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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 microspectroscopy 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 cheesemaking 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., (© 2024, The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

A short-term study was conducted to compare the effect of using poplar wood chips (PWC) instead of wheat straw (WS) litter in dairy cows. A total of 38 lactating Holstein cows (204 ± 119 days in milk, 26.9 ± 6.5 kg of milk yield [MY]) were housed in a tiestall farm for a 10-d trial including 5 d of adaptation followed by 5 sampling days (from d 5 to 10). Cows were divided into 2 homogeneous groups: one group was bedded with WS, and the second with PWC. Both litter materials were provided in the amount of 7 kg/stall per d. Each group was composed of 3 subgroups of 6 or 7 cows; the subgroups were physically separated along the feeding line by wooden boards. During the sampling days, fecal composition, used litter composition, and bacterial count (Clostridium spp., Salmonella spp., Escherichia coli, Lactobacillus, and total bacterial count) were analyzed by subgroup twice a day. On d 1 and from d 5 to 10, udder hygiene score and cow cleanliness score were also evaluated individually twice a day. Meanwhile MY, milk hygiene (total bacterial count [TBC], coliform bacterial count [CBC], and spore-forming units [SFU]) and quality were measured and analyzed from 9 animals per group. Moreover, individual animal behavior (body position and behavioral traits) and subgroup dry matter intake were measured on d 9 and 10. Fecal dry matter did not differ between groups, PWC had the lowest used litter moisture and N content favoring the highest clean cow frequency, but also gave rise to the greatest used litter microbial contamination. The MY, milk quality, TBC, SFU, and CBC were similar. The lying behavior frequency was similar between groups. However, the PWC group showed the lowest sleeping frequency, the highest frequency of other behaviors (including discomfort signs), and the lowest dry matter intake. However, despite this apparent reduction in cow comfort, no biologically important differences were observed in this short-term study between cows on PWC and WS in milk production or hygiene., (© 2023, The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Several studies have reported gross composition differences between organic and conventional milk; however, most studies have not considered other factors such as breed and diet ingredients, which are known to influence milk composition. Thus, this study aimed to provide a detailed characterization of Holstein-Friesian cow milk from organic (ORG) and conventional (CONV) herds with similar diet ingredients and in the same geographic area. Bulk milk samples (n = 225) of 12 ORG and 12 CONV farms were collected from September 2019 to August 2020. Farms were located in Northern Italy, included corn (meal, silage, or both) in the lactating diets, and had similar management conditions, but ORG herds spent a period on pasture. Factors affecting milk composition were tested using a linear mixed model, which included calendar month, farming system (ORG and CONV), and their interactions as fixed effects, and farm nested within farming system as random effect. Results showed that total fat, lactose, vitamin E, and AA did not significantly differ between farming systems. Total protein and casein contents were significantly lower in ORG than CONV herds, and somatic cell score (SCS) was greater in ORG than CONV. Among minerals, differences were observed for Fe, K, Mg, and S in some months, being lower in ORG than CONV for K, Mg, and S and greater or lower for Fe depending on the month. Among fatty acid (FA) groups, index, and ratios, only polyunsaturated FA and n-3 FA tended to be greater in ORG than CONV, and cis-FA were greater in ORG than CONV during October. Among the most abundant individual FA, only C16:1n-9 differed, being lower in ORG than CONV. The calendar month (and hence seasonal feed ration) was significant for milk gross composition, SCS, vitamin E, mineral profile (except for Mo, Sr, and Zn), AA profile, FA groups (except for medium-chain FA), FA index and ratios, and individual FA (except C16:0). We conclude that the overall milk composition was quite similar between the 2 farming systems. This could be related to the similarity of the selected farms, the Holstein-Friesian breed, and generally high level of intensity in both farming systems., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Given consumer interest in Mozzarella di latte di Bufala and other cheeses, and the growing interest of the cheese industry in offering products adequate for lactovegetarian consumers, this study aimed to compare clotting capacity of vegetal and animal rennet in buffalo milk. Milk coagulation properties of 1,261 buffalo bulk milk samples collected during milk quality testing were assessed by lactodynamography using commercial animal (75% chymosin and 25% bovine pepsin) and vegetal (Cynara cardunculus) rennets. Chemical composition of milk samples was predicted by MilkoScan (Foss Analytics, Hillerød, Denmark) calibrated with specific buffalo standards. Rennet effect (animal versus vegetal) was statistically analyzed with a paired t-test. Fat, protein, and lactose contents of milk samples were 7.94%, 4.52%, and 4.80%, respectively. A similar variability of milk coagulation properties was observed with both rennets, with the exception of greater variability of curd