Detection of Veterinary Antimicrobial Residues in Milk through Near-Infrared Absorption Spectroscopy. (2024)

1. Introduction

According to the Food and Agriculture Organization of the UnitedNations, milk is one of the most consumed foods in the world. It notonly has its importance in the nutritional level, but also plays animportant role in the economy. Global consumption of milk and itsderivatives exceeds 6 billion of consumers [1].

The milk contains protein, carbohydrates, lipids, minerals, andvitamins which accomplish important biochemical and nutritionalfunctions, particularly to children and elderly people. The bovine milkcontains about 87.1% of water, 4.0% of fat, 3.3% of protein, 4.6% oflactose, and 0.7% of ash. The basic protein content in milk is casein in78.3%, whey protein 19%, and others totaling 2.7% [2, 3]. Concerningcarbohydrates, lactose is the main one. Constituted by twomonosaccharides, glucose and galactose, they carry nutritional importantfunctions, such as providing 16.8 kJ/g of energy to people [4, 5]. Milkand dairy products are considered a good source of calcium due its highbioavailability. The latter can be understood as the fraction ofingested nutrient and food that is absorbed and used in physiologicaland normal metabolic functions and storage [6, 7]. Although thepotentiality of milk as food is unquestionable, restrictions on itsintake exist in people allergic to lactose and casein.

Adulterations in milk have been highly reported in developingcountries, such as Pakistan, Brazil, India, and China [8]. Mostly theaim is to increase volume with the addition of water [9]. However, thereare other problems, such as the contamination of milk by residues ofveterinary drugs that may be present when the cow is milked in the graceperiod. The most common drugs are antimicrobials andanti-inflammatories. They are widely used in the treatment of dairycattle diseases, such as mastitis, diarrhea, and lung diseases, also inprevention and control, or to increase the production and growth ofanimal [10-13]. A study performed by Van Boeckel et al. showed that,between 2000 and 2010, the consumption of antibiotics by the worldpopulation has increased by 36% and is related to the appearance ofdrug-resistant bacteria. From this total, 76% is mainly due to thecountries that composes the BRICS (Brazil, Russia, India, China, andSouth Africa). Fraction of this increase is due to ingestion of animalsor their food derivatives contaminated with antibiotics [14].

The overuse of drugs in dairy herd results in detectable traces inthe milk. When their concentrations are over the maximum residue limit(MRL), they can cause health damage to the consumer ranging fromallergic reactions to bacterial resistance [13] Contaminated milk isharmful to health and should be discarded [11, 15, 16]. In 2014, VanBoeckel et al. related the excessive use of antibiotics in animals tothe appearance of super bacteria in humans. In order to monitor the milkcontent, the regulatory agencies use a variety of analytical methods todetect antibiotics traces in the milk, such as high-performance liquidchromatography (HPLC), gas chromatography coupled to mass spectroscopy(CG-MS), and antimicrobial detection kits. Nevertheless, there aredrawbacks in their use such as sample preparation, qualified manpower,complex procedures, time consuming, and high cost. Moreover, normallythe tests of antibiotics are specific to a class of antimicrobials.

