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Removing fat from whole milk and adding water to milk to increase its volume are among the most common food fraud practices that alter the characteristics of milk. Usually, deviations from the expected fat content can indicate adulteration. Infrared spectroscopy is a commonly used technique for distinguishing pure milk from adulterated milk, even when it comes from different animal species. More recently, portable spectrometers have enabled in situ analysis with analytical performance comparable to that of benchtop instruments. Partial Least Square (PLS) analysis is the most popular tool for developing calibration models, although the increasing availability of portable near infrared spectroscopy (NIRS) has led to the use of alternative supervised techniques, including support vector machine (SVM). The aim of this study was to develop and implement a method based on the combination of a compact and low-cost Fourier Transform near infrared (FT-NIR) spectrometer and variable cluster–support vector machine (VC-SVM) hybrid model for the rapid classification of milk in accordance with EU Regulation EC No. 1308/2013 without any pre-treatment. The results obtained from the external validation of the VC-SVM hybrid model showed a perfect classification capacity (100% sensitivity, 100% specificity, MCC = 1) for the radial basis function (RBF) kernel when used to classify whole vs. not-whole and skimmed vs. not-skimmed milk samples. A strong classification capacity (94.4% sensitivity, 100% specificity, MCC = 0.95) was also achieved in discriminating semi-skimmed vs. not-semi-skimmed milk samples. This approach provides the dairy industry with a practical, simple and efficient solution to quickly identify skimmed, semi-skimmed and whole milk and detect potential fraud. [ABSTRACT FROM AUTHOR]

Removing fat from whole milk and adding water to milk to increase its volume are among the most common food fraud practices that alter the characteristics of milk. Usually, deviations from the expected fat content can indicate adulteration. Infrared spectroscopy is a commonly used technique for distinguishing pure milk from adulterated milk, even when it comes from different animal species. More recently, portable spectrometers have enabled in situ analysis with analytical performance comparable to that of benchtop instruments. Partial Least Square (PLS) analysis is the most popular tool for developing calibration models, although the increasing availability of portable near infrared spectroscopy (NIRS) has led to the use of alternative supervised techniques, including support vector machine (SVM). The aim of this study was to develop and implement a method based on the combination of a compact and low-cost Fourier Transform near infrared (FT-NIR) spectrometer and variable cluster–support vector machine (VC-SVM) hybrid model for the rapid classification of milk in accordance with EU Regulation EC No. 1308/2013 without any pre-treatment. The results obtained from the external validation of the VC-SVM hybrid model showed a perfect classification capacity (100% sensitivity, 100% specificity, MCC = 1) for the radial basis function (RBF) kernel when used to classify whole vs. not-whole and skimmed vs. not-skimmed milk samples. A strong classification capacity (94.4% sensitivity, 100% specificity, MCC = 0.95) was also achieved in discriminating semi-skimmed vs. not-semi-skimmed milk samples. This approach provides the dairy industry with a practical, simple and efficient solution to quickly identify skimmed, semi-skimmed and whole milk and detect potential fraud.

Electronic tongue mimics human gustatory sensation and is used to characterize and discriminate beverages and foods. Feature extraction plays a key role in improving the classification accuracy by preserving the distinct characteristics while reducing high dimensionality of data generated from electronic tongue. This paper presents a new feature extraction method based on stationary wavelet singular entropy for a developed electronic tongue system to classify pasteurized cow milk. The electronic tongue consists of an array of five working electrodes along with a reference and a counter electrode to characterize milk sample. The feature extraction of acquired data is done by computing stationary wavelet transform to obtain detail and approximate coefficients at different level of decomposition. These coefficients are processed using singular value decomposition followed by calculation of entropy to obtain stationary wavelet singular entropy values. These values form the feature set and feed to two classifiers, k-nearest neighbor and back propagation artificial neural network, and their classification accuracy is evaluated with variation in their model parameters. The proposed method is compared with other wavelet transform-entropy methods in terms of classification accuracy, which indicates that the proposed method is more effective in discriminating milk samples. [ABSTRACT FROM AUTHOR]

The paper presents the application of support vector machine (SVM) neural approach to the calibration of the electronic nose arrangement for milk recognition. The semiconductor gas sensor array mounted into the measurement test chamber has been used to measure the odour. The pre-processed sensor signals are applied to the SVM neural network performing the role of recognition and classification of the milk. The results of numerical experiments of the recognition of different types of milk have been presented and discussed. [Copyright &y& Elsevier]

Background: International guidelines recommend children aged 9 months to 2 years consume whole (3.25%) fat cow's milk, and children older than age 2 years consume reduced (0.1-2%) fat cow's milk to prevent obesity. The objective of this study was to evaluate the longitudinal relationship between cow's milk fat (0.1-3.25%) intake and body mass index z-score (zBMI) in childhood. We hypothesized that higher cow's milk fat intake was associated with lower zBMI., Methods: A prospective cohort study of children aged 9 months to 8 years was conducted through the TARGet Kids! primary care research network. The exposure was cow's milk fat consumption (skim (0.1%), 1%, 2%, whole (3.25%)), measured by parental report. The outcome was zBMI. Height and weight were measured by trained research assistants and zBMI was determined according to WHO growth standards. A linear mixed effects model and logistic generalized estimating equations were used to determine the longitudinal association between cow's milk fat intake and child zBMI., Results: Among children aged 9 months to 8 years (N = 7467; 4699 of whom had repeated measures), each 1% increase in cow's milk fat consumed was associated with a 0.05 lower zBMI score (95% CI -0.07 to -0.03, p < 0.0001) after adjustment for covariates including volume of milk consumed. Compared to children who consumed reduced fat (0.1-2%) milk, there was evidence that children who consumed whole milk had 16% lower odds of overweight (OR = 0.84, 95% CI 0.77 to 0.91, p < 0.0001) and 18% lower odds of obesity (OR = 0.82, 95% CI 0.68 to 1.00, p = 0.047)., Conclusions: Guidelines for reduced fat instead of whole cow's milk during childhood may not be effective in preventing overweight or obesity., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Undernutrition is a major global health problem. Various types of animal milk are used for feeding children at early ages; however, associations of camel milk (CaM) and bovine milk (BM) with the nutritional status of children have not been explored. A comparative community-based cross-sectional study was conducted among pre-schoolers in rural pastoral districts of Somali, Ethiopia. Children were selected from households with lactating camels or cows. Anthropometric measurements followed standard procedures for height-for-age, weight-for-age and weight-for-height scores. Independent sample t -tests identified significant differences in anthropometric indices based on the type of milk consumed. Multivariable logistic regression was used to examine associations between milk consumption and other predictors of growth failures. The prevalence of stunting was 24⋅1 % [95 % confidence interval (CI) 20⋅5, 28⋅3] of pre-schoolers, 34⋅8 % (95 % CI 29⋅9, 39⋅6) were wasted and 34⋅7 % (95 % CI 30⋅1, 39⋅9) were underweight. Higher proportions of BM-fed children were severely stunted, wasted and underweight compared with CaM consumers. Using logistic regression models, children who consumed BM [adjusted odds ratio (AOR): 2⋅10; 95 % CI 1⋅22, 3⋅61] and who were anaemic (AOR: 4⋅22; 95 % CI 2⋅23, 7⋅98) were more likely to be stunted than their counterparts, while girls were less likely to be stunted than boys (AOR: 0⋅57; 95 % CI 0⋅34, 0⋅94). Similarly, children who consumed BM (AOR: 1⋅97; 95 % CI 1⋅20, 3⋅24), who were anaemic (AOR: 2⋅27; 95 % CI 1⋅38, 3⋅72) and who drank unsafe water (AOR: 1⋅91; 95 % CI 1⋅19, 3⋅07) were more likely to be underweight than their counterparts. In conclusion, CaM consumption was associated with lower prevalence of stunting and underweight than BM. Promoting CaM in pastoralist areas may help to curb the high level of undernutrition., (© The Author(s) 2021.)

