Interrelationships among physical and chemical traits of cheese: Explanatory latent factors and clustering of 37 categories of cheeses.

Cheese presents extensive variability in physical, chemical, and sensory characteristics according to the variety of processing methods and conditions used to create it. Relationships between the many characteristics of cheeses are known for single cheese types or by comparing a few of them, but not for a large number of cheese types. This case study used the properties recorded on 1,050 different cheeses from 107 producers grouped into 37 categories to analyze and quantify the interrelationships among the chemical and physical properties of many cheese types. The 15 cheese traits considered were ripening length, weight, firmness, adhesiveness, 6 different chemical characteristics, and 5 different color traits. As the 105 correlations between the 15 cheese traits were highly variable, a multivariate analysis was carried out. Four latent explanatory factors were extracted, representing 86% of the covariance matrix: the first factor (38% of covariance) was named Solids because it is mainly linked positively to fat, protein, water-soluble nitrogen, ash, firmness, adhesiveness, and ripening length, and negatively to moisture and lightness; the second factor (24%) was named Hue because it is linked positively to redness/blueness, yellowness/greenness, and chroma, and negatively to hue; the third factor (17%) was named Size because it is linked positively to weight, ripening length, firmness, and protein; and the fourth factor (7%) was named Basicity because it is linked positively to pH. The 37 cheese categories were grouped into 8 clusters and described using the latent factors: the Grana Padano cluster (characterized mainly by high Size scores); hard mountain cheeses (mainly high Solids scores); very soft cheeses (low Solids scores); blue cheeses (high Basicity scores), yellowish cheeses (high Hue scores), and 3 other clusters (soft cheeses, pasta filata and treated rind, and firm mountain cheeses) according to specific combinations of intermediate latent factors and cheese traits. In this case study, the high variability and interdependence of 15 major cheese traits can be substantially explained by only 4 latent factors, allowing us to identify and characterize 8 cheese type clusters.

Detailed mineral profile of milk, whey, and cheese from cows, buffaloes, goats, ewes and dromedary camels, and efficiency of recovery of minerals in their cheese.

Milk and dairy products are important in the human diet not only for the macro nutrients, such as proteins and fats, that they provide, but also for the supply of essential micronutrients, such as minerals. Minerals are present in milk in soluble form in the aqueous phase and in colloidal form associated with the macronutrients of the milk. These 2 forms affect the nutritional functions of the minerals and their contribution to the technological properties of milk during cheese-making. The aim of the present work was to study and compare the detailed mineral profiles of dairy foods (milk, whey, and cheese) obtained from cows, buffaloes, goats, ewes and dromedary camels, and to analyze the recovery in the curd of the individual minerals according to a model cheese-making procedure applied to the milk of these 5 dairy species. The detailed mineral profile of the milk samples was obtained by inductively coupled plasma - optical emission spectroscopy (ICP - OES). We divided the 21 minerals identified in the 3 different matrices into essential macro- and micro-minerals, and environmental micro-minerals, and calculated the recovery of the individual minerals in the cheeses. The complete mineral profiles and the recoveries in the cheeses were then analyzed using a linear mixed model with Species and Food, and their interaction included as fixed effects, and Sample within Species as a random effect. The mineral profiles of each food matrix were then analyzed separately with a general linear model in which only the fixed effect of Species was included. The results showed that the species could be divided into 2 groups: those producing a more diluted milk characterized by a higher content of soluble minerals (in particular K), and those with a more concentrated milk with a higher colloidal mineral content in the skim of the milk (such as Ca and P). The recoveries of the minerals in the curd were in line with the initial content in the milk, and also highlighted the fact that the influence of the brine was not limited to the Na content but to its whole mineral makeup. These results provide valuable information for the evaluation of the nutritional and technological properties of milk, and for the uses made of the byproducts of cheese making from the milk of different species.

Milk metagenomics and cheese-making properties as affected by indoor farming and summer highland grazing.

