Genetic Variability and Management in Nero di Parma Swine Breed to Preserve Local Diversity

Nero di Parma is an endangered swine breed reared in the North of Italy which nowadays counts 1603 alive pigs. The aims of this study were (i) to explore the genetic diversity of the breed at pedigree level to determine the actual genetic structure, (ii) to evaluate the effectiveness of the breeding recovery project and (iii) to potentially propose breeding strategies for the coming generations. The pedigree dataset contained 14,485 animals and was used to estimate demographic and genetic parameters. The mean equivalent complete generations was equal to 6.47 in the whole population, and it reached a mean value of 7.94 in the live animals, highlighting the quality of the available data. Average inbreeding was 0.28 in the total population, whereas it reached 0.31 in the alive animals and it decreased to 0.27 if only breeding animals were considered. The rate of inbreeding based on the individual increase in inbreeding was equal to 7%. This study showed the effectiveness of the recovery project of the breed. Nevertheless, we found that inbreeding and genetic diversity have reached alarming levels, therefore novel breeding strategies must be applied to ensure long-term survival of this breed

Characterizing the Statistical Properties and Global Distribution of Dansgaard-Oeschger Events

Ice core records from Greenland have shown times of rapid warming during the most recent glacial period, called Dansgaard-Oeschger (D-O) events. D-O events are important to our understanding of both past climate systems and modern climate volatility. In this paper, we present new approaches for sta- tistically evaluating the existence of cyclicity in D-O events and the possible lagged correlation between the Greenland and Antarctica temperature records. Speci cally, we consider permutation testing and bootstrapping methodologies for assessing the cyclicity of D-O events and the correlation between the Green- land and Antarctica records. We nd that there is not enough evidence to conclude that D-O events are cyclical; however, the Antarctica record leads the Greenland record by 545 years with a statistically signi cant correlation of 0.455

Influence of milk somatic cell content on Parmigiano-Reggiano cheese yield

The aim of this study was to determine the influence of the somatic cell content (SCC) of milk on Parmigiano-Reggiano cheese yield, produced in commercial cheese factories under field conditions. The study was carried out following the production of 56 batches of Parmigiano-Reggiano in 13 commercial cheese factories by processing milk collected from Italian Friesian cattle herds. The vat-milk (V-milk) used for making each cheese batch was obtained by mixing evening milk (partially skimmed following spontaneous separation of fat overnight, natural creaming) and morning milk. The batches of cheese produced were divided into 5 classes according to the SCC value of the evening milk determined prior to natural creaming (class 1, from 0 to 200 000; 2, 201 000-300 000; 3, 301 000-400 000; 4, 401 000-500 000; 5, over 501 000 cells/ml). The cheese yield was calculated as the amount of 24-h cheese, expressed in kilograms, obtained from 100 kg of V-milk (24 h ACY). The values of fat, crude protein, true protein, casein and 24 h ACY of V-milk were negatively correlated with the somatic cell score (SCS) of the evening milk. Conversely, a positive correlation was observed between chloride and SCS. Fat, protein fractions (crude protein, casein and whey proteins), P and titratable acidity of V-milk were positively correlated with its 24 h ACY, while chloride, pH and SCS showed a negative correlation. A significant drop in 24 h ACY was observed in classes 3, 4 and 5, therefore when the SCC of the evening milk exceeded 300 000 cells/ml. Finally a lower recovery of milk fat in cheese was observed as SCC of evening milk increase

Effects of Milk Storage Temperature at the Farm on the Characteristics of Parmigiano Reggiano Cheese: Chemical Composition and Proteolysis

Parmigiano Reggiano is a Protected Designation of Origin (PDO) cheese whose official production protocol provides that milk cannot be stored at less than 18 °C at the farm. The possibility of refrigerating milk at the farm is highly debated, since it should allow for the limiting of bacterial growth, thus improving the quality of the cheese. The present research aimed to study the influence of storing the milk at 9 °C on the chemical composition and proteolysis during the ripening of Parmigiano Reggiano cheese. The experimentation considered six cheese-making trials, in which both evening and morning milks were subdivided into two parts that were maintained at 9 and 20 °C. After Parmigiano Reggiano cheese-making, one of the twin wheels obtained was analyzed after 21 months of ripening. From each cheese, two different samples were taken, one from the inner zone, and the other from the outer zone. The results of the chemical analyses evidenced that milk storage at 9 °C significantly (p ≤ 0.05) influenced fat, crude protein, soluble nitrogen and peptone nitrogen contents. Nevertheless, the differences observed with respect to the cheese obtained with milk stored under standard condition were very small and should be considered within the “normal variations” of Parmigiano Reggiano chemical characteristics

