Use of desalinated seawater in arid and semiarid regions for domestic, industrial, and agricultural purposes is on the rise. Consequently, in those regions, drinking water offered to lactating cows has lower salinity and mineral concentrations than in the past. Although water with total dissolved solids)TDS) of up to 1 000 ppm is considered safe for drinking, lower salinity level may affect rumen physiology, feed and water intake, or milk yield. Therefore, we evaluated the effect of drinking water salinity in an electrical conductivity (EC) range of 400 to 1 000 micro Siemens (µS) / cm (TDS of 200 to 500 ppm) on lactating cows’ performance by artificially creating water EC > 400 µS/cm by adding NaCl. Following 2 weeks adaptation to individual feeders and troughs, four Israeli Holstein multiparous lactating cows were offered, in a Latin square design, drinking water with EC levels of 400, 600, 800 or 1 000 µS/cm, through addition of concentrated NaCl solutions (measured EC in troughs averaged 418, 624, 811, and 1 016 µS/cm and 209, 312, 406, and 508 TDS ppm, respectively), for four periods of 18 days each. Water EC in troughs was measured daily. Each period included 5 days for washout, 10 days for collecting data of feed and water intake, milk and milk component yields, and BW and 3 days for samplings of Milk, urine, feces, and rumen fluid. Rumen pH and temperature were recorded continually by inserting loggers into the reticulorumen. We analyzed the total tract apparent digestibility, rumen fluid volatile fatty acids and NH3, and mineral concentrations (Na, Cl, K, and N) in water, urine, feces, and milk. Drinking water salinity was positively correlated with DM intake and energy-corrected milk yield, the latter showing the greatest response between EC of 400 and 600 µS/cm. Digestibility of ash-free amylase-treated neutral detergent fiber was negatively correlated with water salinity. There was no significant effect of water EC on rumen volatile fatty acid or NH3 concentrations, or water intake. The results indicate possible effects of drinking water mineral concentrations on lactating cows’ milk yield and rumen physiology, warranting further investigation.

Metabolomics can describe the molecular phenome and may contribute to dissecting the biological processes linked to economically relevant traits in livestock species. Comparative analyses of metabolomic profiles in purebred pigs can provide insights into the basic biological mechanisms that may explain differences in production performances. Following this concept, this study was designed to compare, on a large scale, the plasma metabolomic profiles of two Italian heavy pig breeds (Italian Duroc, IDU, and Italian Large White, ILW) to indirectly evaluate the impact of their different genetic backgrounds on the breed metabolomes. We utilised a high-throughput untargeted metabolomics approach in a total of 962 pigs that allowed us to detect and relatively quantify 722 metabolites from various biological classes. The molecular data were analysed using a bioinformatics pipeline specifically designed for identifying differentially abundant metabolites between the two breeds in a robust and statistically significant manner, including the Boruta algorithm, which is a Random Forest wrapper, and sparse Partial Least Squares Discriminant Analysis (sPLS-DA) for feature selection. After thoroughly evaluating the impact of random components on missing value imputation, 100 discriminant metabolites were selected by Boruta and 17 discriminant metabolites (all included within the previous list) were identified with sPLS-DA. About half of the 100 discriminant metabolites had a higher concentration in one or the other breed (48 in Italian Large White pigs, with a prevalence of amino acids and peptides; 52 in Italian Duroc pigs, with a prevalence of lipids). These metabolites were from seven distinct super pathways and had an absolute mean value of percentage difference between the two breeds (|Δ|%) of 39.2±32.4. Six of these metabolites had |Δ|%>100. A general correlation network analysis based on Boruta identified metabolites consisted of 31 singletons and 69 metabolites connected by 141 edges, with two large clusters (>15 nodes), three medium clusters (3-6 nodes) and 8 additional pairs, with most metabolites belonging to the same super pathway. The major cluster representing the lipids super-pathway included 24 metabolites, primarily sphingomyelins. Overall, this study identified metabolomic differences between Italian Duroc and Italian Large White pigs explained by the specific genetic background of the two breeds. These biomarkers can explain the biological differences between these two breeds and can have potential practical applications in pig breeding and husbandry.