Due to the prevalence and severity of cow milk (CM) allergy (CMA), an ideal substitute is urgently needed to develop hypoallergenic infant formula for infants who experience anaphylaxis to typical whey-based CM formula. Goat milk (GM) and horse milk (HM) are considered appropriate substitutes; however, whether GM and HM are less allergenic than CM is unclear. In the present study, the difference in allergenicity among CM, GM, and HM was investigated using the Balb/c mouse model. The number of mice with severe respiratory symptoms was significantly lower in the GM- and HM-sensitised groups than in the CM-sensitised group. Furthermore, histologic examination of intestinal and lung tissues revealed a thinner lamina propria of the small intestine and obvious inflammation and congestion in lungs in the CM-sensitised group than in the GM- and HM-sensitised groups. CM-specific immunoglobulin (Ig) E, serum IgG1, and plasma histamine levels were also higher in CM-sensitised mice than in GM- or HM-sensitised mice. In addition, higher interleukin (IL) 4 and IL-17A levels and lower interferon-γ (IFN-γ) and IL-10 levels were observed in CM-sensitised mice compared with GM- and HM-sensitised mice, according to qPCR, indicating Th1/Th2 and Treg/Th17 imbalances. The CM-sensitised group had a higher proportion of IL-4- and IL-17A-producing CD3+ T cells but a lower proportion of IFN-γ- and IL-10-producing CD3+ T cells compared with the GM- and HM-sensitised groups, confirming the Th1/Th2 and Treg/Th17 imbalances. In conclusion, GM and HM were less allergenic than CM in mice as a result of a shift in the Th1/Th2 and Treg/Th17 imbalances; however, HM was less allergenic than GM and can be used as an alternative milk to develop infant formulas for children with CMA.

This study aims at investigating whether the livestock, lactation stage, or geographical origin of specialty milk in China could be classified by the elemental contents. Samples of goat, buffalo, and yak milk were collected from main production provinces in China and the contents of nine elements in milk from different livestock, regions, and lactation stages were determined. Statistical analysis indicated that the contents of Mn, Cu, As, Se, Cs, and Mo in mature milk were significantly different between the three livestock (p < 0.05). The trends of Mn and Cs contents of the goat milk and buffalo milk increased first and then decreased gradually during lactation. The contents of Se, Cs, Ba, and Mo in mature milk of three livestock were significantly different between the three regions (p < 0.05). The result of linear discriminant analysis (LDA) and partial least squares discrimination analysis (PLS-DA) showed that the total correct classification rates in different livestock for mature milk reached 86.7 and 90%. For goat milk, the total correct classification rates of different lactations and regions reached 88.9 and 77.8% for LDA (100 and 87.5% for PLS-DA), and followed by yak milk of different regions which achieved 88.9% for LDA (88.9% for PLS-DA). In summary, the microelements in milk showed a significant correlation with livestock, region, and lactation of goat, buffalo, and yak milk. The elemental fingerprints combined with the LDA could be potential for classifying the livestock, lactation stage, and geographical origin of milk. PRACTICAL APPLICATION: According to study the contents of miroelements in milk from different livestock, regions, and lactation stages, provide evidence and support for classifying the livestock, lactation stage, and geographical origin of milk., (© 2021 Institute of Food Technologists®.)

The main challenges in the purification of α S2 -casein are due to the low quantity in milk and high homology with other casein subunits, i.e., α S1 -casein, β-casein, and κ-casein. To overcome these challenges, the aim of this study was to develop a two-step purification to isolate native α S2 -casein in goat milk from five different breeds; British Alpine, Jamnapari, Saanen, Shami, and Toggenburg. The first step of the purification was executed by anion-exchange chromatography under optimal elution conditions followed by size exclusion chromatography. Tryptic peptides from in-gel digestion of purified α S2 -casein were sequenced and analyzed by LC-ESI-MS/MS. From 1.05 g of whole casein, the highest yield of α S2 -casein (6.7 mg/mL) was obtained from Jamnapari and the lowest yield (2.2 mg/mL) was from Saanen. A single band of pure α S2 -casein was observed on SDS-PAGE for all breeds. The α S2 -casein showed coverage percentage of amino acid sequence from 76.68 to 92.83%. The two-step purification process developed herein was successfully applied for isolating native α S2 -casein from goat milk with high purity, which will allow for future in vitro studies to be conducted on this protein., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Bovine mastitis is a major health problem that affects dairy cows and has a negative impact on milk production. The presence of microRNAs in biofluids, such as blood and milk, could play a pivotal role in the detection of bovine mastitis. The purpose of the current study was to determine the levels of microRNA gene expression in milk, in combination with other reported mastitis indicators, as a biomarker of bovine mastitis. Milk samples (n = 171) were obtained from 113 dairy cows with known disease status (i.e., healthy; n = 23 cows, subclinical mastitis; n = 45 cows, or clinical mastitis; n = 45 cows) and analyzed for the presence of MIR24-2, MIR29B-2, MIR146A, MIR148A, MIR155, MIR181A1, MIR184, and MIR223 expression using the real-time PCR (qPCR) method. The expression data were then utilized in the creation of receiver operator characteristic curves (ROC) and further analyzed by the machine learning (ML) methods. MIR29B-2, MIR146A, MIR148A, and MIR155 expression levels differed significantly among the three groups. These potential microRNA biomarkers of mastitis exhibited high sensitivity and specificity. Next, we applied ML algorithm, specifically, a decision tree (DT) model to predict the status of milk based on MIR29B-2 and MIR146A expression levels. The results suggested that MIR29B-2, when used in combination with the California mastitis test (CMT) and days in milk (DIM) data, was applicable for screening and classification of milk samples from cows as healthy, subclinical mastitis, or mastitis. MIR29B-2 appears to have sufficient discriminatory power to enable it to be utilized as a biomarker in cases where the status of a milk sample cannot be determined based on CMT results., (Copyright © 2020 Elsevier B.V. All rights reserved.)

In this research communication we describe an innovative protocol that combines three pairs of primers, two from the literature and one designed in our laboratory, for application in triplex-PCR on somatic cell DNA to enable identification of the species origin (cow, sheep, goat) of cheeses and yogurts with a detection limit of 0.1%. Mislabeling was detected in 15 out of 40 cheeses and in 18 out of 40 yogurts tested. The suggested procedure is a quick and reliable tool for identifying the animal origin of cheeses and yogurts and it can be used to certify product reliability on the domestic and international market. Additionally, in combination with a serological test it can offer a reliable tool for detecting the presence of cow's whey.