The study of the complex relationships between milk metagenomics and milk composition and cheese-making efficiency as affected by indoor farming and summer highland grazing was the aim of the present work. The experimental design considered monthly sampling (over 5 mo) of the milk produced by 12 Brown Swiss cows divided into 2 groups: the first remained on a lowland indoor farm from June to October, and the second was moved to highland pastures in July and then returned to the lowland farm in September. The resulting 60 milk samples (2 kg each) were used to analyze milk composition, milk coagulation, curd firming, and syneresis processes, and to make individual model cheeses to measure cheese yields and nutrient recoveries in the cheese. After DNA extraction and Illumina Miseq sequencing, milk microbiota amplicons were also processed by means of an open-source pipeline called Quantitative Insights Into Microbial Ecology (Qiime2, version 2018.2; https://qiime2.org). Out of a total of 44 taxa analyzed, 13 bacterial taxa were considered important for the dairy industry (lactic acid bacteria, LAB, 5 taxa; and spoilage bacteria, 4) and for human (other probiotics, 2) and animal health (pathogenic bacteria, 2). The results revealed the transhumant group of cows transferred to summer highland pastures showed an increase in almost all the LAB taxa, bifidobacteria, and propionibacteria, and a reduction in spoilage taxa. All the metagenomic changes disappeared when the transhumant cows were moved back to the permanent indoor farm. The relationships between 17 microbial traits and 30 compositional and technological milk traits were investigated through analysis of correlation and latent explanatory factor analysis. Eight latent factors were identified, explaining 75.3% of the total variance, 2 of which were mainly based on microbial traits: pro-dairy bacteria (14% of total variance, improving during summer pasturing) and pathogenic bacteria (6.0% of total variance). Some bacterial traits contributed to other compositional-technological latent factors (gelation, udder health, and caseins).

Prediction of detailed blood metabolic profile using milk infrared spectra and machine learning methods in dairy cattle.

The adoption of preventive management decisions is crucial to dealing with metabolic impairments in dairy cattle. Various serum metabolites are known to be useful indicators of the health status of cows. In this study, we used milk Fourier-transform mid-infrared (FTIR) spectra and various machine learning (ML) algorithms to develop prediction equations for a panel of 29 blood metabolites, including those related to energy metabolism, liver function/hepatic damage, oxidative stress, inflammation/innate immunity, and minerals. For most traits, the data set comprised observations from 1,204 Holstein-Friesian dairy cows belonging to 5 herds. An exception was represented by ß-hydroxybutyrate prediction, which contained observations from 2,701 multibreed cows pertaining to 33 herds. The best predictive model was developed using an automatic ML algorithm that tested various methods, including elastic net, distributed random forest, gradient boosting machine, artificial neural network, and stacking ensemble. These ML predictions were compared with partial least squares regression, the most commonly used method for FTIR prediction of blood traits. Performance of each model was evaluated using 2 cross-validation (CV) scenarios: 5-fold random (CVr) and herd-out (CVh). We also tested the best model's ability to classify values precisely in the 2 extreme tails, namely, the 25th (Q25) and 75th (Q75) percentiles (true-positive prediction scenario). Compared with partial least squares regression, ML algorithms achieved more accurate performance. Specifically, elastic net increased the R2 value from 5% to 75% for CVr and 2% to 139% for CVh, whereas the stacking ensemble increased the R2 value from 4% to 70% for CVr and 4% to 150% for CVh. Considering the best model, with the CVr scenario, good prediction accuracies were obtained for glucose (R2 = 0.81), urea (R2 = 0.73), albumin (R2 = 0.75), total reactive oxygen metabolites (R2 = 0.79), total thiol groups (R2 = 0.76), ceruloplasmin (R2 = 0.74), total proteins (R2 = 0.81), globulins (R2 = 0.87), and Na (R2 = 0.72). Good prediction accuracy in classifying extreme values was achieved for glucose (Q25 = 70.8%, Q75 = 69.9%), albumin (Q25 = 72.3%), total reactive oxygen metabolites (Q25 = 75.1%, Q75 = 74%), thiol groups (Q75 = 70.4%), total proteins (Q25 = 72.4%, Q75 = 77.2.%), globulins (Q25 = 74.8%, Q75 = 81.5%), and haptoglobin (Q75 = 74.4%). In conclusion, our study shows that FTIR spectra can be used to predict blood metabolites with relatively good accuracy, depending on trait, and are a promising tool for large-scale monitoring.

Composition and aptitude for cheese-making of milk from cows, buffaloes, goats, sheep, dromedary camels, and donkeys.

