The effect of first-lactation calving season, milk production, and morphology on the survival of Simmental cows.

Longevity in dairy and dual-purpose cattle is a complex trait which depends on many individual and managerial factors. The purpose of the present study was to investigate the survival (SURV) rate of Italian Simmental dual-purpose cows across different parities. Data of this study referred to 2 173 primiparous cows under official milk recording that calved between 2002 and 2020. Only cows linearly classified for type traits, including muscularity (MU) and body condition score (BCS) were kept. Survival analysis was carried out, through the Cox regression model, for different pairwise combinations of classes of milk productivity MU, BCS, and calving season. Herd-year of first calving was also considered in the model. SURV (0 = culled; 1 = survived) at each lactation up to the 6th were the dependent variables, so that, for example, SURV2 equal to 1 was attributed to cows that entered the 2nd lactation. Survival rates were 98, 71, 63, 56, and 53% for 2nd, 3rd, 4th, 5th, and 6th lactation, respectively. Results revealed that SURV2 was not dependent on milk yield, while in subsequent parities, low-producing cows were characterized by higher SURV compared to high-producing ones. Additionally, cows starting the lactation in autumn survived less (47.38%) than those starting in spring (53.49%), suggesting that facing the late gestation phase in summer could increase the culling risk. The present study indicates that SURV in Italian Simmental cows is influenced by various factors in addition to milk productivity. However, it is important to consider that in this study all first-calving cows culled before the linear evaluation - carried out between mid- and late lactation in this breed - were not accounted for. Finding can be transferred to other dual-purpose breeds, where the cows' body conformation and muscle development - i.e. meat-related features - are often considered as important as milk performance by farmers undertaking culling decisions.

Characterization of microplastics in skim-milk powders.

The diffusion of microplastics in the food supply chain is prompting public concern as their impact on human health is still largely unknown. The aim of this study was to qualitatively and quantitatively characterize microplastics in skim-milk powder samples (n = 16) from different European countries (n = 8) through Fourier-transform infrared micro-spectroscopy in attenuated total reflectance mode analysis. The present study highlights that the use of hot alkaline digestion has enabled the efficacious identification of microplastics in skim-milk powders used for cheese-making across European countries. The adopted protocol allowed detection of 29 different types of polymeric matrices for a total of 536 plastic particles. The most abundant microplastics were polypropylene, polyethylene, polystyrene, and polyethylene terephthalate. Microplastics were found in skim-milk powders in 3 different shapes (fiber, sphere, and irregular fragments) and 6 different colors (black, blue, brown, fuchsia, green, and gray). Results demonstrate the presence of microplastics in all skim-milk powder samples, suggesting a general contamination. Results of the present study will help to evaluate the impact of microplastics intake on human health.

How animal milk and plant-based alternatives diverge in terms of fatty acid, amino acid, and mineral composition.

The decline in fresh milk in the Western world has in part been substituted by an increased consumption of plant-based beverages (PBB). These are often marketed as healthy and sustainable alternatives to milk and dairy foodstuff, although studies have suggested PBB to be of lower nutrient quality. The current study considered different brands of almond-, oat-, rice-, coconut- and soya-based beverages for a comparative analysis and found that they indeed presented lower contents of total protein, lipids, amino acids, and minerals than cow and goat milk. The only exception was given by soya-based beverages which approximated the protein content (3.47% vs. 3.42 and 3.25% in cow and goat milk, respectively) and amino acid composition of animal milk, and also demonstrated high mineral content. The natural presence of phyto-compounds in PBB characterised as antinutrients and their potential to exacerbate the issue of low nutrient quality by lowering bioavailability have been discussed.

Assessment of energy dispersive X-ray fluorescence (ED-XRF) for quantification of iodine in non-lyophilized milk.

Iodine represents a fundamental element for human health, with particular regard to thyroid function. Dietary intake of milk naturally rich in iodine becomes of primary importance in the prevention of syndromes related to iodine deficiency. The concentration of iodine in milk is characterized by wide variability, mainly related to animal feed and level of mineral supplementation. Therefore, there is interest in the development of fast analytical techniques which are able to predict milk iodine concentration. The aim of the present study was to investigate the effectiveness of energy-dispersive X-ray fluorescence (ED-XRF) for the prediction of iodine in cow milk. Results showed moderate accuracy of the ED-XRF technique, with a coefficient of determination in cross validation of 0.60. This study represents a first contribution towards the possibility to discriminate milk with high or low iodine concentration, as an essential preliminary step for the introduction into the market of naturally fortified milk.