Spectra data from two instruments (UV-Vis/NIR and FT-NIR) consisting of three and one detectors, respectively, were employed in order to discriminate the geographical origin of milk as a way to detect adulteration. Initially, principal component analysis (PCA) was used to see if clusters of milk from different origins are formed. Separation between samples of different origins were not observed with PCA, hence, feed-forward multi-layer perceptron artificial neural network (MLP-ANN) models were designed. ANN models were developed by changing the number of input variables and the best models were chosen based on high values of generalized R-square and entropy R-square, as well as small values of root mean square error (RMSE), mean absolute deviation (Mean Abs. Dev), and -loglikelihood while considering 100% classification rate. Based on the results, whether the spectra data was collected from a single or three detector instrument the same clustering was observed based on geographical origin., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

In the dairy industry, substitution of high priced milk species with low priced ones is a common practice, and determination of milk species is critical. In this study, synchronous fluorescence spectroscopy (SFS) method was developed for identification of milk species in fermented dairy products (yoghurt and cheese). Three partial least square-discriminant analysis models were developed in order to identify pure-mixed samples, milk species and binary mixture type, and partial least square (PLS) model was utilized to quantify the mixing ratio in binary mixtures. PLS models used for yoghurt and cheese samples showed that detection limits of adulteration were below 3.3%. Apart from the buffalo-cow yoghurt and goat-cow cheese, precision of the measurements was found to be below 6.2. It can be said that SFS technique is applicable on yoghurt and cheese samples as it's a less destructive and a less costly method compared to DNA and protein based conventional methods., (Copyright © 2019. Published by Elsevier Ltd.)

In this study, a fungal and two yeast β-galactosidases were immobilized using alginate and chitosan. The biochemical parameters and lactose hydrolysis abilities of immobilized enzymes were analyzed. The pH optima of immobilized fungal β-galactosidases shifted to more acidic pH compared to free enzyme. Remarkably, the optimal temperature of chitosan-entrapped yeast enzyme, Maxilact, increased to 60 °C, which is significantly higher than that of the free Maxilact (40 °C) and other immobilized forms. Chitosan-immobilized A. oryzae β-galactosidase showed improved lactose hydrolysis (95.7%) from milk, compared to the free enzyme (82.7%) in 12 h. Chitosan-immobilized Maxilact was the most efficient in lactose removal from milk (100% lactose hydrolysis in 2 h). The immobilized lactases displayed excellent reusability, and chitosan-immobilized Maxilact hydrolyzed > 95% lactose in milk after five reuses. Compared to free enzymes, the immobilized enzymes are more suitable for cost-effective industrial production of low-lactose milk due to improved thermal activity, lactose hydrolysis efficiencies, and reusability.

Due to the decrease in fluid milk consumption as a beverage in the United States, the importance for dairy industry stakeholders to understand attribute preferences for consumer segments has increased. This paper uses a representative sample of U.S. residents to determine shopping behavior and a Best-Worst experimental design to examine consumer preferences for select milk attributes. The Random Parameters Logit model revealed the largest preference shares were for price (19.1%), fat content (17.6%), and humane handling (16.1%). Segmentation of the respondents was analyzed using a Latent Class Model, and the demographics of segments were analyzed by probabilistic assignment. This contribution, which may be applied to other products, allows for a detailed understanding of consumer preferences for fluid milk. Demographics such as gender and age were not statistically different across the five classes for this topic, unlike shopping behavior. Class 2 was named "The Balancing Act" due to respondents' balance between animal welfare aspects and the physical characteristics of milk. Class 5 was dubbed "Value and Volume" due to large preference shares for price and container size. A lower percentage of respondents in "The Balancing Act" (12.2%) reported purchasing fat-free skim milk when compared to the percentage of respondents in "Value and Volume" (18.6%). Due to the large preference shares for traditional milk attributes, Class 3 was named "Traditional Milk Shoppers." A higher percentage of respondents in "Value and Volume" also reported always reading the information on meat, egg, or milk products when compared to "Traditional Milk Shoppers" (12.2%). Although price is still important to many consumers, certain segments have preferences or demand for other attributes that may be satisfied by producers to increase market share or price premiums., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

This study aimed to calculate economic values (EVs) and economic selection indices for milk production systems in small rural properties. The traits 305-d milk yield in kg (MY), fat (FP) and protein (PP) percentage, daily fat (FY) and protein (PY) yield, cow live weight in kg (LW), calving interval (CI), and logarithm of daily somatic cell count (SCC) in milk were considered the goals and selection criteria. The production systems were identified from 29 commercial properties based on the inventory of revenues and costs and of zootechnical field data. Later, bioeconomic models were developed to calculate the productive performance, revenues, and costs concerning milk production to estimate EVs, which were calculated as the difference in annual profit with dairy production resulting from a change in one unit of the trait while keeping the others constant and dividing the value by the number of cows. After the EVs were known, ten economic selection indices were estimated for each system so they could be compared by modifying the selection criteria and calculating the relative importance of each selection criteria, the accuracy of the economic selection index, and response expected to the selection in USD, among other parameters. One of the systems detected was called less intensive (LS) and was characterized by having ten cows in lactation that produced 13·5 l/d and consumed 1·8 kg of concentrate/d. The second system detected was called more intensive (IS) and had 22 cows in lactation that produced 17·5 l/d and consumed 3·4 kg of concentrate/d. Monthly profits per cows in lactation of USD 2·60 and USD 68·77 were recorded for LS and IS, respectively. The EVs of the traits MY, FP, and PP were all positive, while for the other traits they were all negative in all situations. The best economic selection indices were those featuring selection criteria MY, LW, and CI, while the trait LW had the greatest importance in both systems. These results indicate that animal frame must be controlled in order to maximize the system's profit.

Dairy foods represent an important sector of the food market for their nutritional qualities and their organoleptic characteristics, which are often linked to tradition and to region. These products are typically protected by labels such as PDO (Protected Designation of Origin) and PGI (Protected Geographical Indication). Real-time PCR (qPCR) is a fundamental tool in "Food Genomics;" a discipline concerned with the residual DNA in food, which, alongside traditional physical and chemical methods, is frequently used to determine product safety, quality and authenticity. Compared to conventional or "end-point" PCR, qPCR incorporates continuous monitoring of reaction progress, thereby enabling quantification of target DNA. This review describes qPCR applications to the analysis of microbiota, and to the identification of the animal species source of milk from which dairy products have been made. These are important aspects for ensuring safety and authenticity. The various applications of qPCR are discussed, as well as advantages and disadvantages in comparison with other analytical methods.

A fast and reproducible protocol for milk Nuclear Magnetic Resonance (NMR) metabolomic fingerprinting was developed, allowing for an accurate discrimination among milk samples from large-scale distribution, as well as among milk sample from different farms located in the same restricted geographical area. Seasonal variations in milk composition and correlations with cows' nutritional patterns are also assessed, underlining relationships between feeding and metabolites. The most important difference was related to the use of silage feeding. This finding is relevant to assess the suitability of milk for different dairy products. A prominent example is parmesan cheese, the preparation protocol of which excludes milk from silage-fed cows., (Copyright © 2018. Published by Elsevier Ltd.)

This study compared the effects of a grain-based conventional concentrate (GC) and a concentrate based on agro-industrial by-products (BC), fed with grass silage harvested at early (ES) or late (LS) maturity stage, on dairy performance, CH 4 and CO 2 emissions, and metabolic status of dairy cows. Twenty lactating Nordic Red cows averaging 81 d in milk and 31.9 kg of milk/d pre-trial were assigned to a replicated 4 × 4 Latin square design. Dietary treatments were in a 2 × 2 factorial arrangement. The silages were harvested 2 wk apart from the same primary growth grass ley. The GC was made from oats, barley and wheat, and soybean meal, whereas the BC contained sugar beet pulp, wheat bran, canola meal, distillers dried grains, palm kernel expeller, and molasses. The diets were fed ad libitum as total mixed rations and were formulated from 661 g/kg of silage, 326 g/kg of concentrate, and 13 g/kg of minerals on a dry matter basis. The BC supplied the cows with less energy. Despite this, milk yield and composition were unaffected by concentrate type, except that milk protein was 0.7 g/kg lower in cows fed BC than in those fed GC. These results were accompanied by a 44 g/kg decrease in total-tract digestibility of crude protein and a 54 g/kg increase in neutral detergent fiber digestibility for cows fed BC. Cows fed ES on average consumed 2 kg/d more dry matter and yielded 3.5 kg/d more milk, 149 g/d more protein, and 141 g/d more fat than cows fed LS. There were few interaction effects between concentrate and silage sources on daily intake and dairy performance. However, edible feed conversion ratio (human-edible output in animal/potentially human-edible feed) showed greater improvements with ES than LS when replacing GC with BC. Feeding diets with late-cut silage generally reduced digestibility and energy utilization efficiency, but improved N utilization efficiency. Feeding LS also led to greater CH 4 yield and CH 4 /CO 2 ratio, and higher plasma concentration of nonesterified fatty acids. Plasma parameters reflecting energy metabolism and inflammation were all within the normal ranges, indicating that the cows were in good health during the experiment. In conclusion, a conventional concentrate can be replaced by agro-industrial by-products without compromising production in early lactation dairy cows. However, silage maturity has a stronger effect on the production traits of dairy cows than type of concentrate., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