The search for high sensitive techniques that allow the detectionof residues of antibiotics in milk has been carried out for decades. In1996, Verdon and Couedor used a reverse-phase HPLC technique todetermine ampicillin residues which is able to detect 3 [micro]g/L andto quantify up to 10 [micro]g/L of the drug [17]. In 2002, Sivakesavaand Irudayaraj carried out a study showing the feasibility of measuringtetracycline at [micro]g/L levels with Fourier transform near-infrared(FT-NIR) spectroscopy and Fourier transform medium-infrared (FT-MIR)spectroscopy. Nevertheless, they reported high prediction errors andsuggested that the methodology should be confirmed with naturallycontaminated samples and other drug residues [18]. In 2003, Jankovskaand Sustova used FT-NIR to analyse cow milks. However, the technique wasused to describe physical-chemical characteristics of milk. In addition,partial least squares (PLS) regression was used to develop calibrationmodels for the examined milk components. Through these results, theysuggest that the NIR spectroscopy is applicable for a rapid analysis ofmilk composition [19]. In 2010, Brandao et al. studied fat concentrationin milk samples by means of noninvasive techniques, FT-IR and FT-NIRabsorption. They concluded that the wavelength of 2308 nm can be used todetermine the fat concentration of milk without other components'influence [20]. In 2014, Zhang et al. [21] examined UHT and pasteurizedmilks to verify the presence of residues of tetracyclines, sulfonamides,sulfamethazine, and quinolone. The milk samples were collected in highlypopulated cities of China and analysed by the enzyme-linkedimmunosorbent assay (ELISA). No residue of veterinary drugs has exceededMRL established by China, European Union, and CAC (Codex AlimentariusCommission). Nevertheless, because of the high number of residuespresent in milk, they recommended that the control mechanisms should berigorously applied in order to keep these residues at safe levels. In2015, Moharana et al. [22] analysed the veterinary drug enrofloxacin incow milk samples obtained from two cities of India. According to theauthors, the enrofloxacin is the most rampantly used drug in veterinarypractice. To analyse the samples, they used reverse-phase HPLC. With alimit of detection of 100 [micro]g/L, they have verified that 8% of thesamples had values above the MRL. From the brief historical reviewdescribed above, it is clear that there is a need for more in-depthstudies exploring detection limits, embracing bigger classes ofantibiotics, and analysing real samples.

This work deals with Fourier transform near-infrared (FT-NIR)spectroscopy associated with principal components analysis (PCA) todetect traces of veterinary antimicrobials (enrofloxacin, terramycin,penicillin, and ceftiofur hydrochloride) bellow the MRL allowed by thelegislation of European Agency for Medicinal Products (EMEA) which isadopted in Brazil by Ministry of Agriculture Livestock and Food Supply(MAPA) [23]. The detection of the ceftiofur hydrochloride in milk wasperformed for two consecutive days after the drug has been administeredto the animal.

2. Materials and Methods

The analyses were performed in the Process and Products Laboratory(LPP) and in the Materials Spectroscopy Laboratory (LEM), located in thePhysics Department of Federal University of Juiz de Fora, Brazil.

2.1. Milk Samples. Some samples used in this work were raw milkfrom nonmedicated cows. They were collected at a farm located in thecity of Rio Pomba, MG, Brazil, near the laboratory. After milking, theraw milk samples were immediately stored and kept refrigerated at5[degrees]C until analysis which was performed after approximately onehour. The samples were submitted to chemical-physical analysis to verifytheir conformity with the established standards [24], that is,cryoscopy, density, pH, acidity (Dornic and Alizarol tests), fat,protein, lactose, and solids [25-27]. Each measurement was performed intriplicate. The results are shown in Table 1.

2.2. Contamination Simulation. Initially, two portions wereseparated, one as a control sample and the other as a self-controlledone with a veterinary drug. The drugs used were the antimicrobials:enrofloxacin Baytril[R] injective 10% that has 10 g of enrofloxacin plus100 ml of vehicle in its composition, terramycin/LA Zoetis/Pfizer[R]injective that has 20 g of oxytetracycline plus 100 g of vehicle in itscomposition, and reinforced pentabiotic Pfizer with penicillin.

The simulation was done according to the active principle of eachdrug and not in its volume. More explicitly, in the analysis with PCA,the discrimination of contaminated milk in [micro]g/L is given throughthe active principle, MRL as provided by legislation, and not throughthe drug (excipients + active principle). For this purpose, eachveterinary drug was first diluted in distilled water, and finally, partof this dilution was added in the genuine milk, in order to reach theconcentration of the active principle in the milk. The values equivalentto the MRL allowed by EMEA and MAPA for the antimicrobials and itsmetabolites are as follows: 100 [micro]g/L to enrofloxacin, 100[micro]g/L to terramycin, and 4 [micro]g/L to penicillin [22, 28, 29].This methodology was applied previously to the anti-inflammatory sodiumdiclofenac [30].