Bovines produce about 83% of the milk and dairy products consumed by humans worldwide, the rest represented by bubaline, caprine, ovine, camelid, and equine species, which are particularly important in areas of extensive pastoralism. Although milk is increasingly used for cheese production, the cheese-making efficiency of milk from the different species is not well known. This study compares the cheese-making ability of milk sampled from lactating females of the 6 dairy species in terms of milk composition, coagulation properties (using lactodynamography), curd-firming modeling, nutrients recovered in the curd, and cheese yield (through laboratory model-cheese production). Equine (donkey) milk had the lowest fat and protein content and did not coagulate after rennet addition. Buffalo and ewe milk yielded more fresh cheese (25.5 and 22.9%, respectively) than cow, goat, and dromedary milk (15.4, 11.9, and 13.8%, respectively). This was due to the greater fat and protein contents of the former species with respect to the latter, but also to the greater recovery of fat in the curd of bubaline (88.2%) than in the curd of camelid milk (55.0%) and consequent differences in the recoveries of milk total solids and energy in the curd; protein recovery, however, was much more similar across species (from 74.7% in dromedaries to 83.7% in bovine milk). Compared with bovine milk, the milk from the other Artiodactyla species coagulated more rapidly, reached curd firmness more quickly (especially ovine milk), had a more pronounced syneresis (especially caprine milk), had a greater potential asymptotical curd firmness (except dromedary and goat milk), and reached earlier maximum curd firmness (especially caprine and ovine milk). The maximum measured curd firmness was greater for bubaline and ovine milk, intermediate for bovine and caprine milk, and lower for camelid milk. The milk of all ruminant species can be used to make cheese, but, to improve efficiency, cheese-making procedures need to be optimized to take into account the large differences in their coagulation, curd-firming, and syneresis properties.

Effects of breed, farm intensiveness, and cow productivity level on cheese-making ability predicted using infrared spectral data at the population level.

Fourier-transform infrared (FTIR) spectra collected during milk recording schemes at population level can be used for predicting novel traits of interest for farm management, cows' genetic improvement, and milk payment systems. The aims of this study were as follows. (1) To predict cheese yield traits using FTIR spectra from routine milk recordings exploiting previously developed calibration equations. (2) To compare the predicted cheese-making abilities of different dairy and dual-purpose breeds. (3) To analyze the effects of herds' level of intensiveness (HL) and of the cow's level of productivity (CL). (4) To compare the patterns of predicted cheese yields with the patterns of milk composition in different breeds to discern the drivers of cheese-making efficiency. The major sources of variation of FTIR predictions of cheese yield ability (fresh cheese or cheese solids produced per unit milk) of individual milk samples were studied on 115,819 cows of 4 breeds (2 specialized dairy breeds, Holstein and Brown Swiss, and 2 dual-purpose breeds, Simmental and Alpine Grey) from 6,430 herds and exploiting 1,759,706 FTIR test-day spectra collected over 7 yr of milk sampling. Calibration equations used were previously developed on 1,264 individual laboratory model cheese procedures (cross-validation R2 0.85 and 0.95 for fresh and solids cheese yields, respectively). The linear model used for statistical analysis included the effects of parity, lactation stage, year of calving, month of sampling, HL, CL, breed of cow, and the interactions breed × HL and breed × CL. The HL and CL stratifications (5 classes each) were based on average daily secretion of milk net energy per cow. All effects were highly significant. The major conclusions were as follows. (1) The FTIR-based prediction of cheese yield of milk goes beyond the knowledge of fat and protein content, partially explaining differences in cheese-making ability in different cows, breeds and herds. (2) Differences in cheese yields of different breeds are only partially explained by milk fat and protein composition, and less productive breeds are characterized by a higher milk nutrient content as well as a higher recovery of nutrients in the cheese. (3) High-intensive herds not only produce much more milk, but the milk has a higher nutrient content and a higher cheese yield, whereas within herds, compared with less productive cows, the more productive cows have a much greater milk yield, milk with a greater content of fat but not of protein, and a moderate improvement in cheese yield, differing little from expectations based on milk composition. Finally, (4) the effects of HL and CL on milk quality and cheese-making ability are similar but not identical in different breeds, the less productive ones having some advantage in terms of cheese-making ability. We can obtain FTIR-based prediction of cheese yield from individual milk samples retrospectively at population level, which seems to go beyond the simple knowledge of milk composition, incorporating information on nutrient retention ability in cheese, with possible advantages for management of farms, genetic improvement of dairy cows, and milk payment systems.