There is a growing interest in odd- and branched-chain fatty acids (OBCFA) in milk following reports that several branched-chain fatty acids (FA) have health promoting effects, and certain milk OBCFA could serve as a biomarker to assess ruminal function. Twenty-four Holstein cows were fed 3 low-forage diets containing 30 g/kg of dry matter of prilled palm fat (PPF), sunflower oil (SO), or an equal mixture of both fats (experiment 1) or 3 diets containing 30 g/kg of dry matter of SO with a forage-to-concentrate ratio of 39:61, 44:56, or 48:52 (Experiment 2); diets were fed to investigate milk OBCFA composition and to explore the relationships between ruminal VFA and milk OBCFA using principal component analysis. Including SO in diets decreased yields of milk 13:0 anteiso, 15:0 anteiso, 15:0, 17:0, cis-9 15:1, and cis-9 17:1 compared with PPF. The molar proportion of ruminal propionate was the lowest and the yields of milk 14:0 iso and 16:0 iso were the greatest with the diet containing both fat supplements. Replacing concentrate with forages linearly increased ruminal acetate and yields of milk 13:0 iso, 14:0 iso, 15:0 iso, 16:0 iso, 17:0 iso, 13:0 anteiso, 15:0 anteiso, 15:0, 17:0, cis-9 15:1, and cis-9 17:1. The principal component analysis revealed that ruminal molar proportion of acetate related to concentrations of milk iso FA containing <17-carbon, whereas ruminal propionate related to milk 15:0, 17:0, cis-9 15:1, and cis-9 17:1, with the stronger correlations between milk OBCFA and ruminal acetate than propionate. No associations were found between ruminal molar proportion of butyrate and milk OBCFA concentrations. The results suggest that complete replacement of PPF with SO at 30 g/kg of dry matter in low-forage diets is not an effective strategy to enhance bioactive branched-chain FA in milk, rather this feeding practice lowers anteiso FA in milk; however, increasing forage proportion in diets containing SO enhances several iso and anteiso FA in milk. The milk OBCFA concentrations have stronger correlations with ruminal acetate molar proportion than with propionate or butyrate in cows fed diets containing supplemental fats., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The aim of the studies reported in the Research Communication was to develop a rapid spectroscopic technique as an alternative method for the classification and discrimination of milk sources by Fourier transform infrared spectroscopy (FTIR). Cow, sheep and water buffalo milk samples were collected from various local milk producers in Istanbul, Turkey. In addition, various brands of packaged milk were purchased locally. Spectrums were obtained according to milk species origin and binary mixtures prepared in increments of 10% (10, 20, 30, 40, 50, 60, 70, 80 and 90%) for each sample analysed in FTIR spectroscopy. A successful milk species (cow, sheep, and water buffalo) discrimination and classification were achieved utilising Hierarchical cluster and principle component analyses (PCA) on the basis of Euclidean distance and Ward's algorithm. Amide-I (1700-1600/cm) and Amide-II (1565-1520/cm) spectral bands were used in the chemometric method. The results of the study indicated that adulteration of milk samples can be quantitatively detected by the FTIR technique in a short time with high accuracy. In conclusion, this method could be used as a new alternative technique for routine analysis in authenticity control of milk species origin.

Pasture-raised milk is gaining in importance in some European countries and in the United States. The production of pasture-raised milk is linked to higher costs, as the milk is normally collected and processed separately from conventional barn milk. This could hinder the production of sustainable milk products. We discuss alternative labeling strategies that allow the mixing of pasture-raised (sustainable) and conventional milk to reduce costs and break free from the current niche market. The lower price would allow for more pasture-raised milk to be produced and enter the mainstream market. The aim of this study was to analyze consumers' willingness to pay for alternative labeling types using a discrete choice experiment with 1,065 German milk buyers. The 2 alternative labels, besides the classical labeling approach, are based on the mass balance approach (at least 50% pasture-raised milk in a package) and cause-related marketing (support of farmers who keep their cows on pasture). The discrete choice experiment was combined with a cluster analysis to get a deeper understanding of the buying behavior of the diverse consumer segments for milk. We found that all consumer groups prefer the classical label where products are segregated but also understand the benefits of cause-related marketing. The average consumer was willing to pay €0.50 more for pasture-raised milk certified with the classical label and €0.38 more for pasture-raised milk labeled with a cause-related marketing claim. However, differences between the clusters are strong: The smallest cluster of ethically involved consumers (15%) is willing to pay the highest premiums, especially for the classical label. Cause-related marketing is an interesting alternative for involved buyers under price pressure (41%), whereas the mass balance approach is little understood and thus less valued by consumers. From our results we concluded that cause-related marketing (in our case, the support of pasturing of dairy cows) can be useful for dairies for which it is not efficient to collect and process products separately. This approach is furthermore suitable for reaching consumers who are mainly interested in altruistic issues but at the same time are more price sensitive, as this labeling strategy does not need separate collection and processing and can thereby be marketed at a lower price., (Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

We used a multivariate chemometric approach to differentiate or associate retail bovine milks with different fat contents and non-dairy beverages, using fatty acid profiles and statistical analysis. We collected samples of bovine milk (whole, semi-skim, and skim; n = 62) and non-dairy beverages (n = 27), and we analyzed them using gas-liquid chromatography. Principal component analysis of the fatty acid data yielded 3 significant principal components, which accounted for 72% of the total variance in the data set. Principal component 1 was related to saturated fatty acids (C4:0, C6:0, C8:0, C12:0, C14:0, C17:0, and C18:0) and monounsaturated fatty acids (C14:1 cis-9, C16:1 cis-9, C17:1 cis-9, and C18:1 trans-11); whole milk samples were clearly differentiated from the rest using this principal component. Principal component 2 differentiated semi-skim milk samples by n-3 fatty acid content (C20:3n-3, C20:5n-3, and C22:6n-3). Principal component 3 was related to C18:2 trans-9,trans-12 and C20:4n-6, and its lower scores were observed in skim milk and non-dairy beverages. A cluster analysis yielded 3 groups: group 1 consisted of only whole milk samples, group 2 was represented mainly by semi-skim milks, and group 3 included skim milk and non-dairy beverages. Overall, the present study showed that a multivariate chemometric approach is a useful tool for differentiating or associating retail bovine milks and non-dairy beverages using their fatty acid profile., (Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The current study presents the application of fluorescence spectroscopy for the identification of cow and buffalo milk based on β-carotene and vitamin-A which is of prime importance from the nutritional point of view. All samples were collected from healthy animals of different breeds at the time of lactation in the vicinity of Islamabad, Pakistan. Cow and buffalo milk shows differences at fluorescence emission appeared at band position 382 nm, 440 nm, 505 nm and 525 nm both in classical geometry (right angle) setup as well as front face fluorescence setup. In front face fluorescence geometry, synchronous fluorescence emission shows clear differences at 410 nm and 440 nm between the milk samples of both these species. These fluorescence emissions correspond to fats, vitamin-A and β-carotene. Principal Component Analysis (PCA) further highlighted these differences by showing clear separation between the two data sets on the basis of features obtained from their fluorescence emission spectra. These results indicate that classical geometry (fixed excitation wavelength) as well as front face (synchronous fluorescence emission) of cow and buffalo milk nutrients could be used as fingerprint from identification point of view. This same approach can effectively be used for the determination of adulterants in the milk and other dairy products.