2.3. Real Contaminated Samples. First, the milk free from drugs wascollected from a cow used as a control. The CeF-50 Ceftiofur Agner Unioninjective drug, which has 50 g of ceftiofur hydrochloride plus 1 mL ofvehicle in its composition, was then administered to the cow. This drugdoes not have a grace period. Milk is then collected for two consecutivedays. All the samples were immediately stored and kept refrigerated at5[degrees]C until analysis which was performed after approximately onehour.

2.4. Analysis UsingFT-NIR Method. Analyses of the samples werecarried out with the Multi Purpose FT-NIR Analyser from Bruker operatingin the reflectance mode in the range of 13.500 to 3.700 [cm.sup.-1]wavenumbers with a Te-InGaAs detector and 4 [cm.sup.-1] of resolution.The OPUS[R] software version 5.5 was used for data acquisition. Thesamples were placed in borosilicate cuvettes with 8 mm thickness. Eachanalysis was performed in triplicate with 32 scans for simulated andcontrol samples.

2.5. Statistical Analysis. The reflectance spectra and their firstderivatives were made and analysed with the software OriginPro[R]8 SR2v.8.0891(B891). The eigenvalues were calculated with the softwareBioStat version 5.3. The principal component analysis was conducted withthe software The Unscrambler[R] X version 10.3.

3. Results

Table 1 shows the average results obtained for the milk qualityparameters of the samples and the reference value established by theBrazilian Normative Instruction 62 from MAPA and the FAO/TCP/KEN/6611[24]. The results are in the range accepted by the legislation.

Figure 1 shows the reflectance spectra (top) and their firstderivatives (bottom) of genuine milk and pure antimicrobials. From thefigure, one can see that the spectra are very different from each otherabove all, in the first derivatives.

Figure 2 shows the reflectance spectra (top) and their firstderivatives (bottom) of genuine and contaminated milk samples within theMRL. On the contrary of Figure 1, now the differences between thespectral profiles are not apparent due to the very low concentration ofthe antibiotics. Therefore, we have to rely on a statistical model. Thiswill be accomplished by means of PCA to discriminate control andtampered milk samples.

The principal component of a set of data (dimensionality) isobtained by means of an analysis that consists in finding theeigenvalues of the covariance matrix [31]. Each eigenvector has acorresponding eigenvalue. The eigenvectors with higher eigenvalues arethe principal components and are ordered from the higher to the smallerones furnishing the components in significance degree [32]. Table 2shows the explained and cumulative variances of the principal componentsof genuine and contaminated milk samples within the MRL.

Figure 3 shows the score plot with the clustering of milk samples:control (GEN1, GEN2, GEN3), contaminated with 100 [micro]g/L ofenrofloxacin (EN100.1, EN100.2, EN100.3), contaminated with 100[micro]g/L of terramycin (TE100.1, TE100.2, TE100.3), and contaminatedwith 4 [micro]g/L of penicillin (PE4.1, PE4.2, PE4.3).

From Figure 3, it is clear the formation of clusters resulting fromthe high degree of similarity between groups of samples. Four groups arepresent, one in each quadrant. Group 1 (squares) refers to genuine milk(control samples) and is located in the first quadrant. Group 2 islocated in the second quadrant (circles). This cluster represents agroup of contaminated milk samples with 4 [micro]g/L of penicillin. Thethird quadrant contains elements of group 3 which is related tocontaminated milk samples with 100 [micro]g/L of enrofloxacin(triangles), while the fourth quadrant is occupied by group 4(rhombuses) containing contaminated milk samples with 100 [micro]g/L ofterramycin. Among the elements of the groups, none is far apart fromeach other which discard the presence of outliers. The PCA accuratelydiscriminated the samples in groups despite the very low concentrationof the antimicrobials. From PC1, one can observe that the penicillin andenrofloxacin have the same score in contraposition to terramycin andgenuine milk. This trend maybe depicted in the absorption spectra(Figure 2). Therefore, PC1 represents the degree of milk contaminationwith antibiotics. Note that the group of data containing genuine milk isclose to the centre of the axis. The contaminated clusters havedifferent distances and different positions from the centre. This isrelated to the fact that the concentrations of the drugs are different.For example, samples with 100 [micro]g/L of medication (groups 3 and 4)have similar position. From the above reasoning, we are led to inferthat PC2 is related to the milk similitude.