Shift in the cow milk microbiota during alpine pasture as analyzed by culture dependent and high-throughput sequencing techniques.

In the present study, two groups of cows from a permanent lowland farm (PF) were divided during summer and reared in the PF or in a temporary alpine farm (ALP), respectively. Microbiological analyses were performed with the objective to investigate the microbial evolution of milk before, during, and after summer transhumance comparing, in particular, the two groups of cows to determine whether the alpine pasture could directly influence the milk microbiota. A significant increase of all microbial groups was registered in milk samples collected in the ALP. Interestingly, many strains belonging to species with well reported technological and probiotic activities were isolated from Alpine milk (20% Lactococcus lactis subsp. lactis/cremoris, 18% Lactobacillus paracasei, 14% Bifidobacterium crudilactis and 18% Propionibacterium sp.), whereas only 16% of strains isolated from the permanent farm milk belonged to the species Lactococcus lactis subsp. lactis/cremoris, 6% to Lactobacillus paracasei, 2% to Bifidobacterium crudilactis and 5% to Propionibacterium sp. The MiSeq Illumina data showed that Alpine milk presented a significant reduction of Pseudomonas and an increase of Lactococcus, Bifidobacterium and Lactobacillus genera. These data confirmed the practice of Alpine pasture as one of the main drivers affecting the milk microbiota. All the microbial changes disappeared when cows were delivered back from Alpine pasture to the indoor farm.

Short communication: Dietary protein restriction and conjugated linoleic acid supplementation in dairy cows affect milk composition, the cheese-making process, and cheese quality.

We used 20 mid-lactating Holstein cows, housed in 4 pens according to a Latin square design, to evaluate the effects of dietary protein restriction (crude protein: 12.3 vs. 15.0% dry matter) and conjugated linoleic acid supplementation (CLA: 6.34 g/d of C18:2cis-9,trans-11 and 6.14 g/d of C18:2trans-10,cis-12) on milk composition, coagulation, curd firming and syneresis modeling, and cheese yield and quality (96 small cheeses). Dietary crude protein restriction, suggested as a way to reduce N excretion in farming, caused a reduction in milk protein content (-4%,), milk casein (-3.8%), lactose (-1%), cheese soluble protein (-16.8%), and the cheese maturation index (-15%), and a correlated increase in cheese fat content (+7.5%) and the fat to protein ratio (+18%). A modest reduction (-0.9%) in milk fat recovery in the curd did not affect cheese yield. The addition of CLA to the cows' diet, suggested as a way to improve N use efficiency and the nutritional value of dairy products, caused substantial alterations to the milk composition, cheese-making process, and cheese quality. The CLA reduced the fat (-12.3%), protein (-2%), casein (-2.2%), lactose (-1.0), and total solids (-4%) contents of milk, tended to delay coagulation, and weakened curd firming. The CLA reduced the fresh cheese yield (-7.5%) and cheese solids (-8.2%) because of the lower nutrient content of the milk, but also because of a lower recovery of milk protein in the curd (-0.9%) and lower total solids (-4.5%). It also reduced the fat content in the ripened cheese (-11.8%), as well as the fat to protein ratio (-19.4%) as a result of having increased the protein content (+9.3%). Last, it increased the lightness of the paste of the ripened cheeses (+3.3%), and especially the shear force (+16.3%). Dietary crude protein restriction, and CLA addition in particular, substantially altered the milk composition, cheese-making process, and cheese quality, and therefore needs to be carefully evaluated. Further studies are required to shed light on the causes of these modifications.

The volatile organic compound profile of ripened cheese is influenced by crude protein shortage and conjugated linoleic acid supplementation in the cow's diet.