This research paper describes the potential of synchronous fluorescence (SF) spectroscopy for authentication of buffalo milk, a favourable raw material in the production of some premium dairy products. Buffalo milk is subjected to fraudulent activities like many other high priced foodstuffs. The current methods widely used for the detection of adulteration of buffalo milk have various disadvantages making them unattractive for routine analysis. Thus, the aim of the present study was to assess the potential of SF spectroscopy in combination with multivariate methods for rapid discrimination between buffalo and cow milk and detection of the adulteration of buffalo milk with cow milk. SF spectra of cow and buffalo milk samples were recorded between 400-550 nm excitation range with Δλ of 10-100 nm, in steps of 10 nm. The data obtained for ∆λ = 10 nm were utilised to classify the samples using principal component analysis (PCA), and detect the adulteration level of buffalo milk with cow milk using partial least square (PLS) methods. Successful discrimination of samples and detection of adulteration of buffalo milk with limit of detection value (LOD) of 6% are achieved with the models having root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) values of 2, 7, and 4%, respectively. The results reveal the potential of SF spectroscopy for rapid authentication of buffalo milk.

Water buffalo (WB) casein (CN) and curd samples from indigenous Italian and international breeds were examined with the objective of identifying signature peptides that could function as an indicator to determine the origin of their milk products. CN in complex mixtures were digested with trypsin, and peptide fragments were subsequently identified by matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS). The unique presence of a β-CN A variant and an internally deleted αs1-CN (f35-42) variant in international WB milk samples was ascertained by identifying signature tryptic peptides from either dephosphorylated or native CN. Four signature unphosphorylated peptides derived from β-CN A, i.e. (f49-68) Asn(68) (2223.6 Da), (f1-28) Ser(10) (3169.4 Da), (f1-29) Ser(10) (3297.4 Da) and (f33-48) Thr(41) (1982 Da) and two from αs1-CN (f35-42) deleted fragments, i.e. (f23-34) Met(31) (1415.7 Da) and (f43-58) Val(44) (1752.7 Da), were identified. Two signature casein phosphopeptides (CPPs), i.e. β-CN (f1-28) 4P (3489.1 Da) and β-CN (f33-48) 1P (2062.0 Da), were identified in the tryptic hydrolysate of native casein or curd and cheese samples using in-batch hydroxyapatite (HA) chromatography. All these fragments functioned as analytical surrogates of two αs1- and β-casein variants that specifically occur in the milk of international WB breeds. Furthermore, the bovine peptide β-CN (f1-28) 4P had a distinct and lower molecular mass compared with the WB counterpart and functioned as a species-specific marker for all breeds of WB. Advantages of this analytical approach are that (i) peptides are easier to separate than proteins, (ii) signature peptide probes originating from specific casein variants allow for the targeting of all international WB milk, curd and cheese samples and (iii) bovine and WB casein in mixtures can be simultaneously determined in protected designation of origin (PDO) "Mozzarella di Bufala Campana" cheese. This analytical method enabled the specific detection of international WB and bovine casein with a sensitivity threshold of 2 and 0.78 %, respectively. Graphical Abstract Monitoring of prototypic tryptic CPPs by MALDI-TOF analysis in Mediterranean (A), Romanian (B), Indian (C), Polish (D) and Canadian (E) curd samples to guarantee the authenticity of the PDO "Mozzarella di Bufala Campana" cheese.

There is a need to develop rapid tools to screen milk products for economically motivated adulteration. An understanding of the physiochemical variability within skim milk powder (SMP) and non-fat dry milk (NFDM) is the key to establishing the natural differences of these commodities prior to the development of non-targeted detection methods. This study explored the sources of variance in 71 commercial SMP and NFDM samples using Raman spectroscopy and principal component analysis (PCA) and characterised the largest number of commercial milk powders acquired from a broad number of international manufacturers. Spectral pre-processing using a gap-segment derivative transformation (gap size = 5, segment width = 9, fourth derivative) in combination with sample normalisation was necessary to reduce the fluorescence background of the milk powder samples. PC scores plots revealed no clear trends for various parameters, including day of analysis, powder type, supplier and processing temperatures, while the largest variance was due to irreproducibility in sample positioning. Significant chemical sources of variances were explained by using the spectral features in the PC loadings plots where four samples from the same manufacturer were determined to likely contain an additional component or lactose anomers, and one additional sample was identified as an outlier and likely containing an adulterant or differing quality components. The variance study discussed herein with this large, diverse set of milk powders holds promise for future use as a non-targeted screening method that could be applied to commercial milk powders.

The aim of this study was to identify the differences between the main macro and micronutrients including proteins, fat, minerals and vitamins in cow and goat dehydrated fermented milks. Fermented goat milk had higher protein and lower ash content. All amino acids (except for Ala), were higher in fermented goat milk than in fermented cow milk. Except for the values of C11:0, C13:0, C16:0, C18:0, C20:5, C22:5 and the total quantity of saturated and monounsaturated fatty acids, all the other fatty acid studied were significantly different in both fermented milks. Ca, Mg, Zn, Fe, Cu and Se were higher in fermented goat milk. Fermented goat milk had lower amounts of folic acid, vitamin E and C, and higher values of vitamin A, D3, B6 and B12. The current study demonstrates the better nutritional characteristics of fermented goat milk, suggesting a potential role of this dairy product as a high nutritional value food.

Milk produced by the grazing system, referred to as "grazing milk" contains many components required for human health. The milk fatty acid (FA) profile is strongly associated with the diet on the farms. In the present study, based on the FA profile of farmer's bulk milk, we determined how to discriminate between milk produced on grazing and on a confinement system. A field survey was conducted four times (grazing and confinement season) in the Konsen (29 farms) and Okhotsk (25 farms) area in Hokkaido. Farmer's bulk milk samples and details of feeding management were collected and the FA profile of milk was measured. Milk produced during the grazing season contained less C16:0 and cis-9 C16:0, and more C18:0, cis-9 C18:1, trans-11 C18:1, cis-9,12 C18:2, cis-9,trans-11 C18:2 and cis-9,12,15 C18:3 than milk produced during the confinement season. Discrimination analysis using 16 FA revealed that almost all milk samples were discriminated correctly (confinement season: 90% correct and 10% borderline, grazing season: 88% correct, 9% borderline and 3% incorrect). For farmers that were categorized incorrectly and were considered borderline in the grazing season, the dependency on pasture was low compared with that for farmers correctly discriminated. Therefore, to claim "grazing milk", a high dependency on pasture is required for grazing dairy farmers., (© 2015 Japanese Society of Animal Science.)