firmness at 30 min after the addition of vegetal rennet compared with animal rennet (73 and 26%, respectively). On average, when using plant rennet, milk started to coagulate and reached the 20-mm coagulum 12 ± 0.22 min and 1.9 ± 0.20 min, respectively, later than with animal rennet. Thirty minutes after rennet addition, curds were almost twice as firm in animal as in vegetal rennet (difference of 23.92 ± 0.66 mm). However, curd firmness at 60 min was only 1.21 ± 0.39 mm thicker with vegetal than with animal rennet. Moreover, when using animal rennet, 99.52% of samples started coagulating within the first 30 min of analysis, whereas only 70.42% did so when using vegetal rennet. We conclude that vegetal rennet has the capacity to coagulate buffalo milk, achieving a similar curd firmness to that of animal rennet at 60 min. Further studies are needed to evaluate the sensory characteristics and consumer acceptability of Mozzarella di latte di Bufala processed with vegetal rennet., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

High milk somatic cell count (SCC) influences milk production and quality; however, very little is known about the effect of low SCC on milk quality, especially in terms of mineral content and coagulation properties. Thus, the present study aimed to investigate the effects of somatic cell score (SCS), calculated as log 2 (SCC/100) + 3, on milk yield, composition (fat, crude protein, casein, lactose, milk urea nitrogen, protein fractions, and mineral contents), and coagulation properties of Brown Swiss, Holstein Friesian, and Simmental cows from multibreed herds. Milk composition and coagulation traits were predicted using mid-infrared spectroscopy. The data set comprised 95,591 observations of 6,940 cows in 313 multibreed herds, collected from January 2011 to December 2017. Observations were divided into 8 classes based on SCS. Statistical analysis was performed using a linear mixed model, which included breed, parity, stage of lactation, SCS class, and their interactions as fixed effects, and herd test day, cow, and residual as random effects. The probability that cows experienced SCS > 4.00 at 30 ± 5, 60 ± 5, or 90 ± 5 d after the observation test day was calculated for each SCS class, and odds ratios to the reference class (-1.00 < SCS ≤ 0.00) were reported. Results showed that the relationship between SCS and milk traits followed a third-order polynomial regression. The average loss of milk, fat, and crude protein yields were 0.43, 0.01, and 0.01 kg/d, respectively, for each SCS unit higher than 1.00. Very low SCS (<-1.00) had detrimental effects on milk yield and quality traits similar to or even stronger than high SCS (>4.00). Moreover, cows with SCS lower than -1.00 on a test day were about 7 times more likely to present high SCS within the following 90 ± 5 d than cows with SCS between -1.00 and 0.00. Breeds responded similarly to the increase of SCS, but the overall loss of fat and crude protein yields, and several minerals among Holstein Friesian were lower with increasing SCS. The best milk yield and quality were observed between SCS 0.00 and 1.00, but milk quality of Holstein Friesians started to decrease at lower SCS compared with milk quality of Brown Swiss and Simmental cows. Results suggest a breed-dependent optimum of SCS, and highlighted that very low SCS can be an indicator of udder health problems and, thus, may be used for early detection of mastitis., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Hyperketonemia (HYK) is one of the most frequent and costly metabolic disorders in high-producing dairy cows and its diagnosis is based on β-hydroxybutyrate (BHB) concentration in blood. In the last 10 years, the number of papers that have dealt with the impact of elevated BHB levels in dairy cattle has increased. Therefore, this paper reviewed the recent literature on BHB concentration in blood and milk, and its relationships with dairy cow health and performance, and farm profitability. Most studies applied the threshold of 1.2 mmol/l of BHB concentration in blood to indicate HYK; several authors considered BHB concentrations between 1.2 and 2.9 mmol/l as subclinical ketosis, and values ⩾3.0 mmol/l as clinical ketosis. Results on HYK frequency (prevalence and incidence) and cow performance varied according to parity and days in milk, being greater in multiparous than in primiparous cows, and in the first 2 weeks of lactation than in later stages. Hyperketonemia has been associated with greater milk fat content, fat-to-protein ratio and energy-corrected milk, and lower protein and urea nitrogen in milk. The relationships with milk yield and somatic cell count are still controversial. In general, HYK impairs health of dairy cows by increasing the risk of the onset of other early lactation diseases, and it negatively affects reproductive performance. The economic cost of HYK is mainly due to impaired reproductive performance and milk loss. From a genetic point of view, results from the literature suggested the feasibility of selecting cows with low susceptibility to HYK. The present review highlights that milk is the most promising matrix to identify HYK, because it is easy to sample and allows a complete screening of the herd through BHB concentration predicted using mid-IR spectroscopy during routine milk recording. Further research is needed to validate accurate and convenient methods to discriminate between cows in risk of HYK and healthy animals in field conditions and to support farmers to achieve an early detection and minimise the economic losses.