All samples analysed until now were raw milk. Concerning pureantimicrobial data one may verify that the PCA is also able todiscriminate between them. Figure 4 deals with such fact. It shows thePCA of average values of reflectance spectra of genuine milk, pureenrofloxacin, pure terramycin, and pure penicillin, andmilk-enrofloxacin in 100 [micro]g/L, milk-terramycin in 100 [micro]g/L,and milk-penicillin in 4 [micro]g/L, respectively. It can be seen thatthe milk-like samples (GEN, EN100, TE100, and PE4) are located veryclose in relation to PC1 which indicates the degree of similaritybetween them (cluster formation). For this reason, the samples ofenrofloxacin antimicrobial (ENR), penicillin antimicrobial (PEN), andterramycin antimicrobial (TER) are so far apart from the group. Purepenicillin sample is detached from the other clusters because it was theonly solid matrix (powder), while the others were liquid.

Table 3 shows the explained and cumulative variances for each ofthe principal components of the average values of pure enrofloxacin,pure terramycin, pure penicillin, genuine milk, milk-enrofloxacin andmilk-terramycin in 100 [micro]g/L each, and milk-penicillin in 4[micro]g/L.

Figure 5 shows the methodology applied in a real situation. Itshows data of a control milk, without medication, and contaminated milkin two consecutive days after the administration of the drug ceftiofurhydrochloride in a cow. Table 4 has the respective explained andcumulative variances from the data of Figure 5.

Cluster formation was observed for the genuine milks (GEN1, GEN 2,and GEN3) and one-day and two-day drug administered milk (1DAY and2DAY). It turns out that the GEN and 2DAY groups are along the same PC1,showing the similarity between the groups. This is due to themetabolization of the antibiotic in the milked cow after two days of thedrug administration. Reinforcement of this supposition is apparent whencompared with one day milked sample with genuine milk. The PC2 isconnected with time of milking as the spectroscopic measurements wereperformed after the last day of milking (2DAY).

4. Conclusions

This article dealt with the identification of the antimicrobialsenrofloxacin, terramycin, penicillin, and ceftiofur in milk samples inthe MRL permitted by regulatory agencies. The methodology developed isbased on the combination of Fourier transform near-infrared (FT-NIR)spectroscopy jointly with principal component analysis (PCA). Theexperimental procedure was able to detect antibiotics traces in a fastand accurate way. The methodology was applied also to detect ceftiofurhydrochloride in milk of a cow where the drug was administered. Beyondtrace detection, we are also able to follow the metabolization processin the animal. Our results clearly demonstrate the potentiality of themethod for the development of a portable prototype.

https://doi.org/10.1155/2018/5152832

Data Availability

The data used to support the findings of this study are availablefrom the corresponding author upon request.

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper.

Acknowledgments

The authors thank the Brazilian funding agencies CAPES (PNPD2871/2011), CNPq (309100/2016-0), and FAPEMIG (MPR 00004-13 and MPR01068/16) for financial funding. Leandro da Conceicao Luiz would like tothank the Chemical Department of Rural Federal University of Rio deJaneiro, Brazil, for the access to the software The Unscrambler.

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Leandro da Conceicao Luiz (iD), (1) Maria Jose Valenzuela Bell(iD), (1) Roney Alves da Rocha, (2) Nayara Lizandra Leal, (1) andVirgilio de Carvalho dos Anjos (1)

(1) Grupo de Engentaria e Espectroscopia de Materiais, Departamentode Fisica, Universidade Federal de Juiz de Fora, 36036-900 Juiz de Fora,MG, Brazil

(2) Departamento de Ciencias de Alimentos, Universidade Federal deLavras, 37200-000 Lavras, MG, Brazil

Correspondence should be addressed to Leandro da Conceicao Luiz;[emailprotected]

Received 25 February 2018; Accepted 6 May 2018; Published 3 June2018

Academic Editor: Maria Carmen Yebra-Biurrun

Caption: Figure 1: Reflectance spectra of pure samples of genuinemilk and veterinary drugs with their respective first derivatives.