Effectiveness of mid-infrared spectroscopy for the prediction of cow milk metabolites.

Proton nuclear magnetic resonance (1H NMR) spectroscopy is acknowledged as one of the most powerful analytical methods with cross-cutting applications in dairy foods. To date, the use of 1H NMR spectroscopy for the collection of milk metabolic profile is hindered by costly and time-consuming sample preparation and analysis. The present study aimed at evaluating the accuracy of mid-infrared spectroscopy (MIRS) as a rapid method for the prediction of cow milk metabolites determined through 1H NMR spectroscopy. Bulk milk (n = 72) and individual milk samples (n = 482) were analyzed through one-dimensional 1H NMR spectroscopy and MIRS. Nuclear magnetic resonance spectroscopy identified 35 milk metabolites, which were quantified in terms of relative abundance, and MIRS prediction models were developed on the same 35 milk metabolites, using partial least squares regression analysis. The best MIRS prediction models were developed for galactose-1-phosphate, glycerophosphocholine, orotate, choline, galactose, lecithin, glutamate, and lactose, with coefficient of determination in external validation from 0.58 to 0.85, and ratio of performance to deviation in external validation from 1.50 to 2.64. The remaining 27 metabolites were poorly predicted. This study represents a first attempt to predict milk metabolome. Further research is needed to specifically address whether developed prediction models may find practical application in the dairy sector, with particular regard to the screening of dairy cows' metabolic status, the quality control of dairy foods, and the identification of processed milk or incorrectly stored milk.

Invited review: Iodine level in dairy products-A feed-to-fork overview.

The theme of iodine in the dairy sector is of particular interest due to the involvement and the interconnection of several stakeholders along the dairy food chain. Iodine plays a fundamental role in animal nutrition and physiology, and in cattle it is an essential micronutrient during lactation and for fetal development and the calf's growth. Its correct use in food supplementation is crucial to guarantee the animal's recommended daily requirement to avoid excess intake and long-term toxicity. Milk iodine is fundamental for public health, being one of the major sources of iodine in Mediterranean and Western diets. Public authorities and the scientific community have made great efforts to address how and to what extent different drivers may affect milk iodine concentration. The scientific literature concurs that the amount of iodine administered through animal feed and mineral supplements is the most important factor affecting its concentration in milk of most common dairy species. Additionally, farming practices related to milking (e.g., use of iodized teat sanitizers), herd management (e.g., pasture vs. confinement), and other environmental factors (e.g., seasonality) have been identified as sources of variation of milk iodine concentration. Overall, the aim of this review is to provide a multilevel overview on the mechanisms that contribute to the iodine concentration of milk and dairy products.

Grazing affects metabolic pattern of individual cow milk.

Effective traceability tools able to characterize milk from pasture are important to safeguard low-input farming systems, niche dairy products, and local traditions. The aims of the present study were to investigate the ability of proton nuclear magnetic resonance (1H NMR) spectroscopy to discriminate between milk produced from cows before and after the beginning of the grazing season, and to assess the effects of grazing on milk metabolites. The research trial involved a single alpine holding with 72 lactating cows. Individual milks were repeatedly sampled from the same animals before (i.e., d -3 and -1) and after (i.e., d 2, 3, 7, 10, and 14) the onset of the grazing period. One-dimensional 1H NMR spectra of milk extracts were collected through a Bruker spectrometer. Random forest discriminant analysis was applied to 1H NMR spectra to predict the period of collection for each sample. Data concerning the relative abundance of milk metabolites were analyzed through a linear mixed model, which included the fixed effects of period of sampling, cow breed, stage of lactation, and parity, and the random effect of cow nested within breed. The random forest model exhibited great accuracy (93.1%) in discriminating between samples collected on d -3, -1, 2, and 3 and those collected on d 7, 10, and 14. Univariate analysis performed on the 40 detected metabolites highlighted that milk samples from pasture had lower levels of 14 compounds (with fumarate being the most depressed metabolite) and greater levels of 15 compounds (with methanol and hippurate being the most elevated metabolites). Results indicate that milk 1H NMR spectra are promising to identify milk produced in different conditions. Also, our study highlights that grazing is associated with significant changes of milk metabolic profile, suggesting the potential use of several metabolites as indicators of farm management.