Detailed macro- and micromineral profile of milk: Effects of herd productivity, parity, and stage of lactation of cows of 6 dairy and dual-purpose breeds

The aim of this study was to quantify the major sources of variation in the levels of 15 minerals in individual milk samples collected from cows raised in multibreed dairy herds. The herds (n = 27) were classified into 2 categories, according to milk productivity. Milk productivity was based on the net energy of lactating cows' average daily milk yield. Milk samples were collected from 240 cows of 6 different breeds: 3 specialized dairy (Holstein-Friesian, Brown Swiss, and Jersey) and 3 dual-purpose (Simmental, Rendena, and Alpine Grey). The samples were analyzed for macro-elements (Na, Mg, P, S, K, and Ca), essential micro-elements (Mn, Fe, Cu, Zn, and Se), and environmental micro-elements (B, Si, Sr, and Sn), using inductively coupled plasma-optical emission spectrometry. Data were analyzed using a linear mixed model that included fixed effects of days in milk (DIM), parity, breed, and herd productivity, and a random effect of herd-date within productivity level. Results showed that the effect of herd-date varied across minerals. It was especially large for environmental minerals (ranging from 47 to 91% of total variance) and ranged from 11 to 61% for macrominerals and essential microminerals. Milk samples collected from farms with a high level of herd productivity had a richer mineral profile than samples from low-productivity herds. Parity only influenced macrominerals, with the exception of S and Ca, while DIM influenced almost all minerals, with a few exceptions among the environmental elements. Differences in mineral profile were small between specialized and dual-purpose breeds, but they were large within the group of the specialized cows. These breed differences were reduced after adjusting for milk quality and yield, particularly in the case of milk Mg, S, Ca, Mn, and Zn levels. Milk samples from the Jersey and Brown Swiss cows had higher mineral levels (Sn excluded) than milk from the Holstein-Friesian cows; the other breeds of Alpine origin produced milk of intermediate quality. Our findings suggest that breed has a stronger effect on macrominerals and some of the essential microminerals than herd productivity, parity, and DIM. The modification of the mineral profile in milk seems possible for many minerals, but it likely depends on genetics (e.g., breed, selection) and on environmental and management factors in variable proportions according to the mineral considered

Modeling weight loss of cheese during ripening and the influence of dairy system, parity, stage of lactation, and composition of processed milk.

The yield, flavor, and texture of ripened cheese result from numerous interrelated microbiological, biochemical, and physical reactions that take place during ripening. The aims of the present study were to propose a 2-compartment first-order kinetic model of cheese weight loss over the ripening period; to test the variation in new informative phenotypes describing this process; and to assess the effects on these traits of dairy farming system, individual farms within dairy system, animal factors, and milk composition. A total of 1,211 model cheeses were produced in the laboratory using individual 1.5-L milk samples from Brown Swiss cows reared on 83 farms located in Trento Province. During ripening (60 d; temperature 15°C, relative humidity 85%), the weight of all model cheeses was measured, and cheese yield (cheese weight/processed milk weight, %CY) was calculated at 7 intervals from cheese-making (0, 1, 7, 14, 28, 42, and 60 d). Using these measures, a 2-compartment first-order kinetic model (3-parameter equation) was developed for modeling %CY during the ripening period, as follows: [Formula: see text] , where %CYt is the %CY at ripening time t; %CYi and %CYf are the modeled %CY traits at time 0 d (%CYi = initial %CY) and at the end of a ripening period sufficient to reach a constant wheel weight (%CYf = final %CY after 60 d ripening in the case of small model cheeses); kCY is the instant rate constant for cheese weight loss (%/d). Cheese weight and protein and fat losses were calculated as the % difference between the model cheeses at 0 and after 60 d of ripening. The variation in cheese pH was calculated as the % difference between pH at 0 and after 60 d. Dairy system, individual herd within dairy system, and the cow's parity and lactation stage (tested with a linear mixed model) strongly affected almost all the traits collected during model cheese ripening. Milk fat, protein, lactose, pH, and somatic cell score also greatly affected almost all the traits, although kCY was affected only by milk protein. After including milk composition in the linear mixed model, the importance of all the herd and animal sources of variation was greatly reduced for all traits. The proposed model and novel traits could be tested, first, with the aim of establishing new monitoring procedures enabling the dairy industry to improve milk quality-based payment systems at the herd level and, second, with a view to exploring possible genetic improvements to dairy cow populations