Sheep milk is mainly transformed into cheese; thus, the dairy industry seeks more rapid and cost-effective methods of analysis to determine milk coagulation and acidity traits. This study aimed to assess the feasibility of Fourier-transform mid-infrared spectroscopy to determine milk coagulation and acidity traits of sheep bulk milk and to classify milk samples according to their renneting capacity. A total of 465 bulk milk samples collected in 140 single-breed flocks of Comisana (84 samples, 24 flocks) and Sarda (381 samples, 116 flocks) breeds located in Central Italy were analyzed for coagulation properties (rennet coagulation time, curd firming time, and curd firmness) and acidity traits (pH and titratable acidity) using standard laboratory procedures. Fourier-transform mid-infrared spectroscopy prediction models for these traits were built using partial least squares regression analysis and were externally validated by randomly dividing the full data set into a calibration set (75%) and a validation set (25%). The discriminant capacity of the rennet coagulation time prediction model was determined using partial least squares discriminant analysis. Prediction models were more accurate for acidity traits than for milk coagulation properties, and the ratio of prediction to deviation ranged from 1.01 (curd firmness) to 2.14 (pH). Moreover, the discriminant analysis led to an overall accuracy of 74 and 66% for the calibration and validation sets, respectively, with greater sensitivity for samples that coagulated between 10 and 20 min and greater specificity to detect early-coagulating (<10 min) and late-coagulating (20-30 min) samples. Results suggest that Fourier-transform mid-infrared spectroscopy has the potential to help the dairy sheep industry identify milk with better coagulation ability for cheese production and thus improve milk transformation efficiency. However, further research is needed before this information can be exploited at the industry level., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The aim of the present study was to investigate sources of variation of milk composition and technological characteristics routinely collected in field conditions in the Italian dairy industry. A total of 40,896 bulk milk records from 620 herds and 10 regions across Italy were analyzed. Composition traits were fat, protein, and casein percentages, urea content, and somatic cell score; and technological characteristics were rennet coagulation time, curd firming time, curd firmness 30 min after rennet addition to milk, and titratable acidity. Data of herd bulk milks were analyzed using a model that included fixed effects of region, herd nested within region, and season of milk analysis. An average good milk quality was reported in the dairy industry (especially concerning fat, protein, and casein percentages), and moderate to high correlations between composition and technological traits were observed. All factors included in the statistical model were significant in explaining the variation of the studied traits except for region effect in the analysis of casein and somatic cell score. Northeast and central-southern Italian regions showed the best performance for composition and technological features, respectively. Traits varied greatly across regions, which could reflect differences in herd management and strategies. Overall, less suitable milk for dairy processing was observed in summer. Results of the present study suggested that a constant monitoring of technological traits in the dairy industry is necessary to improve production quality at herd level and it may be a way to segregate milk according to its processing characteristics., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Milk coagulation and acidity traits are important factors to inform the cheesemaking process. Those traits have been deeply studied in bovine milk, whereas scarce information is available for buffalo milk. However, the dairy industry is interested in a method to determine milk coagulation and acidity features quickly and in a cost-effective manner, which could be provided by Fourier-transform mid-infrared (FT-MIR) spectroscopy. The aim of this study was to evaluate the potential of FT-MIR to predict coagulation and acidity traits of Mediterranean buffalo milk. A total of 654 records from 36 herds located in central Italy with information on milk yield, somatic cell score, milk chemical composition, milk acidity [pH, titratable acidity (TA)], and milk coagulation properties (rennet coagulation time, curd firming time, and curd firmness) were available for statistical analysis. Reference measures of milk acidity and coagulation properties were matched with milk spectral information, and FT-MIR prediction models were built using partial least squares regression. The data set was divided into a calibration set (75%) and a validation set (25%). The capacity of FT-MIR spectroscopy to correctly classify milk samples based on their renneting ability was evaluated by a canonical discriminant analysis. Average values for milk coagulation traits were 13.32 min, 3.24 min, and 39.27 mm for rennet coagulation time, curd firming time, and curd firmness, respectively. Milk acidity traits averaged 6.66 (pH) and 7.22 Soxhlet-Henkel degrees/100 mL (TA). All milk coagulation and acidity traits, except for pH, had high variability (17 to 46%). Prediction models of coagulation traits were moderately to scarcely accurate, whereas the coefficients of determination of external validation were 0.76 and 0.66 for pH and TA, respectively. Canonical discriminant analysis indicated that information on milk coagulating ability is present in the MIR spectra, and the model correctly classified as noncoagulating the 91.57 and 67.86% of milk samples in the calibration and validation sets, respectively. In conclusion, our results can be relevant to the dairy industry to classify buffalo milk samples before processing., (Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)