Effects of preservative, storage time, and temperature of analysis on detailed milk protein composition determined by reversed-phase high-performance liquid chromatography.

Milk preservative and freezing are used as strategies to prevent microbial growth and milk degradation, especially when immediate analytical processing is not feasible. The effects of the addition of preservative and freezing procedures have been investigated mainly in relation to milk gross chemical composition predicted through mid-infrared spectroscopy. This study aimed to determine whether different preservatives (i.e., no preservative, hydrogen peroxide, Bronopol, and Azidiol), freezing times (i.e., 0, 7, and 30 d), and temperatures of analysis (i.e., 5 and 21°C) influence the composition of milk protein fractions determined through reversed-phase HPLC. Bulk milk samples for the analysis of protein profile were collected from 5 commercial dairy farms. Data were analyzed with a linear mixed model, which included type of preservative, time of storage, temperature of analysis, and the interaction between type of preservative and time of storage as fixed effects, with the farm and the residual as random effects. Samples with no preservative had the greatest amount of all protein fractions, whereas Bronopol-preserved milk had the lowest amount. Increasing storage time under freezing conditions had a nonlinear detrimental effect on milk protein fractions. The temperature of analysis significantly contributed to the variation of κ-casein, ß-casein, αS1-casein, ß-lactoglobulin, and α-lactalbumin fractions. The z-scores were calculated to evaluate the similarity between detailed protein profile of fresh milk without preservative analyzed at 5°C and detailed protein profile of milk treated according to the tested conditions. Overall results suggested a good agreement between different analytical conditions. Still, short storage time under freezing conditions is recommended to avoid degradation of milk protein fractions and consequent analytical underestimation.

Nuclear magnetic resonance spectroscopy to investigate the association between milk metabolites and udder quarter health status in dairy cows.

Nuclear magnetic resonance spectroscopy was applied to investigate the association between milk metabolome and udder quarter health status in dairy cows. Mammary gland health status was defined by combining information provided by traditional somatic cell count (SCC) and differential SCC (DSCC), which expresses the percentage of neutrophils and lymphocytes over total SCC. Quarter milk samples were collected in triplicate (d 1 to 3) from 10 Simmental cows, 5 defined as cases and 5 defined as controls according to SCC levels at d 0. A total of 120 samples were collected and analyzed for bacteriology, milk composition, SCC, DSCC, and milk metabolome. Bacteriological analysis revealed the presence of mostly coagulase-negative staphylococci in quarter milk samples of cows defined as cases. Nuclear magnetic resonance spectra of all quarter samples were first analyzed using the unsupervised multivariate approach principal component analysis, which revealed a specific metabolomic fingerprint of each cow. Then, the supervised cross-validated orthogonal projections to latent structures discriminant analysis unquestionably showed that each cow could be very well identified according to its milk metabolomic fingerprint (accuracy = 95.8%). The comparison of 12 different models, built on bucketed 1-dimensional NOESY spectra (noesygppr1d, Bruker BioSpin) using different SCC and DSCC thresholds, corroborated the assumption of improved udder health status classification ability by joining information provided by both SCC and DSCC. Univariate analysis performed on the 34 quantitated metabolites revealed lower levels of riboflavin, galactose, galactose-1-phosphate, dimethylsulfone, carnitine, hippurate, orotate, lecithin, succinate, glucose, and lactose, and greater levels of lactate, phenylalanine, choline, acetate, O-acetylcarnitine, 2-oxoglutarate, and valine, in milk samples with high somatic cells. In the 5 cases, results of the udder quarter with the highest SCC compared with its symmetrical relative were in line with quarter-level findings. Our study suggests that increased SCC is associated with changes in milk metabolite fingerprint and highlights the potential use of different metabolites as novel indicators of udder health status and milk quality.

Short communication: Iodine content in bovine milk is lowly heritable and shows limited genetic variation.