Caption: Figure 2: Reflectance spectra and their first derivativesof genuine and contaminated milk samples within the MRL.

Caption: Figure 3: Hotelling score plot of statistical analysis(PCA) showing clustering data for control milk samples GENI, GEN2, andGEN3 (blue square); milk with 100 [micro]g/L of enrofloxacin, EN100.1,EN100.2, and EN100.3 (green triangles); 100 [micro]g/L of terramycin,TE100.1, TE100.2, and TE100.3 (black rhombuses); and milk with 4[micro]g/L of penicillin, PE4.1, PE4.2, and PE4.3 (red circles).

Caption: Figure 4: Score plot of statistical analysis (PCA) foraverage values of samples: pure enrofloxacin (ENR), pure terramycin(TER), pure penicillin (PEN), genuine milk (GEN), milk-enrofloxacin andmilk-terramycin in 100 [micro]g/L each (EN100 and TE100), andmilk-penicillin in 4 [micro]g/L.

Caption: Figure 5: Score plot of statistical analysis (PCA) forsamples of genuine milk (GEN) and milk collected for 2 days after thecow took the ceftiofur hydrochloride.

Table 1: Result of physical-chemical characterizationof milk samples. Average values and their standard deviations.Analysis ValuesCryoscopy (0.536 [+ or -] 0.001) [degrees]HAcidity (17.3 [+ or -] 0.6) [degrees]DornicDensity (1.031 [+ or -] 0.000) g/mLpH to [degrees]C (6.72 [+ or -] 0.01)Fat (3.65 [+ or -] 0.01) %Protein (3.14 [+ or -] 0.01) %Lactose (4.50 [+ or -] 0.01) %Solids (11.29 [+ or -] 0.01) %Analysis Values reference (a,b)Cryoscopy (-0.550 to -0.530) [degrees]HAcidity (14 to 18) [degrees]DornicDensity (1.029 to 1.040) g/mLpH to [degrees]C (6.60 to 6.80)Fat [greater than or equal to] 3.00Protein [greater than or equal to] 2.90Lactose [greater than or equal to] 4.30Solids [greater than or equal to] 8.40(a) IN 62; (b) FAO/TCP/KEN/6611.Table 2: Explained and cumulative variances of genuineand contaminated milk samples within the MRL.PC Explained variance (%) Cumulative variance (%)PC1 99.9159 99.9159PC2 0.0156 99.9315PC3 0.0105 99.9420PC4 0.0102 99.9522PC5 0.0093 99.9615PC6 0.0084 99.9699PC7 0.0080 99.9779PC8 0.0077 99.9857PC9 0.0069 99.9926PC10 0.0060 99.9986PC11 0.0008 99.9993PC12 0.0007 100.0000Table 3: Explained and cumulative variances of average values ofsamples: pure enrofloxacin, pure terramycin, pure penicillin,genuine milk, milk-enrofloxacin and milk-terramycin in 100[micro]g/L each, and milk-penicillin in 4 [micro]g/L.PC Explained variance (%) Cumulative variance (%)PC1 81.9197 81.9197PC2 13.6470 95.5667PC3 3.6040 99.1707PC4 0.8143 99.9850PC5 0.0065 99.9915PC6 0.0045 99.9660PC7 0.0040 100.0000Table 4: Explained and cumulative variances of samples of genuinemilk and milk collected for 2 days after the cow took the ceftiofurhydrochloride.PC Explained variance (%) Cumulative variance (%)PC1 99.7444 99.7444PC2 0.1629 99.9073PC3 0.0170 99.9243PC4 0.0153 99.9538PC5 0.0143 99.9538PC6 0.0137 99.9675PC7 0.0114 99.9790PC8 0.0109 99.9898PC9 0.0102 100.0000