The aim of the study was to investigate the possibility to differentiate the 4 most important species in Italian dairy industry (cow, buffalo, sheep, and goat), applying a bottom-up proteomic approach to assess the milk species involved in cheese production. Selective peptides were detected in milk to use as markers in cheese products. Trypsin-digested milk samples of cow, sheep, goat, and buffalo, analyzed by HPLC-tandem mass spectrometry provided species-specific peptides, some of them recognized by Mascot software (Matrix Science Ltd., Boston, MA) as derived from well-known species specific proteins. A multianalyte multiple reaction monitoring method, built with these specific peptides, was successfully applied to cheeses with different composition, showing high specificity in detection of species involved. Neither aging nor production method seemed to affect the response, demonstrating that chosen peptides well act as species markers for dairy products., (Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Introduction: The US Department of Agriculture has stocking criteria for healthy foods among Supplemental Nutrition Assistant Program (SNAP)-authorized retailers. Increased access to healthy food could improve diet quality among SNAP participants, which has implications for chronic disease prevention. The objective of this study was to quantify healthy foods stocked in small-size to mid-size retailers who are authorized under SNAP but not under the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC)., Methods: We used formative, cross-sectional data from a large policy evaluation to conduct secondary analyses. Store audits were conducted in 2014 in 91 randomly selected, licensed food stores in Minneapolis and St. Paul, Minnesota. Supermarkets and retailers participating in WIC, which are required to stock healthy foods, were excluded as were other stores not reasonably expected to stock staple foods, such as specialty stores or produce stands. Availability of milk, fruits, vegetables, and whole-grain-rich foods was assessed., Results: The 91 stores studied were corner stores, food-gas marts, dollar stores, and pharmacies. More than half carried 1 or more varieties of fat-free or low-fat milk, fresh or canned fruit, and whole-grain-rich cereal. However, only one-third stocked 1 or more varieties of fresh vegetables and only one-quarter stocked whole-grain-rich products, such as whole-grain-rich bread (26%) or tortillas (21%) or brown rice (25%). Few stores stocked at least 2 varieties of each product., Conclusions: Many stores did not stock a variety of healthy foods. The US Department of Agriculture should change policies to improve minimum stocking requirements for SNAP-authorized retailers.

In this work, Coherence backscattering (CBS) of light has been used to detect the onset of denaturation of milk. The CBS cone shape and its enhancement factor are found to be highly sensitive to the physical state of the milk particles. The onset of denaturing of milk not visible to the naked eye, can be easily detected from changes in the CBS cone shape. The onset of denaturation is confirmed by spectral changes in Raman spectra from these milk samples. Further, the possibility to estimate the dilution of milk by water as an adulterant is demonstrated. The method reported has a broad scope in industry for making an inline ultrafast cost effective sensor for milk quality monitoring during production and before consumption.

Background: Cronobacter sakazakii is considered as an emerging foodborne pathogen. The aim of this study was to isolate and characterize virulent strains of Cronobacter sakazakii from food samples of Bangladesh., Result: Six (6) Cronobacter sakazakii was isolated and identified from 54 food samples on the basis of biochemical characteristics, sugar fermentation, SDS-PAGE of whole cell protein, plasmid profile and PCR of Cronobacter spp. specific genes (esak, gluA, zpx, ompA, ERIC, BOX-AIR) and sequencing. These strains were found to have moderately high antibiotic resistance against common antibiotics and some are ESBL producer. Most of the C. sakazakii isolates were capable of producing biofilm (strong biofilm producer), extracellular protease and siderophores, curli expression, haemolysin, haemagglutinin, mannose resistant haemagglutinin, had high cell surface hydrophobicity, significant resistance to human serum, can tolerate high concentration of salt, bile and DNase production. Most of them produced enterotoxins of different molecular weight. The isolates pose significant serological cross-reactivity with other gram negative pathogens such as serotypes of Salmonella spp., Shigella boydii, Shigella sonnei, Shigella flexneri and Vibrio cholerae. They had significant tolerance to high temperature, low pH, dryness and osmotic stress., Conclusion: Special attention should be given in ensuring hygiene in production and post-processing to prevent contamination of food with such stress-tolerant virulent Cronobacter sakazakii.

Purpose: This study's purpose was to assess the cariogenicity of commercial bovine milk types in an experimental biofilm/caries model., Methods: Enamel and dentin slabs were used to grow biofilms of Streptococcus mutans UA159. Slabs/biofilms were exposed three times per day to commercial skim, semi-skim, whole, whole lactose-free, and whole with 10 percent sucrose-added bovine milk and to 10 percent sucrose and 0.9 percent sodium chloride as positive and negative caries-control, respectively. Biofilms were analyzed for bacterial counts, biomass, proteins, and polysaccharide production. Slab's demineralization was assessed by loss of surface microhardness and the biofilm acidogenicity by medium pH., Results: Only whole and whole lactose-free milk kept pH above the demineralization threshold, inducing the lowest demineralization in both enamel and dentin (P<.05). Skim and semi-skim milk induced similar demineralization to the sucrose control, albeit slightly lower for semi-skim milk (P<.05). Whole and whole lactose-free milk produced lower biomass and less insoluble polysaccharides than the other treatments in enamel and dentin (P<.05). Adding 10 percent sucrose to whole milk turned it as cariogenic as 10 percent sucrose solution., Conclusion: Bovine whole milk seemed less cariogenic than sucrose and the other commercial milk types, but not anticariogenic. Fat content in milk seemed to reduce cariogenicity of the fluid.

The present investigation is focused on the use of a comprehensive two-dimensional GC (GC×GC) method, with dual mass spectrometry/flame ionization detection (MS/FID), for the qualitative and quantitative analysis of the unsaponifiable fraction of milk lipids (cow butter, buffalo, ewe, and goat milks). The structure of many constituents (particularly sterols) was confirmed by using GC-high resolution time-of-flight MS. The GC×GC column set used consisted of a low-polarity first dimension, and a medium-polarity secondary one, both characterized by a high thermal stability. The use of dual detection enabled the attainment of both mass spectral information and relative % FID data. The complexity of the fingerprint, generated by the unsaponifiable fraction, justified the employment of the two-dimensional GC technology. However, it was two other GC×GC characteristics that contributed most to the attainment of promising results, namely sensitivity enhancement and the formation of group-type patterns. Because many milk lipid constituents were not contained in the MS databases employed, exact mass information proved to be valuable for identification purposes., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Brand traceability of several different kinds of milk powder was studied by combining near infrared spectroscopy diffuse reflectance mode with soft independent modeling of class analogy (SIMCA) in the present paper. The near infrared spectrum of 138 samples, including 54 Guangming milk powder samples, 43 Netherlands samples, and 33 Nestle samples and 8 Yili samples, were collected. After pretreatment of full spectrum data variables in training set, principal component analysis was performed, and the contribution rate of the cumulative variance of the first three principal components was about 99.07%. Milk powder principal component regression model based on SIMCA was established, and used to classify the milk powder samples in prediction sets. The results showed that the recognition rate of Guangming milk powder, Netherlands milk powder and Nestle milk powder was 78%, 75% and 100%, the rejection rate was 100%, 87%, and 88%, respectively. Therefore, the near infrared spectroscopy combined with SIMCA model can classify milk powder with high accuracy, and is a promising identification method of milk powder variety.

A high prevalence of dental fluorosis has been identified among children in the Gaza Strip. This study aimed to determine the history of breastfeeding and dietary behaviours among children in the Gaza Strip and to examine potential associations with the prevalence and severity of dental fluorosis. A cross-sectional study recruited a stratified cluster random sample of 350 children aged 12-18 years and their mothers. Data about dietary behaviours in the first 7 years of life were collected by interview questionnaire. Dental fluorosis was determined using the Thyllstrup-Fejerskov index. A majority of children were breastfed exclusively in the first 6 months (82.9%) but 98.1% were given tea in the first year of life. The prevalence of dental fluorosis was 78.0%. Both intake of animal proteins and plant proteins were negatively associated with the prevalence and severity of dental fluorosis. Further studies to investigate fluoride intake is required to plan preventive interventions.