Milk and dairy products are considered important sources of iodine in several countries. Despite this, there is a paucity of studies that have investigated sources of variation of milk iodine, especially on a large scale. So far, it is not clear if milk iodine content could be increased through breeding in dairy cattle. Recently, a mid-infrared spectroscopy prediction model has been developed for an indirect quantification of iodine content in cow milk, as it is a faster and less expensive method that allows the prediction at population level. The model has coefficient of determination and ratio of performance to deviation in external validation of 0.57 and 1.44, respectively, and it was used in the present study to predict the iodine content from historical milk spectral data to investigate phenotypic and genetic aspects in the Italian Holstein cattle. Based on the accuracy of the model, the prediction was interpreted as proxy for the real milk iodine concentration (IODP). The data set comprised 33,776 test-day records with IODP from 4,072 cows. Data of IODP were transformed through natural logarithm to achieve a normal distribution. The effect of parity, lactation stage, and month of sampling were investigated, and genetic parameters were estimated using a test-day repeatability animal model. Milk IODP decreased with parities and was the lowest in early lactation. Heritability of IODP was low (0.025) and it was positively genetically correlated with milk yield and negatively with fat content. Results suggested that it would be challenging to directly improve this trait through breeding strategies in dairy cattle, because IODP is mainly affected by temporary environmental factors and thus, cannot be easily improved through genetics. Although preliminary, findings of this study suggest that it would be more convenient to develop feeding and management strategies to drive milk iodine level than to put efforts and resources into breeding strategies. Further studies should validate IODP as an indicator trait of milk iodine content by improving reference data and estimating genetic correlation between predicted and measured values.

Mineral equilibrium in commercial curd and predictive ability of near-infrared spectroscopy.

Curd samples (n = 83) from 3 European dairy companies were analyzed for micellar and soluble mineral fractions content using inductively coupled plasma optical emission spectrometry as a gold standard method. The same curd samples were analyzed through 3 different near-infrared (NIR) instruments, and NIR spectra were merged with reference data. Prediction equations were developed using modified partial least squares analysis, and the accuracy of prediction was evaluated through leave-one-out cross validation. Overall, NIR spectroscopy was capable of predicting micellar and soluble mineral fractions in curd, but with differences among instruments. Fitting statistics showed that the visible NIR instrument in reflectance mode outperformed the NIR instrument in transmittance mode as well as the portable NIR instrument in reflectance mode. Prediction accuracies for most of the analyzed mineral fractions can be used for curd quality control in dairy companies and to aid in decision-making during the cheesemaking process.

Technical note: Repeatability and reproducibility of curd yield and composition in a miniaturized coagulation model.

Miniaturized coagulation (MC) models have been proposed for the evaluation of curd yield (CY) in individual milk samples of different dairy species and breeds, and for the analysis of cheese microstructure and texture. It is still unclear if MC using less than 50 mL of milk is suitable to evaluate CY and chemical composition, and if preservative added to raw milk may interfere with MC process. Therefore, this study aimed at evaluating repeatability and reproducibility of CY, curd moisture, and fat and protein content on curd dry matter (DM) from MC trials using 40 g of milk. Miniaturized coagulations were performed by 3 different operators on 3 consecutive days, using raw milk (RM) and raw milk added with preservative (RMP). Repeatability of CY, calculated as relative standard deviation on 6 miniaturized curds obtained within a day by the same operator, was below 5% for MC carried out with both RM and RMP. The Horwitz ratio, which is the ratio between measured and expected reproducibility, highlighted good reproducibility for CY from RM and fair reproducibility for CY from RMP. The same ratio highlighted lower accuracies for curd moisture and fat and protein content on curd DM, especially for MC trials carried out with RMP. The z-test was performed to evaluate the similarity between curds manufactured with RM and RMP in terms of average yield and chemical composition; z-scores did not highlight significant differences between values obtained from MC carried out with RM and RMP. It can be concluded that preservative had negligible effects on MC, giving the opportunity to extend milk physical and chemical stability, to schedule laboratory trials on longer time span, and to broaden the sample size within a batch of analyses.

Using modified fish scale waste from Sardinella brasiliensis as a low-cost adsorbent to remove dyes from textile effluents.

Textile industry wastewater has become a cause of concern to environmentalists due to its toxic composition and the difficulty of breaking down certain dyes. In this study, modified fish scales of Sardinella brasiliensis (SSb) were used as an alternative for a low-cost adsorbent to remove dyes from textile wastewaters. Adsorption efficiency was assessed by measuring the general, kinetic, and thermodynamic physico-chemical parameters of adsorption isotherms, using Reactive Turquoise Blue 15 (RTB15) and Reactive Red 120 (RR120) dyes as adsorbate models, as local textile industries commonly use these dyes. The isothermal data from the batch experiments were inserted in the Langmuir, Freundlich, and Langmuir-Freundlich (SIPS) equations; the Langmuir isotherm equation showed the most appropriate. The thermodynamic parameters showed that adsorption of dyes by the modified SSb adsorbent was an endothermic yet spontaneous process in the case of RR120. Sorbent-based on SSb material was concluded as adsorbing both of the tested dyes. Because of its abundant availability, and the small amount of activation needed to turn it into an adsorbent, this biowaste can be employed as a low-cost alternative for removal of dyes in the treatment of textile wastewater.