A shortage in crude protein (CP) and supplementation of conjugated linoleic acids (CLA) in the diets of dairy cows could improve the dairy industry's ecological footprint and the nutritional value of milk, but it is not known what effect such a strategy might have on the aroma profiles of dairy products. The aim of this work was to study the effects of reducing the dietary CP content (from 150 to 123 g/kg of dry matter), with or without a supply of rumen-protected CLA (7.9 g/d C18:2 cis-9,trans-11 and 7.7 g/d C18:2 trans-10,cis-12), on the volatile organic compound (VOC) profile of cheeses ripened for 3 mo. Twenty mid-lactation Holstein-Friesian cows were reared in 4 pens (5 to a pen), and fed 4 different experimental diets over 4 periods of 3 wk each, following a 4 × 4 Latin square design. Twice in each period, 10-L milk samples were taken from each group and used to produce 32 cheeses, which we then analyzed for VOC by solid-phase microextraction and gas chromatography-mass spectrometry. We detected 48 VOC belonging to 10 chemical classes (11 alcohols, 8 ketones, 8 esters, 7 acids, 4 aldehydes, 4 sulfurs, 2 lactones, 2 phenolic, 1 monoterpene, 1 hydrocarbon); these were expressed as concentrations in cheese (quantitative data) or as proportions of total VOC (qualitative data). The results of mixed model analysis showed that the majority of VOC families and individual VOC in ripened cheese were affected by the dietary treatments: CP shortage depressed the concentrations of volatile aldehydes and increased the proportions of some esters and limonene, whereas CLA increased the concentration of total VOC, particularly several acids and esters, and decreased the proportions of ketones and phenolic compounds. The interaction between dietary CP and CLA affected the proportions of alcohols and acids. We performed a factor analysis to extract 5 latent explanatory variables from the individual VOC, which represented 79% of total VOC variance for the quantitative data and 78% for the qualitative data. Addition of CLA decreased the first qualitative factor (the "base aroma" of cheese, explaining 44% of total variance), whereas CP reduction increased the second quantitative factor ("ethyl esters," 15% of total variance) and the third qualitative factor ("butan-," 9% of total variance). In summary, the VOC profile of ripened cheese was heavily influenced by CP content and CLA supplementation in the diets of dairy cows, but the effect on sensorial properties of cheese is also worth considering.

Dose response of rumen-protected conjugated linoleic acid supplementation to fattening bulls and heifers on growth, and carcass and meat quality.

We investigated the influence of rumen-protected conjugated linoleic acid (rpCLA) on growth performances, and carcass and meat quality traits in beef. Twenty-four young bulls and 30 heifers obtained from double-muscled beef sires and dairy cows were fed a low-protein ration (110 g/kg DM of crude protein) supplemented with 0, 8 or 80 g/d of a commercial rpCLA product. The animals were monthly weighed and scored for body muscularity and fatness. Blood samples were collected after 140 days on feed. Animals were slaughtered when they reached average in vivo fatness scores of around 2.5 (heifers) and 2.0 (bulls) points respectively. At slaughter, carcasses, various organs and parts of the gastrointestinal tract were weighed; the 5th rib was dissected and its tissue and muscle chemical composition was determined. The rpCLA had little influence on growth performance but decreased the blood urea content by 28% (p < 0.01). The rpCLA × sex interactions for daily gain (p < 0.05), conformation scores (p < 0.01), and blood creatinine content (p < 0.05) suggest that males were more responsive to rpCLA than females when fed a low-protein ration, probably because of the metabolic protein-sparing effect of CLA. Only slight differences were observed in carcass weight and quality at slaughter. The results indicate that the response of beef cattle to rpCLA is dependent on sex or on their propensity for lean and fat accretion. It is also possible that counteracting feedback mechanisms compensate for the influence of rpCLA administration over the course of growth.

Garlic (Allium sativum L.) fed to dairy cows does not modify the cheese-making properties of milk but affects the color, texture, and flavor of ripened cheese.

