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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. [ABSTRACT FROM AUTHOR]

The aim of the study was to evaluate the feasibility of near infrared (NIR) transmittance spectroscopy to predict cheese ripeness using the ratio of water-soluble nitrogen (WSN) to total nitrogen (TN) as an index of cheese maturity (WSN/TN). Fifty-two Protected Designation of Origin cow milk cheeses of 5 varieties (Asiago, Grana Padano, Montasio, Parmigiano Reggiano, and Piave) and different ripening times were available for laboratory and chemometric analyses. Reference measures of WSN and TN were matched with cheese spectral information obtained from ground samples by a NIR instrument that operated in transmittance mode for wavelengths from 850 to 1,050 nm. Prediction equations for WSN and TN were developed using (1) cross-validation on the whole data set and (2) external validation on a subset of the entire data. The WSN/TN was calculated as ratio of predicted WSN to predicted TN in cross-validation. The coefficients of determination for WSN and TN were >0.85 both in cross- and external validation. The high accuracy of the prediction equations for WSN and TN could facilitate implementation of NIR transmittance spectroscopy in the dairy industry to objectively, rapidly, and accurately monitor the ripeness of cheese through WSN/TN. [ABSTRACT FROM AUTHOR]

Conditioned taste aversion (CTA) is a useful tool to modify animal feed preferences, allowing the implementation of selective grazing to control weeds in tree orchards without damaging the trees or affecting fruit production. LiCl is commonly used for inducing CTA. However, studies investigating the long-term persistence of CTA by LiCl in small ruminants are scarce. With this aim, we evaluated the efficiency of two LiCl doses (AV1 and AV2, 175 and 200 mg/kg BW, respectively) and a control (C, 0 mg/kg BW) for averting non-lactating dairy goats (n=15) to olive tree leaves. Aversion induction was reinforced on day 9 in those goats that consumed >10 g of olive leaves. Mid-term aversion effectiveness was assessed by five double-choice feeding tests (days 16, 24, 31, 38 and 53) of 30 min each, where 100 g of olive leaves were offered side-by-side with 390 g of Italian rye-grass (as-fed). Long-term aversion effectiveness was assessed in C, AV1 and AV2 goats by grazing for 30 min in paddocks with a simulated olive tree (days 59, 90, 121, 182 and 420). Moreover, C and AV2 goats were compared under on-field conditions (days 143, 211 and 363) in a commercial olive grove also for 30 min. The CTA proved to be established with a single LiCl dose in all goats and persisted for 4 and 55 days in AV1 and AV2 goats, respectively (P<0.001). However, 80% AV1 and 20% AV2 goats needed to be reinforced at day 9. When grazing under simulated olive tree and commercial olive grove conditions, the CTA goats, especially AV2 group, avoided the contact with the olive trees and minimally used a bipedal stance to feed leaves, than control goats. On average, time proportion spent consuming olive leaves and sprouts was much greater (P<0.05) for C (50.7±9.1%) than for AV1 (14.4±3.9%) and AV2 (3.1±0.9%). In conclusion, the 200 mg LiCl/kg BW dose was more effective than the 175 mg LiCl/kg BW dose for inducing an effective long-term CTA to olive tree leaves in goats. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

Milk and dairy products are important sources of macro- and trace elements for human health. However, fresh cheeses usually have a lower mineral content than other cheeses, and this makes mineral prediction more difficult. Although mineral prediction in several food matrices using infrared spectroscopy has been reported in the literature, very little information is available for cheeses. The present study was aimed at developing near-infrared reflectance (NIR, 866-2,530 nm) and transmittance (NIT, 850-1,050 nm) spectroscopy models to predict the major mineral content of fresh cheeses. We analyzed samples of mozzarella (n = 130) and Stracchino (n = 118) using reference methods and NIR and NIT spectroscopy. We developed prediction models using partial least squares regression analysis, and subjected them to cross- and external validation. Average Na content was 0.15 and 0.22 g/100 g for mozzarella and Stracchino, respectively. The NIR and NIT spectroscopy performed similarly, with few exceptions. Nevertheless, none of the prediction models was accurate enough to replace the current reference analysis. The most accurate prediction model was for the Na content of mozzarella cheese using NIT spectroscopy (coefficient of determination of external validation = 0.75). We obtained the same accuracy of prediction for P in Stracchino cheese with both NIR and NIT spectroscopy. Our results confirmed that mineral content is difficult to predict using NIT and NIR spectroscopy. [ABSTRACT FROM AUTHOR]