Validation of a gold standard method for iodine quantification in raw and processed milk, and its variation in different dairy species.

Adequate milk consumption significantly contributes to meeting the human iodine recommended daily intake, which ranges from 70 µg/d for infants to 200 µg/d for lactating women. The fulfilment of iodine recommended daily intake is fundamental to prevent serious clinical diseases such as cretinism in infants and goiter in adults. In the present study iodine content was measured in raw and processed commercial cow milk, as well as in raw buffalo, goat, sheep, and donkey milk. Iodine extraction was based on 0.6% (vol/vol) ammonia, whereas iodine detection and quantification were carried out through an inductively coupled plasma mass spectrometer analyzer. Among processed commercial cow milk, partially skimmed pasteurized milk had the greatest iodine content (359.42 µg/kg) and raw milk the lowest (166.92 µg/kg). With regard to the other dairy species, the greatest iodine content was found in raw goat milk (575.42 µg/kg), followed by raw buffalo (229.82 µg/kg), sheep (192.64 µg/kg), and donkey milk (7.06 µg/kg). Repeatability of milk iodine content, calculated as relative standard deviation of 5 measurements within a day or operator, ranged from 0.96 to 1.84% and 0.72 to 1.16%, respectively. The overall reproducibility of milk iodine content, calculated as relative standard deviation of 45 measurements across 3 d of analyses and 3 operators, was 4.01%. These results underline the precision of the proposed analytical method for the determination of iodine content in milk.

Genetic (co)variances between milk mineral concentration and chemical composition in lactating Holstein-Friesian dairy cows.

Milk mineral concentration is important from both the perspective of processing milk into dairy products and its nutritive value for human consumption. Precise estimates of genetic parameters for milk mineral concentration are lacking because of the considerable resources required to collect vast phenotypes quantities. The milk concentration of calcium (Ca), potassium (K), magnesium (Mg), sodium (Na) and phosphorus (P) in the present study was quantified from mid-IR spectroscopy on 12 223 test-day records from 1717 Holstein-Friesian cows. (Co)variance components were estimated using random regressions to model both the additive genetic and within-lactation permanent environmental variances of each trait. The coefficient of genetic variation averaged across days-in-milk (DIM) was 6.93%, 3.46%, 6.55%, 5.20% and 6.68% for Ca, K, Mg, Na and P concentration, respectively; heritability estimates varied across lactation from 0.31±0.05 (5 DIM) to 0.67±0.04 (181 DIM) for Ca, from 0.18±0.03 (60 DIM) to 0.24±0.05 (305 DIM) for K, from 0.08±0.03 (15 DIM) to 0.37±0.03 (223 DIM) for Mg, from 0.16±0.03 (30 DIM) to 0.37±0.04 (305 DIM) for Na and from 0.21±0.04 (12 DIM) to 0.57±0.04 (211 DIM) for P. Genetic correlations within the same trait across different DIM were almost unity between adjacent DIM but weakened as the time interval between pairwise compared DIM lengthened; genetic correlations were weaker than 0.80 only when comparing both peripheries of the lactation. The analysis of the geometry of the additive genetic covariance matrix revealed that almost 90% of the additive genetic variation was accounted by the intercept term of the covariance functions for each trait. Milk protein concentration and mineral concentration were, in general, positively genetically correlated with each other across DIM, whereas milk fat concentration was positively genetically correlated throughout the entire lactation with Ca, K and Mg; the genetic correlation with fat concentration changed from negative to positive with Na and P at 243 DIM and 50 DIM, respectively. Genetic correlations between somatic cell score and Na ranged from 0.38±0.21 (5 DIM) to 0.79±0.18 (305 DIM). Exploitable genetic variation existed for all milk minerals, although many national breeding objectives are probably contributing to an indirect positive response to selection in milk mineral concentration.

Technical note: Development and validation of an HPLC method for the quantification of tocopherols in different types of commercial cow milk.