Garlic and garlic components have recently been proposed as ruminal activity modulators to reduce the enteric methane emissions of ruminants, but little is known of their influence on milk coagulation properties, nutrient recovery, cheese yield, and sensorial and rheological characteristics of milk and cheese. The present study assessed the effects of garlic and diallyl sulfide supplements on dry matter intake (DMI), productive performance, milk coagulation properties, cheese yield, milk and cheese sensory profiles, and rheological characteristics. Four dairy cows were fed a total mixed ration either alone (control) or supplemented with 100 or 400 g/d of garlic cloves or 2 g/d of diallyl sulfide in 4 consecutive experimental periods in a 4 × 4 Latin square design. The diallyl sulfide dose was established to provide approximately the same amount of allyl thiosulfinate compounds as 100 g of fresh garlic cloves. The total mixed ration was composed of 0.29 corn silage, 0.23 corn-barley mixture, 0.17 sunflower-soybean mixture, 0.12 alfalfa hay, 0.12 grass hay, 0.04 sugar beet pulp, and 0.02 other additives, and contained 0.253 starch, 0.130 crude protein, and 0.375 neutral detergent fiber, on a dry matter basis. Each experimental period consisted of 7 d of transition and 14 d of treatment. On d 18 and 21 of each period, milk samples (10 L) were collected from each cow for chemical analysis and cheese-making. The organoleptic properties of the milk and 63-d-ripened cheeses were assessed by a panel of 7 trained sensory evaluators. The experimental treatments had no effects on DMI, milk yield, feed efficiency (milk yield/DMI), milk coagulation properties, nutrient recovery, or cheese yield. Garlic-like aroma, taste, and flavor of milk and cheese were significantly influenced by the treatments, particularly the highest dose of garlic cloves, and we found close exponential relationships between milk and cheese for garlic-like aroma (R2 = 0.87) and garlic-like flavor (R2 = 0.79). Diallyl sulfide and 400 g/d of garlic cloves resulted in lower pH, shear force, and shear work of ripened cheeses compared with the other treatments. Garlic cloves and diallyl sulfide had opposite effects on cheese color indices. We conclude that adding 400 g/d of garlic to the feed of lactating dairy cows highly influences the sensory and rheological characteristics of cheese.

Method to evaluate the microbial degradation activity in silage, cow rumen with in vitro test, and in manure and slurry.

Microorganisms are present everywhere and can influence a variety of processes. In agriculture and husbandry, the level of microbial activity can be crucial information, yet the methods for determining microbial activity are usually very long, complex, and costly. In this work, a novel and easy-to-use method, already in use for determining soil microbial activity, named Fertimetro was tested as a fast and cheap solution for measuring microbial activity in silages, in vitro rumen fluids, and manure and slurry. The method was adjusted for the specific conditions of the new testing environments. The results indicate that this method is adequate for measuring cellulolytic microbial activity in vitro rumen fluids, with a coefficient of repeatability (RT%) 92.2 at 24 h and 87.5 at 48 h, and also for cellulolytic microbial activity measures in manure RT% 39.0. While, due to the specific conditions in silages and slurry, this method is less adequate for measuring cellulolytic microbial activity in these environments. This work demonstrates that Fertimetro method can be used in different environments as an easy and cheaper alternative for measuring microbial activity, especially if the interest is only in quantifying the microbial activity and not in knowing the microbial species.1.Fertimetro is an easy-to-use and not costly method to evaluate microbial activity in different environments.2.This method is very adequate for measuring cellulolytic microbial activity in vitro rumen fluids and manure.

Bentonite does not affect in vitro ruminal gross fermentations but could modify ruminal metabolome and mineral content. A proof of concept.

Clay minerals, such as bentonite, are used as feed additives capable of adsorbing mycotoxins and heavy metals and have been related to many positive effects on animal health and productivity. However, these compounds seem to induce also side effects and to interact with the intestinal and ruminal microbiota. The present in vitro study is aimed at evaluating the effects of different doses of bentonite on ruminal fermentations, metabolome and mineral content. Five doses of bentonite (0, 2.5, 5, 10 and 50 mg in 150 mL total volume) were incubated (39 °C for 24 h) with a dairy cow Total Mixed Ratio (TMR) and the ruminal fluid obtained from one healthy Holstein lactating cow. The kinetics of gas production (GP) continuously monitored during the incubation evidenced no significant differences in either cumulative GP (mL/g DM) or GP rate (mL/g DM/h) between the treatment groups. After the incubation, metabolome and mineral content of treated ruminal fluids were studied in pooled replicate samples by 1H NMR spectroscopy and Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES), respectively. The NMR analysis led to the identification of 20 metabolites and suggested a clear metabolic differentiation among treatments. The ICP-OES analysis suggested that the addition of bentonite affected the concentration of Al, Ba, Ca, Cr, Mn, Mo and Sr. It is conceivable that bentonite administration does not affect gross ruminal fermentations, while it seems to modify the ruminal metabolome and the concentrations of few minerals in ruminal fluid.

Technical note: Design, development and validation of an automated gas monitoring equipment for measurement of the dynamics of microbial fermentation.