Effects of somatic cell count on the gross composition, protein fractions and mineral content of individual ewe’s milk

The aim of the research was to evaluate the effect of two somatic cell content (SCC) levels (<265,000 and >265,000 cells/ml) on ewe milk composition, protein fractions and mineral content. Samples were collected during two years, from three different ewe herds. Each herd was surveyed four times per year, one per season. For each survey more than 10 individual milk samples were collected during morning milking and analysed for SCC. On the basis of the results, two individual milk samples were selected: one from a sheep with low milk SCC (up to 265.000 cells/mL; LCC) and one from a sheep with high milk SCC (over 265,000 and less than 1,000,000 cells/mL; HCC). In one herd, it was not possible to collect the milk samples in summer. So, a total of 44 ewe milk samples (22 comparative pairs) were collected. On each milk sample, crude protein, crude whey protein, casein, casein number, non protein nitrogen x 6.38, true protein, true whey protein, fat, lactose, dry matter, ash, phosphorus, calcium, magnesium and chloride were determined. Average SCC in LCC was 170,000 and 466,000 cells/ml in HCC milk. HCC milk had lower lactose (4.05 vs. 4.60 g/100 g), casein (3.91 vs. 4.28 g/100 g), phosphorus (131.31 vs. 138.81 mg/100 g), calcium (157.28 vs. 170.48 mg/100 g) and magnesium (14.59 vs. 15.30 mg/100 g) contents than LCC milk. Additionally, HCC milk had lower casein number (76.53 vs. 79.03%) and higher contents of true whey protein (1.00 vs. 0.92 g/100 g), ash (0.90 vs. 0.87 g/100 g) and chloride (103.57 vs. 93.17 mg/100 g) than LCC milk. Somatic cell content significantly affected ewe milk quality. As a result of the higher lactose, casein, phosphorus, calcium and magnesium contents, LCC milk was more suitable for cheese making than HCC milk.Key words: Ewe milk, milk quality, chemical composition, somatic cell content

Prediction of milk, fat and protein yields in first lactation from serum ß-lactoglobulin concentrations during gestation in Italian Brown heifers

The Authors report the results of a study carried out on 23 pregnant Italian Brown heifers, with the aim to determine the relationships between blood serum ß-lactoglobulin (ß-LG) concentrations during first gestation and subsequent milk production and quality in first lactation, in order to obtain an improved selection method for replacement heifers. At weeks 20, 26 and 32 of gestation, ß-LG concentrations (±SE) were 706±78, 753±66 and 772±63 ng/ml, respectively (P>0.05). High and significant (P≤0.05) correlation coefficients were observed only between ß-LG content at week 32 and total milk and protein yields in first lactation. Prediction equations of milk, fat and protein production in first lactation from log10 ß-LG content at week 32 of gestation, from parent average genetic indexes and from both were calculated by means of multiple regression analysis. When the contribution of both ß-LG content and predicted genetic indexes were considered, the regression equations gave generally a better estimate of the production parameters in first lactation (higher R2, lower SE of estimate) than the above mentioned parameters alone. These results suggest that it is valuable to pre-estimate milk, fat and protein production in Italian Brown first lactating cows by means of the analysis of serum ß-LG content during gestation

Application of FT-IR spectroscopy to analyze casein in cow milk

AbstractInfrared spectrometry is, at present, the most frequently applied methodology for the composition analysis of milk and dairy products. The determination of fat, protein and lactose has been described during recent decades. The introduction of Fourier Transform Infra-red (FT-IR) technology in combination with the application of multi-dimensional procedures (i.e. principal component regression, partial least squares) has improved this methodology, opening new perspectives for the simultaneous and routinely determination of many new parameters such as casein, urea, specific sugars, etc.. The aim of our study was to develop on MilkoScanTM FT 120 (Foss Electric, Hillerod, Denmark) a calibration curve for the analysis of casein in cow milk and to execute a preliminary validation. The calibration curve was developed on 89 individual milk samples collected from 4 dairy herds in the Grana-Padano cheese district. In order to obtain a higher variability of milk protein content and composition, in each herd m..