Product authenticity is an important topic in dairy sector. Dairy products sold for public consumption must be accurately labelled in accordance with the contained milk species. Linear discriminant analysis (LDA), a common chemometric procedure, has been applied to fatty acid% composition to classify pure milk samples (cow, ewe, buffalo, donkey, goat). All original grouped cases were correctly classified, while 90% of cross-validated grouped cases were correctly classified. Another objective of this research was the characterisation of cow-ewe milk mixtures in order to reveal a common fraud in dairy field, that is the addition of cow to ewe milk. Stereospecific analysis of triacylglycerols (TAG), a method based on chemical-enzymatic procedures coupled with chromatographic techniques, has been carried out to detect fraudulent milk additions, in particular 1, 3, 5% cow milk added to ewe milk. When only TAG composition data were used for the elaboration, 75% of original grouped cases were correctly classified, while totally correct classified samples were obtained when both total and intrapositional TAG data were used. Also the results of cross validation were better when TAG stereospecific analysis data were considered as LDA variables. In particular, 100% of cross-validated grouped cases were obtained when 5% cow milk mixtures were considered.

Donkey's milk (DM), representing a safe and alternative food in both IgE-mediated and non-IgE-mediated cow's milk protein allergy, can be categorized as precious pharma-food. Moreover, an economically relevant interest for the use of DM in cosmetology is also developing. The detection of adulterations and contaminations of DM is a matter of fundamental importance from both an economic and allergenic standpoint, and, to this aim, fast and efficient analytical approaches to assess the authenticity of this precious nutrient are desirable. Here, a rapid matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS)-based method aimed to the detection of bovine or caprine milk in raw DM is reported. The presence of the extraneous milks was revealed by monitoring the protein profiles of the most abundant whey proteins, α-lactalbumin (α-LA) and β-lactoglobulin, used as molecular markers. The possibility of obtaining a quantitative analysis of the level of cow or goat milk in DM based on the MALDI-TOF peak areas of α-LAs was also explored. The results showed that the experimental quantitative values were in good agreement with the real composition of each mixture. As pretreatment of the milk samples is not required, and owing to the speed and the high sensitivity of MALDI-MS, the protocol here reported could represent a reliable method for routine analyses aimed to assess the absence of contamination in raw fresh DM samples., (Copyright © 2013 John Wiley & Sons, Ltd.)

The combined use of the state-of-the-art hybrid mass spectrometers together with high efficient liquid chromatography could surely be a useful tool for such a challenging task, as phospholipids (PLs) analysis. In this research, we used hydrophilic interaction liquid chromatography (150 mm×2.1 mm I.D., 2.7 μm d.p. partially porous column) to achieve the separation of major PLs classes in cow's and donkey's milk samples. Solid-phase extraction (SPE) was performed in order to pre-concentrate minor PLs from non polar lipids (triacylglycerols) and the recovery for the extraction method was assayed on a milk sample, fortified with 5 μg/mL of SM pure standard, and analyzed in triplicate. A value of 89.99% was calculated, with a coefficient of variation (CV%) of 1.93. A 70-min long stepwise gradient of water/acetonitrile afforded baseline separation of PLs classes, at 50 μL/min flow rate. Accurate detection by an ion trap-time of flight (IT-TOF) mass spectrometer (in both positive and negative ionization mode) allowed to fully characterize the distinctive phospholipid profile and fatty acid composition of cow's and donkey's milk, the latter being analyzed for the first time. Evaporative light scattering detection was further employed to attain the quantitative evaluation of major PLs classes identified, by the external calibration method using reference material solutions in the 5-200 μg/mL concentration range. Major difference between the two analyzed samples consisted in the total PLs amount, which in cow's milk was determined as over 20-fold higher than the donkey's., (Copyright © 2011 Elsevier B.V. All rights reserved.)

The aim of the present study was to investigate the relationship between the metabolite profile of milk and important technological properties by using nuclear magnetic resonance (NMR)-based metabolomics. The metabolomics approach was introduced for the metabolic profiling of a set of milk samples from two dairy breeds representing a wide span in coagulation properties. The milk metabolite profiles obtained by proton and carbon NMR spectroscopy could be correlated to breed and, more interestingly, also with the coagulation profile, as established by traditional methods by using principal component analysis (PCA). The metabolites responsible for the separation into breed could mainly be ascribed to carnitine and lactose, whereas the metabolites varying in the samples with respect to coagulation properties included citrate, choline, carnitine, and lactose. The results found in the present study demonstrated a promising potential of NMR-based metabolomics for a rapid analysis and classification of milk samples, both of which are useful for the dairy industry.

Massese is an Italian sheep breed, with black or grey coat colour, mainly reared in the Tuscany and Emilia Romagna regions. Recently, the emerging interests in this breed have resulted in the production of Pecorino cheese obtained with only Massese milk. In order to be profitable, this marketing link between Massese breed and its products should be defended against fraudsters who could include milk of other sheep breeds or cow milk in Massese labelled productions. To identify the genetic factors affecting coat colour in sheep, we have recently analysed the melanocortin 1 receptor (MC1R) gene and identified several single nucleotide polymorphisms (SNPs). In this work, as a first step to set up a DNA based protocol for authentication of Massese dairy products, we further investigated the presence and distribution of one of these SNPs (c.-31G>A) in 143 Massese sheep and in another 13 sheep breeds (for a total of 351 animals). The Massese breed was fixed for allele c.-31A, whereas in all other breeds allele c.-31 G was the most frequent or with frequency of 0·50. At the same nucleotide position the cattle MC1R gene carries the G nucleotide. Using these data we developed a method to detect adulterating milk (from other sheep breeds or from cow) in Massese dairy products based on the analysis of the c.-31G>A SNP. We first tested the sensitivity of the protocol and then applied it to analyse DNA extracted from ricotta and Pecorino cheese obtained with only Massese milk or obtained with unrestricted sheep and cattle milk. To our knowledge, this system represents the first one that can be used for breed authentication of a sheep production and that, at the same time, can reveal frauds derived from the admixture of milk of an unreported species.

In 2006, New York City, the largest school district in the country, eliminated whole milk and reduced the availability of sweetened milk in 1,579 schools. Despite pressure from the American Dairy Council, skepticism from school food administrators and elected officials, and the difficulties inherent in changing a system that serves 120,000,000 containers of milk per year, a community-led coalition prevailed. This article describes how parents, educational leaders, advocates, and health professionals collaborated to educate school children and their families to choose low-fat milk, and created change at a system, policy, and environmental level to promote health in the community.

Despite an overall increase in the consumption of milk products, the consumption of plain processed milk in South Korea is decreasing. One of the major reasons for this phenomenon is that consumers in Korea find the taste of plain milk unpalatable. The principal objective of this study was to identify the internal and external drivers of liking for milk among Korean consumers. The results of descriptive analysis (Chung and others 2008) were correlated to the results of consumer taste tests to identify the sensory characteristics that positively and negatively affect consumers' liking of milk. Consumers' health and food-related attitudes were surveyed as well as their daily milk consumption patterns to investigate the effects of these attitudes and consumption patterns on the liking for various types of milk. Consumers' liking of milk samples was positively correlated with sweetness, sweet cream flavor, and smooth texture. Grassy odor, raw milk flavor, artificial milk flavor, and rancid flavor were the negative drivers of liking. Consumers who frequently drink plain processed milk, in particular, preferred the UHT-processed whole milk samples, whereas infrequent drinkers preferred lactose-free milk samples. Consumers with strong food neophobic tendency significantly rated lower than consumers with weak tendency for most of the liking categories and some of the attribute intensities. Finally, when the consumers were grouped based on their common preference for milk samples, plain processed milk consumption frequency was the major determinant affecting the preference for milk.