The present technical note describes design, development and validation of an automated equipment for measurement of kinetics of gas production during fermentation in glass bottles. The overall repeatability and precision of the developed system was evaluated and compared with the manual gas measurement technique in respect to characterization of the fermentation kinetics of ruminant livestock feeds. Two incubations were carried out, during which the GP of six different feeds was measured with the automated system or manual technique. During a 48-hour incubation period, pressure data were collected at 15-minute intervals using automated equipment, yielding 192 head-space pressure measurements for each bottle. In manual measurement, incubations were performed with the nominal 60-mL serum bottle, and headspace pressure was read using a digital pressure gauge and then released at 2, 4, 6, 8, 12, 16, 24, 36, and 48 hours of incubation. The automated equipment recorded greater GP (+11.5%, over the 48-h incubation) than the manual measurement, and the repeatability and coefficient of repeatability values indicated that the GP data obtained with manual equipment were less repeatable. The automated equipment measures the fermentative GP kinetics with greater precision and repeatability than manual technique.•An automated batch GP equipment was designed, developed and validated, and a comparison was made with GP data obtained manually using a digital pressure gauge.•The automated equipment provided more reliable and repeatable data compared with manual measurement.•The automated equipment is available with lower cost and more functionality.

Bibliometric Review on the Volatile Organic Compounds in Meat.

Meat flavor is an important aspect of meat quality that also influences consumer demand, and is therefore very important for the meat industry. Volatile organic compounds (VOCs) contribute in large part to the flavor of meat, and while increasing numbers of articles are published on this topic, reviews of these articles are very scarce. Therefore, our aim was to perform a bibliometric analysis of the scientific publications on VOCs in meat over the period 2000-2020. We selected 611 scientific sources from the Scopus database related to VOCs in meat (seafood excluded). The bibliometric information retrieved included journals, authors, countries, institutions, keywords, and citations. From this analysis, we drew up a list of the most important journals, authors, countries, and institutions, and the trends in VOC research on meat. We conducted a social network analysis (SNA) to identify the collaborations among the many authors and countries, and a keyword analysis to generate a network map of the authors' keywords. We also determined which meat species were most frequently chosen as research subjects, traced the evolution of the various methods/instruments used, and explored the research tendencies. Finally, we point out the need for further research in defining meat quality, improving meat flavor, identifying adulterants, and certifying the authenticity of meat.

Major Causes of Variation of External Appearance, Chemical Composition, Texture, and Color Traits of 37 Categories of Cheeses.

Cheeses are produced by many different procedures, giving rise to many types differing in ripening time, size, shape, chemical composition, color, texture, and sensory properties. As the first step in a large project, our aim was to characterize and quantify the major sources of variation in cheese characteristics by sampling 1050 different cheeses manufactured by over 100 producers and grouped into 37 categories (16 with protected designation of origin, 4 traditional cheese categories, 3 pasta filata cheese categories, 5 flavored cheese categories, 2 goat milk categories, and 7 other categories ranging from very fresh to very hard cheeses). We obtained 17 traits from each cheese (shape, height, diameter, weight, moisture, fat, protein, water soluble nitrogen, ash, pH, 5 color traits, firmness, and adhesiveness). The main groups of cheese categories were characterized and are discussed in terms of the effects of the prevalent area of origin/feeding system, species of lactating females, main cheese-making technologies, and additives used. The results will allow us to proceed with the further steps, which will address the interrelationships among the different traits characterizing cheeses, detailed analyses of the nutrients affecting human health and sensorial fingerprinting.

Associations between Milk Fatty Acid Profile and Body Condition Score, Ultrasound Hepatic Measurements and Blood Metabolites in Holstein Cows.

Dairy cows have high incidences of metabolic disturbances, which often lead to disease, having a subsequent significant impact on productivity and reproductive performance. As the milk fatty acid (FA) profile represents a fingerprint of the cow's nutritional and metabolic status, it could be a suitable indicator of metabolic status at the cow level. In this study, we obtained milk FA profile and a set of metabolic indicators (body condition score, ultrasound liver measurements, and 29 hematochemical parameters) from 297 Holstein-Friesian cows. First, we applied a multivariate factor analysis to detect latent structure among the milk FAs. We then explored the associations between these new synthetic variables and the morphometric, ultrasonographic and hematic indicators of immune and metabolic status. Significant associations were exhibited by the odd-chain FAs, which were inversely associated with ß-hydroxybutyrate and ceruloplasmin, and positively associated with glucose, albumin, and γ-glutamyl transferase. Short-chain FAs were inversely related to predicted triacylglycerol liver content. Rumen biohydrogenation intermediates were associated with glucose, cholesterol, and albumin. These results offer new insights into the potential use of milk FAs as indicators of variations in energy and nutritional metabolism in early lactating dairy cows.