Cheese provides essential nutrients for human nutrition and health, such as minerals and fatty acids (FA). Its composition varies according to milk origin (e.g., species and breed), rearing conditions (e.g., feeding and management), and cheese-making technology (e.g., coagulation process, addition of salt, ripening period). In recent years, cheese production has increased worldwide. Italy is one of the main producers and exporters of cheese. This study aimed to describe mineral, FA, and cholesterol content of 133 samples from 18 commercial cheeses from 4 dairy species (buffalo, cow, goat, and sheep) and from 3 classes of moisture content (hard, <35% moisture; semi-hard, 35-45%; and soft, >45%). Mineral concentrations of cheese samples were determined by inductively coupled plasma optical emission spectrometry, and FA and cholesterol contents were determined by gas chromatography. Moisture and species had a significant effect on almost all traits: the highest levels of Na, Ca, and Fe were found in cheeses made from sheep milk; the greatest level of Cu was found in cow milk cheese, the lowest amount of K was found in buffalo milk cheese, and the lowest amount of Zn was found in goat cheeses. In all samples, Cr and Pb were not detected (below the level of detection). In general, total fat, protein, and minerals significantly increased when the moisture decreased. Buffalo and goat cheeses had the highest saturated FA content, and sheep cheeses showed the highest content of unsaturated and polyunsaturated FA, conjugated linoleic acid, and n-3 FA. Goat and sheep cheeses achieved higher proportions of minor FA than did cow and buffalo cheeses. Buffalo cheese exhibited the lowest cholesterol level. Our results confirm that cheese mineral content is mainly affected by the cheese-making process, whereas FA profile mainly reflects the FA composition of the source milk. This study allowed the characterization of mineral and FA composition and cholesterol content and revealed large variability among different commercial cheeses. [ABSTRACT FROM AUTHOR]

The aim of this study was to characterize the prevalence of intestinal parasite infections in multi-cat shelters and to evaluate facility and the management-related risk factors. The study included adult-cats housed for long periods under two different multi-cat environments: rescue shelters where both dogs and cats were housed and shelters with only cats (cat shelters). A total of 423 fecal samples were collected from 11 rescue shelters and five cat shelters, and examined by coprological examination using a centrifugation-flotation technique with zinc-sulfate solution (ρ=1.18). The overall prevalence of intestinal parasites was 57% (242/423 fecal samples). The following parasites were detected in the study: Giardia spp. (116/423; 27%), Toxocara cati (71/423; 16.7%), Cystoisospora spp. (67/423; 16%), hookworms (36/423;8.4%), Taenidae (33/423; 7.8%), metastrongilids (20/423; 5%), Toxascaris leonina (10/423; 2.4%), Dypilidium caninum (4/423; 1%), Capillaria spp./Eucoleus aerophilus (2/423; 0.5%) and Spirometra sp. (1/423; 0.2%). T. cati and Cystoisospora spp. were the most prevalent parasites in rescue shelters, whereas prevalence of Giardia spp. was similar in both populations studied. Rescue shelters showed higher prevalence of intestinal parasites than cat shelters (P < 0.05). The facilities and management were similar in both shelter types, and therefore it is hypothesized that the vicinity to dogs in rescue shelters constitutes a stressful factor for cats, potentially predisposing them to a higher prevalence of intestinal parasites. [ABSTRACT FROM AUTHOR]

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/).)

Although there are several studies comparing organic and conventional milk characteristics, very few focused on dairy processed products such as cheese. Thus, this study aimed for a detailed controlled examination of gross composition, minerals, and the fatty acid profile of organic (ORG) and conventional (CON) Italian cheeses from parallel production. Four Italian cheese types were analyzed: Latteria (ORG, n = 9; CON, n = 10); Asiago Protected Designation of Origin (PDO) fresco (ORG, n = 9; CON, n = 9); Caciotta (ORG, n = 8; CON, n = 8); and Mozzarella Traditional Specialty Guaranteed (TSG; ORG, n = 14; CON, n = 14). Cheese samples were collected from September 2020 to August 2021. Gross composition, minerals, and fatty acids were determined using infrared spectroscopy. Within each cheese type, paired ORG and CON samples were compared using a nonparametric Wilcoxon signed-rank test. Latteria showed lower PUFA, n-3, and n-6 content, and greater Fe, K, C10:0, C12:0, and C16:0 content in ORG than in CON. Asiago PDO fresco showed lower protein and Zn content and greater salt, ash, and Na content in ORG than in CON. Caciotta showed lower ash, n-3, and n-6 content and greater K, C4:0, C8:0, C10:0, C14:0, and C16:0 content in ORG than in CON. Mozzarella TSG showed lower fat and, therefore, fatty acid content, and greater moisture, ash, and Mg content in ORG than in CON. In conclusion, few significant differences in chemical composition were observed between ORG and CON cheeses, regardless of the type considered. Moreover, Asiago PDO fresco showed fewer significant differences between ORG and CON compared with Latteria, Caciotta, and Mozzarella TSG., (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/).)

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., (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.)

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.)

Dairy products are important sources of nutrients for human health and in recent years their consumption has increased worldwide. Therefore, the food industry is interested in applying analytical technologies that are more rapid and cost-effective than traditional laboratory analyses. Infrared spectroscopy accomplishes both criteria, making real-time determination feasible. However, it is crucial to ensure that prediction models are accurate before their implementation in the dairy industry. In the last 5 yr, several papers have investigated the feasibility of mid- and near-infrared spectroscopy to determine chemical composition and authenticity of dairy products. Most studies have dealt with cheese, and few with yogurt, butter, and milk powder. Also, the use of near-infrared (in reflectance or transmittance mode) has been more prevalent than mid-infrared spectroscopy. This review summarizes recent studies on infrared spectroscopy in dairy products focusing on difficult to determine chemical components such as fatty acids, minerals, and volatile compounds, as well as sensory attributes and ripening time. Promising equations have been developed despite the low concentration or the absence of specific absorption bands (or both) for these compounds., (Copyright © 2018 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.)