The nutritional distinctiveness of pasture-fed dairy products is mainly influenced by the transfer of specific chemical compounds from the grass to the milk and by their effect on rumen microflora and animal metabolism. Thus, the pasture-fed origin has to be objectively proven, using fast and reproducible analytical methods applied to finished products, in order to protect consumers against potential frauds. In this work, Electronic Nose patterns of Alpine milks produced by cows grazing Trifolium alpinum and Festuca nigrescens pasture types have been examined, in order to test the potential use of this device for routine control analyses of the botanical origin of milk and dairy products. The data have been treated with different multivariate analyses (MANOVA, LDA) and chemometrics (MPLS). The results allow a very good classification of the milks, according to the two treatments. Such results demonstrate that this device could be successfully applied to PDO dairy products food chain as a tool for the determination of their dietary origin.

The near infrared spectrum atlases of milk powders mingled with different adjuvant are the object for cluster analysis. Drawing assistance from the disparity in infrared fingerprint atlas that change according to the contents of chemical constituent, and making mingled component models, the milk powders mingled with different adjuvant were taken for a rapid sorting test using SIMCA clustering analytical method. In the experiment, two hundred fifty sorts of milk powders in the markets from different manufacturers were scanned by near infrared ray, and were tested with reproducibility determination. It was found difficult to extract fingerprint characters just from the external appearance of the near infrared spectrum atlases from milk powders mingled with different adjuvant, and it is needed to adopt pattern recognition technique to determine intelligently. One hundred sixty atlases were drawn out randomly for cluster analysis, and unknown samples were pretested. Results showed that the milk powders mingled with different adjuvant can be identified by near infrared spectrum analysis associated with cluster analysis methods, notwithstanding the similar near infrared spectrum atlases of different sample were difficult to identify directly. No overlapping phenomenon was found among milk powders mingled with different adjuvant, and they did not interfere with each other. The results from clustering spectra between samples were satisfactory, and the correct ratios of blind detections were over 90%. In addition, the correct ratios of this method may be elevated remarkably with sufficient number of samples, increasing training set sample quantity and sampling representation, and strengthening the standard degree of manipulation. It is concluded that the designed model to determine milk powders mingled with different adjuvant is rational, and the determination capability is fine.

The ability to detect mastitis pathogens based on their volatile metabolites was studied. Milk samples from cows with clinical mastitis, caused by Staphylococcus aureus, coagulase-negative staphylococci, Streptococcus uberis, Streptococcus dysgalactiae, and Escherichia coli were collected. In addition, samples from cows without clinical mastitis and with low somatic cell count (SCC) were collected for comparison. All mastitis samples were examined by using classical microbiological methods, followed by headspace analysis for volatile metabolites. Milk from culture-negative samples contained a lower number and amount of volatile components compared with cows with clinical mastitis. Because of variability between samples within a group, comparisons between pathogens were not sufficient for classification of the samples by univariate statistics. Therefore, an artificial neural network was trained to classify the pathogen in the milk samples based on the bacterial metabolites. The trained network differentiated milk from uninfected and infected quarters very well. When comparing pathogens, Staph. aureus produced a very different pattern of volatile metabolites compared with the other samples. Samples with coagulase-negative staphylococci and E. coli had enough dissimilarity with the other pathogens, making it possible to separate these 2 pathogens from each other and from the other samples. The 2 streptococcus species did not show significant differences between each other but could be identified as a different group from the other pathogens. Five groups can thus be identified based on the volatile bacterial metabolites: Staph. aureus, coagulase-negative staphylococci, streptococci (Strep. uberis and Strep. dysgalactiae as one group), E. coli, and uninfected quarters.

The aim of the present paper was to provide new insight into the short-wave near-infrared (NIR) spectroscopic analysis of milk powder. Near-infrared spectra in the 800- to 1,025-nm region of 350 samples were analyzed to determine the brands and quality of milk powders. Brand identification was done by a least squares support vector machine (LS-SVM) model coupled with fast fixed-point independent component analysis (ICA). The correct answer rate of the ICA-LS-SVM model reached as high as 98%, which was better than that of the LS-SVM (95%). Contents of fat, protein, and carbohydrate were determined by the LS-SVM and ICA-LS-SVM models. Both processes offered good determination performance for analyzing the main components in milk powder based on short-wave NIR spectra. The coefficients of determination for prediction and root mean square error of prediction of ICA-LS-SVM were 0.983, 0.231, and 0.982, and 0.161, 0.980, and 0.410, respectively, for the 3 components. However, there were less than 10 input variables in the ICA-LS-SVM model compared with 225 in the LS-SVM model. Thus, the processing time was much shorter and the model was simpler. The results presented in this paper demonstrate that the short-wave NIR region is promising for fast and reliable determination of the brand and main components in milk powder.

The 1% or Less Campaign is an effective research-tested program for reducing saturated fat intake by encouraging individuals to switch to low-fat milk. All published studies have been conducted in small communities with mostly White populations. The 6-week intervention included a media campaign, public relations, and taste tests. Campaign effectiveness was measured using sales data and cross-sectional telephone surveys. Survey results showed a significant increase in low-fat milk consumption from 30.2% to 40.8% of milk drinkers (p < .001) with a reduced yet sustained increase at 3 months. This translates to approximately 65,000 people switching to low-fat milk during the campaign with a sustained effect of approximately 32,000 people three months postcampaign. Sales data show an increase of low-fat milk sales from 32.7% to 39.9%. Results are similar to smaller community initiatives, indicating the program is effective in promoting population behavior change but may need booster sessions for sustained effects.

The first objective of the present paper was to assess the potential of both isotopic ( (18)O/ (16)O in milk water) and molecular biomarkers (terpenes, fatty acids, carotenoids, and vitamins) and milk color to discriminate the production zone (lowland or upland areas) from which 49 tanker bulk milks were collected over one year from a total of 204 farms. The milk water (18)O enrichment was higher in lowland (<500 m altitude) than in upland (>700 m altitude), but the delta (18)O values failed to discriminate systematically the production zone at the scale of the year because of its high variability related to the sampling period. In contrast with vitamins A and E, carotenoids, and milk color measurements, terpenes and fatty acids were confirmed to be relevant tracers of the production zone. The milk compounds with the strongest discriminative potential were fatty acids, which were determined by high-resolution gas chromatography. The calculation of fatty acid ratios, which permits the limitation of using fatty acid relative quantity expressed in percentage of total fatty acids to be overcome, was shown to be particularly relevant in discriminating upland from lowland milk ratios. The selection of two pairs of ratios, namely, iso-C17:0/C18:3 n-3 and iso-C15:0/iso-C14:0, enabled the authentication of 100% of the highland versus lowland milks whatever the season. The second objective was to evaluate the relevance of fatty acid composition to discriminate milks according to the proportion of corn silage in the diets of dairy cows. The selection of two fatty acids ratios, namely, trans11 cis15-C18:2/trans11-C18:1 and cis9-C16:1/iso-C16:0, enabled the correct classification of 100% of the milk samples according to the proportion of corn silage in the basic fodder rations (<25% vs >30%). The relationship between the milk production zone and the type of forage fed to the cows is discussed.