In-line near-infrared analysis of milk coupled with machine learning methods for the daily prediction of blood metabolic profile in dairy cattle.

Precision livestock farming technologies are used to monitor animal health and welfare parameters continuously and in real time in order to optimize nutrition and productivity and to detect health issues at an early stage. The possibility of predicting blood metabolites from milk samples obtained during routine milking by means of infrared spectroscopy has become increasingly attractive. We developed, for the first time, prediction equations for a set of blood metabolites using diverse machine learning methods and milk near-infrared spectra collected by the AfiLab instrument. Our dataset was obtained from 385 Holstein Friesian dairy cows. Stacking ensemble and multi-layer feedforward artificial neural network outperformed the other machine learning methods tested, with a reduction in the root mean square error of between 3 and 6% in most blood parameters. We obtained moderate correlations (r) between the observed and predicted phenotypes for γ-glutamyl transferase (r = 0.58), alkaline phosphatase (0.54), haptoglobin (0.66), globulins (0.61), total reactive oxygen metabolites (0.60) and thiol groups (0.57). The AfiLab instrument has strong potential but may not yet be ready to predict the metabolic stress of dairy cows in practice. Further research is needed to find out methods that allow an improvement in accuracy of prediction equations.

Free and Microencapsulated Essential Oils Incubated In Vitro: Ruminal Stability and Fermentation Parameters.

Essential oils (EOs) are generally considered as an alternative to antibiotics because of their antimicrobial properties. Despite their vast variety, their volatile nature poses hindrance on their use in animal feeds, which demands a high degree of stability. This study aimed at testing the susceptibility of three EOs (mixtures of EOs based on cinnamaldehyde, named Olistat-Cyn, Olistat-G, and Olistat-P) in two forms (free: fEOs; and microencapsulated: mEOs) to in vitro ruminal degradation using the Ankom DaisyII technique. The microencapsulation was made using a matrix based on vegetable hydrogenated fatty acids. Compared to the fEOs, which were completely degraded within 48 h of in vitro incubation, the mEOs showed a low ruminal disappearance. In comparison to the fermentation profile at 0 h, Olistat-G significantly decreased the pH and the total protozoa number after 48 h, while the total VFAs increased. However, the other EOs (Olistat-Cyn and Olistat-P) had no effect on the rumen fermentation parameters. In conclusion, the protection of EOs from ruminal degradation by microencapsulation was found to be very effective to ensure rumen by-pass. Among the EOs, Olistat-G was capable of changing rumen fermentation, potentially reducing methane emissions.

Associations between ultrasound measurements and hematochemical parameters for the assessment of liver metabolic status in Holstein-Friesian cows.

Metabolic disorders, including hepatic lipidosis and ketosis, severely affect animal health status and welfare with a large economic burden in dairy herds. The gold standard for diagnosing hepatic lipidosis is the liver biopsy, which is impractical and invasive for the screening at farm level. Ultrasound (US) imaging is a promising technique for identifying liver dysfunction, but standardized specifications in physiological conditions are needed. Herein, we described the features of four US measurements, namely the liver predicted triacylglycerol (pTAG) content, liver depth (LD), and portal vein area (PVA) and depth (PVD) and we investigated their associations with a set of hematochemical (HC) indicators in 342 clinically healthy Holstein Friesian dairy cows. Liver pTAG content was negatively associated with hematocrit and positively with globulin, whereas PVA was negatively associated with thiol group levels, and LD positively with ceruloplasmin. We found significant interactions between some HC parameters and parity: in particular, creatinine, thiol groups and globulin for PVA, and aspartate aminotransferase, paraoxonase and ceruloplasmin for PVD. This study offers new insights on variations in liver function occurring after calving and pave the way for the potential use of minimally invasive techniques for prompt detection of metabolic disorders in dairy herds.