrobial residues and farmers having training on good milking practices were protective against selling milk with antimicrobial residues (adjusted OR and 95% CI 0.20, 0.07-0.55 and 0.33, 0.11-0.99, respectively).Conclusionthe antimicrobial residues above EU MRLs and adulteration of raw marketed cow milk observed in this study provide evidence for routine testing of marketed milk and educating farmers to observe antimicrobial withdrawal period.

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Section: Discussionmentioning

confidence: 99%

Antimicrobial residues and compositional quality of informally marketed raw cow milk, Lamu West Sub-County, Kenya, 2015

et al. 2017

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“…There have been several recent reviews devoted to the detection of adulterants in milk and other liquid foods (Jha et al . ; Nascimento et al . ; Poonia et al .…”

Section: Introductionmentioning

confidence: 99%

“…There have been several recent reviews devoted to the detection of adulterants in milk and other liquid foods (Jha et al 2016;Nascimento et al 2017;Poonia et al 2017). These cover a range of analytical techniques and suggest that the combination of vibrational spectroscopy and chemometrics provides a powerful tool for quality and authenticity analysis of milk.…”

Section: Introductionmentioning

confidence: 99%

Development and application of Fourier transform infrared spectroscopy for detection of milk adulteration in practice

Hansen¹,

Holroyd

2019

Int J of Dairy Tech

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Fourier transform infrared (FT‐IR) spectroscopy is widely applied for routine milk analysis. More recently, it has been used to detect a range of specific milk adulterants. Here, we show that the simultaneous use of targeted and untargeted models applied to FT‐IR spectra for detecting potential milk adulterants across relevant concentration ranges is an effective strategy. Using an appropriate validation strategy, limits of detection, sensitivity and specificity are determined for specific adulterants giving a useful guide to how these models would work in a practical situation. Finally, theoretical limits of detection of a range of potential adulterants are listed.

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“…The increase in the world population and rising incomes together with government and private-aided schemes have led to alarming growth in the demand for dairy products, especially in developing countries such as India (OECD/FAO 2014). This higher demand for milk and milk products has encouraged certain illegal practices, such as adulteration of milk with water, starch, urea, sugar, formalin, synthetic milk, detergents and vegetable fats (Jha and Matsuoka 2004;Koca et al 2010;Jha et al 2016). These ingredients are cheap and readily available.…”

Section: Introductionmentioning

confidence: 99%

“…Spectroscopy is a rapid, accurate and nondestructive technique for the analysis of chemical components requiring minimal sample preparation (Schrader 2008;Karoui et al 2010;Narsaiah et al 2012;Jaiswal et al 2014;Jha et al 2016). Ntakatsane et al (2013) used fluorescence spectroscopy for the rapid detection and characterisation of vegetable oil adulteration in milk fat.…”

Section: Introductionmentioning

confidence: 99%

Rapid detection and quantification of soya bean oil and common sugar in bovine milk using attenuated total reflectance–fourier transform infrared spectroscopy

Jaiswal

Jha

Kaur

et al. 2017

Int J of Dairy Tech

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Attenuated total reflectance–Fourier transform infrared spectroscopy, along with chemometrics, were used to detect and quantify soya bean oil (SO) and sugar (CS) adulteration in milk. Bovine milk was artificially adulterated with SO (0.2–2.0%; v/v) and CS (1–10%; w/v) separately. Spectra revealed significant differences in specific wavenumber regions (SO: 1450–1250 cm−1; CS: 1200–900 cm−1). Soya bean oil adulteration was best predicted in wavenumber range of 1262–1164 cm−1, using partial least square regression (coefficient of determination (R2: 0.90 and 0.88 for calibration and validation, respectively). Common sugar adulteration was best predicted in wavenumber range of 1010–910 cm−1 (R2: 0.99 for calibration and validation) using partial least square.

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Detection of Adulterants and Contaminants in Liquid Foods—A Review

Cited by 66 publications

References 224 publications

Antimicrobial residues and compositional quality of informally marketed raw cow milk, Lamu West Sub-County, Kenya, 2015

Antimicrobial residues and compositional quality of informally marketed raw cow milk, Lamu West Sub-County, Kenya, 2015

Development and application of Fourier transform infrared spectroscopy for detection of milk adulteration in practice

Rapid detection and quantification of soya bean oil and common sugar in bovine milk using attenuated total reflectance–fourier transform infrared spectroscopy

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