In the present study, a methanol-fluorescence-based HPLC method was validated for its use to quantify α-tocopherol and γ-tocopherol in raw milk, whole UHT milk, partially skimmed UHT milk, whole pasteurized milk, and partially skimmed pasteurized milk. Repeatability and reproducibility, calculated as relative standard deviation of 10 measurements within the same day and 30 measurements across 3 d, respectively, were always below 5% for both tocopherols concentrations and retention times. Recovery was assessed through 3 spiking levels and it ranged from 89 to 107%. The method was able to detect the expected declines in tocopherols in milk exposed to UHT or skimming treatments. Vitamin E, calculated as the sum of α-tocopherol and γ-tocopherol, was similar in whole pasteurized and raw milk, averaging 1.57 and 1.56 mg/L, respectively, followed by whole UHT (1.33 mg/L), partially skimmed pasteurized (0.77 mg/L), and partially skimmed UHT milk (0.61 mg/L).

Short communication: Phenotypic characterization of total antioxidant activity of buffalo, goat, and sheep milk.

Free radicals are reactive and unstable waste molecules produced by cells, responsible of damages and alteration on DNA, proteins, and fat. The daily intake of antioxidant compounds, acting against free radicals and their detrimental effects, is essential for human health. Milk contains several compounds with antioxidant activity, and the sum of their reducing potential blocking free radicals development is defined as total antioxidant activity (TAA). This novel trait has been described in literature both in individual and bulk cow milk, but there are no reports from other dairy species. Therefore, the present study aimed to investigate phenotypic variation of TAA in individual samples of buffalo (n = 105), goat (n = 112), and sheep (n = 198) milk. Total antioxidant activity was measured through a reference spectrophotometric method, and expressed as millimoles per liter of Trolox equivalents (TE). The greatest TAA was observed in sheep milk, averaging 7.78 mmol/L of TE and showing also the broadest phenotypic variation expressed as coefficient of variation (13.98%). Significantly lower TAA values were observed for buffalo (7.35 mmol/L of TE) and goat (6.80 mmol/L of TE) milk, with coefficients of variation of 8.18 and 8.47%, respectively. Total antioxidant activity exhibited weak correlations with milk yield and chemical composition. Phenotypic values of TAA presented in this study will be used to assess the ability of mid-infrared spectroscopy to predict this new trait and thus to collect data at the population level.

Technical note: Development and validation of a new method for the quantification of soluble and micellar calcium, magnesium, and potassium in milk.

Milk mineral content is a key trait for its role in dairy processes such as cheese-making, its use as source of minerals for newborns, and for all traits involving salt-protein interactions. This study investigated a new method for measuring mineral partition between soluble and micellar fractions in bovine milk after rennet coagulation. A new whey dilution step was added to correct the quantification bias due to whey trapped in curd and excluded volume. Moreover, the proposed method allowed the quantification of the diffusible volume after milk coagulation. Milk mineral content and concentration in whey, and diluted whey were quantified by acid digestion and inductively coupled plasma optical emission spectrometry. The repeatability of the method for micellar Ca, Mg, and K was between 2.07 and 8.96%, whereas reproducibility ranged from 4.01 to 9.44%. Recovery of total milk minerals over 3 spiking levels ranged from 92 to 97%. The proposed method provided an accurate estimation of micellar and soluble minerals in milk, and curd diffusible volume.

Development and validation of a near infrared spectrophotometric method to determine total antioxidant activity of milk.

In the present study a spectrophotometric method for the determination of total antioxidant activity (TAA) based on ABTS assay was developed and validated on raw milk (RM), whole UHT milk (WUM), partially skimmed UHT milk (SUM), whole pasteurised milk (WM) and partially skimmed pasteurised milk (SM). The most suitable solvent for antioxidant extraction was 80% acetone. Regardless of the type of milk, the coefficient of determination from the linearity test was greater than 0.95. The limit of detection ranged from 0.74 to 6.07µmoll-1 Trolox equivalents. Repeatability, calculated as relative standard deviation of twenty measurements within a day, and reproducibility, calculated as relative standard deviation of sixty measurements across three days, ranged from 1.24 to 4.04% and from 2.18 to 3.52%, respectively. Preservative added to RM had negligible effects on the TAA of milk. The greatest TAA was measured for SM followed by SUM, RM, WM and WUM.